From 24f578cd66bfc3ec35017fc77e136e43c4b74742 Mon Sep 17 00:00:00 2001
From: Gaurav Jain <gjn@google.com>
Date: Thu, 29 Nov 2018 15:30:12 -0800
Subject: [PATCH] Add @run_deprecated_v1 annotation to tests failing in v2
PiperOrigin-RevId: 223422907
---
tensorflow/examples/adding_an_op/fact_test.py | 2 +
.../examples/adding_an_op/zero_out_1_test.py | 2 +
.../examples/adding_an_op/zero_out_2_test.py | 5 +
.../examples/adding_an_op/zero_out_3_test.py | 5 +
.../autograph/integration_tests/keras_test.py | 2 +
.../examples/speech_commands/freeze_test.py | 4 +
.../speech_commands/input_data_test.py | 9 +
.../examples/speech_commands/models_test.py | 6 +
.../speech_commands/wav_to_features_test.py | 2 +
.../autograph/converters/asserts_test.py | 2 +
.../converters/builtin_functions_test.py | 4 +
.../autograph/converters/control_flow_test.py | 13 +
.../converters/function_scopes_test.py | 5 +
.../converters/logical_expressions_test.py | 4 +
.../converters/side_effect_guards_test.py | 3 +
.../python/autograph/core/errors_test.py | 4 +
.../autograph/core/function_wrapping_test.py | 2 +
tensorflow/python/autograph/impl/api_test.py | 10 +
.../autograph/operators/control_flow_test.py | 6 +
.../operators/data_structures_test.py | 4 +
.../autograph/operators/exceptions_test.py | 3 +
.../autograph/operators/logical_test.py | 3 +
.../autograph/operators/py_builtins_test.py | 4 +
.../python/autograph/utils/misc_test.py | 3 +
.../autograph/utils/tensor_list_test.py | 3 +
.../python/autograph/utils/type_check_test.py | 1 +
.../python/client/session_partial_run_test.py | 24 ++
tensorflow/python/client/timeline_test.py | 1 +
.../kernel_tests/copy_to_device_test.py | 10 +
.../experimental/kernel_tests/counter_test.py | 2 +
.../dense_to_sparse_batch_test.py | 5 +
.../directed_interleave_dataset_test.py | 4 +
.../kernel_tests/enumerate_dataset_test.py | 2 +
.../function_buffering_resource_test.py | 4 +
.../kernel_tests/get_single_element_test.py | 2 +
.../kernel_tests/group_by_reducer_test.py | 6 +
.../kernel_tests/group_by_window_test.py | 11 +
.../kernel_tests/ignore_errors_test.py | 4 +
.../kernel_tests/indexed_dataset_ops_test.py | 3 +
.../make_batched_features_dataset_test.py | 2 +
.../kernel_tests/make_csv_dataset_test.py | 9 +
.../kernel_tests/map_and_batch_test.py | 13 +
.../kernel_tests/matching_files_test.py | 7 +
.../kernel_tests/override_threadpool_test.py | 3 +
.../parse_example_dataset_test.py | 4 +
.../kernel_tests/prefetch_to_device_test.py | 5 +
.../kernel_tests/rejection_resample_test.py | 4 +
.../kernel_tests/restructured_dataset_test.py | 2 +
.../experimental/kernel_tests/scan_test.py | 3 +
.../checkpoint_input_pipeline_hook_test.py | 4 +
.../kernel_tests/shuffle_and_repeat_test.py | 7 +
.../experimental/kernel_tests/sleep_test.py | 2 +
.../kernel_tests/stats_dataset_ops_test.py | 17 ++
.../experimental/kernel_tests/unbatch_test.py | 10 +
.../experimental/kernel_tests/unique_test.py | 3 +
.../python/data/kernel_tests/flat_map_test.py | 1 +
.../data/kernel_tests/from_generator_test.py | 17 ++
.../from_sparse_tensor_slices_test.py | 1 +
.../data/kernel_tests/from_tensors_test.py | 1 +
.../python/data/kernel_tests/iterator_test.py | 17 ++
.../data/kernel_tests/list_files_test.py | 1 +
.../python/data/kernel_tests/optional_test.py | 3 +
.../data/kernel_tests/padded_batch_test.py | 3 +
.../python/data/kernel_tests/reduce_test.py | 1 +
.../python/data/kernel_tests/shuffle_test.py | 1 +
tensorflow/python/data/util/convert_test.py | 2 +
tensorflow/python/data/util/sparse_test.py | 3 +
tensorflow/python/data/util/structure_test.py | 2 +
.../python/debug/cli/analyzer_cli_test.py | 33 +++
.../python/debug/cli/cli_shared_test.py | 11 +
.../debug/cli/profile_analyzer_cli_test.py | 5 +
tensorflow/python/debug/lib/common_test.py | 3 +
.../python/debug/lib/debug_gradients_test.py | 14 ++
.../python/debug/lib/debug_utils_test.py | 10 +
.../debug/lib/session_debug_file_test.py | 2 +
.../python/debug/lib/source_utils_test.py | 1 +
.../python/distribute/all_reduce_test.py | 5 +
.../python/distribute/device_util_test.py | 3 +
.../python/distribute/input_ops_test.py | 12 +
.../python/eager/function_gradients_test.py | 1 +
tensorflow/python/eager/function_test.py | 1 +
.../python/eager/graph_only_ops_test.py | 2 +
.../feature_column/feature_column_test.py | 130 ++++++++++
.../feature_column/feature_column_v2_test.py | 141 +++++++++++
.../python/framework/file_system_test.py | 2 +
.../framework/function_def_to_graph_test.py | 3 +
tensorflow/python/framework/function_test.py | 26 ++
.../python/framework/graph_util_test.py | 2 +
.../python/framework/meta_graph_test.py | 17 ++
tensorflow/python/framework/ops_test.py | 57 +++++
.../python/framework/smart_cond_test.py | 5 +
.../python/framework/sparse_tensor_test.py | 2 +
tensorflow/python/framework/subscribe_test.py | 10 +
.../python/framework/tensor_spec_test.py | 4 +
.../python/framework/tensor_util_test.py | 12 +
tensorflow/python/framework/test_util_test.py | 5 +
.../python/grappler/cost_analyzer_test.py | 4 +
tensorflow/python/grappler/item_test.py | 2 +
.../python/grappler/layout_optimizer_test.py | 3 +
.../python/grappler/memory_optimizer_test.py | 3 +
.../python/grappler/model_analyzer_test.py | 3 +
.../python/grappler/tf_optimizer_test.py | 4 +
tensorflow/python/keras/activations_test.py | 4 +
tensorflow/python/keras/backend_test.py | 8 +
tensorflow/python/keras/callbacks_test.py | 10 +
tensorflow/python/keras/engine/saving_test.py | 8 +
.../python/keras/engine/sequential_test.py | 2 +
.../python/keras/engine/topology_test.py | 10 +
.../keras/engine/training_dataset_test.py | 1 +
.../python/keras/engine/training_test.py | 10 +
tensorflow/python/keras/initializers_test.py | 11 +
tensorflow/python/keras/integration_test.py | 8 +
tensorflow/python/keras/layers/local_test.py | 4 +
tensorflow/python/keras/layers/lstm_test.py | 4 +
tensorflow/python/keras/layers/merge_test.py | 1 +
.../python/keras/layers/normalization_test.py | 1 +
.../python/keras/layers/simplernn_test.py | 3 +
.../python/keras/layers/unified_rnn_test.py | 2 +
.../python/keras/layers/wrappers_test.py | 4 +
.../python/keras/model_subclassing_test.py | 4 +
tensorflow/python/keras/models_test.py | 10 +
.../keras/optimizer_v2/adadelta_test.py | 1 +
.../python/keras/optimizer_v2/adagrad_test.py | 7 +
.../python/keras/optimizer_v2/adam_test.py | 6 +
.../python/keras/optimizer_v2/adamax_test.py | 5 +
.../python/keras/optimizer_v2/ftrl_test.py | 14 ++
.../optimizer_v2/gradient_descent_test.py | 9 +
.../python/keras/optimizer_v2/nadam_test.py | 5 +
.../python/keras/optimizer_v2/rmsprop_test.py | 5 +
tensorflow/python/keras/optimizers_test.py | 9 +
tensorflow/python/keras/regularizers_test.py | 2 +
.../python/kernel_tests/accumulate_n_test.py | 4 +
.../python/kernel_tests/ackermann_test.py | 2 +
.../python/kernel_tests/aggregate_ops_test.py | 3 +
.../python/kernel_tests/argmax_op_test.py | 3 +
.../python/kernel_tests/array_ops_test.py | 52 ++++
.../python/kernel_tests/as_string_op_test.py | 7 +
.../python/kernel_tests/atrous_conv2d_test.py | 6 +
.../python/kernel_tests/barrier_ops_test.py | 18 ++
.../python/kernel_tests/basic_gpu_test.py | 3 +
.../kernel_tests/batch_gather_op_test.py | 4 +
.../kernel_tests/batch_scatter_ops_test.py | 4 +
.../kernel_tests/batchtospace_op_test.py | 21 ++
.../python/kernel_tests/bcast_ops_test.py | 6 +
.../python/kernel_tests/betainc_op_test.py | 8 +
.../python/kernel_tests/bias_op_test.py | 12 +
.../python/kernel_tests/bincount_op_test.py | 7 +
.../python/kernel_tests/bitcast_op_test.py | 2 +
.../boosted_trees/prediction_ops_test.py | 15 ++
.../boosted_trees/quantile_ops_test.py | 4 +
.../boosted_trees/resource_ops_test.py | 3 +
.../boosted_trees/stats_ops_test.py | 1 +
.../boosted_trees/training_ops_test.py | 10 +
.../kernel_tests/broadcast_to_ops_test.py | 11 +
.../python/kernel_tests/bucketize_op_test.py | 2 +
.../candidate_sampler_ops_test.py | 3 +
.../python/kernel_tests/cast_op_test.py | 9 +
.../python/kernel_tests/check_ops_test.py | 45 ++++
.../kernel_tests/checkpoint_ops_test.py | 10 +
.../python/kernel_tests/cholesky_op_test.py | 9 +
.../python/kernel_tests/clip_ops_test.py | 10 +
.../python/kernel_tests/concat_op_test.py | 26 ++
.../python/kernel_tests/cond_v2_test.py | 8 +
.../conditional_accumulator_test.py | 24 ++
.../kernel_tests/confusion_matrix_test.py | 23 ++
.../python/kernel_tests/constant_op_test.py | 40 ++++
.../kernel_tests/control_flow_ops_py_test.py | 55 +++++
.../conv2d_backprop_filter_grad_test.py | 2 +
.../kernel_tests/conv2d_transpose_test.py | 2 +
.../conv3d_backprop_filter_v2_grad_test.py | 2 +
.../kernel_tests/conv3d_transpose_test.py | 3 +
.../python/kernel_tests/conv_ops_3d_test.py | 17 ++
.../python/kernel_tests/cross_grad_test.py | 2 +
.../kernel_tests/ctc_decoder_ops_test.py | 3 +
.../python/kernel_tests/ctc_loss_op_test.py | 23 ++
.../kernel_tests/cwise_ops_binary_test.py | 73 ++++++
.../python/kernel_tests/cwise_ops_test.py | 15 ++
.../kernel_tests/cwise_ops_unary_test.py | 8 +
.../kernel_tests/decode_compressed_op_test.py | 3 +
.../kernel_tests/decode_image_op_test.py | 4 +
.../python/kernel_tests/decode_raw_op_test.py | 7 +
.../python/kernel_tests/denormal_test.py | 3 +
.../dense_update_ops_no_tsan_test.py | 5 +
.../kernel_tests/dense_update_ops_test.py | 5 +
.../kernel_tests/depthtospace_op_test.py | 17 ++
.../python/kernel_tests/diag_op_test.py | 26 ++
.../distributions/bernoulli_test.py | 5 +
.../distributions/bijector_test.py | 2 +
.../distributions/categorical_test.py | 17 ++
.../dirichlet_multinomial_test.py | 13 +
.../distributions/identity_bijector_test.py | 2 +
.../distributions/kullback_leibler_test.py | 2 +
.../kernel_tests/distributions/normal_test.py | 1 +
.../distributions/special_math_test.py | 9 +
.../kernel_tests/distributions/util_test.py | 48 ++++
.../python/kernel_tests/duplicate_op_test.py | 2 +
.../kernel_tests/dynamic_partition_op_test.py | 8 +
.../kernel_tests/dynamic_stitch_op_test.py | 8 +
.../python/kernel_tests/embedding_ops_test.py | 44 ++++
.../extract_image_patches_grad_test.py | 3 +
.../fractional_avg_pool_op_test.py | 5 +
.../fractional_max_pool_op_test.py | 5 +
.../kernel_tests/functional_ops_test.py | 33 +++
.../python/kernel_tests/gather_nd_op_test.py | 11 +
.../python/kernel_tests/gather_op_test.py | 8 +
.../kernel_tests/gradient_correctness_test.py | 11 +
.../kernel_tests/identity_n_op_py_test.py | 4 +
.../kernel_tests/identity_op_py_test.py | 5 +
.../python/kernel_tests/init_ops_test.py | 59 +++++
.../python/kernel_tests/inplace_ops_test.py | 7 +
tensorflow/python/kernel_tests/io_ops_test.py | 3 +
.../linalg/linear_operator_addition_test.py | 13 +
.../linalg/linear_operator_circulant_test.py | 20 ++
.../linear_operator_composition_test.py | 4 +
.../linalg/linear_operator_diag_test.py | 4 +
.../linear_operator_full_matrix_test.py | 2 +
.../linalg/linear_operator_identity_test.py | 15 ++
.../linalg/linear_operator_kronecker_test.py | 2 +
.../linalg/linear_operator_test.py | 9 +
.../linalg/linear_operator_util_test.py | 25 ++
.../linalg/linear_operator_zeros_test.py | 7 +
.../python/kernel_tests/linalg_grad_test.py | 2 +
.../python/kernel_tests/linalg_ops_test.py | 5 +
.../python/kernel_tests/list_ops_test.py | 15 ++
.../python/kernel_tests/logging_ops_test.py | 4 +
.../python/kernel_tests/lookup_ops_test.py | 64 +++++
tensorflow/python/kernel_tests/losses_test.py | 62 +++++
tensorflow/python/kernel_tests/lrn_op_test.py | 4 +
.../python/kernel_tests/manip_ops_test.py | 12 +
.../python/kernel_tests/map_stage_op_test.py | 13 +
.../python/kernel_tests/matmul_op_test.py | 4 +
.../matrix_exponential_op_test.py | 4 +
.../kernel_tests/matrix_solve_ls_op_test.py | 4 +
.../kernel_tests/matrix_solve_op_test.py | 6 +
.../matrix_triangular_solve_op_test.py | 7 +
.../python/kernel_tests/metrics_test.py | 226 ++++++++++++++++++
.../kernel_tests/morphological_ops_test.py | 3 +
.../neon_depthwise_conv_op_test.py | 3 +
.../kernel_tests/nth_element_op_test.py | 8 +
.../python/kernel_tests/numerics_test.py | 5 +
tensorflow/python/kernel_tests/pad_op_test.py | 12 +
.../parameterized_truncated_normal_op_test.py | 11 +
.../parse_single_example_op_test.py | 7 +
.../python/kernel_tests/parsing_ops_test.py | 18 ++
.../partitioned_variables_test.py | 13 +
tensorflow/python/kernel_tests/pool_test.py | 4 +
.../kernel_tests/pooling_ops_3d_test.py | 19 ++
.../python/kernel_tests/pooling_ops_test.py | 12 +
.../python/kernel_tests/py_func_test.py | 2 +
tensorflow/python/kernel_tests/qr_op_test.py | 2 +
.../random/multinomial_op_big_test.py | 2 +
.../random/multinomial_op_test.py | 3 +
.../kernel_tests/random/random_crop_test.py | 3 +
.../kernel_tests/random/random_gamma_test.py | 6 +
.../kernel_tests/random/random_grad_test.py | 11 +
.../kernel_tests/random/random_ops_test.py | 22 ++
.../random/random_poisson_test.py | 6 +
.../random/stateless_random_ops_test.py | 6 +
.../python/kernel_tests/reader_ops_test.py | 25 ++
.../python/kernel_tests/record_input_test.py | 4 +
.../kernel_tests/reduce_join_op_test.py | 6 +
.../python/kernel_tests/reduction_ops_test.py | 57 +++++
.../kernel_tests/regex_full_match_op_test.py | 7 +
.../kernel_tests/regex_replace_op_test.py | 9 +
.../python/kernel_tests/relu_op_test.py | 21 ++
.../python/kernel_tests/reshape_op_test.py | 4 +
.../resource_variable_ops_test.py | 19 ++
.../kernel_tests/reverse_sequence_op_test.py | 3 +
tensorflow/python/kernel_tests/rnn_test.py | 10 +
.../kernel_tests/save_restore_ops_test.py | 3 +
.../python/kernel_tests/scan_ops_test.py | 24 ++
.../kernel_tests/scatter_nd_ops_test.py | 29 +++
.../python/kernel_tests/scatter_ops_test.py | 28 +++
.../segment_reduction_ops_test.py | 32 +++
tensorflow/python/kernel_tests/sets_test.py | 16 ++
.../python/kernel_tests/shape_ops_test.py | 21 ++
.../kernel_tests/signal/dct_ops_test.py | 2 +
.../kernel_tests/signal/fft_ops_test.py | 16 ++
.../kernel_tests/signal/mel_ops_test.py | 4 +
.../kernel_tests/signal/mfcc_ops_test.py | 4 +
.../signal/reconstruction_ops_test.py | 5 +
.../kernel_tests/signal/shape_ops_test.py | 12 +
.../kernel_tests/signal/window_ops_test.py | 3 +
.../python/kernel_tests/slice_op_test.py | 8 +
.../python/kernel_tests/softmax_op_test.py | 3 +
.../python/kernel_tests/softplus_op_test.py | 5 +
.../python/kernel_tests/softsign_op_test.py | 3 +
.../kernel_tests/spacetobatch_op_test.py | 36 +++
.../kernel_tests/spacetodepth_op_test.py | 11 +
.../python/kernel_tests/sparse_add_op_test.py | 3 +
.../kernel_tests/sparse_concat_op_test.py | 5 +
.../sparse_conditional_accumulator_test.py | 24 ++
.../kernel_tests/sparse_cross_op_test.py | 18 ++
.../kernel_tests/sparse_matmul_op_test.py | 7 +
.../python/kernel_tests/sparse_ops_test.py | 32 +++
.../kernel_tests/sparse_reorder_op_test.py | 4 +
.../kernel_tests/sparse_reshape_op_test.py | 18 ++
.../sparse_serialization_ops_test.py | 25 ++
.../kernel_tests/sparse_slice_op_test.py | 8 +
.../kernel_tests/sparse_split_op_test.py | 8 +
.../sparse_tensor_dense_matmul_grad_test.py | 2 +
.../sparse_tensor_dense_matmul_op_test.py | 4 +
.../sparse_tensors_map_ops_test.py | 6 +
.../sparse_to_dense_op_py_test.py | 18 ++
.../kernel_tests/sparse_xent_op_test.py | 10 +-
.../python/kernel_tests/sparsemask_op_test.py | 2 +
.../python/kernel_tests/split_op_test.py | 7 +
.../python/kernel_tests/stack_op_test.py | 17 ++
.../python/kernel_tests/stack_ops_test.py | 15 ++
.../python/kernel_tests/stage_op_test.py | 8 +
.../kernel_tests/string_join_op_test.py | 2 +
.../kernel_tests/string_length_op_test.py | 3 +
.../kernel_tests/string_split_op_test.py | 5 +
.../string_to_hash_bucket_op_test.py | 5 +
.../kernel_tests/string_to_number_op_test.py | 5 +
.../python/kernel_tests/substr_op_test.py | 9 +
.../kernel_tests/summary_v1_image_op_test.py | 3 +
.../kernel_tests/summary_v1_ops_test.py | 2 +
.../python/kernel_tests/template_test.py | 5 +
.../kernel_tests/tensor_array_ops_test.py | 42 ++++
.../python/kernel_tests/topk_op_test.py | 4 +
.../python/kernel_tests/trace_op_test.py | 2 +
.../kernel_tests/unicode_decode_op_test.py | 4 +
.../kernel_tests/unicode_script_op_test.py | 3 +
.../kernel_tests/unicode_transcode_op_test.py | 7 +
.../python/kernel_tests/unstack_op_test.py | 6 +
.../python/kernel_tests/variable_ops_test.py | 22 ++
.../kernel_tests/variable_scope_test.py | 14 ++
.../python/kernel_tests/variables_test.py | 27 +++
.../kernel_tests/weights_broadcast_test.py | 31 +++
.../python/kernel_tests/where_op_test.py | 17 ++
.../python/kernel_tests/while_v2_test.py | 15 ++
.../python/kernel_tests/xent_op_test.py | 7 +
.../python/kernel_tests/zero_division_test.py | 1 +
tensorflow/python/layers/base_test.py | 4 +
.../python/layers/convolutional_test.py | 56 +++++
tensorflow/python/layers/core_test.py | 19 ++
.../python/layers/normalization_test.py | 37 +++
tensorflow/python/layers/pooling_test.py | 4 +
tensorflow/python/ops/bitwise_ops_test.py | 6 +
tensorflow/python/ops/clip_ops_test.py | 2 +
tensorflow/python/ops/collective_ops_test.py | 5 +
.../python/ops/gradient_checker_test.py | 14 ++
tensorflow/python/ops/histogram_ops_test.py | 4 +
tensorflow/python/ops/image_grad_test.py | 12 +
tensorflow/python/ops/image_ops_test.py | 92 +++++++
tensorflow/python/ops/losses/util_test.py | 2 +
tensorflow/python/ops/math_grad_test.py | 26 ++
tensorflow/python/ops/math_ops_test.py | 24 ++
tensorflow/python/ops/nn_batchnorm_test.py | 14 ++
tensorflow/python/ops/nn_grad_test.py | 2 +
tensorflow/python/ops/nn_test.py | 20 ++
tensorflow/python/ops/nn_xent_test.py | 6 +
...vert_to_tensor_or_ragged_tensor_op_test.py | 2 +
.../ops/ragged/ragged_batch_gather_op_test.py | 3 +
.../ops/ragged/ragged_boolean_mask_op_test.py | 2 +
.../ops/ragged/ragged_concat_op_test.py | 5 +
.../python/ops/ragged/ragged_const_op_test.py | 2 +
.../ops/ragged/ragged_elementwise_ops_test.py | 1 +
.../ops/ragged/ragged_expand_dims_op_test.py | 1 +
.../ops/ragged/ragged_from_sparse_op_test.py | 5 +
.../ops/ragged/ragged_from_tensor_op_test.py | 5 +
.../ops/ragged/ragged_gather_nd_op_test.py | 3 +
.../ops/ragged/ragged_gather_op_test.py | 10 +
.../ops/ragged/ragged_map_fn_op_test.py | 5 +
.../ragged/ragged_map_inner_values_op_test.py | 13 +
.../ops/ragged/ragged_operators_test.py | 3 +
.../python/ops/ragged/ragged_range_op_test.py | 9 +
.../ops/ragged/ragged_reduce_op_test.py | 4 +
.../ops/ragged/ragged_row_lengths_op_test.py | 1 +
...agged_row_splits_to_segment_ids_op_test.py | 3 +
...agged_segment_ids_to_row_splits_op_test.py | 4 +
.../ops/ragged/ragged_segment_op_test.py | 5 +
.../python/ops/ragged/ragged_stack_op_test.py | 2 +
.../python/ops/ragged/ragged_tensor_test.py | 33 +++
.../python/ops/ragged/ragged_tile_op_test.py | 2 +
.../ops/ragged/ragged_to_sparse_op_test.py | 7 +
.../ops/ragged/ragged_to_tensor_op_test.py | 3 +
.../python/ops/ragged/ragged_where_op_test.py | 1 +
tensorflow/python/ops/sort_ops_test.py | 10 +
.../python/ops/special_math_ops_test.py | 7 +
.../profiler/internal/run_metadata_test.py | 3 +
.../python/profiler/pprof_profiler_test.py | 2 +
.../python/profiler/profile_context_test.py | 4 +
tensorflow/python/profiler/profiler_test.py | 3 +
tensorflow/python/saved_model/loader_test.py | 7 +
tensorflow/python/saved_model/save_test.py | 1 +
.../python/saved_model/saved_model_test.py | 31 +++
.../saved_model/signature_def_utils_test.py | 9 +
.../python/saved_model/simple_save_test.py | 2 +
tensorflow/python/summary/summary_test.py | 13 +
.../python/summary/writer/writer_test.py | 15 ++
tensorflow/python/tools/freeze_graph_test.py | 2 +
.../tools/optimize_for_inference_test.py | 5 +
tensorflow/python/training/adadelta_test.py | 1 +
tensorflow/python/training/adagrad_da_test.py | 7 +
tensorflow/python/training/adagrad_test.py | 9 +
tensorflow/python/training/adam_test.py | 6 +
.../python/training/basic_loops_test.py | 4 +
.../training/basic_session_run_hooks_test.py | 9 +
.../training/checkpoint_management_test.py | 5 +
.../python/training/device_setter_test.py | 11 +
tensorflow/python/training/ftrl_test.py | 14 ++
.../python/training/gradient_descent_test.py | 10 +
tensorflow/python/training/input_test.py | 108 +++++++++
.../training/learning_rate_decay_test.py | 2 +
.../training/learning_rate_decay_v2_test.py | 1 +
tensorflow/python/training/momentum_test.py | 6 +
.../python/training/monitored_session_test.py | 27 +++
.../python/training/moving_averages_test.py | 23 ++
tensorflow/python/training/optimizer_test.py | 4 +
.../python/training/proximal_adagrad_test.py | 9 +
.../proximal_gradient_descent_test.py | 8 +
.../python/training/quantize_training_test.py | 2 +
.../python/training/queue_runner_test.py | 16 ++
tensorflow/python/training/rmsprop_test.py | 6 +
tensorflow/python/training/saver_test.py | 35 +++
.../server_lib_multiple_containers_test.py | 2 +
...lib_same_variables_clear_container_test.py | 2 +
.../server_lib_same_variables_clear_test.py | 2 +
...server_lib_same_variables_no_clear_test.py | 2 +
.../training/server_lib_sparse_job_test.py | 2 +
.../python/training/session_manager_test.py | 15 ++
.../python/training/slot_creator_test.py | 8 +
tensorflow/python/training/supervisor_test.py | 12 +
.../python/training/training_ops_test.py | 8 +
.../python/training/training_util_test.py | 3 +
tensorflow/python/util/deprecation_test.py | 16 ++
tensorflow/python/util/nest_test.py | 1 +
tensorflow/python/util/tf_should_use_test.py | 7 +
.../tools/api/tests/api_compatibility_test.py | 3 +
431 files changed, 4673 insertions(+), 1 deletion(-)
diff --git a/tensorflow/examples/adding_an_op/fact_test.py b/tensorflow/examples/adding_an_op/fact_test.py
index 11163e7ba5c..46beaebe0cc 100644
--- a/tensorflow/examples/adding_an_op/fact_test.py
+++ b/tensorflow/examples/adding_an_op/fact_test.py
@@ -19,10 +19,12 @@ from __future__ import division
from __future__ import print_function
import tensorflow as tf
+from tensorflow.python.framework import test_util
class FactTest(tf.test.TestCase):
+ @test_util.run_deprecated_v1
def test(self):
with self.cached_session():
print(tf.user_ops.my_fact().eval())
diff --git a/tensorflow/examples/adding_an_op/zero_out_1_test.py b/tensorflow/examples/adding_an_op/zero_out_1_test.py
index 342d3a020cc..459ac2dc279 100644
--- a/tensorflow/examples/adding_an_op/zero_out_1_test.py
+++ b/tensorflow/examples/adding_an_op/zero_out_1_test.py
@@ -23,10 +23,12 @@ import os.path
import tensorflow as tf
from tensorflow.examples.adding_an_op import zero_out_op_1
+from tensorflow.python.framework import test_util
class ZeroOut1Test(tf.test.TestCase):
+ @test_util.run_deprecated_v1
def test(self):
with self.cached_session():
result = zero_out_op_1.zero_out([5, 4, 3, 2, 1])
diff --git a/tensorflow/examples/adding_an_op/zero_out_2_test.py b/tensorflow/examples/adding_an_op/zero_out_2_test.py
index 45045978176..650fd9546b5 100644
--- a/tensorflow/examples/adding_an_op/zero_out_2_test.py
+++ b/tensorflow/examples/adding_an_op/zero_out_2_test.py
@@ -24,20 +24,24 @@ import tensorflow as tf
from tensorflow.examples.adding_an_op import zero_out_grad_2 # pylint: disable=unused-import
from tensorflow.examples.adding_an_op import zero_out_op_2
+from tensorflow.python.framework import test_util
class ZeroOut2Test(tf.test.TestCase):
+ @test_util.run_deprecated_v1
def test(self):
with self.cached_session():
result = zero_out_op_2.zero_out([5, 4, 3, 2, 1])
self.assertAllEqual(result.eval(), [5, 0, 0, 0, 0])
+ @test_util.run_deprecated_v1
def test_2d(self):
with self.cached_session():
result = zero_out_op_2.zero_out([[6, 5, 4], [3, 2, 1]])
self.assertAllEqual(result.eval(), [[6, 0, 0], [0, 0, 0]])
+ @test_util.run_deprecated_v1
def test_grad(self):
with self.cached_session():
shape = (5,)
@@ -46,6 +50,7 @@ class ZeroOut2Test(tf.test.TestCase):
err = tf.test.compute_gradient_error(x, shape, y, shape)
self.assertLess(err, 1e-4)
+ @test_util.run_deprecated_v1
def test_grad_2d(self):
with self.cached_session():
shape = (2, 3)
diff --git a/tensorflow/examples/adding_an_op/zero_out_3_test.py b/tensorflow/examples/adding_an_op/zero_out_3_test.py
index 2327e7cd8fa..8cbe2b6793a 100644
--- a/tensorflow/examples/adding_an_op/zero_out_3_test.py
+++ b/tensorflow/examples/adding_an_op/zero_out_3_test.py
@@ -21,26 +21,31 @@ from __future__ import print_function
import tensorflow as tf
from tensorflow.examples.adding_an_op import zero_out_op_3
+from tensorflow.python.framework import test_util
class ZeroOut3Test(tf.test.TestCase):
+ @test_util.run_deprecated_v1
def test(self):
with self.cached_session():
result = zero_out_op_3.zero_out([5, 4, 3, 2, 1])
self.assertAllEqual(result.eval(), [5, 0, 0, 0, 0])
+ @test_util.run_deprecated_v1
def testAttr(self):
with self.cached_session():
result = zero_out_op_3.zero_out([5, 4, 3, 2, 1], preserve_index=3)
self.assertAllEqual(result.eval(), [0, 0, 0, 2, 0])
+ @test_util.run_deprecated_v1
def testNegative(self):
with self.cached_session():
result = zero_out_op_3.zero_out([5, 4, 3, 2, 1], preserve_index=-1)
with self.assertRaisesOpError("Need preserve_index >= 0, got -1"):
self.evaluate(result)
+ @test_util.run_deprecated_v1
def testLarge(self):
with self.cached_session():
result = zero_out_op_3.zero_out([5, 4, 3, 2, 1], preserve_index=17)
diff --git a/tensorflow/examples/autograph/integration_tests/keras_test.py b/tensorflow/examples/autograph/integration_tests/keras_test.py
index fc0b0736965..3fe33df920d 100644
--- a/tensorflow/examples/autograph/integration_tests/keras_test.py
+++ b/tensorflow/examples/autograph/integration_tests/keras_test.py
@@ -21,6 +21,7 @@ from __future__ import print_function
import tensorflow as tf
from tensorflow.python import autograph
+from tensorflow.python.framework import test_util
class MinimalKeras(tf.keras.Model):
@@ -84,6 +85,7 @@ class KerasTest(tf.test.TestCase):
model = ModelWithStaticConditional(True)
self.assertEqual(model.call(), 25)
+ @test_util.run_deprecated_v1
def test_recursive_true(self):
with self.assertRaisesRegexp(NotImplementedError,
'Object conversion is not yet supported.'):
diff --git a/tensorflow/examples/speech_commands/freeze_test.py b/tensorflow/examples/speech_commands/freeze_test.py
index 0c7ca9bc011..9ed9050035b 100644
--- a/tensorflow/examples/speech_commands/freeze_test.py
+++ b/tensorflow/examples/speech_commands/freeze_test.py
@@ -19,11 +19,13 @@ from __future__ import division
from __future__ import print_function
from tensorflow.examples.speech_commands import freeze
+from tensorflow.python.framework import test_util
from tensorflow.python.platform import test
class FreezeTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testCreateInferenceGraphWithMfcc(self):
with self.cached_session() as sess:
freeze.create_inference_graph(
@@ -43,6 +45,7 @@ class FreezeTest(test.TestCase):
ops = [node.op for node in sess.graph_def.node]
self.assertEqual(1, ops.count('Mfcc'))
+ @test_util.run_deprecated_v1
def testCreateInferenceGraphWithoutMfcc(self):
with self.cached_session() as sess:
freeze.create_inference_graph(
@@ -62,6 +65,7 @@ class FreezeTest(test.TestCase):
ops = [node.op for node in sess.graph_def.node]
self.assertEqual(0, ops.count('Mfcc'))
+ @test_util.run_deprecated_v1
def testFeatureBinCount(self):
with self.cached_session() as sess:
freeze.create_inference_graph(
diff --git a/tensorflow/examples/speech_commands/input_data_test.py b/tensorflow/examples/speech_commands/input_data_test.py
index 33b58b9d09b..9269bb6c0bc 100644
--- a/tensorflow/examples/speech_commands/input_data_test.py
+++ b/tensorflow/examples/speech_commands/input_data_test.py
@@ -26,6 +26,7 @@ import tensorflow as tf
from tensorflow.contrib.framework.python.ops import audio_ops as contrib_audio
from tensorflow.examples.speech_commands import input_data
from tensorflow.examples.speech_commands import models
+from tensorflow.python.framework import test_util
from tensorflow.python.platform import test
@@ -96,6 +97,7 @@ class InputDataTest(test.TestCase):
input_data.which_set("foo_nohash_0.wav", 10, 10),
input_data.which_set("foo_nohash_1.wav", 10, 10))
+ @test_util.run_deprecated_v1
def testPrepareDataIndex(self):
tmp_dir = self.get_temp_dir()
self._saveWavFolders(tmp_dir, ["a", "b", "c"], 100)
@@ -125,6 +127,7 @@ class InputDataTest(test.TestCase):
10, self._model_settings(), tmp_dir)
self.assertTrue("Expected to find" in str(e.exception))
+ @test_util.run_deprecated_v1
def testPrepareBackgroundData(self):
tmp_dir = self.get_temp_dir()
background_dir = os.path.join(tmp_dir, "_background_noise_")
@@ -156,6 +159,7 @@ class InputDataTest(test.TestCase):
self.assertIsNotNone(loaded_data)
self.assertEqual(16000, len(loaded_data))
+ @test_util.run_deprecated_v1
def testPrepareProcessingGraph(self):
tmp_dir = self.get_temp_dir()
wav_dir = os.path.join(tmp_dir, "wavs")
@@ -186,15 +190,19 @@ class InputDataTest(test.TestCase):
self.assertIsNotNone(audio_processor.background_volume_placeholder_)
self.assertIsNotNone(audio_processor.output_)
+ @test_util.run_deprecated_v1
def testGetDataAverage(self):
self._runGetDataTest("average", 10)
+ @test_util.run_deprecated_v1
def testGetDataAverageLongWindow(self):
self._runGetDataTest("average", 30)
+ @test_util.run_deprecated_v1
def testGetDataMfcc(self):
self._runGetDataTest("mfcc", 30)
+ @test_util.run_deprecated_v1
def testGetUnprocessedData(self):
tmp_dir = self.get_temp_dir()
wav_dir = os.path.join(tmp_dir, "wavs")
@@ -216,6 +224,7 @@ class InputDataTest(test.TestCase):
self.assertEqual(10, len(result_data))
self.assertEqual(10, len(result_labels))
+ @test_util.run_deprecated_v1
def testGetFeaturesForWav(self):
tmp_dir = self.get_temp_dir()
wav_dir = os.path.join(tmp_dir, "wavs")
diff --git a/tensorflow/examples/speech_commands/models_test.py b/tensorflow/examples/speech_commands/models_test.py
index 04478c09626..cb9304eab8d 100644
--- a/tensorflow/examples/speech_commands/models_test.py
+++ b/tensorflow/examples/speech_commands/models_test.py
@@ -21,6 +21,7 @@ from __future__ import print_function
import tensorflow as tf
from tensorflow.examples.speech_commands import models
+from tensorflow.python.framework import test_util
from tensorflow.python.platform import test
@@ -47,6 +48,7 @@ class ModelsTest(test.TestCase):
feature_bin_count=40,
preprocess="mfcc"))
+ @test_util.run_deprecated_v1
def testCreateModelConvTraining(self):
model_settings = self._modelSettings()
with self.cached_session() as sess:
@@ -58,6 +60,7 @@ class ModelsTest(test.TestCase):
self.assertIsNotNone(sess.graph.get_tensor_by_name(logits.name))
self.assertIsNotNone(sess.graph.get_tensor_by_name(dropout_prob.name))
+ @test_util.run_deprecated_v1
def testCreateModelConvInference(self):
model_settings = self._modelSettings()
with self.cached_session() as sess:
@@ -67,6 +70,7 @@ class ModelsTest(test.TestCase):
self.assertIsNotNone(logits)
self.assertIsNotNone(sess.graph.get_tensor_by_name(logits.name))
+ @test_util.run_deprecated_v1
def testCreateModelLowLatencyConvTraining(self):
model_settings = self._modelSettings()
with self.cached_session() as sess:
@@ -78,6 +82,7 @@ class ModelsTest(test.TestCase):
self.assertIsNotNone(sess.graph.get_tensor_by_name(logits.name))
self.assertIsNotNone(sess.graph.get_tensor_by_name(dropout_prob.name))
+ @test_util.run_deprecated_v1
def testCreateModelFullyConnectedTraining(self):
model_settings = self._modelSettings()
with self.cached_session() as sess:
@@ -98,6 +103,7 @@ class ModelsTest(test.TestCase):
"bad_architecture", True)
self.assertTrue("not recognized" in str(e.exception))
+ @test_util.run_deprecated_v1
def testCreateModelTinyConvTraining(self):
model_settings = self._modelSettings()
with self.cached_session() as sess:
diff --git a/tensorflow/examples/speech_commands/wav_to_features_test.py b/tensorflow/examples/speech_commands/wav_to_features_test.py
index cb8ea912fa2..6234490b267 100644
--- a/tensorflow/examples/speech_commands/wav_to_features_test.py
+++ b/tensorflow/examples/speech_commands/wav_to_features_test.py
@@ -24,6 +24,7 @@ import tensorflow as tf
from tensorflow.contrib.framework.python.ops import audio_ops as contrib_audio
from tensorflow.examples.speech_commands import wav_to_features
+from tensorflow.python.framework import test_util
from tensorflow.python.platform import test
@@ -49,6 +50,7 @@ class WavToFeaturesTest(test.TestCase):
file_path = os.path.join(dir_name, "some_audio_%d.wav" % i)
self._saveTestWavFile(file_path, wav_data)
+ @test_util.run_deprecated_v1
def testWavToFeatures(self):
tmp_dir = self.get_temp_dir()
wav_dir = os.path.join(tmp_dir, "wavs")
diff --git a/tensorflow/python/autograph/converters/asserts_test.py b/tensorflow/python/autograph/converters/asserts_test.py
index 803b6a06dab..9ae448892a0 100644
--- a/tensorflow/python/autograph/converters/asserts_test.py
+++ b/tensorflow/python/autograph/converters/asserts_test.py
@@ -23,12 +23,14 @@ from tensorflow.python.autograph.converters import side_effect_guards
from tensorflow.python.autograph.core import converter_testing
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import errors_impl
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import gen_control_flow_ops
from tensorflow.python.platform import test
class AssertsTest(converter_testing.TestCase):
+ @test_util.run_deprecated_v1
def test_basic(self):
def test_fn(a):
diff --git a/tensorflow/python/autograph/converters/builtin_functions_test.py b/tensorflow/python/autograph/converters/builtin_functions_test.py
index 30cfb13233a..2683be16ec7 100644
--- a/tensorflow/python/autograph/converters/builtin_functions_test.py
+++ b/tensorflow/python/autograph/converters/builtin_functions_test.py
@@ -24,12 +24,14 @@ from tensorflow.python.autograph.converters import builtin_functions
from tensorflow.python.autograph.core import converter_testing
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.platform import test
class BuiltinFunctionsTest(converter_testing.TestCase):
+ @test_util.run_deprecated_v1
def test_len(self):
def test_fn(a):
@@ -41,6 +43,7 @@ class BuiltinFunctionsTest(converter_testing.TestCase):
ops = result.test_fn(p)
self.assertEqual(sess.run(ops, {p: [0, 0, 0]}), 3)
+ @test_util.run_deprecated_v1
def test_print(self):
if six.PY2:
@@ -54,6 +57,7 @@ class BuiltinFunctionsTest(converter_testing.TestCase):
with self.assertPrints('a\n'):
sess.run(result.test_fn('a'))
+ @test_util.run_deprecated_v1
def test_print_multiple_values(self):
if six.PY2:
diff --git a/tensorflow/python/autograph/converters/control_flow_test.py b/tensorflow/python/autograph/converters/control_flow_test.py
index 03fdfc804e4..034fcbe3865 100644
--- a/tensorflow/python/autograph/converters/control_flow_test.py
+++ b/tensorflow/python/autograph/converters/control_flow_test.py
@@ -23,6 +23,7 @@ from tensorflow.python.autograph.core import converter_testing
from tensorflow.python.autograph.pyct import transformer
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.platform import test
@@ -36,6 +37,7 @@ class ControlFlowTest(converter_testing.TestCase):
with self.cached_session() as sess:
self.assertEqual(sess.run(result.test_fn(*inputs)), expected)
+ @test_util.run_deprecated_v1
def test_while_basic(self):
def test_fn(n):
@@ -48,6 +50,7 @@ class ControlFlowTest(converter_testing.TestCase):
self.assertTransformedResult(test_fn, constant_op.constant(5), (10, 5, 5))
+ @test_util.run_deprecated_v1
def test_while_nested(self):
def test_fn(n):
@@ -66,6 +69,7 @@ class ControlFlowTest(converter_testing.TestCase):
self.assertTransformedResult(test_fn, constant_op.constant(5),
(25, 5, 0, 5))
+ @test_util.run_deprecated_v1
def test_while_single_output(self):
def test_fn(n):
@@ -86,6 +90,7 @@ class ControlFlowTest(converter_testing.TestCase):
with self.assertRaises(NameError):
control_flow.transform(node, ctx)
+ @test_util.run_deprecated_v1
def test_if_basic(self):
def test_fn(n):
@@ -100,6 +105,7 @@ class ControlFlowTest(converter_testing.TestCase):
self.assertTransformedResult(test_fn, constant_op.constant(1), (-1, 0))
self.assertTransformedResult(test_fn, constant_op.constant(-1), (0, -2))
+ @test_util.run_deprecated_v1
def test_if_complex_outputs(self):
class TestClass(object):
@@ -124,6 +130,7 @@ class ControlFlowTest(converter_testing.TestCase):
res_obj = result.test_fn(constant_op.constant(-1), TestClass(0, 0))
self.assertEqual(sess.run((res_obj.a, res_obj.b)), (0, -2))
+ @test_util.run_deprecated_v1
def test_if_single_output(self):
def test_fn(n):
@@ -133,6 +140,7 @@ class ControlFlowTest(converter_testing.TestCase):
self.assertTransformedResult(test_fn, constant_op.constant(1), -1)
+ @test_util.run_deprecated_v1
def test_if_semi(self):
def test_fn(n):
@@ -143,6 +151,7 @@ class ControlFlowTest(converter_testing.TestCase):
self.assertTransformedResult(test_fn, constant_op.constant(2), 3)
self.assertTransformedResult(test_fn, constant_op.constant(-3), -3)
+ @test_util.run_deprecated_v1
def test_if_local_var(self):
def test_fn(n):
@@ -154,6 +163,7 @@ class ControlFlowTest(converter_testing.TestCase):
self.assertTransformedResult(test_fn, constant_op.constant(1), 5)
self.assertTransformedResult(test_fn, constant_op.constant(-1), -1)
+ @test_util.run_deprecated_v1
def test_if_no_outputs(self):
def test_fn(n):
@@ -177,6 +187,7 @@ class ControlFlowTest(converter_testing.TestCase):
with self.assertRaises(transformer.AutographParseError):
control_flow.transform(node, ctx)
+ @test_util.run_deprecated_v1
def test_simple_for(self):
def test_fn(l):
@@ -191,6 +202,7 @@ class ControlFlowTest(converter_testing.TestCase):
empty_vector = constant_op.constant([], shape=(0,), dtype=dtypes.int32)
self.assertTransformedResult(test_fn, empty_vector, (0, 0))
+ @test_util.run_deprecated_v1
def test_for_single_output(self):
def test_fn(l):
@@ -235,6 +247,7 @@ class ControlFlowTest(converter_testing.TestCase):
with self.assertRaises(NameError):
control_flow.transform(node, ctx)
+ @test_util.run_deprecated_v1
def test_for_tuple_unpacking(self):
def test_fn(x_list):
z = tf.constant(0) # pylint:disable=undefined-variable
diff --git a/tensorflow/python/autograph/converters/function_scopes_test.py b/tensorflow/python/autograph/converters/function_scopes_test.py
index e5ce03a1090..5a1248c8015 100644
--- a/tensorflow/python/autograph/converters/function_scopes_test.py
+++ b/tensorflow/python/autograph/converters/function_scopes_test.py
@@ -22,11 +22,13 @@ from tensorflow.python.autograph.converters import function_scopes
from tensorflow.python.autograph.core import converter_testing
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.platform import test
class FunctionBodyTransformerTest(converter_testing.TestCase):
+ @test_util.run_deprecated_v1
def test_basic(self):
def test_fn(l):
@@ -40,6 +42,7 @@ class FunctionBodyTransformerTest(converter_testing.TestCase):
self.assertIn('test_fn/', result_op.op.name)
self.assertEqual('Docstring.', result.test_fn.__doc__)
+ @test_util.run_deprecated_v1
def test_multiline_docstring(self):
tf = None
@@ -58,6 +61,7 @@ class FunctionBodyTransformerTest(converter_testing.TestCase):
self.assertIn('First sentence.', result.test_fn.__doc__)
self.assertIn('Second sentence.', result.test_fn.__doc__)
+ @test_util.run_deprecated_v1
def test_nested_functions(self):
def test_fn(l):
@@ -74,6 +78,7 @@ class FunctionBodyTransformerTest(converter_testing.TestCase):
self.assertNotIn('inner_fn', first.op.name)
self.assertIn('test_fn/inner_fn/', second.op.name)
+ @test_util.run_deprecated_v1
def test_method(self):
class TestClass(object):
diff --git a/tensorflow/python/autograph/converters/logical_expressions_test.py b/tensorflow/python/autograph/converters/logical_expressions_test.py
index 99db04a7751..687412750e0 100644
--- a/tensorflow/python/autograph/converters/logical_expressions_test.py
+++ b/tensorflow/python/autograph/converters/logical_expressions_test.py
@@ -21,11 +21,13 @@ from __future__ import print_function
from tensorflow.python.autograph.converters import logical_expressions
from tensorflow.python.autograph.core import converter_testing
from tensorflow.python.framework import constant_op
+from tensorflow.python.framework import test_util
from tensorflow.python.platform import test
class LogicalExpressionTest(converter_testing.TestCase):
+ @test_util.run_deprecated_v1
def test_equals(self):
def test_fn(a, b):
@@ -36,6 +38,7 @@ class LogicalExpressionTest(converter_testing.TestCase):
self.assertTrue(sess.run(result.test_fn(constant_op.constant(1), 1)))
self.assertFalse(sess.run(result.test_fn(constant_op.constant(1), 2)))
+ @test_util.run_deprecated_v1
def test_bool_ops(self):
def test_fn(a, b, c):
@@ -48,6 +51,7 @@ class LogicalExpressionTest(converter_testing.TestCase):
self.assertFalse(
sess.run(result.test_fn(constant_op.constant(True), False, True)))
+ @test_util.run_deprecated_v1
def test_comparison(self):
def test_fn(a, b, c, d):
diff --git a/tensorflow/python/autograph/converters/side_effect_guards_test.py b/tensorflow/python/autograph/converters/side_effect_guards_test.py
index f6d0f73b5b9..645267e5600 100644
--- a/tensorflow/python/autograph/converters/side_effect_guards_test.py
+++ b/tensorflow/python/autograph/converters/side_effect_guards_test.py
@@ -23,6 +23,7 @@ from tensorflow.python.autograph.core import converter_testing
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import errors_impl
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import control_flow_ops
from tensorflow.python.ops import state_ops
from tensorflow.python.ops import variable_scope
@@ -34,6 +35,7 @@ tf = None # Will be replaced by a mock.
class SideEffectGuardsTest(converter_testing.TestCase):
+ @test_util.run_deprecated_v1
def test_side_effect_on_return_only_variable(self):
def test_fn(a):
@@ -75,6 +77,7 @@ class SideEffectGuardsTest(converter_testing.TestCase):
# Right now it's 3 or 4 based on whether the read is synchronized.
self.assertEqual(3, self.evaluate(v))
+ @test_util.run_deprecated_v1
def test_side_effect_on_tensor(self):
def test_fn(a):
diff --git a/tensorflow/python/autograph/core/errors_test.py b/tensorflow/python/autograph/core/errors_test.py
index 00c8a726eda..845a28a5222 100644
--- a/tensorflow/python/autograph/core/errors_test.py
+++ b/tensorflow/python/autograph/core/errors_test.py
@@ -22,6 +22,7 @@ from tensorflow.python.autograph.core import errors
from tensorflow.python.autograph.pyct import origin_info
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors as tf_errors
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.platform import test
from tensorflow.python.util import tf_inspect
@@ -47,6 +48,7 @@ class RuntimeErrorsTest(test.TestCase):
'test_comment')
return loc, origin
+ @test_util.run_deprecated_v1
def test_improved_errors_basic(self):
loc, origin = self.fake_origin(zero_div, 2)
zero_div_caller.ag_source_map = {loc: origin}
@@ -62,6 +64,7 @@ class RuntimeErrorsTest(test.TestCase):
self.assertNotEqual('zero_div', function_name)
self.assertIn(origin.as_frame(), set(cm.exception.custom_traceback))
+ @test_util.run_deprecated_v1
def test_improved_errors_no_matching_lineno(self):
loc, origin = self.fake_origin(zero_div, -1)
zero_div_caller.ag_source_map = {loc: origin}
@@ -79,6 +82,7 @@ class RuntimeErrorsTest(test.TestCase):
self.assertNotEqual('test_function_name', function_name)
self.assertIn('zero_div', all_function_names)
+ @test_util.run_deprecated_v1
def test_improved_errors_failures(self):
loc, _ = self.fake_origin(zero_div, 2)
zero_div_caller.ag_source_map = {loc: 'bogus object'}
diff --git a/tensorflow/python/autograph/core/function_wrapping_test.py b/tensorflow/python/autograph/core/function_wrapping_test.py
index 5e217055c71..7e21b979dbc 100644
--- a/tensorflow/python/autograph/core/function_wrapping_test.py
+++ b/tensorflow/python/autograph/core/function_wrapping_test.py
@@ -20,11 +20,13 @@ from __future__ import print_function
from tensorflow.python.autograph.core import function_wrapping
from tensorflow.python.framework import constant_op
+from tensorflow.python.framework import test_util
from tensorflow.python.platform import test
class FunctionWrappingTest(test.TestCase):
+ @test_util.run_deprecated_v1
def test_function_scope_name(self):
with function_wrapping.function_scope('test_name'):
t = constant_op.constant(1)
diff --git a/tensorflow/python/autograph/impl/api_test.py b/tensorflow/python/autograph/impl/api_test.py
index a0fa501fb83..66edda51193 100644
--- a/tensorflow/python/autograph/impl/api_test.py
+++ b/tensorflow/python/autograph/impl/api_test.py
@@ -29,6 +29,7 @@ from tensorflow.python.autograph.impl import api
from tensorflow.python.autograph.pyct import parser
from tensorflow.python.autograph.utils import py_func
from tensorflow.python.framework import constant_op
+from tensorflow.python.framework import test_util
from tensorflow.python.keras.engine import sequential
from tensorflow.python.keras.layers import core
from tensorflow.python.ops import variables
@@ -44,6 +45,7 @@ class TestResource(str):
class ApiTest(test.TestCase):
+ @test_util.run_deprecated_v1
def test_decorator_recurses(self):
class TestClass(object):
@@ -66,6 +68,7 @@ class ApiTest(test.TestCase):
constant_op.constant(-2))
self.assertListEqual([0, 1], self.evaluate(x).tolist())
+ @test_util.run_deprecated_v1
def test_decorator_does_not_recurse(self):
class TestClass(object):
@@ -86,6 +89,7 @@ class ApiTest(test.TestCase):
constant_op.constant(-2))
self.assertListEqual([0, 1], self.evaluate(x).tolist())
+ @test_util.run_deprecated_v1
def test_decorator_calls_unconverted_graph(self):
class TestClass(object):
@@ -107,6 +111,7 @@ class ApiTest(test.TestCase):
constant_op.constant(-2))
self.assertListEqual([0, 1], self.evaluate(x).tolist())
+ @test_util.run_deprecated_v1
def test_decorator_calls_unconverted_py_func(self):
class TestClass(object):
@@ -133,6 +138,7 @@ class ApiTest(test.TestCase):
constant_op.constant(-2))
self.assertListEqual([0, 1], self.evaluate(x).tolist())
+ @test_util.run_deprecated_v1
def test_decorator_calls_decorated(self):
class TestClass(object):
@@ -172,6 +178,7 @@ class ApiTest(test.TestCase):
list(tf_inspect.getfullargspec(tc.called_member)),
list(tf_inspect.getfullargspec(tc.called_member_converted)))
+ @test_util.run_deprecated_v1
def test_convert_call_site_decorator(self):
class TestClass(object):
@@ -326,6 +333,7 @@ class ApiTest(test.TestCase):
constant_op.constant(0))
self.assertTrue(self.evaluate(x))
+ @test_util.run_deprecated_v1
def test_converted_call_no_user_code(self):
def f(x):
@@ -400,6 +408,7 @@ class ApiTest(test.TestCase):
self.evaluate(variables.global_variables_initializer())
self.assertAllEqual(True, self.evaluate(x))
+ @test_util.run_deprecated_v1
def test_to_graph_basic(self):
def test_fn(x, s):
@@ -413,6 +422,7 @@ class ApiTest(test.TestCase):
x = compiled_fn(constant_op.constant([4, 8]), 4)
self.assertListEqual([1, 2], self.evaluate(x).tolist())
+ @test_util.run_deprecated_v1
def test_to_graph_with_defaults(self):
foo = 4
diff --git a/tensorflow/python/autograph/operators/control_flow_test.py b/tensorflow/python/autograph/operators/control_flow_test.py
index 05b5660941d..0a7d4b64022 100644
--- a/tensorflow/python/autograph/operators/control_flow_test.py
+++ b/tensorflow/python/autograph/operators/control_flow_test.py
@@ -22,12 +22,14 @@ from tensorflow.python.autograph.operators import control_flow
from tensorflow.python.data.ops import dataset_ops
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import math_ops
from tensorflow.python.platform import test
class ForLoopTest(test.TestCase):
+ @test_util.run_deprecated_v1
def test_tensor(self):
s = control_flow.for_stmt(
constant_op.constant([1, 2, 3, 4]),
@@ -45,6 +47,7 @@ class ForLoopTest(test.TestCase):
init_state=(0,))
self.assertEqual(10, s)
+ @test_util.run_deprecated_v1
def test_dataset(self):
to_int32 = lambda i: math_ops.cast(i, dtypes.int32)
s = control_flow.for_stmt(
@@ -58,6 +61,7 @@ class ForLoopTest(test.TestCase):
class WhileLoopTest(test.TestCase):
+ @test_util.run_deprecated_v1
def test_tensor(self):
n = constant_op.constant(5)
results = control_flow.while_stmt(
@@ -87,6 +91,7 @@ class IfStmtTest(test.TestCase):
return control_flow.if_stmt(
cond=cond, body=lambda: (1, 2), orelse=lambda: (-1, -2))
+ @test_util.run_deprecated_v1
def test_tensor(self):
with self.cached_session() as sess:
t = self.single_return_if_stmt(constant_op.constant(True))
@@ -98,6 +103,7 @@ class IfStmtTest(test.TestCase):
self.assertEqual(1, self.single_return_if_stmt(True))
self.assertEqual(-1, self.single_return_if_stmt(False))
+ @test_util.run_deprecated_v1
def test_tensor_multiple_returns(self):
with self.cached_session() as sess:
t = self.multi_return_if_stmt(constant_op.constant(True))
diff --git a/tensorflow/python/autograph/operators/data_structures_test.py b/tensorflow/python/autograph/operators/data_structures_test.py
index 0433e3f130c..9397b9acb82 100644
--- a/tensorflow/python/autograph/operators/data_structures_test.py
+++ b/tensorflow/python/autograph/operators/data_structures_test.py
@@ -22,6 +22,7 @@ from tensorflow.python.autograph.operators import data_structures
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import list_ops
from tensorflow.python.ops import tensor_array_ops
from tensorflow.python.platform import test
@@ -59,6 +60,7 @@ class ListTest(test.TestCase):
with self.cached_session() as sess:
self.assertAllEqual(self.evaluate(t), [3, 4, 5])
+ @test_util.run_deprecated_v1
def test_tf_tensor_list_new_illegal_input(self):
with self.assertRaises(ValueError):
data_structures.tf_tensor_list_new([3, 4.0])
@@ -104,6 +106,7 @@ class ListTest(test.TestCase):
with self.cached_session() as sess:
self.assertAllEqual(self.evaluate(t), [[1, 2, 3]])
+ @test_util.run_deprecated_v1
def test_append_tensorarray(self):
l = tensor_array_ops.TensorArray(dtypes.int32, size=0, dynamic_size=True)
l1 = data_structures.list_append(l, 1)
@@ -154,6 +157,7 @@ class ListTest(test.TestCase):
t = data_structures.list_stack(l, opts)
self.assertAllEqual(self.evaluate(t), self.evaluate(initial_list))
+ @test_util.run_deprecated_v1
def test_stack_tensor_list_empty(self):
l = list_ops.empty_tensor_list(
element_shape=None, element_dtype=dtypes.variant)
diff --git a/tensorflow/python/autograph/operators/exceptions_test.py b/tensorflow/python/autograph/operators/exceptions_test.py
index 24d3f1bd35f..21ba76bb952 100644
--- a/tensorflow/python/autograph/operators/exceptions_test.py
+++ b/tensorflow/python/autograph/operators/exceptions_test.py
@@ -21,6 +21,7 @@ from __future__ import print_function
from tensorflow.python.autograph.operators import exceptions
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import errors_impl
+from tensorflow.python.framework import test_util
from tensorflow.python.platform import test
@@ -32,6 +33,7 @@ class ExceptionsTest(test.TestCase):
constant_op.constant(True), lambda: constant_op.constant('ignored'))
self.evaluate(t)
+ @test_util.run_deprecated_v1
def test_assert_tf_triggered(self):
with self.cached_session() as sess:
t = exceptions.assert_stmt(
@@ -42,6 +44,7 @@ class ExceptionsTest(test.TestCase):
'test message'):
self.evaluate(t)
+ @test_util.run_deprecated_v1
def test_assert_tf_multiple_printed_values(self):
two_tensors = [
constant_op.constant('test message'),
diff --git a/tensorflow/python/autograph/operators/logical_test.py b/tensorflow/python/autograph/operators/logical_test.py
index ebf6458f01e..e22f39932d1 100644
--- a/tensorflow/python/autograph/operators/logical_test.py
+++ b/tensorflow/python/autograph/operators/logical_test.py
@@ -20,6 +20,7 @@ from __future__ import print_function
from tensorflow.python.autograph.operators import logical
from tensorflow.python.framework import constant_op
+from tensorflow.python.framework import test_util
from tensorflow.python.platform import test
@@ -42,6 +43,7 @@ class LogicalOperatorsTest(test.TestCase):
self.assertFalse(logical.and_(lambda: False, lambda: True))
self.assertFalse(logical.and_(lambda: False, self.assertNotCalled))
+ @test_util.run_deprecated_v1
def test_and_tf(self):
with self.cached_session() as sess:
t = logical.and_(self._tf_true, self._tf_true)
@@ -60,6 +62,7 @@ class LogicalOperatorsTest(test.TestCase):
self.assertTrue(logical.or_(lambda: False, lambda: True))
self.assertTrue(logical.or_(lambda: True, self.assertNotCalled))
+ @test_util.run_deprecated_v1
def test_or_tf(self):
with self.cached_session() as sess:
t = logical.or_(self._tf_false, self._tf_true)
diff --git a/tensorflow/python/autograph/operators/py_builtins_test.py b/tensorflow/python/autograph/operators/py_builtins_test.py
index 4d9eec77c38..c856e39d141 100644
--- a/tensorflow/python/autograph/operators/py_builtins_test.py
+++ b/tensorflow/python/autograph/operators/py_builtins_test.py
@@ -27,6 +27,7 @@ from tensorflow.python.autograph.operators import py_builtins
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors_impl
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import tensor_array_ops
from tensorflow.python.platform import test
@@ -81,6 +82,7 @@ class PyBuiltinsTest(test.TestCase):
with self.assertRaises(ValueError):
py_builtins.len_(constant_op.constant(1))
+ @test_util.run_deprecated_v1
def test_len_dynamic_shape(self):
with self.cached_session() as sess:
p = array_ops.placeholder(dtype=dtypes.int32, shape=None)
@@ -91,6 +93,7 @@ class PyBuiltinsTest(test.TestCase):
t = py_builtins.len_(p)
sess.run(t, {p: 1})
+ @test_util.run_deprecated_v1
def test_print_tensors(self):
try:
out_capturer = six.StringIO()
@@ -101,6 +104,7 @@ class PyBuiltinsTest(test.TestCase):
finally:
sys.stdout = sys.__stdout__
+ @test_util.run_deprecated_v1
def test_print_complex(self):
try:
out_capturer = six.StringIO()
diff --git a/tensorflow/python/autograph/utils/misc_test.py b/tensorflow/python/autograph/utils/misc_test.py
index c813e0f5c96..c78df48d626 100644
--- a/tensorflow/python/autograph/utils/misc_test.py
+++ b/tensorflow/python/autograph/utils/misc_test.py
@@ -19,6 +19,7 @@ from __future__ import division
from __future__ import print_function
from tensorflow.python.autograph.utils.misc import alias_tensors
+from tensorflow.python.framework import test_util
from tensorflow.python.framework.constant_op import constant
from tensorflow.python.ops.variables import Variable
from tensorflow.python.platform import test
@@ -26,6 +27,7 @@ from tensorflow.python.platform import test
class MiscTest(test.TestCase):
+ @test_util.run_deprecated_v1
def test_alias_single_tensor(self):
a = constant(1)
@@ -34,6 +36,7 @@ class MiscTest(test.TestCase):
with self.cached_session() as sess:
self.assertEqual(1, self.evaluate(new_a))
+ @test_util.run_deprecated_v1
def test_alias_tensors(self):
a = constant(1)
v = Variable(2)
diff --git a/tensorflow/python/autograph/utils/tensor_list_test.py b/tensorflow/python/autograph/utils/tensor_list_test.py
index c655f773b00..0bd30072497 100644
--- a/tensorflow/python/autograph/utils/tensor_list_test.py
+++ b/tensorflow/python/autograph/utils/tensor_list_test.py
@@ -23,6 +23,7 @@ from tensorflow.python.client.session import Session
from tensorflow.python.eager import context
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.framework.constant_op import constant
from tensorflow.python.ops import list_ops
from tensorflow.python.ops import tensor_array_ops
@@ -34,6 +35,7 @@ class TensorListTest(test.TestCase):
def _shape(self, shape_tuple):
return constant(shape_tuple, dtypes.int32)
+ @test_util.run_deprecated_v1
def test_dynamic_list_append(self):
l = []
l = tl.dynamic_list_append(l, 1)
@@ -80,6 +82,7 @@ class TensorListTest(test.TestCase):
l[0] = ops.convert_to_tensor(b)
self.assertEqual(l[0].numpy(), b.numpy())
+ @test_util.run_deprecated_v1
def test_list_append_tf(self):
a = constant(3.0)
l = tl.TensorList(a.shape, a.dtype)
diff --git a/tensorflow/python/autograph/utils/type_check_test.py b/tensorflow/python/autograph/utils/type_check_test.py
index b3d1304e16f..2521dc9f925 100644
--- a/tensorflow/python/autograph/utils/type_check_test.py
+++ b/tensorflow/python/autograph/utils/type_check_test.py
@@ -28,6 +28,7 @@ from tensorflow.python.platform import test
class TypeCheckTest(test.TestCase):
+ @test_util.run_deprecated_v1
def test_checks(self):
self.assertTrue(type_check.is_tensor(constant_op.constant([1, 2, 3])))
self.assertTrue(
diff --git a/tensorflow/python/client/session_partial_run_test.py b/tensorflow/python/client/session_partial_run_test.py
index a9bd5ab7e08..a97930635af 100644
--- a/tensorflow/python/client/session_partial_run_test.py
+++ b/tensorflow/python/client/session_partial_run_test.py
@@ -188,6 +188,7 @@ class PartialRunTest(test_util.TensorFlowTestCase):
r = sess.partial_run(h, [b], {})
self.assertEqual([6.0], r)
+ @test_util.run_deprecated_v1
def testInvalidPartialRunSetup(self):
sess = session.Session()
x = array_ops.placeholder(dtypes.float32, shape=[])
@@ -196,6 +197,7 @@ class PartialRunTest(test_util.TensorFlowTestCase):
'specify at least one target to fetch or execute.'):
sess.partial_run_setup(fetches=[], feeds=[x])
+ @test_util.run_deprecated_v1
def testPartialRunSetupNoFeedsPassed(self):
sess = session.Session()
r1 = constant_op.constant([6.0])
@@ -204,80 +206,102 @@ class PartialRunTest(test_util.TensorFlowTestCase):
result1 = sess.partial_run(h, r1)
self.assertEqual([6.0], result1)
+ @test_util.run_deprecated_v1
def testPartialRunDirect(self):
self.RunTestPartialRun(session.Session())
+ @test_util.run_deprecated_v1
def testPartialRunIncompleteDirect(self):
self.RunTestPartialRunIncomplete(session.Session())
+ @test_util.run_deprecated_v1
def testConcurrentPartialRunDirect(self):
self.RunTestConcurrentPartialRun(session.Session())
+ @test_util.run_deprecated_v1
def testManyPartialRunDirect(self):
self.RunTestManyPartialRun(session.Session())
+ @test_util.run_deprecated_v1
def testRunAndPartialRunDirect(self):
self.RunTestRunAndPartialRun(session.Session())
+ @test_util.run_deprecated_v1
def testPartialRunMissingPlaceholderFeedExceptionDirect(self):
self.RunTestPartialRunMissingPlaceholderFeedException(session.Session())
+ @test_util.run_deprecated_v1
def testPartialRunUnspecifiedFeedDirect(self):
self.RunTestPartialRunUnspecifiedFeed(session.Session())
+ @test_util.run_deprecated_v1
def testPartialRunUnspecifiedFetchDirect(self):
self.RunTestPartialRunUnspecifiedFetch(session.Session())
+ @test_util.run_deprecated_v1
def testPartialRunAlreadyFedDirect(self):
self.RunTestPartialRunAlreadyFed(session.Session())
+ @test_util.run_deprecated_v1
def testPartialRunAlreadyFetchedDirect(self):
self.RunTestPartialRunAlreadyFetched(session.Session())
+ @test_util.run_deprecated_v1
def testPartialRunEmptyFetchesDirect(self):
self.RunTestPartialRunEmptyFetches(session.Session())
+ @test_util.run_deprecated_v1
def testPartialRunDist(self):
server = server_lib.Server.create_local_server()
self.RunTestPartialRun(session.Session(server.target))
+ @test_util.run_deprecated_v1
def testPartialRunIncompleteDist(self):
server = server_lib.Server.create_local_server()
self.RunTestPartialRunIncomplete(session.Session(server.target))
+ @test_util.run_deprecated_v1
def testConcurrentPartialRunDist(self):
server = server_lib.Server.create_local_server()
self.RunTestConcurrentPartialRun(session.Session(server.target))
+ @test_util.run_deprecated_v1
def testManyPartialRunDist(self):
server = server_lib.Server.create_local_server()
self.RunTestManyPartialRun(session.Session(server.target))
+ @test_util.run_deprecated_v1
def testRunAndPartialRunDist(self):
server = server_lib.Server.create_local_server()
self.RunTestRunAndPartialRun(session.Session(server.target))
+ @test_util.run_deprecated_v1
def testPartialRunMissingPlaceholderFeedExceptionDist(self):
server = server_lib.Server.create_local_server()
self.RunTestPartialRunMissingPlaceholderFeedException(
session.Session(server.target))
+ @test_util.run_deprecated_v1
def testPartialRunUnspecifiedFeedDist(self):
server = server_lib.Server.create_local_server()
self.RunTestPartialRunUnspecifiedFeed(session.Session(server.target))
+ @test_util.run_deprecated_v1
def testPartialRunUnspecifiedFetchDist(self):
server = server_lib.Server.create_local_server()
self.RunTestPartialRunUnspecifiedFetch(session.Session(server.target))
+ @test_util.run_deprecated_v1
def testPartialRunAlreadyFedDist(self):
server = server_lib.Server.create_local_server()
self.RunTestPartialRunAlreadyFed(session.Session(server.target))
+ @test_util.run_deprecated_v1
def testPartialRunAlreadyFetchedDist(self):
server = server_lib.Server.create_local_server()
self.RunTestPartialRunAlreadyFetched(session.Session(server.target))
+ @test_util.run_deprecated_v1
def testPartialRunEmptyFetchesDist(self):
server = server_lib.Server.create_local_server()
self.RunTestPartialRunEmptyFetches(session.Session(server.target))
diff --git a/tensorflow/python/client/timeline_test.py b/tensorflow/python/client/timeline_test.py
index f9bd50957a7..61c0da01b83 100644
--- a/tensorflow/python/client/timeline_test.py
+++ b/tensorflow/python/client/timeline_test.py
@@ -57,6 +57,7 @@ class TimelineTest(test.TestCase):
ctf = tl.generate_chrome_trace_format()
self._validateTrace(ctf)
+ @test_util.run_deprecated_v1
def testTimelineCpu(self):
run_options = config_pb2.RunOptions(
trace_level=config_pb2.RunOptions.FULL_TRACE)
diff --git a/tensorflow/python/data/experimental/kernel_tests/copy_to_device_test.py b/tensorflow/python/data/experimental/kernel_tests/copy_to_device_test.py
index 7edaab81f4c..b0516573f5f 100644
--- a/tensorflow/python/data/experimental/kernel_tests/copy_to_device_test.py
+++ b/tensorflow/python/data/experimental/kernel_tests/copy_to_device_test.py
@@ -35,6 +35,7 @@ from tensorflow.python.util import compat as util_compat
class CopyToDeviceTest(test_base.DatasetTestBase):
+ @test_util.run_deprecated_v1
def testCopyToDevice(self):
host_dataset = dataset_ops.Dataset.range(10)
device_dataset = host_dataset.apply(
@@ -61,6 +62,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element)
+ @test_util.run_deprecated_v1
def testCopyToDeviceInt32(self):
host_dataset = dataset_ops.Dataset.from_tensors([0, 1, 2, 3])
device_dataset = host_dataset.apply(
@@ -86,6 +88,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element)
+ @test_util.run_deprecated_v1
def testCopyToSameDevice(self):
host_dataset = dataset_ops.Dataset.range(10)
device_dataset = host_dataset.apply(
@@ -112,6 +115,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element)
+ @test_util.run_deprecated_v1
def testCopyToDeviceWithPrefetch(self):
host_dataset = dataset_ops.Dataset.range(10)
device_dataset = host_dataset.apply(
@@ -138,6 +142,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element)
+ @test_util.run_deprecated_v1
def testCopyDictToDevice(self):
host_dataset = dataset_ops.Dataset.range(10).map(lambda x: {"a": x})
device_dataset = host_dataset.apply(
@@ -164,6 +169,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element)
+ @test_util.run_deprecated_v1
def testCopyDictToDeviceWithPrefetch(self):
host_dataset = dataset_ops.Dataset.range(10).map(lambda x: {"a": x})
device_dataset = host_dataset.apply(
@@ -190,6 +196,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element)
+ @test_util.run_deprecated_v1
def testCopySparseTensorsToDevice(self):
def make_tensor(i):
@@ -224,6 +231,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element)
+ @test_util.run_deprecated_v1
def testCopySparseTensorsToDeviceWithPrefetch(self):
def make_tensor(i):
@@ -426,6 +434,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element)
+ @test_util.run_deprecated_v1
def testCopyToDeviceWithReInit(self):
host_dataset = dataset_ops.Dataset.range(10)
device_dataset = host_dataset.apply(
@@ -456,6 +465,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element)
+ @test_util.run_deprecated_v1
def testCopyToDeviceWithReInitAndPrefetch(self):
host_dataset = dataset_ops.Dataset.range(10)
device_dataset = host_dataset.apply(
diff --git a/tensorflow/python/data/experimental/kernel_tests/counter_test.py b/tensorflow/python/data/experimental/kernel_tests/counter_test.py
index d1dd07a8794..b370e0029e9 100644
--- a/tensorflow/python/data/experimental/kernel_tests/counter_test.py
+++ b/tensorflow/python/data/experimental/kernel_tests/counter_test.py
@@ -20,11 +20,13 @@ from __future__ import print_function
from tensorflow.python.data.experimental.ops import counter
from tensorflow.python.data.kernel_tests import test_base
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.platform import test
class CounterTest(test_base.DatasetTestBase):
+ @test_util.run_deprecated_v1
def testCounter(self):
"""Test dataset construction using `count`."""
iterator = (counter.Counter(start=3, step=4)
diff --git a/tensorflow/python/data/experimental/kernel_tests/dense_to_sparse_batch_test.py b/tensorflow/python/data/experimental/kernel_tests/dense_to_sparse_batch_test.py
index d9bbfb9c994..4b84446be8a 100644
--- a/tensorflow/python/data/experimental/kernel_tests/dense_to_sparse_batch_test.py
+++ b/tensorflow/python/data/experimental/kernel_tests/dense_to_sparse_batch_test.py
@@ -24,12 +24,14 @@ from tensorflow.python.data.kernel_tests import test_base
from tensorflow.python.data.ops import dataset_ops
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.platform import test
class DenseToSparseBatchTest(test_base.DatasetTestBase):
+ @test_util.run_deprecated_v1
def testDenseToSparseBatchDataset(self):
components = np.random.randint(12, size=(100,)).astype(np.int32)
iterator = (
@@ -58,6 +60,7 @@ class DenseToSparseBatchTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(get_next)
+ @test_util.run_deprecated_v1
def testDenseToSparseBatchDatasetWithUnknownShape(self):
components = np.random.randint(5, size=(40,)).astype(np.int32)
iterator = (
@@ -91,12 +94,14 @@ class DenseToSparseBatchTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(get_next)
+ @test_util.run_deprecated_v1
def testDenseToSparseBatchDatasetWithInvalidShape(self):
input_tensor = array_ops.constant([[1]])
with self.assertRaisesRegexp(ValueError, "Dimension -2 must be >= 0"):
dataset_ops.Dataset.from_tensors(input_tensor).apply(
batching.dense_to_sparse_batch(4, [-2])).make_initializable_iterator()
+ @test_util.run_deprecated_v1
def testDenseToSparseBatchDatasetShapeErrors(self):
input_tensor = array_ops.placeholder(dtypes.int32)
iterator = (
diff --git a/tensorflow/python/data/experimental/kernel_tests/directed_interleave_dataset_test.py b/tensorflow/python/data/experimental/kernel_tests/directed_interleave_dataset_test.py
index 768a8d774b1..269c27dde29 100644
--- a/tensorflow/python/data/experimental/kernel_tests/directed_interleave_dataset_test.py
+++ b/tensorflow/python/data/experimental/kernel_tests/directed_interleave_dataset_test.py
@@ -24,11 +24,13 @@ from tensorflow.python.data.kernel_tests import test_base
from tensorflow.python.data.ops import dataset_ops
from tensorflow.python.framework import errors
from tensorflow.python.framework import random_seed
+from tensorflow.python.framework import test_util
from tensorflow.python.platform import test
class DirectedInterleaveDatasetTest(test_base.DatasetTestBase):
+ @test_util.run_deprecated_v1
def testBasic(self):
selector_dataset = dataset_ops.Dataset.range(10).repeat(100)
input_datasets = [
@@ -77,6 +79,7 @@ class DirectedInterleaveDatasetTest(test_base.DatasetTestBase):
return freqs
+ @test_util.run_deprecated_v1
def testSampleFromDatasets(self):
random_seed.set_random_seed(1619)
num_samples = 5000
@@ -96,6 +99,7 @@ class DirectedInterleaveDatasetTest(test_base.DatasetTestBase):
freqs = self._testSampleFromDatasetsHelper(probs_ds, classes, num_samples)
self.assertLess(self._chi2(probs, freqs / num_samples), 1e-2)
+ @test_util.run_deprecated_v1
def testSelectFromDatasets(self):
words = [b"foo", b"bar", b"baz"]
datasets = [dataset_ops.Dataset.from_tensors(w).repeat() for w in words]
diff --git a/tensorflow/python/data/experimental/kernel_tests/enumerate_dataset_test.py b/tensorflow/python/data/experimental/kernel_tests/enumerate_dataset_test.py
index f32d1d0a6fc..3c2e1bb7f3d 100644
--- a/tensorflow/python/data/experimental/kernel_tests/enumerate_dataset_test.py
+++ b/tensorflow/python/data/experimental/kernel_tests/enumerate_dataset_test.py
@@ -24,11 +24,13 @@ from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors
from tensorflow.python.framework import tensor_shape
+from tensorflow.python.framework import test_util
from tensorflow.python.platform import test
class EnumerateDatasetTest(test_base.DatasetTestBase):
+ @test_util.run_deprecated_v1
def testEnumerateDataset(self):
components = (["a", "b"], [1, 2], [37.0, 38])
start = constant_op.constant(20, dtype=dtypes.int64)
diff --git a/tensorflow/python/data/experimental/kernel_tests/function_buffering_resource_test.py b/tensorflow/python/data/experimental/kernel_tests/function_buffering_resource_test.py
index 860442571eb..a78fb4d229d 100644
--- a/tensorflow/python/data/experimental/kernel_tests/function_buffering_resource_test.py
+++ b/tensorflow/python/data/experimental/kernel_tests/function_buffering_resource_test.py
@@ -107,11 +107,13 @@ class FunctionBufferingResourceTest(test_base.DatasetTestBase):
self.assertEqual(elem, [5.0])
self.evaluate(destroy_op)
+ @test_util.run_deprecated_v1
def testSameDeviceCPU(self):
self._prefetch_fn_helper_one_shot("same_device_cpu",
"/job:localhost/replica:0/task:0/cpu:0",
"/job:localhost/replica:0/task:0/cpu:0")
+ @test_util.run_deprecated_v1
def testDifferentDeviceCPU(self):
self._prefetch_fn_helper_one_shot("diff_device_cpu",
"/job:localhost/replica:0/task:0/cpu:0",
@@ -125,6 +127,7 @@ class FunctionBufferingResourceTest(test_base.DatasetTestBase):
"/job:localhost/replica:0/task:0/cpu:0",
"/job:localhost/replica:0/task:0/gpu:0")
+ @test_util.run_deprecated_v1
def testReinitialization(self):
worker_config = config_pb2.ConfigProto(device_count={"CPU": 2})
@@ -165,6 +168,7 @@ class FunctionBufferingResourceTest(test_base.DatasetTestBase):
self.assertEqual(elem, [5.0])
self.evaluate(destroy_op)
+ @test_util.run_deprecated_v1
def testReinitializationOutOfRange(self):
worker_config = config_pb2.ConfigProto(device_count={"CPU": 2})
diff --git a/tensorflow/python/data/experimental/kernel_tests/get_single_element_test.py b/tensorflow/python/data/experimental/kernel_tests/get_single_element_test.py
index 0147988c595..ef576563a15 100644
--- a/tensorflow/python/data/experimental/kernel_tests/get_single_element_test.py
+++ b/tensorflow/python/data/experimental/kernel_tests/get_single_element_test.py
@@ -25,6 +25,7 @@ from tensorflow.python.data.ops import dataset_ops
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors
from tensorflow.python.framework import sparse_tensor
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.platform import test
@@ -39,6 +40,7 @@ class GetSingleElementTest(test_base.DatasetTestBase, parameterized.TestCase):
("MoreThanOne", 0, 2, errors.InvalidArgumentError,
"Dataset had more than one element."),
)
+ @test_util.run_deprecated_v1
def testGetSingleElement(self, skip, take, error=None, error_msg=None):
skip_t = array_ops.placeholder(dtypes.int64, shape=[])
take_t = array_ops.placeholder(dtypes.int64, shape=[])
diff --git a/tensorflow/python/data/experimental/kernel_tests/group_by_reducer_test.py b/tensorflow/python/data/experimental/kernel_tests/group_by_reducer_test.py
index f9856500c5c..c7366f66411 100644
--- a/tensorflow/python/data/experimental/kernel_tests/group_by_reducer_test.py
+++ b/tensorflow/python/data/experimental/kernel_tests/group_by_reducer_test.py
@@ -27,6 +27,7 @@ from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors
from tensorflow.python.framework import sparse_tensor
from tensorflow.python.framework import tensor_shape
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.platform import test
@@ -44,6 +45,7 @@ class GroupByReducerTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(get_next)
+ @test_util.run_deprecated_v1
def testSum(self):
reducer = grouping.Reducer(
init_func=lambda _: np.int64(0),
@@ -55,6 +57,7 @@ class GroupByReducerTest(test_base.DatasetTestBase):
self.checkResults(
dataset, shapes=tensor_shape.scalar(), values=[(i - 1) * i, i * i])
+ @test_util.run_deprecated_v1
def testAverage(self):
def reduce_fn(x, y):
@@ -72,6 +75,7 @@ class GroupByReducerTest(test_base.DatasetTestBase):
self.checkResults(
dataset, shapes=tensor_shape.scalar(), values=[i - 1, i])
+ @test_util.run_deprecated_v1
def testConcat(self):
components = np.array(list("abcdefghijklmnopqrst")).view(np.chararray)
reducer = grouping.Reducer(
@@ -88,6 +92,7 @@ class GroupByReducerTest(test_base.DatasetTestBase):
shapes=tensor_shape.scalar(),
values=[b"acegikmoqs" [:i], b"bdfhjlnprt" [:i]])
+ @test_util.run_deprecated_v1
def testSparseSum(self):
def _sparse(i):
return sparse_tensor.SparseTensorValue(
@@ -105,6 +110,7 @@ class GroupByReducerTest(test_base.DatasetTestBase):
self.checkResults(
dataset, shapes=tensor_shape.scalar(), values=[(i - 1) * i, i * i])
+ @test_util.run_deprecated_v1
def testChangingStateShape(self):
def reduce_fn(x, _):
diff --git a/tensorflow/python/data/experimental/kernel_tests/group_by_window_test.py b/tensorflow/python/data/experimental/kernel_tests/group_by_window_test.py
index d5a36e7cb15..1e54091c7db 100644
--- a/tensorflow/python/data/experimental/kernel_tests/group_by_window_test.py
+++ b/tensorflow/python/data/experimental/kernel_tests/group_by_window_test.py
@@ -27,6 +27,7 @@ from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors
from tensorflow.python.framework import ops
from tensorflow.python.framework import tensor_shape
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import string_ops
@@ -49,6 +50,7 @@ class GroupByWindowTest(test_base.DatasetTestBase):
32, (tensor_shape.TensorShape([]), tensor_shape.TensorShape(
[None]), tensor_shape.TensorShape([3])))))
+ @test_util.run_deprecated_v1
def testSingleBucket(self):
def _map_fn(v):
@@ -84,6 +86,7 @@ class GroupByWindowTest(test_base.DatasetTestBase):
self.assertAllEqual(expected_unk_int64, bucketed_values[1])
self.assertAllEqual(expected_vec3_str, bucketed_values[2])
+ @test_util.run_deprecated_v1
def testEvenOddBuckets(self):
def _map_fn(v):
@@ -141,6 +144,7 @@ class GroupByWindowTest(test_base.DatasetTestBase):
self.assertAllEqual(expected_unk_int64, bucketed_values_odd[1])
self.assertAllEqual(expected_vec3_str, bucketed_values_odd[2])
+ @test_util.run_deprecated_v1
def testEvenOddBucketsFilterOutAllOdd(self):
def _map_fn(v):
@@ -188,6 +192,7 @@ class GroupByWindowTest(test_base.DatasetTestBase):
self.assertAllEqual(
np.arange(64, 128, 2, dtype=np.int64), bucketed_values_even1["x"])
+ @test_util.run_deprecated_v1
def testDynamicWindowSize(self):
components = np.arange(100).astype(np.int64)
@@ -221,6 +226,7 @@ class GroupByWindowTest(test_base.DatasetTestBase):
self.assertEqual(batches, 15)
+ @test_util.run_deprecated_v1
def testSimple(self):
components = np.random.randint(100, size=(200,)).astype(np.int64)
iterator = (
@@ -248,6 +254,7 @@ class GroupByWindowTest(test_base.DatasetTestBase):
self.assertGreaterEqual(num_full_batches, 24)
self.assertTrue(all(c == 4 for c in counts[:num_full_batches]))
+ @test_util.run_deprecated_v1
def testImmediateOutput(self):
components = np.array(
[0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 0, 0, 2, 2, 0, 0], dtype=np.int64)
@@ -270,6 +277,7 @@ class GroupByWindowTest(test_base.DatasetTestBase):
self.assertAllEqual([2, 2, 2, 2], self.evaluate(get_next))
self.assertAllEqual([0, 0, 0, 0], self.evaluate(get_next))
+ @test_util.run_deprecated_v1
def testSmallGroups(self):
components = np.array([0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0], dtype=np.int64)
iterator = (
@@ -288,6 +296,7 @@ class GroupByWindowTest(test_base.DatasetTestBase):
self.assertAllEqual([0, 0, 0], self.evaluate(get_next))
self.assertAllEqual([1], self.evaluate(get_next))
+ @test_util.run_deprecated_v1
def testEmpty(self):
iterator = (
dataset_ops.Dataset.range(4).apply(
@@ -303,6 +312,7 @@ class GroupByWindowTest(test_base.DatasetTestBase):
"Window size must be greater than zero, but got 0."):
print(self.evaluate(get_next))
+ @test_util.run_deprecated_v1
def testReduceFuncError(self):
components = np.random.randint(100, size=(200,)).astype(np.int64)
@@ -327,6 +337,7 @@ class GroupByWindowTest(test_base.DatasetTestBase):
with self.assertRaises(errors.InvalidArgumentError):
self.evaluate(get_next)
+ @test_util.run_deprecated_v1
def testConsumeWindowDatasetMoreThanOnce(self):
components = np.random.randint(50, size=(200,)).astype(np.int64)
diff --git a/tensorflow/python/data/experimental/kernel_tests/ignore_errors_test.py b/tensorflow/python/data/experimental/kernel_tests/ignore_errors_test.py
index 522b1960606..bd323592e44 100644
--- a/tensorflow/python/data/experimental/kernel_tests/ignore_errors_test.py
+++ b/tensorflow/python/data/experimental/kernel_tests/ignore_errors_test.py
@@ -25,6 +25,7 @@ from tensorflow.python.data.experimental.ops import error_ops
from tensorflow.python.data.kernel_tests import test_base
from tensorflow.python.data.ops import dataset_ops
from tensorflow.python.framework import errors
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import io_ops
from tensorflow.python.platform import test
@@ -35,6 +36,7 @@ _NUMPY_RANDOM_SEED = 42
class IgnoreErrorsTest(test_base.DatasetTestBase):
+ @test_util.run_deprecated_v1
def testMapIgnoreError(self):
components = np.array([1., 2., 3., np.nan, 5.]).astype(np.float32)
@@ -53,6 +55,7 @@ class IgnoreErrorsTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(get_next)
+ @test_util.run_deprecated_v1
def testParallelMapIgnoreError(self):
components = np.array([1., 2., 3., np.nan, 5.]).astype(np.float32)
@@ -71,6 +74,7 @@ class IgnoreErrorsTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(get_next)
+ @test_util.run_deprecated_v1
def testReadFileIgnoreError(self):
def write_string_to_file(value, filename):
diff --git a/tensorflow/python/data/experimental/kernel_tests/indexed_dataset_ops_test.py b/tensorflow/python/data/experimental/kernel_tests/indexed_dataset_ops_test.py
index 0a436034a8c..c3c4ccd0770 100644
--- a/tensorflow/python/data/experimental/kernel_tests/indexed_dataset_ops_test.py
+++ b/tensorflow/python/data/experimental/kernel_tests/indexed_dataset_ops_test.py
@@ -24,6 +24,7 @@ from tensorflow.python.data.kernel_tests import test_base
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gen_experimental_dataset_ops as ged_ops
from tensorflow.python.platform import test
@@ -31,6 +32,7 @@ from tensorflow.python.platform import test
class IndexedDatasetOpsTest(test_base.DatasetTestBase):
+ @test_util.run_deprecated_v1
def testLowLevelIndexedDatasetOps(self):
identity = ged_ops.experimental_identity_indexed_dataset(
ops.convert_to_tensor(16, dtype=dtypes.uint64))
@@ -49,6 +51,7 @@ class IndexedDatasetOpsTest(test_base.DatasetTestBase):
self.evaluate(materialize)
self.assertEqual([3], sess.run(get_op, feed_dict={index: 3}))
+ @test_util.run_deprecated_v1
def testIdentityIndexedDataset(self):
ds = indexed_dataset_ops.IdentityIndexedDataset(16)
materialized = ds.materialize()
diff --git a/tensorflow/python/data/experimental/kernel_tests/make_batched_features_dataset_test.py b/tensorflow/python/data/experimental/kernel_tests/make_batched_features_dataset_test.py
index 109b3696b84..48916471b35 100644
--- a/tensorflow/python/data/experimental/kernel_tests/make_batched_features_dataset_test.py
+++ b/tensorflow/python/data/experimental/kernel_tests/make_batched_features_dataset_test.py
@@ -26,6 +26,7 @@ from tensorflow.python.data.util import nest
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import io_ops
from tensorflow.python.ops import parsing_ops
from tensorflow.python.platform import test
@@ -98,6 +99,7 @@ class MakeBatchedFeaturesDatasetTest(
with self.assertRaises(errors.OutOfRangeError):
self._next_actual_batch(sess)
+ @test_util.run_deprecated_v1
def testReadWithEquivalentDataset(self):
features = {
"file": parsing_ops.FixedLenFeature([], dtypes.int64),
diff --git a/tensorflow/python/data/experimental/kernel_tests/make_csv_dataset_test.py b/tensorflow/python/data/experimental/kernel_tests/make_csv_dataset_test.py
index 1f509384d72..bcbaf1a7c49 100644
--- a/tensorflow/python/data/experimental/kernel_tests/make_csv_dataset_test.py
+++ b/tensorflow/python/data/experimental/kernel_tests/make_csv_dataset_test.py
@@ -30,6 +30,7 @@ from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.platform import test
@@ -127,6 +128,7 @@ class MakeCsvDatasetTest(test_base.DatasetTestBase):
self._verify_output(sess, dataset, batch_size, num_epochs, label_name,
expected_output, expected_keys)
+ @test_util.run_deprecated_v1
def testMakeCSVDataset(self):
"""Tests making a CSV dataset with keys and defaults provided."""
record_defaults = [
@@ -158,6 +160,7 @@ class MakeCsvDatasetTest(test_base.DatasetTestBase):
column_defaults=record_defaults,
)
+ @test_util.run_deprecated_v1
def testMakeCSVDataset_withBatchSizeAndEpochs(self):
"""Tests making a CSV dataset with keys and defaults provided."""
record_defaults = [
@@ -189,6 +192,7 @@ class MakeCsvDatasetTest(test_base.DatasetTestBase):
column_defaults=record_defaults,
)
+ @test_util.run_deprecated_v1
def testMakeCSVDataset_withCompressionType(self):
"""Tests `compression_type` argument."""
record_defaults = [
@@ -257,6 +261,7 @@ class MakeCsvDatasetTest(test_base.DatasetTestBase):
label_name="not_a_real_label",
column_names=column_names)
+ @test_util.run_deprecated_v1
def testMakeCSVDataset_withNoLabel(self):
"""Tests making a CSV dataset with no label provided."""
record_defaults = [
@@ -286,6 +291,7 @@ class MakeCsvDatasetTest(test_base.DatasetTestBase):
column_defaults=record_defaults,
)
+ @test_util.run_deprecated_v1
def testMakeCSVDataset_withNoHeader(self):
"""Tests that datasets can be created from CSV files with no header line.
"""
@@ -347,6 +353,7 @@ class MakeCsvDatasetTest(test_base.DatasetTestBase):
column_defaults=record_defaults,
)
+ @test_util.run_deprecated_v1
def testMakeCSVDataset_withNoColNames(self):
"""Tests that datasets can be created when column names are not specified.
@@ -451,6 +458,7 @@ class MakeCsvDatasetTest(test_base.DatasetTestBase):
header=True,
)
+ @test_util.run_deprecated_v1
def testMakeCSVDataset_withSelectCols(self):
record_defaults = [
constant_op.constant([], dtypes.int32),
@@ -557,6 +565,7 @@ class MakeCsvDatasetTest(test_base.DatasetTestBase):
label_name=None,
select_columns=["invalid_col_name"])
+ @test_util.run_deprecated_v1
def testMakeCSVDataset_withShuffle(self):
record_defaults = [
constant_op.constant([], dtypes.int32),
diff --git a/tensorflow/python/data/experimental/kernel_tests/map_and_batch_test.py b/tensorflow/python/data/experimental/kernel_tests/map_and_batch_test.py
index 8449c0651de..fc97f63358a 100644
--- a/tensorflow/python/data/experimental/kernel_tests/map_and_batch_test.py
+++ b/tensorflow/python/data/experimental/kernel_tests/map_and_batch_test.py
@@ -29,6 +29,7 @@ from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors
from tensorflow.python.framework import sparse_tensor
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import control_flow_ops
from tensorflow.python.ops import math_ops
@@ -48,6 +49,7 @@ class MapAndBatchTest(test_base.DatasetTestBase, parameterized.TestCase):
("ParallelCallsNUMA", 2, None, True),
("ParallelBatchesNUMA", None, 10, True),
)
+ @test_util.run_deprecated_v1
def testMapAndBatch(self, num_parallel_calls, num_parallel_batches,
numa_aware):
"""Test a dataset that maps a TF function across its input elements."""
@@ -132,6 +134,7 @@ class MapAndBatchTest(test_base.DatasetTestBase, parameterized.TestCase):
("EvenNUMA", False, True),
("UnevenNUMA", True, True),
)
+ @test_util.run_deprecated_v1
def testMapAndBatchPartialBatch(self, drop_remainder, numa_aware):
dataset = (
dataset_ops.Dataset.range(10).apply(
@@ -163,6 +166,7 @@ class MapAndBatchTest(test_base.DatasetTestBase, parameterized.TestCase):
("Normal", False),
("NUMA", True),
)
+ @test_util.run_deprecated_v1
def testMapAndBatchYieldsPartialBatch(self, numa_aware):
dataset = (
dataset_ops.Dataset.range(10).apply(
@@ -187,6 +191,7 @@ class MapAndBatchTest(test_base.DatasetTestBase, parameterized.TestCase):
("Normal", False),
("NUMA", True),
)
+ @test_util.run_deprecated_v1
def testMapAndBatchParallelGetNext(self, numa_aware):
dataset = dataset_ops.Dataset.range(50000).apply(
batching.map_and_batch(lambda x: x, batch_size=100))
@@ -214,6 +219,7 @@ class MapAndBatchTest(test_base.DatasetTestBase, parameterized.TestCase):
("Normal", False),
("NUMA", True),
)
+ @test_util.run_deprecated_v1
def testMapAndBatchParallelGetNextDropRemainder(self, numa_aware):
dataset = dataset_ops.Dataset.range(49999).apply(
batching.map_and_batch(
@@ -243,6 +249,7 @@ class MapAndBatchTest(test_base.DatasetTestBase, parameterized.TestCase):
("Normal", False),
("NUMA", True),
)
+ @test_util.run_deprecated_v1
def testMapAndBatchSparse(self, numa_aware):
def _sparse(i):
@@ -277,6 +284,7 @@ class MapAndBatchTest(test_base.DatasetTestBase, parameterized.TestCase):
("Normal", False),
("NUMA", True),
)
+ @test_util.run_deprecated_v1
def testMapAndBatchFails(self, numa_aware):
"""Test a dataset that maps a TF function across its input elements."""
dataset = dataset_ops.Dataset.from_tensors(
@@ -299,6 +307,7 @@ class MapAndBatchTest(test_base.DatasetTestBase, parameterized.TestCase):
("Normal", False),
("NUMA", True),
)
+ @test_util.run_deprecated_v1
def testMapAndBatchShapeMismatch(self, numa_aware):
"""Test a dataset that maps a TF function across its input elements."""
@@ -370,6 +379,7 @@ class MapAndBatchTest(test_base.DatasetTestBase, parameterized.TestCase):
("5NUMA", 95, True),
("6NUMA", 99, True),
)
+ @test_util.run_deprecated_v1
def testMapAndBatchOutOfRangeError(self, threshold, numa_aware):
def raising_py_fn(i):
@@ -452,6 +462,7 @@ class MapAndBatchTest(test_base.DatasetTestBase, parameterized.TestCase):
("Swap", (None, None), lambda x, y: (y, x), None),
("Project", (None, None), lambda x, y: x, None),
)
+ @test_util.run_deprecated_v1
def testShortCircuit(self, structure, map_fn, num_parallel_calls):
dataset = self.structuredDataset(structure).repeat().apply(
batching.map_and_batch(map_fn, batch_size=10))
@@ -466,6 +477,7 @@ class MapAndBatchTest(test_base.DatasetTestBase, parameterized.TestCase):
sess.run(self.structuredElement(structure, shape=[10])))
self.assertAllEqual(expected, self.evaluate(get_next))
+ @test_util.run_deprecated_v1
def testShortCircuitCapturedInput(self):
captured_t = array_ops.placeholder(dtypes.int64, shape=[])
dataset = self.structuredDataset(None).repeat().apply(
@@ -481,6 +493,7 @@ class MapAndBatchTest(test_base.DatasetTestBase, parameterized.TestCase):
("Normal", False),
("NUMA", True),
)
+ @test_util.run_deprecated_v1
def testMapAndBatchControlFlow(self, numa_aware):
def map_fn(x):
diff --git a/tensorflow/python/data/experimental/kernel_tests/matching_files_test.py b/tensorflow/python/data/experimental/kernel_tests/matching_files_test.py
index 938dd4aff4a..787a7a91a4b 100644
--- a/tensorflow/python/data/experimental/kernel_tests/matching_files_test.py
+++ b/tensorflow/python/data/experimental/kernel_tests/matching_files_test.py
@@ -24,6 +24,7 @@ import tempfile
from tensorflow.python.data.experimental.ops import matching_files
from tensorflow.python.data.kernel_tests import test_base
from tensorflow.python.framework import errors
+from tensorflow.python.framework import test_util
from tensorflow.python.platform import test
from tensorflow.python.util import compat
@@ -40,6 +41,7 @@ class MatchingFilesTest(test_base.DatasetTestBase):
for filename in filenames:
open(os.path.join(self.tmp_dir, filename), 'a').close()
+ @test_util.run_deprecated_v1
def testNonExistingDirectory(self):
"""Test the MatchingFiles dataset with a non-existing directory."""
@@ -51,6 +53,7 @@ class MatchingFilesTest(test_base.DatasetTestBase):
with self.assertRaises(errors.NotFoundError):
sess.run(next_element)
+ @test_util.run_deprecated_v1
def testEmptyDirectory(self):
"""Test the MatchingFiles dataset with an empty directory."""
@@ -61,6 +64,7 @@ class MatchingFilesTest(test_base.DatasetTestBase):
with self.assertRaises(errors.NotFoundError):
sess.run(next_element)
+ @test_util.run_deprecated_v1
def testSimpleDirectory(self):
"""Test the MatchingFiles dataset with a simple directory."""
@@ -83,6 +87,7 @@ class MatchingFilesTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
sess.run(next_element)
+ @test_util.run_deprecated_v1
def testFileSuffixes(self):
"""Test the MatchingFiles dataset using the suffixes of filename."""
@@ -104,6 +109,7 @@ class MatchingFilesTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
sess.run(next_element)
+ @test_util.run_deprecated_v1
def testFileMiddles(self):
"""Test the MatchingFiles dataset using the middles of filename."""
@@ -125,6 +131,7 @@ class MatchingFilesTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
sess.run(next_element)
+ @test_util.run_deprecated_v1
def testNestedDirectories(self):
"""Test the MatchingFiles dataset with nested directories."""
diff --git a/tensorflow/python/data/experimental/kernel_tests/override_threadpool_test.py b/tensorflow/python/data/experimental/kernel_tests/override_threadpool_test.py
index 1dfe854f188..7116e7549f9 100644
--- a/tensorflow/python/data/experimental/kernel_tests/override_threadpool_test.py
+++ b/tensorflow/python/data/experimental/kernel_tests/override_threadpool_test.py
@@ -29,6 +29,7 @@ from tensorflow.python.data.kernel_tests import test_base
from tensorflow.python.data.ops import dataset_ops
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import script_ops
from tensorflow.python.platform import test
@@ -81,6 +82,7 @@ class OverrideThreadpoolTest(test_base.DatasetTestBase,
("8", 4, 1),
("9", 4, 4),
)
+ @test_util.run_deprecated_v1
def testNumThreadsDeprecated(self, num_threads, max_intra_op_parallelism):
def override_threadpool_fn(dataset):
@@ -107,6 +109,7 @@ class OverrideThreadpoolTest(test_base.DatasetTestBase,
("11", 4, 4),
("12", None, None),
)
+ @test_util.run_deprecated_v1
def testNumThreads(self, num_threads, max_intra_op_parallelism):
def override_threadpool_fn(dataset):
diff --git a/tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py b/tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py
index c74f754fefb..76e0d4d72a6 100644
--- a/tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py
+++ b/tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py
@@ -144,6 +144,7 @@ class ParseExampleDatasetTest(test_base.DatasetTestBase):
expected_values=expected_output,
create_iterator_twice=True)
+ @test_util.run_deprecated_v1
def testEmptySerializedWithoutDefaultsShouldFail(self):
input_features = {
"st_a":
@@ -177,6 +178,7 @@ class ParseExampleDatasetTest(test_base.DatasetTestBase):
expected_err=(errors_impl.InvalidArgumentError,
"Feature: c \\(data type: float\\) is required"))
+ @test_util.run_deprecated_v1
def testDenseNotMatchingShapeShouldFail(self):
original = [
example(features=features({
@@ -669,6 +671,7 @@ class ParseExampleDatasetTest(test_base.DatasetTestBase):
for batch_size in (1, 10, 20, 100, 256):
self._testSerializedContainingVarLenDenseLargerBatch(batch_size)
+ @test_util.run_deprecated_v1
def testSkipEagerSerializedShapeMismatch(self):
aname = "a"
bname = "b"
@@ -706,6 +709,7 @@ class ParseExampleDatasetTest(test_base.DatasetTestBase):
expected_err=(ValueError,
"Cannot reshape a tensor with 0 elements to shape"))
+ @test_util.run_deprecated_v1
def testSerializedContainingVarLenDense(self):
aname = "a"
bname = "b"
diff --git a/tensorflow/python/data/experimental/kernel_tests/prefetch_to_device_test.py b/tensorflow/python/data/experimental/kernel_tests/prefetch_to_device_test.py
index 8fc18e1ccd3..56befc9e7dc 100644
--- a/tensorflow/python/data/experimental/kernel_tests/prefetch_to_device_test.py
+++ b/tensorflow/python/data/experimental/kernel_tests/prefetch_to_device_test.py
@@ -31,6 +31,7 @@ from tensorflow.python.platform import test
class PrefetchToDeviceTest(test_base.DatasetTestBase):
+ @test_util.run_deprecated_v1
def testPrefetchToDevice(self):
host_dataset = dataset_ops.Dataset.range(10)
device_dataset = host_dataset.apply(
@@ -61,6 +62,7 @@ class PrefetchToDeviceTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element)
+ @test_util.run_deprecated_v1
def testPrefetchToSameDevice(self):
host_dataset = dataset_ops.Dataset.range(10)
device_dataset = host_dataset.apply(
@@ -91,6 +93,7 @@ class PrefetchToDeviceTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element)
+ @test_util.run_deprecated_v1
def testPrefetchDictToDevice(self):
host_dataset = dataset_ops.Dataset.range(10).map(lambda x: {"a": x})
device_dataset = host_dataset.apply(
@@ -121,6 +124,7 @@ class PrefetchToDeviceTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element)
+ @test_util.run_deprecated_v1
def testPrefetchSparseTensorsToDevice(self):
def make_tensor(i):
return sparse_tensor.SparseTensorValue(
@@ -174,6 +178,7 @@ class PrefetchToDeviceTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element)
+ @test_util.run_deprecated_v1
def testPrefetchToDeviceWithReInit(self):
host_dataset = dataset_ops.Dataset.range(10)
device_dataset = host_dataset.apply(
diff --git a/tensorflow/python/data/experimental/kernel_tests/rejection_resample_test.py b/tensorflow/python/data/experimental/kernel_tests/rejection_resample_test.py
index 4c879dbae68..675209d1899 100644
--- a/tensorflow/python/data/experimental/kernel_tests/rejection_resample_test.py
+++ b/tensorflow/python/data/experimental/kernel_tests/rejection_resample_test.py
@@ -28,6 +28,7 @@ from tensorflow.python.data.kernel_tests import test_base
from tensorflow.python.data.ops import dataset_ops
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import random_ops
from tensorflow.python.ops import string_ops
@@ -63,6 +64,7 @@ class RejectionResampleTest(test_base.DatasetTestBase, parameterized.TestCase):
@parameterized.named_parameters(
("InitialDistributionKnown", True),
("InitialDistributionUnknown", False))
+ @test_util.run_deprecated_v1
def testDistribution(self, initial_known):
classes = np.random.randint(5, size=(20000,)) # Uniformly sampled
target_dist = [0.9, 0.05, 0.05, 0.0, 0.0]
@@ -97,6 +99,7 @@ class RejectionResampleTest(test_base.DatasetTestBase, parameterized.TestCase):
@parameterized.named_parameters(
("OnlyInitial", True),
("NotInitial", False))
+ @test_util.run_deprecated_v1
def testEdgeCasesSampleFromInitialDataset(self, only_initial_dist):
init_dist = [0.5, 0.5]
target_dist = [0.5, 0.5] if only_initial_dist else [0.0, 1.0]
@@ -122,6 +125,7 @@ class RejectionResampleTest(test_base.DatasetTestBase, parameterized.TestCase):
while True:
returned.append(sess.run(get_next))
+ @test_util.run_deprecated_v1
def testRandomClasses(self):
init_dist = [0.25, 0.25, 0.25, 0.25]
target_dist = [0.0, 0.0, 0.0, 1.0]
diff --git a/tensorflow/python/data/experimental/kernel_tests/restructured_dataset_test.py b/tensorflow/python/data/experimental/kernel_tests/restructured_dataset_test.py
index 516e489d043..658e6120cf9 100644
--- a/tensorflow/python/data/experimental/kernel_tests/restructured_dataset_test.py
+++ b/tensorflow/python/data/experimental/kernel_tests/restructured_dataset_test.py
@@ -22,12 +22,14 @@ from tensorflow.python.data.kernel_tests import test_base
from tensorflow.python.data.ops import dataset_ops
from tensorflow.python.data.util import nest
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.platform import test
class RestructuredDatasetTest(test_base.DatasetTestBase):
+ @test_util.run_deprecated_v1
def testRestructureDataset(self):
components = (array_ops.placeholder(dtypes.int32),
(array_ops.placeholder(dtypes.int32, shape=[None]),
diff --git a/tensorflow/python/data/experimental/kernel_tests/scan_test.py b/tensorflow/python/data/experimental/kernel_tests/scan_test.py
index dc8a7bca270..43a765b9e02 100644
--- a/tensorflow/python/data/experimental/kernel_tests/scan_test.py
+++ b/tensorflow/python/data/experimental/kernel_tests/scan_test.py
@@ -40,6 +40,7 @@ class ScanTest(test_base.DatasetTestBase):
return dataset_ops.Dataset.from_tensors(0).repeat().apply(
scan_ops.scan(start, scan_fn))
+ @test_util.run_deprecated_v1
def testCount(self):
def make_scan_fn(step):
return lambda state, _: (state + step, state)
@@ -83,6 +84,7 @@ class ScanTest(test_base.DatasetTestBase):
self.assertEqual(5, self.evaluate(next_element()))
self.assertEqual(8, self.evaluate(next_element()))
+ @test_util.run_deprecated_v1
def testSparseCount(self):
def _sparse(i):
return sparse_tensor.SparseTensorValue(
@@ -114,6 +116,7 @@ class ScanTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element)
+ @test_util.run_deprecated_v1
def testChangingStateShape(self):
# Test the fixed-point shape invariant calculations: start with
# initial values with known shapes, and use a scan function that
diff --git a/tensorflow/python/data/experimental/kernel_tests/serialization/checkpoint_input_pipeline_hook_test.py b/tensorflow/python/data/experimental/kernel_tests/serialization/checkpoint_input_pipeline_hook_test.py
index 94393d6d4ba..140ed517ef5 100644
--- a/tensorflow/python/data/experimental/kernel_tests/serialization/checkpoint_input_pipeline_hook_test.py
+++ b/tensorflow/python/data/experimental/kernel_tests/serialization/checkpoint_input_pipeline_hook_test.py
@@ -26,6 +26,7 @@ from tensorflow.python.estimator import model_fn
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import control_flow_ops
from tensorflow.python.ops import variables
from tensorflow.python.platform import test
@@ -68,6 +69,7 @@ class CheckpointInputPipelineHookTest(test_base.DatasetTestBase):
def _build_iterator_saver_hook(self, est):
return iterator_ops.CheckpointInputPipelineHook(est)
+ @test_util.run_deprecated_v1
def testReturnDatasetFromInputFn(self):
def _input_fn():
@@ -80,6 +82,7 @@ class CheckpointInputPipelineHookTest(test_base.DatasetTestBase):
est.train(_input_fn, steps=2, hooks=[self._build_iterator_saver_hook(est)])
self.assertSequenceEqual(self._read_vars(est.model_dir), (4, 3))
+ @test_util.run_deprecated_v1
def testBuildIteratorInInputFn(self):
def _input_fn():
@@ -94,6 +97,7 @@ class CheckpointInputPipelineHookTest(test_base.DatasetTestBase):
est.train(_input_fn, steps=2, hooks=[self._build_iterator_saver_hook(est)])
self.assertSequenceEqual(self._read_vars(est.model_dir), (4, 3))
+ @test_util.run_deprecated_v1
def testDoNotRestore(self):
def _input_fn():
diff --git a/tensorflow/python/data/experimental/kernel_tests/shuffle_and_repeat_test.py b/tensorflow/python/data/experimental/kernel_tests/shuffle_and_repeat_test.py
index 2e8b93feaf0..ce63da6bf98 100644
--- a/tensorflow/python/data/experimental/kernel_tests/shuffle_and_repeat_test.py
+++ b/tensorflow/python/data/experimental/kernel_tests/shuffle_and_repeat_test.py
@@ -24,6 +24,7 @@ from tensorflow.python.data.kernel_tests import test_base
from tensorflow.python.data.ops import dataset_ops
from tensorflow.python.framework import errors
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.platform import test
@@ -44,6 +45,7 @@ class ShuffleAndRepeatTest(test_base.DatasetTestBase):
self.evaluate(get_next)
return outputs
+ @test_util.run_deprecated_v1
def testCorrectOutput(self):
output = self._gen_outputs(lambda: self._build_ds(10), 100)
self.assertSequenceEqual(
@@ -52,6 +54,7 @@ class ShuffleAndRepeatTest(test_base.DatasetTestBase):
for i in range(5):
self.assertSequenceEqual(sorted(output[i * 20:(i + 1) * 20]), range(20))
+ @test_util.run_deprecated_v1
def testReshuffling(self):
# Check that the output orders of different epochs are indeed different.
output = self._gen_outputs(lambda: self._build_ds(10), 100)
@@ -60,17 +63,20 @@ class ShuffleAndRepeatTest(test_base.DatasetTestBase):
epoch2 = output[(i + 1) * 20:(i + 2) * 20]
self.assertNotEqual(epoch1, epoch2)
+ @test_util.run_deprecated_v1
def testSameOrderForSameSeeds(self):
output1 = self._gen_outputs(lambda: self._build_ds(10), 100)
output2 = self._gen_outputs(lambda: self._build_ds(10), 100)
self.assertEqual(output1, output2)
+ @test_util.run_deprecated_v1
def testDifferentOrderForDifferentSeeds(self):
output1 = self._gen_outputs(lambda: self._build_ds(10), 100)
output2 = self._gen_outputs(lambda: self._build_ds(20), 100)
self.assertNotEqual(output1, output2)
self.assertEqual(sorted(output1), sorted(output2))
+ @test_util.run_deprecated_v1
def testCountNone(self):
output1 = self._gen_outputs(
lambda: self._build_ds(10, count=None), 100, verify_exhausted=False)
@@ -79,6 +85,7 @@ class ShuffleAndRepeatTest(test_base.DatasetTestBase):
self.assertNotEqual(output1, output2)
self.assertEqual(sorted(output1), sorted(output2))
+ @test_util.run_deprecated_v1
def testCountMinusOne(self):
output1 = self._gen_outputs(
lambda: self._build_ds(10, count=-1), 100, verify_exhausted=False)
diff --git a/tensorflow/python/data/experimental/kernel_tests/sleep_test.py b/tensorflow/python/data/experimental/kernel_tests/sleep_test.py
index 1a6d5522ef4..8c9e8225d68 100644
--- a/tensorflow/python/data/experimental/kernel_tests/sleep_test.py
+++ b/tensorflow/python/data/experimental/kernel_tests/sleep_test.py
@@ -23,6 +23,7 @@ from tensorflow.python.data.experimental.ops import sleep
from tensorflow.python.data.kernel_tests import test_base
from tensorflow.python.data.ops import dataset_ops
from tensorflow.python.framework import errors
+from tensorflow.python.framework import test_util
from tensorflow.python.platform import test
_NUMPY_RANDOM_SEED = 42
@@ -30,6 +31,7 @@ _NUMPY_RANDOM_SEED = 42
class SleepTest(test_base.DatasetTestBase):
+ @test_util.run_deprecated_v1
def testSleep(self):
sleep_microseconds = 100
dataset = dataset_ops.Dataset.range(10).apply(
diff --git a/tensorflow/python/data/experimental/kernel_tests/stats_dataset_ops_test.py b/tensorflow/python/data/experimental/kernel_tests/stats_dataset_ops_test.py
index e8160069333..b89aa20432a 100644
--- a/tensorflow/python/data/experimental/kernel_tests/stats_dataset_ops_test.py
+++ b/tensorflow/python/data/experimental/kernel_tests/stats_dataset_ops_test.py
@@ -30,6 +30,7 @@ from tensorflow.python.data.experimental.ops import stats_options
from tensorflow.python.data.ops import dataset_ops
from tensorflow.python.framework import errors
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.platform import test
@@ -59,6 +60,7 @@ def function_apply_options(dataset, aggregator, prefix="", counter_prefix=""):
)
class StatsDatasetTest(stats_dataset_test_base.StatsDatasetTestBase):
+ @test_util.run_deprecated_v1
def testBytesProduced(self, dataset_transformation):
aggregator = stats_aggregator.StatsAggregator()
dataset = dataset_ops.Dataset.range(100).map(
@@ -85,6 +87,7 @@ class StatsDatasetTest(stats_dataset_test_base.StatsDatasetTestBase):
self._assertSummaryHasCount(summary_str, "bytes_produced", 100.0)
self._assertSummaryHasSum(summary_str, "bytes_produced", expected_sum)
+ @test_util.run_deprecated_v1
def testLatencyStats(self, dataset_transformation):
aggregator = stats_aggregator.StatsAggregator()
dataset = dataset_ops.Dataset.range(100).apply(
@@ -105,6 +108,7 @@ class StatsDatasetTest(stats_dataset_test_base.StatsDatasetTestBase):
self._assertSummaryHasCount(
self.evaluate(summary_t), "record_latency", 100.0)
+ @test_util.run_deprecated_v1
def testPrefetchBufferUtilization(self, dataset_transformation):
aggregator = stats_aggregator.StatsAggregator()
dataset = dataset_ops.Dataset.range(100).map(
@@ -132,6 +136,7 @@ class StatsDatasetTest(stats_dataset_test_base.StatsDatasetTestBase):
self._assertSummaryHasCount(summary_str, "Prefetch::buffer_utilization",
100)
+ @test_util.run_deprecated_v1
def testPrefetchBufferScalars(self, dataset_transformation):
aggregator = stats_aggregator.StatsAggregator()
dataset = dataset_ops.Dataset.range(10).map(
@@ -154,6 +159,7 @@ class StatsDatasetTest(stats_dataset_test_base.StatsDatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element)
+ @test_util.run_deprecated_v1
def testFilteredElementsStats(self, dataset_transformation):
aggregator = stats_aggregator.StatsAggregator()
dataset = dataset_ops.Dataset.range(101).filter(
@@ -180,6 +186,7 @@ class StatsDatasetTest(stats_dataset_test_base.StatsDatasetTestBase):
self._assertSummaryHasScalarValue(
self.evaluate(summary_t), "Filter::filtered_elements", 34.0)
+ @test_util.run_deprecated_v1
def testMapBufferUtilization(self, dataset_transformation):
def dataset_fn():
@@ -194,6 +201,7 @@ class StatsDatasetTest(stats_dataset_test_base.StatsDatasetTestBase):
dataset_transformation,
function_processing_time=True)
+ @test_util.run_deprecated_v1
def testMapAutoTuneBufferUtilization(self, dataset_transformation):
def dataset_fn():
@@ -211,6 +219,7 @@ class StatsDatasetTest(stats_dataset_test_base.StatsDatasetTestBase):
dataset_transformation,
function_processing_time=True)
+ @test_util.run_deprecated_v1
def testInterleaveAutoTuneBufferUtilization(self, dataset_transformation):
def dataset_fn():
@@ -227,6 +236,7 @@ class StatsDatasetTest(stats_dataset_test_base.StatsDatasetTestBase):
self._testParallelCallsStats(dataset_fn, "ParallelInterleaveV2", 10,
dataset_transformation)
+ @test_util.run_deprecated_v1
def testMapAndBatchAutoTuneBufferUtilization(self, dataset_transformation):
def dataset_fn():
@@ -248,6 +258,7 @@ class StatsDatasetTest(stats_dataset_test_base.StatsDatasetTestBase):
check_elements=False,
function_processing_time=True)
+ @test_util.run_deprecated_v1
def testReinitialize(self, dataset_transformation):
aggregator = stats_aggregator.StatsAggregator()
dataset = dataset_ops.Dataset.range(100).apply(
@@ -270,6 +281,7 @@ class StatsDatasetTest(stats_dataset_test_base.StatsDatasetTestBase):
self._assertSummaryHasCount(
self.evaluate(summary_t), "record_latency", (j + 1) * 100.0)
+ @test_util.run_deprecated_v1
def testNoAggregatorRegistered(self, dataset_transformation):
dataset = dataset_ops.Dataset.range(100).apply(
stats_ops.latency_stats("record_latency"))
@@ -283,6 +295,7 @@ class StatsDatasetTest(stats_dataset_test_base.StatsDatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element)
+ @test_util.run_deprecated_v1
def testMultipleTags(self, dataset_transformation):
aggregator = stats_aggregator.StatsAggregator()
dataset = dataset_ops.Dataset.range(100).apply(
@@ -308,6 +321,7 @@ class StatsDatasetTest(stats_dataset_test_base.StatsDatasetTestBase):
self._assertSummaryHasCount(
self.evaluate(summary_t), "record_latency_2", 100.0)
+ @test_util.run_deprecated_v1
def testRepeatedTags(self, dataset_transformation):
aggregator = stats_aggregator.StatsAggregator()
dataset = dataset_ops.Dataset.range(100).apply(
@@ -329,6 +343,7 @@ class StatsDatasetTest(stats_dataset_test_base.StatsDatasetTestBase):
self._assertSummaryHasCount(
self.evaluate(summary_t), "record_latency", 200.0)
+ @test_util.run_deprecated_v1
def testMultipleIteratorsSameAggregator(self, dataset_transformation):
aggregator = stats_aggregator.StatsAggregator()
dataset = dataset_ops.Dataset.range(100).apply(
@@ -350,6 +365,7 @@ class StatsDatasetTest(stats_dataset_test_base.StatsDatasetTestBase):
self._assertSummaryHasCount(
self.evaluate(summary_t), "record_latency", 200.0)
+ @test_util.run_deprecated_v1
def testMultipleDatasetWithPrefixes(self, dataset_transformation):
aggregator = stats_aggregator.StatsAggregator()
dataset = dataset_ops.Dataset.range(100).apply(
@@ -390,6 +406,7 @@ class FeatureStatsDatasetTest(
stats_dataset_test_base.StatsDatasetTestBase,
reader_dataset_ops_test_base.MakeBatchedFeaturesDatasetTestBase):
+ @test_util.run_deprecated_v1
def testFeaturesStats(self, dataset_transformation):
num_epochs = 5
total_records = num_epochs * self._num_records
diff --git a/tensorflow/python/data/experimental/kernel_tests/unbatch_test.py b/tensorflow/python/data/experimental/kernel_tests/unbatch_test.py
index cb94bb41443..9c6830d9934 100644
--- a/tensorflow/python/data/experimental/kernel_tests/unbatch_test.py
+++ b/tensorflow/python/data/experimental/kernel_tests/unbatch_test.py
@@ -28,6 +28,7 @@ from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors
from tensorflow.python.framework import sparse_tensor
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import string_ops
@@ -37,6 +38,7 @@ from tensorflow.python.util import compat
class UnbatchTest(test_base.DatasetTestBase, parameterized.TestCase):
+ @test_util.run_deprecated_v1
def testUnbatchWithUnknownRankInput(self):
placeholder = array_ops.placeholder(dtypes.int32)
dataset = dataset_ops.Dataset.from_tensors(placeholder).apply(
@@ -51,6 +53,7 @@ class UnbatchTest(test_base.DatasetTestBase, parameterized.TestCase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_elem)
+ @test_util.run_deprecated_v1
def testUnbatchScalarDataset(self):
data = tuple([math_ops.range(10) for _ in range(3)])
data = dataset_ops.Dataset.from_tensor_slices(data)
@@ -70,6 +73,7 @@ class UnbatchTest(test_base.DatasetTestBase, parameterized.TestCase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(op)
+ @test_util.run_deprecated_v1
def testUnbatchDatasetWithStrings(self):
data = tuple([math_ops.range(10) for _ in range(3)])
data = dataset_ops.Dataset.from_tensor_slices(data)
@@ -90,6 +94,7 @@ class UnbatchTest(test_base.DatasetTestBase, parameterized.TestCase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(op)
+ @test_util.run_deprecated_v1
def testUnbatchDatasetWithSparseTensor(self):
st = sparse_tensor.SparseTensorValue(
indices=[[i, i] for i in range(10)],
@@ -111,6 +116,7 @@ class UnbatchTest(test_base.DatasetTestBase, parameterized.TestCase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element)
+ @test_util.run_deprecated_v1
def testUnbatchDatasetWithDenseAndSparseTensor(self):
st = sparse_tensor.SparseTensorValue(
indices=[[i, i] for i in range(10)],
@@ -133,6 +139,7 @@ class UnbatchTest(test_base.DatasetTestBase, parameterized.TestCase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element)
+ @test_util.run_deprecated_v1
def testUnbatchSingleElementTupleDataset(self):
data = tuple([(math_ops.range(10),) for _ in range(3)])
data = dataset_ops.Dataset.from_tensor_slices(data)
@@ -152,6 +159,7 @@ class UnbatchTest(test_base.DatasetTestBase, parameterized.TestCase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(op)
+ @test_util.run_deprecated_v1
def testUnbatchMultiElementTupleDataset(self):
data = tuple([(math_ops.range(10 * i, 10 * i + 10),
array_ops.fill([10], "hi")) for i in range(3)])
@@ -173,6 +181,7 @@ class UnbatchTest(test_base.DatasetTestBase, parameterized.TestCase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(op)
+ @test_util.run_deprecated_v1
def testUnbatchEmpty(self):
data = dataset_ops.Dataset.from_tensors(
(constant_op.constant([]), constant_op.constant([], shape=[0, 4]),
@@ -191,6 +200,7 @@ class UnbatchTest(test_base.DatasetTestBase, parameterized.TestCase):
with self.assertRaises(ValueError):
data.apply(batching.unbatch())
+ @test_util.run_deprecated_v1
def testUnbatchDynamicShapeMismatch(self):
ph1 = array_ops.placeholder(dtypes.int32, shape=[None])
ph2 = array_ops.placeholder(dtypes.int32, shape=None)
diff --git a/tensorflow/python/data/experimental/kernel_tests/unique_test.py b/tensorflow/python/data/experimental/kernel_tests/unique_test.py
index 91f4bc84e99..ddec968858a 100644
--- a/tensorflow/python/data/experimental/kernel_tests/unique_test.py
+++ b/tensorflow/python/data/experimental/kernel_tests/unique_test.py
@@ -22,6 +22,7 @@ from tensorflow.python.data.kernel_tests import test_base
from tensorflow.python.data.ops import dataset_ops
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors
+from tensorflow.python.framework import test_util
from tensorflow.python.platform import test
from tensorflow.python.util import compat
@@ -57,6 +58,7 @@ class UniqueTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element)
+ @test_util.run_deprecated_v1
def testSimpleInt(self):
for dtype in [dtypes.int32, dtypes.int64]:
self._testSimpleHelper(dtype, [
@@ -69,6 +71,7 @@ class UniqueTest(test_base.DatasetTestBase):
([[1, 1], [1, 1], [2, 2], [3, 3], [1, 1]], [[1, 1], [2, 2], [3, 3]]),
])
+ @test_util.run_deprecated_v1
def testSimpleString(self):
self._testSimpleHelper(dtypes.string, [
([], []),
diff --git a/tensorflow/python/data/kernel_tests/flat_map_test.py b/tensorflow/python/data/kernel_tests/flat_map_test.py
index 5f11c2e3a7f..ff52821b107 100644
--- a/tensorflow/python/data/kernel_tests/flat_map_test.py
+++ b/tensorflow/python/data/kernel_tests/flat_map_test.py
@@ -60,6 +60,7 @@ class FlatMapTest(test_base.DatasetTestBase):
self.assertDatasetProduces(dataset, expected_output=expected_output)
# Note: no eager mode coverage, session specific test.
+ @test_util.run_deprecated_v1
def testSkipEagerSharedResourceNestedFlatMapDataset(self):
repeats = [[1, 2], [3, 4], [5, 0], [1, 7]]
components = np.array(repeats, dtype=np.int64)
diff --git a/tensorflow/python/data/kernel_tests/from_generator_test.py b/tensorflow/python/data/kernel_tests/from_generator_test.py
index 4d82c2111c3..d58e3c2364d 100644
--- a/tensorflow/python/data/kernel_tests/from_generator_test.py
+++ b/tensorflow/python/data/kernel_tests/from_generator_test.py
@@ -27,6 +27,7 @@ from tensorflow.python.data.ops import dataset_ops
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import script_ops
from tensorflow.python.platform import test
@@ -69,6 +70,7 @@ class FromGeneratorTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
+ @test_util.run_deprecated_v1
def testFromGeneratorUsingFunction(self):
def generator():
for i in range(1, 100):
@@ -79,18 +81,21 @@ class FromGeneratorTest(test_base.DatasetTestBase):
self._testFromGeneratorOneShot(generator, elem_sequence, 1)
self._testFromGeneratorOneShot(generator, elem_sequence, 5)
+ @test_util.run_deprecated_v1
def testFromGeneratorUsingList(self):
generator = lambda: [[i] * i for i in range(1, 100)]
elem_sequence = list(generator())
self._testFromGenerator(generator, elem_sequence, 1)
self._testFromGenerator(generator, elem_sequence, 5)
+ @test_util.run_deprecated_v1
def testFromGeneratorUsingNdarray(self):
generator = lambda: np.arange(100, dtype=np.int64)
elem_sequence = list(generator())
self._testFromGenerator(generator, elem_sequence, 1, output_types=np.int64)
self._testFromGenerator(generator, elem_sequence, 5, output_types=np.int64)
+ @test_util.run_deprecated_v1
def testFromGeneratorUsingGeneratorExpression(self):
# NOTE(mrry): Generator *expressions* are not repeatable (or in
# general reusable), because they eagerly evaluate the `for`
@@ -102,6 +107,7 @@ class FromGeneratorTest(test_base.DatasetTestBase):
self._testFromGenerator(generator, elem_sequence, 1)
self._testFromGenerator(generator, elem_sequence, 5)
+ @test_util.run_deprecated_v1
def testFromMultipleConcurrentGenerators(self):
num_inner_repeats = 5
num_outer_repeats = 100
@@ -199,6 +205,7 @@ class FromGeneratorTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
+ @test_util.run_deprecated_v1
def testFromGeneratorImplicitConversion(self):
def generator():
yield [1]
@@ -223,6 +230,7 @@ class FromGeneratorTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
+ @test_util.run_deprecated_v1
def testFromGeneratorString(self):
def generator():
yield "foo"
@@ -243,6 +251,7 @@ class FromGeneratorTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
+ @test_util.run_deprecated_v1
def testFromGeneratorTypeError(self):
def generator():
yield np.array([1, 2, 3], dtype=np.int64)
@@ -266,6 +275,7 @@ class FromGeneratorTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
+ @test_util.run_deprecated_v1
def testFromGeneratorShapeError(self):
def generator():
yield np.array([1, 2, 3], dtype=np.int64)
@@ -289,6 +299,7 @@ class FromGeneratorTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
+ @test_util.run_deprecated_v1
def testFromGeneratorStructureError(self):
def generator():
yield 1, 2
@@ -317,6 +328,7 @@ class FromGeneratorTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
+ @test_util.run_deprecated_v1
def testFromGeneratorHeterogeneous(self):
def generator():
yield 1
@@ -335,6 +347,7 @@ class FromGeneratorTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
+ @test_util.run_deprecated_v1
def testFromGeneratorStopShort(self):
def generator():
@@ -353,6 +366,7 @@ class FromGeneratorTest(test_base.DatasetTestBase):
self.assertAllEqual(0, sess.run(get_next))
self.assertAllEqual(1, sess.run(get_next))
+ @test_util.run_deprecated_v1
def testFromGeneratorDestructorCalled(self):
# Use an `Event` to signal that the generator has been deleted.
event = threading.Event()
@@ -387,6 +401,7 @@ class FromGeneratorTest(test_base.DatasetTestBase):
# iterator terminates (and the generator iterator is deleted).
self.assertTrue(event.is_set())
+ @test_util.run_deprecated_v1
def testFromGeneratorWithArgs(self):
def flat_map_fn(elem):
@@ -414,6 +429,7 @@ class FromGeneratorTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
+ @test_util.run_deprecated_v1
def testFromGeneratorWithTwoArgs(self):
def flat_map_fn(elem, message):
@@ -446,6 +462,7 @@ class FromGeneratorTest(test_base.DatasetTestBase):
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
+ @test_util.run_deprecated_v1
def testGeneratorDatasetFinalizeFunctionCalled(self):
# NOTE(mrry): This test tests the internal `_GeneratorDataset`,
# which affords more control over what the finalize function can do than
diff --git a/tensorflow/python/data/kernel_tests/from_sparse_tensor_slices_test.py b/tensorflow/python/data/kernel_tests/from_sparse_tensor_slices_test.py
index d23ac0ebe9c..80ed26e7fbc 100644
--- a/tensorflow/python/data/kernel_tests/from_sparse_tensor_slices_test.py
+++ b/tensorflow/python/data/kernel_tests/from_sparse_tensor_slices_test.py
@@ -32,6 +32,7 @@ from tensorflow.python.platform import test
@test_util.run_all_in_graph_and_eager_modes
class FromSparseTensorSlicesTest(test_base.DatasetTestBase):
+ @test_util.run_deprecated_v1
def testSkipEagerFromSparseTensorSlices(self):
"""Test a dataset based on slices of a `tf.SparseTensor`."""
st = array_ops.sparse_placeholder(dtypes.float64)
diff --git a/tensorflow/python/data/kernel_tests/from_tensors_test.py b/tensorflow/python/data/kernel_tests/from_tensors_test.py
index 2857817e14e..ce706375724 100644
--- a/tensorflow/python/data/kernel_tests/from_tensors_test.py
+++ b/tensorflow/python/data/kernel_tests/from_tensors_test.py
@@ -154,6 +154,7 @@ class FromTensorsTest(test_base.DatasetTestBase):
self.assertEquals(([], ([], []), []), dataset.output_shapes)
# TODO(b/117581999): more specific shapes in eager mode.
+ @test_util.run_deprecated_v1
def testSkipEagerNestedStructure(self):
components = (np.array([1, 2, 3], dtype=np.int64), (np.array([4., 5.]),
np.array([6., 7.])),
diff --git a/tensorflow/python/data/kernel_tests/iterator_test.py b/tensorflow/python/data/kernel_tests/iterator_test.py
index de95a53e576..b836a6aecf1 100644
--- a/tensorflow/python/data/kernel_tests/iterator_test.py
+++ b/tensorflow/python/data/kernel_tests/iterator_test.py
@@ -55,6 +55,7 @@ from tensorflow.python.util import compat
class IteratorTest(test.TestCase, parameterized.TestCase):
+ @test_util.run_deprecated_v1
def testNoGradients(self):
component = constant_op.constant([1.])
side = constant_op.constant(0.)
@@ -65,6 +66,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
self.assertIsNone(gradients_impl.gradients(value, side)[0])
self.assertIsNone(gradients_impl.gradients(value, [component, side])[0])
+ @test_util.run_deprecated_v1
def testCapturingStateInOneShotRaisesException(self):
var = variables.Variable(37.0, name="myvar")
dataset = (
@@ -75,6 +77,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
"datasets that capture stateful objects.+myvar"):
dataset.make_one_shot_iterator()
+ @test_util.run_deprecated_v1
def testOneShotIterator(self):
components = (np.arange(7),
np.array([[1, 2, 3]]) * np.arange(7)[:, np.newaxis],
@@ -100,6 +103,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
+ @test_util.run_deprecated_v1
def testOneShotIteratorCaptureByValue(self):
components = (np.arange(7),
np.array([[1, 2, 3]]) * np.arange(7)[:, np.newaxis],
@@ -162,6 +166,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
+ @test_util.run_deprecated_v1
def testOneShotIteratorNonBlocking(self):
dataset = dataset_ops.Dataset.from_tensors([1, 2, 3]).map(lambda x: x * x)
iterator = dataset.make_one_shot_iterator()
@@ -200,6 +205,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
len([None for r in results if r is None]))
self.assertAllEqual([[1, 4, 9]], [r for r in results if r is not None])
+ @test_util.run_deprecated_v1
def testOneShotIteratorInitializerFails(self):
# Define a dataset whose initialization will always fail.
dataset = dataset_ops.Dataset.from_tensors(
@@ -280,6 +286,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
+ @test_util.run_deprecated_v1
def testNotInitializedError(self):
components = (np.array(1), np.array([1, 2, 3]), np.array(37.0))
iterator = (
@@ -292,6 +299,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
"iterator has not been initialized"):
sess.run(get_next)
+ @test_util.run_deprecated_v1
def testReinitializableIterator(self):
dataset_3 = dataset_ops.Dataset.from_tensors(
constant_op.constant([1, 2, 3]))
@@ -331,6 +339,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
+ @test_util.run_deprecated_v1
def testReinitializableIteratorWithFunctions(self):
def g():
@@ -390,6 +399,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
(constant_op.constant([1, 2, 3], dtype=dtypes.int64),
constant_op.constant([4., 5., 6., 7.], dtype=dtypes.float64))))
+ @test_util.run_deprecated_v1
def testIteratorStringHandle(self):
dataset_3 = dataset_ops.Dataset.from_tensor_slices([1, 2, 3])
dataset_4 = dataset_ops.Dataset.from_tensor_slices([10, 20, 30, 40])
@@ -445,6 +455,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
sess.run(
next_element, feed_dict={handle_placeholder: iterator_4_handle})
+ @test_util.run_deprecated_v1
def testIteratorStringHandleFuture(self):
with forward_compat.forward_compatibility_horizon(2018, 8, 4):
dataset_3 = dataset_ops.Dataset.from_tensor_slices([1, 2, 3])
@@ -508,6 +519,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
sess.run(
next_element, feed_dict={handle_placeholder: iterator_4_handle})
+ @test_util.run_deprecated_v1
def testIteratorStringHandleReuseTensorObject(self):
dataset = dataset_ops.Dataset.from_tensor_slices([1, 2, 3])
one_shot_iterator = dataset.make_one_shot_iterator()
@@ -536,6 +548,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
self.assertEqual("foo_1", handle_with_same_name.op.name)
self.assertIsNot(handle_with_name, handle_with_same_name)
+ @test_util.run_deprecated_v1
def testIteratorStringHandleError(self):
dataset_int_scalar = (
dataset_ops.Dataset.from_tensor_slices([1, 2, 3]).repeat())
@@ -576,6 +589,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
feedable_int_vector.get_next(),
feed_dict={handle_placeholder: handle_float_vector}))
+ @test_util.run_deprecated_v1
def testRemoteIteratorUsingRemoteCallOpDirectSession(self):
worker_config = config_pb2.ConfigProto()
worker_config.device_count["CPU"] = 3
@@ -632,6 +646,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
target_placeholder: "/job:localhost/replica:0/task:0/cpu:1"
})
+ @test_util.run_deprecated_v1
def testRemoteIteratorUsingRemoteCallOpMultiWorkers(self):
s1 = server_lib.Server.create_local_server()
s2 = server_lib.Server.create_local_server()
@@ -739,6 +754,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
target_placeholder: "/job:localhost/replica:0/task:0/cpu:0"
})
+ @test_util.run_deprecated_v1
def testIncorrectIteratorRestore(self):
def _path():
@@ -797,6 +813,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
with self.assertRaises(errors.InvalidArgumentError):
sess.run(restore_op)
+ @test_util.run_deprecated_v1
def testRepeatedGetNextWarning(self):
iterator = dataset_ops.Dataset.range(10).make_one_shot_iterator()
warnings.simplefilter("always")
diff --git a/tensorflow/python/data/kernel_tests/list_files_test.py b/tensorflow/python/data/kernel_tests/list_files_test.py
index 26c536086bc..789f1ab6de7 100644
--- a/tensorflow/python/data/kernel_tests/list_files_test.py
+++ b/tensorflow/python/data/kernel_tests/list_files_test.py
@@ -44,6 +44,7 @@ class ListFilesTest(test_base.DatasetTestBase):
open(path.join(self.tmp_dir, filename), 'a').close()
# Note: eager mode fails in assertion error same as initializer in graph mode.
+ @test_util.run_deprecated_v1
def testSkipEagerEmptyDirectory(self):
dataset = dataset_ops.Dataset.list_files(path.join(self.tmp_dir, '*'))
self.assertDatasetProduces(dataset, expected_output=[])
diff --git a/tensorflow/python/data/kernel_tests/optional_test.py b/tensorflow/python/data/kernel_tests/optional_test.py
index 864013171d8..c2c62e9423e 100644
--- a/tensorflow/python/data/kernel_tests/optional_test.py
+++ b/tensorflow/python/data/kernel_tests/optional_test.py
@@ -74,6 +74,7 @@ class OptionalTest(test_base.DatasetTestBase, parameterized.TestCase):
self.assertAllEqual(expected.dense_shape,
self.evaluate(actual.dense_shape))
+ @test_util.run_deprecated_v1
def testFromNone(self):
value_structure = structure.TensorStructure(dtypes.float32, [])
opt = optional_ops.Optional.none_from_structure(value_structure)
@@ -267,6 +268,7 @@ class OptionalTest(test_base.DatasetTestBase, parameterized.TestCase):
optional_ops.OptionalStructure(
structure.TensorStructure(dtypes.float32, []))),
)
+ @test_util.run_deprecated_v1
def testSkipEagerOptionalStructure(self, tf_value_fn,
expected_value_structure):
tf_value = tf_value_fn()
@@ -322,6 +324,7 @@ class OptionalTest(test_base.DatasetTestBase, parameterized.TestCase):
indices=[[0, 1], [1, 0]], values=[37.0, 42.0],
dense_shape=[2, 2])}, False),
)
+ @test_util.run_deprecated_v1
def testSkipEagerIteratorGetNextAsOptional(self, np_value, tf_value_fn,
works_on_gpu):
if not works_on_gpu and test.is_gpu_available():
diff --git a/tensorflow/python/data/kernel_tests/padded_batch_test.py b/tensorflow/python/data/kernel_tests/padded_batch_test.py
index 5f20d7b4240..dcfb2f507bf 100644
--- a/tensorflow/python/data/kernel_tests/padded_batch_test.py
+++ b/tensorflow/python/data/kernel_tests/padded_batch_test.py
@@ -93,6 +93,7 @@ class PaddedBatchTest(test_base.DatasetTestBase, parameterized.TestCase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(get_next())
+ @test_util.run_deprecated_v1
def testPaddedBatchShortPadding(self):
dataset = (
dataset_ops.Dataset.from_tensor_slices(
@@ -155,6 +156,7 @@ class PaddedBatchTest(test_base.DatasetTestBase, parameterized.TestCase):
next_element = self.getNext(padded_dataset)
self.evaluate(next_element())
+ @test_util.run_deprecated_v1
def testSkipEagerPaddedBatchDatasetShapeSpecifications(self):
int_placeholder = array_ops.placeholder(dtypes.int32)
float_placeholder = array_ops.placeholder(dtypes.float32)
@@ -226,6 +228,7 @@ class PaddedBatchTest(test_base.DatasetTestBase, parameterized.TestCase):
_ = dataset_ops.Dataset.range(10).padded_batch(
5, padded_shapes=shape_as_tensor)
+ @test_util.run_deprecated_v1
def testSkipEagerPaddedBatchShapeError(self):
with self.assertRaisesRegexp(
ValueError,
diff --git a/tensorflow/python/data/kernel_tests/reduce_test.py b/tensorflow/python/data/kernel_tests/reduce_test.py
index d7b653961d6..14bbc0bf72c 100644
--- a/tensorflow/python/data/kernel_tests/reduce_test.py
+++ b/tensorflow/python/data/kernel_tests/reduce_test.py
@@ -68,6 +68,7 @@ class ReduceTest(test_base.DatasetTestBase, parameterized.TestCase):
self.assertEqual(((i + 1) * i) // 2, s)
self.assertEqual(i, c)
+ @test_util.run_deprecated_v1
def testSkipEagerSquareUsingPlaceholder(self):
delta = array_ops.placeholder(dtype=dtypes.int64)
diff --git a/tensorflow/python/data/kernel_tests/shuffle_test.py b/tensorflow/python/data/kernel_tests/shuffle_test.py
index 49460a1a4ed..05d5d814c01 100644
--- a/tensorflow/python/data/kernel_tests/shuffle_test.py
+++ b/tensorflow/python/data/kernel_tests/shuffle_test.py
@@ -115,6 +115,7 @@ class ShuffleTest(test_base.DatasetTestBase, parameterized.TestCase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(get_next())
+ @test_util.run_deprecated_v1
def testSkipEagerSeedZero(self):
"""Test for same behavior when the seed is a Python or Tensor zero."""
iterator = (
diff --git a/tensorflow/python/data/util/convert_test.py b/tensorflow/python/data/util/convert_test.py
index 3058e2b3f60..78ca6e95139 100644
--- a/tensorflow/python/data/util/convert_test.py
+++ b/tensorflow/python/data/util/convert_test.py
@@ -22,6 +22,7 @@ from tensorflow.python.data.util import convert
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import tensor_shape
+from tensorflow.python.framework import test_util
from tensorflow.python.platform import test
from tensorflow.python.util import compat
@@ -60,6 +61,7 @@ class ConvertTest(test.TestCase):
convert.partial_shape_to_tensor(
constant_op.constant([1], dtype=dtypes.int64))))
+ @test_util.run_deprecated_v1
def testPartialShapeToTensorUnknownDimension(self):
self.assertAllEqual([-1],
self.evaluate(
diff --git a/tensorflow/python/data/util/sparse_test.py b/tensorflow/python/data/util/sparse_test.py
index 4ba314f06a4..06acf55ab9d 100644
--- a/tensorflow/python/data/util/sparse_test.py
+++ b/tensorflow/python/data/util/sparse_test.py
@@ -25,6 +25,7 @@ from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
from tensorflow.python.framework import sparse_tensor
from tensorflow.python.framework import tensor_shape
+from tensorflow.python.framework import test_util
from tensorflow.python.platform import test
@@ -296,6 +297,7 @@ class SparseTest(test.TestCase):
self.assertAllEqual(a.eval().values, self.evaluate(b).values)
self.assertAllEqual(a.eval().dense_shape, self.evaluate(b).dense_shape)
+ @test_util.run_deprecated_v1
def testSerializeDeserialize(self):
test_cases = (
(),
@@ -325,6 +327,7 @@ class SparseTest(test.TestCase):
for a, e in zip(nest.flatten(actual), nest.flatten(expected)):
self.assertSparseValuesEqual(a, e)
+ @test_util.run_deprecated_v1
def testSerializeManyDeserialize(self):
test_cases = (
(),
diff --git a/tensorflow/python/data/util/structure_test.py b/tensorflow/python/data/util/structure_test.py
index 65a41a50f11..e9e2f5be0ae 100644
--- a/tensorflow/python/data/util/structure_test.py
+++ b/tensorflow/python/data/util/structure_test.py
@@ -28,6 +28,7 @@ from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
from tensorflow.python.framework import sparse_tensor
from tensorflow.python.framework import tensor_shape
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import variables
from tensorflow.python.platform import test
@@ -115,6 +116,7 @@ class StructureTest(test.TestCase, parameterized.TestCase):
indices=[[0], [1], [2]], values=[4, 5, 6], dense_shape=[3])
}, (constant_op.constant(15.0), constant_op.constant([4, 5, 6]))]),
)
+ @test_util.run_deprecated_v1
def testIsCompatibleWithStructure(
self, original_value_fn, compatible_values_fn, incompatible_values_fn):
original_value = original_value_fn()
diff --git a/tensorflow/python/debug/cli/analyzer_cli_test.py b/tensorflow/python/debug/cli/analyzer_cli_test.py
index 5aa7d1bb4c3..322ecf94667 100644
--- a/tensorflow/python/debug/cli/analyzer_cli_test.py
+++ b/tensorflow/python/debug/cli/analyzer_cli_test.py
@@ -645,6 +645,7 @@ class AnalyzerCLISimpleMulAddTest(test_util.TensorFlowTestCase):
self.assertEqual(len("Size (B)") + 1, dump_size_col_width)
self.assertEqual(len("Op type") + 1, op_type_col_width)
+ @test_util.run_deprecated_v1
def testMeasureTensorListColumnWidthsGivesRightAnswerForData(self):
dump = self._debug_dump.dumped_tensor_data[0]
self.assertLess(dump.dump_size_bytes, 1000)
@@ -660,6 +661,7 @@ class AnalyzerCLISimpleMulAddTest(test_util.TensorFlowTestCase):
# column should be determined by the length of "VariableV2".
self.assertEqual(len("VariableV2") + 1, op_type_col_width)
+ @test_util.run_deprecated_v1
def testListTensors(self):
# Use shorthand alias for the command prefix.
out = self._registry.dispatch_command("lt", [])
@@ -673,6 +675,7 @@ class AnalyzerCLISimpleMulAddTest(test_util.TensorFlowTestCase):
# Check the main menu.
check_main_menu(self, out, list_tensors_enabled=False)
+ @test_util.run_deprecated_v1
def testListTensorsInReverseTimeOrderWorks(self):
# Use shorthand alias for the command prefix.
out = self._registry.dispatch_command("lt", ["-s", "timestamp", "-r"])
@@ -688,6 +691,7 @@ class AnalyzerCLISimpleMulAddTest(test_util.TensorFlowTestCase):
reverse=True)
check_main_menu(self, out, list_tensors_enabled=False)
+ @test_util.run_deprecated_v1
def testListTensorsInDumpSizeOrderWorks(self):
out = self._registry.dispatch_command("lt", ["-s", "dump_size"])
assert_listed_tensors(
@@ -701,6 +705,7 @@ class AnalyzerCLISimpleMulAddTest(test_util.TensorFlowTestCase):
sort_by="dump_size")
check_main_menu(self, out, list_tensors_enabled=False)
+ @test_util.run_deprecated_v1
def testListTensorsInReverseDumpSizeOrderWorks(self):
out = self._registry.dispatch_command("lt", ["-s", "dump_size", "-r"])
assert_listed_tensors(
@@ -720,6 +725,7 @@ class AnalyzerCLISimpleMulAddTest(test_util.TensorFlowTestCase):
self.assertIn("ValueError: Unsupported key to sort tensors by: foobar",
out.lines)
+ @test_util.run_deprecated_v1
def testListTensorsInOpTypeOrderWorks(self):
# Use shorthand alias for the command prefix.
out = self._registry.dispatch_command("lt", ["-s", "op_type"])
@@ -735,6 +741,7 @@ class AnalyzerCLISimpleMulAddTest(test_util.TensorFlowTestCase):
reverse=False)
check_main_menu(self, out, list_tensors_enabled=False)
+ @test_util.run_deprecated_v1
def testListTensorsInReverseOpTypeOrderWorks(self):
# Use shorthand alias for the command prefix.
out = self._registry.dispatch_command("lt", ["-s", "op_type", "-r"])
@@ -750,6 +757,7 @@ class AnalyzerCLISimpleMulAddTest(test_util.TensorFlowTestCase):
reverse=True)
check_main_menu(self, out, list_tensors_enabled=False)
+ @test_util.run_deprecated_v1
def testListTensorsInTensorNameOrderWorks(self):
# Use shorthand alias for the command prefix.
out = self._registry.dispatch_command("lt", ["-s", "tensor_name"])
@@ -765,6 +773,7 @@ class AnalyzerCLISimpleMulAddTest(test_util.TensorFlowTestCase):
reverse=False)
check_main_menu(self, out, list_tensors_enabled=False)
+ @test_util.run_deprecated_v1
def testListTensorsInReverseTensorNameOrderWorks(self):
# Use shorthand alias for the command prefix.
out = self._registry.dispatch_command("lt", ["-s", "tensor_name", "-r"])
@@ -780,6 +789,7 @@ class AnalyzerCLISimpleMulAddTest(test_util.TensorFlowTestCase):
reverse=True)
check_main_menu(self, out, list_tensors_enabled=False)
+ @test_util.run_deprecated_v1
def testListTensorsFilterByNodeNameRegex(self):
out = self._registry.dispatch_command("list_tensors",
["--node_name_filter", ".*read.*"])
@@ -793,6 +803,7 @@ class AnalyzerCLISimpleMulAddTest(test_util.TensorFlowTestCase):
assert_listed_tensors(self, out, [], [], node_name_regex="^read")
check_main_menu(self, out, list_tensors_enabled=False)
+ @test_util.run_deprecated_v1
def testListTensorFilterByOpTypeRegex(self):
out = self._registry.dispatch_command("list_tensors",
["--op_type_filter", "Identity"])
@@ -821,6 +832,7 @@ class AnalyzerCLISimpleMulAddTest(test_util.TensorFlowTestCase):
op_type_regex="(Add|MatMul)")
check_main_menu(self, out, list_tensors_enabled=False)
+ @test_util.run_deprecated_v1
def testListTensorWithFilterAndNodeNameExclusionWorks(self):
# First, create and register the filter.
def is_2x1_vector(datum, tensor):
@@ -877,6 +889,7 @@ class AnalyzerCLISimpleMulAddTest(test_util.TensorFlowTestCase):
out = self._registry.dispatch_command("list_tensors", ["--bar"])
check_syntax_error_output(self, out, "list_tensors")
+ @test_util.run_deprecated_v1
def testNodeInfoByNodeName(self):
node_name = "simple_mul_add/matmul"
out = self._registry.dispatch_command("node_info", [node_name])
@@ -901,6 +914,7 @@ class AnalyzerCLISimpleMulAddTest(test_util.TensorFlowTestCase):
[(len(out.lines[0]) - len(node_name), len(out.lines[0]), "bold")],
out.font_attr_segs[0])
+ @test_util.run_deprecated_v1
def testNodeInfoShowAttributes(self):
node_name = "simple_mul_add/matmul"
out = self._registry.dispatch_command("node_info", ["-a", node_name])
@@ -924,6 +938,7 @@ class AnalyzerCLISimpleMulAddTest(test_util.TensorFlowTestCase):
print_tensor_node_name=node_name,
list_outputs_node_name=node_name)
+ @test_util.run_deprecated_v1
def testNodeInfoShowDumps(self):
node_name = "simple_mul_add/matmul"
out = self._registry.dispatch_command("node_info", ["-d", node_name])
@@ -948,6 +963,7 @@ class AnalyzerCLISimpleMulAddTest(test_util.TensorFlowTestCase):
len(out.lines[16]) - len(out.lines[16].strip()),
len(out.lines[16]), "pt %s:0 -n 0" % node_name)
+ @test_util.run_deprecated_v1
def testNodeInfoShowStackTraceUnavailableIsIndicated(self):
self._debug_dump.set_python_graph(None)
@@ -971,6 +987,7 @@ class AnalyzerCLISimpleMulAddTest(test_util.TensorFlowTestCase):
print_tensor_node_name=node_name,
list_outputs_node_name=node_name)
+ @test_util.run_deprecated_v1
def testNodeInfoShowStackTraceAvailableWorks(self):
self._debug_dump.set_python_graph(self._sess.graph)
@@ -994,6 +1011,7 @@ class AnalyzerCLISimpleMulAddTest(test_util.TensorFlowTestCase):
print_tensor_node_name=node_name,
list_outputs_node_name=node_name)
+ @test_util.run_deprecated_v1
def testNodeInfoByTensorName(self):
node_name = "simple_mul_add/u/read"
tensor_name = node_name + ":0"
@@ -1363,6 +1381,7 @@ class AnalyzerCLISimpleMulAddTest(test_util.TensorFlowTestCase):
break
return index
+ @test_util.run_deprecated_v1
def testPrintSourceForOpNamesWholeFileWorks(self):
self._debug_dump.set_python_graph(self._sess.graph)
out = self._registry.dispatch_command(
@@ -1415,6 +1434,7 @@ class AnalyzerCLISimpleMulAddTest(test_util.TensorFlowTestCase):
self.assertEqual("pt simple_mul_add/add",
out.font_attr_segs[index + 1][0][2].content)
+ @test_util.run_deprecated_v1
def testPrintSourceForTensorNamesWholeFileWorks(self):
self._debug_dump.set_python_graph(self._sess.graph)
out = self._registry.dispatch_command(
@@ -1435,6 +1455,7 @@ class AnalyzerCLISimpleMulAddTest(test_util.TensorFlowTestCase):
self.assertEqual("pt simple_mul_add/u:0",
out.font_attr_segs[index + 2][0][2].content)
+ @test_util.run_deprecated_v1
def testPrintSourceForOpNamesStartingAtSpecifiedLineWorks(self):
self._debug_dump.set_python_graph(self._sess.graph)
out = self._registry.dispatch_command(
@@ -1461,6 +1482,7 @@ class AnalyzerCLISimpleMulAddTest(test_util.TensorFlowTestCase):
self.assertEqual("pt simple_mul_add/u/read",
out.font_attr_segs[index + 3][0][2].content)
+ @test_util.run_deprecated_v1
def testPrintSourceForOpNameSettingMaximumElementCountWorks(self):
self._debug_dump.set_python_graph(self._sess.graph)
out = self._registry.dispatch_command(
@@ -1505,6 +1527,7 @@ class AnalyzerCLISimpleMulAddTest(test_util.TensorFlowTestCase):
self.assertTrue(cli_shared.COLOR_GRAY in attr_seg[2] or
attr_seg[2] == cli_shared.COLOR_GRAY)
+ @test_util.run_deprecated_v1
def testListSourceWithNodeNameFilterWithMatchesWorks(self):
self._debug_dump.set_python_graph(self._sess.graph)
out = self._registry.dispatch_command("list_source", ["-n", ".*/read"])
@@ -1719,6 +1742,7 @@ class AnalyzerCLIControlDepTest(test_util.TensorFlowTestCase):
# Tear down temporary dump directory.
shutil.rmtree(cls._dump_root)
+ @test_util.run_deprecated_v1
def testNodeInfoWithControlDependencies(self):
# Call node_info on a node with control inputs.
out = self._registry.dispatch_command("node_info",
@@ -1759,6 +1783,7 @@ class AnalyzerCLIControlDepTest(test_util.TensorFlowTestCase):
len(out.lines[z_line]),
"ni -a -d -t control_deps/ctrl_dep_z")
+ @test_util.run_deprecated_v1
def testListInputsNonRecursiveNoControl(self):
"""List inputs non-recursively, without any control inputs."""
@@ -1801,6 +1826,7 @@ class AnalyzerCLIControlDepTest(test_util.TensorFlowTestCase):
len(out.lines[3]) - len("control_deps/ctrl_dep_y"),
len(out.lines[3]), "li -c -r control_deps/ctrl_dep_y")
+ @test_util.run_deprecated_v1
def testListInputsNonRecursiveNoControlUsingTensorName(self):
"""List inputs using the name of an output tensor of the node."""
@@ -1829,6 +1855,7 @@ class AnalyzerCLIControlDepTest(test_util.TensorFlowTestCase):
len(out.lines[3]) - len("control_deps/ctrl_dep_y"),
len(out.lines[3]), "li -c -r control_deps/ctrl_dep_y")
+ @test_util.run_deprecated_v1
def testListInputsNonRecursiveWithControls(self):
"""List inputs non-recursively, with control inputs."""
node_name = "control_deps/ctrl_dep_z"
@@ -1859,6 +1886,7 @@ class AnalyzerCLIControlDepTest(test_util.TensorFlowTestCase):
len(out.lines[5]) - len("control_deps/x"),
len(out.lines[5]), "li -c -r control_deps/x")
+ @test_util.run_deprecated_v1
def testListInputsRecursiveWithControls(self):
"""List inputs recursively, with control inputs."""
node_name = "control_deps/ctrl_dep_z"
@@ -1904,6 +1932,7 @@ class AnalyzerCLIControlDepTest(test_util.TensorFlowTestCase):
len(out.lines[18]) - len("control_deps/x"),
len(out.lines[18]), "li -c -r control_deps/x")
+ @test_util.run_deprecated_v1
def testListInputsRecursiveWithControlsWithDepthLimit(self):
"""List inputs recursively, with control inputs and a depth limit."""
node_name = "control_deps/ctrl_dep_z"
@@ -1963,6 +1992,7 @@ class AnalyzerCLIControlDepTest(test_util.TensorFlowTestCase):
"ERROR: There is no node named \"control_deps/z/foo\" in the "
"partition graphs"], out.lines)
+ @test_util.run_deprecated_v1
def testListRecipientsRecursiveWithControlsWithDepthLimit(self):
"""List recipients recursively, with control inputs and a depth limit."""
@@ -2034,6 +2064,7 @@ class AnalyzerCLIWhileLoopTest(test_util.TensorFlowTestCase):
# Tear down temporary dump directory.
shutil.rmtree(cls._dump_root)
+ @test_util.run_deprecated_v1
def testMultipleDumpsPrintTensorNoNumber(self):
output = self._registry.dispatch_command("pt", ["while/Identity:0"])
@@ -2051,6 +2082,7 @@ class AnalyzerCLIWhileLoopTest(test_util.TensorFlowTestCase):
self.assertEqual("For example:", output.lines[-2])
self.assertEqual(" print_tensor while/Identity:0 -n 0", output.lines[-1])
+ @test_util.run_deprecated_v1
def testMultipleDumpsPrintTensorWithNumber(self):
for i in xrange(5):
output = self._registry.dispatch_command(
@@ -2064,6 +2096,7 @@ class AnalyzerCLIWhileLoopTest(test_util.TensorFlowTestCase):
self.assertTrue(output.lines[4].startswith("array(%d" % i))
self.assertTrue(output.lines[4].endswith(")"))
+ @test_util.run_deprecated_v1
def testMultipleDumpsPrintTensorInvalidNumber(self):
output = self._registry.dispatch_command("pt",
["while/Identity:0", "-n", "10"])
diff --git a/tensorflow/python/debug/cli/cli_shared_test.py b/tensorflow/python/debug/cli/cli_shared_test.py
index 07b364db9f2..d191a234fde 100644
--- a/tensorflow/python/debug/cli/cli_shared_test.py
+++ b/tensorflow/python/debug/cli/cli_shared_test.py
@@ -118,6 +118,7 @@ class GetRunStartIntroAndDescriptionTest(test_util.TensorFlowTestCase):
def tearDown(self):
ops.reset_default_graph()
+ @test_util.run_deprecated_v1
def testSingleFetchNoFeeds(self):
run_start_intro = cli_shared.get_run_start_intro(12, self.const_a, None, {})
@@ -181,6 +182,7 @@ class GetRunStartIntroAndDescriptionTest(test_util.TensorFlowTestCase):
run_start_intro = cli_shared.get_run_start_intro(1, self.sparse_d, None, {})
self.assertEqual(str(self.sparse_d), run_start_intro.lines[4].strip())
+ @test_util.run_deprecated_v1
def testTwoFetchesListNoFeeds(self):
fetches = [self.const_a, self.const_b]
run_start_intro = cli_shared.get_run_start_intro(1, fetches, None, {})
@@ -197,6 +199,7 @@ class GetRunStartIntroAndDescriptionTest(test_util.TensorFlowTestCase):
description = cli_shared.get_run_short_description(1, fetches, None)
self.assertEqual("run #1: 2 fetches; 0 feeds", description)
+ @test_util.run_deprecated_v1
def testNestedListAsFetches(self):
fetches = [self.const_c, [self.const_a, self.const_b]]
run_start_intro = cli_shared.get_run_start_intro(1, fetches, None, {})
@@ -210,6 +213,7 @@ class GetRunStartIntroAndDescriptionTest(test_util.TensorFlowTestCase):
description = cli_shared.get_run_short_description(1, fetches, None)
self.assertEqual("run #1: 3 fetches; 0 feeds", description)
+ @test_util.run_deprecated_v1
def testNestedDictAsFetches(self):
fetches = {"c": self.const_c, "ab": {"a": self.const_a, "b": self.const_b}}
run_start_intro = cli_shared.get_run_start_intro(1, fetches, None, {})
@@ -227,6 +231,7 @@ class GetRunStartIntroAndDescriptionTest(test_util.TensorFlowTestCase):
description = cli_shared.get_run_short_description(1, fetches, None)
self.assertEqual("run #1: 3 fetches; 0 feeds", description)
+ @test_util.run_deprecated_v1
def testTwoFetchesAsTupleNoFeeds(self):
fetches = (self.const_a, self.const_b)
run_start_intro = cli_shared.get_run_start_intro(1, fetches, None, {})
@@ -243,6 +248,7 @@ class GetRunStartIntroAndDescriptionTest(test_util.TensorFlowTestCase):
description = cli_shared.get_run_short_description(1, fetches, None)
self.assertEqual("run #1: 2 fetches; 0 feeds", description)
+ @test_util.run_deprecated_v1
def testTwoFetchesAsNamedTupleNoFeeds(self):
fetches_namedtuple = namedtuple("fetches", "x y")
fetches = fetches_namedtuple(self.const_b, self.const_c)
@@ -260,6 +266,7 @@ class GetRunStartIntroAndDescriptionTest(test_util.TensorFlowTestCase):
description = cli_shared.get_run_short_description(1, fetches, None)
self.assertEqual("run #1: 2 fetches; 0 feeds", description)
+ @test_util.run_deprecated_v1
def testWithFeedDict(self):
feed_dict = {
self.const_a: 10.0,
@@ -283,6 +290,7 @@ class GetRunStartIntroAndDescriptionTest(test_util.TensorFlowTestCase):
feed_dict)
self.assertEqual("run #1: 1 fetch (c:0); 2 feeds", description)
+ @test_util.run_deprecated_v1
def testTensorFilters(self):
feed_dict = {self.const_a: 10.0}
tensor_filters = {
@@ -313,11 +321,13 @@ class GetRunStartIntroAndDescriptionTest(test_util.TensorFlowTestCase):
command_set.add(annot[2].content)
self.assertEqual({"run -f filter_a", "run -f filter_b"}, command_set)
+ @test_util.run_deprecated_v1
def testGetRunShortDescriptionWorksForTensorFeedKey(self):
short_description = cli_shared.get_run_short_description(
1, self.const_a, {self.const_a: 42.0})
self.assertEqual("run #1: 1 fetch (a:0); 1 feed (a:0)", short_description)
+ @test_util.run_deprecated_v1
def testGetRunShortDescriptionWorksForUnicodeFeedKey(self):
short_description = cli_shared.get_run_short_description(
1, self.const_a, {u"foo": 42.0})
@@ -332,6 +342,7 @@ class GetErrorIntroTest(test_util.TensorFlowTestCase):
def tearDown(self):
ops.reset_default_graph()
+ @test_util.run_deprecated_v1
def testShapeError(self):
tf_error = errors.OpError(None, self.var_a.initializer, "foo description",
None)
diff --git a/tensorflow/python/debug/cli/profile_analyzer_cli_test.py b/tensorflow/python/debug/cli/profile_analyzer_cli_test.py
index 60b60479707..effcd500c70 100644
--- a/tensorflow/python/debug/cli/profile_analyzer_cli_test.py
+++ b/tensorflow/python/debug/cli/profile_analyzer_cli_test.py
@@ -348,6 +348,7 @@ class ProfileAnalyzerPrintSourceTest(test_util.TensorFlowTestCase):
ops.reset_default_graph()
super(ProfileAnalyzerPrintSourceTest, self).tearDown()
+ @test_util.run_deprecated_v1
def testPrintSourceForWhileLoop(self):
prof_output = self.prof_analyzer.print_source([__file__])
@@ -361,6 +362,7 @@ class ProfileAnalyzerPrintSourceTest(test_util.TensorFlowTestCase):
r"\[(\|)+(\s)*\] .*us .*7\(55\) .*L%d.*(\S)+" % self.loop_lineno,
prof_output.lines)
+ @test_util.run_deprecated_v1
def testPrintSourceOutputContainsClickableLinks(self):
prof_output = self.prof_analyzer.print_source([__file__])
any_match, line_index = _at_least_one_line_matches(
@@ -377,6 +379,7 @@ class ProfileAnalyzerPrintSourceTest(test_util.TensorFlowTestCase):
break
self.assertTrue(any_menu_item_match)
+ @test_util.run_deprecated_v1
def testPrintSourceWithNonDefaultTimeUnit(self):
prof_output = self.prof_analyzer.print_source([
__file__, "--time_unit", "ms"])
@@ -391,6 +394,7 @@ class ProfileAnalyzerPrintSourceTest(test_util.TensorFlowTestCase):
r"\[(\|)+(\s)*\] .*ms .*7\(55\) .*L%d.*(\S)+" % self.loop_lineno,
prof_output.lines)
+ @test_util.run_deprecated_v1
def testPrintSourceWithNodeNameFilter(self):
prof_output = self.prof_analyzer.print_source([
__file__, "--node_name_filter", "x$"])
@@ -423,6 +427,7 @@ class ProfileAnalyzerPrintSourceTest(test_util.TensorFlowTestCase):
break
self.assertTrue(any_menu_item_match)
+ @test_util.run_deprecated_v1
def testPrintSourceWithOpTypeFilter(self):
prof_output = self.prof_analyzer.print_source([
__file__, "--op_type_filter", "Less"])
diff --git a/tensorflow/python/debug/lib/common_test.py b/tensorflow/python/debug/lib/common_test.py
index 5af0dafcf9f..f6413f6b7b3 100644
--- a/tensorflow/python/debug/lib/common_test.py
+++ b/tensorflow/python/debug/lib/common_test.py
@@ -27,6 +27,7 @@ from tensorflow.python.platform import googletest
class CommonTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testOnFeedOneFetch(self):
a = constant_op.constant(10.0, name="a")
b = constant_op.constant(20.0, name="b")
@@ -35,6 +36,7 @@ class CommonTest(test_util.TensorFlowTestCase):
self.assertItemsEqual(["a:0"], loaded[0])
self.assertItemsEqual(["b:0"], loaded[1])
+ @test_util.run_deprecated_v1
def testGetRunKeyFlat(self):
a = constant_op.constant(10.0, name="a")
b = constant_op.constant(20.0, name="b")
@@ -43,6 +45,7 @@ class CommonTest(test_util.TensorFlowTestCase):
self.assertItemsEqual(["a:0"], loaded[0])
self.assertItemsEqual(["a:0", "b:0"], loaded[1])
+ @test_util.run_deprecated_v1
def testGetRunKeyNestedFetches(self):
a = constant_op.constant(10.0, name="a")
b = constant_op.constant(20.0, name="b")
diff --git a/tensorflow/python/debug/lib/debug_gradients_test.py b/tensorflow/python/debug/lib/debug_gradients_test.py
index 01867fc69d0..1c531478638 100644
--- a/tensorflow/python/debug/lib/debug_gradients_test.py
+++ b/tensorflow/python/debug/lib/debug_gradients_test.py
@@ -54,6 +54,7 @@ class IdentifyGradientTest(test_util.TensorFlowTestCase):
ops.reset_default_graph()
debug_gradients.clear_gradient_debuggers()
+ @test_util.run_deprecated_v1
def testIdentifyGradientGivesCorrectTensorObjectWithoutContextManager(self):
grad_debugger = debug_gradients.GradientsDebugger()
id_grad_w = grad_debugger.identify_gradient(self.w)
@@ -84,6 +85,7 @@ class IdentifyGradientTest(test_util.TensorFlowTestCase):
self.assertIsInstance(w_grad, ops.Tensor)
self.assertAllClose(1.0, self.sess.run(w_grad))
+ @test_util.run_deprecated_v1
def testIdentifyGradientGivesCorrectTensorObjectWithTfGradients(self):
grad_debugger = debug_gradients.GradientsDebugger()
id_grad_w = grad_debugger.identify_gradient(self.w)
@@ -115,6 +117,7 @@ class IdentifyGradientTest(test_util.TensorFlowTestCase):
self.assertIsInstance(w_grad, ops.Tensor)
self.assertAllClose(1.0, self.sess.run(w_grad))
+ @test_util.run_deprecated_v1
def testCallingIdentifyGradientTwiceWithTheSameGradientsDebuggerErrors(self):
grad_debugger = debug_gradients.GradientsDebugger()
grad_debugger.identify_gradient(self.w)
@@ -122,6 +125,7 @@ class IdentifyGradientTest(test_util.TensorFlowTestCase):
"The graph already contains an op named .*"):
grad_debugger.identify_gradient(self.w)
+ @test_util.run_deprecated_v1
def testIdentifyGradientWorksOnMultipleLosses(self):
grad_debugger_1 = debug_gradients.GradientsDebugger()
grad_debugger_2 = debug_gradients.GradientsDebugger()
@@ -150,6 +154,7 @@ class IdentifyGradientTest(test_util.TensorFlowTestCase):
self.assertAllClose(2.0 * 5.0, self.sess.run(dz1_dy))
self.assertAllClose(0.5 * (5.0**-0.5), self.sess.run(dz2_dy))
+ @test_util.run_deprecated_v1
def testIdentifyGradientRaisesLookupErrorForUnknownXTensor(self):
grad_debugger_1 = debug_gradients.GradientsDebugger()
grad_debugger_2 = debug_gradients.GradientsDebugger()
@@ -170,6 +175,7 @@ class IdentifyGradientTest(test_util.TensorFlowTestCase):
r"This GradientsDebugger has not received any gradient tensor for "):
grad_debugger_2.gradient_tensor(self.w)
+ @test_util.run_deprecated_v1
def testIdentifyGradientRaisesTypeErrorForNonTensorOrTensorNameInput(self):
grad_debugger = debug_gradients.GradientsDebugger()
with self.assertRaisesRegexp(
@@ -178,6 +184,7 @@ class IdentifyGradientTest(test_util.TensorFlowTestCase):
r"has type .*Operation.*"):
grad_debugger.gradient_tensor(variables.global_variables_initializer())
+ @test_util.run_deprecated_v1
def testIdentifyGradientTensorWorksWithGradientDescentOptimizer(self):
grad_debugger = debug_gradients.GradientsDebugger()
id_grad_w = grad_debugger.identify_gradient(self.w)
@@ -193,6 +200,7 @@ class IdentifyGradientTest(test_util.TensorFlowTestCase):
self.assertIsInstance(w_grad, ops.Tensor)
self.assertAllClose(1.0, self.sess.run(w_grad))
+ @test_util.run_deprecated_v1
def testWatchGradientsByXTensorNamesWorks(self):
y = math_ops.add(self.w, -1.0, name="y")
@@ -219,6 +227,7 @@ class IdentifyGradientTest(test_util.TensorFlowTestCase):
self.assertIsInstance(w_grad, ops.Tensor)
self.assertAllClose(1.0, self.sess.run(w_grad))
+ @test_util.run_deprecated_v1
def testWatchGradientsByXTensorNamesWorksWithoutContextManager(self):
y = math_ops.add(self.w, -1.0, name="y")
@@ -245,6 +254,7 @@ class IdentifyGradientTest(test_util.TensorFlowTestCase):
self.assertIsInstance(w_grad, ops.Tensor)
self.assertAllClose(1.0, self.sess.run(w_grad))
+ @test_util.run_deprecated_v1
def testWatchGradientsWorksOnRefTensor(self):
y = math_ops.add(self.w, -1.0, name="y")
@@ -263,6 +273,7 @@ class IdentifyGradientTest(test_util.TensorFlowTestCase):
self.assertAllClose(3.0, self.sess.run(
grad_debugger.gradient_tensor("u:0")))
+ @test_util.run_deprecated_v1
def testWatchGradientsWorksOnMultipleTensors(self):
y = math_ops.add(self.w, -1.0, name="y")
@@ -283,6 +294,7 @@ class IdentifyGradientTest(test_util.TensorFlowTestCase):
self.assertAllClose(3.0, self.sess.run(
grad_debugger.gradient_tensor("u:0")))
+ @test_util.run_deprecated_v1
def testWatchGradientsByXTensorsWorks(self):
y = math_ops.add(self.w, -1.0, name="foo/y")
z = math_ops.square(y, name="foo/z")
@@ -305,6 +317,7 @@ class IdentifyGradientTest(test_util.TensorFlowTestCase):
self.assertAllClose(10.0, self.sess.run(w_grad))
self.assertAllClose(30.0, self.sess.run(u_grad))
+ @test_util.run_deprecated_v1
def testWatchGradientsByTensorCanWorkOnMultipleLosses(self):
y = math_ops.add(self.w, -1.0, name="y")
z1 = math_ops.square(y, name="z1")
@@ -330,6 +343,7 @@ class IdentifyGradientTest(test_util.TensorFlowTestCase):
self.assertAllClose(2.0 * 5.0, self.sess.run(dz1_dy))
self.assertAllClose(0.5 * (5.0**-0.5), self.sess.run(dz2_dy))
+ @test_util.run_deprecated_v1
def testGradientsValuesFromDumpWorks(self):
y = math_ops.add(self.w, -1.0, name="y")
z = math_ops.square(y, name="z")
diff --git a/tensorflow/python/debug/lib/debug_utils_test.py b/tensorflow/python/debug/lib/debug_utils_test.py
index 23ab98444cd..cf59b30e3da 100644
--- a/tensorflow/python/debug/lib/debug_utils_test.py
+++ b/tensorflow/python/debug/lib/debug_utils_test.py
@@ -185,6 +185,7 @@ class DebugUtilsTest(test_util.TensorFlowTestCase):
self.assertEqual(["file:///tmp/tfdbg_1", "file:///tmp/tfdbg_2"],
watch_0.debug_urls)
+ @test_util.run_deprecated_v1
def testWatchGraph_allNodes(self):
debug_utils.watch_graph(
self._run_options,
@@ -216,6 +217,7 @@ class DebugUtilsTest(test_util.TensorFlowTestCase):
self.assertTrue("p1" in node_names)
self.assertTrue("s" in node_names)
+ @test_util.run_deprecated_v1
def testWatchGraph_nodeNameWhitelist(self):
debug_utils.watch_graph(
self._run_options,
@@ -230,6 +232,7 @@ class DebugUtilsTest(test_util.TensorFlowTestCase):
sorted(["a1_init", "a1", "a1/Assign", "a1/read", "p1"]),
sorted(node_names))
+ @test_util.run_deprecated_v1
def testWatchGraph_opTypeWhitelist(self):
debug_utils.watch_graph(
self._run_options,
@@ -255,6 +258,7 @@ class DebugUtilsTest(test_util.TensorFlowTestCase):
["DebugIdentity"], ["file:///tmp/tfdbg_1"])
self.assertEqual(["p1"], node_names)
+ @test_util.run_deprecated_v1
def testWatchGraph_tensorDTypeWhitelist(self):
debug_utils.watch_graph(
self._run_options,
@@ -267,6 +271,7 @@ class DebugUtilsTest(test_util.TensorFlowTestCase):
["DebugIdentity"], ["file:///tmp/tfdbg_1"])
self.assertItemsEqual(["a1", "a1/Assign", "b", "b/Assign"], node_names)
+ @test_util.run_deprecated_v1
def testWatchGraph_nodeNameAndTensorDTypeWhitelists(self):
debug_utils.watch_graph(
self._run_options,
@@ -280,6 +285,7 @@ class DebugUtilsTest(test_util.TensorFlowTestCase):
["DebugIdentity"], ["file:///tmp/tfdbg_1"])
self.assertItemsEqual(["a1", "a1/Assign"], node_names)
+ @test_util.run_deprecated_v1
def testWatchGraph_nodeNameBlacklist(self):
debug_utils.watch_graph_with_blacklists(
self._run_options,
@@ -294,6 +300,7 @@ class DebugUtilsTest(test_util.TensorFlowTestCase):
sorted(["b_init", "b", "b/Assign", "b/read", "c", "s"]),
sorted(node_names))
+ @test_util.run_deprecated_v1
def testWatchGraph_opTypeBlacklist(self):
debug_utils.watch_graph_with_blacklists(
self._run_options,
@@ -306,6 +313,7 @@ class DebugUtilsTest(test_util.TensorFlowTestCase):
["DebugIdentity"], ["file:///tmp/tfdbg_1"])
self.assertEqual(sorted(["p1", "s"]), sorted(node_names))
+ @test_util.run_deprecated_v1
def testWatchGraph_nodeNameAndOpTypeBlacklists(self):
debug_utils.watch_graph_with_blacklists(
self._run_options,
@@ -319,6 +327,7 @@ class DebugUtilsTest(test_util.TensorFlowTestCase):
["DebugIdentity"], ["file:///tmp/tfdbg_1"])
self.assertEqual(["s"], node_names)
+ @test_util.run_deprecated_v1
def testWatchGraph_tensorDTypeBlacklists(self):
debug_utils.watch_graph_with_blacklists(
self._run_options,
@@ -335,6 +344,7 @@ class DebugUtilsTest(test_util.TensorFlowTestCase):
self.assertNotIn("b/Assign", node_names)
self.assertIn("s", node_names)
+ @test_util.run_deprecated_v1
def testWatchGraph_nodeNameAndTensorDTypeBlacklists(self):
debug_utils.watch_graph_with_blacklists(
self._run_options,
diff --git a/tensorflow/python/debug/lib/session_debug_file_test.py b/tensorflow/python/debug/lib/session_debug_file_test.py
index 1874160dd63..f5f9ba29ab5 100644
--- a/tensorflow/python/debug/lib/session_debug_file_test.py
+++ b/tensorflow/python/debug/lib/session_debug_file_test.py
@@ -28,6 +28,7 @@ from tensorflow.python.debug.lib import debug_utils
from tensorflow.python.debug.lib import session_debug_testlib
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import variables
from tensorflow.python.platform import googletest
@@ -44,6 +45,7 @@ class SessionDebugFileTest(session_debug_testlib.SessionDebugTestBase):
else:
return os.path.join(self._dump_root, "run_%d" % run_number)
+ @test_util.run_deprecated_v1
def testAllowsDifferentWatchesOnDifferentRuns(self):
"""Test watching different tensors on different runs of the same graph."""
diff --git a/tensorflow/python/debug/lib/source_utils_test.py b/tensorflow/python/debug/lib/source_utils_test.py
index a16d68329a3..9083297fdbb 100644
--- a/tensorflow/python/debug/lib/source_utils_test.py
+++ b/tensorflow/python/debug/lib/source_utils_test.py
@@ -65,6 +65,7 @@ class GuessIsTensorFlowLibraryTest(test_util.TensorFlowTestCase):
self.assertTrue(
source_utils.guess_is_tensorflow_py_library(source_utils.__file__))
+ @test_util.run_deprecated_v1
def testFileInPythonKernelsPathReturnsTrue(self):
x = constant_op.constant(42.0, name="x")
self.assertTrue(
diff --git a/tensorflow/python/distribute/all_reduce_test.py b/tensorflow/python/distribute/all_reduce_test.py
index 5bf983a1b20..2c6b853124c 100644
--- a/tensorflow/python/distribute/all_reduce_test.py
+++ b/tensorflow/python/distribute/all_reduce_test.py
@@ -37,6 +37,7 @@ from tensorflow.python.platform import tf_logging
class AllReduceTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testFlattenTensorsShapesDefined(self):
x = array_ops.placeholder(types_pb2.DT_FLOAT, [None])
with self.assertRaisesRegexp(ValueError,
@@ -100,6 +101,7 @@ class AllReduceTest(test_util.TensorFlowTestCase):
input_tensors.append(array_ops.identity(t8))
return input_tensors, device_names
+ @test_util.run_deprecated_v1
def testBuildRingGatherPassStructure(self):
# 1 worker, 1 device
input_tensors, device_names = self._buildInput(1, 1)
@@ -170,6 +172,7 @@ class AllReduceTest(test_util.TensorFlowTestCase):
"subdiv=%d elapsed=%f" %
(num_workers, num_gpus, shape, subdiv, elapsed))
+ @test_util.run_deprecated_v1
def testRingAllReduce(self):
self._testRingAllReduce(1, 2, [], 1)
self._testRingAllReduce(1, 2, [8], 1)
@@ -199,6 +202,7 @@ class AllReduceTest(test_util.TensorFlowTestCase):
tf_logging.info("ShuffleAllReduce num_workers=%d num_gpus=%d shape=%s "
"elapsed=%f" % (num_workers, num_gpus, shape, elapsed))
+ @test_util.run_deprecated_v1
def testShuffleAllReduce(self):
self._testShuffleAllReduce(1, 2, [], 1)
self._testShuffleAllReduce(1, 2, [8], 1)
@@ -225,6 +229,7 @@ class AllReduceTest(test_util.TensorFlowTestCase):
"shape=%s elapsed=%f" %
(num_workers, num_gpus, shape, elapsed))
+ @test_util.run_deprecated_v1
def testRecursiveHDAllReduce(self):
self._testRecursiveHDAllReduce(1, 2, [8])
self._testRecursiveHDAllReduce(1, 2, [4, 4])
diff --git a/tensorflow/python/distribute/device_util_test.py b/tensorflow/python/distribute/device_util_test.py
index baecd43c8e4..2f0d7ed3b31 100644
--- a/tensorflow/python/distribute/device_util_test.py
+++ b/tensorflow/python/distribute/device_util_test.py
@@ -21,11 +21,13 @@ from __future__ import print_function
from tensorflow.python.distribute import device_util
from tensorflow.python.eager import context
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.platform import test
class DeviceUtilTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testCurrentDeviceWithGlobalGraph(self):
with ops.device("/cpu:0"):
self.assertEqual(device_util.current(), "/device:CPU:0")
@@ -49,6 +51,7 @@ class DeviceUtilTest(test.TestCase):
self.assertEqual(device_util.current(),
"/job:localhost/replica:0/task:0/device:CPU:0")
+ @test_util.run_deprecated_v1
def testCanonicalizeWithoutDefaultDevice(self):
self.assertEqual(
device_util.canonicalize("/cpu:0"),
diff --git a/tensorflow/python/distribute/input_ops_test.py b/tensorflow/python/distribute/input_ops_test.py
index d5f41b70931..dcf946ba477 100644
--- a/tensorflow/python/distribute/input_ops_test.py
+++ b/tensorflow/python/distribute/input_ops_test.py
@@ -24,6 +24,7 @@ from tensorflow.python.data.ops import dataset_ops
from tensorflow.python.data.ops import readers
from tensorflow.python.distribute import input_ops
from tensorflow.python.framework import errors
+from tensorflow.python.framework import test_util
from tensorflow.python.lib.io import python_io
from tensorflow.python.platform import test
from tensorflow.python.util import compat
@@ -96,6 +97,7 @@ class AutoShardDatasetTest(test.TestCase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element)
+ @test_util.run_deprecated_v1
def testTFRecordDataset(self):
dataset = readers.TFRecordDataset(self._createTFRecordFiles())
dataset = input_ops.auto_shard_dataset(
@@ -103,6 +105,7 @@ class AutoShardDatasetTest(test.TestCase):
self._verifySimpleShardingOutput(dataset, self._record)
+ @test_util.run_deprecated_v1
def testFlatMap(self):
dataset = dataset_ops.Dataset.from_tensor_slices(
self._createTFRecordFiles())
@@ -112,6 +115,7 @@ class AutoShardDatasetTest(test.TestCase):
self._verifySimpleShardingOutput(dataset, self._record)
+ @test_util.run_deprecated_v1
def testInterleave(self):
dataset = dataset_ops.Dataset.from_tensor_slices(
self._createTFRecordFiles())
@@ -124,6 +128,7 @@ class AutoShardDatasetTest(test.TestCase):
# contain records in order of files.
self._verifySimpleShardingOutput(dataset, self._record)
+ @test_util.run_deprecated_v1
def testListfiles(self):
filenames = self._createTFRecordFiles()
file_pattern = filenames[0].rsplit(os.sep, 1)[0] + "/tf_record.*.txt"
@@ -144,6 +149,7 @@ class AutoShardDatasetTest(test.TestCase):
self.evaluate(next_element)
self.assertAllEqual(expected, actual)
+ @test_util.run_deprecated_v1
def testComplexPipeline(self):
# Setup a complex input pipeline.
batch_size = 2
@@ -183,6 +189,7 @@ class AutoShardDatasetTest(test.TestCase):
self.assertAllEqual(sorted(expected), sorted(actual))
+ @test_util.run_deprecated_v1
def testZip(self):
dataset1 = readers.TFRecordDataset(self._createTFRecordFiles())
dataset2 = readers.TextLineDataset(self._createTextFiles())
@@ -193,6 +200,7 @@ class AutoShardDatasetTest(test.TestCase):
record_fn = lambda r, f: (self._record(r, f), self._text_line(r, f))
self._verifySimpleShardingOutput(dataset, record_fn)
+ @test_util.run_deprecated_v1
def testConcat(self):
dataset1 = readers.TFRecordDataset(self._createTFRecordFiles())
dataset2 = readers.TextLineDataset(self._createTextFiles())
@@ -213,6 +221,7 @@ class AutoShardDatasetTest(test.TestCase):
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element)
+ @test_util.run_deprecated_v1
def testTextLineReader(self):
dataset = readers.TextLineDataset(self._createTextFiles())
dataset = input_ops.auto_shard_dataset(
@@ -220,6 +229,7 @@ class AutoShardDatasetTest(test.TestCase):
self._verifySimpleShardingOutput(dataset, self._text_line)
+ @test_util.run_deprecated_v1
def testTextLineReaderWithFlatMap(self):
dataset = dataset_ops.Dataset.from_tensor_slices(self._createTextFiles())
dataset = dataset.flat_map(readers.TextLineDataset)
@@ -228,6 +238,7 @@ class AutoShardDatasetTest(test.TestCase):
self._verifySimpleShardingOutput(dataset, self._text_line)
+ @test_util.run_deprecated_v1
def testFixedLengthReader(self):
dataset = readers.FixedLengthRecordDataset(
self._createFixedLengthRecordFiles(), self._record_bytes)
@@ -236,6 +247,7 @@ class AutoShardDatasetTest(test.TestCase):
self._verifySimpleShardingOutput(dataset, self._fixed_length_record)
+ @test_util.run_deprecated_v1
def testFixedLengthReaderWithFlatMap(self):
dataset = dataset_ops.Dataset.from_tensor_slices(
self._createFixedLengthRecordFiles())
diff --git a/tensorflow/python/eager/function_gradients_test.py b/tensorflow/python/eager/function_gradients_test.py
index 1ba596573f9..9b83f57089a 100644
--- a/tensorflow/python/eager/function_gradients_test.py
+++ b/tensorflow/python/eager/function_gradients_test.py
@@ -187,6 +187,7 @@ class FunctionGradientsTest(test.TestCase, parameterized.TestCase):
self.assertAllEqual(2, g(constant_op.constant(2.)))
+ @test_util.run_deprecated_v1
def testGraphModeEagerGradError(self):
with context.graph_mode():
def f():
diff --git a/tensorflow/python/eager/function_test.py b/tensorflow/python/eager/function_test.py
index a206b1f7911..e47c5083a39 100644
--- a/tensorflow/python/eager/function_test.py
+++ b/tensorflow/python/eager/function_test.py
@@ -1283,6 +1283,7 @@ class FunctionTest(test.TestCase, parameterized.TestCase):
defined.get_concrete_function(
tensor_spec.TensorSpec(shape=(3,), dtype=dtypes.float32))
+ @test_util.run_deprecated_v1
def testInputSignatureForFunctionWithNonTensorInputsNotAllowed(self):
def foo(a, training=True):
diff --git a/tensorflow/python/eager/graph_only_ops_test.py b/tensorflow/python/eager/graph_only_ops_test.py
index 3aedf5fee1c..914b4d9a95a 100644
--- a/tensorflow/python/eager/graph_only_ops_test.py
+++ b/tensorflow/python/eager/graph_only_ops_test.py
@@ -29,12 +29,14 @@ from tensorflow.python.platform import test
class GraphOnlyOpsTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testGraphZerosLike(self):
x = np.array([[1, 2, 3], [4, 5, 6]], dtype=np.int32)
z_tf = graph_only_ops.graph_zeros_like(x)
with self.cached_session():
self.assertAllClose(np.zeros((2, 3)), self.evaluate(z_tf))
+ @test_util.run_deprecated_v1
def testGraphPlaceholder(self):
x_tf = graph_only_ops.graph_placeholder(dtypes.int32, shape=(1,))
y_tf = math_ops.square(x_tf)
diff --git a/tensorflow/python/feature_column/feature_column_test.py b/tensorflow/python/feature_column/feature_column_test.py
index 2c70d668103..daa0a3b3a4b 100644
--- a/tensorflow/python/feature_column/feature_column_test.py
+++ b/tensorflow/python/feature_column/feature_column_test.py
@@ -170,6 +170,7 @@ class LazyColumnTest(test.TestCase):
TypeError, '"key" must be either a "str" or "_FeatureColumn".'):
builder.get(NotAFeatureColumn())
+ @test_util.run_deprecated_v1
def test_expand_dim_rank_1_sparse_tensor_empty_batch(self):
# empty 1-D sparse tensor:
builder = _LazyBuilder(features={'a': sparse_tensor.SparseTensor(
@@ -185,6 +186,7 @@ class LazyColumnTest(test.TestCase):
class NumericColumnTest(test.TestCase):
+ @test_util.run_deprecated_v1
def test_defaults(self):
a = fc._numeric_column('aaa')
self.assertEqual('aaa', a.key)
@@ -263,6 +265,7 @@ class NumericColumnTest(test.TestCase):
'aaa': parsing_ops.FixedLenFeature((2, 3), dtype=dtypes.int32)
}, a._parse_example_spec)
+ @test_util.run_deprecated_v1
def test_parse_example_no_default_value(self):
price = fc._numeric_column('price', shape=[2])
data = example_pb2.Example(features=feature_pb2.Features(
@@ -278,6 +281,7 @@ class NumericColumnTest(test.TestCase):
with self.cached_session():
self.assertAllEqual([[20., 110.]], features['price'].eval())
+ @test_util.run_deprecated_v1
def test_parse_example_with_default_value(self):
price = fc._numeric_column('price', shape=[2], default_value=11.)
data = example_pb2.Example(features=feature_pb2.Features(
@@ -304,6 +308,7 @@ class NumericColumnTest(test.TestCase):
with self.assertRaisesRegexp(TypeError, 'must be a callable'):
fc._numeric_column('price', normalizer_fn='NotACallable')
+ @test_util.run_deprecated_v1
def test_normalizer_fn_transform_feature(self):
def _increment_two(input_tensor):
@@ -314,6 +319,7 @@ class NumericColumnTest(test.TestCase):
with self.cached_session():
self.assertAllEqual([[3., 4.], [7., 8.]], output[price].eval())
+ @test_util.run_deprecated_v1
def test_get_dense_tensor(self):
def _increment_two(input_tensor):
@@ -333,6 +339,7 @@ class NumericColumnTest(test.TestCase):
with self.assertRaisesRegexp(ValueError, 'must be a Tensor'):
price._transform_feature(builder)
+ @test_util.run_deprecated_v1
def test_deep_copy(self):
a = fc._numeric_column('aaa', shape=[1, 2], default_value=[[3., 2.]])
a_copy = copy.deepcopy(a)
@@ -345,6 +352,7 @@ class NumericColumnTest(test.TestCase):
'aaa', shape=[1, 2], default_value=np.array([[3., 2.]]))
self.assertEqual(a.default_value, ((3., 2.),))
+ @test_util.run_deprecated_v1
def test_linear_model(self):
price = fc._numeric_column('price')
with ops.Graph().as_default():
@@ -359,6 +367,7 @@ class NumericColumnTest(test.TestCase):
sess.run(price_var.assign([[10.]]))
self.assertAllClose([[10.], [50.]], self.evaluate(predictions))
+ @test_util.run_deprecated_v1
def test_keras_linear_model(self):
price = fc._numeric_column('price')
with ops.Graph().as_default():
@@ -433,6 +442,7 @@ class BucketizedColumnTest(test.TestCase):
# Column 'aaa` has shape [2] times three buckets -> num_buckets=6.
self.assertEqual(6, b._num_buckets)
+ @test_util.run_deprecated_v1
def test_parse_example(self):
price = fc._numeric_column('price', shape=[2])
bucketized_price = fc._bucketized_column(price, boundaries=[0, 50])
@@ -449,6 +459,7 @@ class BucketizedColumnTest(test.TestCase):
with self.cached_session():
self.assertAllEqual([[20., 110.]], features['price'].eval())
+ @test_util.run_deprecated_v1
def test_transform_feature(self):
price = fc._numeric_column('price', shape=[2])
bucketized_price = fc._bucketized_column(price, boundaries=[0, 2, 4, 6])
@@ -531,6 +542,7 @@ class BucketizedColumnTest(test.TestCase):
with self.assertRaisesRegexp(ValueError, 'must be a Tensor'):
bucketized_price._transform_feature(builder)
+ @test_util.run_deprecated_v1
def test_deep_copy(self):
a = fc._numeric_column('aaa', shape=[2])
a_bucketized = fc._bucketized_column(a, boundaries=[0, 1])
@@ -658,6 +670,7 @@ class BucketizedColumnTest(test.TestCase):
class HashedCategoricalColumnTest(test.TestCase):
+ @test_util.run_deprecated_v1
def test_defaults(self):
a = fc._categorical_column_with_hash_bucket('aaa', 10)
self.assertEqual('aaa', a.name)
@@ -685,6 +698,7 @@ class HashedCategoricalColumnTest(test.TestCase):
with self.assertRaisesRegexp(ValueError, 'dtype must be string or integer'):
fc._categorical_column_with_hash_bucket('aaa', 10, dtype=dtypes.float32)
+ @test_util.run_deprecated_v1
def test_deep_copy(self):
original = fc._categorical_column_with_hash_bucket('aaa', 10)
for column in (original, copy.deepcopy(original)):
@@ -705,6 +719,7 @@ class HashedCategoricalColumnTest(test.TestCase):
'aaa': parsing_ops.VarLenFeature(dtypes.int32)
}, a._parse_example_spec)
+ @test_util.run_deprecated_v1
def test_parse_example(self):
a = fc._categorical_column_with_hash_bucket('aaa', 10)
data = example_pb2.Example(features=feature_pb2.Features(
@@ -726,6 +741,7 @@ class HashedCategoricalColumnTest(test.TestCase):
dense_shape=[1, 2]),
features['aaa'].eval())
+ @test_util.run_deprecated_v1
def test_strings_should_be_hashed(self):
hashed_sparse = fc._categorical_column_with_hash_bucket('wire', 10)
wire_tensor = sparse_tensor.SparseTensor(
@@ -781,6 +797,7 @@ class HashedCategoricalColumnTest(test.TestCase):
with self.assertRaisesRegexp(ValueError, 'dtype must be compatible'):
builder.get(hashed_sparse)
+ @test_util.run_deprecated_v1
def test_ints_should_be_hashed(self):
hashed_sparse = fc._categorical_column_with_hash_bucket(
'wire', 10, dtype=dtypes.int64)
@@ -795,6 +812,7 @@ class HashedCategoricalColumnTest(test.TestCase):
with self.cached_session():
self.assertAllEqual(expected_values, output.values.eval())
+ @test_util.run_deprecated_v1
def test_int32_64_is_compatible(self):
hashed_sparse = fc._categorical_column_with_hash_bucket(
'wire', 10, dtype=dtypes.int64)
@@ -809,6 +827,7 @@ class HashedCategoricalColumnTest(test.TestCase):
with self.cached_session():
self.assertAllEqual(expected_values, output.values.eval())
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors(self):
hashed_sparse = fc._categorical_column_with_hash_bucket('wire', 10)
builder = _LazyBuilder({
@@ -837,6 +856,7 @@ class HashedCategoricalColumnTest(test.TestCase):
[], ops.get_collection(ops.GraphKeys.GLOBAL_VARIABLES))
self.assertItemsEqual([], ops.get_collection('my_weights'))
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_dense_input(self):
hashed_sparse = fc._categorical_column_with_hash_bucket('wire', 10)
builder = _LazyBuilder({'wire': (('omar', ''), ('stringer', 'marlo'))})
@@ -844,6 +864,7 @@ class HashedCategoricalColumnTest(test.TestCase):
self.assertIsNone(id_weight_pair.weight_tensor)
self.assertEqual(builder.get(hashed_sparse), id_weight_pair.id_tensor)
+ @test_util.run_deprecated_v1
def test_linear_model(self):
wire_column = fc._categorical_column_with_hash_bucket('wire', 4)
self.assertEqual(4, wire_column._num_buckets)
@@ -866,6 +887,7 @@ class HashedCategoricalColumnTest(test.TestCase):
# 'skywalker' -> 2, 'omar' -> 2: wire_var[2] + wire_var[2] = 3+3 = 6
self.assertAllClose(((4.,), (6.,)), self.evaluate(predictions))
+ @test_util.run_deprecated_v1
def test_keras_linear_model(self):
wire_column = fc._categorical_column_with_hash_bucket('wire', 4)
self.assertEqual(4, wire_column._num_buckets)
@@ -975,6 +997,7 @@ class CrossedColumnTest(test.TestCase):
crossed = fc._crossed_column([b, 'c'], 15)
self.assertEqual(15, crossed._num_buckets)
+ @test_util.run_deprecated_v1
def test_deep_copy(self):
a = fc._numeric_column('a', dtype=dtypes.int32)
b = fc._bucketized_column(a, boundaries=[0, 1])
@@ -985,6 +1008,7 @@ class CrossedColumnTest(test.TestCase):
self.assertEqual(15, crossed2_copy.hash_bucket_size)
self.assertEqual(5, crossed2_copy.hash_key)
+ @test_util.run_deprecated_v1
def test_parse_example(self):
price = fc._numeric_column('price', shape=[2])
bucketized_price = fc._bucketized_column(price, boundaries=[0, 50])
@@ -1011,6 +1035,7 @@ class CrossedColumnTest(test.TestCase):
self.assertAllEqual([b'omar', b'stringer'], wire_sparse.values.eval())
self.assertAllEqual([1, 2], wire_sparse.dense_shape.eval())
+ @test_util.run_deprecated_v1
def test_transform_feature(self):
price = fc._numeric_column('price', shape=[2])
bucketized_price = fc._bucketized_column(price, boundaries=[0, 50])
@@ -1034,6 +1059,7 @@ class CrossedColumnTest(test.TestCase):
self.assertIn(val, list(range(hash_bucket_size)))
self.assertAllEqual([2, 4], output_val.dense_shape)
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors(self):
a = fc._numeric_column('a', dtype=dtypes.int32, shape=(2,))
b = fc._bucketized_column(a, boundaries=(0, 1))
@@ -1101,6 +1127,7 @@ class CrossedColumnTest(test.TestCase):
self.assertAllEqual(expected_values, id_tensor_eval.values)
self.assertAllEqual((2, 4), id_tensor_eval.dense_shape)
+ @test_util.run_deprecated_v1
def test_linear_model(self):
"""Tests linear_model.
@@ -1182,6 +1209,7 @@ class CrossedColumnTest(test.TestCase):
dense_shape=(2, 2)),
}, (crossed,))
+ @test_util.run_deprecated_v1
def test_keras_linear_model(self):
"""Tests _LinearModel.
@@ -1854,6 +1882,7 @@ class LinearModelTest(test.TestCase):
features['price2']: [[1.], [5.]],
})
+ @test_util.run_deprecated_v1
def test_with_1d_sparse_tensor(self):
price = fc._numeric_column('price')
price_buckets = fc._bucketized_column(
@@ -1889,6 +1918,7 @@ class LinearModelTest(test.TestCase):
self.assertAllClose([[10 - 1000 + 5.], [1000 - 10 + 5.]],
self.evaluate(net))
+ @test_util.run_deprecated_v1
def test_with_1d_unknown_shape_sparse_tensor(self):
price = fc._numeric_column('price')
price_buckets = fc._bucketized_column(
@@ -1936,6 +1966,7 @@ class LinearModelTest(test.TestCase):
features['country']: country_data
}))
+ @test_util.run_deprecated_v1
def test_with_rank_0_feature(self):
price = fc._numeric_column('price')
features = {
@@ -2488,6 +2519,7 @@ class _LinearModelTest(test.TestCase):
features['price2']: [[1.], [5.]],
})
+ @test_util.run_deprecated_v1
def test_with_1d_sparse_tensor(self):
price = fc._numeric_column('price')
price_buckets = fc._bucketized_column(
@@ -2529,6 +2561,7 @@ class _LinearModelTest(test.TestCase):
self.assertAllClose([[10 - 1000 + 5.], [1000 - 10 + 5.]],
self.evaluate(net))
+ @test_util.run_deprecated_v1
def test_with_1d_unknown_shape_sparse_tensor(self):
price = fc._numeric_column('price')
price_buckets = fc._bucketized_column(
@@ -2575,6 +2608,7 @@ class _LinearModelTest(test.TestCase):
features['country']: country_data
}))
+ @test_util.run_deprecated_v1
def test_with_rank_0_feature(self):
price = fc._numeric_column('price')
features = {
@@ -2815,6 +2849,7 @@ class FunctionalInputLayerTest(test.TestCase):
variables_lib.Variable)
self.assertAllEqual(cols_to_vars[some_embedding_column][0].shape, [5, 10])
+ @test_util.run_deprecated_v1
def test_fills_cols_to_vars_shared_embedding(self):
# Provide 5 DenseColumn's to input_layer: a NumericColumn, a
# BucketizedColumn, an EmbeddingColumn, two SharedEmbeddingColumns. The
@@ -3012,6 +3047,7 @@ class FunctionalInputLayerTest(test.TestCase):
expected_var_names,
[v.name for v in ops.get_collection(ops.GraphKeys.GLOBAL_VARIABLES)])
+ @test_util.run_deprecated_v1
def test_multiple_layers_with_same_shared_embedding_column(self):
categorical_column_a = fc._categorical_column_with_identity(
key='aaa', num_buckets=3)
@@ -3045,6 +3081,7 @@ class FunctionalInputLayerTest(test.TestCase):
['input_layer/aaa_bbb_shared_embedding/embedding_weights:0'],
[v.name for v in ops.get_collection(ops.GraphKeys.GLOBAL_VARIABLES)])
+ @test_util.run_deprecated_v1
def test_multiple_layers_with_same_shared_embedding_column_diff_graphs(self):
categorical_column_a = fc._categorical_column_with_identity(
key='aaa', num_buckets=3)
@@ -3096,6 +3133,7 @@ class FunctionalInputLayerTest(test.TestCase):
['input_layer/aaa_bbb_shared_embedding/embedding_weights:0'],
[v.name for v in ops.get_collection(ops.GraphKeys.GLOBAL_VARIABLES)])
+ @test_util.run_deprecated_v1
def test_with_1d_sparse_tensor(self):
embedding_values = (
(1., 2., 3., 4., 5.), # id 0
@@ -3146,6 +3184,7 @@ class FunctionalInputLayerTest(test.TestCase):
[1., 0., 0., 1., 2., 3., 4., 5., 12.]],
sess.run(net))
+ @test_util.run_deprecated_v1
def test_with_1d_unknown_shape_sparse_tensor(self):
embedding_values = (
(1., 2.), # id 0
@@ -3205,6 +3244,7 @@ class FunctionalInputLayerTest(test.TestCase):
features['country']: country_data
}))
+ @test_util.run_deprecated_v1
def test_with_rank_0_feature(self):
# price has 1 dimension in input_layer
price = fc._numeric_column('price')
@@ -3335,6 +3375,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
'python/feature_column/testdata/wire_vocabulary.txt')
self._wire_vocabulary_size = 3
+ @test_util.run_deprecated_v1
def test_defaults(self):
column = fc._categorical_column_with_vocabulary_file(
key='aaa', vocabulary_file='path_to_file', vocabulary_size=3)
@@ -3351,6 +3392,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
fc._categorical_column_with_vocabulary_file(
key=('aaa',), vocabulary_file='path_to_file', vocabulary_size=3)
+ @test_util.run_deprecated_v1
def test_all_constructor_args(self):
column = fc._categorical_column_with_vocabulary_file(
key='aaa',
@@ -3363,6 +3405,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
'aaa': parsing_ops.VarLenFeature(dtypes.int32)
}, column._parse_example_spec)
+ @test_util.run_deprecated_v1
def test_deep_copy(self):
original = fc._categorical_column_with_vocabulary_file(
key='aaa',
@@ -3387,6 +3430,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
fc._categorical_column_with_vocabulary_file(
key='aaa', vocabulary_file='', vocabulary_size=3)
+ @test_util.run_deprecated_v1
def test_invalid_vocabulary_file(self):
column = fc._categorical_column_with_vocabulary_file(
key='aaa', vocabulary_file='file_does_not_exist', vocabulary_size=10)
@@ -3411,6 +3455,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
vocabulary_file=self._wire_vocabulary_file_name,
vocabulary_size=0)
+ @test_util.run_deprecated_v1
def test_too_large_vocabulary_size(self):
column = fc._categorical_column_with_vocabulary_file(
key='aaa',
@@ -3477,6 +3522,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
with self.assertRaisesRegexp(ValueError, 'dtype must be compatible'):
column._get_sparse_tensors(_LazyBuilder({'aaa': inputs}))
+ @test_util.run_deprecated_v1
def test_parse_example(self):
a = fc._categorical_column_with_vocabulary_file(
key='aaa', vocabulary_file='path_to_file', vocabulary_size=3)
@@ -3499,6 +3545,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
dense_shape=[1, 2]),
features['aaa'].eval())
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors(self):
column = fc._categorical_column_with_vocabulary_file(
key='aaa',
@@ -3519,6 +3566,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
dense_shape=inputs.dense_shape),
id_weight_pair.id_tensor.eval())
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_none_vocabulary_size(self):
column = fc._categorical_column_with_vocabulary_file(
key='aaa', vocabulary_file=self._wire_vocabulary_file_name)
@@ -3537,6 +3585,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
dense_shape=inputs.dense_shape),
id_weight_pair.id_tensor.eval())
+ @test_util.run_deprecated_v1
def test_transform_feature(self):
column = fc._categorical_column_with_vocabulary_file(
key='aaa',
@@ -3573,6 +3622,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
[], ops.get_collection(ops.GraphKeys.GLOBAL_VARIABLES))
self.assertItemsEqual([], ops.get_collection('my_weights'))
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_dense_input(self):
column = fc._categorical_column_with_vocabulary_file(
key='aaa',
@@ -3592,6 +3642,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
dense_shape=(2, 2)),
id_weight_pair.id_tensor.eval())
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_default_value_in_vocabulary(self):
column = fc._categorical_column_with_vocabulary_file(
key='aaa',
@@ -3613,6 +3664,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
dense_shape=inputs.dense_shape),
id_weight_pair.id_tensor.eval())
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_with_oov_buckets(self):
column = fc._categorical_column_with_vocabulary_file(
key='aaa',
@@ -3634,6 +3686,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
dense_shape=inputs.dense_shape),
id_weight_pair.id_tensor.eval())
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_small_vocabulary_size(self):
# 'marlo' is the last entry in our vocabulary file, so be setting
# `vocabulary_size` to 1 less than number of entries in file, we take
@@ -3657,6 +3710,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
dense_shape=inputs.dense_shape),
id_weight_pair.id_tensor.eval())
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_int32(self):
column = fc._categorical_column_with_vocabulary_file(
key='aaa',
@@ -3678,6 +3732,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
dense_shape=inputs.dense_shape),
id_weight_pair.id_tensor.eval())
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_int32_dense_input(self):
default_value = -100
column = fc._categorical_column_with_vocabulary_file(
@@ -3700,6 +3755,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
dense_shape=(3, 3)),
id_weight_pair.id_tensor.eval())
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_int32_with_oov_buckets(self):
column = fc._categorical_column_with_vocabulary_file(
key='aaa',
@@ -3722,6 +3778,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
dense_shape=inputs.dense_shape),
id_weight_pair.id_tensor.eval())
+ @test_util.run_deprecated_v1
def test_linear_model(self):
wire_column = fc._categorical_column_with_vocabulary_file(
key='wire',
@@ -3748,6 +3805,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
# 'skywalker' -> 3, 'omar' -> 0: wire_var[3] + wire_var[0] = 4+1 = 5
self.assertAllClose(((3.,), (5.,)), self.evaluate(predictions))
+ @test_util.run_deprecated_v1
def test_keras_linear_model(self):
wire_column = fc._categorical_column_with_vocabulary_file(
key='wire',
@@ -3805,6 +3863,7 @@ class VocabularyListCategoricalColumnTest(test.TestCase):
'aaa': parsing_ops.VarLenFeature(dtypes.int64)
}, column._parse_example_spec)
+ @test_util.run_deprecated_v1
def test_all_constructor_args(self):
column = fc._categorical_column_with_vocabulary_list(
key='aaa',
@@ -3816,6 +3875,7 @@ class VocabularyListCategoricalColumnTest(test.TestCase):
'aaa': parsing_ops.VarLenFeature(dtypes.int32)
}, column._parse_example_spec)
+ @test_util.run_deprecated_v1
def test_deep_copy(self):
original = fc._categorical_column_with_vocabulary_list(
key='aaa', vocabulary_list=(12, 24, 36), dtype=dtypes.int32)
@@ -3904,6 +3964,7 @@ class VocabularyListCategoricalColumnTest(test.TestCase):
with self.assertRaisesRegexp(ValueError, 'dtype must be compatible'):
column._get_sparse_tensors(_LazyBuilder({'aaa': inputs}))
+ @test_util.run_deprecated_v1
def test_parse_example_string(self):
a = fc._categorical_column_with_vocabulary_list(
key='aaa', vocabulary_list=('omar', 'stringer', 'marlo'))
@@ -3926,6 +3987,7 @@ class VocabularyListCategoricalColumnTest(test.TestCase):
dense_shape=[1, 2]),
features['aaa'].eval())
+ @test_util.run_deprecated_v1
def test_parse_example_int(self):
a = fc._categorical_column_with_vocabulary_list(
key='aaa', vocabulary_list=(11, 21, 31))
@@ -3948,6 +4010,7 @@ class VocabularyListCategoricalColumnTest(test.TestCase):
dense_shape=[1, 2]),
features['aaa'].eval())
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors(self):
column = fc._categorical_column_with_vocabulary_list(
key='aaa', vocabulary_list=('omar', 'stringer', 'marlo'))
@@ -3966,6 +4029,7 @@ class VocabularyListCategoricalColumnTest(test.TestCase):
dense_shape=inputs.dense_shape),
id_weight_pair.id_tensor.eval())
+ @test_util.run_deprecated_v1
def test_transform_feature(self):
column = fc._categorical_column_with_vocabulary_list(
key='aaa', vocabulary_list=('omar', 'stringer', 'marlo'))
@@ -3998,6 +4062,7 @@ class VocabularyListCategoricalColumnTest(test.TestCase):
[], ops.get_collection(ops.GraphKeys.GLOBAL_VARIABLES))
self.assertItemsEqual([], ops.get_collection('my_weights'))
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_dense_input(self):
column = fc._categorical_column_with_vocabulary_list(
key='aaa', vocabulary_list=('omar', 'stringer', 'marlo'))
@@ -4015,6 +4080,7 @@ class VocabularyListCategoricalColumnTest(test.TestCase):
dense_shape=(2, 2)),
id_weight_pair.id_tensor.eval())
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_default_value_in_vocabulary(self):
column = fc._categorical_column_with_vocabulary_list(
key='aaa',
@@ -4035,6 +4101,7 @@ class VocabularyListCategoricalColumnTest(test.TestCase):
dense_shape=inputs.dense_shape),
id_weight_pair.id_tensor.eval())
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_with_oov_buckets(self):
column = fc._categorical_column_with_vocabulary_list(
key='aaa',
@@ -4055,6 +4122,7 @@ class VocabularyListCategoricalColumnTest(test.TestCase):
dense_shape=inputs.dense_shape),
id_weight_pair.id_tensor.eval())
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_int32(self):
column = fc._categorical_column_with_vocabulary_list(
key='aaa',
@@ -4075,6 +4143,7 @@ class VocabularyListCategoricalColumnTest(test.TestCase):
dense_shape=inputs.dense_shape),
id_weight_pair.id_tensor.eval())
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_int32_dense_input(self):
default_value = -100
column = fc._categorical_column_with_vocabulary_list(
@@ -4098,6 +4167,7 @@ class VocabularyListCategoricalColumnTest(test.TestCase):
dense_shape=(3, 3)),
id_weight_pair.id_tensor.eval())
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_int32_with_oov_buckets(self):
column = fc._categorical_column_with_vocabulary_list(
key='aaa',
@@ -4119,6 +4189,7 @@ class VocabularyListCategoricalColumnTest(test.TestCase):
dense_shape=inputs.dense_shape),
id_weight_pair.id_tensor.eval())
+ @test_util.run_deprecated_v1
def test_linear_model(self):
wire_column = fc._categorical_column_with_vocabulary_list(
key='aaa',
@@ -4144,6 +4215,7 @@ class VocabularyListCategoricalColumnTest(test.TestCase):
# 'skywalker' -> 3, 'omar' -> 0: wire_var[3] + wire_var[0] = 4+1 = 5
self.assertAllClose(((3.,), (5.,)), self.evaluate(predictions))
+ @test_util.run_deprecated_v1
def test_keras_linear_model(self):
wire_column = fc._categorical_column_with_vocabulary_list(
key='aaa',
@@ -4187,6 +4259,7 @@ class IdentityCategoricalColumnTest(test.TestCase):
with self.assertRaisesRegexp(ValueError, 'key must be a string.'):
fc._categorical_column_with_identity(key=('aaa',), num_buckets=3)
+ @test_util.run_deprecated_v1
def test_deep_copy(self):
original = fc._categorical_column_with_identity(key='aaa', num_buckets=3)
for column in (original, copy.deepcopy(original)):
@@ -4223,6 +4296,7 @@ class IdentityCategoricalColumnTest(test.TestCase):
with self.assertRaisesRegexp(ValueError, 'Invalid input, not integer'):
column._get_sparse_tensors(_LazyBuilder({'aaa': inputs}))
+ @test_util.run_deprecated_v1
def test_parse_example(self):
a = fc._categorical_column_with_identity(key='aaa', num_buckets=30)
data = example_pb2.Example(features=feature_pb2.Features(
@@ -4244,6 +4318,7 @@ class IdentityCategoricalColumnTest(test.TestCase):
dense_shape=[1, 2]),
features['aaa'].eval())
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors(self):
column = fc._categorical_column_with_identity(key='aaa', num_buckets=3)
inputs = sparse_tensor.SparseTensorValue(
@@ -4261,6 +4336,7 @@ class IdentityCategoricalColumnTest(test.TestCase):
dense_shape=inputs.dense_shape),
id_weight_pair.id_tensor.eval())
+ @test_util.run_deprecated_v1
def test_transform_feature(self):
column = fc._categorical_column_with_identity(key='aaa', num_buckets=3)
inputs = sparse_tensor.SparseTensorValue(
@@ -4291,6 +4367,7 @@ class IdentityCategoricalColumnTest(test.TestCase):
[], ops.get_collection(ops.GraphKeys.GLOBAL_VARIABLES))
self.assertItemsEqual([], ops.get_collection('my_weights'))
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_dense_input(self):
column = fc._categorical_column_with_identity(key='aaa', num_buckets=3)
id_weight_pair = column._get_sparse_tensors(
@@ -4307,6 +4384,7 @@ class IdentityCategoricalColumnTest(test.TestCase):
dense_shape=(2, 2)),
id_weight_pair.id_tensor.eval())
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_with_inputs_too_small(self):
column = fc._categorical_column_with_identity(key='aaa', num_buckets=3)
inputs = sparse_tensor.SparseTensorValue(
@@ -4320,6 +4398,7 @@ class IdentityCategoricalColumnTest(test.TestCase):
errors.OpError, 'assert_greater_or_equal_0'):
id_weight_pair.id_tensor.eval()
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_with_inputs_too_big(self):
column = fc._categorical_column_with_identity(key='aaa', num_buckets=3)
inputs = sparse_tensor.SparseTensorValue(
@@ -4333,6 +4412,7 @@ class IdentityCategoricalColumnTest(test.TestCase):
errors.OpError, 'assert_less_than_num_buckets'):
id_weight_pair.id_tensor.eval()
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_with_default_value(self):
column = fc._categorical_column_with_identity(
key='aaa', num_buckets=4, default_value=3)
@@ -4351,6 +4431,7 @@ class IdentityCategoricalColumnTest(test.TestCase):
dense_shape=inputs.dense_shape),
id_weight_pair.id_tensor.eval())
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_with_default_value_and_placeholder_inputs(self):
column = fc._categorical_column_with_identity(
key='aaa', num_buckets=4, default_value=3)
@@ -4376,6 +4457,7 @@ class IdentityCategoricalColumnTest(test.TestCase):
input_shape: (2, 2),
}))
+ @test_util.run_deprecated_v1
def test_linear_model(self):
column = fc._categorical_column_with_identity(key='aaa', num_buckets=3)
self.assertEqual(3, column._num_buckets)
@@ -4397,6 +4479,7 @@ class IdentityCategoricalColumnTest(test.TestCase):
# weight_var[2] + weight_var[1] = 3+2 = 5
self.assertAllClose(((1.,), (5.,)), self.evaluate(predictions))
+ @test_util.run_deprecated_v1
def test_keras_linear_model(self):
column = fc._categorical_column_with_identity(key='aaa', num_buckets=3)
self.assertEqual(3, column._num_buckets)
@@ -4548,6 +4631,7 @@ class IndicatorColumnTest(test.TestCase):
with self.cached_session():
self.assertAllEqual([[0., 1., 1., 0.]], self.evaluate(output))
+ @test_util.run_deprecated_v1
def test_deep_copy(self):
a = fc._categorical_column_with_hash_bucket('a', 4)
column = fc._indicator_column(a)
@@ -4556,6 +4640,7 @@ class IndicatorColumnTest(test.TestCase):
self.assertEqual(column.name, 'a_indicator')
self.assertEqual(column._variable_shape, [1, 4])
+ @test_util.run_deprecated_v1
def test_parse_example(self):
a = fc._categorical_column_with_vocabulary_list(
key='aaa', vocabulary_list=('omar', 'stringer', 'marlo'))
@@ -4579,6 +4664,7 @@ class IndicatorColumnTest(test.TestCase):
dense_shape=[1, 2]),
features['aaa'].eval())
+ @test_util.run_deprecated_v1
def test_transform(self):
a = fc._categorical_column_with_vocabulary_list(
key='aaa', vocabulary_list=('omar', 'stringer', 'marlo'))
@@ -4594,6 +4680,7 @@ class IndicatorColumnTest(test.TestCase):
self.assertAllEqual([[0, 0, 1], [1, 0, 0]],
self.evaluate(indicator_tensor))
+ @test_util.run_deprecated_v1
def test_transform_with_weighted_column(self):
# Github issue 12557
ids = fc._categorical_column_with_vocabulary_list(
@@ -4608,6 +4695,7 @@ class IndicatorColumnTest(test.TestCase):
with _initialized_session():
self.assertAllEqual([[6., 4., 3.]], self.evaluate(indicator_tensor))
+ @test_util.run_deprecated_v1
def test_transform_with_missing_value_in_weighted_column(self):
# Github issue 12583
ids = fc._categorical_column_with_vocabulary_list(
@@ -4622,6 +4710,7 @@ class IndicatorColumnTest(test.TestCase):
with _initialized_session():
self.assertAllEqual([[0., 4., 2.]], self.evaluate(indicator_tensor))
+ @test_util.run_deprecated_v1
def test_transform_with_missing_value_in_categorical_column(self):
# Github issue 12583
ids = fc._categorical_column_with_vocabulary_list(
@@ -4634,6 +4723,7 @@ class IndicatorColumnTest(test.TestCase):
with _initialized_session():
self.assertAllEqual([[0., 1., 1.]], self.evaluate(indicator_tensor))
+ @test_util.run_deprecated_v1
def test_linear_model(self):
animal = fc._indicator_column(
fc._categorical_column_with_identity('animal', num_buckets=4))
@@ -4653,6 +4743,7 @@ class IndicatorColumnTest(test.TestCase):
weight_var.assign([[1.], [2.], [3.], [4.]]).eval()
self.assertAllClose([[2. + 3.]], self.evaluate(predictions))
+ @test_util.run_deprecated_v1
def test_keras_linear_model(self):
animal = fc._indicator_column(
fc._categorical_column_with_identity('animal', num_buckets=4))
@@ -4672,6 +4763,7 @@ class IndicatorColumnTest(test.TestCase):
weight_var.assign([[1.], [2.], [3.], [4.]]).eval()
self.assertAllClose([[2. + 3.]], self.evaluate(predictions))
+ @test_util.run_deprecated_v1
def test_input_layer(self):
animal = fc._indicator_column(
fc._categorical_column_with_identity('animal', num_buckets=4))
@@ -4688,6 +4780,7 @@ class IndicatorColumnTest(test.TestCase):
class EmbeddingColumnTest(test.TestCase):
+ @test_util.run_deprecated_v1
def test_defaults(self):
categorical_column = fc._categorical_column_with_identity(
key='aaa', num_buckets=3)
@@ -4709,6 +4802,7 @@ class EmbeddingColumnTest(test.TestCase):
'aaa': parsing_ops.VarLenFeature(dtypes.int64)
}, embedding_column._parse_example_spec)
+ @test_util.run_deprecated_v1
def test_all_constructor_args(self):
categorical_column = fc._categorical_column_with_identity(
key='aaa', num_buckets=3)
@@ -4737,6 +4831,7 @@ class EmbeddingColumnTest(test.TestCase):
'aaa': parsing_ops.VarLenFeature(dtypes.int64)
}, embedding_column._parse_example_spec)
+ @test_util.run_deprecated_v1
def test_deep_copy(self):
categorical_column = fc._categorical_column_with_identity(
key='aaa', num_buckets=3)
@@ -4770,6 +4865,7 @@ class EmbeddingColumnTest(test.TestCase):
'aaa': parsing_ops.VarLenFeature(dtypes.int64)
}, embedding_column._parse_example_spec)
+ @test_util.run_deprecated_v1
def test_invalid_initializer(self):
categorical_column = fc._categorical_column_with_identity(
key='aaa', num_buckets=3)
@@ -4777,6 +4873,7 @@ class EmbeddingColumnTest(test.TestCase):
fc._embedding_column(
categorical_column, dimension=2, initializer='not_fn')
+ @test_util.run_deprecated_v1
def test_parse_example(self):
a = fc._categorical_column_with_vocabulary_list(
key='aaa', vocabulary_list=('omar', 'stringer', 'marlo'))
@@ -4800,6 +4897,7 @@ class EmbeddingColumnTest(test.TestCase):
dense_shape=[1, 2]),
features['aaa'].eval())
+ @test_util.run_deprecated_v1
def test_transform_feature(self):
a = fc._categorical_column_with_identity(key='aaa', num_buckets=3)
a_embedded = fc._embedding_column(a, dimension=2)
@@ -4816,6 +4914,7 @@ class EmbeddingColumnTest(test.TestCase):
_assert_sparse_tensor_value(self, self.evaluate(output_a),
self.evaluate(output_embedded))
+ @test_util.run_deprecated_v1
def test_get_dense_tensor(self):
# Inputs.
vocabulary_size = 3
@@ -4875,6 +4974,7 @@ class EmbeddingColumnTest(test.TestCase):
self.assertAllEqual(embedding_values, global_vars[0].eval())
self.assertAllEqual(expected_lookups, self.evaluate(embedding_lookup))
+ @test_util.run_deprecated_v1
def test_get_dense_tensor_3d(self):
# Inputs.
vocabulary_size = 4
@@ -4936,6 +5036,7 @@ class EmbeddingColumnTest(test.TestCase):
self.assertAllEqual(embedding_values, global_vars[0].eval())
self.assertAllEqual(expected_lookups, self.evaluate(embedding_lookup))
+ @test_util.run_deprecated_v1
def test_get_dense_tensor_weight_collections(self):
sparse_input = sparse_tensor.SparseTensorValue(
# example 0, ids [2]
@@ -4965,6 +5066,7 @@ class EmbeddingColumnTest(test.TestCase):
self.assertItemsEqual(
('embedding_weights:0',), tuple([v.name for v in my_vars]))
+ @test_util.run_deprecated_v1
def test_get_dense_tensor_placeholder_inputs(self):
# Inputs.
vocabulary_size = 3
@@ -5036,6 +5138,7 @@ class EmbeddingColumnTest(test.TestCase):
input_shape: sparse_input.dense_shape,
}))
+ @test_util.run_deprecated_v1
def test_get_dense_tensor_restore_from_ckpt(self):
# Inputs.
vocabulary_size = 3
@@ -5094,6 +5197,7 @@ class EmbeddingColumnTest(test.TestCase):
self.assertAllEqual(embedding_values, global_vars[0].eval())
self.assertAllEqual(expected_lookups, self.evaluate(embedding_lookup))
+ @test_util.run_deprecated_v1
def test_linear_model(self):
# Inputs.
batch_size = 4
@@ -5173,6 +5277,7 @@ class EmbeddingColumnTest(test.TestCase):
self.assertAllClose(((94.,), (29.,), (0.,), (42.,)),
self.evaluate(predictions))
+ @test_util.run_deprecated_v1
def test_keras_linear_model(self):
# Inputs.
batch_size = 4
@@ -5252,6 +5357,7 @@ class EmbeddingColumnTest(test.TestCase):
self.assertAllClose(((94.,), (29.,), (0.,), (42.,)),
self.evaluate(predictions))
+ @test_util.run_deprecated_v1
def test_input_layer(self):
# Inputs.
vocabulary_size = 3
@@ -5313,6 +5419,7 @@ class EmbeddingColumnTest(test.TestCase):
self.assertAllEqual(embedding_values, trainable_vars[0].eval())
self.assertAllEqual(expected_lookups, self.evaluate(input_layer))
+ @test_util.run_deprecated_v1
def test_input_layer_not_trainable(self):
# Inputs.
vocabulary_size = 3
@@ -5376,6 +5483,7 @@ class EmbeddingColumnTest(test.TestCase):
class SharedEmbeddingColumnTest(test.TestCase):
+ @test_util.run_deprecated_v1
def test_defaults(self):
categorical_column_a = fc._categorical_column_with_identity(
key='aaa', num_buckets=3)
@@ -5420,6 +5528,7 @@ class SharedEmbeddingColumnTest(test.TestCase):
'bbb': parsing_ops.VarLenFeature(dtypes.int64)
}, embedding_column_b._parse_example_spec)
+ @test_util.run_deprecated_v1
def test_all_constructor_args(self):
categorical_column_a = fc._categorical_column_with_identity(
key='aaa', num_buckets=3)
@@ -5471,6 +5580,7 @@ class SharedEmbeddingColumnTest(test.TestCase):
'bbb': parsing_ops.VarLenFeature(dtypes.int64)
}, embedding_column_b._parse_example_spec)
+ @test_util.run_deprecated_v1
def test_deep_copy(self):
categorical_column_a = fc._categorical_column_with_identity(
key='aaa', num_buckets=3)
@@ -5509,6 +5619,7 @@ class SharedEmbeddingColumnTest(test.TestCase):
'aaa': parsing_ops.VarLenFeature(dtypes.int64)
}, embedding_column_a._parse_example_spec)
+ @test_util.run_deprecated_v1
def test_invalid_initializer(self):
categorical_column_a = fc._categorical_column_with_identity(
key='aaa', num_buckets=3)
@@ -5520,6 +5631,7 @@ class SharedEmbeddingColumnTest(test.TestCase):
dimension=2,
initializer='not_fn')
+ @test_util.run_deprecated_v1
def test_incompatible_column_type(self):
categorical_column_a = fc._categorical_column_with_identity(
key='aaa', num_buckets=3)
@@ -5535,6 +5647,7 @@ class SharedEmbeddingColumnTest(test.TestCase):
[categorical_column_a, categorical_column_b, categorical_column_c],
dimension=2)
+ @test_util.run_deprecated_v1
def test_weighted_categorical_column_ok(self):
categorical_column_a = fc._categorical_column_with_identity(
key='aaa', num_buckets=3)
@@ -5552,6 +5665,7 @@ class SharedEmbeddingColumnTest(test.TestCase):
[weighted_categorical_column_a, weighted_categorical_column_b],
dimension=2)
+ @test_util.run_deprecated_v1
def test_parse_example(self):
a = fc._categorical_column_with_vocabulary_list(
key='aaa', vocabulary_list=('omar', 'stringer', 'marlo'))
@@ -5589,6 +5703,7 @@ class SharedEmbeddingColumnTest(test.TestCase):
dense_shape=[1, 2]),
features['bbb'].eval())
+ @test_util.run_deprecated_v1
def test_transform_feature(self):
a = fc._categorical_column_with_identity(key='aaa', num_buckets=3)
b = fc._categorical_column_with_identity(key='bbb', num_buckets=3)
@@ -5615,6 +5730,7 @@ class SharedEmbeddingColumnTest(test.TestCase):
_assert_sparse_tensor_value(self, self.evaluate(output_b),
self.evaluate(output_b_embedded))
+ @test_util.run_deprecated_v1
def test_get_dense_tensor(self):
# Inputs.
vocabulary_size = 3
@@ -5683,6 +5799,7 @@ class SharedEmbeddingColumnTest(test.TestCase):
self.assertAllEqual(expected_lookups_a, self.evaluate(embedding_lookup_a))
self.assertAllEqual(expected_lookups_b, self.evaluate(embedding_lookup_b))
+ @test_util.run_deprecated_v1
def test_get_dense_tensor_weight_collections(self):
# Inputs.
vocabulary_size = 3
@@ -5735,6 +5852,7 @@ class SharedEmbeddingColumnTest(test.TestCase):
('input_layer/aaa_bbb_shared_embedding/embedding_weights:0',),
tuple(v.name for v in my_vars))
+ @test_util.run_deprecated_v1
def test_get_dense_tensor_placeholder_inputs(self):
# Inputs.
vocabulary_size = 3
@@ -5791,6 +5909,7 @@ class SharedEmbeddingColumnTest(test.TestCase):
with _initialized_session() as sess:
sess.run([embedding_lookup_a, embedding_lookup_b], feed_dict=feed_dict)
+ @test_util.run_deprecated_v1
def test_linear_model(self):
# Inputs.
batch_size = 2
@@ -5881,6 +6000,7 @@ class SharedEmbeddingColumnTest(test.TestCase):
# = [3*1 + 5*2, 3*0 +5*0] = [13, 0]
self.assertAllClose([[94. + 13.], [29.]], self.evaluate(predictions))
+ @test_util.run_deprecated_v1
def test_keras_linear_model(self):
# Inputs.
batch_size = 2
@@ -6048,15 +6168,18 @@ class SharedEmbeddingColumnTest(test.TestCase):
self.assertAllEqual(embedding_values, shared_embedding_vars[0].eval())
self.assertAllEqual(expected_lookups, self.evaluate(input_layer))
+ @test_util.run_deprecated_v1
def test_input_layer(self):
self._test_input_layer()
+ @test_util.run_deprecated_v1
def test_input_layer_no_trainable(self):
self._test_input_layer(trainable=False)
class WeightedCategoricalColumnTest(test.TestCase):
+ @test_util.run_deprecated_v1
def test_defaults(self):
column = fc._weighted_categorical_column(
categorical_column=fc._categorical_column_with_identity(
@@ -6070,6 +6193,7 @@ class WeightedCategoricalColumnTest(test.TestCase):
'values': parsing_ops.VarLenFeature(dtypes.float32)
}, column._parse_example_spec)
+ @test_util.run_deprecated_v1
def test_deep_copy(self):
"""Tests deepcopy of categorical_column_with_hash_bucket."""
original = fc._weighted_categorical_column(
@@ -6132,6 +6256,7 @@ class WeightedCategoricalColumnTest(test.TestCase):
ValueError, 'values is not in features dictionary'):
_transform_features({'ids': inputs}, (column,))
+ @test_util.run_deprecated_v1
def test_parse_example(self):
a = fc._categorical_column_with_vocabulary_list(
key='aaa', vocabulary_list=('omar', 'stringer', 'marlo'))
@@ -6167,6 +6292,7 @@ class WeightedCategoricalColumnTest(test.TestCase):
dense_shape=[1, 2]),
features['weights'].eval())
+ @test_util.run_deprecated_v1
def test_transform_features(self):
column = fc._weighted_categorical_column(
categorical_column=fc._categorical_column_with_identity(
@@ -6198,6 +6324,7 @@ class WeightedCategoricalColumnTest(test.TestCase):
values=np.array(weights.values, dtype=np.float32),
dense_shape=weights.dense_shape), self.evaluate(weight_tensor))
+ @test_util.run_deprecated_v1
def test_transform_features_dense_input(self):
column = fc._weighted_categorical_column(
categorical_column=fc._categorical_column_with_identity(
@@ -6225,6 +6352,7 @@ class WeightedCategoricalColumnTest(test.TestCase):
values=np.array(weights.values, dtype=np.float32),
dense_shape=weights.dense_shape), self.evaluate(weight_tensor))
+ @test_util.run_deprecated_v1
def test_transform_features_dense_weights(self):
column = fc._weighted_categorical_column(
categorical_column=fc._categorical_column_with_identity(
@@ -6252,6 +6380,7 @@ class WeightedCategoricalColumnTest(test.TestCase):
values=np.array((.5, 1., .1), dtype=np.float32),
dense_shape=(2, 2)), self.evaluate(weight_tensor))
+ @test_util.run_deprecated_v1
def test_keras_linear_model(self):
column = fc._weighted_categorical_column(
categorical_column=fc._categorical_column_with_identity(
@@ -6354,6 +6483,7 @@ class WeightedCategoricalColumnTest(test.TestCase):
# = 3*1 + 2*.1 = 3+.2 = 3.2
self.assertAllClose(((.5,), (3.2,)), self.evaluate(predictions))
+ @test_util.run_deprecated_v1
def test_linear_model(self):
column = fc._weighted_categorical_column(
categorical_column=fc._categorical_column_with_identity(
diff --git a/tensorflow/python/feature_column/feature_column_v2_test.py b/tensorflow/python/feature_column/feature_column_v2_test.py
index 3147754bee4..083cd526e46 100644
--- a/tensorflow/python/feature_column/feature_column_v2_test.py
+++ b/tensorflow/python/feature_column/feature_column_v2_test.py
@@ -218,6 +218,7 @@ class LazyColumnTest(test.TestCase):
TypeError, '"key" must be either a "str" or "FeatureColumn".'):
transformation_cache.get(NotAFeatureColumn(), None)
+ @test_util.run_deprecated_v1
def test_expand_dim_rank_1_sparse_tensor_empty_batch(self):
# empty 1-D sparse tensor:
transformation_cache = fc.FeatureTransformationCache(
@@ -237,6 +238,7 @@ class LazyColumnTest(test.TestCase):
class NumericColumnTest(test.TestCase):
+ @test_util.run_deprecated_v1
def test_defaults(self):
a = fc.numeric_column('aaa')
self.assertEqual('aaa', a.key)
@@ -315,6 +317,7 @@ class NumericColumnTest(test.TestCase):
'aaa': parsing_ops.FixedLenFeature((2, 3), dtype=dtypes.int32)
}, a.parse_example_spec)
+ @test_util.run_deprecated_v1
def test_parse_example_no_default_value(self):
price = fc.numeric_column('price', shape=[2])
data = example_pb2.Example(
@@ -331,6 +334,7 @@ class NumericColumnTest(test.TestCase):
self.assertAllEqual([[20., 110.]], self.evaluate(features['price']))
+ @test_util.run_deprecated_v1
def test_parse_example_with_default_value(self):
price = fc.numeric_column('price', shape=[2], default_value=11.)
data = example_pb2.Example(
@@ -360,6 +364,7 @@ class NumericColumnTest(test.TestCase):
with self.assertRaisesRegexp(TypeError, 'must be a callable'):
fc.numeric_column('price', normalizer_fn='NotACallable')
+ @test_util.run_deprecated_v1
def test_normalizer_fn_transform_feature(self):
def _increment_two(input_tensor):
@@ -372,6 +377,7 @@ class NumericColumnTest(test.TestCase):
self.assertAllEqual([[3., 4.], [7., 8.]], self.evaluate(output[price]))
+ @test_util.run_deprecated_v1
def test_get_dense_tensor(self):
def _increment_two(input_tensor):
@@ -395,6 +401,7 @@ class NumericColumnTest(test.TestCase):
with self.assertRaisesRegexp(ValueError, 'must be a Tensor'):
price.transform_feature(transformation_cache, None)
+ @test_util.run_deprecated_v1
def test_deep_copy(self):
a = fc.numeric_column('aaa', shape=[1, 2], default_value=[[3., 2.]])
a_copy = copy.deepcopy(a)
@@ -407,6 +414,7 @@ class NumericColumnTest(test.TestCase):
'aaa', shape=[1, 2], default_value=np.array([[3., 2.]]))
self.assertEqual(a.default_value, ((3., 2.),))
+ @test_util.run_deprecated_v1
def test_linear_model(self):
price = fc.numeric_column('price')
with ops.Graph().as_default():
@@ -435,6 +443,7 @@ class NumericColumnTest(test.TestCase):
sess.run(price_var.assign([[10.]]))
self.assertAllClose([[10.], [50.]], self.evaluate(predictions))
+ @test_util.run_deprecated_v1
def test_serialization(self):
def _increment_two(input_tensor):
@@ -519,6 +528,7 @@ class BucketizedColumnTest(test.TestCase):
# Column 'aaa` has shape [2] times three buckets -> num_buckets=6.
self.assertEqual(6, b.num_buckets)
+ @test_util.run_deprecated_v1
def test_parse_example(self):
price = fc.numeric_column('price', shape=[2])
bucketized_price = fc.bucketized_column(price, boundaries=[0, 50])
@@ -536,6 +546,7 @@ class BucketizedColumnTest(test.TestCase):
self.assertAllEqual([[20., 110.]], self.evaluate(features['price']))
+ @test_util.run_deprecated_v1
def test_transform_feature(self):
price = fc.numeric_column('price', shape=[2])
bucketized_price = fc.bucketized_column(price, boundaries=[0, 2, 4, 6])
@@ -639,6 +650,7 @@ class BucketizedColumnTest(test.TestCase):
with self.assertRaisesRegexp(ValueError, 'must be a Tensor'):
bucketized_price.transform_feature(transformation_cache, None)
+ @test_util.run_deprecated_v1
def test_deep_copy(self):
a = fc.numeric_column('aaa', shape=[2])
a_bucketized = fc.bucketized_column(a, boundaries=[0, 1])
@@ -789,6 +801,7 @@ class BucketizedColumnTest(test.TestCase):
self.assertAllClose([[11.], [21.], [41.], [51.]],
self.evaluate(predictions))
+ @test_util.run_deprecated_v1
def test_serialization(self):
price = fc.numeric_column('price', shape=[2])
bucketized_price = fc.bucketized_column(price, boundaries=[0, 2, 4, 6])
@@ -821,6 +834,7 @@ class BucketizedColumnTest(test.TestCase):
class HashedCategoricalColumnTest(test.TestCase):
+ @test_util.run_deprecated_v1
def test_defaults(self):
a = fc.categorical_column_with_hash_bucket('aaa', 10)
self.assertEqual('aaa', a.name)
@@ -848,6 +862,7 @@ class HashedCategoricalColumnTest(test.TestCase):
with self.assertRaisesRegexp(ValueError, 'dtype must be string or integer'):
fc.categorical_column_with_hash_bucket('aaa', 10, dtype=dtypes.float32)
+ @test_util.run_deprecated_v1
def test_deep_copy(self):
original = fc.categorical_column_with_hash_bucket('aaa', 10)
for column in (original, copy.deepcopy(original)):
@@ -868,6 +883,7 @@ class HashedCategoricalColumnTest(test.TestCase):
'aaa': parsing_ops.VarLenFeature(dtypes.int32)
}, a.parse_example_spec)
+ @test_util.run_deprecated_v1
def test_parse_example(self):
a = fc.categorical_column_with_hash_bucket('aaa', 10)
data = example_pb2.Example(
@@ -890,6 +906,7 @@ class HashedCategoricalColumnTest(test.TestCase):
values=np.array([b'omar', b'stringer'], dtype=np.object_),
dense_shape=[1, 2]), self.evaluate(features['aaa']))
+ @test_util.run_deprecated_v1
def test_strings_should_be_hashed(self):
hashed_sparse = fc.categorical_column_with_hash_bucket('wire', 10)
wire_tensor = sparse_tensor.SparseTensor(
@@ -943,6 +960,7 @@ class HashedCategoricalColumnTest(test.TestCase):
with self.assertRaisesRegexp(ValueError, 'dtype must be compatible'):
transformation_cache.get(hashed_sparse, None)
+ @test_util.run_deprecated_v1
def test_ints_should_be_hashed(self):
hashed_sparse = fc.categorical_column_with_hash_bucket(
'wire', 10, dtype=dtypes.int64)
@@ -957,6 +975,7 @@ class HashedCategoricalColumnTest(test.TestCase):
self.assertAllEqual(expected_values, self.evaluate(output.values))
+ @test_util.run_deprecated_v1
def test_int32_64_is_compatible(self):
hashed_sparse = fc.categorical_column_with_hash_bucket(
'wire', 10, dtype=dtypes.int64)
@@ -971,6 +990,7 @@ class HashedCategoricalColumnTest(test.TestCase):
self.assertAllEqual(expected_values, self.evaluate(output.values))
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors(self):
hashed_sparse = fc.categorical_column_with_hash_bucket('wire', 10)
transformation_cache = fc.FeatureTransformationCache({
@@ -986,6 +1006,7 @@ class HashedCategoricalColumnTest(test.TestCase):
self.assertEqual(
transformation_cache.get(hashed_sparse, None), id_weight_pair.id_tensor)
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_dense_input(self):
hashed_sparse = fc.categorical_column_with_hash_bucket('wire', 10)
transformation_cache = fc.FeatureTransformationCache({
@@ -997,6 +1018,7 @@ class HashedCategoricalColumnTest(test.TestCase):
self.assertEqual(
transformation_cache.get(hashed_sparse, None), id_weight_pair.id_tensor)
+ @test_util.run_deprecated_v1
def test_linear_model(self):
wire_column = fc.categorical_column_with_hash_bucket('wire', 4)
self.assertEqual(4, wire_column.num_buckets)
@@ -1047,6 +1069,7 @@ class HashedCategoricalColumnTest(test.TestCase):
# 'skywalker' -> 2, 'omar' -> 2: wire_var[2] + wire_var[2] = 3+3 = 6
self.assertAllClose(((4.,), (6.,)), self.evaluate(predictions))
+ @test_util.run_deprecated_v1
def test_serialization(self):
wire_column = fc.categorical_column_with_hash_bucket('wire', 4)
self.assertEqual(['wire'], wire_column.parents)
@@ -1148,6 +1171,7 @@ class CrossedColumnTest(test.TestCase):
crossed = fc.crossed_column([b, 'c'], 15)
self.assertEqual(15, crossed.num_buckets)
+ @test_util.run_deprecated_v1
def test_deep_copy(self):
a = fc.numeric_column('a', dtype=dtypes.int32)
b = fc.bucketized_column(a, boundaries=[0, 1])
@@ -1161,6 +1185,7 @@ class CrossedColumnTest(test.TestCase):
self.assertEqual(15, crossed2_copy.hash_bucket_size)
self.assertEqual(5, crossed2_copy.hash_key)
+ @test_util.run_deprecated_v1
def test_parse_example(self):
price = fc.numeric_column('price', shape=[2])
bucketized_price = fc.bucketized_column(price, boundaries=[0, 50])
@@ -1190,6 +1215,7 @@ class CrossedColumnTest(test.TestCase):
self.evaluate(wire_sparse.values))
self.assertAllEqual([1, 2], self.evaluate(wire_sparse.dense_shape))
+ @test_util.run_deprecated_v1
def test_transform_feature(self):
price = fc.numeric_column('price', shape=[2])
bucketized_price = fc.bucketized_column(price, boundaries=[0, 50])
@@ -1214,6 +1240,7 @@ class CrossedColumnTest(test.TestCase):
self.assertIn(val, list(range(hash_bucket_size)))
self.assertAllEqual([2, 4], output_val.dense_shape)
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors(self):
a = fc.numeric_column('a', dtype=dtypes.int32, shape=(2,))
b = fc.bucketized_column(a, boundaries=(0, 1))
@@ -1285,6 +1312,7 @@ class CrossedColumnTest(test.TestCase):
self.assertAllEqual(expected_values, id_tensor_eval.values)
self.assertAllEqual((2, 4), id_tensor_eval.dense_shape)
+ @test_util.run_deprecated_v1
def test_linear_model(self):
"""Tests linear_model.
@@ -1520,6 +1548,7 @@ class CrossedColumnTest(test.TestCase):
sess.run(bias.assign((.1,)))
self.assertAllClose(((3.1,), (14.1,)), self.evaluate(predictions))
+ @test_util.run_deprecated_v1
def test_serialization(self):
a = fc.numeric_column('a', dtype=dtypes.int32, shape=(2,))
b = fc.bucketized_column(a, boundaries=(0, 1))
@@ -2077,6 +2106,7 @@ class LinearModelTest(test.TestCase):
features['price2']: [[1.], [5.]],
})
+ @test_util.run_deprecated_v1
def test_with_numpy_input_fn(self):
price = fc.numeric_column('price')
price_buckets = fc.bucketized_column(
@@ -2115,6 +2145,7 @@ class LinearModelTest(test.TestCase):
coord.request_stop()
coord.join(threads)
+ @test_util.run_deprecated_v1
def test_with_1d_sparse_tensor(self):
price = fc.numeric_column('price')
price_buckets = fc.bucketized_column(
@@ -2154,6 +2185,7 @@ class LinearModelTest(test.TestCase):
self.assertAllClose([[10 - 1000 + 5.], [1000 - 10 + 5.]],
self.evaluate(net))
+ @test_util.run_deprecated_v1
def test_with_1d_unknown_shape_sparse_tensor(self):
price = fc.numeric_column('price')
price_buckets = fc.bucketized_column(
@@ -2198,6 +2230,7 @@ class LinearModelTest(test.TestCase):
features['country']: country_data
}))
+ @test_util.run_deprecated_v1
def test_with_rank_0_feature(self):
price = fc.numeric_column('price')
features = {
@@ -2835,6 +2868,7 @@ class OldLinearModelTest(test.TestCase):
features['price2']: [[1.], [5.]],
})
+ @test_util.run_deprecated_v1
def test_with_1d_sparse_tensor(self):
price = fc.numeric_column('price')
price_buckets = fc.bucketized_column(
@@ -2875,6 +2909,7 @@ class OldLinearModelTest(test.TestCase):
self.assertAllClose([[10 - 1000 + 5.], [1000 - 10 + 5.]],
self.evaluate(net))
+ @test_util.run_deprecated_v1
def test_with_1d_unknown_shape_sparse_tensor(self):
price = fc.numeric_column('price')
price_buckets = fc.bucketized_column(
@@ -2920,6 +2955,7 @@ class OldLinearModelTest(test.TestCase):
features['country']: country_data
}))
+ @test_util.run_deprecated_v1
def test_with_rank_0_feature(self):
price = fc.numeric_column('price')
features = {
@@ -2962,6 +2998,7 @@ class OldLinearModelTest(test.TestCase):
sess.run(bias2.assign([5.]))
self.assertAllClose([[25.], [105.]], self.evaluate(predictions2))
+ @test_util.run_deprecated_v1
def test_linear_model_v1_shared_embedding_all_other_v2(self):
price = fc.numeric_column('price') # v2
some_sparse_column = fc.categorical_column_with_hash_bucket(
@@ -3001,6 +3038,7 @@ class OldLinearModelTest(test.TestCase):
self.assertAllClose([0.], self.evaluate(bias))
+ @test_util.run_deprecated_v1
def test_linear_model_v1_shared_embedding_with_v2_cat_all_other_v2(self):
price = fc.numeric_column('price') # v2
some_sparse_column = fc.categorical_column_with_hash_bucket(
@@ -3040,6 +3078,7 @@ class OldLinearModelTest(test.TestCase):
self.assertAllClose([0.], self.evaluate(bias))
+ @test_util.run_deprecated_v1
def test_linear_model_v1_v2_mix(self):
price = fc.numeric_column('price') # v2
some_sparse_column = fc.categorical_column_with_hash_bucket(
@@ -3079,6 +3118,7 @@ class OldLinearModelTest(test.TestCase):
self.assertAllClose([0.], self.evaluate(bias))
+ @test_util.run_deprecated_v1
def test_linear_model_v2_shared_embedding_all_other_v1(self):
price = fc.numeric_column('price') # v1
some_sparse_column = fc.categorical_column_with_hash_bucket(
@@ -3468,6 +3508,7 @@ class DenseFeaturesTest(test.TestCase):
expected_var_names,
[v.name for v in ops.get_collection(ops.GraphKeys.GLOBAL_VARIABLES)])
+ @test_util.run_deprecated_v1
def test_multiple_layers_with_same_shared_embedding_column(self):
categorical_column_a = fc.categorical_column_with_identity(
key='aaa', num_buckets=3)
@@ -3501,6 +3542,7 @@ class DenseFeaturesTest(test.TestCase):
['aaa_bbb_shared_embedding:0'],
[v.name for v in ops.get_collection(ops.GraphKeys.GLOBAL_VARIABLES)])
+ @test_util.run_deprecated_v1
def test_multiple_layers_with_same_shared_embedding_column_diff_graphs(self):
categorical_column_a = fc.categorical_column_with_identity(
key='aaa', num_buckets=3)
@@ -3552,6 +3594,7 @@ class DenseFeaturesTest(test.TestCase):
['aaa_bbb_shared_embedding:0'],
[v.name for v in ops.get_collection(ops.GraphKeys.GLOBAL_VARIABLES)])
+ @test_util.run_deprecated_v1
def test_with_numpy_input_fn(self):
embedding_values = (
(1., 2., 3., 4., 5.), # id 0
@@ -3596,6 +3639,7 @@ class DenseFeaturesTest(test.TestCase):
coord.request_stop()
coord.join(threads)
+ @test_util.run_deprecated_v1
def test_with_1d_sparse_tensor(self):
embedding_values = (
(1., 2., 3., 4., 5.), # id 0
@@ -3652,6 +3696,7 @@ class DenseFeaturesTest(test.TestCase):
[1., 0., 0., 1., 2., 3., 4., 5., 12.]],
sess.run(net))
+ @test_util.run_deprecated_v1
def test_with_1d_unknown_shape_sparse_tensor(self):
embedding_values = (
(1., 2.), # id 0
@@ -3710,6 +3755,7 @@ class DenseFeaturesTest(test.TestCase):
features['country']: country_data
}))
+ @test_util.run_deprecated_v1
def test_with_rank_0_feature(self):
# price has 1 dimension in dense_features
price = fc.numeric_column('price')
@@ -3967,6 +4013,7 @@ class FunctionalInputLayerTest(test.TestCase):
variables_lib.Variable)
self.assertAllEqual(cols_to_vars[some_embedding_column][0].shape, [5, 10])
+ @test_util.run_deprecated_v1
def test_fills_cols_to_vars_shared_embedding(self):
# Provide 5 DenseColumn's to input_layer: a NumericColumn, a
# BucketizedColumn, an EmbeddingColumn, two SharedEmbeddingColumns. The
@@ -4167,6 +4214,7 @@ class FunctionalInputLayerTest(test.TestCase):
expected_var_names,
[v.name for v in ops.get_collection(ops.GraphKeys.GLOBAL_VARIABLES)])
+ @test_util.run_deprecated_v1
def test_with_1d_sparse_tensor(self):
embedding_values = (
(1., 2., 3., 4., 5.), # id 0
@@ -4223,6 +4271,7 @@ class FunctionalInputLayerTest(test.TestCase):
[1., 0., 0., 1., 2., 3., 4., 5., 12.]],
sess.run(net))
+ @test_util.run_deprecated_v1
def test_with_1d_unknown_shape_sparse_tensor(self):
embedding_values = (
(1., 2.), # id 0
@@ -4281,6 +4330,7 @@ class FunctionalInputLayerTest(test.TestCase):
features['country']: country_data
}))
+ @test_util.run_deprecated_v1
def test_with_rank_0_feature(self):
# price has 1 dimension in input_layer
price = fc.numeric_column('price')
@@ -4444,6 +4494,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
'python/feature_column/testdata/wire_vocabulary.txt')
self._wire_vocabulary_size = 3
+ @test_util.run_deprecated_v1
def test_defaults(self):
column = fc.categorical_column_with_vocabulary_file(
key='aaa', vocabulary_file='path_to_file', vocabulary_size=3)
@@ -4460,6 +4511,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
fc.categorical_column_with_vocabulary_file(
key=('aaa',), vocabulary_file='path_to_file', vocabulary_size=3)
+ @test_util.run_deprecated_v1
def test_all_constructor_args(self):
column = fc.categorical_column_with_vocabulary_file(
key='aaa',
@@ -4472,6 +4524,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
'aaa': parsing_ops.VarLenFeature(dtypes.int32)
}, column.parse_example_spec)
+ @test_util.run_deprecated_v1
def test_deep_copy(self):
original = fc.categorical_column_with_vocabulary_file(
key='aaa',
@@ -4496,6 +4549,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
fc.categorical_column_with_vocabulary_file(
key='aaa', vocabulary_file='', vocabulary_size=3)
+ @test_util.run_deprecated_v1
def test_invalid_vocabulary_file(self):
column = fc.categorical_column_with_vocabulary_file(
key='aaa', vocabulary_file='file_does_not_exist', vocabulary_size=10)
@@ -4522,6 +4576,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
vocabulary_file=self._wire_vocabulary_file_name,
vocabulary_size=0)
+ @test_util.run_deprecated_v1
def test_too_large_vocabulary_size(self):
column = fc.categorical_column_with_vocabulary_file(
key='aaa',
@@ -4596,6 +4651,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
'aaa': inputs
}), None)
+ @test_util.run_deprecated_v1
def test_parse_example(self):
a = fc.categorical_column_with_vocabulary_file(
key='aaa', vocabulary_file='path_to_file', vocabulary_size=3)
@@ -4619,6 +4675,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
values=np.array([b'omar', b'stringer'], dtype=np.object_),
dense_shape=[1, 2]), self.evaluate(features['aaa']))
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors(self):
column = fc.categorical_column_with_vocabulary_file(
key='aaa',
@@ -4645,6 +4702,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
dense_shape=inputs.dense_shape),
self.evaluate(id_weight_pair.id_tensor))
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_none_vocabulary_size(self):
column = fc.categorical_column_with_vocabulary_file(
key='aaa', vocabulary_file=self._wire_vocabulary_file_name)
@@ -4669,6 +4727,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
dense_shape=inputs.dense_shape),
self.evaluate(id_weight_pair.id_tensor))
+ @test_util.run_deprecated_v1
def test_transform_feature(self):
column = fc.categorical_column_with_vocabulary_file(
key='aaa',
@@ -4692,6 +4751,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
values=np.array((2, -1, 0), dtype=np.int64),
dense_shape=inputs.dense_shape), self.evaluate(id_tensor))
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_dense_input(self):
column = fc.categorical_column_with_vocabulary_file(
key='aaa',
@@ -4713,6 +4773,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
values=np.array((2, -1, 0), dtype=np.int64),
dense_shape=(2, 2)), self.evaluate(id_weight_pair.id_tensor))
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_default_value_in_vocabulary(self):
column = fc.categorical_column_with_vocabulary_file(
key='aaa',
@@ -4740,6 +4801,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
dense_shape=inputs.dense_shape),
self.evaluate(id_weight_pair.id_tensor))
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_with_oov_buckets(self):
column = fc.categorical_column_with_vocabulary_file(
key='aaa',
@@ -4767,6 +4829,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
dense_shape=inputs.dense_shape),
self.evaluate(id_weight_pair.id_tensor))
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_small_vocabulary_size(self):
# 'marlo' is the last entry in our vocabulary file, so be setting
# `vocabulary_size` to 1 less than number of entries in file, we take
@@ -4796,6 +4859,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
dense_shape=inputs.dense_shape),
self.evaluate(id_weight_pair.id_tensor))
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_int32(self):
column = fc.categorical_column_with_vocabulary_file(
key='aaa',
@@ -4823,6 +4887,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
dense_shape=inputs.dense_shape),
self.evaluate(id_weight_pair.id_tensor))
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_int32_dense_input(self):
default_value = -100
column = fc.categorical_column_with_vocabulary_file(
@@ -4847,6 +4912,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
values=np.array((2, default_value, 0, 4), dtype=np.int64),
dense_shape=(3, 3)), self.evaluate(id_weight_pair.id_tensor))
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_int32_with_oov_buckets(self):
column = fc.categorical_column_with_vocabulary_file(
key='aaa',
@@ -4875,6 +4941,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
dense_shape=inputs.dense_shape),
self.evaluate(id_weight_pair.id_tensor))
+ @test_util.run_deprecated_v1
def test_linear_model(self):
wire_column = fc.categorical_column_with_vocabulary_file(
key='wire',
@@ -4933,6 +5000,7 @@ class VocabularyFileCategoricalColumnTest(test.TestCase):
# 'skywalker' -> 3, 'omar' -> 0: wire_var[3] + wire_var[0] = 4+1 = 5
self.assertAllClose(((3.,), (5.,)), self.evaluate(predictions))
+ @test_util.run_deprecated_v1
def test_serialization(self):
wire_column = fc.categorical_column_with_vocabulary_file(
key='wire',
@@ -4984,6 +5052,7 @@ class VocabularyListCategoricalColumnTest(test.TestCase):
'aaa': parsing_ops.VarLenFeature(dtypes.int64)
}, column.parse_example_spec)
+ @test_util.run_deprecated_v1
def test_all_constructor_args(self):
column = fc.categorical_column_with_vocabulary_list(
key='aaa',
@@ -4995,6 +5064,7 @@ class VocabularyListCategoricalColumnTest(test.TestCase):
'aaa': parsing_ops.VarLenFeature(dtypes.int32)
}, column.parse_example_spec)
+ @test_util.run_deprecated_v1
def test_deep_copy(self):
original = fc.categorical_column_with_vocabulary_list(
key='aaa', vocabulary_list=(12, 24, 36), dtype=dtypes.int32)
@@ -5089,6 +5159,7 @@ class VocabularyListCategoricalColumnTest(test.TestCase):
'aaa': inputs
}), None)
+ @test_util.run_deprecated_v1
def test_parse_example_string(self):
a = fc.categorical_column_with_vocabulary_list(
key='aaa', vocabulary_list=('omar', 'stringer', 'marlo'))
@@ -5112,6 +5183,7 @@ class VocabularyListCategoricalColumnTest(test.TestCase):
values=np.array([b'omar', b'stringer'], dtype=np.object_),
dense_shape=[1, 2]), self.evaluate(features['aaa']))
+ @test_util.run_deprecated_v1
def test_parse_example_int(self):
a = fc.categorical_column_with_vocabulary_list(
key='aaa', vocabulary_list=(11, 21, 31))
@@ -5133,6 +5205,7 @@ class VocabularyListCategoricalColumnTest(test.TestCase):
indices=[[0, 0], [0, 1]], values=[11, 21], dense_shape=[1, 2]),
self.evaluate(features['aaa']))
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors(self):
column = fc.categorical_column_with_vocabulary_list(
key='aaa', vocabulary_list=('omar', 'stringer', 'marlo'))
@@ -5157,6 +5230,7 @@ class VocabularyListCategoricalColumnTest(test.TestCase):
dense_shape=inputs.dense_shape),
self.evaluate(id_weight_pair.id_tensor))
+ @test_util.run_deprecated_v1
def test_transform_feature(self):
column = fc.categorical_column_with_vocabulary_list(
key='aaa', vocabulary_list=('omar', 'stringer', 'marlo'))
@@ -5178,6 +5252,7 @@ class VocabularyListCategoricalColumnTest(test.TestCase):
values=np.array((2, -1, 0), dtype=np.int64),
dense_shape=inputs.dense_shape), self.evaluate(id_tensor))
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_dense_input(self):
column = fc.categorical_column_with_vocabulary_list(
key='aaa', vocabulary_list=('omar', 'stringer', 'marlo'))
@@ -5197,6 +5272,7 @@ class VocabularyListCategoricalColumnTest(test.TestCase):
values=np.array((2, -1, 0), dtype=np.int64),
dense_shape=(2, 2)), self.evaluate(id_weight_pair.id_tensor))
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_default_value_in_vocabulary(self):
column = fc.categorical_column_with_vocabulary_list(
key='aaa',
@@ -5223,6 +5299,7 @@ class VocabularyListCategoricalColumnTest(test.TestCase):
dense_shape=inputs.dense_shape),
self.evaluate(id_weight_pair.id_tensor))
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_with_oov_buckets(self):
column = fc.categorical_column_with_vocabulary_list(
key='aaa',
@@ -5249,6 +5326,7 @@ class VocabularyListCategoricalColumnTest(test.TestCase):
dense_shape=inputs.dense_shape),
self.evaluate(id_weight_pair.id_tensor))
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_int32(self):
column = fc.categorical_column_with_vocabulary_list(
key='aaa',
@@ -5275,6 +5353,7 @@ class VocabularyListCategoricalColumnTest(test.TestCase):
dense_shape=inputs.dense_shape),
self.evaluate(id_weight_pair.id_tensor))
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_int32_dense_input(self):
default_value = -100
column = fc.categorical_column_with_vocabulary_list(
@@ -5300,6 +5379,7 @@ class VocabularyListCategoricalColumnTest(test.TestCase):
values=np.array((2, default_value, 0, 4), dtype=np.int64),
dense_shape=(3, 3)), self.evaluate(id_weight_pair.id_tensor))
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_int32_with_oov_buckets(self):
column = fc.categorical_column_with_vocabulary_list(
key='aaa',
@@ -5327,6 +5407,7 @@ class VocabularyListCategoricalColumnTest(test.TestCase):
dense_shape=inputs.dense_shape),
self.evaluate(id_weight_pair.id_tensor))
+ @test_util.run_deprecated_v1
def test_linear_model(self):
wire_column = fc.categorical_column_with_vocabulary_list(
key='aaa',
@@ -5383,6 +5464,7 @@ class VocabularyListCategoricalColumnTest(test.TestCase):
# 'skywalker' -> 3, 'omar' -> 0: wire_var[3] + wire_var[0] = 4+1 = 5
self.assertAllClose(((3.,), (5.,)), self.evaluate(predictions))
+ @test_util.run_deprecated_v1
def test_serialization(self):
wire_column = fc.categorical_column_with_vocabulary_list(
key='aaa',
@@ -5420,6 +5502,7 @@ class IdentityCategoricalColumnTest(test.TestCase):
with self.assertRaisesRegexp(ValueError, 'key must be a string.'):
fc.categorical_column_with_identity(key=('aaa',), num_buckets=3)
+ @test_util.run_deprecated_v1
def test_deep_copy(self):
original = fc.categorical_column_with_identity(key='aaa', num_buckets=3)
for column in (original, copy.deepcopy(original)):
@@ -5459,6 +5542,7 @@ class IdentityCategoricalColumnTest(test.TestCase):
'aaa': inputs
}), None)
+ @test_util.run_deprecated_v1
def test_parse_example(self):
a = fc.categorical_column_with_identity(key='aaa', num_buckets=30)
data = example_pb2.Example(
@@ -5480,6 +5564,7 @@ class IdentityCategoricalColumnTest(test.TestCase):
values=np.array([11, 21], dtype=np.int64),
dense_shape=[1, 2]), self.evaluate(features['aaa']))
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors(self):
column = fc.categorical_column_with_identity(key='aaa', num_buckets=3)
inputs = sparse_tensor.SparseTensorValue(
@@ -5501,6 +5586,7 @@ class IdentityCategoricalColumnTest(test.TestCase):
dense_shape=inputs.dense_shape),
self.evaluate(id_weight_pair.id_tensor))
+ @test_util.run_deprecated_v1
def test_transform_feature(self):
column = fc.categorical_column_with_identity(key='aaa', num_buckets=3)
inputs = sparse_tensor.SparseTensorValue(
@@ -5519,6 +5605,7 @@ class IdentityCategoricalColumnTest(test.TestCase):
values=np.array((0, 1, 0), dtype=np.int64),
dense_shape=inputs.dense_shape), self.evaluate(id_tensor))
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_dense_input(self):
column = fc.categorical_column_with_identity(key='aaa', num_buckets=3)
id_weight_pair = column.get_sparse_tensors(
@@ -5537,6 +5624,7 @@ class IdentityCategoricalColumnTest(test.TestCase):
values=np.array((0, 1, 0), dtype=np.int64),
dense_shape=(2, 2)), self.evaluate(id_weight_pair.id_tensor))
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_with_inputs_too_small(self):
column = fc.categorical_column_with_identity(key='aaa', num_buckets=3)
inputs = sparse_tensor.SparseTensorValue(
@@ -5553,6 +5641,7 @@ class IdentityCategoricalColumnTest(test.TestCase):
with self.assertRaisesRegexp(errors.OpError, 'assert_greater_or_equal_0'):
self.evaluate(id_weight_pair.id_tensor)
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_with_inputs_too_big(self):
column = fc.categorical_column_with_identity(key='aaa', num_buckets=3)
inputs = sparse_tensor.SparseTensorValue(
@@ -5570,6 +5659,7 @@ class IdentityCategoricalColumnTest(test.TestCase):
'assert_less_than_num_buckets'):
self.evaluate(id_weight_pair.id_tensor)
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_with_default_value(self):
column = fc.categorical_column_with_identity(
key='aaa', num_buckets=4, default_value=3)
@@ -5594,6 +5684,7 @@ class IdentityCategoricalColumnTest(test.TestCase):
dense_shape=inputs.dense_shape),
self.evaluate(id_weight_pair.id_tensor))
+ @test_util.run_deprecated_v1
def test_get_sparse_tensors_with_default_value_and_placeholder_inputs(self):
column = fc.categorical_column_with_identity(
key='aaa', num_buckets=4, default_value=3)
@@ -5624,6 +5715,7 @@ class IdentityCategoricalColumnTest(test.TestCase):
input_shape: (2, 2),
}))
+ @test_util.run_deprecated_v1
def test_linear_model(self):
column = fc.categorical_column_with_identity(key='aaa', num_buckets=3)
self.assertEqual(3, column.num_buckets)
@@ -5674,6 +5766,7 @@ class IdentityCategoricalColumnTest(test.TestCase):
# weight_var[2] + weight_var[1] = 3+2 = 5
self.assertAllClose(((1.,), (5.,)), self.evaluate(predictions))
+ @test_util.run_deprecated_v1
def test_serialization(self):
column = fc.categorical_column_with_identity(key='aaa', num_buckets=3)
@@ -5827,6 +5920,7 @@ class IndicatorColumnTest(test.TestCase):
self.assertAllEqual([[0., 1., 1., 0.]], self.evaluate(output))
+ @test_util.run_deprecated_v1
def test_deep_copy(self):
a = fc.categorical_column_with_hash_bucket('a', 4)
column = fc.indicator_column(a)
@@ -5835,6 +5929,7 @@ class IndicatorColumnTest(test.TestCase):
self.assertEqual(column.name, 'a_indicator')
self.assertEqual(column.variable_shape, [1, 4])
+ @test_util.run_deprecated_v1
def test_parse_example(self):
a = fc.categorical_column_with_vocabulary_list(
key='aaa', vocabulary_list=('omar', 'stringer', 'marlo'))
@@ -5859,6 +5954,7 @@ class IndicatorColumnTest(test.TestCase):
values=np.array([b'omar', b'stringer'], dtype=np.object_),
dense_shape=[1, 2]), self.evaluate(features['aaa']))
+ @test_util.run_deprecated_v1
def test_transform(self):
a = fc.categorical_column_with_vocabulary_list(
key='aaa', vocabulary_list=('omar', 'stringer', 'marlo'))
@@ -5878,6 +5974,7 @@ class IndicatorColumnTest(test.TestCase):
self.assertAllEqual([[0, 0, 1], [1, 0, 0]], self.evaluate(indicator_tensor))
+ @test_util.run_deprecated_v1
def test_transform_with_weighted_column(self):
# Github issue 12557
ids = fc.categorical_column_with_vocabulary_list(
@@ -5896,6 +5993,7 @@ class IndicatorColumnTest(test.TestCase):
self.assertAllEqual([[6., 4., 3.]], self.evaluate(indicator_tensor))
+ @test_util.run_deprecated_v1
def test_transform_with_missing_value_in_weighted_column(self):
# Github issue 12583
ids = fc.categorical_column_with_vocabulary_list(
@@ -5914,6 +6012,7 @@ class IndicatorColumnTest(test.TestCase):
self.assertAllEqual([[0., 4., 2.]], self.evaluate(indicator_tensor))
+ @test_util.run_deprecated_v1
def test_transform_with_missing_value_in_categorical_column(self):
# Github issue 12583
ids = fc.categorical_column_with_vocabulary_list(
@@ -5930,6 +6029,7 @@ class IndicatorColumnTest(test.TestCase):
self.assertAllEqual([[0., 1., 1.]], self.evaluate(indicator_tensor))
+ @test_util.run_deprecated_v1
def test_linear_model(self):
animal = fc.indicator_column(
fc.categorical_column_with_identity('animal', num_buckets=4))
@@ -5997,6 +6097,7 @@ class IndicatorColumnTest(test.TestCase):
self.evaluate(weight_var.assign([[1.], [2.], [3.], [4.]]))
self.assertAllClose([[2. + 3.]], self.evaluate(predictions))
+ @test_util.run_deprecated_v1
def test_dense_features(self):
animal = fc.indicator_column(
fc.categorical_column_with_identity('animal', num_buckets=4))
@@ -6013,6 +6114,7 @@ class IndicatorColumnTest(test.TestCase):
self.assertAllClose([[0., 1., 1., 0.]], self.evaluate(net))
+ @test_util.run_deprecated_v1
def test_input_layer(self):
animal = fc.indicator_column(
fc.categorical_column_with_identity('animal', num_buckets=4))
@@ -6045,6 +6147,7 @@ class IndicatorColumnTest(test.TestCase):
self.assertAllClose([[0., 1., 1., 0.]], self.evaluate(net))
+ @test_util.run_deprecated_v1
def test_serialization(self):
parent = fc.categorical_column_with_identity('animal', num_buckets=4)
animal = fc.indicator_column(parent)
@@ -6114,6 +6217,7 @@ class _TestStateManager(fc.StateManager):
class EmbeddingColumnTest(test.TestCase):
+ @test_util.run_deprecated_v1
def test_defaults(self):
categorical_column = fc.categorical_column_with_identity(
key='aaa', num_buckets=3)
@@ -6142,6 +6246,7 @@ class EmbeddingColumnTest(test.TestCase):
categorical_column, dimension=embedding_dimension)
self.assertFalse(embedding_column._is_v2_column)
+ @test_util.run_deprecated_v1
def test_all_constructor_args(self):
categorical_column = fc.categorical_column_with_identity(
key='aaa', num_buckets=3)
@@ -6168,6 +6273,7 @@ class EmbeddingColumnTest(test.TestCase):
'aaa': parsing_ops.VarLenFeature(dtypes.int64)
}, embedding_column.parse_example_spec)
+ @test_util.run_deprecated_v1
def test_deep_copy(self):
categorical_column = fc.categorical_column_with_identity(
key='aaa', num_buckets=3)
@@ -6200,12 +6306,14 @@ class EmbeddingColumnTest(test.TestCase):
'aaa': parsing_ops.VarLenFeature(dtypes.int64)
}, embedding_column.parse_example_spec)
+ @test_util.run_deprecated_v1
def test_invalid_initializer(self):
categorical_column = fc.categorical_column_with_identity(
key='aaa', num_buckets=3)
with self.assertRaisesRegexp(ValueError, 'initializer must be callable'):
fc.embedding_column(categorical_column, dimension=2, initializer='not_fn')
+ @test_util.run_deprecated_v1
def test_parse_example(self):
a = fc.categorical_column_with_vocabulary_list(
key='aaa', vocabulary_list=('omar', 'stringer', 'marlo'))
@@ -6230,6 +6338,7 @@ class EmbeddingColumnTest(test.TestCase):
values=np.array([b'omar', b'stringer'], dtype=np.object_),
dense_shape=[1, 2]), self.evaluate(features['aaa']))
+ @test_util.run_deprecated_v1
def test_transform_feature(self):
a = fc.categorical_column_with_identity(key='aaa', num_buckets=3)
a_embedded = fc.embedding_column(a, dimension=2)
@@ -6250,6 +6359,7 @@ class EmbeddingColumnTest(test.TestCase):
_assert_sparse_tensor_value(self, self.evaluate(output_a),
self.evaluate(output_embedded))
+ @test_util.run_deprecated_v1
def test_get_dense_tensor(self):
# Inputs.
vocabulary_size = 3
@@ -6315,6 +6425,7 @@ class EmbeddingColumnTest(test.TestCase):
self.assertAllEqual(embedding_values, self.evaluate(global_vars[0]))
self.assertAllEqual(expected_lookups, self.evaluate(embedding_lookup))
+ @test_util.run_deprecated_v1
def test_get_dense_tensor_old_categorical(self):
# Inputs.
vocabulary_size = 3
@@ -6378,6 +6489,7 @@ class EmbeddingColumnTest(test.TestCase):
self.assertAllEqual(embedding_values, self.evaluate(global_vars[0]))
self.assertAllEqual(expected_lookups, self.evaluate(embedding_lookup))
+ @test_util.run_deprecated_v1
def test_get_dense_tensor_3d(self):
# Inputs.
vocabulary_size = 4
@@ -6445,6 +6557,7 @@ class EmbeddingColumnTest(test.TestCase):
self.assertAllEqual(embedding_values, self.evaluate(global_vars[0]))
self.assertAllEqual(expected_lookups, self.evaluate(embedding_lookup))
+ @test_util.run_deprecated_v1
def test_get_dense_tensor_placeholder_inputs(self):
# Inputs.
vocabulary_size = 3
@@ -6524,6 +6637,7 @@ class EmbeddingColumnTest(test.TestCase):
input_shape: sparse_input.dense_shape,
}))
+ @test_util.run_deprecated_v1
def test_get_dense_tensor_restore_from_ckpt(self):
# Inputs.
vocabulary_size = 3
@@ -6587,6 +6701,7 @@ class EmbeddingColumnTest(test.TestCase):
self.assertAllEqual(embedding_values, self.evaluate(global_vars[0]))
self.assertAllEqual(expected_lookups, self.evaluate(embedding_lookup))
+ @test_util.run_deprecated_v1
def test_linear_model(self):
# Inputs.
batch_size = 4
@@ -6668,6 +6783,7 @@ class EmbeddingColumnTest(test.TestCase):
self.assertAllClose(((94.,), (29.,), (0.,), (42.,)),
self.evaluate(predictions))
+ @test_util.run_deprecated_v1
def test_dense_features(self):
# Inputs.
vocabulary_size = 3
@@ -6734,6 +6850,7 @@ class EmbeddingColumnTest(test.TestCase):
self.assertAllEqual(embedding_values, self.evaluate(trainable_vars[0]))
self.assertAllEqual(expected_lookups, self.evaluate(dense_features))
+ @test_util.run_deprecated_v1
def test_dense_features_not_trainable(self):
# Inputs.
vocabulary_size = 3
@@ -6799,6 +6916,7 @@ class EmbeddingColumnTest(test.TestCase):
self.assertAllEqual(embedding_values, self.evaluate(global_vars[0]))
self.assertAllEqual(expected_lookups, self.evaluate(dense_features))
+ @test_util.run_deprecated_v1
def test_input_layer(self):
# Inputs.
vocabulary_size = 3
@@ -7028,6 +7146,7 @@ class EmbeddingColumnTest(test.TestCase):
self.assertAllClose(((94.,), (29.,), (0.,), (42.,)),
self.evaluate(predictions))
+ @test_util.run_deprecated_v1
def test_serialization(self):
def _initializer(shape, dtype, partition_info):
@@ -7081,6 +7200,7 @@ class EmbeddingColumnTest(test.TestCase):
class SharedEmbeddingColumnTest(test.TestCase):
+ @test_util.run_deprecated_v1
def test_defaults(self):
categorical_column_a = fc.categorical_column_with_identity(
key='aaa', num_buckets=3)
@@ -7105,6 +7225,7 @@ class SharedEmbeddingColumnTest(test.TestCase):
'bbb': parsing_ops.VarLenFeature(dtypes.int64)
}, embedding_column_b.parse_example_spec)
+ @test_util.run_deprecated_v1
def test_all_constructor_args(self):
categorical_column_a = fc.categorical_column_with_identity(
key='aaa', num_buckets=3)
@@ -7136,6 +7257,7 @@ class SharedEmbeddingColumnTest(test.TestCase):
'bbb': parsing_ops.VarLenFeature(dtypes.int64)
}, embedding_column_b.parse_example_spec)
+ @test_util.run_deprecated_v1
def test_deep_copy(self):
categorical_column_a = fc.categorical_column_with_identity(
key='aaa', num_buckets=3)
@@ -7167,6 +7289,7 @@ class SharedEmbeddingColumnTest(test.TestCase):
'aaa': parsing_ops.VarLenFeature(dtypes.int64)
}, embedding_column_a.parse_example_spec)
+ @test_util.run_deprecated_v1
def test_invalid_initializer(self):
categorical_column_a = fc.categorical_column_with_identity(
key='aaa', num_buckets=3)
@@ -7178,6 +7301,7 @@ class SharedEmbeddingColumnTest(test.TestCase):
dimension=2,
initializer='not_fn')
+ @test_util.run_deprecated_v1
def test_incompatible_column_type(self):
categorical_column_a = fc.categorical_column_with_identity(
key='aaa', num_buckets=3)
@@ -7192,6 +7316,7 @@ class SharedEmbeddingColumnTest(test.TestCase):
[categorical_column_a, categorical_column_b, categorical_column_c],
dimension=2)
+ @test_util.run_deprecated_v1
def test_weighted_categorical_column_ok(self):
categorical_column_a = fc.categorical_column_with_identity(
key='aaa', num_buckets=3)
@@ -7209,6 +7334,7 @@ class SharedEmbeddingColumnTest(test.TestCase):
[weighted_categorical_column_a, weighted_categorical_column_b],
dimension=2)
+ @test_util.run_deprecated_v1
def test_parse_example(self):
a = fc.categorical_column_with_vocabulary_list(
key='aaa', vocabulary_list=('omar', 'stringer', 'marlo'))
@@ -7246,6 +7372,7 @@ class SharedEmbeddingColumnTest(test.TestCase):
values=np.array([b'stringer', b'marlo'], dtype=np.object_),
dense_shape=[1, 2]), self.evaluate(features['bbb']))
+ @test_util.run_deprecated_v1
def test_transform_feature(self):
a = fc.categorical_column_with_identity(key='aaa', num_buckets=3)
b = fc.categorical_column_with_identity(key='bbb', num_buckets=3)
@@ -7277,6 +7404,7 @@ class SharedEmbeddingColumnTest(test.TestCase):
_assert_sparse_tensor_value(self, self.evaluate(output_b),
self.evaluate(output_b_embedded))
+ @test_util.run_deprecated_v1
def test_get_dense_tensor(self):
# Inputs.
vocabulary_size = 3
@@ -7348,6 +7476,7 @@ class SharedEmbeddingColumnTest(test.TestCase):
self.assertAllEqual(expected_lookups_a, self.evaluate(embedding_lookup_a))
self.assertAllEqual(expected_lookups_b, self.evaluate(embedding_lookup_b))
+ @test_util.run_deprecated_v1
def test_get_dense_tensor_placeholder_inputs(self):
# Inputs.
vocabulary_size = 3
@@ -7407,6 +7536,7 @@ class SharedEmbeddingColumnTest(test.TestCase):
with _initialized_session() as sess:
sess.run([embedding_lookup_a, embedding_lookup_b], feed_dict=feed_dict)
+ @test_util.run_deprecated_v1
def test_linear_model(self):
# Inputs.
batch_size = 2
@@ -7619,12 +7749,15 @@ class SharedEmbeddingColumnTest(test.TestCase):
self.evaluate(shared_embedding_vars[0]))
self.assertAllEqual(expected_lookups, self.evaluate(dense_features))
+ @test_util.run_deprecated_v1
def test_dense_features(self):
self._test_dense_features()
+ @test_util.run_deprecated_v1
def test_dense_features_no_trainable(self):
self._test_dense_features(trainable=False)
+ @test_util.run_deprecated_v1
def test_serialization(self):
def _initializer(shape, dtype, partition_info):
@@ -7647,6 +7780,7 @@ class SharedEmbeddingColumnTest(test.TestCase):
class WeightedCategoricalColumnTest(test.TestCase):
+ @test_util.run_deprecated_v1
def test_defaults(self):
column = fc.weighted_categorical_column(
categorical_column=fc.categorical_column_with_identity(
@@ -7667,6 +7801,7 @@ class WeightedCategoricalColumnTest(test.TestCase):
weight_feature_key='values')
self.assertFalse(column._is_v2_column)
+ @test_util.run_deprecated_v1
def test_deep_copy(self):
"""Tests deepcopy of categorical_column_with_hash_bucket."""
original = fc.weighted_categorical_column(
@@ -7732,6 +7867,7 @@ class WeightedCategoricalColumnTest(test.TestCase):
'values is not in features dictionary'):
fc._transform_features_v2({'ids': inputs}, (column,), None)
+ @test_util.run_deprecated_v1
def test_parse_example(self):
a = fc.categorical_column_with_vocabulary_list(
key='aaa', vocabulary_list=('omar', 'stringer', 'marlo'))
@@ -7766,6 +7902,7 @@ class WeightedCategoricalColumnTest(test.TestCase):
values=np.array([1., 10.], dtype=np.float32),
dense_shape=[1, 2]), self.evaluate(features['weights']))
+ @test_util.run_deprecated_v1
def test_transform_features(self):
column = fc.weighted_categorical_column(
categorical_column=fc.categorical_column_with_identity(
@@ -7798,6 +7935,7 @@ class WeightedCategoricalColumnTest(test.TestCase):
values=np.array(weights.values, dtype=np.float32),
dense_shape=weights.dense_shape), self.evaluate(weight_tensor))
+ @test_util.run_deprecated_v1
def test_transform_features_dense_input(self):
column = fc.weighted_categorical_column(
categorical_column=fc.categorical_column_with_identity(
@@ -7828,6 +7966,7 @@ class WeightedCategoricalColumnTest(test.TestCase):
values=np.array(weights.values, dtype=np.float32),
dense_shape=weights.dense_shape), self.evaluate(weight_tensor))
+ @test_util.run_deprecated_v1
def test_transform_features_dense_weights(self):
column = fc.weighted_categorical_column(
categorical_column=fc.categorical_column_with_identity(
@@ -7856,6 +7995,7 @@ class WeightedCategoricalColumnTest(test.TestCase):
values=np.array((.5, 1., .1), dtype=np.float32),
dense_shape=(2, 2)), self.evaluate(weight_tensor))
+ @test_util.run_deprecated_v1
def test_linear_model(self):
column = fc.weighted_categorical_column(
categorical_column=fc.categorical_column_with_identity(
@@ -8106,6 +8246,7 @@ class WeightedCategoricalColumnTest(test.TestCase):
# TODO(ptucker): Add test with embedding of weighted categorical.
+ @test_util.run_deprecated_v1
def test_serialization(self):
categorical_column = fc.categorical_column_with_identity(
key='ids', num_buckets=3)
diff --git a/tensorflow/python/framework/file_system_test.py b/tensorflow/python/framework/file_system_test.py
index 066d34e781c..8687bc5a785 100644
--- a/tensorflow/python/framework/file_system_test.py
+++ b/tensorflow/python/framework/file_system_test.py
@@ -21,6 +21,7 @@ from __future__ import print_function
import os
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.framework import load_library
from tensorflow.python.ops import data_flow_ops
from tensorflow.python.ops import io_ops
@@ -36,6 +37,7 @@ class FileSystemTest(test.TestCase):
"test_file_system.so")
load_library.load_file_system_library(file_system_library)
+ @test_util.run_deprecated_v1
def testBasic(self):
with self.cached_session() as sess:
reader = io_ops.WholeFileReader("test_reader")
diff --git a/tensorflow/python/framework/function_def_to_graph_test.py b/tensorflow/python/framework/function_def_to_graph_test.py
index b2ef64f8730..ddf1a6e74d2 100644
--- a/tensorflow/python/framework/function_def_to_graph_test.py
+++ b/tensorflow/python/framework/function_def_to_graph_test.py
@@ -25,6 +25,7 @@ from tensorflow.python.framework import function_def_to_graph
from tensorflow.python.framework import graph_to_function_def
from tensorflow.python.framework import ops
from tensorflow.python.framework import tensor_shape
+from tensorflow.python.framework import test_util
from tensorflow.python.framework import test_ops
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import math_ops
@@ -52,6 +53,7 @@ class FunctionDefToGraphTest(test.TestCase):
fdef.signature.name = "_whats_in_a_name"
return fdef
+ @test_util.run_deprecated_v1
def testInputsAndOutputs(self):
fdef = self._build_function_def()
g = function_def_to_graph.function_def_to_graph(fdef)
@@ -186,6 +188,7 @@ class FunctionDefToGraphDefTest(test.TestCase):
self.assertEqual(g.node[0].attr["shape"].shape.unknown_rank, False)
self.assertFalse("shape" in g.node[2].attr)
+ @test_util.run_deprecated_v1
def testFunctionCallsFromFunction(self):
x = constant_op.constant(5.0)
y = constant_op.constant(10.0)
diff --git a/tensorflow/python/framework/function_test.py b/tensorflow/python/framework/function_test.py
index 1a17a480502..d71f06ea528 100644
--- a/tensorflow/python/framework/function_test.py
+++ b/tensorflow/python/framework/function_test.py
@@ -35,6 +35,7 @@ from tensorflow.python.framework import function
from tensorflow.python.framework import graph_to_function_def
from tensorflow.python.framework import ops
from tensorflow.python.framework import tensor_shape
+from tensorflow.python.framework import test_util
from tensorflow.python.framework.errors import InvalidArgumentError
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import control_flow_ops
@@ -104,6 +105,7 @@ class FunctionTest(test.TestCase):
with session.Session() as sess:
self.assertAllEqual([18.0], self.evaluate(call))
+ @test_util.run_deprecated_v1
def testIdentityImplicitDeref(self):
@function.Defun(dtypes.float32, func_name="MyIdentity")
@@ -322,6 +324,7 @@ class FunctionTest(test.TestCase):
self.assertEqual(x.get_shape(), dx.get_shape())
self.assertEqual(y.get_shape(), dy.get_shape())
+ @test_util.run_deprecated_v1
def testSymGradAttr(self):
@function.Defun(noinline=True)
@@ -438,6 +441,7 @@ class FunctionTest(test.TestCase):
"assertion failed.*-3"):
self.assertAllEqual(Foo(constant_op.constant(-3.0)).eval(), 6.0)
+ @test_util.run_deprecated_v1
def testAssertWrapper(self):
@function.Defun(dtypes.float32)
@@ -452,6 +456,7 @@ class FunctionTest(test.TestCase):
"assertion"):
_ = MyFn(100.0).eval()
+ @test_util.run_deprecated_v1
def testWhileLoopCallsFunc(self):
with self.session(use_gpu=True) as sess:
@@ -471,6 +476,7 @@ class FunctionTest(test.TestCase):
ans = self.evaluate(loop)
self.assertAllClose(ans, 131072.)
+ @test_util.run_deprecated_v1
def testControlFlowStrictness(self):
"""Inlined functions must not execute in a untaken control flow branch."""
@@ -517,6 +523,7 @@ class FunctionTest(test.TestCase):
"assertion"):
sess.run(loop, {pred: True, x: 3})
+ @test_util.run_deprecated_v1
def testVar(self):
@function.Defun(dtypes.float32)
@@ -532,6 +539,7 @@ class FunctionTest(test.TestCase):
variables.global_variables_initializer().run()
self.assertAllEqual(z.eval(), 101.)
+ @test_util.run_deprecated_v1
def testResourceVarAsImplicitInput(self):
g = ops.Graph()
with g.as_default(), ops.device("cpu:0"):
@@ -707,6 +715,7 @@ class FunctionTest(test.TestCase):
gdef = g.as_graph_def()
self.assertEqual(0, len(gdef.library.function))
+ @test_util.run_deprecated_v1
def testReduction(self):
g = ops.Graph()
@@ -735,6 +744,7 @@ class FunctionTest(test.TestCase):
self.assertAllClose(vals[0], vals[1])
self.assertAllClose(vals[2], vals[3])
+ @test_util.run_deprecated_v1
def testCapture(self):
g = ops.Graph()
with g.as_default():
@@ -781,6 +791,7 @@ class FunctionTest(test.TestCase):
# NOTE: We still do not support capturing control deps.
_ = Foo(x)
+ @test_util.run_deprecated_v1
def testCaptureInWhileLoop(self):
g = ops.Graph()
with g.as_default():
@@ -796,6 +807,7 @@ class FunctionTest(test.TestCase):
with self.session(graph=g) as sess:
self.assertEqual(self.evaluate(y), 10)
+ @test_util.run_deprecated_v1
def testCaptureInCond(self):
g = ops.Graph()
with g.as_default():
@@ -825,6 +837,7 @@ class FunctionTest(test.TestCase):
self.assertEqual("Foo_aCYSbwBkR5A",
Foo.instantiate([dtypes.float32] * 3).name)
+ @test_util.run_deprecated_v1
def testSignatureHash(self):
# Foo.Inner and Bar.Inner have identical function body but have
# different signatures. They should be treated as two different functions.
@@ -877,6 +890,7 @@ class FunctionTest(test.TestCase):
y = Bar(array_ops.zeros([1, 2, 3]))
self.assertAllEqual(y.get_shape().as_list(), [1, 1, 2, 3])
+ @test_util.run_deprecated_v1
def testVariableReuse(self):
def LinearWithReuse(input_tensor, reuse=None):
@@ -905,6 +919,7 @@ class FunctionTest(test.TestCase):
output_op, feed_dict={input_op: np.random.rand(32, 100)})
self.assertEqual(output_val.shape, (32, 100))
+ @test_util.run_deprecated_v1
def testFunctionCallInDifferentVariableScopes(self):
@function.Defun(dtypes.float32)
@@ -968,6 +983,7 @@ class FunctionTest(test.TestCase):
self.assertAllClose(
np.array([1.0, 0.0]).astype(np.float32), sess.run(dinp, {inp: x}))
+ @test_util.run_deprecated_v1
def testFunctionMarkedStateful(self):
@function.Defun(dtypes.int32, dtypes.float32)
@@ -995,6 +1011,7 @@ class FunctionTest(test.TestCase):
self.assertEqual(100, self.evaluate(result_2))
self.assertEqual((4.0, 100), sess.run((result_1, result_2)))
+ @test_util.run_deprecated_v1
def testStatefulFunction(self):
@function.Defun()
@@ -1037,6 +1054,7 @@ class FunctionTest(test.TestCase):
self.assertFalse(all(val3 == val1))
self.assertFalse(all(val4 == val2))
+ @test_util.run_deprecated_v1
def testSameFunctionOnTwoDevices(self):
@function.Defun(dtypes.float32)
@@ -1056,6 +1074,7 @@ class FunctionTest(test.TestCase):
self.assertEqual(44.0, self.evaluate(f_1))
self.assertEqual((42.0, 44.0), sess.run((f_0, f_1)))
+ @test_util.run_deprecated_v1
def testGuaranteedConstsAreCaptured(self):
var = variables.Variable(1.0)
const = array_ops.guarantee_const(var)
@@ -1079,6 +1098,7 @@ class FunctionTest(test.TestCase):
self.evaluate(var.initializer)
_ = sess.run(CapturesGuaranteedConst(), {also_not_const: 1.0})
+ @test_util.run_deprecated_v1
def testSameFunctionDifferentGrads(self):
def PartOne(x):
@@ -1150,6 +1170,7 @@ class FunctionsFromProtos(test.TestCase):
self.assertEqual(func.declared_input_types, new_func.declared_input_types)
self.assertEqual(func.captured_inputs, new_func.captured_inputs)
+ @test_util.run_deprecated_v1
def testBasic(self):
@function.Defun(dtypes.float32, dtypes.float32)
@@ -1359,6 +1380,7 @@ class FunctionsFromProtos(test.TestCase):
class FunctionOverloadTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testBasic(self):
@function.Defun()
@@ -1411,6 +1433,7 @@ class FunctionOverloadTest(test.TestCase):
class FunctionCaptureByValueTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testCaptureByValue(self):
g = ops.Graph()
with g.as_default():
@@ -1634,6 +1657,7 @@ class FunctionInlineControlTest(test.TestCase):
class ModuleFunctionTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testBasic(self):
@function.Defun(*[dtypes.float32] * 3)
@@ -1717,10 +1741,12 @@ class VariableHoistingTest(test.TestCase):
self.assertAllEqual(db.shape, (64,))
self.assertAllClose(np.sum(db), 0.509, rtol=1e-2)
+ @test_util.run_deprecated_v1
def testBasic(self):
self._testSimpleModel(True)
self._testSimpleModel(False)
+ @test_util.run_deprecated_v1
def testBasicResource(self):
self._testSimpleModel(True, use_resource=True)
self._testSimpleModel(False, use_resource=True)
diff --git a/tensorflow/python/framework/graph_util_test.py b/tensorflow/python/framework/graph_util_test.py
index 10a01c71f2c..4e7408ad49f 100644
--- a/tensorflow/python/framework/graph_util_test.py
+++ b/tensorflow/python/framework/graph_util_test.py
@@ -29,6 +29,7 @@ from tensorflow.python.framework import graph_util
from tensorflow.python.framework import importer
from tensorflow.python.framework import ops
from tensorflow.python.framework import tensor_util
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import gen_state_ops
from tensorflow.python.ops import math_ops # pylint: disable=unused-import
from tensorflow.python.ops import math_ops as math_ops_lib
@@ -102,6 +103,7 @@ class DeviceFunctionsTest(test.TestCase):
self.assertDeviceEqual(var_5.device, "/device:GPU:0")
self.assertDeviceEqual(var_6.device, "/device:CPU:0")
+ @test_util.run_deprecated_v1
def testNestedDeviceFunctions(self):
with ops.Graph().as_default():
var_0 = variables.VariableV1(0)
diff --git a/tensorflow/python/framework/meta_graph_test.py b/tensorflow/python/framework/meta_graph_test.py
index cc93f8b1b87..46ce4616a50 100644
--- a/tensorflow/python/framework/meta_graph_test.py
+++ b/tensorflow/python/framework/meta_graph_test.py
@@ -63,6 +63,7 @@ def _TestDir(test_name):
class SimpleMetaGraphTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testNoVariables(self):
test_dir = _TestDir("no_variables")
filename = os.path.join(test_dir, "metafile")
@@ -116,6 +117,7 @@ class SimpleMetaGraphTest(test.TestCase):
{new_input_tensor: input_feed_value})
self.assertEqual(new_output_value, output_value)
+ @test_util.run_deprecated_v1
def testStrippedOpListNestedFunctions(self):
with self.cached_session():
# Square two levels deep
@@ -158,6 +160,7 @@ class SimpleMetaGraphTest(test.TestCase):
op_list = meta_graph.stripped_op_list_for_graph(graph)
self.assertEqual(["Const"], [op.name for op in op_list.op])
+ @test_util.run_deprecated_v1
def testDefaultAttrStripping(self):
"""Verifies that default attributes are stripped from a graph def."""
@@ -210,6 +213,7 @@ class SimpleMetaGraphTest(test.TestCase):
self.assertEqual(node_def.attr["Tout"].type, dtypes.complex128)
self.assertTrue(meta_graph_def.meta_info_def.stripped_default_attrs)
+ @test_util.run_deprecated_v1
def testDefaultAttrStrippingNestedFunctions(self):
"""Verifies that default attributes are stripped from function node defs."""
with self.cached_session():
@@ -261,6 +265,7 @@ class SimpleMetaGraphTest(test.TestCase):
self.assertEqual(node_def.attr["attr_1"].i, 1)
self.assertTrue(meta_graph_def.meta_info_def.stripped_default_attrs)
+ @test_util.run_deprecated_v1
def testVariableObjectsAreSharedAmongCollections(self):
with ops.Graph().as_default() as graph1:
v = variables.Variable(3.0)
@@ -454,6 +459,7 @@ class ScopedMetaGraphTest(test.TestCase):
# Verifies that we can export the subgraph under each layer and import
# them into new layers in a new graph.
+ @test_util.run_deprecated_v1
def testScopedExportAndImport(self):
test_dir = _TestDir("scoped_export_import")
filenames = [
@@ -522,6 +528,7 @@ class ScopedMetaGraphTest(test.TestCase):
actual_grad_value = self.evaluate(grad)
self.assertEqual(expected_grad_value, actual_grad_value)
+ @test_util.run_deprecated_v1
def testImportWhileLoopInWhileLoop(self):
# Create a simple while loop.
with ops.Graph().as_default():
@@ -547,6 +554,7 @@ class ScopedMetaGraphTest(test.TestCase):
self.evaluate(variables.global_variables_initializer())
self.evaluate(x)
+ @test_util.run_deprecated_v1
def testScopedImportUnderNameScope(self):
graph = ops.Graph()
with graph.as_default():
@@ -562,6 +570,7 @@ class ScopedMetaGraphTest(test.TestCase):
self.assertEqual(list(imported_variables.values())[0].name,
"foo/bar/myvar:0")
+ @test_util.run_deprecated_v1
def testScopedImportUnderNameScopeNoVarScope(self):
graph = ops.Graph()
with graph.as_default():
@@ -590,6 +599,7 @@ class ScopedMetaGraphTest(test.TestCase):
self.assertEqual(list(imported_variables.values())[0].name,
"s" + suffix + "/v:0")
+ @test_util.run_deprecated_v1
def testScopedImportWithSelectedCollections(self):
meta_graph_filename = os.path.join(
_TestDir("selected_collections_import"), "meta_graph.pb")
@@ -687,6 +697,7 @@ class ScopedMetaGraphTest(test.TestCase):
# Verifies that we can export the subgraph containing a FIFOQueue under
# "queue1" and import it into "new_queue1" in a new graph.
+ @test_util.run_deprecated_v1
def testScopedWithQueue(self):
test_dir = _TestDir("scoped_with_queue")
orig_meta_graph = self._testScopedExportWithQueue(test_dir,
@@ -749,12 +760,15 @@ class ScopedMetaGraphTest(test.TestCase):
for n, e in zip(nodes, expected):
self.assertEqual([e], graph2.get_operation_by_name(n).get_attr("_class"))
+ @test_util.run_deprecated_v1
def testExportNestedNames(self):
self.doTestExportNestedNames(use_resource=False)
+ @test_util.run_deprecated_v1
def testExportNestedNamesResource(self):
self.doTestExportNestedNames(use_resource=True)
+ @test_util.run_deprecated_v1
def testPotentialCycle(self):
graph1 = ops.Graph()
with graph1.as_default():
@@ -783,6 +797,7 @@ class ScopedMetaGraphTest(test.TestCase):
4.0, shape=[2, 2])
})
+ @test_util.run_deprecated_v1
def testClearDevices(self):
graph1 = ops.Graph()
with graph1.as_default():
@@ -842,6 +857,7 @@ class ScopedMetaGraphTest(test.TestCase):
class MetaGraphWithVariableScopeTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testMetricsCollection(self):
def _enqueue_vector(sess, queue, values, shape=None):
@@ -899,6 +915,7 @@ class MetaGraphWithVariableScopeTest(test.TestCase):
class ExportImportAcrossScopesTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testPartionedVariables(self):
def make_graph_with_partitioned_variables(use_resource):
diff --git a/tensorflow/python/framework/ops_test.py b/tensorflow/python/framework/ops_test.py
index 9c9ef799f72..04a9ed05fd2 100644
--- a/tensorflow/python/framework/ops_test.py
+++ b/tensorflow/python/framework/ops_test.py
@@ -57,11 +57,13 @@ ops._set_call_cpp_shape_fn(common_shapes.call_cpp_shape_fn)
class ResourceTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testBuildGraph(self):
with self.cached_session():
pt = test_ops.stub_resource_handle_op(container="a", shared_name="b")
test_ops.resource_create_op(pt).run()
+ @test_util.run_deprecated_v1
def testInitialize(self):
with self.cached_session():
handle = test_ops.stub_resource_handle_op(container="a", shared_name="b")
@@ -106,6 +108,7 @@ class TensorAndShapeTest(test_util.TensorFlowTestCase):
c = a + b
self.assertEqual([2, 3], c.shape)
+ @test_util.run_deprecated_v1
def testUnknownDim(self):
with self.cached_session():
a = array_ops.placeholder(dtype=dtypes.float32, shape=[2, None, 3])
@@ -113,6 +116,7 @@ class TensorAndShapeTest(test_util.TensorFlowTestCase):
c = a + b
self.assertEqual([2, None, 3], c.shape.as_list())
+ @test_util.run_deprecated_v1
def testUnknownShape(self):
with self.cached_session():
a = array_ops.placeholder(dtype=dtypes.float32, shape=None)
@@ -120,6 +124,7 @@ class TensorAndShapeTest(test_util.TensorFlowTestCase):
c = a + b
self.assertEqual(tensor_shape.unknown_shape(), c.shape)
+ @test_util.run_deprecated_v1
def testScalarShape(self):
with self.cached_session():
a = array_ops.placeholder(dtype=dtypes.float32, shape=[])
@@ -127,6 +132,7 @@ class TensorAndShapeTest(test_util.TensorFlowTestCase):
c = a + b
self.assertEqual(tensor_shape.scalar(), c.shape)
+ @test_util.run_deprecated_v1
def testShapeFunctionError(self):
with self.cached_session():
a = array_ops.ones([1, 2, 3])
@@ -140,6 +146,7 @@ class TensorAndShapeTest(test_util.TensorFlowTestCase):
class IndexedSlicesTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testToTensor(self):
with self.cached_session():
values = constant_op.constant([2, 3, 5, 7], shape=[2, 2])
@@ -149,6 +156,7 @@ class IndexedSlicesTest(test_util.TensorFlowTestCase):
tensor = ops.convert_to_tensor(x, name="tensor")
self.assertAllEqual(tensor.eval(), [[2, 3], [0, 0], [5, 7]])
+ @test_util.run_deprecated_v1
def testNegation(self):
with self.cached_session():
values = constant_op.constant([2, 3, 5, 7], shape=[2, 2])
@@ -157,6 +165,7 @@ class IndexedSlicesTest(test_util.TensorFlowTestCase):
self.assertAllEqual(x.values.eval(), [[-2, -3], [-5, -7]])
self.assertAllEqual(x.indices.eval(), [0, 2])
+ @test_util.run_deprecated_v1
def testScalarMul(self):
with self.cached_session():
values = constant_op.constant([2, 3, 5, 7], shape=[2, 2])
@@ -190,6 +199,7 @@ def _apply_op(g, *args, **kwargs):
class OperationTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testNoInputs(self):
op = test_ops.float_output_string_output(name="myop").a.op
self.assertEqual(2, len(op.values()))
@@ -212,6 +222,7 @@ class OperationTest(test_util.TensorFlowTestCase):
self.assertProtoEquals("op:'FloatOutputStringOutput' name:'myop'",
op.node_def)
+ @test_util.run_deprecated_v1
def testNoOutputs(self):
op1 = test_ops.float_output(name="myop1").op
float_t, = op1.values()
@@ -227,6 +238,7 @@ class OperationTest(test_util.TensorFlowTestCase):
self.assertProtoEquals("op:'FloatInput' name:'myop2' input:'myop1'",
op2.node_def)
+ @test_util.run_deprecated_v1
def testInputsAndOutputs(self):
op1 = test_ops.float_output(name="myop1").op
self.assertEqual(1, len(op1.values()))
@@ -308,6 +320,7 @@ class OperationTest(test_util.TensorFlowTestCase):
with self.assertRaises(ValueError):
ops.Operation(ops._NodeDef("op", "invalid:0"), g)
+ @test_util.run_deprecated_v1
def testNoShapeFunction(self):
op = test_ops.a()
self.assertEqual(tensor_shape.unknown_shape(), op.get_shape())
@@ -333,6 +346,7 @@ class OperationTest(test_util.TensorFlowTestCase):
converted = ops.convert_to_tensor(1)
self.assertTrue(isinstance(converted, ops.EagerTensor))
+ @test_util.run_deprecated_v1
def testConvertToTensorNestedTuple(self):
with self.cached_session():
values = ((2,), (3,), (5,), (7,))
@@ -384,6 +398,7 @@ class OperationTest(test_util.TensorFlowTestCase):
values = [1.23]
_ = ops.convert_to_tensor(values, dtype=dtypes.int64)
+ @test_util.run_deprecated_v1
def testNoConvert(self):
# Operation cannot be converted to Tensor.
op = control_flow_ops.no_op()
@@ -401,6 +416,7 @@ class OperationTest(test_util.TensorFlowTestCase):
ops._NodeDef("None", "op1"), ops.Graph(), [], [dtypes.float32])
self.assertEqual("<tf.Operation 'op1' type=None>", repr(op))
+ @test_util.run_deprecated_v1
def testGetAttr(self):
op = test_ops.default_attrs()
self.assertEqual(op.get_attr("string_val"), b"abc")
@@ -446,6 +462,7 @@ class OperationTest(test_util.TensorFlowTestCase):
# TODO(b/65162920): remove this test when users who are directly mutating the
# node_def have been updated to proper usage.
+ @test_util.run_deprecated_v1
def testSetAttr(self):
op = test_ops.int_attr().op
op._set_attr("foo", attr_value_pb2.AttrValue(i=2))
@@ -466,6 +483,7 @@ class OperationTest(test_util.TensorFlowTestCase):
self.assertEqual(z.control_inputs, [x, y])
self.assertEqual(x._control_outputs, [z])
+ @test_util.run_deprecated_v1
def testRemoveAllControlInputs(self):
a = constant_op.constant(1)
with ops.control_dependencies([a]):
@@ -490,6 +508,7 @@ class OperationTest(test_util.TensorFlowTestCase):
self.assertEqual(f.op.control_inputs, [])
self.assertEqual(list(f.op.inputs), [d, e])
+ @test_util.run_deprecated_v1
def testControlInputCycle(self):
graph = ops.Graph()
with graph.as_default():
@@ -582,6 +601,7 @@ class OperationTest(test_util.TensorFlowTestCase):
):
x.op._update_input(1, x) # pylint: disable=protected-access
+ @test_util.run_deprecated_v1
def testOpDef(self):
x = constant_op.constant(0)
y = constant_op.constant(1)
@@ -681,6 +701,7 @@ class CreateOpTest(test_util.TensorFlowTestCase):
# the low-level behavior.
class CreateOpFromTFOperationTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testBasic(self):
g = ops.Graph()
with g.as_default():
@@ -731,6 +752,7 @@ class CreateOpFromTFOperationTest(test_util.TensorFlowTestCase):
self.assertEqual(op3.name, "myop_2")
self.assertEqual(op4.name, "myop_1_1")
+ @test_util.run_deprecated_v1
def testCond(self):
g = ops.Graph()
with g.as_default():
@@ -760,6 +782,7 @@ class CreateOpFromTFOperationTest(test_util.TensorFlowTestCase):
"cond/cond_text")
# pylint: enable=protected-access
+ @test_util.run_deprecated_v1
def testWhileLoop(self):
g = ops.Graph()
with g.as_default():
@@ -789,6 +812,7 @@ class CreateOpFromTFOperationTest(test_util.TensorFlowTestCase):
"myloop/while_context")
# pylint: enable=protected-access
+ @test_util.run_deprecated_v1
def testWhileLoopWithInternalControlDep(self):
g = ops.Graph()
with g.as_default():
@@ -812,6 +836,7 @@ class CreateOpFromTFOperationTest(test_util.TensorFlowTestCase):
# Internal control dep is preserved
self.assertEqual(op.control_inputs, [c])
+ @test_util.run_deprecated_v1
def testWhileLoopWithExternalControlDep(self):
g = ops.Graph()
with g.as_default():
@@ -945,6 +970,7 @@ class NameStackTest(test_util.TensorFlowTestCase):
self.assertEqual("bar_2", g.unique_name("bar", mark_as_used=False))
self.assertEqual("bar_2", g.unique_name("bar"))
+ @test_util.run_deprecated_v1
def testNameAndVariableScope(self):
with self.cached_session() as sess:
with sess.graph.name_scope("l0"):
@@ -1671,6 +1697,7 @@ def _CopyOverrideGrad(op, x_grad): # pylint: disable=invalid-name
class RegistrationTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testRegisterGradients(self):
x = test_ops.float_output()
y = test_ops.copy_op(x)
@@ -1710,6 +1737,7 @@ class ComparisonTest(test_util.TensorFlowTestCase):
class ControlDependenciesTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testBasic(self):
g = ops.Graph()
with g.as_default():
@@ -1953,6 +1981,7 @@ class OpScopeTest(test_util.TensorFlowTestCase):
with ops.name_scope(None, "default2") as scope2:
self.assertEqual(scope2, "default/default2/")
+ @test_util.run_deprecated_v1
def testNoScopeName(self):
g0 = ops.Graph()
values = [
@@ -1966,6 +1995,7 @@ class OpScopeTest(test_util.TensorFlowTestCase):
with ops.name_scope(None, None, values):
pass
+ @test_util.run_deprecated_v1
def testEmptyScopeName(self):
g0 = ops.Graph()
a = g0.create_op("A", [], [dtypes.float32])
@@ -1977,6 +2007,7 @@ class OpScopeTest(test_util.TensorFlowTestCase):
self.assertEqual("", scope)
self.assertEqual(g0, ops.get_default_graph())
+ @test_util.run_deprecated_v1
def testDefaultScopeName(self):
g0 = ops.Graph()
a = g0.create_op("A", [], [dtypes.float32])
@@ -2001,12 +2032,14 @@ class OpScopeTest(test_util.TensorFlowTestCase):
with ops.name_scope(scope_name, values=graph_elements + [a]):
pass
+ @test_util.run_deprecated_v1
def testTensor(self):
g0 = ops.Graph()
a = g0.create_op("A", [], [dtypes.float32])
b = g0.create_op("B", [], [dtypes.float32])
self._testGraphElements([a, b])
+ @test_util.run_deprecated_v1
def testSparseTensor(self):
g0 = ops.Graph()
a = g0.create_op("A", [], [dtypes.float32])
@@ -2017,6 +2050,7 @@ class OpScopeTest(test_util.TensorFlowTestCase):
_apply_op(g0, "Int64Output", [], [dtypes.int64]))
self._testGraphElements([a, sparse, b])
+ @test_util.run_deprecated_v1
def testVariable(self):
g0 = ops.Graph()
with g0.as_default():
@@ -2221,6 +2255,7 @@ class InitScopeTest(test_util.TensorFlowTestCase):
self.assertEqual(4, int(compiled_outer(inner=compiled_inner)))
self.assertEqual(7, int(compiled_outer(inner=compiled_inner)))
+ @test_util.run_deprecated_v1
def testFallsBackToGlobalGraphWhenAllGraphsAreBuildingFunctions(self):
with context.graph_mode():
ops.reset_default_graph()
@@ -2357,6 +2392,7 @@ class GraphTest(test_util.TensorFlowTestCase):
g.prevent_feeding(a)
self.assertFalse(g.is_feedable(a))
+ @test_util.run_deprecated_v1
def testPreventFetching(self):
g = ops.Graph()
a = constant_op.constant(2.0)
@@ -2440,10 +2476,12 @@ class AttrScopeTest(test_util.TensorFlowTestCase):
b = None
return (a, b)
+ @test_util.run_deprecated_v1
def testNoLabel(self):
with self.cached_session():
self.assertAllEqual((None, None), self._get_test_attrs())
+ @test_util.run_deprecated_v1
def testLabelMap(self):
with self.cached_session() as sess:
a1 = self._get_test_attrs()
@@ -2478,11 +2516,13 @@ ops.RegisterShape("KernelLabel")(common_shapes.scalar_shape)
class KernelLabelTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testNoLabel(self):
with self.cached_session():
self.assertAllEqual(b"My label is: default",
test_ops.kernel_label().eval())
+ @test_util.run_deprecated_v1
def testLabelMap(self):
with self.cached_session() as sess:
default_1 = test_ops.kernel_label()
@@ -2599,6 +2639,7 @@ class StatisticsTest(test_util.TensorFlowTestCase):
class DeviceStackTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testBasicDeviceAssignmentMetadata(self):
def device_func(unused_op):
@@ -2630,6 +2671,7 @@ class DeviceStackTest(test_util.TensorFlowTestCase):
expected_regex = r"device_func<.*ops_test.py, [0-9]+"
self.assertRegexpMatches(func_description, expected_regex)
+ @test_util.run_deprecated_v1
def testDeviceAssignmentMetadataForGraphDeviceAndTfDeviceFunctions(self):
with ops.device("/cpu"):
@@ -2649,6 +2691,7 @@ class DeviceStackTest(test_util.TensorFlowTestCase):
class ColocationGroupTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testBasic(self):
a = constant_op.constant([2.0], name="a")
with ops.colocate_with(a.op):
@@ -2659,6 +2702,7 @@ class ColocationGroupTest(test_util.TensorFlowTestCase):
with self.assertRaises(ValueError):
c.op.get_attr("_class")
+ @test_util.run_deprecated_v1
def testBasicColocationMetadata(self):
const_two = constant_op.constant([2.0], name="two")
with ops.colocate_with(const_two.op):
@@ -2671,6 +2715,7 @@ class ColocationGroupTest(test_util.TensorFlowTestCase):
# colocation statement.
self.assertEqual("ops_test.py", os.path.basename(metadata.filename))
+ @test_util.run_deprecated_v1
def testColocationDeviceInteraction(self):
with ops.device("/cpu:0"):
with ops.device("/device:GPU:0"):
@@ -2683,6 +2728,7 @@ class ColocationGroupTest(test_util.TensorFlowTestCase):
self.assertEqual([b"loc:@a"], b.op.colocation_groups())
self.assertEqual(a.op.device, b.op.device)
+ @test_util.run_deprecated_v1
def testColocationCanonicalization(self):
with ops.device("/device:GPU:0"):
_ = constant_op.constant(2.0)
@@ -2698,6 +2744,7 @@ class ColocationGroupTest(test_util.TensorFlowTestCase):
# inherits B's device name, after canonicalizing the names.
self.assertEqual(b.op.device, c.op.device)
+ @test_util.run_deprecated_v1
def testLocationOverrides(self):
with ops.device("/cpu:0"):
with ops.device("/device:GPU:0"):
@@ -2719,6 +2766,7 @@ class ColocationGroupTest(test_util.TensorFlowTestCase):
self.assertEqual("/device:GPU:0", c.op.device)
self.assertEqual("/device:CPU:0", d.op.device)
+ @test_util.run_deprecated_v1
def testNestedColocateWith(self):
a = constant_op.constant([2.0], name="a")
with ops.colocate_with(a.op):
@@ -2728,6 +2776,7 @@ class ColocationGroupTest(test_util.TensorFlowTestCase):
self.assertEqual([b"loc:@a"], b.op.colocation_groups())
self.assertEqual([b"loc:@a"], c.op.colocation_groups())
+ @test_util.run_deprecated_v1
def testMultiColocationGroups(self):
a = constant_op.constant([2.0], name="a")
b = constant_op.constant(3.0, name="b")
@@ -2736,6 +2785,7 @@ class ColocationGroupTest(test_util.TensorFlowTestCase):
c = constant_op.constant(4.0)
self.assertEqual(set([b"loc:@a", b"loc:@b"]), set(c.op.colocation_groups()))
+ @test_util.run_deprecated_v1
def testColocationIgnoreStack(self):
a = constant_op.constant([2.0], name="a")
b = constant_op.constant(3.0, name="b")
@@ -2744,6 +2794,7 @@ class ColocationGroupTest(test_util.TensorFlowTestCase):
c = constant_op.constant(4.0)
self.assertEqual(set([b"loc:@b"]), set(c.op.colocation_groups()))
+ @test_util.run_deprecated_v1
def testColocateWithReset(self):
a = constant_op.constant([2.0], name="a")
with ops.colocate_with(a.op):
@@ -2753,6 +2804,7 @@ class ColocationGroupTest(test_util.TensorFlowTestCase):
self.assertEqual([b"loc:@a"], b.op.colocation_groups())
self.assertEqual([b"loc:@c"], c.op.colocation_groups())
+ @test_util.run_deprecated_v1
def testColocateWithInitialNoneThenNested(self):
a = constant_op.constant([2.0], name="a")
with ops.colocate_with(a.op):
@@ -2763,12 +2815,14 @@ class ColocationGroupTest(test_util.TensorFlowTestCase):
self.assertEqual([b"loc:@b"], b.op.colocation_groups())
self.assertEqual([b"loc:@b"], c.op.colocation_groups())
+ @test_util.run_deprecated_v1
def testColocateVariables(self):
a = variables.Variable([2.0], name="a")
with ops.colocate_with(a.op):
b = variables.Variable([3.0], name="b")
self.assertEqual([b"loc:@a"], b.op.colocation_groups())
+ @test_util.run_deprecated_v1
def testInconsistentDeviceWithinColocate(self):
with ops.device("/device:GPU:0"):
a = constant_op.constant([2.0], name="a")
@@ -2782,6 +2836,7 @@ class ColocationGroupTest(test_util.TensorFlowTestCase):
self.assertEqual("/device:CPU:0", b.device)
+ @test_util.run_deprecated_v1
def testMakeColocationConflictMessage(self):
"""Test that provides an example of a complicated error message."""
# We could test the message with any ops, but this test will be more
@@ -2926,6 +2981,7 @@ class NameScopeTest(test_util.TensorFlowTestCase):
class TracebackTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testTracebackWithStartLines(self):
with self.cached_session() as sess:
a = constant_op.constant(2.0)
@@ -2947,6 +3003,7 @@ class TracebackTest(test_util.TensorFlowTestCase):
class EnableEagerExecutionTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testBadArgumentsToEnableEagerExecution(self):
with self.assertRaisesRegexp(TypeError, "config must be a tf.ConfigProto"):
ops.enable_eager_execution(context.DEVICE_PLACEMENT_SILENT)
diff --git a/tensorflow/python/framework/smart_cond_test.py b/tensorflow/python/framework/smart_cond_test.py
index 174ada9fe11..f964c87f024 100644
--- a/tensorflow/python/framework/smart_cond_test.py
+++ b/tensorflow/python/framework/smart_cond_test.py
@@ -35,6 +35,7 @@ def raise_exception():
class SmartCondTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testTrue(self):
with ops.Graph().as_default():
with session.Session():
@@ -44,6 +45,7 @@ class SmartCondTest(test_util.TensorFlowTestCase):
lambda: math_ops.multiply(y, 5))
self.assertEqual(z.eval(), 32)
+ @test_util.run_deprecated_v1
def testFalse(self):
with ops.Graph().as_default():
with session.Session():
@@ -99,6 +101,7 @@ class SmartCondTest(test_util.TensorFlowTestCase):
class SmartCaseTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testTrue(self):
x = array_ops.placeholder(dtype=dtypes.int32, shape=[])
conditions = [(True, lambda: constant_op.constant(1)),
@@ -112,6 +115,7 @@ class SmartCaseTest(test_util.TensorFlowTestCase):
self.assertEqual(self.evaluate(y), 1)
self.assertEqual(self.evaluate(z), 1)
+ @test_util.run_deprecated_v1
def testFalse(self):
conditions = [(False, raise_exception)]
y = smart_cond.smart_case(conditions,
@@ -124,6 +128,7 @@ class SmartCaseTest(test_util.TensorFlowTestCase):
self.assertEqual(self.evaluate(y), 1)
self.assertEqual(self.evaluate(z), 1)
+ @test_util.run_deprecated_v1
def testMix(self):
x = array_ops.placeholder(dtype=dtypes.int32, shape=[])
y = constant_op.constant(10)
diff --git a/tensorflow/python/framework/sparse_tensor_test.py b/tensorflow/python/framework/sparse_tensor_test.py
index 9ee1bd75a53..a999c12ca89 100644
--- a/tensorflow/python/framework/sparse_tensor_test.py
+++ b/tensorflow/python/framework/sparse_tensor_test.py
@@ -65,6 +65,7 @@ class SparseTensorTest(test_util.TensorFlowTestCase):
sparse_tensor.is_sparse(
sparse_tensor.SparseTensorValue([[0]], [0], [1])))
+ @test_util.run_deprecated_v1
def testConsumers(self):
sp = sparse_tensor.SparseTensor([[0, 0], [1, 2]], [1.0, 3.0], [3, 4])
w = ops.convert_to_tensor(np.ones([4, 1], np.float32))
@@ -87,6 +88,7 @@ class ConvertToTensorOrSparseTensorTest(test_util.TensorFlowTestCase):
value)
self.assertAllEqual(value, self.evaluate(from_value))
+ @test_util.run_deprecated_v1
def test_convert_sparse(self):
with self.cached_session():
indices = [[0, 1], [1, 0]]
diff --git a/tensorflow/python/framework/subscribe_test.py b/tensorflow/python/framework/subscribe_test.py
index 5322204ce67..61c6ea65190 100644
--- a/tensorflow/python/framework/subscribe_test.py
+++ b/tensorflow/python/framework/subscribe_test.py
@@ -43,6 +43,7 @@ class SubscribeTest(test_util.TensorFlowTestCase):
self.assertTrue(
all(subscribe._is_subscribed_identity(x) for x in container))
+ @test_util.run_deprecated_v1
def testSideEffect(self):
a = constant_op.constant(1)
b = constant_op.constant(1)
@@ -75,6 +76,7 @@ class SubscribeTest(test_util.TensorFlowTestCase):
self.assertEqual(d_out, [42])
self.assertEqual(shared, [2, 2, 2])
+ @test_util.run_deprecated_v1
def testSupportedTypes(self):
"""Confirm that supported types are correctly detected and handled."""
@@ -120,6 +122,7 @@ class SubscribeTest(test_util.TensorFlowTestCase):
subscribe.subscribe(c.name,
lambda t: script_ops.py_func(sub, [t], [t.dtype]))
+ @test_util.run_deprecated_v1
def testCaching(self):
"""Confirm caching of control output is recalculated between calls."""
a = constant_op.constant(1)
@@ -152,6 +155,7 @@ class SubscribeTest(test_util.TensorFlowTestCase):
self.assertEqual(d_out, [11])
self.assertEqual(shared, {2: 1, 1: 1})
+ @test_util.run_deprecated_v1
def testIsSubscribedIdentity(self):
"""Confirm subscribed identity ops are correctly detected."""
a = constant_op.constant(1)
@@ -165,6 +169,7 @@ class SubscribeTest(test_util.TensorFlowTestCase):
self.assertFalse(subscribe._is_subscribed_identity(idop))
self.assertTrue(subscribe._is_subscribed_identity(c_sub))
+ @test_util.run_deprecated_v1
def testSubscribeExtend(self):
"""Confirm side effect are correctly added for different input types."""
a = constant_op.constant(1)
@@ -210,6 +215,7 @@ class SubscribeTest(test_util.TensorFlowTestCase):
self.assertIn('graph2', shared)
self.assertIn('graph3', shared)
+ @test_util.run_deprecated_v1
def testSubscribeVariable(self):
"""Confirm that variables can be subscribed."""
v1 = variables.VariableV1(0.0)
@@ -248,6 +254,7 @@ class SubscribeTest(test_util.TensorFlowTestCase):
# Make sure the values read from the variable match the expected ones.
self.assertEqual([0.0, 3.0], shared)
+ @test_util.run_deprecated_v1
def testResourceType(self):
"""Confirm that subscribe correctly handles tensors with 'resource' type."""
tensor_array = tensor_array_ops.TensorArray(
@@ -276,6 +283,7 @@ class SubscribeTest(test_util.TensorFlowTestCase):
self.evaluate([reader])
self.assertEqual(0, len(shared))
+ @test_util.run_deprecated_v1
def testMultipleOutputs(self):
"""Handle subscriptions to multiple outputs from the same op."""
sparse_tensor_1 = sparse_tensor.SparseTensor(
@@ -309,6 +317,7 @@ class SubscribeTest(test_util.TensorFlowTestCase):
# All three ops have been processed.
self.assertEqual(3, len(shared))
+ @test_util.run_deprecated_v1
def test_subscribe_tensors_on_different_devices(self):
"""Side effect ops are added with the same device of the subscribed op."""
c1 = constant_op.constant(10)
@@ -335,6 +344,7 @@ class SubscribeTest(test_util.TensorFlowTestCase):
self.assertEqual(add.device, add_sub.device)
self.assertEqual(mul.device, mul_sub.device)
+ @test_util.run_deprecated_v1
def test_subscribe_tensors_within_control_flow_context(self):
"""Side effect ops are added with the same control flow context."""
c1 = constant_op.constant(10)
diff --git a/tensorflow/python/framework/tensor_spec_test.py b/tensorflow/python/framework/tensor_spec_test.py
index e3aad7cc236..75c197df09e 100644
--- a/tensorflow/python/framework/tensor_spec_test.py
+++ b/tensorflow/python/framework/tensor_spec_test.py
@@ -45,6 +45,7 @@ class TensorSpecTest(test_util.TensorFlowTestCase):
desc = tensor_spec.TensorSpec(shape=None, dtype=dtypes.float32)
self.assertEqual(desc.shape, tensor_shape.TensorShape(None))
+ @test_util.run_deprecated_v1
def testShapeCompatibility(self):
unknown = array_ops.placeholder(dtypes.int64)
partial = array_ops.placeholder(dtypes.int64, shape=[None, 1])
@@ -75,6 +76,7 @@ class TensorSpecTest(test_util.TensorFlowTestCase):
self.assertFalse(desc_rank3.is_compatible_with(full))
self.assertTrue(desc_rank3.is_compatible_with(rank3))
+ @test_util.run_deprecated_v1
def testTypeCompatibility(self):
floats = array_ops.placeholder(dtypes.float32, shape=[10, 10])
ints = array_ops.placeholder(dtypes.int32, shape=[10, 10])
@@ -106,6 +108,7 @@ class TensorSpecTest(test_util.TensorFlowTestCase):
spec_2 = tensor_spec.TensorSpec.from_spec(spec_1)
self.assertEqual(spec_1, spec_2)
+ @test_util.run_deprecated_v1
def testFromTensor(self):
zero = constant_op.constant(0)
spec = tensor_spec.TensorSpec.from_tensor(zero)
@@ -113,6 +116,7 @@ class TensorSpecTest(test_util.TensorFlowTestCase):
self.assertEqual(spec.shape, [])
self.assertEqual(spec.name, "Const")
+ @test_util.run_deprecated_v1
def testFromPlaceholder(self):
unknown = array_ops.placeholder(dtypes.int64, name="unknown")
partial = array_ops.placeholder(dtypes.float32,
diff --git a/tensorflow/python/framework/tensor_util_test.py b/tensorflow/python/framework/tensor_util_test.py
index 87d65c8c466..00337546186 100644
--- a/tensorflow/python/framework/tensor_util_test.py
+++ b/tensorflow/python/framework/tensor_util_test.py
@@ -758,6 +758,7 @@ class TensorUtilTest(test.TestCase):
self.assertFalse(tensor_util.ShapeEquals(t, [1, 4]))
self.assertFalse(tensor_util.ShapeEquals(t, [4]))
+ @test_util.run_deprecated_v1
def testMockArray(self):
class MockArray(object):
@@ -787,6 +788,7 @@ class ConstantValueTest(test.TestCase):
tf_val = constant_op.constant(np_val)
self.assertAllClose(np_val, tensor_util.constant_value(tf_val))
+ @test_util.run_deprecated_v1
def testUnknown(self):
tf_val = gen_state_ops.variable(
shape=[3, 4, 7],
@@ -815,12 +817,14 @@ class ConstantValueTest(test.TestCase):
c_val = tensor_util.constant_value(tf_val)
self.assertEqual(6, c_val)
+ @test_util.run_deprecated_v1
def testSizeOfScalar(self):
tf_val = array_ops.size(constant_op.constant(0.0))
c_val = tensor_util.constant_value(tf_val)
self.assertEqual(1, c_val)
self.assertEqual(np.ndarray, type(c_val))
+ @test_util.run_deprecated_v1
def testRank(self):
tf_val = array_ops.rank(constant_op.constant(0.0, shape=[1, 2, 3]))
c_val = tensor_util.constant_value(tf_val)
@@ -852,6 +856,7 @@ class ConstantValueTest(test.TestCase):
c_val = tensor_util.constant_value(tf_val)
self.assertAllClose(np_val.astype(np.float64), c_val)
+ @test_util.run_deprecated_v1
def testConcat(self):
np_val = np.random.rand(3, 4, 7).astype(np.float32)
tf_val = array_ops.concat(
@@ -871,6 +876,7 @@ class ConstantValueTest(test.TestCase):
c_val = tensor_util.constant_value(tf_val)
self.assertIs(None, c_val)
+ @test_util.run_deprecated_v1
def testPack_Axis0(self):
inputs = [np.random.rand(4, 7) for _ in range(3)]
np_val = np.array(inputs)
@@ -883,6 +889,7 @@ class ConstantValueTest(test.TestCase):
c_val = tensor_util.constant_value(tf_val)
self.assertIs(None, c_val)
+ @test_util.run_deprecated_v1
def testPack_Axis1(self):
inputs = [np.random.rand(4, 7) for _ in range(3)]
tf_val = array_ops.stack(inputs, axis=1)
@@ -894,6 +901,7 @@ class ConstantValueTest(test.TestCase):
c_val = tensor_util.constant_value(tf_val)
self.assertIs(None, c_val)
+ @test_util.run_deprecated_v1
def testPack_Partial_Axis0(self):
input_ = np.random.rand(4, 7)
tf_val = array_ops.stack([input_, array_ops.placeholder(dtypes.float32)])
@@ -901,6 +909,7 @@ class ConstantValueTest(test.TestCase):
self.assertAllClose(input_, c_val[0])
self.assertIsNone(c_val[1])
+ @test_util.run_deprecated_v1
def testPack_Partial_Axis1(self):
input_ = np.random.rand(4, 7)
tf_val = array_ops.stack([input_, array_ops.placeholder(dtypes.float32)],
@@ -966,12 +975,14 @@ class ConstantValueAsShapeTest(test.TestCase):
c_val = tensor_util.constant_value_as_shape(tf_val)
self.assertEqual([None, 1, None], c_val.as_list())
+ @test_util.run_deprecated_v1
def testPack(self):
tf_val = array_ops.stack(
[constant_op.constant(16), 37, array_ops.placeholder(dtypes.int32)])
c_val = tensor_util.constant_value_as_shape(tf_val)
self.assertEqual([16, 37, None], c_val.as_list())
+ @test_util.run_deprecated_v1
def testConcat(self):
tf_val = array_ops.concat(
[[16, 37], array_ops.placeholder(
@@ -985,6 +996,7 @@ class ConstantValueAsShapeTest(test.TestCase):
c_val = tensor_util.constant_value_as_shape(tf_val)
self.assertEqual([16, 37, None, 48], c_val.as_list())
+ @test_util.run_deprecated_v1
def testSlice(self):
tf_val = array_ops.placeholder(dtypes.int32, shape=(4,))[0:2]
c_val = tensor_util.constant_value_as_shape(tf_val)
diff --git a/tensorflow/python/framework/test_util_test.py b/tensorflow/python/framework/test_util_test.py
index 2a37253db6d..dfdced5a988 100644
--- a/tensorflow/python/framework/test_util_test.py
+++ b/tensorflow/python/framework/test_util_test.py
@@ -49,6 +49,7 @@ from tensorflow.python.platform import googletest
class TestUtilTest(test_util.TensorFlowTestCase, parameterized.TestCase):
+ @test_util.run_deprecated_v1
def test_assert_ops_in_graph(self):
with self.test_session():
constant_op.constant(["hello", "taffy"], name="hello")
@@ -60,6 +61,7 @@ class TestUtilTest(test_util.TensorFlowTestCase, parameterized.TestCase):
self.assertRaises(ValueError, test_util.assert_ops_in_graph,
{"hello": "Variable"}, ops.get_default_graph())
+ @test_util.run_deprecated_v1
def test_session_functions(self):
with self.test_session() as sess:
sess_ref = weakref.ref(sess)
@@ -551,6 +553,7 @@ class TestUtilTest(test_util.TensorFlowTestCase, parameterized.TestCase):
with self.assertRaises(AssertionError):
self.assertAllLessEqual(x, 95.0)
+ @test_util.run_deprecated_v1
def testAssertAllInRangeWithNonNumericValuesFails(self):
s1 = constant_op.constant("Hello, ", name="s1")
c = constant_op.constant([1 + 2j, -3 + 5j], name="c")
@@ -614,6 +617,7 @@ class TestUtilTest(test_util.TensorFlowTestCase, parameterized.TestCase):
with self.assertRaises(AssertionError):
self.assertAllInSet(x, (42,))
+ @test_util.run_deprecated_v1
def testRandomSeed(self):
# Call setUp again for WithCApi case (since it makes a new defeault graph
# after setup).
@@ -706,6 +710,7 @@ class TestUtilTest(test_util.TensorFlowTestCase, parameterized.TestCase):
test_util.run_in_graph_and_eager_modes(_test)(self)
self.assertEqual(modes, ["graph"])
+ @test_util.run_deprecated_v1
def test_run_in_graph_and_eager_modes_setup_in_same_mode(self):
modes = []
mode_name = lambda: "eager" if context.executing_eagerly() else "graph"
diff --git a/tensorflow/python/grappler/cost_analyzer_test.py b/tensorflow/python/grappler/cost_analyzer_test.py
index de80df1879d..ee3e289f65d 100644
--- a/tensorflow/python/grappler/cost_analyzer_test.py
+++ b/tensorflow/python/grappler/cost_analyzer_test.py
@@ -38,6 +38,7 @@ from tensorflow.python.training import adam
class CostAnalysisTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testBasicCost(self):
"""Make sure arguments can be passed correctly."""
a = constant_op.constant(10, name="a")
@@ -62,6 +63,7 @@ class CostAnalysisTest(test.TestCase):
# Also print the report to make it easier to debug
print("{}".format(report))
+ @test_util.run_deprecated_v1
def testVerbose(self):
"""Make sure the full report is generated with verbose=True."""
a = constant_op.constant(10, name="a")
@@ -81,6 +83,7 @@ class CostAnalysisTest(test.TestCase):
# Also print the report to make it easier to debug
print("{}".format(report))
+ @test_util.run_deprecated_v1
def testSmallNetworkCost(self):
image = array_ops.placeholder(dtypes.float32, shape=[1, 28, 28, 1])
label = array_ops.placeholder(dtypes.float32, shape=[1, 10])
@@ -129,6 +132,7 @@ class CostAnalysisTest(test.TestCase):
# self.assertTrue(0 < upper)
# self.assertTrue(lower <= upper)
+ @test_util.run_deprecated_v1
def testBasicMemory(self):
"""Make sure arguments can be passed correctly."""
with test_util.device(use_gpu=False):
diff --git a/tensorflow/python/grappler/item_test.py b/tensorflow/python/grappler/item_test.py
index d3d96c646cd..78604b259ca 100644
--- a/tensorflow/python/grappler/item_test.py
+++ b/tensorflow/python/grappler/item_test.py
@@ -24,6 +24,7 @@ from tensorflow.python.framework import errors_impl
from tensorflow.python.framework import meta_graph
from tensorflow.python.framework import ops
from tensorflow.python.framework import tensor_shape
+from tensorflow.python.framework import test_util
from tensorflow.python.grappler import item
from tensorflow.python.ops import control_flow_ops
from tensorflow.python.ops import gen_array_ops
@@ -107,6 +108,7 @@ class ItemTest(test.TestCase):
newest_tf_item = grappler_item.tf_item
self.assertEqual(new_tf_item, newest_tf_item)
+ @test_util.run_deprecated_v1
def testColocationContraints(self):
with ops.Graph().as_default() as g:
c = constant_op.constant([10])
diff --git a/tensorflow/python/grappler/layout_optimizer_test.py b/tensorflow/python/grappler/layout_optimizer_test.py
index 55ccfbb93c3..98f2e6d7181 100644
--- a/tensorflow/python/grappler/layout_optimizer_test.py
+++ b/tensorflow/python/grappler/layout_optimizer_test.py
@@ -29,6 +29,7 @@ from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
from tensorflow.python.framework import random_seed
+from tensorflow.python.framework import test_util
from tensorflow.python.grappler import cluster as gcluster
from tensorflow.python.grappler import tf_optimizer
from tensorflow.python.layers import convolutional as conv_layers
@@ -1441,6 +1442,7 @@ class LayoutOptimizerTest(test.TestCase):
self._assert_trans_nchw_to_nhwc('Add-0-0', nodes)
self.assertAllClose(output_val_ref, output_val, atol=1e-3)
+ @test_util.run_deprecated_v1
def testGradient(self):
meta_graph = _simple_metagraph()
config = config_pb2.ConfigProto()
@@ -1458,6 +1460,7 @@ class LayoutOptimizerTest(test.TestCase):
self.assertEqual(node.attr['data_format'].s, b'NCHW')
self.assertEqual(found, 5)
+ @test_util.run_deprecated_v1
def testDepthwise(self):
meta_graph = _simple_metagraph(depthwise=True)
config = config_pb2.ConfigProto()
diff --git a/tensorflow/python/grappler/memory_optimizer_test.py b/tensorflow/python/grappler/memory_optimizer_test.py
index d233629cbbd..6eb16fbd39e 100644
--- a/tensorflow/python/grappler/memory_optimizer_test.py
+++ b/tensorflow/python/grappler/memory_optimizer_test.py
@@ -25,6 +25,7 @@ from tensorflow.python.client import session
from tensorflow.python.framework import meta_graph
from tensorflow.python.framework import ops
from tensorflow.python.framework import random_seed
+from tensorflow.python.framework import test_util
from tensorflow.python.grappler import tf_optimizer
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import nn
@@ -37,6 +38,7 @@ from tensorflow.python.training import training as train
class MemoryOptimizerSwapTest(test.TestCase):
"""Tests the Grappler memory optimizer."""
+ @test_util.run_deprecated_v1
def testNoSwapping(self):
"""Make sure the graph is preserved when there is nothing to swap."""
a = variables.VariableV1(10, name='a')
@@ -60,6 +62,7 @@ class MemoryOptimizerSwapTest(test.TestCase):
self.assertEqual(len(graph.node), graph_size)
self.assertItemsEqual([node.name for node in graph.node], nodes)
+ @test_util.run_deprecated_v1
def testSimpleSwap(self):
"""Check that the swap annotations are followed."""
a = variables.VariableV1(10, name='a')
diff --git a/tensorflow/python/grappler/model_analyzer_test.py b/tensorflow/python/grappler/model_analyzer_test.py
index ec172755f1a..d000cfa1ba2 100644
--- a/tensorflow/python/grappler/model_analyzer_test.py
+++ b/tensorflow/python/grappler/model_analyzer_test.py
@@ -21,6 +21,7 @@ from __future__ import print_function
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import meta_graph
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.grappler import model_analyzer
from tensorflow.python.ops import math_ops
from tensorflow.python.platform import test
@@ -28,6 +29,7 @@ from tensorflow.python.platform import test
class PyWrapOptimizeGraphTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testBasic(self):
"""Make sure arguments can be passed correctly."""
a = constant_op.constant([10, 11], name="a")
@@ -49,6 +51,7 @@ class PyWrapOptimizeGraphTest(test.TestCase):
# Also print the report to make it easier to debug
print("{}".format(report))
+ @test_util.run_deprecated_v1
def testDebugMode(self):
"""Make sure arguments can be passed correctly."""
a = constant_op.constant([10, 11], name="a")
diff --git a/tensorflow/python/grappler/tf_optimizer_test.py b/tensorflow/python/grappler/tf_optimizer_test.py
index 0a4d4cbe2db..06ccaa813f2 100644
--- a/tensorflow/python/grappler/tf_optimizer_test.py
+++ b/tensorflow/python/grappler/tf_optimizer_test.py
@@ -23,6 +23,7 @@ from tensorflow.python.framework import dtypes
from tensorflow.python.framework import meta_graph
from tensorflow.python.framework import ops
from tensorflow.python.framework import tensor_shape
+from tensorflow.python.framework import test_util
from tensorflow.python.grappler import item as gitem
from tensorflow.python.grappler import tf_optimizer
from tensorflow.python.ops import array_ops
@@ -34,6 +35,7 @@ from tensorflow.python.platform import test
class PyWrapOptimizeGraphTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testBasic(self):
"""Make sure arguments can be passed correctly."""
a = constant_op.constant(10, name='a')
@@ -55,6 +57,7 @@ class PyWrapOptimizeGraphTest(test.TestCase):
self.assertEqual(len(graph.node), 1)
self.assertItemsEqual([node.name for node in graph.node], ['d'])
+ @test_util.run_deprecated_v1
def testKeepNodes(self):
g = ops.Graph()
with g.as_default():
@@ -83,6 +86,7 @@ class PyWrapOptimizeGraphTest(test.TestCase):
self.assertEqual(len(optimized_graph_nodes), len(expected_nodes))
self.assertAllInSet(optimized_graph_nodes, expected_nodes)
+ @test_util.run_deprecated_v1
def testLoops(self):
g = ops.Graph()
with g.as_default():
diff --git a/tensorflow/python/keras/activations_test.py b/tensorflow/python/keras/activations_test.py
index ad238cb0a9b..6b7bfb698b8 100644
--- a/tensorflow/python/keras/activations_test.py
+++ b/tensorflow/python/keras/activations_test.py
@@ -21,6 +21,7 @@ from __future__ import print_function
import numpy as np
from tensorflow.python import keras
+from tensorflow.python.framework import test_util
from tensorflow.python.platform import test
@@ -67,6 +68,7 @@ class KerasActivationsTest(test.TestCase):
expected = _ref_softmax(test_values[0, 0])
self.assertAllClose(result[0, 0], expected, rtol=1e-05)
+ @test_util.run_deprecated_v1
def test_selu(self):
x = keras.backend.placeholder(ndim=2)
f = keras.backend.function([x], [keras.activations.selu(x)])
@@ -124,6 +126,7 @@ class KerasActivationsTest(test.TestCase):
expected = sigmoid(test_values)
self.assertAllClose(result, expected, rtol=1e-05)
+ @test_util.run_deprecated_v1
def test_hard_sigmoid(self):
def ref_hard_sigmoid(x):
x = (x * 0.2) + 0.5
@@ -147,6 +150,7 @@ class KerasActivationsTest(test.TestCase):
# No negative values in test values...
self.assertAllClose(result, test_values, rtol=1e-05)
+ @test_util.run_deprecated_v1
def test_elu(self):
with self.cached_session():
x = keras.backend.placeholder(ndim=2)
diff --git a/tensorflow/python/keras/backend_test.py b/tensorflow/python/keras/backend_test.py
index 48fdd56e9f6..fa32b1ecd7a 100644
--- a/tensorflow/python/keras/backend_test.py
+++ b/tensorflow/python/keras/backend_test.py
@@ -1422,6 +1422,7 @@ class TestCTC(test.TestCase):
decode_truth[i] == keras.backend.eval(decode_pred_tf[i])))
self.assertAllClose(log_prob_truth, log_prob_pred)
+ @test_util.run_deprecated_v1
def test_ctc_batch_cost(self):
with self.cached_session():
label_lens = np.expand_dims(np.asarray([5, 4]), 1)
@@ -1507,6 +1508,7 @@ class TestRandomOps(test.TestCase):
class BackendGraphTests(test.TestCase):
+ @test_util.run_deprecated_v1
def test_is_placeholder(self):
x = keras.backend.placeholder(shape=(1,))
self.assertEqual(keras.backend.is_placeholder(x), True)
@@ -1546,6 +1548,7 @@ class BackendGraphTests(test.TestCase):
output_values = f([None, None])
self.assertEqual(output_values, [5., 6.])
+ @test_util.run_deprecated_v1
def test_function_tf_feed_symbols(self):
# Test Keras backend functions with TF tensor inputs.
with self.cached_session():
@@ -1579,6 +1582,7 @@ class BackendGraphTests(test.TestCase):
outs = f([y5, y2, None])
self.assertEqual(outs, [11., 2.])
+ @test_util.run_deprecated_v1
def test_function_tf_fetches(self):
# Additional operations can be passed to tf.Session().run() via its
# `fetches` arguments. In contrast to `updates` argument of
@@ -1601,6 +1605,7 @@ class BackendGraphTests(test.TestCase):
self.assertEqual(keras.backend.get_session().run(fetches=[x, y]),
[11., 5.])
+ @test_util.run_deprecated_v1
def test_function_tf_feed_dict(self):
# Additional substitutions can be passed to `tf.Session().run()` via its
# `feed_dict` arguments. Note that the feed_dict is passed once in the
@@ -1633,6 +1638,7 @@ class BackendGraphTests(test.TestCase):
self.assertEqual(keras.backend.get_session().run(fetches=[x, y]),
[30., 40.])
+ @test_util.run_deprecated_v1
def test_function_tf_run_options_with_run_metadata(self):
with self.cached_session():
x_placeholder = keras.backend.placeholder(shape=())
@@ -1658,6 +1664,7 @@ class BackendGraphTests(test.TestCase):
self.assertEqual(output1, [30.])
self.assertEqual(len(run_metadata.partition_graphs), 0)
+ @test_util.run_deprecated_v1
def test_function_fetch_callbacks(self):
class CallbackStub(object):
@@ -1694,6 +1701,7 @@ class BackendGraphTests(test.TestCase):
x = keras.backend.placeholder(shape=(3, 4), sparse=True)
self.assertEqual(x.get_shape().as_list(), [3, 4])
+ @test_util.run_deprecated_v1
def test_batch_normalization(self):
# No eager CPU kernel.
g_val = np.random.random((3,))
diff --git a/tensorflow/python/keras/callbacks_test.py b/tensorflow/python/keras/callbacks_test.py
index 9d9ede22c01..ed05572c68b 100644
--- a/tensorflow/python/keras/callbacks_test.py
+++ b/tensorflow/python/keras/callbacks_test.py
@@ -404,6 +404,7 @@ class KerasCallbacksTest(test.TestCase):
float(keras.backend.get_value(
model.optimizer.lr)) - 0.01 / 4) < keras.backend.epsilon()
+ @test_util.run_deprecated_v1
def test_ReduceLROnPlateau(self):
with self.cached_session():
np.random.seed(1337)
@@ -675,6 +676,7 @@ class KerasCallbacksTest(test.TestCase):
self.assertEqual(len(loss), 1)
self.assertEqual(loss[0], np.inf)
+ @test_util.run_deprecated_v1
def test_TensorBoard(self):
np.random.seed(1337)
@@ -778,6 +780,7 @@ class KerasCallbacksTest(test.TestCase):
data_generator(True), len(x_train), epochs=2, callbacks=cbks)
assert os.path.exists(temp_dir)
+ @test_util.run_deprecated_v1
def test_TensorBoard_histogram_freq_must_have_validation_data(self):
np.random.seed(1337)
tmpdir = self.get_temp_dir()
@@ -850,6 +853,7 @@ class KerasCallbacksTest(test.TestCase):
# Make sure file writer cache is clear to avoid failures during cleanup.
writer_cache.FileWriterCache.clear()
+ @test_util.run_deprecated_v1
def test_TensorBoard_multi_input_output(self):
np.random.seed(1337)
tmpdir = self.get_temp_dir()
@@ -921,6 +925,7 @@ class KerasCallbacksTest(test.TestCase):
callbacks=callbacks_factory(histogram_freq=1))
assert os.path.isdir(filepath)
+ @test_util.run_deprecated_v1
def test_Tensorboard_histogram_summaries_in_test_function(self):
class FileWriterStub(object):
@@ -998,6 +1003,7 @@ class KerasCallbacksTest(test.TestCase):
self.assertAllEqual(tsb.writer.steps_seen, [0, 0.5, 1, 1.5, 2, 2.5])
+ @test_util.run_deprecated_v1
def test_Tensorboard_histogram_summaries_with_generator(self):
np.random.seed(1337)
tmpdir = self.get_temp_dir()
@@ -1129,6 +1135,7 @@ class KerasCallbacksTest(test.TestCase):
assert os.path.exists(temp_dir)
+ @test_util.run_deprecated_v1
def test_Tensorboard_batch_logging(self):
class FileWriterStub(object):
@@ -1163,6 +1170,7 @@ class KerasCallbacksTest(test.TestCase):
self.assertEqual(tb_cbk.writer.summary_values, [0., 1., 2., 3., 4.])
self.assertEqual(tb_cbk.writer.summary_tags, ['batch_acc'] * 5)
+ @test_util.run_deprecated_v1
def test_Tensorboard_epoch_and_batch_logging(self):
class FileWriterStub(object):
@@ -1234,6 +1242,7 @@ class KerasCallbacksTest(test.TestCase):
self.assertTrue(os.path.exists(temp_dir))
+ @test_util.run_deprecated_v1
def test_TensorBoard_update_freq(self):
class FileWriterStub(object):
@@ -1325,6 +1334,7 @@ class KerasCallbacksTest(test.TestCase):
callbacks=cbks,
epochs=1)
+ @test_util.run_deprecated_v1
def test_fit_generator_with_callback(self):
class TestCallback(keras.callbacks.Callback):
diff --git a/tensorflow/python/keras/engine/saving_test.py b/tensorflow/python/keras/engine/saving_test.py
index b92f06449e9..6d9d9a2fcae 100644
--- a/tensorflow/python/keras/engine/saving_test.py
+++ b/tensorflow/python/keras/engine/saving_test.py
@@ -289,6 +289,7 @@ class TestWeightSavingAndLoading(test.TestCase, parameterized.TestCase):
r'element\(s\)\.'):
saving.load_weights_from_hdf5_group_by_name(f_model, model.layers)
+ @test_util.run_deprecated_v1
def test_sequential_weight_loading_group_name_with_incorrect_shape(self):
if h5py is None:
return
@@ -331,6 +332,7 @@ class TestWeightSavingAndLoading(test.TestCase, parameterized.TestCase):
class TestWholeModelSaving(test.TestCase):
+ @test_util.run_deprecated_v1
def test_sequential_model_saving(self):
if h5py is None:
self.skipTest('h5py required to run this test')
@@ -383,6 +385,7 @@ class TestWholeModelSaving(test.TestCase):
out2 = new_model.predict(x)
self.assertAllClose(out, out2, atol=1e-05)
+ @test_util.run_deprecated_v1
def test_sequential_model_saving_without_input_shape(self):
if h5py is None:
self.skipTest('h5py required to run this test')
@@ -443,6 +446,7 @@ class TestWholeModelSaving(test.TestCase):
out2 = new_model.predict(x)
self.assertAllClose(out, out2, atol=1e-05)
+ @test_util.run_deprecated_v1
def test_sequential_model_saving_2(self):
if h5py is None:
self.skipTest('h5py required to run this test')
@@ -479,6 +483,7 @@ class TestWholeModelSaving(test.TestCase):
out2 = model.predict(x)
self.assertAllClose(out, out2, atol=1e-05)
+ @test_util.run_deprecated_v1
def test_functional_model_saving(self):
if h5py is None:
self.skipTest('h5py required to run this test')
@@ -630,6 +635,7 @@ class TestWholeModelSaving(test.TestCase):
os.close(fd)
os.remove(fname)
+ @test_util.run_deprecated_v1
def test_saving_model_with_long_weights_names(self):
if h5py is None:
self.skipTest('h5py required to run this test')
@@ -675,6 +681,7 @@ class TestWholeModelSaving(test.TestCase):
os.close(fd)
os.remove(fname)
+ @test_util.run_deprecated_v1
def test_model_saving_to_pre_created_h5py_file(self):
if h5py is None:
self.skipTest('h5py required to run this test')
@@ -749,6 +756,7 @@ class SubclassedModel(training.Model):
class TestWeightSavingAndLoadingTFFormat(test.TestCase):
+ @test_util.run_deprecated_v1
def test_keras_optimizer_warning(self):
graph = ops.Graph()
with graph.as_default(), self.session(graph):
diff --git a/tensorflow/python/keras/engine/sequential_test.py b/tensorflow/python/keras/engine/sequential_test.py
index 2e2927bf472..fbf893c6633 100644
--- a/tensorflow/python/keras/engine/sequential_test.py
+++ b/tensorflow/python/keras/engine/sequential_test.py
@@ -132,6 +132,7 @@ class TestSequential(test.TestCase, parameterized.TestCase):
self.assertFalse(model._is_graph_network)
@parameterized.parameters((True,), (False,))
+ @tf_test_util.run_deprecated_v1
def test_training_and_eval_methods_on_symbolic_tensors(self, deferred):
with self.cached_session():
@@ -219,6 +220,7 @@ class TestSequential(test.TestCase, parameterized.TestCase):
inner_model.trainable = True
self.assertEqual(len(model.trainable_weights), 4)
+ @tf_test_util.run_deprecated_v1
def test_sequential_update_disabling(self):
val_a = np.random.random((10, 4))
val_out = np.random.random((10, 4))
diff --git a/tensorflow/python/keras/engine/topology_test.py b/tensorflow/python/keras/engine/topology_test.py
index b4a4babf259..03bfd35589c 100644
--- a/tensorflow/python/keras/engine/topology_test.py
+++ b/tensorflow/python/keras/engine/topology_test.py
@@ -42,6 +42,7 @@ except ImportError:
class TopologyConstructionTest(test.TestCase):
+ @test_util.run_deprecated_v1
def test_get_updates(self):
class MyLayer(keras.layers.Layer):
@@ -115,6 +116,7 @@ class TopologyConstructionTest(test.TestCase):
self.assertEqual(len(layer.get_updates_for(x1)), 2)
self.assertEqual(len(layer.get_updates_for(None)), 0)
+ @test_util.run_deprecated_v1
def test_get_losses(self):
class MyLayer(keras.layers.Layer):
@@ -268,6 +270,7 @@ class TopologyConstructionTest(test.TestCase):
self.assertEqual(test_layer.input_shape, [(None, 32), (None, 32)])
self.assertEqual(test_layer.output_shape, (None, 32))
+ @test_util.run_deprecated_v1
def testBasicNetwork(self):
# minimum viable network
x = input_layer_lib.Input(shape=(32,))
@@ -341,6 +344,7 @@ class TopologyConstructionTest(test.TestCase):
self.assertListEqual(model.trainable_weights, [])
self.assertListEqual(model.non_trainable_weights, weights)
+ @test_util.run_deprecated_v1
def test_layer_call_arguments(self):
# Test the ability to pass and serialize arguments to `call`.
inp = keras.layers.Input(shape=(2,))
@@ -491,6 +495,7 @@ class TopologyConstructionTest(test.TestCase):
fn_outputs = fn([input_a_np, input_b_np])
self.assertListEqual([x.shape for x in fn_outputs], [(10, 64), (10, 5)])
+ @test_util.run_deprecated_v1
def test_recursion(self):
with self.cached_session():
a = keras.layers.Input(shape=(32,), name='input_a')
@@ -675,6 +680,7 @@ class TopologyConstructionTest(test.TestCase):
with self.assertRaises(Exception):
keras.models.Model([j, k], [m, n, 0])
+ @test_util.run_deprecated_v1
def test_raw_tf_compatibility(self):
# test calling layers/models on TF tensors
a = keras.layers.Input(shape=(32,), name='input_a')
@@ -719,6 +725,7 @@ class TopologyConstructionTest(test.TestCase):
model = keras.models.Model(a, b)
self.assertEqual(model.output_mask.get_shape().as_list(), [None, 10])
+ @test_util.run_deprecated_v1
def testMaskingSingleInput(self):
class MaskedLayer(keras.layers.Layer):
@@ -756,6 +763,7 @@ class TopologyConstructionTest(test.TestCase):
y_2 = network(x_2)
self.assertEqual(y_2.get_shape().as_list(), [None, 32])
+ @test_util.run_deprecated_v1
def test_activity_regularization_with_model_composition(self):
def reg(x):
@@ -825,6 +833,7 @@ class TopologyConstructionTest(test.TestCase):
output_val_2 = m2.predict(x_val)
self.assertAllClose(output_val, output_val_2, atol=1e-6)
+ @test_util.run_deprecated_v1
def test_explicit_training_argument(self):
with self.cached_session():
a = keras.layers.Input(shape=(2,))
@@ -1145,6 +1154,7 @@ class DefaultShapeInferenceBehaviorTest(test.TestCase):
class GraphUtilsTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testGetReachableFromInputs(self):
with self.cached_session():
diff --git a/tensorflow/python/keras/engine/training_dataset_test.py b/tensorflow/python/keras/engine/training_dataset_test.py
index e79e5842a1c..8020326377e 100644
--- a/tensorflow/python/keras/engine/training_dataset_test.py
+++ b/tensorflow/python/keras/engine/training_dataset_test.py
@@ -274,6 +274,7 @@ class TestTrainingWithDataset(test.TestCase, parameterized.TestCase):
model.fit(dataset, epochs=1, steps_per_epoch=2, verbose=1)
+ @tf_test_util.run_deprecated_v1
def test_dataset_input_shape_validation(self):
with self.cached_session():
model = testing_utils.get_small_functional_mlp(1, 4, input_dim=3)
diff --git a/tensorflow/python/keras/engine/training_test.py b/tensorflow/python/keras/engine/training_test.py
index 97dfe6d9003..4674bce2449 100644
--- a/tensorflow/python/keras/engine/training_test.py
+++ b/tensorflow/python/keras/engine/training_test.py
@@ -449,6 +449,7 @@ class TrainingTest(test.TestCase):
optimizer=keras.optimizers.Adam(lr=0.0001),
metrics=['accuracy'])
+ @tf_test_util.run_deprecated_v1
def test_that_trainable_disables_updates(self):
val_a = np.random.random((10, 4))
val_out = np.random.random((10, 4))
@@ -1146,6 +1147,7 @@ class LossMaskingTest(test.TestCase):
class TestDynamicTrainability(test.TestCase):
+ @tf_test_util.run_deprecated_v1
def test_trainable_warning(self):
with self.cached_session():
x = np.random.random((5, 3))
@@ -1159,6 +1161,7 @@ class TestDynamicTrainability(test.TestCase):
model.train_on_batch(x, y)
self.assertRaises(Warning)
+ @tf_test_util.run_deprecated_v1
def test_trainable_argument(self):
with self.cached_session():
x = np.random.random((5, 3))
@@ -1289,6 +1292,7 @@ class TestDynamicTrainability(test.TestCase):
class TestTrainingWithDataTensors(test.TestCase):
+ @tf_test_util.run_deprecated_v1
def test_training_and_eval_methods_on_symbolic_tensors_single_io(self):
with self.cached_session():
x = keras.layers.Input(shape=(3,), name='input')
@@ -1329,6 +1333,7 @@ class TestTrainingWithDataTensors(test.TestCase):
epochs=1, steps_per_epoch=2, verbose=0,
validation_data=(inputs, targets), validation_steps=2)
+ @tf_test_util.run_deprecated_v1
def test_training_and_eval_methods_on_symbolic_tensors_multi_io(self):
with self.cached_session():
a = keras.layers.Input(shape=(3,), name='input_a')
@@ -1424,6 +1429,7 @@ class TestTrainingWithDataTensors(test.TestCase):
model.predict([input_a_tf, input_b_tf], steps=2)
model.test_on_batch([input_a_tf, input_b_tf], [output_d_tf, output_e_tf])
+ @tf_test_util.run_deprecated_v1
def test_model_with_input_feed_tensor(self):
"""We test building a model with a TF variable as input.
@@ -1602,6 +1608,7 @@ class TestTrainingWithDataTensors(test.TestCase):
# evaluate
_ = model.evaluate(input_a_np, [output_a_np])
+ @tf_test_util.run_deprecated_v1
def test_model_with_external_loss(self):
with self.cached_session():
# None loss, only regularization loss.
@@ -1797,6 +1804,7 @@ class TestTrainingWithDataTensors(test.TestCase):
model.train_on_batch(input_val, None,
sample_weight={'dense_a': np.random.random((10,))})
+ @tf_test_util.run_deprecated_v1
def test_model_custom_target_tensors(self):
with self.cached_session():
a = keras.Input(shape=(3,), name='input_a')
@@ -2018,6 +2026,7 @@ class TestTrainingWithMetrics(test.TestCase):
scores = model.train_on_batch(x, y, sample_weight=w)
self.assertArrayNear(scores, [0.3328, 0.8], 0.001)
+ @tf_test_util.run_deprecated_v1
def test_add_metric_with_tensor_on_model_in_graph_mode(self):
with self.cached_session():
x = keras.layers.Input(shape=(1,))
@@ -2180,6 +2189,7 @@ class TestTrainingWithMetrics(test.TestCase):
self.assertEqual(history.history['metric_1'][-1], 5)
self.assertAlmostEqual(history.history['val_metric_1'][-1], 5, 0)
+ @tf_test_util.run_deprecated_v1
def test_model_metrics_list(self):
with self.cached_session():
x = keras.layers.Input(shape=(1,))
diff --git a/tensorflow/python/keras/initializers_test.py b/tensorflow/python/keras/initializers_test.py
index 2b758a98f30..4f91bea1e33 100644
--- a/tensorflow/python/keras/initializers_test.py
+++ b/tensorflow/python/keras/initializers_test.py
@@ -22,6 +22,7 @@ import numpy as np
from tensorflow.python import keras
from tensorflow.python.ops import init_ops
+from tensorflow.python.framework import test_util
from tensorflow.python.platform import test
@@ -38,6 +39,7 @@ class KerasInitializersTest(test.TestCase):
output_2 = keras.backend.get_value(variable)
self.assertAllClose(output, output_2, atol=1e-4)
+ @test_util.run_deprecated_v1
def test_uniform(self):
tensor_shape = (9, 6, 7)
with self.cached_session():
@@ -47,6 +49,7 @@ class KerasInitializersTest(test.TestCase):
tensor_shape,
target_mean=0., target_max=1, target_min=-1)
+ @test_util.run_deprecated_v1
def test_normal(self):
tensor_shape = (8, 12, 99)
with self.cached_session():
@@ -54,6 +57,7 @@ class KerasInitializersTest(test.TestCase):
tensor_shape,
target_mean=0., target_std=1)
+ @test_util.run_deprecated_v1
def test_truncated_normal(self):
tensor_shape = (12, 99, 7)
with self.cached_session():
@@ -69,6 +73,7 @@ class KerasInitializersTest(test.TestCase):
self._runner(keras.initializers.Constant(2), tensor_shape,
target_mean=2, target_max=2, target_min=2)
+ @test_util.run_deprecated_v1
def test_lecun_uniform(self):
tensor_shape = (5, 6, 4, 2)
with self.cached_session():
@@ -77,6 +82,7 @@ class KerasInitializersTest(test.TestCase):
self._runner(keras.initializers.lecun_uniform(seed=123), tensor_shape,
target_mean=0., target_std=std)
+ @test_util.run_deprecated_v1
def test_glorot_uniform(self):
tensor_shape = (5, 6, 4, 2)
with self.cached_session():
@@ -85,6 +91,7 @@ class KerasInitializersTest(test.TestCase):
self._runner(keras.initializers.glorot_uniform(seed=123), tensor_shape,
target_mean=0., target_std=std)
+ @test_util.run_deprecated_v1
def test_he_uniform(self):
tensor_shape = (5, 6, 4, 2)
with self.cached_session():
@@ -93,6 +100,7 @@ class KerasInitializersTest(test.TestCase):
self._runner(keras.initializers.he_uniform(seed=123), tensor_shape,
target_mean=0., target_std=std)
+ @test_util.run_deprecated_v1
def test_lecun_normal(self):
tensor_shape = (5, 6, 4, 2)
with self.cached_session():
@@ -101,6 +109,7 @@ class KerasInitializersTest(test.TestCase):
self._runner(keras.initializers.lecun_normal(seed=123), tensor_shape,
target_mean=0., target_std=std)
+ @test_util.run_deprecated_v1
def test_glorot_normal(self):
tensor_shape = (5, 6, 4, 2)
with self.cached_session():
@@ -109,6 +118,7 @@ class KerasInitializersTest(test.TestCase):
self._runner(keras.initializers.glorot_normal(seed=123), tensor_shape,
target_mean=0., target_std=std)
+ @test_util.run_deprecated_v1
def test_he_normal(self):
tensor_shape = (5, 6, 4, 2)
with self.cached_session():
@@ -117,6 +127,7 @@ class KerasInitializersTest(test.TestCase):
self._runner(keras.initializers.he_normal(seed=123), tensor_shape,
target_mean=0., target_std=std)
+ @test_util.run_deprecated_v1
def test_orthogonal(self):
tensor_shape = (20, 20)
with self.cached_session():
diff --git a/tensorflow/python/keras/integration_test.py b/tensorflow/python/keras/integration_test.py
index 3c0f73b1c3a..f1a0932613b 100644
--- a/tensorflow/python/keras/integration_test.py
+++ b/tensorflow/python/keras/integration_test.py
@@ -22,6 +22,7 @@ import numpy as np
from tensorflow.python import keras
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.keras import testing_utils
from tensorflow.python.layers import core as tf_core_layers
from tensorflow.python.ops import nn
@@ -34,6 +35,7 @@ class KerasIntegrationTest(test.TestCase):
def test_version(self):
self.assertTrue(keras.__version__.endswith('-tf'))
+ @test_util.run_deprecated_v1
def test_vector_classification_sequential(self):
with self.cached_session():
np.random.seed(1337)
@@ -59,6 +61,7 @@ class KerasIntegrationTest(test.TestCase):
verbose=2)
self.assertGreater(history.history['val_acc'][-1], 0.7)
+ @test_util.run_deprecated_v1
def test_vector_classification_functional(self):
with self.cached_session():
np.random.seed(1337)
@@ -83,6 +86,7 @@ class KerasIntegrationTest(test.TestCase):
verbose=2)
self.assertGreater(history.history['val_acc'][-1], 0.7)
+ @test_util.run_deprecated_v1
def test_temporal_classification_sequential(self):
with self.cached_session():
np.random.seed(1337)
@@ -105,6 +109,7 @@ class KerasIntegrationTest(test.TestCase):
verbose=2)
self.assertGreater(history.history['val_acc'][-1], 0.7)
+ @test_util.run_deprecated_v1
def test_temporal_classification_sequential_tf_rnn(self):
with self.cached_session():
np.random.seed(1337)
@@ -163,6 +168,7 @@ class KerasIntegrationTest(test.TestCase):
verbose=2)
self.assertGreater(history.history['val_acc'][-1], 0.7)
+ @test_util.run_deprecated_v1
def test_video_classification_functional(self):
with self.cached_session():
np.random.seed(1337)
@@ -191,6 +197,7 @@ class KerasIntegrationTest(test.TestCase):
verbose=2)
self.assertGreater(history.history['val_acc'][-1], 0.7)
+ @test_util.run_deprecated_v1
def test_vector_classification_shared_sequential(self):
# Test that Sequential models that feature internal updates
# and internal losses can be shared.
@@ -225,6 +232,7 @@ class KerasIntegrationTest(test.TestCase):
verbose=2)
self.assertGreater(history.history['val_acc'][-1], 0.7)
+ @test_util.run_deprecated_v1
def test_vector_classification_shared_model(self):
# Test that functional models that feature internal updates
# and internal losses can be shared.
diff --git a/tensorflow/python/keras/layers/local_test.py b/tensorflow/python/keras/layers/local_test.py
index 1c20d437064..a23c5c38fe9 100644
--- a/tensorflow/python/keras/layers/local_test.py
+++ b/tensorflow/python/keras/layers/local_test.py
@@ -32,6 +32,7 @@ class LocallyConnected1DLayersTest(test.TestCase):
# fails inside a graph function in an eager context (fails with error
# "Incompatible shapes between op input and calculated input gradient").
+ @tf_test_util.run_deprecated_v1
def test_locallyconnected_1d(self):
with self.cached_session():
num_samples = 2
@@ -120,6 +121,7 @@ class LocallyConnected2DLayersTest(test.TestCase):
# fails inside a graph function in an eager context (fails with error
# "Incompatible shapes between op input and calculated input gradient").
+ @tf_test_util.run_deprecated_v1
def test_locallyconnected_2d(self):
with self.cached_session():
num_samples = 8
@@ -155,6 +157,7 @@ class LocallyConnected2DLayersTest(test.TestCase):
kwargs=kwargs,
input_shape=(num_samples, num_row, num_col, stack_size))
+ @tf_test_util.run_deprecated_v1
def test_locallyconnected_2d_channels_first(self):
with self.cached_session():
num_samples = 8
@@ -232,6 +235,7 @@ class LocallyConnected2DLayersTest(test.TestCase):
class LocallyConnectedImplementationModeTest(test.TestCase):
+ @tf_test_util.run_deprecated_v1
def test_locallyconnected_implementation(self):
with self.cached_session():
num_samples = 4
diff --git a/tensorflow/python/keras/layers/lstm_test.py b/tensorflow/python/keras/layers/lstm_test.py
index 9db697871fe..732bbcfa18e 100644
--- a/tensorflow/python/keras/layers/lstm_test.py
+++ b/tensorflow/python/keras/layers/lstm_test.py
@@ -114,6 +114,7 @@ class LSTMLayerTest(test.TestCase):
self.assertEqual(layer.cell.recurrent_kernel.constraint, r_constraint)
self.assertEqual(layer.cell.bias.constraint, b_constraint)
+ @tf_test_util.run_deprecated_v1
def test_with_masking_layer_LSTM(self):
layer_class = keras.layers.LSTM
inputs = np.random.random((2, 3, 4))
@@ -126,6 +127,7 @@ class LSTMLayerTest(test.TestCase):
optimizer=RMSPropOptimizer(0.01))
model.fit(inputs, targets, epochs=1, batch_size=2, verbose=1)
+ @tf_test_util.run_deprecated_v1
def test_masking_with_stacking_LSTM(self):
inputs = np.random.random((2, 3, 4))
targets = np.abs(np.random.random((2, 3, 5)))
@@ -311,6 +313,7 @@ class LSTMLayerTest(test.TestCase):
class LSTMLayerGraphOnlyTest(test.TestCase):
+ @tf_test_util.run_deprecated_v1
def test_statefulness_LSTM(self):
num_samples = 2
timesteps = 3
@@ -374,6 +377,7 @@ class LSTMLayerGraphOnlyTest(test.TestCase):
self.assertAllClose(out7, out6, atol=1e-5)
+ @tf_test_util.run_deprecated_v1
def test_regularizers_LSTM(self):
embedding_dim = 4
layer_class = keras.layers.LSTM
diff --git a/tensorflow/python/keras/layers/merge_test.py b/tensorflow/python/keras/layers/merge_test.py
index 698c5662b6f..fcb161ae20a 100644
--- a/tensorflow/python/keras/layers/merge_test.py
+++ b/tensorflow/python/keras/layers/merge_test.py
@@ -207,6 +207,7 @@ class MergeLayersGraphOnlyTest(test.TestCase):
mask = layer.output_mask
self.assertListEqual(mask.get_shape().as_list(), [None, 4])
+ @tf_test_util.run_deprecated_v1
def test_merge_add_dynamic_shape(self):
with self.cached_session():
i1 = array_ops.placeholder(shape=(4, None), dtype='float32')
diff --git a/tensorflow/python/keras/layers/normalization_test.py b/tensorflow/python/keras/layers/normalization_test.py
index 2f7f042b7f7..9138c0a08a3 100644
--- a/tensorflow/python/keras/layers/normalization_test.py
+++ b/tensorflow/python/keras/layers/normalization_test.py
@@ -301,6 +301,7 @@ class NormalizationLayersGraphModeOnlyTest(test.TestCase):
x2 = model.predict(val_a)
self.assertAllClose(x1, x2, atol=1e-7)
+ @tf_test_util.run_deprecated_v1
def test_batchnorm_trainable(self):
"""Tests that batchnorm layer is trainable when learning phase is enabled.
diff --git a/tensorflow/python/keras/layers/simplernn_test.py b/tensorflow/python/keras/layers/simplernn_test.py
index 93456b5e3a7..b49b159b719 100644
--- a/tensorflow/python/keras/layers/simplernn_test.py
+++ b/tensorflow/python/keras/layers/simplernn_test.py
@@ -98,6 +98,7 @@ class SimpleRNNLayerTest(test.TestCase):
self.assertEqual(layer.cell.recurrent_kernel.constraint, r_constraint)
self.assertEqual(layer.cell.bias.constraint, b_constraint)
+ @tf_test_util.run_deprecated_v1
def test_with_masking_layer_SimpleRNN(self):
layer_class = keras.layers.SimpleRNN
inputs = np.random.random((2, 3, 4))
@@ -120,6 +121,7 @@ class SimpleRNNLayerTest(test.TestCase):
class SimpleRNNLayerGraphOnlyTest(test.TestCase):
+ @tf_test_util.run_deprecated_v1
def test_statefulness_SimpleRNN(self):
num_samples = 2
timesteps = 3
@@ -183,6 +185,7 @@ class SimpleRNNLayerGraphOnlyTest(test.TestCase):
np.testing.assert_allclose(out7, out6, atol=1e-5)
+ @tf_test_util.run_deprecated_v1
def test_regularizers_SimpleRNN(self):
embedding_dim = 4
layer_class = keras.layers.SimpleRNN
diff --git a/tensorflow/python/keras/layers/unified_rnn_test.py b/tensorflow/python/keras/layers/unified_rnn_test.py
index b08ff3cafc2..e26e47000d8 100644
--- a/tensorflow/python/keras/layers/unified_rnn_test.py
+++ b/tensorflow/python/keras/layers/unified_rnn_test.py
@@ -69,6 +69,7 @@ class RNNTest(test.TestCase):
def tearDown(self):
ops.reset_default_graph()
+ @test_util.run_deprecated_v1
def test_unifiedRNN(self):
input_shape = 10
rnn_state_size = 8
@@ -113,6 +114,7 @@ class RNNTest(test.TestCase):
self.assertNotEqual(existing_loss, loss_value)
existing_loss = loss_value
+ @test_util.run_deprecated_v1
def test_unifiedRNN_with_cond(self):
# This test is to demonstrate the graph rewrite of grappler plugin under
# the condition that the function returns different number of internal
diff --git a/tensorflow/python/keras/layers/wrappers_test.py b/tensorflow/python/keras/layers/wrappers_test.py
index bbafa96aab8..427314faf17 100644
--- a/tensorflow/python/keras/layers/wrappers_test.py
+++ b/tensorflow/python/keras/layers/wrappers_test.py
@@ -201,6 +201,7 @@ class TimeDistributedTest(test.TestCase):
assert len(layer.updates) == 2
assert len(layer.trainable_weights) == 2
+ @tf_test_util.run_deprecated_v1
def test_TimeDistributed_with_masked_embedding_and_unspecified_shape(self):
with self.cached_session():
# test with unspecified shape and Embeddings with mask_zero
@@ -233,6 +234,7 @@ class TimeDistributedTest(test.TestCase):
self.assertAllEqual(mask_outputs_val[i], ref_mask_val[i])
self.assertIs(mask_outputs[-1], None) # final layer
+ @tf_test_util.run_deprecated_v1
def test_TimeDistributed_with_masking_layer(self):
with self.cached_session():
# test with Masking layer
@@ -375,6 +377,7 @@ class BidirectionalTest(test.TestCase):
model.compile(loss='mse', optimizer='sgd')
model.fit(x, y, epochs=1, batch_size=1)
+ @tf_test_util.run_deprecated_v1
def test_Bidirectional_merged_value(self):
rnn = keras.layers.LSTM
samples = 2
@@ -505,6 +508,7 @@ class BidirectionalTest(test.TestCase):
layer.trainable = True
assert len(layer.trainable_weights) == 6
+ @tf_test_util.run_deprecated_v1
def test_Bidirectional_updates(self):
with self.cached_session():
x = keras.layers.Input(shape=(3, 2))
diff --git a/tensorflow/python/keras/model_subclassing_test.py b/tensorflow/python/keras/model_subclassing_test.py
index ccfff57a3bd..ca7dded60d4 100644
--- a/tensorflow/python/keras/model_subclassing_test.py
+++ b/tensorflow/python/keras/model_subclassing_test.py
@@ -917,6 +917,7 @@ class ModelSubclassingTest(test.TestCase):
class GraphSpecificModelSubclassingTests(test.TestCase):
+ @test_util.run_deprecated_v1
def test_single_io_workflow_with_tensors(self):
num_classes = 2
num_samples = 10
@@ -934,6 +935,7 @@ class GraphSpecificModelSubclassingTests(test.TestCase):
model.fit(x, y, epochs=2, steps_per_epoch=10, verbose=0)
_ = model.evaluate(steps=10, verbose=0)
+ @test_util.run_deprecated_v1
def test_multi_io_workflow_with_tensors(self):
num_classes = (2, 3)
num_samples = 10
@@ -953,6 +955,7 @@ class GraphSpecificModelSubclassingTests(test.TestCase):
model.fit([x1, x2], [y1, y2], epochs=2, steps_per_epoch=10, verbose=0)
_ = model.evaluate(steps=10, verbose=0)
+ @test_util.run_deprecated_v1
def test_updates_and_losses_for_nested_models_in_subclassed_model(self):
# Case 1: deferred-build sequential nested in subclass.
@@ -1020,6 +1023,7 @@ class GraphSpecificModelSubclassingTests(test.TestCase):
self.assertEqual(len(model.get_updates_for(x)), 2)
self.assertEqual(len(model.get_losses_for(x)), 1)
+ @test_util.run_deprecated_v1
def test_multi_io_workflow_with_numpy_arrays_and_custom_placeholders(self):
num_classes = (2, 3)
num_samples = 1000
diff --git a/tensorflow/python/keras/models_test.py b/tensorflow/python/keras/models_test.py
index c68c80f0cc5..8af3cc05f5d 100644
--- a/tensorflow/python/keras/models_test.py
+++ b/tensorflow/python/keras/models_test.py
@@ -69,6 +69,7 @@ def sequential_model(add_input_layer, include_input_shape=True):
class TestModelCloning(test.TestCase):
+ @test_util.run_deprecated_v1
def test_clone_sequential_model(self):
with self.cached_session():
val_a = np.random.random((10, 4))
@@ -101,7 +102,10 @@ class TestModelCloning(test.TestCase):
new_model.compile('rmsprop', 'mse')
new_model.train_on_batch(None, val_out)
+ @test_util.run_deprecated_v1
def test_clone_sequential_model_input_layer(self):
+
+ @test_util.run_deprecated_v1
def test_input_layer(include_inputs):
with self.cached_session():
val_a = np.random.random((10, 4))
@@ -138,6 +142,7 @@ class TestModelCloning(test.TestCase):
test_input_layer(True)
test_input_layer(False)
+ @test_util.run_deprecated_v1
def test_clone_functional_model(self):
with self.cached_session():
val_a = np.random.random((10, 4))
@@ -397,6 +402,7 @@ class TestCloneAndBuildModel(test.TestCase):
new_model.train_on_batch(inp, out)
new_model.evaluate(inp, out)
+ @test_util.run_deprecated_v1
def test_clone_and_build_compiled_sequential_model(self):
with self.cached_session():
model = keras.models.Sequential()
@@ -409,6 +415,7 @@ class TestCloneAndBuildModel(test.TestCase):
self._clone_and_build_test_helper(model)
+ @test_util.run_deprecated_v1
def test_clone_and_build_functional_model(self):
with self.cached_session():
input_a = keras.Input(shape=(4,))
@@ -425,6 +432,7 @@ class TestCloneAndBuildModel(test.TestCase):
self._clone_and_build_test_helper(model)
+ @test_util.run_deprecated_v1
def test_clone_and_build_subclassed_model(self):
class SubclassedModel(keras.Model):
@@ -473,9 +481,11 @@ class TestCloneAndBuildModel(test.TestCase):
def test_replace_tf_optimizer_iterations_variable(self):
self.assert_optimizer_iterations_increases(adam.AdamOptimizer(0.01))
+ @test_util.run_deprecated_v1
def test_replace_keras_optimizer_iterations_variable(self):
self.assert_optimizer_iterations_increases('adam')
+ @test_util.run_deprecated_v1
def test_clone_and_build_sequential_model_without_inputs_defined(self):
with self.cached_session():
model = sequential_model(False, False)
diff --git a/tensorflow/python/keras/optimizer_v2/adadelta_test.py b/tensorflow/python/keras/optimizer_v2/adadelta_test.py
index ef95d27abff..6409f3ead44 100644
--- a/tensorflow/python/keras/optimizer_v2/adadelta_test.py
+++ b/tensorflow/python/keras/optimizer_v2/adadelta_test.py
@@ -147,6 +147,7 @@ class AdadeltaOptimizerTest(test.TestCase):
with context.eager_mode():
self.doTestBasic(use_resource=True, use_callable_params=True)
+ @test_util.run_deprecated_v1
def testMinimizeSparseResourceVariable(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
diff --git a/tensorflow/python/keras/optimizer_v2/adagrad_test.py b/tensorflow/python/keras/optimizer_v2/adagrad_test.py
index 5ddeb1ad801..8004907bf52 100644
--- a/tensorflow/python/keras/optimizer_v2/adagrad_test.py
+++ b/tensorflow/python/keras/optimizer_v2/adagrad_test.py
@@ -160,6 +160,7 @@ class AdagradOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(var0_np, self.evaluate(var0))
self.assertAllCloseAccordingToType(var1_np, self.evaluate(var1))
+ @test_util.run_deprecated_v1
def testMinimizeSparseResourceVariable(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -179,6 +180,7 @@ class AdagradOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(
[[0, 1], [3, 4]], var0.eval(), atol=0.01)
+ @test_util.run_deprecated_v1
def testTensorLearningRate(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -211,6 +213,7 @@ class AdagradOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(var0_np, self.evaluate(var0))
self.assertAllCloseAccordingToType(var1_np, self.evaluate(var1))
+ @test_util.run_deprecated_v1
def testSparseBasic(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -255,6 +258,7 @@ class AdagradOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(var0_np, self.evaluate(var0))
self.assertAllCloseAccordingToType(var1_np, self.evaluate(var1))
+ @test_util.run_deprecated_v1
def testSparseRepeatedIndices(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -287,6 +291,7 @@ class AdagradOptimizerTest(test.TestCase):
self.assertAllClose(aggregated_update_var.eval(),
repeated_index_update_var.eval())
+ @test_util.run_deprecated_v1
def testSparseRepeatedIndicesByEmbeddingLookUp(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -311,6 +316,7 @@ class AdagradOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(
var_repeated.eval(), var_aggregated.eval())
+ @test_util.run_deprecated_v1
def testSparseStability(self):
for dtype in [dtypes.half]:
with self.cached_session():
@@ -343,6 +349,7 @@ class AdagradOptimizerTest(test.TestCase):
-0.01029443
]]), var0.eval())
+ @test_util.run_deprecated_v1
def testSharing(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
diff --git a/tensorflow/python/keras/optimizer_v2/adam_test.py b/tensorflow/python/keras/optimizer_v2/adam_test.py
index e2bc6a39f96..b1b17f8f088 100644
--- a/tensorflow/python/keras/optimizer_v2/adam_test.py
+++ b/tensorflow/python/keras/optimizer_v2/adam_test.py
@@ -62,6 +62,7 @@ def get_beta_accumulators(opt, dtype):
class AdamOptimizerTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testSparse(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -106,6 +107,7 @@ class AdamOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(var0_np, self.evaluate(var0))
self.assertAllCloseAccordingToType(var1_np, self.evaluate(var1))
+ @test_util.run_deprecated_v1
def testSparseDevicePlacement(self):
for index_dtype in [dtypes.int32, dtypes.int64]:
with self.cached_session(force_gpu=test.is_gpu_available()):
@@ -119,6 +121,7 @@ class AdamOptimizerTest(test.TestCase):
variables.global_variables_initializer().run()
minimize_op.run()
+ @test_util.run_deprecated_v1
def testSparseRepeatedIndices(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -208,6 +211,7 @@ class AdamOptimizerTest(test.TestCase):
with context.eager_mode():
self.doTestBasic(use_callable_params=True)
+ @test_util.run_deprecated_v1
def testBasicWithLearningRateDecay(self):
for i, dtype in enumerate([dtypes.half, dtypes.float32, dtypes.float64]):
with self.session(graph=ops.Graph()):
@@ -254,6 +258,7 @@ class AdamOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(var0_np, self.evaluate(var0))
self.assertAllCloseAccordingToType(var1_np, self.evaluate(var1))
+ @test_util.run_deprecated_v1
def testTensorLearningRate(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -292,6 +297,7 @@ class AdamOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(var0_np, self.evaluate(var0))
self.assertAllCloseAccordingToType(var1_np, self.evaluate(var1))
+ @test_util.run_deprecated_v1
def testSharing(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
diff --git a/tensorflow/python/keras/optimizer_v2/adamax_test.py b/tensorflow/python/keras/optimizer_v2/adamax_test.py
index aa215b0faf3..7521a6196e4 100644
--- a/tensorflow/python/keras/optimizer_v2/adamax_test.py
+++ b/tensorflow/python/keras/optimizer_v2/adamax_test.py
@@ -124,9 +124,11 @@ class AdamaxOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(var0_np, var0.eval())
self.assertAllCloseAccordingToType(var1_np, var1.eval())
+ @test_util.run_deprecated_v1
def testResourceSparse(self):
self.doTestSparse(use_resource=True)
+ @test_util.run_deprecated_v1
def testSparseDevicePlacement(self):
for index_dtype in [dtypes.int32, dtypes.int64]:
with self.cached_session(force_gpu=test.is_gpu_available()):
@@ -140,6 +142,7 @@ class AdamaxOptimizerTest(test.TestCase):
variables.global_variables_initializer().run()
minimize_op.run()
+ @test_util.run_deprecated_v1
def testSparseRepeatedIndices(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -272,6 +275,7 @@ class AdamaxOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(var1_np, self.evaluate(var1),
rtol=1e-2)
+ @test_util.run_deprecated_v1
def testTensorLearningRate(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -308,6 +312,7 @@ class AdamaxOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(var0_np, var0.eval())
self.assertAllCloseAccordingToType(var1_np, var1.eval())
+ @test_util.run_deprecated_v1
def testSharing(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
diff --git a/tensorflow/python/keras/optimizer_v2/ftrl_test.py b/tensorflow/python/keras/optimizer_v2/ftrl_test.py
index ca8c33dfa6d..bec400e8cbb 100644
--- a/tensorflow/python/keras/optimizer_v2/ftrl_test.py
+++ b/tensorflow/python/keras/optimizer_v2/ftrl_test.py
@@ -23,6 +23,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.keras.optimizer_v2 import ftrl
from tensorflow.python.ops import embedding_ops
from tensorflow.python.ops import math_ops
@@ -68,12 +69,15 @@ class FtrlOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(
np.array([-0.28432083, -0.56694895]), v1_val)
+ @test_util.run_deprecated_v1
def testFtrlWithoutRegularization(self):
self.doTestFtrlwithoutRegularization(use_resource=False)
+ @test_util.run_deprecated_v1
def testResourceFtrlWithoutRegularization(self):
self.doTestFtrlwithoutRegularization(use_resource=True)
+ @test_util.run_deprecated_v1
def testFtrlwithoutRegularization2(self):
for dtype in [dtypes.half, dtypes.float32]:
with self.cached_session() as sess:
@@ -103,6 +107,7 @@ class FtrlOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(
np.array([-0.28232238, -0.56096673]), v1_val)
+ @test_util.run_deprecated_v1
def testMinimizeSparseResourceVariable(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -121,6 +126,7 @@ class FtrlOptimizerTest(test.TestCase):
self.evaluate(var0),
atol=0.01)
+ @test_util.run_deprecated_v1
def testFtrlWithL1(self):
for dtype in [dtypes.half, dtypes.float32]:
with self.cached_session() as sess:
@@ -150,6 +156,7 @@ class FtrlOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(
np.array([-0.93460727, -1.86147261]), v1_val)
+ @test_util.run_deprecated_v1
def testFtrlWithL1_L2(self):
for dtype in [dtypes.half, dtypes.float32]:
with self.cached_session() as sess:
@@ -180,6 +187,7 @@ class FtrlOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(
np.array([-0.02406147, -0.04830509]), v1_val)
+ @test_util.run_deprecated_v1
def testFtrlWithL1_L2_L2Shrinkage(self):
"""Test the new FTRL op with support for l2 shrinkage.
@@ -217,6 +225,7 @@ class FtrlOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(
np.array([-0.14378493, -0.13229476]), v1_val)
+ @test_util.run_deprecated_v1
def testFtrlWithL1_L2_L2ShrinkageSparse(self):
"""Tests the new FTRL op with support for l2 shrinkage on sparse grads."""
for dtype in [dtypes.half, dtypes.float32]:
@@ -251,6 +260,7 @@ class FtrlOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType([[-0.22578995], [2.]], v0_val)
self.assertAllCloseAccordingToType([[4.], [-0.13229476]], v1_val)
+ @test_util.run_deprecated_v1
def testFtrlWithL2ShrinkageDoesNotChangeLrSchedule(self):
"""Verifies that l2 shrinkage in FTRL does not change lr schedule."""
for dtype in [dtypes.half, dtypes.float32]:
@@ -335,6 +345,7 @@ class FtrlOptimizerTest(test.TestCase):
# with Adagrad.
# So, basing on these two properties, we test if our implementation of
# FTRL-Proximal performs same updates as Adagrad or GradientDescent.
+ @test_util.run_deprecated_v1
def testEquivAdagradwithoutRegularization(self):
for dtype in [dtypes.half, dtypes.float32]:
with self.cached_session():
@@ -355,6 +366,7 @@ class FtrlOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(val0, val2)
self.assertAllCloseAccordingToType(val1, val3)
+ @test_util.run_deprecated_v1
def testEquivSparseAdagradwithoutRegularization(self):
for dtype in [dtypes.half, dtypes.float32]:
with self.cached_session():
@@ -378,6 +390,7 @@ class FtrlOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(val0, val2)
self.assertAllCloseAccordingToType(val1, val3)
+ @test_util.run_deprecated_v1
def testEquivSparseGradientDescentwithoutRegularization(self):
for dtype in [dtypes.half, dtypes.float32]:
with self.cached_session():
@@ -401,6 +414,7 @@ class FtrlOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(val0, val2)
self.assertAllCloseAccordingToType(val1, val3)
+ @test_util.run_deprecated_v1
def testEquivGradientDescentwithoutRegularization(self):
for dtype in [dtypes.half, dtypes.float32]:
with self.cached_session():
diff --git a/tensorflow/python/keras/optimizer_v2/gradient_descent_test.py b/tensorflow/python/keras/optimizer_v2/gradient_descent_test.py
index 348d2728c89..dae2a47735e 100644
--- a/tensorflow/python/keras/optimizer_v2/gradient_descent_test.py
+++ b/tensorflow/python/keras/optimizer_v2/gradient_descent_test.py
@@ -134,6 +134,7 @@ class GradientDescentOptimizerTest(test.TestCase):
self.evaluate(var0))
self.assertAllCloseAccordingToType([3.0 - 1.0], self.evaluate(var1))
+ @test_util.run_deprecated_v1
def testMinimizeSparseResourceVariable(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -173,6 +174,7 @@ class GradientDescentOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType([3.0 - 3.0 * 0.01, 4.0 - 3.0 * 0.01],
self.evaluate(var1))
+ @test_util.run_deprecated_v1
def testGradWrtRef(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -206,6 +208,7 @@ class GradientDescentOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType([[3.0], [4.0 - 3.0 * 0.01]],
self.evaluate(var1))
+ @test_util.run_deprecated_v1
def testSparseBasicWithLearningRateDecay(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -331,6 +334,7 @@ class MomentumOptimizerTest(test.TestCase):
3.98 - ((0.9 * 0.01 + 0.01) * 2.0)
]), self.evaluate(var1))
+ @test_util.run_deprecated_v1
def testNesterovMomentum(self):
for dtype in [dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -358,6 +362,7 @@ class MomentumOptimizerTest(test.TestCase):
self.assertAllClose(var0_np, self.evaluate(var0))
self.assertAllClose(var1_np, self.evaluate(var1))
+ @test_util.run_deprecated_v1
def testSparseNesterovMomentum(self):
for dtype in [dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -399,6 +404,7 @@ class MomentumOptimizerTest(test.TestCase):
self.assertAllClose(var1_np, self.evaluate(var1))
@test_util.run_in_graph_and_eager_modes
+ @test_util.run_deprecated_v1
def testMinimizeSparseResourceVariable(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
# This test invokes the ResourceSparseApplyMomentum operation, which
@@ -452,6 +458,7 @@ class MomentumOptimizerTest(test.TestCase):
self.evaluate(sgd_op)
self.assertAllCloseAccordingToType([[1, 1], [0, 0]], self.evaluate(var0))
+ @test_util.run_deprecated_v1
def testTensorLearningRateAndMomentum(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -510,6 +517,7 @@ class MomentumOptimizerTest(test.TestCase):
3.98 - ((0.9 * 0.01 + 0.01) * 2.0)
]), self.evaluate(var1))
+ @test_util.run_deprecated_v1
def testSparse(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -585,6 +593,7 @@ class MomentumOptimizerTest(test.TestCase):
]),
self.evaluate(var1)[2])
+ @test_util.run_deprecated_v1
def testSharing(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
diff --git a/tensorflow/python/keras/optimizer_v2/nadam_test.py b/tensorflow/python/keras/optimizer_v2/nadam_test.py
index b7132bbea74..d991e3117ca 100644
--- a/tensorflow/python/keras/optimizer_v2/nadam_test.py
+++ b/tensorflow/python/keras/optimizer_v2/nadam_test.py
@@ -23,6 +23,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.keras.optimizer_v2 import nadam
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import resource_variable_ops
@@ -111,9 +112,11 @@ class NadamOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(var0_np, var0.eval())
self.assertAllCloseAccordingToType(var1_np, var1.eval())
+ @test_util.run_deprecated_v1
def testSparse(self):
self.doTestSparse(use_resource=False)
+ @test_util.run_deprecated_v1
def testResourceSparse(self):
self.doTestSparse(use_resource=True)
@@ -158,9 +161,11 @@ class NadamOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(var0_np, var0.eval())
self.assertAllCloseAccordingToType(var1_np, var1.eval())
+ @test_util.run_deprecated_v1
def testResourceBasic(self):
self.doTestBasic(use_resource=True)
+ @test_util.run_deprecated_v1
def testBasicWithLearningRateDecay(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
diff --git a/tensorflow/python/keras/optimizer_v2/rmsprop_test.py b/tensorflow/python/keras/optimizer_v2/rmsprop_test.py
index a320cc0c490..a8658a85507 100644
--- a/tensorflow/python/keras/optimizer_v2/rmsprop_test.py
+++ b/tensorflow/python/keras/optimizer_v2/rmsprop_test.py
@@ -86,6 +86,7 @@ class RMSpropOptimizerTest(test.TestCase):
var_t[gindex] = var[gindex] - mom_t[gindex]
return var_t, mg_t, rms_t, mom_t
+ @test_util.run_deprecated_v1
def testDense(self):
for (dtype, learning_rate, rho, momentum, epsilon, centered) in _TESTPARAMS:
with test_util.use_gpu():
@@ -158,6 +159,7 @@ class RMSpropOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(var0_np, self.evaluate(var0))
self.assertAllCloseAccordingToType(var1_np, self.evaluate(var1))
+ @test_util.run_deprecated_v1
def testDenseWithLearningRateDecay(self):
var0_np = np.array([1.0, 2.0])
grads0_np = np.array([0.1, 0.2])
@@ -225,6 +227,7 @@ class RMSpropOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(var0_np, self.evaluate(var0))
self.assertAllCloseAccordingToType(var1_np, self.evaluate(var1))
+ @test_util.run_deprecated_v1
def testMinimizeSparseResourceVariable(self):
for dtype in [dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -249,6 +252,7 @@ class RMSpropOptimizerTest(test.TestCase):
self.evaluate(var0),
atol=0.01)
+ @test_util.run_deprecated_v1
def testMinimizeSparseResourceVariableCentered(self):
for dtype in [dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -273,6 +277,7 @@ class RMSpropOptimizerTest(test.TestCase):
self.evaluate(var0),
atol=0.01)
+ @test_util.run_deprecated_v1
def testSparse(self):
for (dtype, learning_rate, rho, momentum, epsilon, centered) in _TESTPARAMS:
with test_util.use_gpu():
diff --git a/tensorflow/python/keras/optimizers_test.py b/tensorflow/python/keras/optimizers_test.py
index 46bb0274c6e..d3cacb702c9 100644
--- a/tensorflow/python/keras/optimizers_test.py
+++ b/tensorflow/python/keras/optimizers_test.py
@@ -91,22 +91,26 @@ def _test_optimizer(optimizer, target=0.75):
class KerasOptimizersTest(test.TestCase):
+ @test_util.run_deprecated_v1
def test_sgd(self):
with self.cached_session():
_test_optimizer(keras.optimizers.SGD(lr=0.01,
momentum=0.9,
nesterov=True))
+ @test_util.run_deprecated_v1
def test_rmsprop(self):
with self.cached_session():
_test_optimizer(keras.optimizers.RMSprop())
_test_optimizer(keras.optimizers.RMSprop(decay=1e-3))
+ @test_util.run_deprecated_v1
def test_adagrad(self):
with self.cached_session():
_test_optimizer(keras.optimizers.Adagrad())
_test_optimizer(keras.optimizers.Adagrad(decay=1e-3))
+ @test_util.run_deprecated_v1
def test_adadelta(self):
with self.cached_session():
_test_optimizer(keras.optimizers.Adadelta(), target=0.6)
@@ -115,27 +119,32 @@ class KerasOptimizersTest(test.TestCase):
# the accuracy.
_test_optimizer(keras.optimizers.Adadelta(decay=1e-3), target=0.4)
+ @test_util.run_deprecated_v1
def test_adam(self):
with self.cached_session():
_test_optimizer(keras.optimizers.Adam())
_test_optimizer(keras.optimizers.Adam(decay=1e-3))
_test_optimizer(keras.optimizers.Adam(amsgrad=True))
+ @test_util.run_deprecated_v1
def test_adamax(self):
with self.cached_session():
_test_optimizer(keras.optimizers.Adamax())
_test_optimizer(keras.optimizers.Adamax(decay=1e-3))
+ @test_util.run_deprecated_v1
def test_nadam(self):
with self.cached_session():
_test_optimizer(keras.optimizers.Nadam())
+ @test_util.run_deprecated_v1
def test_clipnorm(self):
with self.cached_session():
_test_optimizer(keras.optimizers.SGD(lr=0.01,
momentum=0.9,
clipnorm=0.5))
+ @test_util.run_deprecated_v1
def test_clipvalue(self):
with self.cached_session():
_test_optimizer(keras.optimizers.SGD(lr=0.01,
diff --git a/tensorflow/python/keras/regularizers_test.py b/tensorflow/python/keras/regularizers_test.py
index bba4ebb287b..3d6b259d87d 100644
--- a/tensorflow/python/keras/regularizers_test.py
+++ b/tensorflow/python/keras/regularizers_test.py
@@ -20,6 +20,7 @@ from __future__ import print_function
from tensorflow.python import keras
from tensorflow.python.keras import testing_utils
+from tensorflow.python.framework import test_util
from tensorflow.python.platform import test
@@ -61,6 +62,7 @@ class KerasRegularizersTest(test.TestCase):
model.fit(x_train, y_train, batch_size=10,
epochs=1, verbose=0)
+ @test_util.run_deprecated_v1
def test_activity_regularization(self):
with self.cached_session():
(x_train, y_train), _ = get_data()
diff --git a/tensorflow/python/kernel_tests/accumulate_n_test.py b/tensorflow/python/kernel_tests/accumulate_n_test.py
index c7f11f854d1..5eece9c9413 100644
--- a/tensorflow/python/kernel_tests/accumulate_n_test.py
+++ b/tensorflow/python/kernel_tests/accumulate_n_test.py
@@ -32,6 +32,7 @@ from tensorflow.python.platform import googletest
class AccumulateNV2Test(test_util.TensorFlowTestCase):
"""Tests of the new, differentiable version of accumulate_n."""
+ @test_util.run_deprecated_v1
def testFloat(self):
np.random.seed(12345)
x = [np.random.random((1, 2, 3, 4, 5)) - 0.5 for _ in range(5)]
@@ -41,6 +42,7 @@ class AccumulateNV2Test(test_util.TensorFlowTestCase):
self.assertAllClose(x[0] * 5,
math_ops.accumulate_n([tf_x[0]] * 5).eval())
+ @test_util.run_deprecated_v1
def testInt(self):
np.random.seed(54321)
x = [np.random.randint(-128, 128, (5, 4, 3, 2, 1)) for _ in range(6)]
@@ -50,12 +52,14 @@ class AccumulateNV2Test(test_util.TensorFlowTestCase):
self.assertAllEqual(x[0] * 6,
math_ops.accumulate_n([tf_x[0]] * 6).eval())
+ @test_util.run_deprecated_v1
def testUnknownShape(self):
with self.session(use_gpu=True):
x0 = array_ops.placeholder(dtype=dtypes_lib.int32, shape=[None])
acc = math_ops.accumulate_n([x0, x0], shape=[None])
self.assertAllEqual([2, 4], acc.eval(feed_dict={x0: [1, 2]}))
+ @test_util.run_deprecated_v1
def testGrad(self):
np.random.seed(42)
for num_inputs in range(1, 10):
diff --git a/tensorflow/python/kernel_tests/ackermann_test.py b/tensorflow/python/kernel_tests/ackermann_test.py
index d267e497527..6c20b19be9e 100644
--- a/tensorflow/python/kernel_tests/ackermann_test.py
+++ b/tensorflow/python/kernel_tests/ackermann_test.py
@@ -20,12 +20,14 @@ from __future__ import print_function
import os
from tensorflow.python.framework import load_library
+from tensorflow.python.framework import test_util
from tensorflow.python.platform import resource_loader
from tensorflow.python.platform import test
class AckermannTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testBasic(self):
library_filename = os.path.join(resource_loader.get_data_files_path(),
'ackermann_op.so')
diff --git a/tensorflow/python/kernel_tests/aggregate_ops_test.py b/tensorflow/python/kernel_tests/aggregate_ops_test.py
index 874d6166580..d9787cc3bf6 100644
--- a/tensorflow/python/kernel_tests/aggregate_ops_test.py
+++ b/tensorflow/python/kernel_tests/aggregate_ops_test.py
@@ -24,6 +24,7 @@ from tensorflow.core.framework import tensor_pb2
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import tensor_shape
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import logging_ops
from tensorflow.python.ops import math_ops
@@ -67,6 +68,7 @@ class AddNTest(test.TestCase):
tol = 5e-3 if dtype == dtypes.float16 else 5e-7
self.assertAllClose(expected, actual, rtol=tol, atol=tol)
+ @test_util.run_deprecated_v1
def testUnknownShapes(self):
np.random.seed(12345)
with self.session(use_gpu=True) as sess:
@@ -80,6 +82,7 @@ class AddNTest(test.TestCase):
tol = 5e-3 if dtype == dtypes.float16 else 5e-7
self.assertAllClose(expected, actual, rtol=tol, atol=tol)
+ @test_util.run_deprecated_v1
def testVariant(self):
def create_constant_variant(value):
diff --git a/tensorflow/python/kernel_tests/argmax_op_test.py b/tensorflow/python/kernel_tests/argmax_op_test.py
index d34a1dc9b29..06ec0948c25 100644
--- a/tensorflow/python/kernel_tests/argmax_op_test.py
+++ b/tensorflow/python/kernel_tests/argmax_op_test.py
@@ -20,6 +20,7 @@ from __future__ import print_function
import numpy as np
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.platform import test
@@ -110,12 +111,14 @@ class ArgMaxTest(test.TestCase):
r"Reduction axis 0 is empty in shape \[0\]"):
op([], 0).eval()
+ @test_util.run_deprecated_v1
def testDefaultAxis(self):
with self.cached_session():
for op in math_ops.argmin, math_ops.argmax:
ans = op([1]).eval()
self.assertAllEqual(ans, 0)
+ @test_util.run_deprecated_v1
def testOutputEmpty(self):
with self.cached_session():
for op in math_ops.argmin, math_ops.argmax:
diff --git a/tensorflow/python/kernel_tests/array_ops_test.py b/tensorflow/python/kernel_tests/array_ops_test.py
index afc158f6975..f4c442b7b19 100644
--- a/tensorflow/python/kernel_tests/array_ops_test.py
+++ b/tensorflow/python/kernel_tests/array_ops_test.py
@@ -143,36 +143,43 @@ class BooleanMaskTest(test_util.TensorFlowTestCase):
self.assertAllClose(masked_arr, masked_tensor.eval())
+ @test_util.run_deprecated_v1
def testMaskDim1ArrDim2Axis1(self):
ndims_mask = 1
for arr_shape in [(1, 1), (2, 2), (2, 5)]:
self.CheckVersusNumpy(ndims_mask, arr_shape, axis=1)
+ @test_util.run_deprecated_v1
def testMaskDim2ArrDim2Axis1(self):
ndims_mask = 2
for arr_shape in [(1, 1), (2, 2), (2, 5)]:
self.CheckVersusNumpy(ndims_mask, arr_shape, axis=1)
+ @test_util.run_deprecated_v1
def testMaskDim1ArrDim1(self):
ndims_mask = 1
for arr_shape in [(1,), (2,), (3,), (10,)]:
self.CheckVersusNumpy(ndims_mask, arr_shape)
+ @test_util.run_deprecated_v1
def testMaskDim1ArrDim2(self):
ndims_mask = 1
for arr_shape in [(1, 1), (2, 2), (2, 5)]:
self.CheckVersusNumpy(ndims_mask, arr_shape)
+ @test_util.run_deprecated_v1
def testMaskDim2ArrDim2(self):
ndims_mask = 2
for arr_shape in [(1, 1), (2, 2), (2, 5)]:
self.CheckVersusNumpy(ndims_mask, arr_shape)
+ @test_util.run_deprecated_v1
def testMaskDim2ArrDim3(self):
ndims_mask = 2
for arr_shape in [(1, 1, 1), (1, 2, 2), (2, 2, 1)]:
self.CheckVersusNumpy(ndims_mask, arr_shape)
+ @test_util.run_deprecated_v1
def testEmptyInput2D(self):
mask = np.array([True, False])
arr = np.array([[], []]).astype(np.float32)
@@ -191,6 +198,7 @@ class BooleanMaskTest(test_util.TensorFlowTestCase):
with self.cached_session():
self.assertAllClose(numpy_result, tf_result.eval())
+ @test_util.run_deprecated_v1
def testEmptyOutput(self):
make_mask = lambda shape: np.zeros(shape, dtype=bool)
for ndims_mask in range(1, 4):
@@ -199,6 +207,7 @@ class BooleanMaskTest(test_util.TensorFlowTestCase):
arr_shape = np.random.randint(1, 5, size=ndims_arr)
self.CheckVersusNumpy(ndims_mask, arr_shape, make_mask=make_mask)
+ @test_util.run_deprecated_v1
def testWorksWithDimensionsEqualToNoneDuringGraphBuild(self):
# The rank of the mask tensor must be specified. This is explained
# in the docstring as well.
@@ -217,6 +226,7 @@ class BooleanMaskTest(test_util.TensorFlowTestCase):
})
np.testing.assert_allclose(masked_tensor, arr[mask])
+ @test_util.run_deprecated_v1
def testMaskDimensionsSetToNoneRaises(self):
# The rank of the mask tensor must be specified. This is explained
# in the docstring as well.
@@ -283,6 +293,7 @@ class OperatorShapeTest(test_util.TensorFlowTestCase):
class ReverseV2Test(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testReverse0DimAuto(self):
x_np = 4
for use_gpu in [False, True]:
@@ -327,6 +338,7 @@ class ReverseV2Test(test_util.TensorFlowTestCase):
# This test covers the axis validation in the shape function
# (no eval())
+ @test_util.run_deprecated_v1
def testInvalidAxis(self):
x_np = np.array([[1, 2, 3], [4, 5, 6]], dtype=np.float32)
with self.assertRaisesRegexp(ValueError,
@@ -345,6 +357,7 @@ class ReverseV2Test(test_util.TensorFlowTestCase):
#
# Note: this test passes placeholder as constant axis is validated
# in shape function (see testInvalidAxis)
+ @test_util.run_deprecated_v1
def testInvalid(self):
x_np = np.array([[1, 2, 3], [4, 5, 6]], dtype=np.float32)
axis = array_ops.placeholder(dtypes.int32)
@@ -359,6 +372,7 @@ class ReverseV2Test(test_util.TensorFlowTestCase):
"axis 0 specified more than once"):
array_ops.reverse_v2(x_np, axis).eval(feed_dict={axis: [0, -2]})
+ @test_util.run_deprecated_v1
def testReverse1DimAuto(self):
for dtype in [
np.uint8, np.int8, np.uint16, np.int16, np.int32, np.int64, np.bool,
@@ -367,6 +381,7 @@ class ReverseV2Test(test_util.TensorFlowTestCase):
]:
self._reverse1DimAuto(dtype)
+ @test_util.run_deprecated_v1
def testReverse2DimAuto(self):
for dtype in [
np.uint8, np.int8, np.uint16, np.int16, np.int32, np.int64, np.bool,
@@ -375,6 +390,7 @@ class ReverseV2Test(test_util.TensorFlowTestCase):
]:
self._reverse2DimAuto(dtype)
+ @test_util.run_deprecated_v1
def testUnknownDims(self):
reverse_v2 = array_ops.reverse_v2
data_t = array_ops.placeholder(dtypes.float32)
@@ -392,6 +408,7 @@ class ReverseV2Test(test_util.TensorFlowTestCase):
reverse_2d_t = reverse_v2(data_2d_t, axis_2d_t)
self.assertEqual(2, reverse_2d_t.get_shape().ndims)
+ @test_util.run_deprecated_v1
def testReverseRowsOf3Channels(self):
"""Tests optimized code for reversing rows with last dim size = 3."""
with self.session(use_gpu=True):
@@ -405,6 +422,7 @@ class ReverseV2Test(test_util.TensorFlowTestCase):
np_answer = x_np[:, ::-1, :]
self.assertAllEqual(x_tf, np_answer)
+ @test_util.run_deprecated_v1
def testReverseRowsOf4Channels(self):
with self.session(use_gpu=True):
for reverse_f in [array_ops.reverse_v2, array_ops.reverse]:
@@ -454,6 +472,7 @@ class MeshgridTest(test_util.TensorFlowTestCase):
for x_np, x_tf in zip(numpy_out, tf_out):
self.assertAllEqual(x_np, x_tf.eval())
+ @test_util.run_deprecated_v1
def testCompare(self):
for t in (np.float16, np.float32, np.float64, np.int32, np.int64,
np.complex64, np.complex128):
@@ -526,6 +545,7 @@ STRIDED_SLICE_TYPES = [
class StridedSliceTest(test_util.TensorFlowTestCase):
"""Test the strided slice operation with variants of slices."""
+ @test_util.run_deprecated_v1
def test_basic_slice(self):
for tensor_type in STRIDED_SLICE_TYPES:
with self.cached_session(use_gpu=True):
@@ -581,6 +601,7 @@ class StridedSliceTest(test_util.TensorFlowTestCase):
v = variables.Variable([1., 2.])
v[0] # pylint: disable=pointless-statement
+ @test_util.run_deprecated_v1
def testDegenerateSlices(self):
with self.session(use_gpu=True):
checker = StridedSliceChecker(self, StridedSliceChecker.REF_TENSOR)
@@ -591,6 +612,7 @@ class StridedSliceTest(test_util.TensorFlowTestCase):
# empty interval in every dimension
_ = checker[-1:0, 2:2, 2:3:-1]
+ @test_util.run_deprecated_v1
def testEllipsis(self):
with self.session(use_gpu=True):
raw = [[[[[1, 2], [3, 4], [5, 6]]], [[[7, 8], [9, 10], [11, 12]]]]]
@@ -611,6 +633,7 @@ class StridedSliceTest(test_util.TensorFlowTestCase):
with self.assertRaisesRegexp(ValueError, "Multiple ellipses"):
_ = checker[..., :, ...].eval()
+ @test_util.run_deprecated_v1
def testShrink(self):
with self.session(use_gpu=True):
raw = [[[[[1, 2, 4, 5], [5, 6, 7, 8], [9, 10, 11, 12]]],
@@ -621,6 +644,7 @@ class StridedSliceTest(test_util.TensorFlowTestCase):
_ = checker[:, 0]
_ = checker[:, :, 0]
+ @test_util.run_deprecated_v1
def testBothNewAxisAndShrink(self):
with self.session(use_gpu=True):
ones = array_ops.placeholder(shape=[2, 2], dtype=dtypes.int16)
@@ -629,6 +653,7 @@ class StridedSliceTest(test_util.TensorFlowTestCase):
feed_dict={ones: [[1, 1], [1, 1]]}),
[[1, 1]])
+ @test_util.run_deprecated_v1
def testTensorIndexing(self):
with self.session(use_gpu=True):
raw = [[[[[1, 2, 4, 5], [5, 6, 7, 8], [9, 10, 11, 12]]],
@@ -654,6 +679,7 @@ class StridedSliceTest(test_util.TensorFlowTestCase):
with self.assertRaisesRegexp(TypeError, expected):
_ = checker[constant_op.constant(0.0)]
+ @test_util.run_deprecated_v1
def testExpand(self):
with self.session(use_gpu=True):
raw = [[[[[1, 2, 4, 5], [5, 6, 7, 8], [9, 10, 11, 12]]],
@@ -671,6 +697,7 @@ class StridedSliceTest(test_util.TensorFlowTestCase):
# Ellipsis in middle of two newaxis
_ = checker[np.newaxis, ..., np.newaxis]
+ @test_util.run_deprecated_v1
def testExpandVariable(self):
with self.session(use_gpu=True):
x = variables.Variable(7, dtype=dtypes.int32)
@@ -679,6 +706,7 @@ class StridedSliceTest(test_util.TensorFlowTestCase):
self.assertEqual(y.shape, (1,))
self.assertAllEqual(y, (7,))
+ @test_util.run_deprecated_v1
def testOptimizedCases(self):
with self.session(use_gpu=True):
checker = StridedSliceChecker(self,
@@ -708,6 +736,7 @@ class StridedSliceShapeChecker(object):
class StridedSliceShapeTest(test_util.TensorFlowTestCase):
"""Test the shape inference of StridedSliceShapes."""
+ @test_util.run_deprecated_v1
def testUnknown(self):
with self.session(use_gpu=True):
uncertain_tensor = array_ops.placeholder(dtypes.float32)
@@ -719,6 +748,7 @@ class StridedSliceShapeTest(test_util.TensorFlowTestCase):
self.assertTrue(x is not None and y is not None or x is None and y is None)
self.assertEqual(x.as_list(), y.as_list())
+ @test_util.run_deprecated_v1
def testTensorShapeUncertain(self):
with self.session(use_gpu=True):
uncertain_tensor = array_ops.placeholder(
@@ -742,6 +772,7 @@ class StridedSliceShapeTest(test_util.TensorFlowTestCase):
self.tensorShapeEqual(a[::-1, :, array_ops.newaxis, ::-2],
tensor_shape.TensorShape([5, None, 1, 4]))
+ @test_util.run_deprecated_v1
def testTensorValuedIndexShape(self):
with self.session(use_gpu=True):
defined_shape_tensor = array_ops.placeholder(
@@ -798,6 +829,7 @@ class GradSliceChecker(object):
class StridedSliceGradTest(test_util.TensorFlowTestCase):
"""Test that strided slice's custom gradient produces correct gradients."""
+ @test_util.run_deprecated_v1
def testGradient(self):
with self.session(use_gpu=True) as sess:
var = variables.Variable(
@@ -827,6 +859,7 @@ class StridedSliceGradTest(test_util.TensorFlowTestCase):
grad = GradSliceChecker(self, sess, var, np.array(8))
_ = grad[tuple()]
+ @test_util.run_deprecated_v1
def testInt64Indices(self):
with self.session(use_gpu=True) as sess:
a = math_ops.range(3, dtype=dtypes.float32)
@@ -839,6 +872,7 @@ class StridedSliceGradTest(test_util.TensorFlowTestCase):
class StridedSliceGradTypeTest(test_util.TensorFlowTestCase):
"""Test varied index types and host located memory."""
+ @test_util.run_deprecated_v1
def testHostVsDevice(self):
with self.session(use_gpu=True) as sess:
var2 = variables.Variable(
@@ -853,6 +887,7 @@ class StridedSliceGradTypeTest(test_util.TensorFlowTestCase):
foo = array_ops.strided_slice_grad(varshape, begin, end, strides, var2)
sess.run(foo)
+ @test_util.run_deprecated_v1
def testInt64Shape(self):
with self.session(use_gpu=True) as sess:
original_dy = array_ops.reshape(
@@ -867,6 +902,7 @@ class StridedSliceGradTypeTest(test_util.TensorFlowTestCase):
original_dy)
sess.run(dx)
+ @test_util.run_deprecated_v1
def testMixedIndexTypes(self):
with self.session(use_gpu=True) as sess:
original_dy = array_ops.reshape(
@@ -975,6 +1011,7 @@ class StridedSliceAssignChecker(object):
class SliceAssignTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testInvalidSlice(self):
with self.cached_session() as sess:
foo = constant_op.constant([1, 2, 3])
@@ -1012,12 +1049,15 @@ class SliceAssignTest(test_util.TensorFlowTestCase):
checker2[...] = 6 # ellipsis
checker2[None] = [6] # new axis
+ @test_util.run_deprecated_v1
def testSliceAssign(self):
self.doTestSliceAssign(use_resource=False)
+ @test_util.run_deprecated_v1
def testSliceAssignResource(self):
self.doTestSliceAssign(use_resource=True)
+ @test_util.run_deprecated_v1
def testUninitialized(self):
with self.assertRaisesRegexp(
errors.FailedPreconditionError,
@@ -1036,6 +1076,7 @@ class SliceAssignTest(test_util.TensorFlowTestCase):
with self.assertRaises(TypeError):
v[:].assign(too_large_val)
+ @test_util.run_deprecated_v1
def testTypeErrorResource(self):
init_val = constant_op.constant([1, 2], dtype=dtypes.int32)
too_small_val = constant_op.constant([3, 4], dtype=dtypes.int8)
@@ -1092,6 +1133,7 @@ class SequenceMaskTest(test_util.TensorFlowTestCase):
with self.assertRaisesRegexp(ValueError, "maxlen must be scalar"):
array_ops.sequence_mask([10, 20], [10, 20])
+ @test_util.run_deprecated_v1
def testOneDimensionalWithMaxlen(self):
with self.cached_session():
res = array_ops.sequence_mask(constant_op.constant([1, 3, 2]), 5)
@@ -1101,6 +1143,7 @@ class SequenceMaskTest(test_util.TensorFlowTestCase):
[[True, False, False, False, False], [True, True, True, False, False],
[True, True, False, False, False]])
+ @test_util.run_deprecated_v1
def testOneDimensionalDtypeWithoutMaxlen(self):
with self.cached_session():
# test dtype and default maxlen:
@@ -1111,6 +1154,7 @@ class SequenceMaskTest(test_util.TensorFlowTestCase):
res.eval(),
[[0.0, 0.0, 0.0, 0.0], [1.0, 0.0, 0.0, 0.0], [1.0, 1.0, 1.0, 1.0]])
+ @test_util.run_deprecated_v1
def testOneDimensionalWithoutMaxlen(self):
with self.cached_session():
res = array_ops.sequence_mask(
@@ -1139,11 +1183,13 @@ class SequenceMaskTest(test_util.TensorFlowTestCase):
[[[0.0, 0.0, 0.0, 0.0], [1.0, 0.0, 0.0, 0.0], [1.0, 1.0, 1.0, 1.0]],
[[1.0, 0.0, 0.0, 0.0], [1.0, 1.0, 0.0, 0.0], [1.0, 1.0, 1.0, 0.0]]])
+ @test_util.run_deprecated_v1
def testUnknownShape(self):
lengths = array_ops.placeholder(dtype=dtypes.int32)
res = array_ops.sequence_mask(lengths)
self.assertEqual(res.shape, None)
+ @test_util.run_deprecated_v1
def testDtypes(self):
def check_dtypes(lengths_dtype, maxlen_dtype):
@@ -1166,6 +1212,7 @@ class SequenceMaskTest(test_util.TensorFlowTestCase):
class ConcatSliceResourceTest(test_util.TensorFlowTestCase):
@test_util.run_in_graph_and_eager_modes
+ @test_util.run_deprecated_v1
def testConcatSlice(self):
r1 = test_ops.stub_resource_handle_op(container="a", shared_name="b")
r2 = test_ops.stub_resource_handle_op(container="a", shared_name="c")
@@ -1221,6 +1268,7 @@ class PadTest(test_util.TensorFlowTestCase):
class InvertPermutationTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testInvertPermutation(self):
for dtype in [dtypes.int32, dtypes.int64]:
with self.cached_session(use_gpu=True):
@@ -1255,12 +1303,14 @@ class UnravelIndexTest(test_util.TensorFlowTestCase):
class GuaranteeConstOpTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testSimple(self):
with self.cached_session():
a = array_ops.constant(10)
guarantee_a = array_ops.guarantee_const(a)
self.assertEqual(10, guarantee_a.eval())
+ @test_util.run_deprecated_v1
def testVariables(self):
with self.cached_session() as sess:
for use_resource in [False, True]:
@@ -1272,6 +1322,7 @@ class GuaranteeConstOpTest(test_util.TensorFlowTestCase):
self.evaluate(variables.global_variables_initializer())
self.assertEqual(10.0, guarantee_a.eval())
+ @test_util.run_deprecated_v1
def testResourceRejection(self):
with self.cached_session() as sess:
a = variable_scope.get_variable(
@@ -1287,6 +1338,7 @@ class GuaranteeConstOpTest(test_util.TensorFlowTestCase):
class SnapshotOpTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testInvertPermutation(self):
for dtype in [dtypes.int32, dtypes.int64, dtypes.float32, dtypes.float64]:
with self.cached_session(use_gpu=True):
diff --git a/tensorflow/python/kernel_tests/as_string_op_test.py b/tensorflow/python/kernel_tests/as_string_op_test.py
index dd4a90e5f65..287701a73e4 100644
--- a/tensorflow/python/kernel_tests/as_string_op_test.py
+++ b/tensorflow/python/kernel_tests/as_string_op_test.py
@@ -20,6 +20,7 @@ from __future__ import print_function
import numpy as np
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import string_ops
from tensorflow.python.platform import test
@@ -27,6 +28,7 @@ from tensorflow.python.platform import test
class AsStringOpTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testFloat(self):
float_inputs_ = [
0, 1, -1, 0.5, 0.25, 0.125, float("INF"), float("NAN"), float("-INF")
@@ -78,6 +80,7 @@ class AsStringOpTest(test.TestCase):
output = string_ops.as_string(input_, fill="ab")
output.eval(feed_dict={input_: float_inputs_})
+ @test_util.run_deprecated_v1
def testInt(self):
# Cannot use values outside -128..127 for test, because we're also
# testing int8
@@ -112,6 +115,7 @@ class AsStringOpTest(test.TestCase):
output = string_ops.as_string(input_, precision=0)
output.eval(feed_dict={input_: int_inputs_})
+ @test_util.run_deprecated_v1
def testLargeInt(self):
# Cannot use values outside -128..127 for test, because we're also
# testing int8
@@ -130,6 +134,7 @@ class AsStringOpTest(test.TestCase):
result = output.eval(feed_dict={input_: int_inputs_})
self.assertAllEqual(s(result), ["%d" % x for x in int_inputs_])
+ @test_util.run_deprecated_v1
def testHalfInt(self):
s = lambda strs: [x.decode("ascii") for x in strs]
@@ -140,6 +145,7 @@ class AsStringOpTest(test.TestCase):
result = output.eval(feed_dict={input_: int_inputs_})
self.assertAllEqual(s(result), ["%d" % x for x in int_inputs_])
+ @test_util.run_deprecated_v1
def testBool(self):
bool_inputs_ = [False, True]
s = lambda strs: [x.decode("ascii") for x in strs]
@@ -152,6 +158,7 @@ class AsStringOpTest(test.TestCase):
result = output.eval(feed_dict={input_: bool_inputs_})
self.assertAllEqual(s(result), ["false", "true"])
+ @test_util.run_deprecated_v1
def testComplex(self):
float_inputs_ = [
0, 1, -1, 0.5, 0.25, 0.125, complex("INF"), complex("NAN"),
diff --git a/tensorflow/python/kernel_tests/atrous_conv2d_test.py b/tensorflow/python/kernel_tests/atrous_conv2d_test.py
index fefb7979956..a13e325835c 100644
--- a/tensorflow/python/kernel_tests/atrous_conv2d_test.py
+++ b/tensorflow/python/kernel_tests/atrous_conv2d_test.py
@@ -22,6 +22,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import nn_impl
@@ -58,6 +59,7 @@ def _upsample_filters(filters, rate):
class AtrousConv2DTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testAtrousConv2DForward(self):
with self.session(use_gpu=True):
# Input: [batch, height, width, input_depth]
@@ -82,6 +84,7 @@ class AtrousConv2DTest(test.TestCase):
self.assertAllClose(
y1.eval(), self.evaluate(y2), rtol=1e-3, atol=1e-3)
+ @test_util.run_deprecated_v1
def testAtrousSequence(self):
"""Tests optimization of sequence of atrous convolutions.
@@ -135,6 +138,7 @@ class AtrousConv2DTest(test.TestCase):
self.assertAllClose(
y1.eval(), self.evaluate(y2), rtol=1e-2, atol=1e-2)
+ @test_util.run_deprecated_v1
def testGradient(self):
with self.session(use_gpu=True):
# Input: [batch, height, width, input_depth]
@@ -162,6 +166,7 @@ class AtrousConv2DTest(test.TestCase):
class AtrousConv2DTransposeTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testAtrousConv2DTransposeForward(self):
with self.session(use_gpu=True):
# Input: [batch, height, width, input_depth]
@@ -201,6 +206,7 @@ class AtrousConv2DTransposeTest(test.TestCase):
class AtrousDepthwiseConv2DTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testAtrousDepthwiseConv2DForward(self):
strides = [1, 1, 1, 1]
with self.session(use_gpu=True):
diff --git a/tensorflow/python/kernel_tests/barrier_ops_test.py b/tensorflow/python/kernel_tests/barrier_ops_test.py
index 495bbe7b341..60fe6f0eecd 100644
--- a/tensorflow/python/kernel_tests/barrier_ops_test.py
+++ b/tensorflow/python/kernel_tests/barrier_ops_test.py
@@ -25,6 +25,7 @@ import numpy as np
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors_impl
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import data_flow_ops
from tensorflow.python.platform import test
@@ -66,6 +67,7 @@ class BarrierTest(test.TestCase):
attr { key: 'shared_name' value: { s: 'B' } }
""", b.barrier_ref.op.node_def)
+ @test_util.run_deprecated_v1
def testInsertMany(self):
with self.cached_session():
b = data_flow_ops.Barrier(
@@ -90,6 +92,7 @@ class BarrierTest(test.TestCase):
data_flow_ops.Barrier(
(dtypes.float32, dtypes.float32), shapes=((1,), (0,)), name="B")
+ @test_util.run_deprecated_v1
def testInsertManyEmptyTensorUnknown(self):
with self.cached_session():
b = data_flow_ops.Barrier((dtypes.float32, dtypes.float32), name="B")
@@ -102,6 +105,7 @@ class BarrierTest(test.TestCase):
".*Tensors with no elements are not supported.*"):
insert_0_op.run()
+ @test_util.run_deprecated_v1
def testTakeMany(self):
with self.cached_session() as sess:
b = data_flow_ops.Barrier(
@@ -127,6 +131,7 @@ class BarrierTest(test.TestCase):
self.assertEqual(values_0_val[idx], v0)
self.assertEqual(values_1_val[idx], v1)
+ @test_util.run_deprecated_v1
def testTakeManySmallBatch(self):
with self.cached_session() as sess:
b = data_flow_ops.Barrier(
@@ -191,6 +196,7 @@ class BarrierTest(test.TestCase):
with self.assertRaisesOpError("is closed"):
insert_1_3_op.run()
+ @test_util.run_deprecated_v1
def testUseBarrierWithShape(self):
with self.cached_session() as sess:
b = data_flow_ops.Barrier(
@@ -220,6 +226,7 @@ class BarrierTest(test.TestCase):
self.assertAllEqual(values_0_val[idx], v0)
self.assertAllEqual(values_1_val[idx], v1)
+ @test_util.run_deprecated_v1
def testParallelInsertMany(self):
with self.cached_session() as sess:
b = data_flow_ops.Barrier(dtypes.float32, shapes=())
@@ -240,6 +247,7 @@ class BarrierTest(test.TestCase):
idx = keys_val.tolist().index(k)
self.assertEqual(values_val[idx], v)
+ @test_util.run_deprecated_v1
def testParallelTakeMany(self):
with self.cached_session() as sess:
b = data_flow_ops.Barrier(dtypes.float32, shapes=())
@@ -274,6 +282,7 @@ class BarrierTest(test.TestCase):
self.assertItemsEqual(
zip(keys, values), [(k[0], v[0]) for k, v in zip(key_vals, value_vals)])
+ @test_util.run_deprecated_v1
def testBlockingTakeMany(self):
with self.cached_session() as sess:
b = data_flow_ops.Barrier(dtypes.float32, shapes=())
@@ -296,6 +305,7 @@ class BarrierTest(test.TestCase):
insert_op.run()
t.join()
+ @test_util.run_deprecated_v1
def testParallelInsertManyTakeMany(self):
with self.cached_session() as sess:
b = data_flow_ops.Barrier(
@@ -375,6 +385,7 @@ class BarrierTest(test.TestCase):
2 + outer_indices_from_keys + inner_indices_from_keys)).T
self.assertAllEqual(taken_i["values_1"], expected_values_1)
+ @test_util.run_deprecated_v1
def testClose(self):
with self.cached_session() as sess:
b = data_flow_ops.Barrier(
@@ -433,6 +444,7 @@ class BarrierTest(test.TestCase):
with self.assertRaisesOpError("is closed and has insufficient elements"):
sess.run(take_t[0])
+ @test_util.run_deprecated_v1
def testCancel(self):
with self.cached_session() as sess:
b = data_flow_ops.Barrier(
@@ -495,6 +507,7 @@ class BarrierTest(test.TestCase):
with self.assertRaisesOpError("is closed and has insufficient elements"):
self.evaluate(take_t)
+ @test_util.run_deprecated_v1
def testClosedEmptyBarrierTakeManyAllowSmallBatchRaises(self):
self._testClosedEmptyBarrierTakeManyAllowSmallBatchRaises(cancel=False)
self._testClosedEmptyBarrierTakeManyAllowSmallBatchRaises(cancel=True)
@@ -569,9 +582,11 @@ class BarrierTest(test.TestCase):
sorted(taken),
[0] * (num_iterations // 2) + [10] * (num_iterations // 2))
+ @test_util.run_deprecated_v1
def testParallelInsertManyTakeManyCloseHalfwayThrough(self):
self._testParallelInsertManyTakeManyCloseHalfwayThrough(cancel=False)
+ @test_util.run_deprecated_v1
def testParallelInsertManyTakeManyCancelHalfwayThrough(self):
self._testParallelInsertManyTakeManyCloseHalfwayThrough(cancel=True)
@@ -669,12 +684,15 @@ class BarrierTest(test.TestCase):
else:
self.assertEqual(taken, [10] * num_iterations)
+ @test_util.run_deprecated_v1
def testParallelPartialInsertManyTakeManyCloseHalfwayThrough(self):
self._testParallelPartialInsertManyTakeManyCloseHalfwayThrough(cancel=False)
+ @test_util.run_deprecated_v1
def testParallelPartialInsertManyTakeManyCancelHalfwayThrough(self):
self._testParallelPartialInsertManyTakeManyCloseHalfwayThrough(cancel=True)
+ @test_util.run_deprecated_v1
def testIncompatibleSharedBarrierErrors(self):
with self.cached_session():
# Do component types and shapes.
diff --git a/tensorflow/python/kernel_tests/basic_gpu_test.py b/tensorflow/python/kernel_tests/basic_gpu_test.py
index cd330481214..1a8513d022d 100644
--- a/tensorflow/python/kernel_tests/basic_gpu_test.py
+++ b/tensorflow/python/kernel_tests/basic_gpu_test.py
@@ -159,6 +159,7 @@ class BroadcastSimpleTest(test.TestCase):
with self.cached_session(use_gpu=True) as sess:
return sess.run(broadcast_gradient_args(xs, ys))
+ @test_util.run_deprecated_v1
def testBroadcast(self):
r0, r1 = self._GetGradientArgs([2, 3, 5], [1])
self.assertAllEqual(r0, [])
@@ -219,6 +220,7 @@ class BroadcastSimpleTest(test.TestCase):
self.assertShapeEqual(np_ans, out)
# TODO(zhifengc/ke): make gradient checker work on GPU.
+ @test_util.run_deprecated_v1
def testGradient(self):
x = (1 + np.linspace(0, 5, np.prod([1, 3, 2]))).astype(np.float32).reshape(
[1, 3, 2])
@@ -255,6 +257,7 @@ class GpuMultiSessionMemoryTest(test_util.TensorFlowTestCase):
if len(results) != 1:
break
+ @test_util.run_deprecated_v1
def testConcurrentSessions(self):
n_threads = 4
threads = []
diff --git a/tensorflow/python/kernel_tests/batch_gather_op_test.py b/tensorflow/python/kernel_tests/batch_gather_op_test.py
index ad4e8791314..7e0b3e1b5ea 100644
--- a/tensorflow/python/kernel_tests/batch_gather_op_test.py
+++ b/tensorflow/python/kernel_tests/batch_gather_op_test.py
@@ -23,6 +23,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.platform import test
@@ -87,6 +88,7 @@ class GatherTest(test.TestCase, parameterized.TestCase):
self.assertAllEqual(np_val, gather_val)
self.assertEqual(np_val.shape, gather_t.get_shape())
+ @test_util.run_deprecated_v1
def testString(self):
params = np.array([[b"asdf", b"zxcv"], [b"qwer", b"uiop"]])
with self.cached_session():
@@ -94,6 +96,7 @@ class GatherTest(test.TestCase, parameterized.TestCase):
self.assertAllEqual([[b"qwer", b"uiop"]],
array_ops.batch_gather(params, indices_tf).eval())
+ @test_util.run_deprecated_v1
def testUnknownIndices(self):
params = constant_op.constant([[0, 1, 2]])
indices = array_ops.placeholder(dtypes.int32, shape=[None, None])
@@ -106,6 +109,7 @@ class GatherTest(test.TestCase, parameterized.TestCase):
with self.assertRaisesOpError(r"indices\[0\] = 7 is not in \[0, 2\)"):
array_ops.batch_gather(params, [7]).eval()
+ @test_util.run_deprecated_v1
def testEmptySlices(self):
with self.session(use_gpu=True):
for dtype in _TEST_TYPES:
diff --git a/tensorflow/python/kernel_tests/batch_scatter_ops_test.py b/tensorflow/python/kernel_tests/batch_scatter_ops_test.py
index a4b461bc87b..eefcdc508f0 100644
--- a/tensorflow/python/kernel_tests/batch_scatter_ops_test.py
+++ b/tensorflow/python/kernel_tests/batch_scatter_ops_test.py
@@ -22,6 +22,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import state_ops
from tensorflow.python.ops import variables
from tensorflow.python.platform import test
@@ -73,6 +74,7 @@ class ScatterTest(test.TestCase):
tf_scatter(ref, indices, updates).eval()
self.assertAllClose(ref.eval(), new)
+ @test_util.run_deprecated_v1
def testVariableRankUpdate(self):
vtypes = [np.float32, np.float64]
for vtype in vtypes:
@@ -80,6 +82,7 @@ class ScatterTest(test.TestCase):
self._VariableRankTest(
state_ops.batch_scatter_update, vtype, itype)
+ @test_util.run_deprecated_v1
def testBooleanScatterUpdate(self):
with self.session(use_gpu=False) as session:
var = variables.Variable([True, False])
@@ -93,6 +96,7 @@ class ScatterTest(test.TestCase):
self.assertAllEqual([False, True], self.evaluate(var))
+ @test_util.run_deprecated_v1
def testScatterOutOfRange(self):
params = np.array([1, 2, 3, 4, 5, 6]).astype(np.float32)
updates = np.array([-3, -4, -5]).astype(np.float32)
diff --git a/tensorflow/python/kernel_tests/batchtospace_op_test.py b/tensorflow/python/kernel_tests/batchtospace_op_test.py
index 03f3f64353d..c422df8806f 100644
--- a/tensorflow/python/kernel_tests/batchtospace_op_test.py
+++ b/tensorflow/python/kernel_tests/batchtospace_op_test.py
@@ -27,6 +27,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gen_array_ops
from tensorflow.python.ops import gradient_checker
@@ -50,6 +51,7 @@ class CppOpImpl(object):
class BatchToSpaceDepthToSpace(test.TestCase, PythonOpImpl):
# Verifies that: batch_to_space(x) = transpose(depth_to_space(transpose(x)))
+ @test_util.run_deprecated_v1
def testDepthToSpaceTranspose(self):
x = np.arange(20 * 5 * 8 * 7, dtype=np.float32).reshape([20, 5, 8, 7])
block_size = 2
@@ -70,6 +72,7 @@ class BatchToSpaceDepthToSpaceCpp(BatchToSpaceDepthToSpace, CppOpImpl):
class BatchToSpaceErrorHandlingTest(test.TestCase, PythonOpImpl):
+ @test_util.run_deprecated_v1
def testInputWrongDimMissingBatch(self):
# The input is missing the first dimension ("batch")
x_np = [[[1], [2]], [[3], [4]]]
@@ -78,6 +81,7 @@ class BatchToSpaceErrorHandlingTest(test.TestCase, PythonOpImpl):
with self.assertRaises(ValueError):
_ = self.batch_to_space(x_np, crops, block_size)
+ @test_util.run_deprecated_v1
def testBlockSize0(self):
# The block size is 0.
x_np = [[[[1], [2]], [[3], [4]]]]
@@ -87,6 +91,7 @@ class BatchToSpaceErrorHandlingTest(test.TestCase, PythonOpImpl):
out_tf = self.batch_to_space(x_np, crops, block_size)
out_tf.eval()
+ @test_util.run_deprecated_v1
def testBlockSizeOne(self):
# The block size is 1. The block size needs to be > 1.
x_np = [[[[1], [2]], [[3], [4]]]]
@@ -96,6 +101,7 @@ class BatchToSpaceErrorHandlingTest(test.TestCase, PythonOpImpl):
out_tf = self.batch_to_space(x_np, crops, block_size)
out_tf.eval()
+ @test_util.run_deprecated_v1
def testBlockSizeLarger(self):
# The block size is too large for this input.
x_np = [[[[1], [2]], [[3], [4]]]]
@@ -105,6 +111,7 @@ class BatchToSpaceErrorHandlingTest(test.TestCase, PythonOpImpl):
out_tf = self.batch_to_space(x_np, crops, block_size)
out_tf.eval()
+ @test_util.run_deprecated_v1
def testBlockSizeSquaredNotDivisibleBatch(self):
# The block size squared does not divide the batch.
x_np = [[[[1], [2], [3]], [[3], [4], [7]]]]
@@ -113,6 +120,7 @@ class BatchToSpaceErrorHandlingTest(test.TestCase, PythonOpImpl):
with self.assertRaises(ValueError):
_ = self.batch_to_space(x_np, crops, block_size)
+ @test_util.run_deprecated_v1
def testUnknownShape(self):
t = self.batch_to_space(
array_ops.placeholder(dtypes.float32),
@@ -160,28 +168,35 @@ class BatchToSpaceNDErrorHandlingTest(test.TestCase):
self._testStaticShape(input_shape, block_shape, paddings, error)
self._testDynamicShape(input_shape, block_shape, paddings)
+ @test_util.run_deprecated_v1
def testInputWrongDimMissingBatch(self):
self._testShape([2, 2], [2, 2], [[0, 0], [0, 0]], ValueError)
self._testShape([2, 2, 3], [2, 2, 3], [[0, 0], [0, 0]], ValueError)
+ @test_util.run_deprecated_v1
def testBlockSize0(self):
# The block size is 0.
self._testShape([1, 2, 2, 1], [0, 1], [[0, 0], [0, 0]], ValueError)
+ @test_util.run_deprecated_v1
def testBlockSizeNegative(self):
self._testShape([1, 2, 2, 1], [-1, 1], [[0, 0], [0, 0]], ValueError)
+ @test_util.run_deprecated_v1
def testNegativePadding(self):
self._testShape([1, 2, 2], [1, 1], [[0, -1], [0, 0]], ValueError)
+ @test_util.run_deprecated_v1
def testCropTooLarge(self):
# The amount to crop exceeds the padded size.
self._testShape([1 * 2 * 2, 2, 3, 1], [2, 2], [[3, 2], [0, 0]], ValueError)
+ @test_util.run_deprecated_v1
def testBlockSizeSquaredNotDivisibleBatch(self):
# The batch dimension is not divisible by the product of the block_shape.
self._testShape([3, 1, 1, 1], [2, 3], [[0, 0], [0, 0]], ValueError)
+ @test_util.run_deprecated_v1
def testUnknownShape(self):
# Verify that input shape and paddings shape can be unknown.
_ = array_ops.batch_to_space_nd(
@@ -263,18 +278,21 @@ class BatchToSpaceGradientTest(test.TestCase, PythonOpImpl):
# Don't use very large numbers as dimensions here as the result is tensor
# with cartesian product of the dimensions.
+ @test_util.run_deprecated_v1
def testSmall(self):
block_size = 2
crop_beg = 0
crop_end = 0
self._compare(1, 2, 3, 5, block_size, crop_beg, crop_end)
+ @test_util.run_deprecated_v1
def testSmall2(self):
block_size = 2
crop_beg = 0
crop_end = 0
self._compare(2, 4, 3, 2, block_size, crop_beg, crop_end)
+ @test_util.run_deprecated_v1
def testSmallCrop1x1(self):
block_size = 2
crop_beg = 1
@@ -316,14 +334,17 @@ class BatchToSpaceNDGradientTest(test.TestCase):
# Don't use very large numbers as dimensions here as the result is tensor
# with cartesian product of the dimensions.
+ @test_util.run_deprecated_v1
def testSmall(self):
for dtype in [dtypes.int64, dtypes.int32]:
self._compare([1, 2, 3, 5], [2, 2], [[0, 0], [0, 0]], dtype)
+ @test_util.run_deprecated_v1
def testSmall2(self):
for dtype in [dtypes.int64, dtypes.int32]:
self._compare([2, 4, 3, 2], [2, 2], [[0, 0], [0, 0]], dtype)
+ @test_util.run_deprecated_v1
def testSmallCrop1x1(self):
for dtype in [dtypes.int64, dtypes.int32]:
self._compare([1, 2, 3, 5], [2, 2], [[1, 1], [1, 1]], dtype)
diff --git a/tensorflow/python/kernel_tests/bcast_ops_test.py b/tensorflow/python/kernel_tests/bcast_ops_test.py
index 3ec820aeada..ae00955ac29 100644
--- a/tensorflow/python/kernel_tests/bcast_ops_test.py
+++ b/tensorflow/python/kernel_tests/bcast_ops_test.py
@@ -20,6 +20,7 @@ from __future__ import print_function
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops.gen_array_ops import broadcast_args
from tensorflow.python.ops.gen_array_ops import broadcast_gradient_args
from tensorflow.python.platform import test
@@ -35,6 +36,7 @@ class BcastOpsTest(test.TestCase):
with self.cached_session() as sess:
return sess.run(broadcast_gradient_args(xs, ys))
+ @test_util.run_deprecated_v1
def testBasic(self):
r = self._GetBroadcastShape([2, 3, 5], [1])
self.assertAllEqual(r, [2, 3, 5])
@@ -66,6 +68,7 @@ class BcastOpsTest(test.TestCase):
r = self._GetBroadcastShape([3, 1], [2, 1, 5])
self.assertAllEqual(r, [2, 3, 5])
+ @test_util.run_deprecated_v1
def testBasicGradient(self):
r0, r1 = self._GetGradientArgs([2, 3, 5], [1])
self.assertAllEqual(r0, [])
@@ -107,6 +110,7 @@ class BcastOpsTest(test.TestCase):
self.assertAllEqual(r0, [0, 2])
self.assertAllEqual(r1, [1])
+ @test_util.run_deprecated_v1
def testZeroDims(self):
r = self._GetBroadcastShape([2, 0, 3, 0, 5], [3, 0, 5])
self.assertAllEqual(r, [2, 0, 3, 0, 5])
@@ -120,6 +124,7 @@ class BcastOpsTest(test.TestCase):
r = self._GetBroadcastShape([3, 1, 5], [2, 0, 3, 0, 5])
self.assertAllEqual(r, [2, 0, 3, 0, 5])
+ @test_util.run_deprecated_v1
def testZeroDimsGradient(self):
r0, r1 = self._GetGradientArgs([2, 0, 3, 0, 5], [3, 0, 5])
self.assertAllEqual(r0, [])
@@ -137,6 +142,7 @@ class BcastOpsTest(test.TestCase):
self.assertAllEqual(r0, [0, 1, 3])
self.assertAllEqual(r1, [])
+ @test_util.run_deprecated_v1
def testDataTypes(self):
for dtype in [dtypes.int32, dtypes.int64]:
r = self._GetBroadcastShape(
diff --git a/tensorflow/python/kernel_tests/betainc_op_test.py b/tensorflow/python/kernel_tests/betainc_op_test.py
index 5d7446042e1..9dc34a60628 100644
--- a/tensorflow/python/kernel_tests/betainc_op_test.py
+++ b/tensorflow/python/kernel_tests/betainc_op_test.py
@@ -24,6 +24,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import gradients_impl
@@ -109,36 +110,42 @@ class BetaincTest(test.TestCase):
except ImportError as e:
tf_logging.warn("Cannot test special functions: %s" % str(e))
+ @test_util.run_deprecated_v1
def testBetaIncFloat(self):
a_s = np.abs(np.random.randn(10, 10) * 30) # in (0, infty)
b_s = np.abs(np.random.randn(10, 10) * 30) # in (0, infty)
x_s = np.random.rand(10, 10) # in (0, 1)
self._testBetaInc(a_s, b_s, x_s, dtypes.float32)
+ @test_util.run_deprecated_v1
def testBetaIncDouble(self):
a_s = np.abs(np.random.randn(10, 10) * 30) # in (0, infty)
b_s = np.abs(np.random.randn(10, 10) * 30) # in (0, infty)
x_s = np.random.rand(10, 10) # in (0, 1)
self._testBetaInc(a_s, b_s, x_s, dtypes.float64)
+ @test_util.run_deprecated_v1
def testBetaIncDoubleVeryLargeValues(self):
a_s = np.abs(np.random.randn(10, 10) * 1e15) # in (0, infty)
b_s = np.abs(np.random.randn(10, 10) * 1e15) # in (0, infty)
x_s = np.random.rand(10, 10) # in (0, 1)
self._testBetaInc(a_s, b_s, x_s, dtypes.float64)
+ @test_util.run_deprecated_v1
def testBetaIncDoubleVerySmallValues(self):
a_s = np.abs(np.random.randn(10, 10) * 1e-16) # in (0, infty)
b_s = np.abs(np.random.randn(10, 10) * 1e-16) # in (0, infty)
x_s = np.random.rand(10, 10) # in (0, 1)
self._testBetaInc(a_s, b_s, x_s, dtypes.float64)
+ @test_util.run_deprecated_v1
def testBetaIncFloatVerySmallValues(self):
a_s = np.abs(np.random.randn(10, 10) * 1e-8) # in (0, infty)
b_s = np.abs(np.random.randn(10, 10) * 1e-8) # in (0, infty)
x_s = np.random.rand(10, 10) # in (0, 1)
self._testBetaInc(a_s, b_s, x_s, dtypes.float32)
+ @test_util.run_deprecated_v1
def testBetaIncFpropAndBpropAreNeverNAN(self):
with self.cached_session() as sess:
space = np.logspace(-8, 5).tolist()
@@ -159,6 +166,7 @@ class BetaincTest(test.TestCase):
self.assertAllEqual(np.zeros_like(grads_x).astype(np.bool),
np.isnan(grads_x))
+ @test_util.run_deprecated_v1
def testBetaIncGrads(self):
err_tolerance = 1e-3
with self.cached_session():
diff --git a/tensorflow/python/kernel_tests/bias_op_test.py b/tensorflow/python/kernel_tests/bias_op_test.py
index 749d6a791e3..66f442dbddb 100644
--- a/tensorflow/python/kernel_tests/bias_op_test.py
+++ b/tensorflow/python/kernel_tests/bias_op_test.py
@@ -22,6 +22,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import gradients_impl
@@ -89,10 +90,12 @@ class BiasAddTest(test.TestCase):
self._testBiasNCHW(np_inputs, np_bias, use_gpu=True)
+ @test_util.run_deprecated_v1
def testInputDims(self):
with self.assertRaises(ValueError):
nn_ops.bias_add([1, 2], [1])
+ @test_util.run_deprecated_v1
def testBiasVec(self):
with self.assertRaises(ValueError):
nn_ops.bias_add(
@@ -101,6 +104,7 @@ class BiasAddTest(test.TestCase):
array_ops.reshape(
[1, 2], shape=[1, 2]))
+ @test_util.run_deprecated_v1
def testBiasInputsMatch(self):
with self.assertRaises(ValueError):
nn_ops.bias_add(
@@ -109,23 +113,27 @@ class BiasAddTest(test.TestCase):
array_ops.reshape(
[1], shape=[1]))
+ @test_util.run_deprecated_v1
def testIntTypes(self):
for t in [np.int8, np.int16, np.int32, np.int64]:
self._testAll(
np.array([[10, 20, 30], [40, 50, 60]]).astype(t),
np.array([1, 2, 3]).astype(t))
+ @test_util.run_deprecated_v1
def testFloatTypes(self):
for t in [np.float16, np.float32, np.float64]:
self._testAll(
np.random.rand(4, 3, 3).astype(t), np.random.rand(3).astype(t))
+ @test_util.run_deprecated_v1
def test4DFloatTypes(self):
for t in [np.float16, np.float32, np.float64]:
self._testAll(
np.random.rand(4, 3, 2, 3).astype(t),
np.random.rand(3).astype(t))
+ @test_util.run_deprecated_v1
def test5DFloatTypes(self):
for t in [np.float16, np.float32, np.float64]:
self._testAll(
@@ -187,6 +195,7 @@ class BiasAddTest(test.TestCase):
self.assertAllClose(bias_jacob_t, bias_jacob_n, threshold, threshold)
self.assertAllClose(grad_jacob_t, grad_jacob_n, threshold, threshold)
+ @test_util.run_deprecated_v1
def testGradientTensor(self):
# TODO(yongtang): BiasAddGrad with NCHW only works 4D. Reenable once
# all dimensions are supported.
@@ -198,6 +207,7 @@ class BiasAddTest(test.TestCase):
bias = np.array([1.3, 2.4], dtype=dtype.as_numpy_dtype)
self._testGradient(np_input, bias, dtype, data_format, use_gpu)
+ @test_util.run_deprecated_v1
def testGradientTensor4D(self):
# BiasAddGrad with NCHW support 4D so all are enabled.
for (data_format, use_gpu) in [("NHWC", False), ("NHWC", True),
@@ -209,11 +219,13 @@ class BiasAddTest(test.TestCase):
bias = np.array([1.3, 2.4], dtype=dtype.as_numpy_dtype)
self._testGradient(np_input, bias, dtype, data_format, use_gpu)
+ @test_util.run_deprecated_v1
def testEmpty(self):
np.random.seed(7)
for shape in (0, 0), (2, 0), (0, 2), (4, 3, 0), (4, 0, 3), (0, 4, 3):
self._testAll(np.random.randn(*shape), np.random.randn(shape[-1]))
+ @test_util.run_deprecated_v1
def testEmptyGradient(self):
# TODO(yongtang): BiasAddGrad with NCHW only works 4D. Reenable once
# all dimensions are supported.
diff --git a/tensorflow/python/kernel_tests/bincount_op_test.py b/tensorflow/python/kernel_tests/bincount_op_test.py
index 49eb835847e..d064d736cf2 100644
--- a/tensorflow/python/kernel_tests/bincount_op_test.py
+++ b/tensorflow/python/kernel_tests/bincount_op_test.py
@@ -30,6 +30,7 @@ from tensorflow.python.platform import googletest
class BincountTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def test_empty(self):
with self.session(use_gpu=True):
self.assertAllEqual(
@@ -43,6 +44,7 @@ class BincountTest(test_util.TensorFlowTestCase):
math_ops.bincount([], minlength=3, dtype=np.float64).eval().dtype,
np.float64)
+ @test_util.run_deprecated_v1
def test_values(self):
with self.session(use_gpu=True):
self.assertAllEqual(
@@ -58,12 +60,14 @@ class BincountTest(test_util.TensorFlowTestCase):
self.assertAllEqual(
math_ops.bincount(np.arange(10000)).eval(), np.ones(10000))
+ @test_util.run_deprecated_v1
def test_maxlength(self):
with self.session(use_gpu=True):
self.assertAllEqual(math_ops.bincount([5], maxlength=3).eval(), [0, 0, 0])
self.assertAllEqual(math_ops.bincount([1], maxlength=3).eval(), [0, 1])
self.assertAllEqual(math_ops.bincount([], maxlength=3).eval(), [])
+ @test_util.run_deprecated_v1
def test_random_with_weights(self):
num_samples = 10000
with self.session(use_gpu=True):
@@ -77,6 +81,7 @@ class BincountTest(test_util.TensorFlowTestCase):
self.assertAllClose(
math_ops.bincount(arr, weights).eval(), np.bincount(arr, weights))
+ @test_util.run_deprecated_v1
def test_random_without_weights(self):
num_samples = 10000
with self.session(use_gpu=True):
@@ -87,6 +92,7 @@ class BincountTest(test_util.TensorFlowTestCase):
self.assertAllClose(
math_ops.bincount(arr, None).eval(), np.bincount(arr, weights))
+ @test_util.run_deprecated_v1
def test_zero_weights(self):
with self.session(use_gpu=True):
self.assertAllEqual(
@@ -99,6 +105,7 @@ class BincountTest(test_util.TensorFlowTestCase):
with self.assertRaises(errors.InvalidArgumentError):
math_ops.bincount([1, 2, 3, -1, 6, 8]).eval()
+ @test_util.run_deprecated_v1
def test_shape_function(self):
# size must be scalar.
with self.assertRaisesRegexp(
diff --git a/tensorflow/python/kernel_tests/bitcast_op_test.py b/tensorflow/python/kernel_tests/bitcast_op_test.py
index 5ceffcfeda3..b4f9a21a899 100644
--- a/tensorflow/python/kernel_tests/bitcast_op_test.py
+++ b/tensorflow/python/kernel_tests/bitcast_op_test.py
@@ -60,6 +60,7 @@ class BitcastTest(test.TestCase):
shape = [3, 4]
self._testBitcast(x, dtypes.int64, shape)
+ @test_util.run_deprecated_v1
def testErrors(self):
x = np.zeros([1, 1], np.int8)
datatype = dtypes.int32
@@ -72,6 +73,7 @@ class BitcastTest(test.TestCase):
shape = [4]
self._testBitcast(x, datatype, shape)
+ @test_util.run_deprecated_v1
def testUnknown(self):
x = array_ops.placeholder(dtypes.float32)
datatype = dtypes.int8
diff --git a/tensorflow/python/kernel_tests/boosted_trees/prediction_ops_test.py b/tensorflow/python/kernel_tests/boosted_trees/prediction_ops_test.py
index 7cdc67f83f0..6b04e8abf40 100644
--- a/tensorflow/python/kernel_tests/boosted_trees/prediction_ops_test.py
+++ b/tensorflow/python/kernel_tests/boosted_trees/prediction_ops_test.py
@@ -28,6 +28,7 @@ from tensorflow.python.platform import googletest
class TrainingPredictionOpsTest(test_util.TensorFlowTestCase):
"""Tests prediction ops for training."""
+ @test_util.run_deprecated_v1
def testCachedPredictionOnEmptyEnsemble(self):
"""Tests that prediction on a dummy ensemble does not fail."""
with self.cached_session() as session:
@@ -61,6 +62,7 @@ class TrainingPredictionOpsTest(test_util.TensorFlowTestCase):
self.assertAllClose(cached_node_ids, new_node_ids)
self.assertAllClose([[0], [0]], logits_updates)
+ @test_util.run_deprecated_v1
def testNoCachedPredictionButTreeExists(self):
"""Tests that predictions are updated once trees are added."""
with self.cached_session() as session:
@@ -127,6 +129,7 @@ class TrainingPredictionOpsTest(test_util.TensorFlowTestCase):
self.assertAllClose([2, 1], new_node_ids)
self.assertAllClose([[0.1 * 8.79], [0.1 * 1.14]], logits_updates)
+ @test_util.run_deprecated_v1
def testCachedPredictionIsCurrent(self):
"""Tests that prediction based on previous node in the tree works."""
with self.cached_session() as session:
@@ -199,6 +202,7 @@ class TrainingPredictionOpsTest(test_util.TensorFlowTestCase):
self.assertAllClose(cached_node_ids, new_node_ids)
self.assertAllClose([[0], [0]], logits_updates)
+ @test_util.run_deprecated_v1
def testCachedPredictionFromTheSameTree(self):
"""Tests that prediction based on previous node in the tree works."""
with self.cached_session() as session:
@@ -313,6 +317,7 @@ class TrainingPredictionOpsTest(test_util.TensorFlowTestCase):
# 1.65 and -3.875, and then multiply them by 0.1 (lr)
self.assertAllClose([[0.1 * 1.65], [0.1 * -3.875]], logits_updates)
+ @test_util.run_deprecated_v1
def testCachedPredictionFromPreviousTree(self):
"""Tests the predictions work when we have cache from previous trees."""
with self.cached_session() as session:
@@ -445,6 +450,7 @@ class TrainingPredictionOpsTest(test_util.TensorFlowTestCase):
# change= 0.1(1.14+7.0-7.0)
self.assertAllClose([[1], [0.114]], logits_updates)
+ @test_util.run_deprecated_v1
def testCategoricalSplits(self):
"""Tests the training prediction work for categorical splits."""
with self.cached_session() as session:
@@ -517,6 +523,7 @@ class TrainingPredictionOpsTest(test_util.TensorFlowTestCase):
self.assertAllClose([3, 4, 2], new_node_ids)
self.assertAllClose([[5.], [6.], [7.]], logits_updates)
+ @test_util.run_deprecated_v1
def testCachedPredictionFromTheSameTreeWithPostPrunedNodes(self):
"""Tests that prediction based on previous node in the tree works."""
with self.cached_session() as session:
@@ -647,6 +654,7 @@ class TrainingPredictionOpsTest(test_util.TensorFlowTestCase):
self.assertAllClose([[0.01], [0.01], [0.0553], [0.0783], [0.01], [0.01]],
logits_updates + cached_values)
+ @test_util.run_deprecated_v1
def testCachedPredictionFromThePreviousTreeWithPostPrunedNodes(self):
"""Tests that prediction based on previous node in the tree works."""
with self.cached_session() as session:
@@ -792,6 +800,7 @@ class TrainingPredictionOpsTest(test_util.TensorFlowTestCase):
[root + 0.0783], [root + 0.01], [root + 0.01]],
logits_updates + cached_values)
+ @test_util.run_deprecated_v1
def testCachedPredictionTheWholeTreeWasPruned(self):
"""Tests that prediction based on previous node in the tree works."""
with self.cached_session() as session:
@@ -864,6 +873,7 @@ class TrainingPredictionOpsTest(test_util.TensorFlowTestCase):
class PredictionOpsTest(test_util.TensorFlowTestCase):
"""Tests prediction ops for inference."""
+ @test_util.run_deprecated_v1
def testPredictionOnEmptyEnsemble(self):
"""Tests that prediction on a empty ensemble does not fail."""
with self.cached_session() as session:
@@ -886,6 +896,7 @@ class PredictionOpsTest(test_util.TensorFlowTestCase):
logits = session.run(predict_op)
self.assertAllClose(expected_logits, logits)
+ @test_util.run_deprecated_v1
def testPredictionMultipleTree(self):
"""Tests the predictions work when we have multiple trees."""
with self.cached_session() as session:
@@ -996,6 +1007,7 @@ class PredictionOpsTest(test_util.TensorFlowTestCase):
logits = session.run(predict_op)
self.assertAllClose(expected_logits, logits)
+ @test_util.run_deprecated_v1
def testCategoricalSplits(self):
"""Tests the predictions work for categorical splits."""
with self.cached_session() as session:
@@ -1062,6 +1074,7 @@ class PredictionOpsTest(test_util.TensorFlowTestCase):
class FeatureContribsOpsTest(test_util.TensorFlowTestCase):
"""Tests feature contribs ops for model understanding."""
+ @test_util.run_deprecated_v1
def testContribsForOnlyABiasNode(self):
"""Tests case when, after training, only left with a bias node.
@@ -1122,6 +1135,7 @@ class FeatureContribsOpsTest(test_util.TensorFlowTestCase):
self.assertAllClose(feature_ids, expected_feature_ids)
self.assertAllClose(logits_paths, expected_logits_paths)
+ @test_util.run_deprecated_v1
def testContribsMultipleTreeWhenFirstTreeIsABiasNode(self):
"""Tests case when, after training, first tree contains only a bias node."""
with self.cached_session() as session:
@@ -1219,6 +1233,7 @@ class FeatureContribsOpsTest(test_util.TensorFlowTestCase):
self.assertAllClose(feature_ids, expected_feature_ids)
self.assertAllClose(logits_paths, expected_logits_paths)
+ @test_util.run_deprecated_v1
def testContribsMultipleTree(self):
"""Tests that the contribs work when we have multiple trees."""
with self.cached_session() as session:
diff --git a/tensorflow/python/kernel_tests/boosted_trees/quantile_ops_test.py b/tensorflow/python/kernel_tests/boosted_trees/quantile_ops_test.py
index 1a7b1a7e90e..390672febeb 100644
--- a/tensorflow/python/kernel_tests/boosted_trees/quantile_ops_test.py
+++ b/tensorflow/python/kernel_tests/boosted_trees/quantile_ops_test.py
@@ -82,6 +82,7 @@ class QuantileOpsTest(test_util.TensorFlowTestCase):
self.max_elements = 1 << 16
self.num_quantiles = constant_op.constant(3, dtype=dtypes.int64)
+ @test_util.run_deprecated_v1
def testBasicQuantileBucketsSingleResource(self):
with self.cached_session() as sess:
quantile_accumulator_handle = self.create_resource("floats", self.eps,
@@ -106,6 +107,7 @@ class QuantileOpsTest(test_util.TensorFlowTestCase):
self.assertAllClose(self._feature_0_quantiles, quantiles[0].eval())
self.assertAllClose(self._feature_1_quantiles, quantiles[1].eval())
+ @test_util.run_deprecated_v1
def testBasicQuantileBucketsMultipleResources(self):
with self.cached_session() as sess:
quantile_accumulator_handle_0 = self.create_resource("float_0", self.eps,
@@ -140,6 +142,7 @@ class QuantileOpsTest(test_util.TensorFlowTestCase):
self.assertAllClose(self._feature_0_quantiles, quantiles[0].eval())
self.assertAllClose(self._feature_1_quantiles, quantiles[1].eval())
+ @test_util.run_deprecated_v1
def testSaveRestoreAfterFlush(self):
save_dir = os.path.join(self.get_temp_dir(), "save_restore")
save_path = os.path.join(tempfile.mkdtemp(prefix=save_dir), "hash")
@@ -172,6 +175,7 @@ class QuantileOpsTest(test_util.TensorFlowTestCase):
self.assertAllClose(self._feature_0_boundaries, buckets[0].eval())
self.assertAllClose(self._feature_1_boundaries, buckets[1].eval())
+ @test_util.run_deprecated_v1
def testSaveRestoreBeforeFlush(self):
save_dir = os.path.join(self.get_temp_dir(), "save_restore")
save_path = os.path.join(tempfile.mkdtemp(prefix=save_dir), "hash")
diff --git a/tensorflow/python/kernel_tests/boosted_trees/resource_ops_test.py b/tensorflow/python/kernel_tests/boosted_trees/resource_ops_test.py
index 493cad80f3c..0a34277bbdb 100644
--- a/tensorflow/python/kernel_tests/boosted_trees/resource_ops_test.py
+++ b/tensorflow/python/kernel_tests/boosted_trees/resource_ops_test.py
@@ -30,6 +30,7 @@ from tensorflow.python.platform import googletest
class ResourceOpsTest(test_util.TensorFlowTestCase):
"""Tests resource_ops."""
+ @test_util.run_deprecated_v1
def testCreate(self):
with self.cached_session():
ensemble = boosted_trees_ops.TreeEnsemble('ensemble')
@@ -43,6 +44,7 @@ class ResourceOpsTest(test_util.TensorFlowTestCase):
self.assertEqual(0, self.evaluate(num_attempted_layers))
self.assertAllEqual([0, 1], self.evaluate(nodes_range))
+ @test_util.run_deprecated_v1
def testCreateWithProto(self):
with self.cached_session():
ensemble_proto = boosted_trees_pb2.TreeEnsemble()
@@ -160,6 +162,7 @@ class ResourceOpsTest(test_util.TensorFlowTestCase):
self.assertEqual(6, self.evaluate(num_attempted_layers))
self.assertAllEqual([16, 19], self.evaluate(nodes_range))
+ @test_util.run_deprecated_v1
def testSerializeDeserialize(self):
with self.cached_session():
# Initialize.
diff --git a/tensorflow/python/kernel_tests/boosted_trees/stats_ops_test.py b/tensorflow/python/kernel_tests/boosted_trees/stats_ops_test.py
index e1036b0b754..e2e23486b5a 100644
--- a/tensorflow/python/kernel_tests/boosted_trees/stats_ops_test.py
+++ b/tensorflow/python/kernel_tests/boosted_trees/stats_ops_test.py
@@ -327,6 +327,7 @@ class StatsOpsTest(test_util.TensorFlowTestCase):
max_splits=max_splits)
self.assertAllEqual([[], []], self.evaluate(node_ids_list))
+ @test_util.run_deprecated_v1
def testMakeStatsSummarySimple(self):
"""Simple test for MakeStatsSummary."""
with self.cached_session():
diff --git a/tensorflow/python/kernel_tests/boosted_trees/training_ops_test.py b/tensorflow/python/kernel_tests/boosted_trees/training_ops_test.py
index ea022820e44..afc0564fc5a 100644
--- a/tensorflow/python/kernel_tests/boosted_trees/training_ops_test.py
+++ b/tensorflow/python/kernel_tests/boosted_trees/training_ops_test.py
@@ -30,6 +30,7 @@ from tensorflow.python.platform import googletest
class UpdateTreeEnsembleOpTest(test_util.TensorFlowTestCase):
"""Tests for growing tree ensemble from split candidates."""
+ @test_util.run_deprecated_v1
def testGrowWithEmptyEnsemble(self):
"""Test growing an empty ensemble."""
with self.cached_session() as session:
@@ -139,6 +140,7 @@ class UpdateTreeEnsembleOpTest(test_util.TensorFlowTestCase):
self.assertEqual(new_stamp, 1)
self.assertProtoEquals(expected_result, tree_ensemble)
+ @test_util.run_deprecated_v1
def testBiasCenteringOnEmptyEnsemble(self):
"""Test growing with bias centering on an empty ensemble."""
with self.cached_session() as session:
@@ -182,6 +184,7 @@ class UpdateTreeEnsembleOpTest(test_util.TensorFlowTestCase):
self.assertEqual(new_stamp, 1)
self.assertProtoEquals(expected_result, tree_ensemble)
+ @test_util.run_deprecated_v1
def testGrowExistingEnsembleTreeNotFinalized(self):
"""Test growing an existing ensemble with the last tree not finalized."""
with self.cached_session() as session:
@@ -366,6 +369,7 @@ class UpdateTreeEnsembleOpTest(test_util.TensorFlowTestCase):
self.assertEqual(new_stamp, 1)
self.assertProtoEquals(expected_result, tree_ensemble)
+ @test_util.run_deprecated_v1
def testGrowExistingEnsembleTreeFinalized(self):
"""Test growing an existing ensemble with the last tree finalized."""
with self.cached_session() as session:
@@ -515,6 +519,7 @@ class UpdateTreeEnsembleOpTest(test_util.TensorFlowTestCase):
self.assertEqual(new_stamp, 1)
self.assertProtoEquals(expected_result, tree_ensemble)
+ @test_util.run_deprecated_v1
def testPrePruning(self):
"""Test growing an existing ensemble with pre-pruning."""
with self.cached_session() as session:
@@ -671,6 +676,7 @@ class UpdateTreeEnsembleOpTest(test_util.TensorFlowTestCase):
self.assertEqual(new_stamp, 1)
self.assertProtoEquals(expected_result, tree_ensemble)
+ @test_util.run_deprecated_v1
def testMetadataWhenCantSplitDueToEmptySplits(self):
"""Test that the metadata is updated even though we can't split."""
with self.cached_session() as session:
@@ -782,6 +788,7 @@ class UpdateTreeEnsembleOpTest(test_util.TensorFlowTestCase):
self.assertEqual(new_stamp, 1)
self.assertProtoEquals(expected_result, tree_ensemble)
+ @test_util.run_deprecated_v1
def testMetadataWhenCantSplitDuePrePruning(self):
"""Test metadata is updated correctly when no split due to prepruning."""
with self.cached_session() as session:
@@ -917,6 +924,7 @@ class UpdateTreeEnsembleOpTest(test_util.TensorFlowTestCase):
self.assertEqual(new_stamp, 1)
self.assertProtoEquals(expected_result, tree_ensemble)
+ @test_util.run_deprecated_v1
def testPostPruningOfSomeNodes(self):
"""Test growing an ensemble with post-pruning."""
with self.cached_session() as session:
@@ -1251,6 +1259,7 @@ class UpdateTreeEnsembleOpTest(test_util.TensorFlowTestCase):
self.assertEqual(new_stamp, 3)
self.assertProtoEquals(expected_result, res_ensemble)
+ @test_util.run_deprecated_v1
def testPostPruningOfAllNodes(self):
"""Test growing an ensemble with post-pruning, with all nodes are pruned."""
with self.cached_session() as session:
@@ -1434,6 +1443,7 @@ class UpdateTreeEnsembleOpTest(test_util.TensorFlowTestCase):
}
""", res_ensemble)
+ @test_util.run_deprecated_v1
def testPostPruningChangesNothing(self):
"""Test growing an ensemble with post-pruning with all gains >0."""
with self.cached_session() as session:
diff --git a/tensorflow/python/kernel_tests/broadcast_to_ops_test.py b/tensorflow/python/kernel_tests/broadcast_to_ops_test.py
index 233c1664052..b9eb2391b49 100644
--- a/tensorflow/python/kernel_tests/broadcast_to_ops_test.py
+++ b/tensorflow/python/kernel_tests/broadcast_to_ops_test.py
@@ -29,6 +29,7 @@ from tensorflow.python.platform import test as test_lib
class BroadcastToTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testBroadcastToBasic(self):
for dtype in [np.uint8, np.uint16, np.int8, np.int16, np.int32, np.int64]:
with self.session(use_gpu=True):
@@ -37,6 +38,7 @@ class BroadcastToTest(test_util.TensorFlowTestCase):
v_np = np.broadcast_to(x, [3, 3])
self.assertAllEqual(v_tf.eval(), v_np)
+ @test_util.run_deprecated_v1
def testBroadcastToString(self):
with self.session(use_gpu=True):
x = np.array([b"1", b"2", b"3"])
@@ -44,6 +46,7 @@ class BroadcastToTest(test_util.TensorFlowTestCase):
v_np = np.broadcast_to(x, [3, 3])
self.assertAllEqual(v_tf.eval(), v_np)
+ @test_util.run_deprecated_v1
def testBroadcastToBool(self):
with self.session(use_gpu=True):
x = np.array([True, False, True], dtype=np.bool)
@@ -51,6 +54,7 @@ class BroadcastToTest(test_util.TensorFlowTestCase):
v_np = np.broadcast_to(x, [3, 3])
self.assertAllEqual(v_tf.eval(), v_np)
+ @test_util.run_deprecated_v1
def testBroadcastToShape(self):
for input_dim in range(1, 6):
for output_dim in range(input_dim, 6):
@@ -62,6 +66,7 @@ class BroadcastToTest(test_util.TensorFlowTestCase):
v_np = np.broadcast_to(x, output_shape)
self.assertAllEqual(v_tf.eval(), v_np)
+ @test_util.run_deprecated_v1
def testBroadcastToScalar(self):
with self.session(use_gpu=True):
x = np.array(1, dtype=np.int32)
@@ -69,6 +74,7 @@ class BroadcastToTest(test_util.TensorFlowTestCase):
v_np = np.broadcast_to(x, [3, 3])
self.assertAllEqual(v_tf.eval(), v_np)
+ @test_util.run_deprecated_v1
def testBroadcastScalarToNonScalar(self):
with self.session(use_gpu=True):
x = np.array(1.0, dtype=np.float)
@@ -76,6 +82,7 @@ class BroadcastToTest(test_util.TensorFlowTestCase):
v_np = np.broadcast_to(x, [2, 3, 4])
self.assertAllEqual(v_tf.eval(), v_np)
+ @test_util.run_deprecated_v1
def testBroadcastToShapeTypeAndInference(self):
for dtype in [dtypes.int32, dtypes.int64]:
with self.cached_session(use_gpu=True):
@@ -89,6 +96,7 @@ class BroadcastToTest(test_util.TensorFlowTestCase):
# check shape inference when shape input is constant
self.assertAllEqual(shape, v_np.shape)
+ @test_util.run_deprecated_v1
def testGradientForScalar(self):
x = constant_op.constant(1, dtype=dtypes.float32)
v = array_ops.broadcast_to(x, [2, 4, 3])
@@ -98,6 +106,7 @@ class BroadcastToTest(test_util.TensorFlowTestCase):
out.get_shape())
self.assertLess(err, 1e-4)
+ @test_util.run_deprecated_v1
def testGradientWithSameRank(self):
x = constant_op.constant(np.reshape(np.arange(6), (2, 1, 3)),
dtype=dtypes.float32)
@@ -108,6 +117,7 @@ class BroadcastToTest(test_util.TensorFlowTestCase):
out, out.get_shape())
self.assertLess(err, 1e-4)
+ @test_util.run_deprecated_v1
def testGradientWithIncreasingRank(self):
x = constant_op.constant([[1], [2]],
dtype=dtypes.float32)
@@ -118,6 +128,7 @@ class BroadcastToTest(test_util.TensorFlowTestCase):
out, out.get_shape())
self.assertLess(err, 1e-4)
+ @test_util.run_deprecated_v1
def testGradientWithBroadcastAllDimensions(self):
x = constant_op.constant([[1, 2, 3], [4, 5, 6]], dtype=dtypes.float32)
v = array_ops.broadcast_to(x, [5, 4, 6])
diff --git a/tensorflow/python/kernel_tests/bucketize_op_test.py b/tensorflow/python/kernel_tests/bucketize_op_test.py
index f40ca825270..95df6943705 100644
--- a/tensorflow/python/kernel_tests/bucketize_op_test.py
+++ b/tensorflow/python/kernel_tests/bucketize_op_test.py
@@ -20,6 +20,7 @@ from __future__ import print_function
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import errors_impl
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import math_ops
from tensorflow.python.platform import test
@@ -50,6 +51,7 @@ class BucketizationOpTest(test.TestCase):
with self.session(use_gpu=True) as sess:
self.assertAllEqual(expected_out, self.evaluate(op))
+ @test_util.run_deprecated_v1
def testInvalidBoundariesOrder(self):
op = math_ops._bucketize(
constant_op.constant([-5, 0]), boundaries=[0, 8, 3, 11])
diff --git a/tensorflow/python/kernel_tests/candidate_sampler_ops_test.py b/tensorflow/python/kernel_tests/candidate_sampler_ops_test.py
index 031accee553..fa6eb5c9689 100644
--- a/tensorflow/python/kernel_tests/candidate_sampler_ops_test.py
+++ b/tensorflow/python/kernel_tests/candidate_sampler_ops_test.py
@@ -22,6 +22,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import candidate_sampling_ops
from tensorflow.python.ops import math_ops
@@ -37,6 +38,7 @@ class RangeSamplerOpsTest(test.TestCase):
TRUE_LABELS = [[1, 2], [0, 4], [3, 3]]
+ @test_util.run_deprecated_v1
def testTrueCandidates(self):
with self.cached_session() as sess:
indices = constant_op.constant([0, 0, 1, 1, 2, 2])
@@ -106,6 +108,7 @@ class RangeSamplerOpsTest(test.TestCase):
self.assertTrue(id_ in self.TRUE_LABELS[index])
self.assertLess(weight, -1.0e37)
+ @test_util.run_deprecated_v1
def testSeed(self):
def draw(seed):
diff --git a/tensorflow/python/kernel_tests/cast_op_test.py b/tensorflow/python/kernel_tests/cast_op_test.py
index 2cfe084d957..b3187e16371 100644
--- a/tensorflow/python/kernel_tests/cast_op_test.py
+++ b/tensorflow/python/kernel_tests/cast_op_test.py
@@ -25,6 +25,7 @@ import platform
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import sparse_tensor
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import math_ops
@@ -90,10 +91,12 @@ class CastOpTest(test.TestCase):
if x.dtype == np.float32 or x.dtype == np.float64:
self._testTypes(x, use_gpu=True)
+ @test_util.run_deprecated_v1
def testBasic(self):
self._testAll(np.arange(-10, 10).reshape(2, 10))
self._testAll(np.linspace(-10, 10, 17))
+ @test_util.run_deprecated_v1
def testSmallValues(self):
f4 = np.finfo(np.float32)
f8 = np.finfo(np.float64)
@@ -112,6 +115,7 @@ class CastOpTest(test.TestCase):
b = math_ops.cast(math_ops.cast(a, dtypes.bfloat16), dtypes.float32)
self.assertAllClose(a, self.evaluate(b), rtol=1 / 128.)
+ @test_util.run_deprecated_v1
def testRandom(self):
self._testAll(np.random.normal(0, 10, 210).reshape([2, 3, 5, 7]))
self._testAll(np.random.normal(0, 1e6, 210).reshape([2, 3, 5, 7]))
@@ -124,6 +128,7 @@ class CastOpTest(test.TestCase):
self._cast(
x, dst_dtype, use_gpu=use_gpu), dst_dtype(expected))
+ @test_util.run_deprecated_v1
def testIntToFloatBoundary(self):
i4 = np.iinfo(np.int32)
i8 = np.iinfo(np.int64)
@@ -138,6 +143,7 @@ class CastOpTest(test.TestCase):
self._compare(i8.max, np.float64, i8.max, False)
# NOTE: GPU does not support int32/int64 for casting.
+ @test_util.run_deprecated_v1
def testInfNan(self):
i4 = np.iinfo(np.int32)
i8 = np.iinfo(np.int64)
@@ -181,6 +187,7 @@ class CastOpTest(test.TestCase):
def testNotImplemented(self):
self._OpError(np.arange(0, 10), dtypes.string, "Cast.*int64.*string.*")
+ @test_util.run_deprecated_v1
def testCastToTypeOfVariable(self):
with self.cached_session() as sess:
x = variables.Variable(5, dtype=dtypes.float32)
@@ -189,6 +196,7 @@ class CastOpTest(test.TestCase):
variables.global_variables_initializer().run()
self.assertEqual(1.0, self.evaluate(cast))
+ @test_util.run_deprecated_v1
def testGradients(self):
t = [dtypes.float32, dtypes.float64, dtypes.complex64, dtypes.complex128]
for src_t in t:
@@ -203,6 +211,7 @@ class CastOpTest(test.TestCase):
class SparseTensorCastTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testCast(self):
indices = constant_op.constant([[0], [1], [2]], dtypes.int64)
values = constant_op.constant(np.array([1, 2, 3], np.int64))
diff --git a/tensorflow/python/kernel_tests/check_ops_test.py b/tensorflow/python/kernel_tests/check_ops_test.py
index 15124a19a27..95bac85027b 100644
--- a/tensorflow/python/kernel_tests/check_ops_test.py
+++ b/tensorflow/python/kernel_tests/check_ops_test.py
@@ -173,6 +173,7 @@ class AssertEqualTest(test.TestCase):
assert x is None
@test_util.run_in_graph_and_eager_modes
+ @test_util.run_deprecated_v1
def test_raises_when_greater(self):
# Static check
static_small = constant_op.constant([1, 2], name="small")
@@ -180,6 +181,7 @@ class AssertEqualTest(test.TestCase):
with self.assertRaisesRegexp(errors.InvalidArgumentError, "fail"):
check_ops.assert_equal(static_big, static_small, message="fail")
+ @test_util.run_deprecated_v1
def test_raises_when_greater_dynamic(self):
with self.cached_session():
small = array_ops.placeholder(dtypes.int32, name="small")
@@ -251,6 +253,7 @@ First 2 elements of y:
summarize=2)
@test_util.run_in_graph_and_eager_modes
+ @test_util.run_deprecated_v1
def test_raises_when_less(self):
# Static check
static_small = constant_op.constant([3, 1], name="small")
@@ -258,6 +261,7 @@ First 2 elements of y:
with self.assertRaisesRegexp(errors.InvalidArgumentError, "fail"):
check_ops.assert_equal(static_big, static_small, message="fail")
+ @test_util.run_deprecated_v1
def test_raises_when_less_dynamic(self):
with self.cached_session():
small = array_ops.placeholder(dtypes.int32, name="small")
@@ -317,6 +321,7 @@ class AssertNoneEqualTest(test.TestCase):
self.evaluate(out)
@test_util.run_in_graph_and_eager_modes
+ @test_util.run_deprecated_v1
def test_raises_when_equal(self):
small = constant_op.constant([3, 1], name="small")
with self.assertRaisesOpError("x != y did not hold"):
@@ -506,6 +511,7 @@ class AssertAllCloseTest(test.TestCase):
class AssertLessTest(test.TestCase):
@test_util.run_in_graph_and_eager_modes
+ @test_util.run_deprecated_v1
def test_raises_when_equal(self):
small = constant_op.constant([1, 2], name="small")
with self.assertRaisesOpError("failure message.*\n*.* x < y did not hold"):
@@ -516,6 +522,7 @@ class AssertLessTest(test.TestCase):
self.evaluate(out)
@test_util.run_in_graph_and_eager_modes
+ @test_util.run_deprecated_v1
def test_raises_when_greater(self):
small = constant_op.constant([1, 2], name="small")
big = constant_op.constant([3, 4], name="big")
@@ -582,6 +589,7 @@ class AssertLessEqualTest(test.TestCase):
self.evaluate(out)
@test_util.run_in_graph_and_eager_modes
+ @test_util.run_deprecated_v1
def test_raises_when_greater(self):
small = constant_op.constant([1, 2], name="small")
big = constant_op.constant([3, 4], name="big")
@@ -637,6 +645,7 @@ class AssertLessEqualTest(test.TestCase):
class AssertGreaterTest(test.TestCase):
@test_util.run_in_graph_and_eager_modes
+ @test_util.run_deprecated_v1
def test_raises_when_equal(self):
small = constant_op.constant([1, 2], name="small")
with self.assertRaisesOpError("fail"):
@@ -647,6 +656,7 @@ class AssertGreaterTest(test.TestCase):
self.evaluate(out)
@test_util.run_in_graph_and_eager_modes
+ @test_util.run_deprecated_v1
def test_raises_when_less(self):
small = constant_op.constant([1, 2], name="small")
big = constant_op.constant([3, 4], name="big")
@@ -706,6 +716,7 @@ class AssertGreaterEqualTest(test.TestCase):
self.evaluate(out)
@test_util.run_in_graph_and_eager_modes
+ @test_util.run_deprecated_v1
def test_raises_when_less(self):
small = constant_op.constant([1, 2], name="small")
big = constant_op.constant([3, 4], name="big")
@@ -770,6 +781,7 @@ class AssertNegativeTest(test.TestCase):
self.evaluate(out)
@test_util.run_in_graph_and_eager_modes
+ @test_util.run_deprecated_v1
def test_raises_when_positive(self):
doug = constant_op.constant([1, 2], name="doug")
with self.assertRaisesOpError("fail"):
@@ -780,6 +792,7 @@ class AssertNegativeTest(test.TestCase):
self.evaluate(out)
@test_util.run_in_graph_and_eager_modes
+ @test_util.run_deprecated_v1
def test_raises_when_zero(self):
claire = constant_op.constant([0], name="claire")
with self.assertRaisesOpError("x < 0 did not hold"):
@@ -802,6 +815,7 @@ class AssertNegativeTest(test.TestCase):
class AssertPositiveTest(test.TestCase):
@test_util.run_in_graph_and_eager_modes
+ @test_util.run_deprecated_v1
def test_raises_when_negative(self):
freddie = constant_op.constant([-1, -2], name="freddie")
with self.assertRaisesOpError("fail"):
@@ -819,6 +833,7 @@ class AssertPositiveTest(test.TestCase):
self.evaluate(out)
@test_util.run_in_graph_and_eager_modes
+ @test_util.run_deprecated_v1
def test_raises_when_zero(self):
meechum = constant_op.constant([0], name="meechum")
with self.assertRaisesOpError("x > 0 did not hold"):
@@ -841,26 +856,31 @@ class AssertPositiveTest(test.TestCase):
class EnsureShapeTest(test.TestCase):
# Static shape inference
+ @test_util.run_deprecated_v1
def testStaticShape(self):
placeholder = array_ops.placeholder(dtypes.int32)
ensure_shape_op = check_ops.ensure_shape(placeholder, (3, 3, 3))
self.assertEqual(ensure_shape_op.get_shape(), (3, 3, 3))
+ @test_util.run_deprecated_v1
def testStaticShape_MergesShapes(self):
placeholder = array_ops.placeholder(dtypes.int32, shape=(None, None, 3))
ensure_shape_op = check_ops.ensure_shape(placeholder, (5, 4, None))
self.assertEqual(ensure_shape_op.get_shape(), (5, 4, 3))
+ @test_util.run_deprecated_v1
def testStaticShape_RaisesErrorWhenRankIncompatible(self):
placeholder = array_ops.placeholder(dtypes.int32, shape=(None, None, 3))
with self.assertRaises(ValueError):
check_ops.ensure_shape(placeholder, (2, 3))
+ @test_util.run_deprecated_v1
def testStaticShape_RaisesErrorWhenDimIncompatible(self):
placeholder = array_ops.placeholder(dtypes.int32, shape=(None, None, 3))
with self.assertRaises(ValueError):
check_ops.ensure_shape(placeholder, (2, 2, 4))
+ @test_util.run_deprecated_v1
def testStaticShape_CanSetUnknownShape(self):
placeholder = array_ops.placeholder(dtypes.int32)
derived = placeholder / 3
@@ -868,6 +888,7 @@ class EnsureShapeTest(test.TestCase):
self.assertEqual(ensure_shape_op.get_shape(), None)
# Dynamic shape check
+ @test_util.run_deprecated_v1
def testEnsuresDynamicShape_RaisesError(self):
placeholder = array_ops.placeholder(dtypes.int32)
derived = math_ops.divide(placeholder, 3, name="MyDivide")
@@ -880,6 +901,7 @@ class EnsureShapeTest(test.TestCase):
r"expected shape \[3,3,3\]."):
sess.run(derived, feed_dict={placeholder: feed_val})
+ @test_util.run_deprecated_v1
def testEnsuresDynamicShape_RaisesErrorDimUnknown(self):
placeholder = array_ops.placeholder(dtypes.int32)
derived = placeholder / 3
@@ -892,6 +914,7 @@ class EnsureShapeTest(test.TestCase):
r"expected shape \[\?,\?,3\]."):
sess.run(derived, feed_dict={placeholder: feed_val})
+ @test_util.run_deprecated_v1
def testEnsuresDynamicShape(self):
placeholder = array_ops.placeholder(dtypes.int32)
derived = placeholder / 3
@@ -900,6 +923,7 @@ class EnsureShapeTest(test.TestCase):
with self.cached_session() as sess:
sess.run(derived, feed_dict={placeholder: feed_val})
+ @test_util.run_deprecated_v1
def testEnsuresDynamicShape_WithUnknownDims(self):
placeholder = array_ops.placeholder(dtypes.int32)
derived = placeholder / 3
@@ -908,6 +932,7 @@ class EnsureShapeTest(test.TestCase):
with self.cached_session() as sess:
sess.run(derived, feed_dict={placeholder: feed_val})
+ @test_util.run_deprecated_v1
def testGradient(self):
placeholder = array_ops.placeholder(dtypes.float32)
derived = check_ops.ensure_shape(placeholder, (None, None))
@@ -1003,6 +1028,7 @@ class AssertRankTest(test.TestCase):
tensor, desired_rank, message="fail")]):
self.evaluate(array_ops.identity(tensor))
+ @test_util.run_deprecated_v1
def test_rank_zero_tensor_raises_if_rank_too_small_dynamic_rank(self):
with self.cached_session():
tensor = array_ops.placeholder(dtypes.float32, name="my_tensor")
@@ -1021,6 +1047,7 @@ class AssertRankTest(test.TestCase):
[check_ops.assert_rank(tensor, desired_rank)]):
self.evaluate(array_ops.identity(tensor))
+ @test_util.run_deprecated_v1
def test_rank_zero_tensor_doesnt_raise_if_rank_just_right_dynamic_rank(self):
with self.cached_session():
tensor = array_ops.placeholder(dtypes.float32, name="my_tensor")
@@ -1038,6 +1065,7 @@ class AssertRankTest(test.TestCase):
[check_ops.assert_rank(tensor, desired_rank)]):
self.evaluate(array_ops.identity(tensor))
+ @test_util.run_deprecated_v1
def test_rank_one_tensor_raises_if_rank_too_large_dynamic_rank(self):
with self.cached_session():
tensor = array_ops.placeholder(dtypes.float32, name="my_tensor")
@@ -1055,6 +1083,7 @@ class AssertRankTest(test.TestCase):
[check_ops.assert_rank(tensor, desired_rank)]):
self.evaluate(array_ops.identity(tensor))
+ @test_util.run_deprecated_v1
def test_rank_one_tensor_doesnt_raise_if_rank_just_right_dynamic_rank(self):
with self.cached_session():
tensor = array_ops.placeholder(dtypes.float32, name="my_tensor")
@@ -1072,6 +1101,7 @@ class AssertRankTest(test.TestCase):
[check_ops.assert_rank(tensor, desired_rank)]):
self.evaluate(array_ops.identity(tensor))
+ @test_util.run_deprecated_v1
def test_rank_one_tensor_raises_if_rank_too_small_dynamic_rank(self):
with self.cached_session():
tensor = array_ops.placeholder(dtypes.float32, name="my_tensor")
@@ -1087,6 +1117,7 @@ class AssertRankTest(test.TestCase):
with self.assertRaisesRegexp(ValueError, "Rank must be a scalar"):
check_ops.assert_rank(tensor, np.array([], dtype=np.int32))
+ @test_util.run_deprecated_v1
def test_raises_if_rank_is_not_scalar_dynamic(self):
with self.cached_session():
tensor = constant_op.constant(
@@ -1104,6 +1135,7 @@ class AssertRankTest(test.TestCase):
"must be of type <dtype: 'int32'>"):
check_ops.assert_rank(tensor, .5)
+ @test_util.run_deprecated_v1
def test_raises_if_rank_is_not_integer_dynamic(self):
with self.cached_session():
tensor = constant_op.constant(
@@ -1127,6 +1159,7 @@ class AssertRankInTest(test.TestCase):
check_ops.assert_rank_in(tensor_rank0, (1, 2), message="fail")]):
self.evaluate(array_ops.identity(tensor_rank0))
+ @test_util.run_deprecated_v1
def test_rank_zero_tensor_raises_if_rank_mismatch_dynamic_rank(self):
with self.cached_session():
tensor_rank0 = array_ops.placeholder(dtypes.float32, name="my_tensor")
@@ -1143,6 +1176,7 @@ class AssertRankInTest(test.TestCase):
check_ops.assert_rank_in(tensor_rank0, desired_ranks)]):
self.evaluate(array_ops.identity(tensor_rank0))
+ @test_util.run_deprecated_v1
def test_rank_zero_tensor_doesnt_raise_if_rank_matches_dynamic_rank(self):
with self.cached_session():
tensor_rank0 = array_ops.placeholder(dtypes.float32, name="my_tensor")
@@ -1159,6 +1193,7 @@ class AssertRankInTest(test.TestCase):
check_ops.assert_rank_in(tensor_rank1, desired_ranks)]):
self.evaluate(array_ops.identity(tensor_rank1))
+ @test_util.run_deprecated_v1
def test_rank_one_tensor_doesnt_raise_if_rank_matches_dynamic_rank(self):
with self.cached_session():
tensor_rank1 = array_ops.placeholder(dtypes.float32, name="my_tensor")
@@ -1177,6 +1212,7 @@ class AssertRankInTest(test.TestCase):
check_ops.assert_rank_in(tensor_rank1, (0, 2))]):
self.evaluate(array_ops.identity(tensor_rank1))
+ @test_util.run_deprecated_v1
def test_rank_one_tensor_raises_if_rank_mismatches_dynamic_rank(self):
with self.cached_session():
tensor_rank1 = array_ops.placeholder(dtypes.float32, name="my_tensor")
@@ -1196,6 +1232,7 @@ class AssertRankInTest(test.TestCase):
with self.assertRaisesRegexp(ValueError, "Rank must be a scalar"):
check_ops.assert_rank_in(tensor, desired_ranks)
+ @test_util.run_deprecated_v1
def test_raises_if_rank_is_not_scalar_dynamic(self):
with self.cached_session():
tensor = constant_op.constant(
@@ -1218,6 +1255,7 @@ class AssertRankInTest(test.TestCase):
"must be of type <dtype: 'int32'>"):
check_ops.assert_rank_in(tensor, (1, .5,))
+ @test_util.run_deprecated_v1
def test_raises_if_rank_is_not_integer_dynamic(self):
with self.cached_session():
tensor = constant_op.constant(
@@ -1241,6 +1279,7 @@ class AssertRankAtLeastTest(test.TestCase):
[check_ops.assert_rank_at_least(tensor, desired_rank)]):
self.evaluate(array_ops.identity(tensor))
+ @test_util.run_deprecated_v1
def test_rank_zero_tensor_raises_if_rank_too_small_dynamic_rank(self):
with self.cached_session():
tensor = array_ops.placeholder(dtypes.float32, name="my_tensor")
@@ -1258,6 +1297,7 @@ class AssertRankAtLeastTest(test.TestCase):
[check_ops.assert_rank_at_least(tensor, desired_rank)]):
self.evaluate(array_ops.identity(tensor))
+ @test_util.run_deprecated_v1
def test_rank_zero_tensor_doesnt_raise_if_rank_just_right_dynamic_rank(self):
with self.cached_session():
tensor = array_ops.placeholder(dtypes.float32, name="my_tensor")
@@ -1274,6 +1314,7 @@ class AssertRankAtLeastTest(test.TestCase):
[check_ops.assert_rank_at_least(tensor, desired_rank)]):
self.evaluate(array_ops.identity(tensor))
+ @test_util.run_deprecated_v1
def test_rank_one_ten_doesnt_raise_if_rank_too_large_dynamic_rank(self):
with self.cached_session():
tensor = array_ops.placeholder(dtypes.float32, name="my_tensor")
@@ -1290,6 +1331,7 @@ class AssertRankAtLeastTest(test.TestCase):
[check_ops.assert_rank_at_least(tensor, desired_rank)]):
self.evaluate(array_ops.identity(tensor))
+ @test_util.run_deprecated_v1
def test_rank_one_tensor_doesnt_raise_if_rank_just_right_dynamic_rank(self):
with self.cached_session():
tensor = array_ops.placeholder(dtypes.float32, name="my_tensor")
@@ -1307,6 +1349,7 @@ class AssertRankAtLeastTest(test.TestCase):
[check_ops.assert_rank_at_least(tensor, desired_rank)]):
self.evaluate(array_ops.identity(tensor))
+ @test_util.run_deprecated_v1
def test_rank_one_tensor_raises_if_rank_too_small_dynamic_rank(self):
with self.cached_session():
tensor = array_ops.placeholder(dtypes.float32, name="my_tensor")
@@ -1320,6 +1363,7 @@ class AssertRankAtLeastTest(test.TestCase):
class AssertNonNegativeTest(test.TestCase):
@test_util.run_in_graph_and_eager_modes
+ @test_util.run_deprecated_v1
def test_raises_when_negative(self):
zoe = constant_op.constant([-1, -2], name="zoe")
with self.assertRaisesOpError("x >= 0 did not hold"):
@@ -1356,6 +1400,7 @@ class AssertNonPositiveTest(test.TestCase):
self.evaluate(out)
@test_util.run_in_graph_and_eager_modes
+ @test_util.run_deprecated_v1
def test_raises_when_positive(self):
rachel = constant_op.constant([0, 2], name="rachel")
with self.assertRaisesOpError("x <= 0 did not hold"):
diff --git a/tensorflow/python/kernel_tests/checkpoint_ops_test.py b/tensorflow/python/kernel_tests/checkpoint_ops_test.py
index 213ac292d3e..b8c8c9edb5a 100644
--- a/tensorflow/python/kernel_tests/checkpoint_ops_test.py
+++ b/tensorflow/python/kernel_tests/checkpoint_ops_test.py
@@ -24,6 +24,7 @@ from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import gen_checkpoint_ops
from tensorflow.python.ops import partitioned_variables
from tensorflow.python.ops import variable_scope
@@ -48,6 +49,7 @@ class GenerateVocabRemappingTest(test.TestCase):
with open(self.old_vocab_file, 'w') as f:
f.write('\n'.join(['knitting', 'eminem', 'MISSING']) + '\n')
+ @test_util.run_deprecated_v1
def test_generate_remapping_with_no_vocab_changes(self):
"""Tests where vocab does not change at all."""
remapping, num_present = gen_checkpoint_ops.generate_vocab_remapping(
@@ -368,6 +370,7 @@ class LoadAndRemapMatrixWithMaxRowsTest(test.TestCase):
np.reshape(initializing_values, (new_rows, num_cols)),
self.evaluate(remapped_matrix))
+ @test_util.run_deprecated_v1
def test_loading_rows_divisible_by_max_rows(self):
"""Tests loading normal var when rows are evenly divisible by max_rows."""
self._test_loading_variable_with_max_rows(
@@ -376,6 +379,7 @@ class LoadAndRemapMatrixWithMaxRowsTest(test.TestCase):
# 9 is evenly divisible by 3.
max_rows_in_memory=3)
+ @test_util.run_deprecated_v1
def test_loading_rows_not_divisible_by_max_rows(self):
"""Tests loading normal var when rows aren't divisible by max_rows."""
self._test_loading_variable_with_max_rows(
@@ -384,6 +388,7 @@ class LoadAndRemapMatrixWithMaxRowsTest(test.TestCase):
# 9 is not evenly divisible by 4.
max_rows_in_memory=4)
+ @test_util.run_deprecated_v1
def test_loading_rows_less_than_max_rows(self):
"""Tests loading normal var as a single slice.
@@ -395,6 +400,7 @@ class LoadAndRemapMatrixWithMaxRowsTest(test.TestCase):
# 10 > 9.
max_rows_in_memory=10)
+ @test_util.run_deprecated_v1
def test_loading_no_max_rows(self):
"""Tests loading normal var as a single slice with no valid max_rows."""
self._test_loading_variable_with_max_rows(
@@ -402,6 +408,7 @@ class LoadAndRemapMatrixWithMaxRowsTest(test.TestCase):
partitioner=None,
max_rows_in_memory=-1)
+ @test_util.run_deprecated_v1
def test_loading_partitions_equals_max_rows(self):
"""Tests loading partitioned var sliced on partition boundary."""
self._test_loading_variable_with_max_rows(
@@ -411,6 +418,7 @@ class LoadAndRemapMatrixWithMaxRowsTest(test.TestCase):
# exactly 3 rows.
max_rows_in_memory=3)
+ @test_util.run_deprecated_v1
def test_loading_partitions_greater_than_max_rows(self):
"""Tests loading partitioned var with more slices than partitions."""
self._test_loading_variable_with_max_rows(
@@ -420,6 +428,7 @@ class LoadAndRemapMatrixWithMaxRowsTest(test.TestCase):
# row at a time.
max_rows_in_memory=1)
+ @test_util.run_deprecated_v1
def test_loading_partitions_less_than_max_rows(self):
"""Tests loading partitioned var as a single slice.
@@ -430,6 +439,7 @@ class LoadAndRemapMatrixWithMaxRowsTest(test.TestCase):
partitioner=partitioned_variables.fixed_size_partitioner(3),
max_rows_in_memory=10)
+ @test_util.run_deprecated_v1
def test_loading_partitions_no_max_rows(self):
"""Tests loading partitioned var as single slice with no valid max_rows."""
self._test_loading_variable_with_max_rows(
diff --git a/tensorflow/python/kernel_tests/cholesky_op_test.py b/tensorflow/python/kernel_tests/cholesky_op_test.py
index 1a509a43d1f..f3947236b1f 100644
--- a/tensorflow/python/kernel_tests/cholesky_op_test.py
+++ b/tensorflow/python/kernel_tests/cholesky_op_test.py
@@ -26,6 +26,7 @@ from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes as dtypes_lib
from tensorflow.python.framework import errors_impl
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import control_flow_ops
from tensorflow.python.ops import gen_linalg_ops
@@ -145,6 +146,7 @@ class CholeskyOpTest(test.TestCase):
matrices[i] = np.dot(matrices[i].T.conj(), matrices[i])
self._verifyCholesky(matrices)
+ @test_util.run_deprecated_v1
def testNonSquareMatrix(self):
with self.assertRaises(ValueError):
linalg_ops.cholesky(np.array([[1., 2., 3.], [3., 4., 5.]]))
@@ -175,6 +177,7 @@ class CholeskyOpTest(test.TestCase):
self._verifyCholesky(np.empty([0, 2, 2]))
self._verifyCholesky(np.empty([2, 0, 0]))
+ @test_util.run_deprecated_v1
def testConcurrentExecutesWithoutError(self):
with self.session(use_gpu=True) as sess:
matrix1 = random_ops.random_normal([5, 5], seed=42)
@@ -193,18 +196,21 @@ class CholeskyGradTest(test.TestCase):
def getShapes(self, shapeList):
return ((elem, int(np.floor(1.2 * elem))) for elem in shapeList)
+ @test_util.run_deprecated_v1
def testSmallMatrices(self):
np.random.seed(0)
shapes = self.getShapes([1, 2, 10])
self.runFiniteDifferences(
shapes, dtypes=(dtypes_lib.float32, dtypes_lib.float64))
+ @test_util.run_deprecated_v1
def testSmallMatricesComplex(self):
np.random.seed(0)
shapes = self.getShapes([1, 2, 10])
self.runFiniteDifferences(
shapes, dtypes=(dtypes_lib.complex64, dtypes_lib.complex128))
+ @test_util.run_deprecated_v1
def testOneBlockMatrices(self):
np.random.seed(0)
shapes = self.getShapes([self._backprop_block_size + 1])
@@ -213,12 +219,14 @@ class CholeskyGradTest(test.TestCase):
dtypes=(dtypes_lib.float32, dtypes_lib.float64),
scalarTest=True)
+ @test_util.run_deprecated_v1
def testTwoBlockMatrixFloat(self):
np.random.seed(0)
shapes = self.getShapes([2 * self._backprop_block_size + 1])
self.runFiniteDifferences(
shapes, dtypes=(dtypes_lib.float32,), scalarTest=True)
+ @test_util.run_deprecated_v1
def testTwoBlockMatrixDouble(self):
np.random.seed(0)
shapes = self.getShapes([2 * self._backprop_block_size + 1])
@@ -231,6 +239,7 @@ class CholeskyGradTest(test.TestCase):
self.runFiniteDifferences(
shapes, dtypes=(dtypes_lib.complex64,), scalarTest=True)
+ @test_util.run_deprecated_v1
def testTwoBlockMatrixComplexDouble(self):
np.random.seed(0)
shapes = self.getShapes([2 * self._backprop_block_size + 1])
diff --git a/tensorflow/python/kernel_tests/clip_ops_test.py b/tensorflow/python/kernel_tests/clip_ops_test.py
index 5f1b6b6917a..45f1e6152a2 100644
--- a/tensorflow/python/kernel_tests/clip_ops_test.py
+++ b/tensorflow/python/kernel_tests/clip_ops_test.py
@@ -24,6 +24,7 @@ from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import clip_ops
from tensorflow.python.ops import gradient_checker
@@ -166,6 +167,7 @@ class ClipTest(test.TestCase):
self.assertAllClose(np_ans, tf_ans)
self.assertAllClose(np_ans, tf_ans_tensor)
+ @test_util.run_deprecated_v1
def testClipByNormGradientZeros(self):
with self.session(use_gpu=True):
x = array_ops.zeros([3])
@@ -242,6 +244,7 @@ class ClipTest(test.TestCase):
self.assertAllClose(np_ans, tf_ans)
# ClipByGlobalNorm tests
+ @test_util.run_deprecated_v1
def testClipByGlobalNormClipped(self):
# Norm clipping when clip_norm < 5
with self.session(use_gpu=True):
@@ -263,6 +266,7 @@ class ClipTest(test.TestCase):
self.assertAllClose(np_ans_0, tf_ans_1)
self.assertAllClose(np_ans_1, tf_ans_2)
+ @test_util.run_deprecated_v1
def testClipByGlobalNormClippedTensor(self):
# Norm clipping when clip_norm < 5
with self.session(use_gpu=True):
@@ -284,6 +288,7 @@ class ClipTest(test.TestCase):
self.assertAllClose(np_ans_0, tf_ans_1)
self.assertAllClose(np_ans_1, tf_ans_2)
+ @test_util.run_deprecated_v1
def testClipByGlobalNormSupportsNone(self):
# Norm clipping when clip_norm < 5
with self.session(use_gpu=True):
@@ -307,6 +312,7 @@ class ClipTest(test.TestCase):
self.assertAllClose(np_ans_0, tf_ans_1)
self.assertAllClose(np_ans_1, tf_ans_2)
+ @test_util.run_deprecated_v1
def testClipByGlobalNormWithIndexedSlicesClipped(self):
# Norm clipping when clip_norm < 5
with self.session(use_gpu=True):
@@ -340,6 +346,7 @@ class ClipTest(test.TestCase):
self.assertEqual(dense_shape, slices.dense_shape)
self.assertEqual(dense_shape, modified_slices.dense_shape)
+ @test_util.run_deprecated_v1
def testClipByGlobalNormNotClipped(self):
# No norm clipping when clip_norm >= 5
with self.session(use_gpu=True):
@@ -359,6 +366,7 @@ class ClipTest(test.TestCase):
self.assertAllClose(np_ans_0, tf_ans_1)
self.assertAllClose(np_ans_1, tf_ans_2)
+ @test_util.run_deprecated_v1
def testClipByGlobalNormZero(self):
# No norm clipping when norm = 0
with self.session(use_gpu=True):
@@ -378,6 +386,7 @@ class ClipTest(test.TestCase):
self.assertAllClose(np_ans_0, tf_ans_1)
self.assertAllClose(np_ans_1, tf_ans_2)
+ @test_util.run_deprecated_v1
def testClipByGlobalNormInf(self):
with self.session(use_gpu=True):
x0 = constant_op.constant([-2.0, 0.0, np.inf, 4.0, 0.0, 0.0],
@@ -456,6 +465,7 @@ class ClipTest(test.TestCase):
clip_by_norm_ans = self.evaluate(without_norm)
self.assertAllClose(clip_by_average_norm_ans, clip_by_norm_ans)
+ @test_util.run_deprecated_v1
def testClipByValueEmptyTensor(self):
# Test case for GitHub issue 19337
zero = array_ops.placeholder(dtype=dtypes.float32, shape=None)
diff --git a/tensorflow/python/kernel_tests/concat_op_test.py b/tensorflow/python/kernel_tests/concat_op_test.py
index 27137f76bd1..474760a93ff 100644
--- a/tensorflow/python/kernel_tests/concat_op_test.py
+++ b/tensorflow/python/kernel_tests/concat_op_test.py
@@ -35,6 +35,7 @@ from tensorflow.python.platform import test
class ConcatOpTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testHStack(self):
with self.session(use_gpu=True):
p1 = array_ops.placeholder(dtypes.float32, shape=[4, 4])
@@ -50,6 +51,7 @@ class ConcatOpTest(test.TestCase):
self.assertAllEqual(result[:4, :], params[p1])
self.assertAllEqual(result[4:, :], params[p2])
+ @test_util.run_deprecated_v1
def testVStack(self):
with self.session(use_gpu=True):
p1 = array_ops.placeholder(dtypes.float32, shape=[4, 4])
@@ -138,6 +140,7 @@ class ConcatOpTest(test.TestCase):
else:
self.assertAllClose(result[ind], params[p[i]], 0.01)
+ @test_util.run_deprecated_v1
def testRandom(self):
self._testRandom(dtypes.bool)
self._testRandom(dtypes.float32)
@@ -148,6 +151,7 @@ class ConcatOpTest(test.TestCase):
self._testRandom(dtypes.complex64)
self._testRandom(dtypes.complex128)
+ @test_util.run_deprecated_v1
def testInvalidConcatDimTypeAndShape(self):
a = variables.Variable(constant_op.constant(1.0, shape=[1]))
b = variables.Variable(constant_op.constant(2.0, shape=[1]))
@@ -199,10 +203,12 @@ class ConcatOpTest(test.TestCase):
result = self.evaluate(concated_grad)
self.assertAllEqual(result, grad_inp)
+ @test_util.run_deprecated_v1
def testGradientsSimple(self):
self._testGradientsSimple(dtypes.float32)
self._testGradientsSimple(dtypes.complex64)
+ @test_util.run_deprecated_v1
def testGradientsFirstDim(self):
with test_util.use_gpu():
inp = []
@@ -227,6 +233,7 @@ class ConcatOpTest(test.TestCase):
self.assertAllEqual(result, grad_inp)
+ @test_util.run_deprecated_v1
def testGradientsLastDim(self):
# Test both positive and negative concat axis.
# -1 and 2 correspond to the same axis for 3-dimensional tensors.
@@ -284,10 +291,12 @@ class ConcatOpTest(test.TestCase):
self.assertAllEqual(result, grad_inp)
+ @test_util.run_deprecated_v1
def testGradientsRandom(self):
for _ in range(5):
self._RunAndVerifyGradientsRandom()
+ @test_util.run_deprecated_v1
def testGradientWithUnknownInputDim(self):
with self.session(use_gpu=True):
x = array_ops.placeholder(dtypes.float32)
@@ -309,6 +318,7 @@ class ConcatOpTest(test.TestCase):
self.assertAllEqual(result, grad_inp)
+ @test_util.run_deprecated_v1
def testShapeError(self):
# Rank doesn't match.
with self.assertRaises(ValueError):
@@ -338,6 +348,7 @@ class ConcatOpTest(test.TestCase):
constant_op.constant(20.0, shape=[4, 4, 4])
], -4)
+ @test_util.run_deprecated_v1
def testShapeWithUnknownConcatDim(self):
p1 = array_ops.placeholder(dtypes.float32)
c1 = constant_op.constant(10.0, shape=[4, 4, 4, 4])
@@ -356,6 +367,7 @@ class ConcatOpTest(test.TestCase):
with self.assertRaises(ValueError):
array_ops.concat([p1, c1, p2, c3], dim)
+ @test_util.run_deprecated_v1
def testZeroSize(self):
# Verify that concat doesn't crash and burn for zero size inputs
np.random.seed(7)
@@ -377,6 +389,7 @@ class ConcatOpTest(test.TestCase):
dxs = self.evaluate(gradients_impl.gradients(c, xs, dc))
self.assertAllEqual(dc, np.concatenate(dxs, axis=axis))
+ @test_util.run_deprecated_v1
def testTensorConcatDim0Grad(self):
x_shapes = [[20, 7, 3], [10, 7, 3], [14, 7, 3]]
output_shape = [44, 7, 3]
@@ -391,6 +404,7 @@ class ConcatOpTest(test.TestCase):
output_shape)
self.assertLess(err, 1e-11)
+ @test_util.run_deprecated_v1
def testTensorConcatDim1Grad(self):
x_shapes = [[20, 7, 3], [20, 3, 3], [20, 1, 3]]
output_shape = [20, 11, 3]
@@ -405,6 +419,7 @@ class ConcatOpTest(test.TestCase):
output_shape)
self.assertLess(err, 1e-11)
+ @test_util.run_deprecated_v1
def testIndexedSlicesConcatDim0Grad(self):
x_shapes = [[20, 7, 3], [10, 7, 3], [14, 7, 3]]
output_shape = [4, 7, 3]
@@ -420,6 +435,7 @@ class ConcatOpTest(test.TestCase):
output_shape)
self.assertLess(err, 1e-11)
+ @test_util.run_deprecated_v1
def testIndexedSlicesConcatDim1Grad(self):
x_shapes = [[20, 7, 3], [20, 3, 3], [20, 1, 3]]
output_shape = [4, 11, 3]
@@ -435,6 +451,7 @@ class ConcatOpTest(test.TestCase):
output_shape)
self.assertLess(err, 1e-11)
+ @test_util.run_deprecated_v1
def testIndexedSlicesConcatDim2Grad(self):
x_shapes = [[20, 7, 3], [20, 7, 1], [20, 7, 2]]
output_shape = [4, 7, 6]
@@ -450,6 +467,7 @@ class ConcatOpTest(test.TestCase):
output_shape)
self.assertLess(err, 1e-11)
+ @test_util.run_deprecated_v1
def testIndexedSlicesConcatDim1Grad_UnknownInputDim(self):
x_shapes = [[20, 7, 3], [20, 3, 3], [20, 1, 3]]
output_shape = [4, 11, 3]
@@ -479,6 +497,7 @@ class ConcatOpTest(test.TestCase):
self.assertAllEqual(
self.evaluate(concat_list_t), self.evaluate(concat_tuple_t))
+ @test_util.run_deprecated_v1
def testConcatNoScalars(self):
scalar = constant_op.constant(7)
dim = array_ops.placeholder(dtypes.int32)
@@ -488,6 +507,7 @@ class ConcatOpTest(test.TestCase):
# important as gpu implementation could fail if
# shared memory is not large for all the inputs
+ @test_util.run_deprecated_v1
def testConcatLargeNumberOfTensors(self):
with self.session(use_gpu=True):
for concat_dim in range(2):
@@ -529,6 +549,7 @@ class ConcatOpTest(test.TestCase):
output = gen_array_ops.concat_v2([t1, t2], 0)
self.assertFalse(self.evaluate(output)) # Checks that output is empty
+ @test_util.run_deprecated_v1
def testConcatInvalidAxis(self):
with self.assertRaises(ValueError):
with test_util.use_gpu():
@@ -578,6 +599,7 @@ class ConcatOpTest(test.TestCase):
result = concated_grad.eval(feed_dict=feed_dict)
self.assertAllEqual(result, grad_inp)
+ @test_util.run_deprecated_v1
def testGradientsNegativeAxis(self):
x1 = [[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]]
x2 = [[7.0, 8.0, 9.0], [10.0, 11.0, 12.0]]
@@ -630,6 +652,7 @@ class ConcatOffsetTest(test.TestCase):
ans = self.evaluate(off)
self.assertAllEqual(ans, [[0, 0, 0], [0, 3, 0], [0, 10, 0]])
+ @test_util.run_deprecated_v1
def testNotVector(self):
cdim = constant_op.constant(1, dtypes.int32)
s0 = constant_op.constant([[2, 3, 5]], dtypes.int32)
@@ -639,6 +662,7 @@ class ConcatOffsetTest(test.TestCase):
r"should be a vector"):
self.evaluate(off)
+ @test_util.run_deprecated_v1
def testConcatDimOutOfRange(self):
cdim = constant_op.constant(4, dtypes.int32)
s0 = constant_op.constant([2, 3, 5], dtypes.int32)
@@ -648,6 +672,7 @@ class ConcatOffsetTest(test.TestCase):
r"Concat dim is out of range: 4 vs. 3"):
self.evaluate(off)
+ @test_util.run_deprecated_v1
def testDimMismatch(self):
cdim = constant_op.constant(1, dtypes.int32)
s0 = constant_op.constant([2, 3, 5], dtypes.int32)
@@ -657,6 +682,7 @@ class ConcatOffsetTest(test.TestCase):
r"should contain 3 elem"):
self.evaluate(off)
+ @test_util.run_deprecated_v1
def testSizeMismatch(self):
cdim = constant_op.constant(1, dtypes.int32)
s0 = constant_op.constant([2, 3, 5], dtypes.int32)
diff --git a/tensorflow/python/kernel_tests/cond_v2_test.py b/tensorflow/python/kernel_tests/cond_v2_test.py
index 4baa8b02124..1f4b37ce2a4 100644
--- a/tensorflow/python/kernel_tests/cond_v2_test.py
+++ b/tensorflow/python/kernel_tests/cond_v2_test.py
@@ -68,6 +68,7 @@ class CondV2Test(test.TestCase):
self.assertEqual(expected_val, actual_val)
self.assertEqual(expected_grad_val, actual_grad_val)
+ @test_util.run_deprecated_v1
def testBasic(self):
x = constant_op.constant(1.0, name="x")
y = constant_op.constant(2.0, name="y")
@@ -82,6 +83,7 @@ class CondV2Test(test.TestCase):
self._testCond(true_fn, false_fn, [x, y])
self._testCond(true_fn, false_fn, [y])
+ @test_util.run_deprecated_v1
def testMultipleOutputs(self):
x = constant_op.constant(1.0, name="x")
y = constant_op.constant(3.0, name="y")
@@ -96,6 +98,7 @@ class CondV2Test(test.TestCase):
self._testCond(true_fn, false_fn, [x, y])
self._testCond(true_fn, false_fn, [y])
+ @test_util.run_deprecated_v1
def testBasic2(self):
x = constant_op.constant(1.0, name="x")
y = constant_op.constant(2.0, name="y")
@@ -110,6 +113,7 @@ class CondV2Test(test.TestCase):
self._testCond(true_fn, false_fn, [x, y])
self._testCond(true_fn, false_fn, [y])
+ @test_util.run_deprecated_v1
def testNoInputs(self):
with self.cached_session() as sess:
pred = array_ops.placeholder(dtypes.bool, name="pred")
@@ -540,6 +544,7 @@ class CondV2Test(test.TestCase):
pred_inner: False
}), [5., 0.])
+ @test_util.run_deprecated_v1
def testSecondDerivative(self):
with self.cached_session() as sess:
pred = array_ops.placeholder(dtypes.bool, name="pred")
@@ -636,6 +641,7 @@ class CondV2Test(test.TestCase):
self.assertFalse(if_found,
"An `If` op was found, but it should be lowered.")
+ @test_util.run_deprecated_v1
def testLoweringDisabledInXLA(self):
with self.session(graph=ops.Graph()) as sess:
# Build the cond_v2 in an XLA context
@@ -668,6 +674,7 @@ class CondV2Test(test.TestCase):
if_found,
"An `If` op was not found, but the graph should not be lowered.")
+ @test_util.run_deprecated_v1
def testLoweringDisabledWithSingleThreadedExecutorContext(self):
with self.session(graph=ops.Graph()) as sess:
@function.defun
@@ -702,6 +709,7 @@ class CondV2Test(test.TestCase):
self.assertEqual(self.evaluate(output[1]), 9.)
@test_util.enable_control_flow_v2
+ @test_util.run_deprecated_v1
def testRaisesOutputStructuresMismatch(self):
x = constant_op.constant(1.0, name="x")
y = constant_op.constant(3.0, name="y")
diff --git a/tensorflow/python/kernel_tests/conditional_accumulator_test.py b/tensorflow/python/kernel_tests/conditional_accumulator_test.py
index 7ee1a4bc327..5847e4639bb 100644
--- a/tensorflow/python/kernel_tests/conditional_accumulator_test.py
+++ b/tensorflow/python/kernel_tests/conditional_accumulator_test.py
@@ -26,6 +26,7 @@ from tensorflow.python.framework import dtypes as dtypes_lib
from tensorflow.python.framework import errors_impl
from tensorflow.python.framework import ops
from tensorflow.python.framework import tensor_shape
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import data_flow_ops
from tensorflow.python.ops import math_ops
@@ -79,11 +80,13 @@ class ConditionalAccumulatorTest(test.TestCase):
attr { key: 'reduction_type' value {s: 'MEAN'} }
""", q.accumulator_ref.op.node_def)
+ @test_util.run_deprecated_v1
def testAccumulatorSizeEmpty(self):
with self.cached_session():
q = data_flow_ops.ConditionalAccumulator(dtypes_lib.float32, name="Q")
self.assertEqual(q.num_accumulated().eval(), 0)
+ @test_util.run_deprecated_v1
def testAccumulatorSetGlobalStep(self):
with self.cached_session():
q = data_flow_ops.ConditionalAccumulator(
@@ -91,6 +94,7 @@ class ConditionalAccumulatorTest(test.TestCase):
set_global_step_op = q.set_global_step(1)
set_global_step_op.run()
+ @test_util.run_deprecated_v1
def testAccumulatorApplyGradFloat32(self):
with self.cached_session():
q = data_flow_ops.ConditionalAccumulator(
@@ -98,6 +102,7 @@ class ConditionalAccumulatorTest(test.TestCase):
accum_op = q.apply_grad((10.0,))
accum_op.run()
+ @test_util.run_deprecated_v1
def testDtypes(self):
with self.cached_session() as sess:
dtypes = [dtypes_lib.float16, dtypes_lib.float32, dtypes_lib.float64]
@@ -115,6 +120,7 @@ class ConditionalAccumulatorTest(test.TestCase):
self.assertEqual(sum(elems) / len(elems), result)
+ @test_util.run_deprecated_v1
def testAccumulatorMultipleAccumulators(self):
with self.cached_session():
q_f32_0 = data_flow_ops.ConditionalAccumulator(
@@ -134,6 +140,7 @@ class ConditionalAccumulatorTest(test.TestCase):
result = accums[i].take_grad(1).eval()
self.assertEqual(result, i + 10.0)
+ @test_util.run_deprecated_v1
def testAccumulatorApplyAndTakeGradWithShape(self):
with self.cached_session():
q = data_flow_ops.ConditionalAccumulator(
@@ -155,6 +162,7 @@ class ConditionalAccumulatorTest(test.TestCase):
is_all_equal &= (val[i][j] == elems_ave[i][j])
self.assertTrue(is_all_equal)
+ @test_util.run_deprecated_v1
def testAccumulatorApplyGradWithWrongShape(self):
q = data_flow_ops.ConditionalAccumulator(
dtypes_lib.float32, name="Q", shape=(3, 2))
@@ -165,6 +173,7 @@ class ConditionalAccumulatorTest(test.TestCase):
with self.assertRaises(ValueError):
q.apply_grad([[1.0], [2.0], [3.0]])
+ @test_util.run_deprecated_v1
def testAccumulatorDynamicShape(self):
with self.cached_session() as sess:
q = data_flow_ops.ConditionalAccumulator(
@@ -190,6 +199,7 @@ class ConditionalAccumulatorTest(test.TestCase):
is_all_equal &= (val[i][j] == elems_ave[i][j])
self.assertTrue(is_all_equal)
+ @test_util.run_deprecated_v1
def testAccumulatorWrongDynamicShape(self):
with self.cached_session() as sess:
q = data_flow_ops.ConditionalAccumulator(
@@ -208,6 +218,7 @@ class ConditionalAccumulatorTest(test.TestCase):
with self.assertRaises(errors_impl.InvalidArgumentError):
sess.run(accum_op, feed_dict={x: [[1.0], [2.0], [3.0]]})
+ @test_util.run_deprecated_v1
def testAccumulatorSizeAfterApplyGrad(self):
with self.cached_session():
q = data_flow_ops.ConditionalAccumulator(
@@ -219,6 +230,7 @@ class ConditionalAccumulatorTest(test.TestCase):
accum_op.run()
self.assertEqual(q.num_accumulated().eval(), 2)
+ @test_util.run_deprecated_v1
def testAccumulatorSizeAfterApplyGradAndTakeGrad(self):
with self.cached_session():
q = data_flow_ops.ConditionalAccumulator(
@@ -247,6 +259,7 @@ class ConditionalAccumulatorTest(test.TestCase):
extract_t.op.run()
self.assertEqual(q.num_accumulated().eval(), 0)
+ @test_util.run_deprecated_v1
def testAccumulatorTakeGradMean(self):
with self.cached_session():
q = data_flow_ops.ConditionalAccumulator(
@@ -271,6 +284,7 @@ class ConditionalAccumulatorTest(test.TestCase):
val = self.evaluate(takeg_t)
self.assertEqual(15.0, val)
+ @test_util.run_deprecated_v1
def testAccumulatorTakeGradSum(self):
with self.cached_session():
q = data_flow_ops.ConditionalAccumulator(
@@ -298,6 +312,7 @@ class ConditionalAccumulatorTest(test.TestCase):
val = self.evaluate(takeg_t)
self.assertEqual(30.0, val)
+ @test_util.run_deprecated_v1
def testAccumulatorTakeGradInvalidReductionType(self):
with self.assertRaises(ValueError):
data_flow_ops.ConditionalAccumulator(
@@ -306,6 +321,7 @@ class ConditionalAccumulatorTest(test.TestCase):
shape=tensor_shape.TensorShape([1]),
reduction_type="Invalid")
+ @test_util.run_deprecated_v1
def testAccumulatorInvalidTakeGrad(self):
with self.cached_session():
q = data_flow_ops.ConditionalAccumulator(
@@ -321,6 +337,7 @@ class ConditionalAccumulatorTest(test.TestCase):
with self.assertRaises(errors_impl.InvalidArgumentError):
self.evaluate(takeg_t)
+ @test_util.run_deprecated_v1
def testAccumulatorRepeatedTakeGradMean(self):
with self.cached_session():
q = data_flow_ops.ConditionalAccumulator(
@@ -348,6 +365,7 @@ class ConditionalAccumulatorTest(test.TestCase):
val = self.evaluate(takeg_t)
self.assertEqual(elems_ave + 0.0, val)
+ @test_util.run_deprecated_v1
def testAccumulatorRepeatedTakeGradSum(self):
with self.cached_session():
q = data_flow_ops.ConditionalAccumulator(
@@ -378,6 +396,7 @@ class ConditionalAccumulatorTest(test.TestCase):
val = self.evaluate(takeg_t)
self.assertEqual(elems_sum, val)
+ @test_util.run_deprecated_v1
def testAccumulatorIncrementGlobalStep(self):
with self.cached_session():
q = data_flow_ops.ConditionalAccumulator(
@@ -394,6 +413,7 @@ class ConditionalAccumulatorTest(test.TestCase):
set_global_step_op.run()
self.evaluate(inc_global_step)
+ @test_util.run_deprecated_v1
def testAccumulatorSetGlobalStepPreventsAccumulation(self):
with self.cached_session():
q = data_flow_ops.ConditionalAccumulator(
@@ -415,6 +435,7 @@ class ConditionalAccumulatorTest(test.TestCase):
if x >= ls) / sum(1 for x in local_steps
if x >= ls), val)
+ @test_util.run_deprecated_v1
def testParallelApplyGrad(self):
with self.cached_session() as sess:
q = data_flow_ops.ConditionalAccumulator(
@@ -440,6 +461,7 @@ class ConditionalAccumulatorTest(test.TestCase):
self.assertEqual(val, sum(elems) / len(elems))
+ @test_util.run_deprecated_v1
def testParallelTakeGrad(self):
with self.cached_session() as sess:
q = data_flow_ops.ConditionalAccumulator(
@@ -472,6 +494,7 @@ class ConditionalAccumulatorTest(test.TestCase):
self.assertItemsEqual(elems, results)
+ @test_util.run_deprecated_v1
def testAccumulatorApplyAndBlockingTake(self):
with self.cached_session() as sess:
q = data_flow_ops.ConditionalAccumulator(
@@ -505,6 +528,7 @@ class ConditionalAccumulatorTest(test.TestCase):
with self.assertRaisesOpError("was cancelled"):
self.evaluate(takeg_op)
+ @test_util.run_deprecated_v1
def testAccumulatorCancel(self):
with self.cached_session() as sess:
q = data_flow_ops.ConditionalAccumulator(
diff --git a/tensorflow/python/kernel_tests/confusion_matrix_test.py b/tensorflow/python/kernel_tests/confusion_matrix_test.py
index b001341c03d..ae13c8e32e5 100644
--- a/tensorflow/python/kernel_tests/confusion_matrix_test.py
+++ b/tensorflow/python/kernel_tests/confusion_matrix_test.py
@@ -71,9 +71,11 @@ class ConfusionMatrixTest(test.TestCase):
self._testConfMatrix(labels=labels, predictions=predictions, truth=truth)
+ @test_util.run_deprecated_v1
def testInt32Basic(self):
self._testBasic(dtype=np.int32)
+ @test_util.run_deprecated_v1
def testInt64Basic(self):
self._testBasic(dtype=np.int64)
@@ -111,9 +113,11 @@ class ConfusionMatrixTest(test.TestCase):
self.assertEqual(cm_out.dtype, np_dtype)
self.assertAllClose(cm_out, truth, atol=1e-10)
+ @test_util.run_deprecated_v1
def testOnTensors_int32(self):
self._testConfMatrixOnTensors(dtypes.int32, np.int32)
+ @test_util.run_deprecated_v1
def testOnTensors_int64(self):
self._testConfMatrixOnTensors(dtypes.int64, np.int64)
@@ -133,9 +137,11 @@ class ConfusionMatrixTest(test.TestCase):
self._testConfMatrix(labels=labels, predictions=predictions, truth=truth)
+ @test_util.run_deprecated_v1
def testInt32DifferentLabels(self, dtype=np.int32):
self._testDifferentLabelsInPredictionAndTarget(dtype)
+ @test_util.run_deprecated_v1
def testInt64DifferentLabels(self, dtype=np.int64):
self._testDifferentLabelsInPredictionAndTarget(dtype)
@@ -155,12 +161,15 @@ class ConfusionMatrixTest(test.TestCase):
self._testConfMatrix(labels=labels, predictions=predictions, truth=truth)
+ @test_util.run_deprecated_v1
def testInt32MultipleLabels(self, dtype=np.int32):
self._testMultipleLabels(dtype)
+ @test_util.run_deprecated_v1
def testInt64MultipleLabels(self, dtype=np.int64):
self._testMultipleLabels(dtype)
+ @test_util.run_deprecated_v1
def testWeighted(self):
labels = np.arange(5, dtype=np.int32)
predictions = np.arange(5, dtype=np.int32)
@@ -177,6 +186,7 @@ class ConfusionMatrixTest(test.TestCase):
self._testConfMatrix(
labels=labels, predictions=predictions, weights=weights, truth=truth)
+ @test_util.run_deprecated_v1
def testLabelsTooLarge(self):
labels = np.asarray([1, 1, 0, 3, 5], dtype=np.int32)
predictions = np.asarray([2, 1, 0, 2, 2], dtype=np.int32)
@@ -191,6 +201,7 @@ class ConfusionMatrixTest(test.TestCase):
self._testConfMatrix(
labels=labels, predictions=predictions, num_classes=3, truth=None)
+ @test_util.run_deprecated_v1
def testPredictionsTooLarge(self):
labels = np.asarray([1, 1, 0, 2, 2], dtype=np.int32)
predictions = np.asarray([2, 1, 0, 3, 5], dtype=np.int32)
@@ -205,6 +216,7 @@ class ConfusionMatrixTest(test.TestCase):
self._testConfMatrix(
labels=labels, predictions=predictions, num_classes=3, truth=None)
+ @test_util.run_deprecated_v1
def testInvalidRank_predictionsTooBig(self):
labels = np.asarray([1, 2, 3])
predictions = np.asarray([[1, 2, 3]])
@@ -212,6 +224,7 @@ class ConfusionMatrixTest(test.TestCase):
confusion_matrix.confusion_matrix, predictions,
labels)
+ @test_util.run_deprecated_v1
def testInvalidRank_predictionsTooSmall(self):
labels = np.asarray([[1, 2, 3]])
predictions = np.asarray([1, 2, 3])
@@ -219,6 +232,7 @@ class ConfusionMatrixTest(test.TestCase):
confusion_matrix.confusion_matrix, predictions,
labels)
+ @test_util.run_deprecated_v1
def testInputDifferentSize(self):
labels = np.asarray([1, 2])
predictions = np.asarray([1, 2, 3])
@@ -247,6 +261,7 @@ class ConfusionMatrixTest(test.TestCase):
class RemoveSqueezableDimensionsTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testBothScalarShape(self):
label_values = 1.0
prediction_values = 0.0
@@ -272,6 +287,7 @@ class RemoveSqueezableDimensionsTest(test.TestCase):
self.assertAllEqual(
prediction_values, dynamic_predictions.eval(feed_dict=feed_dict))
+ @test_util.run_deprecated_v1
def testSameShape(self):
label_values = np.ones(shape=(2, 3, 1))
prediction_values = np.zeros_like(label_values)
@@ -297,6 +313,7 @@ class RemoveSqueezableDimensionsTest(test.TestCase):
self.assertAllEqual(
prediction_values, dynamic_predictions.eval(feed_dict=feed_dict))
+ @test_util.run_deprecated_v1
def testSameShapeExpectedRankDiff0(self):
label_values = np.ones(shape=(2, 3, 1))
prediction_values = np.zeros_like(label_values)
@@ -322,6 +339,7 @@ class RemoveSqueezableDimensionsTest(test.TestCase):
self.assertAllEqual(
prediction_values, dynamic_predictions.eval(feed_dict=feed_dict))
+ @test_util.run_deprecated_v1
def testSqueezableLabels(self):
label_values = np.ones(shape=(2, 3, 1))
prediction_values = np.zeros(shape=(2, 3))
@@ -348,6 +366,7 @@ class RemoveSqueezableDimensionsTest(test.TestCase):
self.assertAllEqual(
prediction_values, dynamic_predictions.eval(feed_dict=feed_dict))
+ @test_util.run_deprecated_v1
def testSqueezableLabelsExpectedRankDiffPlus1(self):
label_values = np.ones(shape=(2, 3, 1))
prediction_values = np.zeros(shape=(2, 3, 5))
@@ -374,6 +393,7 @@ class RemoveSqueezableDimensionsTest(test.TestCase):
self.assertAllEqual(
prediction_values, dynamic_predictions.eval(feed_dict=feed_dict))
+ @test_util.run_deprecated_v1
def testSqueezablePredictions(self):
label_values = np.ones(shape=(2, 3))
prediction_values = np.zeros(shape=(2, 3, 1))
@@ -402,6 +422,7 @@ class RemoveSqueezableDimensionsTest(test.TestCase):
expected_prediction_values,
dynamic_predictions.eval(feed_dict=feed_dict))
+ @test_util.run_deprecated_v1
def testSqueezablePredictionsExpectedRankDiffMinus1(self):
label_values = np.ones(shape=(2, 3, 5))
prediction_values = np.zeros(shape=(2, 3, 1))
@@ -430,6 +451,7 @@ class RemoveSqueezableDimensionsTest(test.TestCase):
expected_prediction_values,
dynamic_predictions.eval(feed_dict=feed_dict))
+ @test_util.run_deprecated_v1
def testUnsqueezableLabels(self):
label_values = np.ones(shape=(2, 3, 2))
prediction_values = np.zeros(shape=(2, 3))
@@ -455,6 +477,7 @@ class RemoveSqueezableDimensionsTest(test.TestCase):
self.assertAllEqual(
prediction_values, dynamic_predictions.eval(feed_dict=feed_dict))
+ @test_util.run_deprecated_v1
def testUnsqueezablePredictions(self):
label_values = np.ones(shape=(2, 3))
prediction_values = np.zeros(shape=(2, 3, 2))
diff --git a/tensorflow/python/kernel_tests/constant_op_test.py b/tensorflow/python/kernel_tests/constant_op_test.py
index 9c3c96bd317..583082c2aa2 100644
--- a/tensorflow/python/kernel_tests/constant_op_test.py
+++ b/tensorflow/python/kernel_tests/constant_op_test.py
@@ -70,6 +70,7 @@ class ConstantTest(test.TestCase):
with self.assertRaises(TypeError):
constant_op.constant(dtypes_lib.string, "[,]")
+ @test_util.run_deprecated_v1
def testBFloat16(self):
bfloat16 = dtypes_lib.bfloat16.as_numpy_dtype
self._testAll(np.arange(-15, 15).reshape([2, 3, 5]).astype(bfloat16))
@@ -77,36 +78,42 @@ class ConstantTest(test.TestCase):
np.random.normal(size=30).reshape([2, 3, 5]).astype(bfloat16))
self._testAll(np.empty((2, 0, 5)).astype(bfloat16))
+ @test_util.run_deprecated_v1
def testHalf(self):
self._testAll(np.arange(-15, 15).reshape([2, 3, 5]).astype(np.float16))
self._testAll(
np.random.normal(size=30).reshape([2, 3, 5]).astype(np.float16))
self._testAll(np.empty((2, 0, 5)).astype(np.float16))
+ @test_util.run_deprecated_v1
def testFloat(self):
self._testAll(np.arange(-15, 15).reshape([2, 3, 5]).astype(np.float32))
self._testAll(
np.random.normal(size=30).reshape([2, 3, 5]).astype(np.float32))
self._testAll(np.empty((2, 0, 5)).astype(np.float32))
+ @test_util.run_deprecated_v1
def testDouble(self):
self._testAll(np.arange(-15, 15).reshape([2, 3, 5]).astype(np.float64))
self._testAll(
np.random.normal(size=30).reshape([2, 3, 5]).astype(np.float64))
self._testAll(np.empty((2, 0, 5)).astype(np.float64))
+ @test_util.run_deprecated_v1
def testInt32(self):
self._testAll(np.arange(-15, 15).reshape([2, 3, 5]).astype(np.int32))
self._testAll((100 * np.random.normal(size=30)).reshape([2, 3, 5]).astype(
np.int32))
self._testAll(np.empty((2, 0, 5)).astype(np.int32))
+ @test_util.run_deprecated_v1
def testInt64(self):
self._testAll(np.arange(-15, 15).reshape([2, 3, 5]).astype(np.int64))
self._testAll((100 * np.random.normal(size=30)).reshape([2, 3, 5]).astype(
np.int64))
self._testAll(np.empty((2, 0, 5)).astype(np.int64))
+ @test_util.run_deprecated_v1
def testComplex64(self):
self._testAll(
np.complex(1, 2) *
@@ -116,6 +123,7 @@ class ConstantTest(test.TestCase):
np.random.normal(size=30).reshape([2, 3, 5]).astype(np.complex64))
self._testAll(np.empty((2, 0, 5)).astype(np.complex64))
+ @test_util.run_deprecated_v1
def testComplex128(self):
self._testAll(
np.complex(1, 2) *
@@ -125,12 +133,14 @@ class ConstantTest(test.TestCase):
np.random.normal(size=30).reshape([2, 3, 5]).astype(np.complex128))
self._testAll(np.empty((2, 0, 5)).astype(np.complex128))
+ @test_util.run_deprecated_v1
def testString(self):
self._testCpu(
np.array([compat.as_bytes(str(x)) for x in np.arange(-15, 15)]).reshape(
[2, 3, 5]))
self._testCpu(np.empty((2, 0, 5)).astype(np.str_))
+ @test_util.run_deprecated_v1
def testVariant(self):
# TODO(ebrevdo): Re-enable use_gpu=True once non-DMA Variant
# copying between CPU and GPU is supported.
@@ -161,6 +171,7 @@ class ConstantTest(test.TestCase):
message="Variant storing an int, decoded const value:").op
logging_const_op.run()
+ @test_util.run_deprecated_v1
def testStringWithNulls(self):
with self.cached_session():
val = ops.convert_to_tensor(b"\0\0\0\0").eval()
@@ -265,6 +276,7 @@ class ConstantTest(test.TestCase):
"GraphDef cannot be larger than 2GB."):
g.as_graph_def()
+ @test_util.run_deprecated_v1
def testSparseValuesRaiseErrors(self):
with self.assertRaisesRegexp(ValueError,
"setting an array element with a sequence"):
@@ -342,6 +354,7 @@ class AsTensorTest(test.TestCase):
ops.convert_to_tensor(
tensor_shape.TensorShape([1, 2, 3]), dtype=dtypes_lib.float32)
+ @test_util.run_deprecated_v1
def testAsTensorForDimensionInput(self):
with self.cached_session():
x = ops.convert_to_tensor(tensor_shape.TensorShape([1, 2, 3])[1])
@@ -409,6 +422,7 @@ class ZerosTest(test.TestCase):
self.assertShapeEqual(np_ans, d)
self.assertShapeEqual(np_ans, z)
+ @test_util.run_deprecated_v1
def testDtype(self):
with self.cached_session():
d = array_ops.fill([2, 3], 12., name="fill")
@@ -477,6 +491,7 @@ class ZerosLikeTest(test.TestCase):
self.assertFalse(np.any(z_value))
self.assertEqual((2, 3), z_value.shape)
+ @test_util.run_deprecated_v1
def testZerosLikeCPU(self):
for dtype in [
dtypes_lib.half, dtypes_lib.float32, dtypes_lib.float64,
@@ -487,6 +502,7 @@ class ZerosLikeTest(test.TestCase):
self._compareZeros(dtype, fully_defined_shape=False, use_gpu=False)
self._compareZeros(dtype, fully_defined_shape=True, use_gpu=False)
+ @test_util.run_deprecated_v1
def testZerosLikeGPU(self):
for dtype in [
dtypes_lib.half, dtypes_lib.float32, dtypes_lib.float64,
@@ -496,11 +512,13 @@ class ZerosLikeTest(test.TestCase):
self._compareZeros(dtype, fully_defined_shape=False, use_gpu=True)
self._compareZeros(dtype, fully_defined_shape=True, use_gpu=True)
+ @test_util.run_deprecated_v1
def testZerosLikePartialShape(self):
d = array_ops.placeholder(dtypes_lib.float32, shape=[None, 4, None])
z = array_ops.zeros_like(d)
self.assertEqual(d.get_shape().as_list(), z.get_shape().as_list())
+ @test_util.run_deprecated_v1
def testZerosLikeDtype(self):
# Make sure zeros_like works even for dtypes that cannot be cast between
with self.cached_session():
@@ -514,6 +532,7 @@ class ZerosLikeTest(test.TestCase):
self.assertEqual(y.shape, shape)
self.assertAllEqual(y, np.zeros(shape, dtype=out_type))
+ @test_util.run_deprecated_v1
def testZerosLikeVariant(self):
# TODO(ebrevdo): Re-enable use_gpu=True once non-DMA Variant
# copying between CPU and GPU is supported AND we register a
@@ -574,6 +593,7 @@ class OnesTest(test.TestCase):
self.assertShapeEqual(np_ans, d)
self.assertShapeEqual(np_ans, z)
+ @test_util.run_deprecated_v1
def testAutoPack(self):
with self.cached_session():
h = array_ops.placeholder(dtypes_lib.int32, shape=[])
@@ -582,6 +602,7 @@ class OnesTest(test.TestCase):
out = z.eval(feed_dict={h: 4, w: 16})
self.assertAllEqual(out, np.array([[1] * 16] * 4))
+ @test_util.run_deprecated_v1
def testDtype(self):
with self.cached_session():
d = array_ops.fill([2, 3], 12., name="fill")
@@ -635,6 +656,7 @@ class OnesLikeTest(test.TestCase):
self.assertTrue(np.array_equal(z_value, np.array([[1] * 3] * 2)))
self.assertEqual([2, 3], z_var.get_shape())
+ @test_util.run_deprecated_v1
def testOnesLikePartialShape(self):
d = array_ops.placeholder(dtypes_lib.float32, shape=[None, 4, None])
z = array_ops.ones_like(d)
@@ -679,12 +701,14 @@ class FillTest(test.TestCase):
np_ans = np.array([[0.15 + 0.3j] * 3] * 2).astype(np.complex128)
self._compareAll([2, 3], np_ans[0][0], np_ans)
+ @test_util.run_deprecated_v1
def testFillString(self):
np_ans = np.array([[b"yolo"] * 3] * 2)
with self.session(use_gpu=False):
tf_ans = array_ops.fill([2, 3], np_ans[0][0], name="fill").eval()
self.assertAllEqual(np_ans, tf_ans)
+ @test_util.run_deprecated_v1
def testFillNegative(self):
with self.cached_session():
for shape in (-1,), (2, -1), (-1, 2), (-2), (-3):
@@ -698,6 +722,7 @@ class FillTest(test.TestCase):
with self.assertRaises(errors_impl.InvalidArgumentError):
fill_t.eval({dims: shape})
+ @test_util.run_deprecated_v1
def testShapeFunctionEdgeCases(self):
# Non-vector dimensions.
with self.assertRaises(ValueError):
@@ -716,6 +741,7 @@ class FillTest(test.TestCase):
dtypes_lib.int32, shape=()), 17], 1.0)
self.assertEqual([None, 17], f.get_shape().as_list())
+ @test_util.run_deprecated_v1
def testGradient(self):
with self.cached_session():
in_v = constant_op.constant(5.0)
@@ -728,6 +754,7 @@ class FillTest(test.TestCase):
class PlaceholderTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testDtype(self):
with self.cached_session():
p = array_ops.placeholder(dtypes_lib.float32, shape=(10, 10), name="p")
@@ -740,6 +767,7 @@ class PlaceholderTest(test.TestCase):
"must feed a value for placeholder tensor 'p' with dtype float"):
self.evaluate(p_identity)
+ @test_util.run_deprecated_v1
def testShape(self):
with self.cached_session():
p = array_ops.placeholder(dtypes_lib.float32, shape=(10, 10), name="p")
@@ -757,6 +785,7 @@ class PlaceholderTest(test.TestCase):
ValueError, lambda e: "Cannot feed value of shape" in str(e)):
p_identity.eval(feed_dict={p: feed_array[:5, :5]})
+ @test_util.run_deprecated_v1
def testUnknownShape(self):
with self.cached_session():
p = array_ops.placeholder(dtypes_lib.float32, shape=None, name="p")
@@ -769,12 +798,14 @@ class PlaceholderTest(test.TestCase):
self.assertAllClose(
p_identity.eval(feed_dict={p: feed_array}), feed_array)
+ @test_util.run_deprecated_v1
def testScalarShape(self):
with self.cached_session():
p = array_ops.placeholder(dtypes_lib.float32, shape=[], name="p")
p_identity = array_ops.identity(p)
self.assertAllClose(p_identity.eval(feed_dict={p: 5}), 5)
+ @test_util.run_deprecated_v1
def testPartialShape(self):
with self.cached_session():
p = array_ops.placeholder(dtypes_lib.float32, shape=[None, 3], name="p")
@@ -787,6 +818,7 @@ class PlaceholderTest(test.TestCase):
ValueError, lambda e: "Cannot feed value of shape" in str(e)):
p_identity.eval(feed_dict={p: feed_array[:5, :2]})
+ @test_util.run_deprecated_v1
def testPartialShapeWhenNotFed(self):
with self.cached_session():
p = array_ops.placeholder(dtypes_lib.float32, shape=[None, 3], name="p")
@@ -797,6 +829,7 @@ class PlaceholderTest(test.TestCase):
"must feed a value for placeholder tensor 'p' with dtype float"):
self.evaluate(p_identity)
+ @test_util.run_deprecated_v1
def testControlDependency(self):
with self.cached_session():
p = array_ops.placeholder(dtypes_lib.int32, shape=[], name="p")
@@ -806,10 +839,12 @@ class PlaceholderTest(test.TestCase):
val = np.array(2).astype(np.int)
self.assertEqual(10, d.eval(feed_dict={p: val}))
+ @test_util.run_deprecated_v1
def testBadShape(self):
with self.assertRaises(ValueError):
array_ops.placeholder(dtypes_lib.float32, shape=(-1, 10))
+ @test_util.run_deprecated_v1
def testTensorStr(self):
a = array_ops.placeholder(dtypes_lib.float32, shape=None, name="a")
self.assertEqual("<tf.Tensor 'a:0' shape=<unknown> dtype=float32>", repr(a))
@@ -825,6 +860,7 @@ class PlaceholderTest(test.TestCase):
self.assertEqual(
"<tf.Tensor 'c:0' shape=(32, ?, 2) dtype=qint32>", repr(c))
+ @test_util.run_deprecated_v1
def testOldGraph(self):
# Load graph generated from earlier version of TF where
# placeholder shape was not set.
@@ -904,6 +940,7 @@ versions {
class PlaceholderWithDefaultTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testFullShape(self):
with self.session(force_gpu=test_util.is_gpu_available()):
p = array_ops.placeholder_with_default([[2, 2], [2, 2]], shape=[2, 2])
@@ -915,6 +952,7 @@ class PlaceholderWithDefaultTest(test.TestCase):
with self.assertRaises(ValueError):
a.eval(feed_dict={p: [[6, 6, 6], [6, 6, 6]]})
+ @test_util.run_deprecated_v1
def testPartialShape(self):
with self.session(force_gpu=test_util.is_gpu_available()):
p = array_ops.placeholder_with_default([1, 2, 3], shape=[None])
@@ -925,6 +963,7 @@ class PlaceholderWithDefaultTest(test.TestCase):
with self.assertRaises(ValueError):
a.eval(feed_dict={p: [[2, 2], [2, 2]]})
+ @test_util.run_deprecated_v1
def testNoShape(self):
with self.session(force_gpu=test_util.is_gpu_available()):
p = array_ops.placeholder_with_default([17], shape=None)
@@ -934,6 +973,7 @@ class PlaceholderWithDefaultTest(test.TestCase):
self.assertAllEqual(
[[3, 3], [3, 3]], a.eval(feed_dict={p: [[3, 3], [3, 3]]}))
+ @test_util.run_deprecated_v1
def testGradient(self):
with self.session(force_gpu=test_util.is_gpu_available()):
x = array_ops.placeholder(dtypes_lib.float32, [5, 7])
diff --git a/tensorflow/python/kernel_tests/control_flow_ops_py_test.py b/tensorflow/python/kernel_tests/control_flow_ops_py_test.py
index 685d0438af2..f1efc5ce59d 100644
--- a/tensorflow/python/kernel_tests/control_flow_ops_py_test.py
+++ b/tensorflow/python/kernel_tests/control_flow_ops_py_test.py
@@ -141,6 +141,7 @@ class ControlFlowTest(test.TestCase):
variables.global_variables_initializer().run()
self.assertEqual(9, self.evaluate(v2))
+ @test_util.run_deprecated_v1
def testRefEnter(self):
with self.cached_session():
v = variables.VariableV1(7)
@@ -154,6 +155,7 @@ class ControlFlowTest(test.TestCase):
variables.global_variables_initializer().run()
self.assertEqual(9, self.evaluate(v3))
+ @test_util.run_deprecated_v1
def testRefSwitch(self):
with self.cached_session():
v = variables.VariableV1(7)
@@ -176,6 +178,7 @@ class ControlFlowTest(test.TestCase):
result = self.evaluate(exit_op)
self.assertAllEqual(np.array([x * 5 for x in [1, 2, 3, 4, 5, 6]]), result)
+ @test_util.run_deprecated_v1
def testEnterShapePropagation(self):
with self.cached_session():
v = variables.Variable([0.0, 0.0], dtype=dtypes.float32)
@@ -272,6 +275,7 @@ class ControlFlowTest(test.TestCase):
result = self.evaluate(exit_n)
self.assertAllEqual(10, result)
+ @test_util.run_deprecated_v1
def testLoop_1(self):
with self.cached_session():
zero = constant_op.constant(0)
@@ -333,6 +337,7 @@ class ControlFlowTest(test.TestCase):
with self.assertRaisesOpError("has inputs from different frames"):
res.eval(feed_dict={data: 1.0})
+ @test_util.run_deprecated_v1
def testCondBool(self):
values = constant_op.constant(10)
fn1 = lambda: math_ops.add(values, 1)
@@ -340,6 +345,7 @@ class ControlFlowTest(test.TestCase):
with self.assertRaisesRegexp(TypeError, "must not be a Python bool"):
_ = control_flow_ops.cond(False, fn1, fn2)
+ @test_util.run_deprecated_v1
def testCondInt(self):
p = array_ops.placeholder(dtypes.bool, shape=[])
v = constant_op.constant(10)
@@ -627,6 +633,7 @@ class ControlFlowTest(test.TestCase):
test_result = self.evaluate(r)
self.assertDictEqual({"a": 210, "b": 210}, test_result)
+ @test_util.run_deprecated_v1
def testEmbeddedListOutput(self):
with self.cached_session() as sess:
x = constant_op.constant(10)
@@ -678,6 +685,7 @@ class ControlFlowTest(test.TestCase):
r = control_flow_ops.cond(pred, fn1, fn2)
self.evaluate(r)
+ @test_util.run_deprecated_v1
def testCondRef(self):
with self.cached_session():
@@ -693,6 +701,7 @@ class ControlFlowTest(test.TestCase):
self.assertAllEqual([2.0], self.evaluate(r))
@test_util.disable_control_flow_v2("b/79881896 (control deps)")
+ @test_util.run_deprecated_v1
def testCondWithControl(self):
with self.cached_session():
control_holder = array_ops.placeholder(dtypes.float32, shape=())
@@ -773,6 +782,7 @@ class ControlFlowTest(test.TestCase):
grad = gradients_impl.gradients(r, [x])[0]
self.assertAllEqual(1.0, self.evaluate(grad))
+ @test_util.run_deprecated_v1
def testCondGrad_2(self):
with self.cached_session():
c = array_ops.placeholder(dtypes.int32, shape=[])
@@ -788,6 +798,7 @@ class ControlFlowTest(test.TestCase):
@test_util.disable_control_flow_v2(
"b/110550782 (gradient w.r.t external variable)")
+ @test_util.run_deprecated_v1
def testCondGrad_3(self):
with self.cached_session():
c = array_ops.placeholder(dtypes.int32, shape=[])
@@ -805,6 +816,7 @@ class ControlFlowTest(test.TestCase):
self.assertAllEqual(980.0, r.eval(feed_dict={c: 1}))
self.assertAllEqual(30.0, r.eval(feed_dict={c: 3}))
+ @test_util.run_deprecated_v1
def testCondGradMultiDevice(self):
config = config_pb2.ConfigProto(device_count={"CPU": 2},
allow_soft_placement=True)
@@ -849,6 +861,7 @@ class ControlFlowTest(test.TestCase):
self.assertEqual(1.0, self.evaluate(result))
@test_util.disable_control_flow_v2("b/113327884")
+ @test_util.run_deprecated_v1
def testCondGrad_Gather(self):
with self.cached_session() as sess:
v1 = variables.Variable([1.0, 42.0])
@@ -1030,6 +1043,7 @@ class ControlFlowTest(test.TestCase):
self.assertAllEqual(v.eval(), 1.0)
@test_util.disable_control_flow_v2("b/113324949 (RefVariable)")
+ @test_util.run_deprecated_v1
def testWhileWithRefs_1(self):
with self.cached_session() as sess:
x = variables.VariableV1(0)._ref() # pylint: disable=protected-access
@@ -1269,6 +1283,7 @@ class ControlFlowTest(test.TestCase):
# Have more than 10 parallel iterations and hence exercise k-bound
# most of the time.
+ @test_util.run_deprecated_v1
def testWhile_3(self):
with self.cached_session():
@@ -1289,6 +1304,7 @@ class ControlFlowTest(test.TestCase):
result = r[3].eval()
self.assertAllEqual(10100, result)
+ @test_util.run_deprecated_v1
def testWhile_4(self):
with self.cached_session():
@@ -1402,6 +1418,7 @@ class ControlFlowTest(test.TestCase):
r = r[1] * array_ops.ones([8, 8])
self.assertAllEqual(np.ones((8, 8)), self.evaluate(r))
+ @test_util.run_deprecated_v1
def testWhileWithNonTensorInput_Scalar(self):
with self.cached_session():
n = 0
@@ -1476,6 +1493,7 @@ class ControlFlowTest(test.TestCase):
[i.get_shape(), tensor_shape.TensorShape([5])])
@test_util.disable_control_flow_v2("b/116282023 (IndexedSlices)")
+ @test_util.run_deprecated_v1
def testWhileShapeInferenceIndexedSlices(self):
with self.cached_session():
values = constant_op.constant([[2.0, 4.0], [3.0, 5.0]], name="values")
@@ -1582,6 +1600,7 @@ class ControlFlowTest(test.TestCase):
condition, body, [n, r], parallel_iterations=1)
self.assertAllEqual(12, res[1].eval())
+ @test_util.run_deprecated_v1
def testWhileWithControl_2(self):
with self.cached_session():
r = constant_op.constant(0)
@@ -1736,6 +1755,7 @@ class ControlFlowTest(test.TestCase):
self.assertEqual([2.0], sess.run(r1, {p: False}))
@test_util.disable_control_flow_v2("b/116743589")
+ @test_util.run_deprecated_v1
def testCondWhile_3(self):
self._testCondWhile_3(use_gpu=False)
self._testCondWhile_3(use_gpu=True)
@@ -1779,6 +1799,7 @@ class ControlFlowTest(test.TestCase):
r = control_flow_ops.while_loop(c, b, [n])
self.assertAllEqual(10, self.evaluate(r))
+ @test_util.run_deprecated_v1
def testWhileCondGradMultiDevice(self):
config = config_pb2.ConfigProto(device_count={"CPU": 2},
allow_soft_placement=True)
@@ -1810,6 +1831,7 @@ class ControlFlowTest(test.TestCase):
# NOTE: It is ok to have parallel_iterations > 1
@test_util.disable_control_flow_v2("b/113324949 (RefVariable)")
+ @test_util.run_deprecated_v1
def testWhileUpdateVariable_1(self):
with self.cached_session():
select = variables.Variable([3.0, 4.0, 5.0])
@@ -1860,6 +1882,7 @@ class ControlFlowTest(test.TestCase):
self.assertAllClose(np.array([10.0, 10.0, 10.0]), result2)
@test_util.disable_control_flow_v2("b/113324949 (RefVariable)")
+ @test_util.run_deprecated_v1
def testWhileUpdateVariable_3(self):
with self.cached_session():
select = variables.Variable([3.0, 4.0, 5.0])
@@ -1882,6 +1905,7 @@ class ControlFlowTest(test.TestCase):
self.assertAllClose(np.array([10.0, 10.0, 10.0]), result)
@test_util.disable_control_flow_v2("b/113324949 (RefVariable)")
+ @test_util.run_deprecated_v1
def testWhileUpdateVariable_4(self):
with self.cached_session():
var_a = variables.Variable(0, name="a")
@@ -1910,6 +1934,7 @@ class ControlFlowTest(test.TestCase):
self.assertEqual(10, self.evaluate(var_b))
@test_util.disable_control_flow_v2("b/113324949 (RefVariable)")
+ @test_util.run_deprecated_v1
def testWhileUpdateVariable_5(self):
with self.cached_session():
# Create some variables.
@@ -2089,6 +2114,7 @@ class ControlFlowTest(test.TestCase):
self.assertEqual([None], r.get_shape().as_list())
self.assertAllClose([810.0, 2560.0], r.eval(feed_dict={x: [3.0, 4.0]}))
+ @test_util.run_deprecated_v1
def testWhileGrad_BaseShape(self):
with self.cached_session() as sess:
x = array_ops.placeholder(dtypes.float32, [None])
@@ -2137,6 +2163,7 @@ class ControlFlowTest(test.TestCase):
self.assertAllClose(81.0, grad_v_val)
@test_util.disable_control_flow_v2("b/116630618 (parallel_iters: times out)")
+ @test_util.run_deprecated_v1
def testWhileGrad_Mul(self):
self._testWhileGrad_Mul(use_gpu=False, p_iters=1)
self._testWhileGrad_Mul(use_gpu=False, p_iters=10)
@@ -2166,9 +2193,11 @@ class ControlFlowTest(test.TestCase):
r = gradients_impl.gradients(r, v)[0]
self.assertAllClose(512.0, self.evaluate(r))
+ @test_util.run_deprecated_v1
def testNestedWhileCondWhileGrad(self):
self._testNestedWhileCondWhileGrad(use_gpu=False)
+ @test_util.run_deprecated_v1
def testNestedWhileCondWhileGradGpu(self):
self._testNestedWhileCondWhileGrad(use_gpu=True)
@@ -2184,6 +2213,7 @@ class ControlFlowTest(test.TestCase):
variables.global_variables_initializer().run()
self.assertAllClose(216.0, r[0].eval())
+ @test_util.run_deprecated_v1
def testWhileGrad_ResourceVariable(self):
with self.cached_session():
a = resource_variable_ops.ResourceVariable(3.0)
@@ -2213,6 +2243,7 @@ class ControlFlowTest(test.TestCase):
self.assertAllClose(9.0, r.eval(feed_dict={x: 1.0}))
@test_util.disable_control_flow_v2("b/116340060")
+ @test_util.run_deprecated_v1
def testGradInWhileWrtInitialLoopVal(self):
with self.cached_session():
x = array_ops.placeholder(dtypes.float32, shape=(), name="x")
@@ -2330,6 +2361,7 @@ class ControlFlowTest(test.TestCase):
r = gradients_impl.gradients([rx], y)
self.assertAllClose(120.0, r[0].eval())
+ @test_util.run_deprecated_v1
def testWhileGrad_Dependency(self):
with self.cached_session():
i = constant_op.constant(0, name="i")
@@ -2381,6 +2413,7 @@ class ControlFlowTest(test.TestCase):
variables.global_variables_initializer().run()
self.assertAllClose(np.ones([2, 3]), sess.run(grad[0]))
+ @test_util.run_deprecated_v1
def testWhileGrad_Const(self):
with self.cached_session() as sess:
c0 = constant_op.constant(0.0, name="c0")
@@ -2475,6 +2508,7 @@ class ControlFlowTest(test.TestCase):
r = gradients_impl.gradients(r, v)[0]
self.assertAllClose(8.0, self.evaluate(r))
+ @test_util.run_deprecated_v1
def testNestedWhileGrad_Simple(self):
self._testNestedWhileGrad_Simple(use_gpu=False)
self._testNestedWhileGrad_Simple(use_gpu=True)
@@ -2502,6 +2536,7 @@ class ControlFlowTest(test.TestCase):
r = gradients_impl.gradients(r, v)[0]
self.assertAllClose(256.0, self.evaluate(r))
+ @test_util.run_deprecated_v1
def testNestedWhileGrad_ParallelInner(self):
with self.cached_session():
v = constant_op.constant(1.0)
@@ -2564,11 +2599,13 @@ class ControlFlowTest(test.TestCase):
self.assertAllClose(1024.0, self.evaluate(r))
@test_util.disable_control_flow_v2("b/117519152")
+ @test_util.run_deprecated_v1
def testWhileCondGrad_Simple(self):
self._testWhileCondGrad_Simple(use_gpu=False)
self._testWhileCondGrad_Simple(use_gpu=True)
@test_util.disable_control_flow_v2("b/117276490")
+ @test_util.run_deprecated_v1
def testWhileCondGrad_UnknownShape(self):
with self.cached_session() as sess:
v = array_ops.placeholder(dtypes.float32)
@@ -2586,6 +2623,7 @@ class ControlFlowTest(test.TestCase):
r = sess.run(r, feed_dict={v: 2.0})
self.assertAllClose(1024.0, r)
+ @test_util.run_deprecated_v1
def testWhileGrad_Concat(self):
with self.cached_session() as sess:
x = variable_scope.get_variable("x", initializer=[[1., 2.]])
@@ -2661,6 +2699,7 @@ class ControlFlowTest(test.TestCase):
self.assertAllClose(np.array([1024.0, 1024.0]), self.evaluate(r))
@test_util.disable_control_flow_v2("b/116328420 (SparseTensor)")
+ @test_util.run_deprecated_v1
def testWhileGrad_SparseTensor(self):
with self.cached_session():
values = constant_op.constant([2.0, 4.0], name="values")
@@ -2703,6 +2742,7 @@ class ControlFlowTest(test.TestCase):
c, b, [i0, constant_op.constant(0.0)])
self.assertAllClose(600.0, self.evaluate(output_grad)[1])
+ @test_util.run_deprecated_v1
def testWhileAndTensorArray(self):
with self.cached_session() as sess:
param = constant_op.constant(2.0)
@@ -2722,6 +2762,7 @@ class ControlFlowTest(test.TestCase):
r = gradients_impl.gradients(r, param)[0]
self.assertAllClose(107520.0, self.evaluate(r))
+ @test_util.run_deprecated_v1
def testWhileGrad_StopGrad(self):
with self.cached_session():
x = constant_op.constant(3.0, name="x")
@@ -2765,6 +2806,7 @@ class ControlFlowTest(test.TestCase):
math_ops.add(array_ops.stop_gradient(rx), ry), y)[0]
self.assertEqual(32.0, self.evaluate(r))
+ @test_util.run_deprecated_v1
def testWhileGrad_StopGradInside(self):
with self.cached_session():
x = constant_op.constant(3.0, name="x")
@@ -2784,6 +2826,7 @@ class ControlFlowTest(test.TestCase):
r = gradients_impl.gradients(rx, x)[0]
self.assertAllClose(156.0, self.evaluate(r))
+ @test_util.run_deprecated_v1
def testWhileGrad_StopGradInsideNoShape(self):
with self.cached_session() as sess:
x = array_ops.placeholder(dtypes.float32)
@@ -2808,6 +2851,7 @@ class ControlFlowTest(test.TestCase):
self.assertFalse(any(name in op.name for op in all_ops))
@test_util.disable_control_flow_v2("b/117954949")
+ @test_util.run_deprecated_v1
def testWhileGradGradFail(self):
theta = variables.Variable(initial_value=1.)
@@ -2822,6 +2866,7 @@ class ControlFlowTest(test.TestCase):
grad_theta_stopped = array_ops.stop_gradient(grad_theta)
gradients_impl.gradients(grad_theta_stopped, theta)
+ @test_util.run_deprecated_v1
def testStopGradOnWhileGrad(self):
with self.cached_session():
x = constant_op.constant(2.0, name="x")
@@ -2839,6 +2884,7 @@ class ControlFlowTest(test.TestCase):
self.assertEqual(388.0, self.evaluate(r))
@test_util.disable_control_flow_v2("b/113324949 (RefVariable)")
+ @test_util.run_deprecated_v1
def testWhileGradientWithNontrainablePath1(self):
q = variables.Variable([7., 8.])
@@ -2940,6 +2986,7 @@ class ControlFlowTest(test.TestCase):
# False case: c = 0 is not >= 1
self.assertEqual([2], i.eval(feed_dict={c: 0}))
+ @test_util.run_deprecated_v1
def testExampleCond(self):
with self.cached_session():
@@ -3191,6 +3238,7 @@ class ControlFlowTest(test.TestCase):
self.assertEqual(op.type, "NoOp")
self.assertEqual(op.control_inputs, [])
+ @test_util.run_deprecated_v1
def testMergeShapes(self):
# All inputs unknown.
p1 = array_ops.placeholder(dtypes.float32)
@@ -3245,6 +3293,7 @@ class ControlFlowTest(test.TestCase):
self.assertEqual([None, None], m.get_shape().as_list())
self.assertEqual([], index.get_shape())
+ @test_util.run_deprecated_v1
def testRefSelect(self):
index = array_ops.placeholder(dtypes.int32)
@@ -3278,6 +3327,7 @@ class ControlFlowTest(test.TestCase):
s = control_flow_ops.ref_select(index, [v1, v2])
self.assertEqual(None, s.get_shape())
+ @test_util.run_deprecated_v1
def testRunLoopTensor(self):
with self.cached_session() as sess:
tensor_list = []
@@ -3364,6 +3414,7 @@ class ControlFlowTest(test.TestCase):
result = control_flow_ops.merge([v_f, v_t])
self.evaluate(result)
+ @test_util.run_deprecated_v1
def testQIntArgAndRet(self):
@function.Defun(dtypes.qint8)
@@ -3411,6 +3462,7 @@ class ControlFlowContextCheckTest(test.TestCase):
"is in a while loop. See info log for more details."):
math_ops.add(1, while_tensor)
+ @test_util.run_deprecated_v1
def testInvalidContextInCond(self):
# Accessing a while loop tensor in cond is illegal.
while_tensor = self._getWhileTensor()
@@ -3479,6 +3531,7 @@ class ControlFlowContextCheckTest(test.TestCase):
control_flow_ops.while_loop(lambda i: i < 5, body, [0])
+ @test_util.run_deprecated_v1
def testInvalidNestedContexts(self):
# Accessing a tensor from a while context in a different while context, all
# inside a cond context, is illegal.
@@ -3527,6 +3580,7 @@ class TupleTest(test.TestCase):
self.assertAllClose([30.0], self.evaluate(t2))
self.assertAllClose([1.0], self.evaluate(v1))
+ @test_util.run_deprecated_v1
def testIndexedSlices(self):
for v1_first in [True, False]:
with self.cached_session():
@@ -3582,6 +3636,7 @@ class TupleTest(test.TestCase):
class AssertTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testGuardedAssertDoesNotCopyWhenTrue(self):
with self.session(use_gpu=True) as sess:
with ops.device(test.gpu_device_name()):
diff --git a/tensorflow/python/kernel_tests/conv2d_backprop_filter_grad_test.py b/tensorflow/python/kernel_tests/conv2d_backprop_filter_grad_test.py
index af6ffc1d195..7b3b560b240 100644
--- a/tensorflow/python/kernel_tests/conv2d_backprop_filter_grad_test.py
+++ b/tensorflow/python/kernel_tests/conv2d_backprop_filter_grad_test.py
@@ -22,6 +22,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import nn_ops
@@ -31,6 +32,7 @@ from tensorflow.python.platform import test
class Conv2DBackpropFilterGradTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testGradient(self):
with self.cached_session():
for padding in ["SAME", "VALID"]:
diff --git a/tensorflow/python/kernel_tests/conv2d_transpose_test.py b/tensorflow/python/kernel_tests/conv2d_transpose_test.py
index d9aa4ab9672..c603c086306 100644
--- a/tensorflow/python/kernel_tests/conv2d_transpose_test.py
+++ b/tensorflow/python/kernel_tests/conv2d_transpose_test.py
@@ -23,6 +23,7 @@ from six.moves import xrange # pylint: disable=redefined-builtin
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import nn_ops
@@ -154,6 +155,7 @@ class Conv2DTransposeTest(test.TestCase):
self.assertAllClose(cache_values, value)
+ @test_util.run_deprecated_v1
def testGradient(self):
x_shape = [2, 6, 4, 3]
f_shape = [3, 3, 2, 3]
diff --git a/tensorflow/python/kernel_tests/conv3d_backprop_filter_v2_grad_test.py b/tensorflow/python/kernel_tests/conv3d_backprop_filter_v2_grad_test.py
index 89b64068ace..7e913febed3 100644
--- a/tensorflow/python/kernel_tests/conv3d_backprop_filter_v2_grad_test.py
+++ b/tensorflow/python/kernel_tests/conv3d_backprop_filter_v2_grad_test.py
@@ -22,6 +22,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import nn_ops
@@ -31,6 +32,7 @@ from tensorflow.python.platform import test
class Conv3DBackpropFilterV2GradTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testGradient(self):
with self.cached_session():
for padding in ["SAME", "VALID"]:
diff --git a/tensorflow/python/kernel_tests/conv3d_transpose_test.py b/tensorflow/python/kernel_tests/conv3d_transpose_test.py
index d4e7ec14da3..22ba5b90375 100644
--- a/tensorflow/python/kernel_tests/conv3d_transpose_test.py
+++ b/tensorflow/python/kernel_tests/conv3d_transpose_test.py
@@ -23,6 +23,7 @@ from six.moves import xrange # pylint: disable=redefined-builtin
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import nn_ops
import tensorflow.python.ops.nn_grad # pylint: disable=unused-import
@@ -119,6 +120,7 @@ class Conv3DTransposeTest(test.TestCase):
target = 3.0
self.assertAllClose(target, value[n, d, h, w, k])
+ @test_util.run_deprecated_v1
def testConv3DTransposeShapeMismatch(self):
# Test case for GitHub issue 18460
x_shape = [2, 2, 3, 4, 3]
@@ -201,6 +203,7 @@ class Conv3DTransposeTest(test.TestCase):
self.assertAllClose(cache_values, value)
+ @test_util.run_deprecated_v1
def testGradient(self):
x_shape = [2, 3, 4, 3, 2]
f_shape = [3, 3, 3, 2, 2]
diff --git a/tensorflow/python/kernel_tests/conv_ops_3d_test.py b/tensorflow/python/kernel_tests/conv_ops_3d_test.py
index 3ec5c29df7d..4a689b3fdfa 100644
--- a/tensorflow/python/kernel_tests/conv_ops_3d_test.py
+++ b/tensorflow/python/kernel_tests/conv_ops_3d_test.py
@@ -462,6 +462,7 @@ class Conv3DTest(test.TestCase):
self._ConstructAndTestGradientForConfig(data_format=data_format,
use_gpu=use_gpu, **kwargs)
+ @test_util.run_deprecated_v1
def testInputGradientValidPaddingStrideOne(self):
self.ConstructAndTestGradient(
batch=2,
@@ -473,6 +474,7 @@ class Conv3DTest(test.TestCase):
padding="VALID",
test_input=True)
+ @test_util.run_deprecated_v1
def testFilterGradientValidPaddingStrideOne(self):
self.ConstructAndTestGradient(
batch=4,
@@ -484,6 +486,7 @@ class Conv3DTest(test.TestCase):
padding="VALID",
test_input=False)
+ @test_util.run_deprecated_v1
def testInputGradientValidPaddingStrideTwo(self):
self.ConstructAndTestGradient(
batch=2,
@@ -495,6 +498,7 @@ class Conv3DTest(test.TestCase):
padding="VALID",
test_input=True)
+ @test_util.run_deprecated_v1
def testFilterGradientValidPaddingStrideTwo(self):
self.ConstructAndTestGradient(
batch=2,
@@ -506,6 +510,7 @@ class Conv3DTest(test.TestCase):
padding="VALID",
test_input=False)
+ @test_util.run_deprecated_v1
def testInputGradientValidPaddingStrideThree(self):
self.ConstructAndTestGradient(
batch=2,
@@ -517,6 +522,7 @@ class Conv3DTest(test.TestCase):
padding="VALID",
test_input=True)
+ @test_util.run_deprecated_v1
def testFilterGradientValidPaddingStrideThree(self):
self.ConstructAndTestGradient(
batch=2,
@@ -528,6 +534,7 @@ class Conv3DTest(test.TestCase):
padding="VALID",
test_input=False)
+ @test_util.run_deprecated_v1
def testInputGradientSamePaddingStrideOne(self):
self.ConstructAndTestGradient(
batch=2,
@@ -539,6 +546,7 @@ class Conv3DTest(test.TestCase):
padding="SAME",
test_input=True)
+ @test_util.run_deprecated_v1
def testFilterGradientSamePaddingStrideOne(self):
self.ConstructAndTestGradient(
batch=2,
@@ -550,6 +558,7 @@ class Conv3DTest(test.TestCase):
padding="SAME",
test_input=False)
+ @test_util.run_deprecated_v1
def testInputGradientSamePaddingStrideTwo(self):
self.ConstructAndTestGradient(
batch=2,
@@ -561,6 +570,7 @@ class Conv3DTest(test.TestCase):
padding="SAME",
test_input=True)
+ @test_util.run_deprecated_v1
def testFilterGradientSamePaddingStrideTwo(self):
self.ConstructAndTestGradient(
batch=4,
@@ -572,6 +582,7 @@ class Conv3DTest(test.TestCase):
padding="SAME",
test_input=False)
+ @test_util.run_deprecated_v1
def testInputGradientSamePaddingStrideThree(self):
self.ConstructAndTestGradient(
batch=2,
@@ -583,6 +594,7 @@ class Conv3DTest(test.TestCase):
padding="SAME",
test_input=True)
+ @test_util.run_deprecated_v1
def testFilterGradientSamePaddingStrideThree(self):
self.ConstructAndTestGradient(
batch=2,
@@ -594,6 +606,7 @@ class Conv3DTest(test.TestCase):
padding="SAME",
test_input=False)
+ @test_util.run_deprecated_v1
def testInputGradientSamePaddingDifferentStrides(self):
self.ConstructAndTestGradient(
batch=1,
@@ -605,6 +618,7 @@ class Conv3DTest(test.TestCase):
padding="SAME",
test_input=True)
+ @test_util.run_deprecated_v1
def testFilterGradientKernelSizeMatchesInputSize(self):
self.ConstructAndTestGradient(
batch=2,
@@ -616,6 +630,7 @@ class Conv3DTest(test.TestCase):
padding="VALID",
test_input=False)
+ @test_util.run_deprecated_v1
def testInputGradientKernelSizeMatchesInputSize(self):
self.ConstructAndTestGradient(
batch=2,
@@ -640,6 +655,7 @@ class Conv3DTest(test.TestCase):
# Test the fast path in gemm_pack_rhs/mkldnn_gemm_pack, when channel
# dimension is a multiple of packet size.
+ @test_util.run_deprecated_v1
def testInputGradientValidPaddingStrideOneFastPath(self):
self.ConstructAndTestGradient(
batch=2,
@@ -651,6 +667,7 @@ class Conv3DTest(test.TestCase):
padding="VALID",
test_input=True)
+ @test_util.run_deprecated_v1
def testFilterGradientValidPaddingStrideOneFastPath(self):
self.ConstructAndTestGradient(
batch=2,
diff --git a/tensorflow/python/kernel_tests/cross_grad_test.py b/tensorflow/python/kernel_tests/cross_grad_test.py
index 0bd4006d6ac..b397133fd73 100644
--- a/tensorflow/python/kernel_tests/cross_grad_test.py
+++ b/tensorflow/python/kernel_tests/cross_grad_test.py
@@ -18,6 +18,7 @@ from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import math_ops
@@ -26,6 +27,7 @@ from tensorflow.python.platform import test
class CrossOpTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testGradientRandomValues(self):
with self.cached_session():
us = [2, 3]
diff --git a/tensorflow/python/kernel_tests/ctc_decoder_ops_test.py b/tensorflow/python/kernel_tests/ctc_decoder_ops_test.py
index d818fbd75ce..0d86d13c715 100644
--- a/tensorflow/python/kernel_tests/ctc_decoder_ops_test.py
+++ b/tensorflow/python/kernel_tests/ctc_decoder_ops_test.py
@@ -25,6 +25,7 @@ from six.moves import zip_longest
from tensorflow.python.framework import errors
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import ctc_ops
from tensorflow.python.platform import test
@@ -94,6 +95,7 @@ class CTCGreedyDecoderTest(test.TestCase):
with self.assertRaisesOpError(expected_err_re):
sess.run(decoded_unwrapped + [log_probability])
+ @test_util.run_deprecated_v1
def testCTCGreedyDecoder(self):
"""Test two batch entries - best path decoder."""
max_time_steps = 6
@@ -170,6 +172,7 @@ class CTCGreedyDecoderTest(test.TestCase):
self._testCTCDecoder(ctc_ops.ctc_greedy_decoder, inputs, seq_lens,
log_prob_truth, decode_truth)
+ @test_util.run_deprecated_v1
def testCTCDecoderBeamSearch(self):
"""Test one batch, two beams - hibernating beam search."""
# max_time_steps == 8
diff --git a/tensorflow/python/kernel_tests/ctc_loss_op_test.py b/tensorflow/python/kernel_tests/ctc_loss_op_test.py
index 36cae2846cd..e6b5835079e 100644
--- a/tensorflow/python/kernel_tests/ctc_loss_op_test.py
+++ b/tensorflow/python/kernel_tests/ctc_loss_op_test.py
@@ -26,6 +26,7 @@ from tensorflow.python.framework import errors_impl
from tensorflow.python.framework import ops
from tensorflow.python.framework import random_seed
from tensorflow.python.framework import sparse_tensor
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import ctc_ops
from tensorflow.python.ops import gradients_impl
@@ -105,6 +106,7 @@ class CTCLossTest(test.TestCase):
with self.assertRaisesOpError(expected_err_re):
self.evaluate([loss, grad])
+ @test_util.run_deprecated_v1
def testBasic(self):
"""Test two batch entries."""
# Input and ground truth from Alex Graves' implementation.
@@ -240,6 +242,7 @@ class CTCLossTest(test.TestCase):
self._testCTCLoss(inputs, seq_lens, labels, loss_truth, grad_truth)
+ @test_util.run_deprecated_v1
def test_time_major(self):
"""Testing time_major param.
@@ -269,6 +272,7 @@ class CTCLossTest(test.TestCase):
(tf_loss, tf_loss_transposed) = self.evaluate([loss, loss_transposed])
self.assertAllEqual(tf_loss, tf_loss_transposed)
+ @test_util.run_deprecated_v1
def testInvalidSecondGradient(self):
inputs = np.random.randn(2, 2, 3).astype(np.float32)
inputs_t = constant_op.constant(inputs)
@@ -285,6 +289,7 @@ class CTCLossTest(test.TestCase):
"explicitly disabled"):
_ = gradients_impl._hessian_vector_product(loss, [inputs_t], v)
+ @test_util.run_deprecated_v1
def testEmptyBatch(self):
inputs = constant_op.constant([], dtype=dtypes.float32, shape=(1, 0, 2))
sequence_lengths = constant_op.constant([], dtype=dtypes.int32)
@@ -301,6 +306,7 @@ class CTCLossTest(test.TestCase):
class CTCLossTestV2(test.TestCase):
+ @test_util.run_deprecated_v1
def testCtcLossV2(self):
random_seed.set_random_seed(5)
@@ -345,6 +351,7 @@ class CTCLossTestV2(test.TestCase):
logit_length=logit_length,
blank_index=0))
+ @test_util.run_deprecated_v1
def testCtcLossDenseIsSameAsCtcLoss(self):
with ops.device("/GPU:0" if test.is_gpu_available() else "/CPU:0"):
random_seed.set_random_seed(5)
@@ -398,6 +405,7 @@ class CTCLossTestV2(test.TestCase):
rtol=2e-06,
atol=2e-06)
+ @test_util.run_deprecated_v1
def testCtcLossDenseUniqueFastPathIsSameAsCtcLoss(self):
random_seed.set_random_seed(5)
@@ -451,6 +459,7 @@ class CTCLossTestV2(test.TestCase):
rtol=2e-06,
atol=2e-06)
+ @test_util.run_deprecated_v1
def testCtcLossDenseWithBlankIndexIsSameAsCtcLoss(self):
random_seed.set_random_seed(5)
@@ -507,6 +516,7 @@ class CTCLossTestV2(test.TestCase):
rtol=2e-06,
atol=2e-06)
+ @test_util.run_deprecated_v1
def testCtcLossDenseWithNegativeBlankIndexIsSameAsCtcLoss(self):
with ops.device("/GPU:0" if test.is_gpu_available() else "/CPU:0"):
random_seed.set_random_seed(5)
@@ -555,6 +565,7 @@ class CTCLossTestV2(test.TestCase):
rtol=2e-06,
atol=2e-06)
+ @test_util.run_deprecated_v1
def testCollapseRepeated(self):
collapsed, new_seq_lengths = ctc_ops.collapse_repeated(
labels=[[1, 3, 3, 3, 0],
@@ -568,6 +579,7 @@ class CTCLossTestV2(test.TestCase):
[1, 4, 0, 0],
[4, 2, 9, 4]])
+ @test_util.run_deprecated_v1
def testCollapseRepeatedPreservesDtypes(self):
collapsed, new_seq_lengths = ctc_ops.collapse_repeated(
labels=constant_op.constant(
@@ -585,6 +597,7 @@ class CTCLossTestV2(test.TestCase):
[1, 4, 0, 0],
[4, 2, 9, 4]])
+ @test_util.run_deprecated_v1
def testCollapseRepeatedExtraPadding(self):
collapsed, new_seq_lengths = ctc_ops.collapse_repeated(
labels=[[1, 3, 3, 3, 0, 0, 0],
@@ -598,6 +611,7 @@ class CTCLossTestV2(test.TestCase):
[1, 4, 0, 0],
[4, 2, 9, 4]])
+ @test_util.run_deprecated_v1
def testCollapseRepeatedFrontRepeats(self):
collapsed, new_seq_lengths = ctc_ops.collapse_repeated(
labels=[[1, 1, 1, 2, 2],
@@ -611,6 +625,7 @@ class CTCLossTestV2(test.TestCase):
[1, 2],
[1, 0]])
+ @test_util.run_deprecated_v1
def testCollapseRepeatedAllLabelsTheSame(self):
collapsed, new_seq_lengths = ctc_ops.collapse_repeated(
labels=[[1, 1, 1, 1, 1],
@@ -643,6 +658,7 @@ class CTCLossTestV2(test.TestCase):
self.assertAllEqual(padded_dense, new_dense)
+ @test_util.run_deprecated_v1
def testUnique(self):
labels = [
[3, 4, 4, 3],
@@ -658,6 +674,7 @@ class CTCLossTestV2(test.TestCase):
[0, 0, 0, 1],
], idx)
+ @test_util.run_deprecated_v1
def testSumStates(self):
idx = [
[0, 1, 0, 1],
@@ -677,6 +694,7 @@ class CTCLossTestV2(test.TestCase):
[1.8, 0.8, 0.0, 0.0]]
], sum_of_states)
+ @test_util.run_deprecated_v1
def testStateToOlabel(self):
labels = [
[3, 4, 3, 4],
@@ -715,6 +733,7 @@ class CTCLossTestV2(test.TestCase):
[22.0 + 23.0 + 24.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]],
])
+ @test_util.run_deprecated_v1
def testStateToOlabelUnique(self):
labels = [
[3, 4, 3, 4],
@@ -753,6 +772,7 @@ class CTCLossTestV2(test.TestCase):
[22.0 + 23.0 + 24.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]],
])
+ @test_util.run_deprecated_v1
def testScan(self):
with ops.device("/GPU:0" if test.is_gpu_available() else "/CPU:0"):
out = ctc_ops._scan(
@@ -785,6 +805,7 @@ class CTCLossTestV2(test.TestCase):
constant_op.constant([23.0, 24.0]))
self.assertAllEqual([[23.0, 25.0], [25.0, 28.0], [29.0, 33.0]], out)
+ @test_util.run_deprecated_v1
def testScanCapturesVariables(self):
with self.cached_session() as sess:
x = random_ops.random_uniform([])
@@ -794,6 +815,7 @@ class CTCLossTestV2(test.TestCase):
[23.0 + x * 0.0, 23.0 + x * 1.0, 23.0 + x * 3.0], out
]))
+ @test_util.run_deprecated_v1
def testScanMultipleAccumulators(self):
with ops.device("/GPU:0" if test.is_gpu_available() else "/CPU:0"):
def fn(accum, elem):
@@ -806,6 +828,7 @@ class CTCLossTestV2(test.TestCase):
self.assertAllEqual([24.0, 26.0, 29.0], a)
self.assertAllEqual([[1.0, 2.0], [2.0, 4.0], [6.0, 12.0]], b)
+ @test_util.run_deprecated_v1
def testScanMultipleElements(self):
with ops.device("/GPU:0" if test.is_gpu_available() else "/CPU:0"):
def fn(accum, elem):
diff --git a/tensorflow/python/kernel_tests/cwise_ops_binary_test.py b/tensorflow/python/kernel_tests/cwise_ops_binary_test.py
index 272c2b1dac8..49dbbb125a1 100644
--- a/tensorflow/python/kernel_tests/cwise_ops_binary_test.py
+++ b/tensorflow/python/kernel_tests/cwise_ops_binary_test.py
@@ -196,6 +196,7 @@ class BinaryOpTest(test.TestCase):
self._compareGradientY(x, y, np_func, tf_func)
self._compareGpu(x, y, np_func, tf_func)
+ @test_util.run_deprecated_v1
def testFloatBasic(self):
x = np.linspace(-5, 20, 15).reshape(1, 3, 5).astype(np.float32)
y = np.linspace(20, -5, 15).reshape(1, 3, 5).astype(np.float32)
@@ -233,6 +234,7 @@ class BinaryOpTest(test.TestCase):
except ImportError as e:
tf_logging.warn("Cannot test special functions: %s" % str(e))
+ @test_util.run_deprecated_v1
def testFloatDifferentShapes(self):
x = np.array([1, 2, 3, 4]).reshape(2, 2).astype(np.float32)
y = np.array([1, 2]).reshape(2, 1).astype(np.float32)
@@ -262,6 +264,7 @@ class BinaryOpTest(test.TestCase):
self.assertAllEqual(np_result, left_result)
self.assertAllEqual(np_result, right_result)
+ @test_util.run_deprecated_v1
def testDoubleBasic(self):
x = np.linspace(-5, 20, 15).reshape(1, 3, 5).astype(np.float64)
y = np.linspace(20, -5, 15).reshape(1, 3, 5).astype(np.float64)
@@ -353,6 +356,7 @@ class BinaryOpTest(test.TestCase):
self._compareBoth(x, y, np.floor_divide, _FLOORDIV)
self._compareBoth(x, y, np.mod, _MOD)
+ @test_util.run_deprecated_v1
def testComplex64Basic(self):
x = np.complex(1, 1) * np.linspace(-10, 10, 6).reshape(1, 3, 2).astype(
np.complex64)
@@ -367,6 +371,7 @@ class BinaryOpTest(test.TestCase):
self._compareBoth(x, y, np.multiply, _MUL)
self._compareBoth(x, y + 0.1, np.true_divide, _TRUEDIV)
+ @test_util.run_deprecated_v1
def testComplex128Basic(self):
x = np.complex(1, 1) * np.linspace(-10, 10, 6).reshape(1, 3, 2).astype(
np.complex128)
@@ -480,198 +485,263 @@ class BinaryOpTest(test.TestCase):
]
self._testBCastByFunc(funcs, xs, ys)
+ @test_util.run_deprecated_v1
def testBCast_0A(self):
self._testBCastA([1, 3, 2], [1])
+ @test_util.run_deprecated_v1
def testBCast_0B(self):
self._testBCastB([1, 3, 2], [1])
+ @test_util.run_deprecated_v1
def testBCast_0C(self):
self._testBCastC([1, 3, 2], [1])
+ @test_util.run_deprecated_v1
def testBCast_0D(self):
self._testBCastD([1, 3, 2], [1])
+ @test_util.run_deprecated_v1
def testBCast_1A(self):
self._testBCastA([1, 3, 2], [2])
+ @test_util.run_deprecated_v1
def testBCast_1B(self):
self._testBCastB([1, 3, 2], [2])
+ @test_util.run_deprecated_v1
def testBCast_1C(self):
self._testBCastC([1, 3, 2], [2])
+ @test_util.run_deprecated_v1
def testBCast_1D(self):
self._testBCastD([1, 3, 2], [2])
+ @test_util.run_deprecated_v1
def testBCast_2A(self):
self._testBCastA([1, 3, 2], [3, 2])
+ @test_util.run_deprecated_v1
def testBCast_2B(self):
self._testBCastB([1, 3, 2], [3, 2])
+ @test_util.run_deprecated_v1
def testBCast_2C(self):
self._testBCastC([1, 3, 2], [3, 2])
+ @test_util.run_deprecated_v1
def testBCast_2D(self):
self._testBCastD([1, 3, 2], [3, 2])
+ @test_util.run_deprecated_v1
def testBCast_3A(self):
self._testBCastA([1, 3, 2], [3, 1])
+ @test_util.run_deprecated_v1
def testBCast_3B(self):
self._testBCastB([1, 3, 2], [3, 1])
+ @test_util.run_deprecated_v1
def testBCast_3C(self):
self._testBCastC([1, 3, 2], [3, 1])
+ @test_util.run_deprecated_v1
def testBCast_3D(self):
self._testBCastD([1, 3, 2], [3, 1])
+ @test_util.run_deprecated_v1
def testBCast_4A(self):
self._testBCastA([1, 3, 2], [1, 3, 2])
+ @test_util.run_deprecated_v1
def testBCast_4B(self):
self._testBCastB([1, 3, 2], [1, 3, 2])
+ @test_util.run_deprecated_v1
def testBCast_4C(self):
self._testBCastC([1, 3, 2], [1, 3, 2])
+ @test_util.run_deprecated_v1
def testBCast_4D(self):
self._testBCastD([1, 3, 2], [1, 3, 2])
+ @test_util.run_deprecated_v1
def testBCast_5A(self):
self._testBCastA([1, 3, 2], [2, 3, 1])
+ @test_util.run_deprecated_v1
def testBCast_5B(self):
self._testBCastB([1, 3, 2], [2, 3, 1])
+ @test_util.run_deprecated_v1
def testBCast_5C(self):
self._testBCastC([1, 3, 2], [2, 3, 1])
+ @test_util.run_deprecated_v1
def testBCast_5D(self):
self._testBCastD([1, 3, 2], [2, 3, 1])
+ @test_util.run_deprecated_v1
def testBCast_6A(self):
self._testBCastA([1, 3, 2], [2, 1, 1])
+ @test_util.run_deprecated_v1
def testBCast_6B(self):
self._testBCastB([1, 3, 2], [2, 1, 1])
+ @test_util.run_deprecated_v1
def testBCast_6C(self):
self._testBCastC([1, 3, 2], [2, 1, 1])
+ @test_util.run_deprecated_v1
def testBCast_6D(self):
self._testBCastD([1, 3, 2], [2, 1, 1])
+ @test_util.run_deprecated_v1
def testBCast_7A(self):
self._testBCastA([1, 3, 2], [1, 3, 1])
+ @test_util.run_deprecated_v1
def testBCast_7B(self):
self._testBCastB([1, 3, 2], [1, 3, 1])
+ @test_util.run_deprecated_v1
def testBCast_7C(self):
self._testBCastC([1, 3, 2], [1, 3, 1])
+ @test_util.run_deprecated_v1
def testBCast_7D(self):
self._testBCastD([1, 3, 2], [1, 3, 1])
+ @test_util.run_deprecated_v1
def testBCast_8A(self):
self._testBCastA([2, 1, 5], [2, 3, 1])
+ @test_util.run_deprecated_v1
def testBCast_8B(self):
self._testBCastB([2, 1, 5], [2, 3, 1])
+ @test_util.run_deprecated_v1
def testBCast_8C(self):
self._testBCastC([2, 1, 5], [2, 3, 1])
+ @test_util.run_deprecated_v1
def testBCast_8D(self):
self._testBCastD([2, 1, 5], [2, 3, 1])
+ @test_util.run_deprecated_v1
def testBCast_9A(self):
self._testBCastA([2, 0, 5], [2, 0, 1])
+ @test_util.run_deprecated_v1
def testBCast_9B(self):
self._testBCastB([2, 0, 5], [2, 0, 1])
+ @test_util.run_deprecated_v1
def testBCast_9C(self):
self._testBCastC([2, 0, 5], [2, 0, 1])
+ @test_util.run_deprecated_v1
def testBCast_9D(self):
self._testBCastD([2, 0, 5], [2, 0, 1])
+ @test_util.run_deprecated_v1
def testBCast_10A(self):
self._testBCastA([2, 3, 0], [2, 3, 1])
+ @test_util.run_deprecated_v1
def testBCast_10B(self):
self._testBCastB([2, 3, 0], [2, 3, 1])
+ @test_util.run_deprecated_v1
def testBCast_10C(self):
self._testBCastC([2, 3, 0], [2, 3, 1])
+ @test_util.run_deprecated_v1
def testBCast_10D(self):
self._testBCastD([2, 3, 0], [2, 3, 1])
+ @test_util.run_deprecated_v1
def testBCast_11A(self):
self._testBCastA([1, 3, 2], [1, 3, 2])
+ @test_util.run_deprecated_v1
def testBCast_11B(self):
self._testBCastB([1, 3, 2], [1, 3, 2])
+ @test_util.run_deprecated_v1
def testBCast_11C(self):
self._testBCastC([1, 3, 2], [1, 3, 2])
+ @test_util.run_deprecated_v1
def testBCast_11D(self):
self._testBCastD([1, 3, 2], [1, 3, 2])
+ @test_util.run_deprecated_v1
def testBCast_12A(self):
self._testBCastA([1, 1, 1, 1, 3, 2], [1, 3, 2])
+ @test_util.run_deprecated_v1
def testBCast_12B(self):
self._testBCastB([1, 1, 1, 1, 3, 2], [1, 3, 2])
+ @test_util.run_deprecated_v1
def testBCast_12C(self):
self._testBCastC([1, 1, 1, 1, 3, 2], [1, 3, 2])
+ @test_util.run_deprecated_v1
def testBCast_12D(self):
self._testBCastD([1, 1, 1, 1, 3, 2], [1, 3, 2])
+ @test_util.run_deprecated_v1
def testBCast_13A(self):
self._testBCastA([1, 3, 2, 1, 1], [1])
+ @test_util.run_deprecated_v1
def testBCast_13B(self):
self._testBCastB([1, 3, 2, 1, 1], [1])
+ @test_util.run_deprecated_v1
def testBCast_13C(self):
self._testBCastC([1, 3, 2, 1, 1], [1])
+ @test_util.run_deprecated_v1
def testBCast_13D(self):
self._testBCastD([1, 3, 2, 1, 1], [1])
+ @test_util.run_deprecated_v1
def testBCast_14A(self):
self._testBCastA([2, 3, 1, 1, 5], [1])
+ @test_util.run_deprecated_v1
def testBCast_14B(self):
self._testBCastB([2, 3, 1, 1, 5], [1])
+ @test_util.run_deprecated_v1
def testBCast_14C(self):
self._testBCastC([2, 3, 1, 1, 5], [1])
+ @test_util.run_deprecated_v1
def testBCast_14D(self):
self._testBCastD([2, 3, 1, 1, 5], [1])
+ @test_util.run_deprecated_v1
def testBCast_15A(self):
self._testBCastA([10, 3, 1, 2], [3, 1, 2])
+ @test_util.run_deprecated_v1
def testBCast_15B(self):
self._testBCastB([10, 3, 1, 2], [3, 1, 2])
+ @test_util.run_deprecated_v1
def testBCast_15C(self):
self._testBCastC([10, 3, 1, 2], [3, 1, 2])
+ @test_util.run_deprecated_v1
def testBCast_15D(self):
self._testBCastD([10, 3, 1, 2], [3, 1, 2])
+ @test_util.run_deprecated_v1
def testMismatchedDimensions(self):
for func in [
math_ops.add, math_ops.subtract, math_ops.multiply, math_ops.div, _ADD,
@@ -683,6 +753,7 @@ class BinaryOpTest(test.TestCase):
ops.convert_to_tensor([10.0, 20.0, 30.0]),
ops.convert_to_tensor([[40.0, 50.0], [60.0, 70.0]]))
+ @test_util.run_deprecated_v1
def testZeroPowGrad(self):
with self.cached_session():
for dtype in (np.float16, np.float32, np.float64, np.complex64,
@@ -693,6 +764,7 @@ class BinaryOpTest(test.TestCase):
error = gradient_checker.compute_gradient_error(y, [], z, [])
self.assertEqual(error, 0)
+ @test_util.run_deprecated_v1
def testComplexPowGrad(self):
with self.cached_session():
for dtype in np.complex64, np.complex128:
@@ -861,6 +933,7 @@ class ComparisonOpTest(test.TestCase):
self._testBCastByFunc(
np.not_equal, math_ops.not_equal, include_complex=True)
+ @test_util.run_deprecated_v1
def testShapeMismatch(self):
dtypes = [np.float16, np.float32, np.float64, np.int32, np.int64]
funcs = [
diff --git a/tensorflow/python/kernel_tests/cwise_ops_test.py b/tensorflow/python/kernel_tests/cwise_ops_test.py
index 7e14f95be42..9bb7d8b8b12 100644
--- a/tensorflow/python/kernel_tests/cwise_ops_test.py
+++ b/tensorflow/python/kernel_tests/cwise_ops_test.py
@@ -199,6 +199,7 @@ class ComparisonOpTest(test.TestCase):
self._testBCastByFunc(
np.not_equal, math_ops.not_equal, include_complex=True)
+ @test_util.run_deprecated_v1
def testShapeMismatch(self):
dtypes = [np.float16, np.float32, np.float64, np.int32, np.int64]
funcs = [
@@ -280,6 +281,7 @@ class LogicalOpTest(test.TestCase):
self._compareBinary(x, y, np.logical_or, math_ops.logical_or, use_gpu)
self._compareBinary(x, y, np.logical_xor, math_ops.logical_xor, use_gpu)
+ @test_util.run_deprecated_v1
def testShapeMismatch(self):
x = np.random.randint(0, 2, 6).astype(np.bool).reshape(1, 3, 2)
y = np.random.randint(0, 2, 6).astype(np.bool).reshape(3, 2, 1)
@@ -288,6 +290,7 @@ class LogicalOpTest(test.TestCase):
ValueError, lambda e: "Dimensions must" in str(e)):
f(x, y)
+ @test_util.run_deprecated_v1
def testUsingAsPythonValueFails(self):
# Ensure that we raise an error when the user attempts to treat a
# `Tensor` as a Python `bool`.
@@ -396,6 +399,7 @@ class SelectOpTest(test.TestCase):
if t in [np.float16, np.float32, np.float64]:
self._compare(c, xt, yt, use_gpu=True)
+ @test_util.run_deprecated_v1
def testGradients(self):
c = np.random.randint(0, 2, 6).astype(np.bool).reshape(1, 3, 2)
x = np.random.rand(1, 3, 2) * 100
@@ -415,6 +419,7 @@ class SelectOpTest(test.TestCase):
self._compareGradientX(c, xt, yt)
self._compareGradientY(c, xt, yt)
+ @test_util.run_deprecated_v1
def testShapeMismatch(self):
c = np.random.randint(0, 2, 6).astype(np.bool).reshape(1, 3, 2)
x = np.random.rand(1, 3, 2) * 100
@@ -428,6 +433,7 @@ class SelectOpTest(test.TestCase):
with self.assertRaises(ValueError):
array_ops.where(c, xt, yt)
+ @test_util.run_deprecated_v1
def testEmptyTensor(self):
c = np.random.randint(0, 3, 0).astype(np.bool).reshape(1, 3, 0)
x = np.random.rand(1, 3, 0) * 100
@@ -439,6 +445,7 @@ class SelectOpTest(test.TestCase):
z = array_ops.where(c, xt, yt).eval()
self.assertAllEqual(z_expected, z)
+ @test_util.run_deprecated_v1
def testNan(self):
"""Verify that nans don't propagate where they shouldn't."""
with self.cached_session():
@@ -525,6 +532,7 @@ class BatchSelectOpTest(test.TestCase):
if t in [np.float16, np.float32, np.float64]:
self._compare(c, xt, yt, use_gpu=True)
+ @test_util.run_deprecated_v1
def testGradients(self):
c = np.random.randint(0, 2, 16).astype(np.bool)
x = np.random.rand(16, 2, 8) * 100
@@ -544,6 +552,7 @@ class BatchSelectOpTest(test.TestCase):
self._compareGradientX(c, xt, yt)
self._compareGradientY(c, xt, yt)
+ @test_util.run_deprecated_v1
def testShapeMismatch(self):
c = np.random.randint(0, 2, 8).astype(np.bool)
x = np.random.rand(16, 3, 2) * 100
@@ -622,6 +631,7 @@ class MinMaxOpTest(test.TestCase):
elif x.dtype == np.float64:
self.assertAllClose(jacob_t, jacob_n, rtol=1e-5, atol=1e-5)
+ @test_util.run_deprecated_v1
def testGradients(self):
x = np.random.rand(1, 3, 2) * 100.
# ensure x != y
@@ -898,6 +908,7 @@ class ComplexMakeRealImagTest(test.TestCase):
# build failures on GPU (See #10643 for context).
# self._compareAngle(cplx, use_gpu=True)
+ @test_util.run_deprecated_v1
def testRealReal(self):
for dtype in (dtypes_lib.int32, dtypes_lib.int64, dtypes_lib.float32,
dtypes_lib.float64):
@@ -928,6 +939,7 @@ class ComplexMakeRealImagTest(test.TestCase):
self._compareConj(cplx, use_gpu=False)
self._compareConj(cplx, use_gpu=True)
+ @test_util.run_deprecated_v1
def testConjReal(self):
for dtype in (dtypes_lib.int32, dtypes_lib.int64, dtypes_lib.float16,
dtypes_lib.float32, dtypes_lib.float64):
@@ -935,6 +947,7 @@ class ComplexMakeRealImagTest(test.TestCase):
y = math_ops.conj(x)
self.assertEqual(x, y)
+ @test_util.run_deprecated_v1
def testConjString(self):
x = array_ops.placeholder(dtypes_lib.string)
with self.assertRaisesRegexp(TypeError,
@@ -971,6 +984,7 @@ class ComplexMakeRealImagTest(test.TestCase):
x_, list(x.shape), z, [1], x_init_value=x, delta=epsilon)
self.assertAllClose(jacob_t, jacob_n, rtol=epsilon, atol=epsilon)
+ @test_util.run_deprecated_v1
def testGradient(self):
# complex64
data = np.arange(1, 2, 0.10).reshape([5, 2]).astype(np.float32)
@@ -1006,6 +1020,7 @@ class ComplexMakeRealImagTest(test.TestCase):
inp, list(data.shape), loss, [1], x_init_value=data, delta=epsilon)
self.assertAllClose(jacob_t, jacob_n, rtol=epsilon, atol=epsilon)
+ @test_util.run_deprecated_v1
def testMulGradient(self):
data = np.arange(1, 2, 0.125).reshape([2, 4]).astype(np.float32)
self._compareMulGradient(data)
diff --git a/tensorflow/python/kernel_tests/cwise_ops_unary_test.py b/tensorflow/python/kernel_tests/cwise_ops_unary_test.py
index 3e8294f34bd..709a20f3d0d 100644
--- a/tensorflow/python/kernel_tests/cwise_ops_unary_test.py
+++ b/tensorflow/python/kernel_tests/cwise_ops_unary_test.py
@@ -184,6 +184,7 @@ class UnaryOpTest(test.TestCase):
return func
+ @test_util.run_deprecated_v1
def testFloatBasic(self):
x = np.arange(-3, 3).reshape(1, 3, 2).astype(np.float32)
w = x - x.min() + 1.02 # all greater than 1
@@ -238,12 +239,14 @@ class UnaryOpTest(test.TestCase):
self._compareBothSparse(y, np.sign, math_ops.sign)
self._compareBothSparse(x, np.vectorize(math.erf), math_ops.erf)
+ @test_util.run_deprecated_v1
def testFloatTanhEdge(self):
x = np.arange(40, 40 + 6).reshape(6).astype(np.float32)
self._compareBoth(x, np.tanh, math_ops.tanh)
x = np.arange(-40, -40 + 6).reshape(6).astype(np.float32)
self._compareBoth(x, np.tanh, math_ops.tanh)
+ @test_util.run_deprecated_v1
def testFloatEmpty(self):
x = np.empty((2, 0, 5), dtype=np.float32)
self._compareBoth(x, np.abs, math_ops.abs)
@@ -289,6 +292,7 @@ class UnaryOpTest(test.TestCase):
self._compareBothSparse(x, np.sign, math_ops.sign)
self._compareBothSparse(x, np.sign, math_ops.erf)
+ @test_util.run_deprecated_v1
def testDoubleBasic(self):
x = np.arange(-3, 3).reshape(1, 3, 2).astype(np.float64)
w = x - x.min() + 1.02 # all greater than 1
@@ -342,6 +346,7 @@ class UnaryOpTest(test.TestCase):
self._compareBothSparse(y, np.sign, math_ops.sign)
self._compareBothSparse(x, np.vectorize(math.erf), math_ops.erf)
+ @test_util.run_deprecated_v1
def testHalfBasic(self):
x = np.arange(-3, 3).reshape(1, 3, 2).astype(np.float16)
y = (x + .5).astype(np.float16) # no zero
@@ -414,6 +419,7 @@ class UnaryOpTest(test.TestCase):
self._compareCpu(x, np.square, math_ops.square)
self._compareBothSparse(x, np.square, math_ops.square)
+ @test_util.run_deprecated_v1
def testComplex64Basic(self):
x = np.complex(1, 1) * np.arange(-3, 3).reshape(1, 3, 2).astype(
np.complex64)
@@ -458,6 +464,7 @@ class UnaryOpTest(test.TestCase):
self._compareBoth(y, complex_sign, math_ops.sign)
self._compareBothSparse(y, complex_sign, math_ops.sign)
+ @test_util.run_deprecated_v1
def testComplex128Basic(self):
x = np.complex(1, 1) * np.arange(-3, 3).reshape(1, 3, 2).astype(
np.complex128)
@@ -497,6 +504,7 @@ class UnaryOpTest(test.TestCase):
self._compareBoth(y, complex_sign, math_ops.sign)
self._compareBothSparse(y, complex_sign, math_ops.sign)
+ @test_util.run_deprecated_v1
def testGradGrad(self):
np.random.seed(7)
shape = (5,)
diff --git a/tensorflow/python/kernel_tests/decode_compressed_op_test.py b/tensorflow/python/kernel_tests/decode_compressed_op_test.py
index 1cc1c7da30a..fd871c00906 100644
--- a/tensorflow/python/kernel_tests/decode_compressed_op_test.py
+++ b/tensorflow/python/kernel_tests/decode_compressed_op_test.py
@@ -24,6 +24,7 @@ import zlib
from six import BytesIO
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import parsing_ops
from tensorflow.python.platform import test
@@ -42,6 +43,7 @@ class DecodeCompressedOpTest(test.TestCase):
f.write(bytes_in)
return out.getvalue()
+ @test_util.run_deprecated_v1
def testDecompress(self):
for compression_type in ["ZLIB", "GZIP", ""]:
with self.cached_session():
@@ -55,6 +57,7 @@ class DecodeCompressedOpTest(test.TestCase):
self._compress(b"bBbb", compression_type)]})
self.assertAllEqual([b"AaAA", b"bBbb"], result)
+ @test_util.run_deprecated_v1
def testDecompressWithRaw(self):
for compression_type in ["ZLIB", "GZIP", ""]:
with self.cached_session():
diff --git a/tensorflow/python/kernel_tests/decode_image_op_test.py b/tensorflow/python/kernel_tests/decode_image_op_test.py
index 267afdeb5e1..ba5770001ad 100644
--- a/tensorflow/python/kernel_tests/decode_image_op_test.py
+++ b/tensorflow/python/kernel_tests/decode_image_op_test.py
@@ -23,6 +23,7 @@ import os.path
import numpy as np
from tensorflow.python.framework import errors_impl
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import image_ops
from tensorflow.python.ops import io_ops
import tensorflow.python.ops.nn_grad # pylint: disable=unused-import
@@ -44,6 +45,7 @@ class DecodeImageOpTest(test.TestCase):
self.assertEqual(len(bmp0), 4194)
self.assertAllEqual(image0, image1)
+ @test_util.run_deprecated_v1
def testGif(self):
# Read some real GIFs
path = os.path.join(prefix_path, "gif", "testdata", "scan.gif")
@@ -78,6 +80,7 @@ class DecodeImageOpTest(test.TestCase):
with self.assertRaises(errors_impl.InvalidArgumentError):
self.evaluate(bad_channels)
+ @test_util.run_deprecated_v1
def testJpeg(self):
# Read a real jpeg and verify shape
path = os.path.join(prefix_path, "jpeg", "testdata", "jpeg_merge_test1.jpg")
@@ -108,6 +111,7 @@ class DecodeImageOpTest(test.TestCase):
self.assertEqual(image0.shape, (26, 51, channels or channels_in))
self.assertAllEqual(image0, image1)
+ @test_util.run_deprecated_v1
def testInvalidBytes(self):
image_bytes = b"ThisIsNotAnImage!"
decode = image_ops.decode_image(image_bytes)
diff --git a/tensorflow/python/kernel_tests/decode_raw_op_test.py b/tensorflow/python/kernel_tests/decode_raw_op_test.py
index dcc984811cb..008e59ba3e6 100644
--- a/tensorflow/python/kernel_tests/decode_raw_op_test.py
+++ b/tensorflow/python/kernel_tests/decode_raw_op_test.py
@@ -21,6 +21,7 @@ from __future__ import print_function
import numpy as np
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import parsing_ops
from tensorflow.python.platform import test
@@ -28,6 +29,7 @@ from tensorflow.python.platform import test
class DecodeRawOpTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testToUint8(self):
with self.cached_session():
in_bytes = array_ops.placeholder(dtypes.string, shape=[2])
@@ -46,6 +48,7 @@ class DecodeRawOpTest(test.TestCase):
"element 1 has size 5 != 6"):
decode.eval(feed_dict={in_bytes: ["short", "longer"]})
+ @test_util.run_deprecated_v1
def testToInt16(self):
with self.cached_session():
in_bytes = array_ops.placeholder(dtypes.string, shape=[None])
@@ -61,6 +64,7 @@ class DecodeRawOpTest(test.TestCase):
"size of int16"):
decode.eval(feed_dict={in_bytes: ["123", "456"]})
+ @test_util.run_deprecated_v1
def testEndianness(self):
with self.cached_session():
in_bytes = array_ops.placeholder(dtypes.string, shape=[None])
@@ -73,6 +77,7 @@ class DecodeRawOpTest(test.TestCase):
result = decode_be.eval(feed_dict={in_bytes: ["\x01\x02\x03\x04"]})
self.assertAllEqual([[0x01020304]], result)
+ @test_util.run_deprecated_v1
def testToFloat16(self):
with self.cached_session():
in_bytes = array_ops.placeholder(dtypes.string, shape=[None])
@@ -84,6 +89,7 @@ class DecodeRawOpTest(test.TestCase):
self.assertAllEqual(expected_result, result)
+ @test_util.run_deprecated_v1
def testEmptyStringInput(self):
with self.cached_session():
in_bytes = array_ops.placeholder(dtypes.string, shape=[None])
@@ -93,6 +99,7 @@ class DecodeRawOpTest(test.TestCase):
result = decode.eval(feed_dict={in_bytes: [""] * num_inputs})
self.assertEqual((num_inputs, 0), result.shape)
+ @test_util.run_deprecated_v1
def testToUInt16(self):
with self.cached_session():
in_bytes = array_ops.placeholder(dtypes.string, shape=[None])
diff --git a/tensorflow/python/kernel_tests/denormal_test.py b/tensorflow/python/kernel_tests/denormal_test.py
index 71a528c4aa2..80a3033ecc4 100644
--- a/tensorflow/python/kernel_tests/denormal_test.py
+++ b/tensorflow/python/kernel_tests/denormal_test.py
@@ -22,6 +22,7 @@ import numpy as np
import platform
from tensorflow.python.framework import constant_op
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.platform import test
@@ -50,10 +51,12 @@ class DenormalTest(test.TestCase):
# Make sure the flags don't leak out
self.testPythonHasDenormals()
+ @test_util.run_deprecated_v1
def testFlushDenormalsCPU(self):
# On CPUs, the processor flags flush for both single and double precision.
self._flushDenormalsTest(use_gpu=False, dtypes=(np.float32, np.float64))
+ @test_util.run_deprecated_v1
def testFlushDenormalsGPU(self):
# On GPUs, only single precision can flush to zero.
self._flushDenormalsTest(use_gpu=True, dtypes=(np.float32,))
diff --git a/tensorflow/python/kernel_tests/dense_update_ops_no_tsan_test.py b/tensorflow/python/kernel_tests/dense_update_ops_no_tsan_test.py
index 0676664685d..4f74e1e7412 100644
--- a/tensorflow/python/kernel_tests/dense_update_ops_no_tsan_test.py
+++ b/tensorflow/python/kernel_tests/dense_update_ops_no_tsan_test.py
@@ -20,6 +20,7 @@ from __future__ import print_function
import numpy as np
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import state_ops
@@ -32,6 +33,7 @@ class AssignOpTest(test.TestCase):
# NOTE(mrry): We exclude thess tests from the TSAN TAP target, because they
# contain benign and deliberate data races when multiple threads update
# the same parameters without a lock.
+ @test_util.run_deprecated_v1
def testParallelUpdateWithoutLocking(self):
with self.cached_session() as sess:
ones_t = array_ops.fill([1024, 1024], 1.0)
@@ -59,6 +61,7 @@ class AssignOpTest(test.TestCase):
self.assertTrue((vals >= ones).all())
self.assertTrue((vals <= ones * 20).all())
+ @test_util.run_deprecated_v1
def testParallelAssignWithoutLocking(self):
with self.cached_session() as sess:
ones_t = array_ops.fill([1024, 1024], float(1))
@@ -91,6 +94,7 @@ class AssignOpTest(test.TestCase):
# contain non-benign but known data races between the variable assignment and
# returning the output tensors. This issue will be resolved with the new
# resource variables.
+ @test_util.run_deprecated_v1
def testParallelUpdateWithLocking(self):
with self.cached_session() as sess:
zeros_t = array_ops.fill([1024, 1024], 0.0)
@@ -118,6 +122,7 @@ class AssignOpTest(test.TestCase):
ones = np.ones((1024, 1024)).astype(np.float32)
self.assertAllEqual(vals, ones * 20)
+ @test_util.run_deprecated_v1
def testParallelAssignWithLocking(self):
with self.cached_session() as sess:
zeros_t = array_ops.fill([1024, 1024], 0.0)
diff --git a/tensorflow/python/kernel_tests/dense_update_ops_test.py b/tensorflow/python/kernel_tests/dense_update_ops_test.py
index a4766fed72e..309da88bef7 100644
--- a/tensorflow/python/kernel_tests/dense_update_ops_test.py
+++ b/tensorflow/python/kernel_tests/dense_update_ops_test.py
@@ -21,6 +21,7 @@ from __future__ import print_function
import numpy as np
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import state_ops
from tensorflow.python.ops import variables
@@ -81,9 +82,11 @@ class AssignOpTest(test.TestCase):
self.assertAllEqual(x - y, var_value)
self.assertAllEqual(x - y, op_value)
+ @test_util.run_deprecated_v1
def testBasic(self):
self._testTypes(np.arange(0, 20).reshape([4, 5]))
+ @test_util.run_deprecated_v1
def testAssignNonStrictShapeChecking(self):
with self.cached_session():
data = array_ops.fill([1024, 1024], 0)
@@ -98,6 +101,7 @@ class AssignOpTest(test.TestCase):
a2.op.run()
self.assertAllEqual(p.eval(), self.evaluate(data2))
+ @test_util.run_deprecated_v1
def testInitRequiredAssignAdd(self):
with self.cached_session():
p = variables.VariableV1(array_ops.fill([1024, 1024], 1), dtypes.int32)
@@ -105,6 +109,7 @@ class AssignOpTest(test.TestCase):
with self.assertRaisesOpError("use uninitialized"):
a.op.run()
+ @test_util.run_deprecated_v1
def testInitRequiredAssignSub(self):
with self.cached_session():
p = variables.VariableV1(array_ops.fill([1024, 1024], 1), dtypes.int32)
diff --git a/tensorflow/python/kernel_tests/depthtospace_op_test.py b/tensorflow/python/kernel_tests/depthtospace_op_test.py
index 19f145865fd..96c9b5258e2 100644
--- a/tensorflow/python/kernel_tests/depthtospace_op_test.py
+++ b/tensorflow/python/kernel_tests/depthtospace_op_test.py
@@ -53,12 +53,14 @@ class DepthToSpaceTest(test.TestCase):
output_nhwc = test_util.NCHWToNHWC(output_nchw)
self.assertAllEqual(output_nhwc.eval(), outputs)
+ @test_util.run_deprecated_v1
def testBasic(self):
x_np = [[[[1, 2, 3, 4]]]]
block_size = 2
x_out = [[[[1], [2]], [[3], [4]]]]
self._testOne(x_np, block_size, x_out)
+ @test_util.run_deprecated_v1
def testBasicFloat16(self):
x_np = [[[[1, 2, 3, 4]]]]
block_size = 2
@@ -67,6 +69,7 @@ class DepthToSpaceTest(test.TestCase):
# Tests for larger input dimensions. To make sure elements are
# correctly ordered spatially.
+ @test_util.run_deprecated_v1
def testBlockSize2(self):
x_np = [[[[1, 2, 3, 4],
[5, 6, 7, 8]],
@@ -79,6 +82,7 @@ class DepthToSpaceTest(test.TestCase):
[[11], [12], [15], [16]]]]
self._testOne(x_np, block_size, x_out)
+ @test_util.run_deprecated_v1
def testBlockSize2Batch10(self):
block_size = 2
def batch_input_elt(i):
@@ -115,6 +119,7 @@ class DepthToSpaceTest(test.TestCase):
self.evaluate(x_tf)
# Tests for different width and height.
+ @test_util.run_deprecated_v1
def testNonSquare(self):
x_np = [[[[1, 10, 2, 20, 3, 30, 4, 40]],
[[5, 50, 6, 60, 7, 70, 8, 80]],
@@ -130,6 +135,7 @@ class DepthToSpaceTest(test.TestCase):
# Tests for larger input dimensions. To make sure elements are
# correctly ordered spatially.
+ @test_util.run_deprecated_v1
def testBlockSize4FlatInput(self):
x_np = [[[[1, 2, 5, 6, 3, 4, 7, 8, 9, 10, 13, 14, 11, 12, 15, 16]]]]
block_size = 4
@@ -141,6 +147,7 @@ class DepthToSpaceTest(test.TestCase):
# Tests for larger input depths.
# To make sure elements are properly interleaved in depth.
+ @test_util.run_deprecated_v1
def testDepthInterleaved(self):
x_np = [[[[1, 10, 2, 20, 3, 30, 4, 40]]]]
block_size = 2
@@ -150,6 +157,7 @@ class DepthToSpaceTest(test.TestCase):
# Tests for larger input depths. Here an odd depth.
# To make sure elements are properly interleaved in depth.
+ @test_util.run_deprecated_v1
def testDepthInterleavedDepth3(self):
x_np = [[[[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]]]]
block_size = 2
@@ -159,6 +167,7 @@ class DepthToSpaceTest(test.TestCase):
# Tests for larger input depths.
# To make sure elements are properly interleaved in depth.
+ @test_util.run_deprecated_v1
def testDepthInterleavedLarger(self):
x_np = [[[[1, 10, 2, 20, 3, 30, 4, 40],
[5, 50, 6, 60, 7, 70, 8, 80]],
@@ -175,6 +184,7 @@ class DepthToSpaceTest(test.TestCase):
# Tests for a block larger for the depth. In this case should raise an
# exception.
+ @test_util.run_deprecated_v1
def testBlockSizeTooLarge(self):
x_np = [[[[1, 2, 3, 4],
[5, 6, 7, 8]],
@@ -188,6 +198,7 @@ class DepthToSpaceTest(test.TestCase):
self.evaluate(out_tf)
# Test when the block size is 0.
+ @test_util.run_deprecated_v1
def testBlockSize0(self):
x_np = [[[[1], [2]],
[[3], [4]]]]
@@ -197,6 +208,7 @@ class DepthToSpaceTest(test.TestCase):
self.evaluate(out_tf)
# Test when the block size is 1. The block size should be > 1.
+ @test_util.run_deprecated_v1
def testBlockSizeOne(self):
x_np = [[[[1, 1, 1, 1],
[2, 2, 2, 2]],
@@ -207,6 +219,7 @@ class DepthToSpaceTest(test.TestCase):
out_tf = array_ops.depth_to_space(x_np, block_size)
self.evaluate(out_tf)
+ @test_util.run_deprecated_v1
def testBlockSizeLargerThanInput(self):
# The block size is too large for this input.
x_np = [[[[1], [2]],
@@ -216,6 +229,7 @@ class DepthToSpaceTest(test.TestCase):
out_tf = array_ops.space_to_depth(x_np, block_size)
self.evaluate(out_tf)
+ @test_util.run_deprecated_v1
def testBlockSizeNotDivisibleDepth(self):
# The depth is not divisible by the square of the block size.
x_np = [[[[1, 1, 1, 1],
@@ -226,6 +240,7 @@ class DepthToSpaceTest(test.TestCase):
with self.assertRaises(ValueError):
_ = array_ops.space_to_depth(x_np, block_size)
+ @test_util.run_deprecated_v1
def testUnknownShape(self):
t = array_ops.depth_to_space(
array_ops.placeholder(dtypes.float32), block_size=4)
@@ -343,11 +358,13 @@ class DepthToSpaceGradientTest(test.TestCase):
# Don't use very large numbers as dimensions here, as the result is tensor
# with cartesian product of the dimensions.
+ @test_util.run_deprecated_v1
def testSmall(self):
block_size = 2
self._compare(3, 2, 5, 3, block_size, "NHWC")
self._compare(3, 2, 5, 3, block_size, "NCHW")
+ @test_util.run_deprecated_v1
def testSmall2(self):
block_size = 3
self._compare(1, 2, 3, 2, block_size, "NHWC")
diff --git a/tensorflow/python/kernel_tests/diag_op_test.py b/tensorflow/python/kernel_tests/diag_op_test.py
index f7a9cd8d6e2..ed2a9e8e47e 100644
--- a/tensorflow/python/kernel_tests/diag_op_test.py
+++ b/tensorflow/python/kernel_tests/diag_op_test.py
@@ -22,6 +22,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes as dtypes_lib
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import gradients_impl
@@ -31,6 +32,7 @@ from tensorflow.python.platform import tf_logging
class MatrixDiagTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testVector(self):
with self.session(use_gpu=True):
v = np.array([1.0, 2.0, 3.0])
@@ -49,6 +51,7 @@ class MatrixDiagTest(test.TestCase):
self.assertEqual((2, 3, 3), v_batch_diag.get_shape())
self.assertAllEqual(v_batch_diag.eval(), mat_batch)
+ @test_util.run_deprecated_v1
def testBatchVector(self):
self._testBatchVector(np.float32)
self._testBatchVector(np.float64)
@@ -56,16 +59,19 @@ class MatrixDiagTest(test.TestCase):
self._testBatchVector(np.int64)
self._testBatchVector(np.bool)
+ @test_util.run_deprecated_v1
def testInvalidShape(self):
with self.assertRaisesRegexp(ValueError, "must be at least rank 1"):
array_ops.matrix_diag(0)
+ @test_util.run_deprecated_v1
def testInvalidShapeAtEval(self):
with self.session(use_gpu=True):
v = array_ops.placeholder(dtype=dtypes_lib.float32)
with self.assertRaisesOpError("input must be at least 1-dim"):
array_ops.matrix_diag(v).eval(feed_dict={v: 0.0})
+ @test_util.run_deprecated_v1
def testGrad(self):
shapes = ((3,), (7, 4))
with self.session(use_gpu=True):
@@ -81,6 +87,7 @@ class MatrixDiagTest(test.TestCase):
class MatrixSetDiagTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testSquare(self):
with self.session(use_gpu=True):
v = np.array([1.0, 2.0, 3.0])
@@ -91,6 +98,7 @@ class MatrixSetDiagTest(test.TestCase):
self.assertEqual((3, 3), output.get_shape())
self.assertAllEqual(mat_set_diag, self.evaluate(output))
+ @test_util.run_deprecated_v1
def testRectangular(self):
with self.session(use_gpu=True):
v = np.array([3.0, 4.0])
@@ -123,6 +131,7 @@ class MatrixSetDiagTest(test.TestCase):
self.assertEqual((2, 3, 3), output.get_shape())
self.assertAllEqual(mat_set_diag_batch, self.evaluate(output))
+ @test_util.run_deprecated_v1
def testSquareBatch(self):
self._testSquareBatch(np.float32)
self._testSquareBatch(np.float64)
@@ -130,6 +139,7 @@ class MatrixSetDiagTest(test.TestCase):
self._testSquareBatch(np.int64)
self._testSquareBatch(np.bool)
+ @test_util.run_deprecated_v1
def testRectangularBatch(self):
with self.session(use_gpu=True):
v_batch = np.array([[-1.0, -2.0], [-4.0, -5.0]])
@@ -142,12 +152,14 @@ class MatrixSetDiagTest(test.TestCase):
self.assertEqual((2, 2, 3), output.get_shape())
self.assertAllEqual(mat_set_diag_batch, self.evaluate(output))
+ @test_util.run_deprecated_v1
def testInvalidShape(self):
with self.assertRaisesRegexp(ValueError, "must be at least rank 2"):
array_ops.matrix_set_diag(0, [0])
with self.assertRaisesRegexp(ValueError, "must be at least rank 1"):
array_ops.matrix_set_diag([[0]], 0)
+ @test_util.run_deprecated_v1
def testInvalidShapeAtEval(self):
with self.session(use_gpu=True):
v = array_ops.placeholder(dtype=dtypes_lib.float32)
@@ -157,6 +169,7 @@ class MatrixSetDiagTest(test.TestCase):
r"but received input shape: \[1,1\] and diagonal shape: \[\]"):
array_ops.matrix_set_diag([[v]], v).eval(feed_dict={v: 0.0})
+ @test_util.run_deprecated_v1
def testGrad(self):
shapes = ((3, 4, 4), (3, 3, 4), (3, 4, 3), (7, 4, 8, 8))
with self.session(use_gpu=True):
@@ -178,6 +191,7 @@ class MatrixSetDiagTest(test.TestCase):
y.get_shape().as_list())
self.assertLess(error_x_diag, 1e-4)
+ @test_util.run_deprecated_v1
def testGradWithNoShapeInformation(self):
with self.session(use_gpu=True) as sess:
v = array_ops.placeholder(dtype=dtypes_lib.float32)
@@ -200,6 +214,7 @@ class MatrixSetDiagTest(test.TestCase):
class MatrixDiagPartTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testSquare(self):
with self.session(use_gpu=True):
v = np.array([1.0, 2.0, 3.0])
@@ -208,6 +223,7 @@ class MatrixDiagPartTest(test.TestCase):
self.assertEqual((3,), mat_diag.get_shape())
self.assertAllEqual(mat_diag.eval(), v)
+ @test_util.run_deprecated_v1
def testRectangular(self):
with self.session(use_gpu=True):
mat = np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]])
@@ -228,6 +244,7 @@ class MatrixDiagPartTest(test.TestCase):
self.assertEqual((2, 3), mat_batch_diag.get_shape())
self.assertAllEqual(mat_batch_diag.eval(), v_batch)
+ @test_util.run_deprecated_v1
def testSquareBatch(self):
self._testSquareBatch(np.float32)
self._testSquareBatch(np.float64)
@@ -235,6 +252,7 @@ class MatrixDiagPartTest(test.TestCase):
self._testSquareBatch(np.int64)
self._testSquareBatch(np.bool)
+ @test_util.run_deprecated_v1
def testRectangularBatch(self):
with self.session(use_gpu=True):
v_batch = np.array([[1.0, 2.0], [4.0, 5.0]])
@@ -245,16 +263,19 @@ class MatrixDiagPartTest(test.TestCase):
self.assertEqual((2, 2), mat_batch_diag.get_shape())
self.assertAllEqual(mat_batch_diag.eval(), v_batch)
+ @test_util.run_deprecated_v1
def testInvalidShape(self):
with self.assertRaisesRegexp(ValueError, "must be at least rank 2"):
array_ops.matrix_diag_part(0)
+ @test_util.run_deprecated_v1
def testInvalidShapeAtEval(self):
with self.session(use_gpu=True):
v = array_ops.placeholder(dtype=dtypes_lib.float32)
with self.assertRaisesOpError("input must be at least 2-dim"):
array_ops.matrix_diag_part(v).eval(feed_dict={v: 0.0})
+ @test_util.run_deprecated_v1
def testGrad(self):
shapes = ((3, 3), (2, 3), (3, 2), (5, 3, 3))
with self.session(use_gpu=True):
@@ -407,6 +428,7 @@ class DiagTest(test.TestCase):
dtype=dtype)
self.diagOp(x, dtype, expected_ans)
+ @test_util.run_deprecated_v1
def testInvalidRank(self):
with self.assertRaisesRegexp(ValueError, "must be at least rank 1"):
array_ops.diag(0.0)
@@ -476,6 +498,7 @@ class DiagPartOpTest(test.TestCase):
self.diagPartOp(x, np.complex64, expected_ans)
self.diagPartOp(x, np.complex128, expected_ans)
+ @test_util.run_deprecated_v1
def testOddRank(self):
w = np.random.rand(2)
x = np.random.rand(2, 2, 2)
@@ -484,6 +507,7 @@ class DiagPartOpTest(test.TestCase):
with self.assertRaises(ValueError):
array_ops.diag_part(0.0)
+ @test_util.run_deprecated_v1
def testUnevenDimensions(self):
w = np.random.rand(2, 5)
x = np.random.rand(2, 1, 2, 3)
@@ -493,6 +517,7 @@ class DiagPartOpTest(test.TestCase):
class DiagGradOpTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testDiagGrad(self):
np.random.seed(0)
shapes = ((3,), (3, 3), (3, 3, 3))
@@ -513,6 +538,7 @@ class DiagGradOpTest(test.TestCase):
class DiagGradPartOpTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testDiagPartGrad(self):
np.random.seed(0)
shapes = ((3, 3), (3, 3, 3, 3))
diff --git a/tensorflow/python/kernel_tests/distributions/bernoulli_test.py b/tensorflow/python/kernel_tests/distributions/bernoulli_test.py
index 37b35ba51a8..e6d560b4bc4 100644
--- a/tensorflow/python/kernel_tests/distributions/bernoulli_test.py
+++ b/tensorflow/python/kernel_tests/distributions/bernoulli_test.py
@@ -151,6 +151,7 @@ class BernoulliTest(test.TestCase):
self.assertAllClose(self.evaluate(dist.prob(x)), expected_pmf)
self.assertAllClose(self.evaluate(dist.log_prob(x)), np.log(expected_pmf))
+ @test_util.run_deprecated_v1
def testPmfCorrectBroadcastDynamicShape(self):
with self.cached_session():
p = array_ops.placeholder(dtype=dtypes.float32)
@@ -167,6 +168,7 @@ class BernoulliTest(test.TestCase):
}), [[0.2, 0.7, 0.4]])
@test_util.run_in_graph_and_eager_modes
+ @test_util.run_deprecated_v1
def testPmfInvalid(self):
p = [0.1, 0.2, 0.7]
dist = bernoulli.Bernoulli(probs=p, validate_args=True)
@@ -193,6 +195,7 @@ class BernoulliTest(test.TestCase):
self.evaluate(
bernoulli.Bernoulli(probs=p, validate_args=False).log_prob(samps)))
+ @test_util.run_deprecated_v1
def testBroadcasting(self):
with self.cached_session():
p = array_ops.placeholder(dtypes.float32)
@@ -207,6 +210,7 @@ class BernoulliTest(test.TestCase):
p: [0.5, 0.5, 0.5]
}))
+ @test_util.run_deprecated_v1
def testPmfShapes(self):
with self.cached_session():
p = array_ops.placeholder(dtypes.float32, shape=[None, 1])
@@ -276,6 +280,7 @@ class BernoulliTest(test.TestCase):
grad_p = tape.gradient(samples, p)
self.assertIsNone(grad_p)
+ @test_util.run_deprecated_v1
def testSampleActsLikeSampleN(self):
with self.cached_session() as sess:
p = [0.2, 0.6]
diff --git a/tensorflow/python/kernel_tests/distributions/bijector_test.py b/tensorflow/python/kernel_tests/distributions/bijector_test.py
index e20f59f48ac..a0e0a36fecc 100644
--- a/tensorflow/python/kernel_tests/distributions/bijector_test.py
+++ b/tensorflow/python/kernel_tests/distributions/bijector_test.py
@@ -132,6 +132,7 @@ class BijectorTestEventNdims(test.TestCase):
with self.assertRaisesRegexp(ValueError, "Expected scalar"):
bij.inverse_log_det_jacobian(1., event_ndims=(1, 2))
+ @test_util.run_deprecated_v1
def testBijectorDynamicEventNdims(self):
bij = BrokenBijector(validate_args=True)
event_ndims = array_ops.placeholder(dtype=np.int32, shape=None)
@@ -301,6 +302,7 @@ class BijectorReduceEventDimsTest(test.TestCase):
8.,
self.evaluate(bij.inverse_log_det_jacobian(x, event_ndims=2)))
+ @test_util.run_deprecated_v1
def testHandlesNonStaticEventNdims(self):
x_ = [[[1., 2.], [3., 4.]]]
x = array_ops.placeholder_with_default(x_, shape=None)
diff --git a/tensorflow/python/kernel_tests/distributions/categorical_test.py b/tensorflow/python/kernel_tests/distributions/categorical_test.py
index 9c593d2737a..ec1d4ed2070 100644
--- a/tensorflow/python/kernel_tests/distributions/categorical_test.py
+++ b/tensorflow/python/kernel_tests/distributions/categorical_test.py
@@ -25,6 +25,7 @@ from tensorflow.python.eager import backprop
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import tensor_util
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradients_impl
from tensorflow.python.ops import math_ops
@@ -44,6 +45,7 @@ def make_categorical(batch_shape, num_classes, dtype=dtypes.int32):
class CategoricalTest(test.TestCase, parameterized.TestCase):
+ @test_util.run_deprecated_v1
def testP(self):
p = [0.2, 0.8]
dist = categorical.Categorical(probs=p)
@@ -51,6 +53,7 @@ class CategoricalTest(test.TestCase, parameterized.TestCase):
self.assertAllClose(p, dist.probs.eval())
self.assertAllEqual([2], dist.logits.get_shape())
+ @test_util.run_deprecated_v1
def testLogits(self):
p = np.array([0.2, 0.8], dtype=np.float32)
logits = np.log(p) - 50.
@@ -61,6 +64,7 @@ class CategoricalTest(test.TestCase, parameterized.TestCase):
self.assertAllClose(dist.probs.eval(), p)
self.assertAllClose(dist.logits.eval(), logits)
+ @test_util.run_deprecated_v1
def testShapes(self):
with self.cached_session():
for batch_shape in ([], [1], [2, 3, 4]):
@@ -107,6 +111,7 @@ class CategoricalTest(test.TestCase, parameterized.TestCase):
self.assertEqual(dist.dtype, dtype)
self.assertEqual(dist.dtype, dist.sample(5).dtype)
+ @test_util.run_deprecated_v1
def testUnknownShape(self):
with self.cached_session():
logits = array_ops.placeholder(dtype=dtypes.float32)
@@ -121,18 +126,21 @@ class CategoricalTest(test.TestCase, parameterized.TestCase):
feed_dict={logits: [[-1000.0, 1000.0], [1000.0, -1000.0]]})
self.assertAllEqual([1, 0], sample_value_batch)
+ @test_util.run_deprecated_v1
def testPMFWithBatch(self):
histograms = [[0.2, 0.8], [0.6, 0.4]]
dist = categorical.Categorical(math_ops.log(histograms) - 50.)
with self.cached_session():
self.assertAllClose(dist.prob([0, 1]).eval(), [0.2, 0.4])
+ @test_util.run_deprecated_v1
def testPMFNoBatch(self):
histograms = [0.2, 0.8]
dist = categorical.Categorical(math_ops.log(histograms) - 50.)
with self.cached_session():
self.assertAllClose(dist.prob(0).eval(), 0.2)
+ @test_util.run_deprecated_v1
def testCDFWithDynamicEventShapeKnownNdims(self):
"""Test that dynamically-sized events with unknown shape work."""
batch_size = 2
@@ -184,6 +192,7 @@ class CategoricalTest(test.TestCase, parameterized.TestCase):
actual_cdf = self.evaluate(cdf_op)
self.assertAllClose(actual_cdf, expected_cdf)
+ @test_util.run_deprecated_v1
def testCDFWithBatch(self):
histograms = [[0.1, 0.2, 0.3, 0.25, 0.15],
[0.0, 0.75, 0.2, 0.05, 0.0]]
@@ -195,6 +204,7 @@ class CategoricalTest(test.TestCase, parameterized.TestCase):
with self.cached_session():
self.assertAllClose(cdf_op.eval(), expected_cdf)
+ @test_util.run_deprecated_v1
def testCDFNoBatch(self):
histogram = [0.1, 0.2, 0.3, 0.4]
event = 2
@@ -205,6 +215,7 @@ class CategoricalTest(test.TestCase, parameterized.TestCase):
with self.cached_session():
self.assertAlmostEqual(cdf_op.eval(), expected_cdf)
+ @test_util.run_deprecated_v1
def testCDFBroadcasting(self):
# shape: [batch=2, n_bins=3]
histograms = [[0.2, 0.1, 0.7],
@@ -298,6 +309,7 @@ class CategoricalTest(test.TestCase, parameterized.TestCase):
self.assertAllEqual(run_result["cat_log_cdf"].shape,
run_result["norm_log_cdf"].shape)
+ @test_util.run_deprecated_v1
def testLogPMF(self):
logits = np.log([[0.2, 0.8], [0.6, 0.4]]) - 50.
dist = categorical.Categorical(logits)
@@ -305,6 +317,7 @@ class CategoricalTest(test.TestCase, parameterized.TestCase):
self.assertAllClose(dist.log_prob([0, 1]).eval(), np.log([0.2, 0.4]))
self.assertAllClose(dist.log_prob([0.0, 1.0]).eval(), np.log([0.2, 0.4]))
+ @test_util.run_deprecated_v1
def testEntropyNoBatch(self):
logits = np.log([0.2, 0.8]) - 50.
dist = categorical.Categorical(logits)
@@ -312,6 +325,7 @@ class CategoricalTest(test.TestCase, parameterized.TestCase):
self.assertAllClose(dist.entropy().eval(),
-(0.2 * np.log(0.2) + 0.8 * np.log(0.8)))
+ @test_util.run_deprecated_v1
def testEntropyWithBatch(self):
logits = np.log([[0.2, 0.8], [0.6, 0.4]]) - 50.
dist = categorical.Categorical(logits)
@@ -321,6 +335,7 @@ class CategoricalTest(test.TestCase, parameterized.TestCase):
-(0.6 * np.log(0.6) + 0.4 * np.log(0.4))
])
+ @test_util.run_deprecated_v1
def testEntropyGradient(self):
with self.cached_session() as sess:
logits = constant_op.constant([[1., 2., 3.], [2., 5., 1.]])
@@ -440,12 +455,14 @@ class CategoricalTest(test.TestCase, parameterized.TestCase):
self.assertEqual(3, log_prob.get_shape().ndims)
self.assertAllEqual([2, 2, 2], log_prob.get_shape())
+ @test_util.run_deprecated_v1
def testMode(self):
with self.cached_session():
histograms = [[[0.2, 0.8], [0.6, 0.4]]]
dist = categorical.Categorical(math_ops.log(histograms) - 50.)
self.assertAllEqual(dist.mode().eval(), [[1, 0]])
+ @test_util.run_deprecated_v1
def testCategoricalCategoricalKL(self):
def np_softmax(logits):
diff --git a/tensorflow/python/kernel_tests/distributions/dirichlet_multinomial_test.py b/tensorflow/python/kernel_tests/distributions/dirichlet_multinomial_test.py
index 3662ca1ad1f..c530037e1ed 100644
--- a/tensorflow/python/kernel_tests/distributions/dirichlet_multinomial_test.py
+++ b/tensorflow/python/kernel_tests/distributions/dirichlet_multinomial_test.py
@@ -22,6 +22,7 @@ from tensorflow.python.eager import backprop
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import tensor_shape
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.ops.distributions import dirichlet_multinomial
@@ -36,6 +37,7 @@ class DirichletMultinomialTest(test.TestCase):
def setUp(self):
self._rng = np.random.RandomState(42)
+ @test_util.run_deprecated_v1
def testSimpleShapes(self):
with self.cached_session():
alpha = np.random.rand(3)
@@ -45,6 +47,7 @@ class DirichletMultinomialTest(test.TestCase):
self.assertEqual(tensor_shape.TensorShape([3]), dist.event_shape)
self.assertEqual(tensor_shape.TensorShape([]), dist.batch_shape)
+ @test_util.run_deprecated_v1
def testComplexShapes(self):
with self.cached_session():
alpha = np.random.rand(3, 2, 2)
@@ -55,6 +58,7 @@ class DirichletMultinomialTest(test.TestCase):
self.assertEqual(tensor_shape.TensorShape([2]), dist.event_shape)
self.assertEqual(tensor_shape.TensorShape([3, 2]), dist.batch_shape)
+ @test_util.run_deprecated_v1
def testNproperty(self):
alpha = [[1., 2, 3]]
n = [[5.]]
@@ -63,6 +67,7 @@ class DirichletMultinomialTest(test.TestCase):
self.assertEqual([1, 1], dist.total_count.get_shape())
self.assertAllClose(n, dist.total_count.eval())
+ @test_util.run_deprecated_v1
def testAlphaProperty(self):
alpha = [[1., 2, 3]]
with self.cached_session():
@@ -70,6 +75,7 @@ class DirichletMultinomialTest(test.TestCase):
self.assertEqual([1, 3], dist.concentration.get_shape())
self.assertAllClose(alpha, dist.concentration.eval())
+ @test_util.run_deprecated_v1
def testPmfNandCountsAgree(self):
alpha = [[1., 2, 3]]
n = [[5.]]
@@ -83,6 +89,7 @@ class DirichletMultinomialTest(test.TestCase):
"last-dimension must sum to `self.total_count`"):
dist.prob([3., 3, 0]).eval()
+ @test_util.run_deprecated_v1
def testPmfNonIntegerCounts(self):
alpha = [[1., 2, 3]]
n = [[5.]]
@@ -178,6 +185,7 @@ class DirichletMultinomialTest(test.TestCase):
self.assertAllClose([1 / 3., 2 / 5.], self.evaluate(pmf))
self.assertAllEqual([2], pmf.get_shape())
+ @test_util.run_deprecated_v1
def testPmfForOneVoteIsTheMeanWithOneRecordInput(self):
# The probabilities of one vote falling into class k is the mean for class
# k.
@@ -194,6 +202,7 @@ class DirichletMultinomialTest(test.TestCase):
self.assertAllEqual([3], mean.shape)
self.assertAllEqual([], pmf.shape)
+ @test_util.run_deprecated_v1
def testMeanDoubleTwoVotes(self):
# The probabilities of two votes falling into class k for
# DirichletMultinomial(2, alpha) is twice as much as the probability of one
@@ -215,6 +224,7 @@ class DirichletMultinomialTest(test.TestCase):
self.assertAllClose(mean2[class_num], 2 * mean1[class_num])
self.assertAllEqual([3], mean1.shape)
+ @test_util.run_deprecated_v1
def testCovarianceFromSampling(self):
# We will test mean, cov, var, stddev on a DirichletMultinomial constructed
# via broadcast between alpha, n.
@@ -412,6 +422,7 @@ class DirichletMultinomialTest(test.TestCase):
self.assertLess(5 * self.evaluate(pmf_different), self.evaluate(pmf_same))
self.assertEqual((), pmf_same.get_shape())
+ @test_util.run_deprecated_v1
def testNonStrictTurnsOffAllChecks(self):
# Make totally invalid input.
with self.cached_session():
@@ -421,6 +432,7 @@ class DirichletMultinomialTest(test.TestCase):
dist = ds.DirichletMultinomial(n, alpha, validate_args=False)
dist.prob(counts).eval() # Should not raise.
+ @test_util.run_deprecated_v1
def testSampleUnbiasedNonScalarBatch(self):
with self.cached_session() as sess:
dist = ds.DirichletMultinomial(
@@ -450,6 +462,7 @@ class DirichletMultinomialTest(test.TestCase):
self.assertAllClose(
actual_covariance_, sample_covariance_, atol=0., rtol=0.20)
+ @test_util.run_deprecated_v1
def testSampleUnbiasedScalarBatch(self):
with self.cached_session() as sess:
dist = ds.DirichletMultinomial(
diff --git a/tensorflow/python/kernel_tests/distributions/identity_bijector_test.py b/tensorflow/python/kernel_tests/distributions/identity_bijector_test.py
index e35a8e1cdd7..62b562387d0 100644
--- a/tensorflow/python/kernel_tests/distributions/identity_bijector_test.py
+++ b/tensorflow/python/kernel_tests/distributions/identity_bijector_test.py
@@ -18,6 +18,7 @@ from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
+from tensorflow.python.framework import test_util
from tensorflow.python.ops.distributions import bijector_test_util
from tensorflow.python.ops.distributions import identity_bijector
from tensorflow.python.platform import test
@@ -41,6 +42,7 @@ class IdentityBijectorTest(test.TestCase):
self.evaluate(
bijector.forward_log_det_jacobian(x, event_ndims=3)))
+ @test_util.run_deprecated_v1
def testScalarCongruency(self):
with self.cached_session():
bijector = identity_bijector.Identity()
diff --git a/tensorflow/python/kernel_tests/distributions/kullback_leibler_test.py b/tensorflow/python/kernel_tests/distributions/kullback_leibler_test.py
index b8bc2e55cfe..1e967de570f 100644
--- a/tensorflow/python/kernel_tests/distributions/kullback_leibler_test.py
+++ b/tensorflow/python/kernel_tests/distributions/kullback_leibler_test.py
@@ -18,6 +18,7 @@ from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops.distributions import kullback_leibler
from tensorflow.python.ops.distributions import normal
@@ -45,6 +46,7 @@ class KLTest(test.TestCase):
a = MyDist(loc=0.0, scale=1.0)
self.assertEqual("OK", kullback_leibler.kl_divergence(a, a, name="OK"))
+ @test_util.run_deprecated_v1
def testDomainErrorExceptions(self):
class MyDistException(normal.Normal):
diff --git a/tensorflow/python/kernel_tests/distributions/normal_test.py b/tensorflow/python/kernel_tests/distributions/normal_test.py
index 6625a88843f..f2a193e69bd 100644
--- a/tensorflow/python/kernel_tests/distributions/normal_test.py
+++ b/tensorflow/python/kernel_tests/distributions/normal_test.py
@@ -511,6 +511,7 @@ class NormalTest(test.TestCase):
self.assertAllEqual(self.evaluate(normal.event_shape_tensor()), [])
self.assertEqual(normal.event_shape, tensor_shape.TensorShape([]))
+ @test_util.run_deprecated_v1
def testNormalShapeWithPlaceholders(self):
mu = array_ops.placeholder(dtype=dtypes.float32)
sigma = array_ops.placeholder(dtype=dtypes.float32)
diff --git a/tensorflow/python/kernel_tests/distributions/special_math_test.py b/tensorflow/python/kernel_tests/distributions/special_math_test.py
index 0f800b95fac..d97fcfa655f 100644
--- a/tensorflow/python/kernel_tests/distributions/special_math_test.py
+++ b/tensorflow/python/kernel_tests/distributions/special_math_test.py
@@ -104,6 +104,7 @@ class NdtriTest(test.TestCase):
x = special_math.ndtri(p)
self.assertAllClose(expected_x, self.evaluate(x), atol=0.)
+ @test_util.run_deprecated_v1
def testNdtriDynamicShape(self):
"""Verifies that ndtri computation is correct."""
with self.cached_session() as sess:
@@ -213,9 +214,11 @@ class NdtrTest(test.TestCase):
rtol=error_spec.rtol,
atol=error_spec.atol)
+ @test_util.run_deprecated_v1
def test_float32(self):
self._test_grid(np.float32, self._grid32, self._error32)
+ @test_util.run_deprecated_v1
def test_float64(self):
self._test_grid(np.float64, self._grid64, self._error64)
@@ -338,10 +341,12 @@ class NdtrGradientTest(test.TestCase):
rtol=error_spec.rtol,
atol=error_spec.atol)
+ @test_util.run_deprecated_v1
def test_float32(self):
self._test_grad_accuracy(np.float32, self._grid, self._error32)
self._test_grad_finite(np.float32)
+ @test_util.run_deprecated_v1
def test_float64(self):
self._test_grad_accuracy(np.float64, self._grid, self._error64)
self._test_grad_finite(np.float64)
@@ -418,6 +423,7 @@ class LogCDFLaplaceTest(test.TestCase):
rtol=error_spec.rtol,
atol=error_spec.atol)
+ @test_util.run_deprecated_v1
def test_float32_lower_and_mid_segment_scipy_float32_ok(self):
# Choose values mild enough that we can use scipy in float32, which will
# allow for a high accuracy match to scipy (since we both use float32).
@@ -427,6 +433,7 @@ class LogCDFLaplaceTest(test.TestCase):
GridSpec(min=-10, max=self.CUTOFF_FLOAT32_UPPER - 5, shape=[100]),
ErrorSpec(rtol=5e-4, atol=0))
+ @test_util.run_deprecated_v1
def test_float32_all_segments_with_scipy_float64_ok(self):
# Choose values outside the range where scipy float32 works.
# Let scipy use float64. This means we
@@ -437,6 +444,7 @@ class LogCDFLaplaceTest(test.TestCase):
GridSpec(min=-50, max=self.CUTOFF_FLOAT32_UPPER + 5, shape=[100]),
ErrorSpec(rtol=0.05, atol=0))
+ @test_util.run_deprecated_v1
def test_float32_extreme_values_result_and_gradient_finite_and_nonzero(self):
with self.cached_session() as sess:
# On the lower branch, log_cdf_laplace(x) = x, so we know this will be
@@ -456,6 +464,7 @@ class LogCDFLaplaceTest(test.TestCase):
self.assertFalse(np.any(actual_ == 0))
self.assertFalse(np.any(grad_ == 0))
+ @test_util.run_deprecated_v1
def test_float64_extreme_values_result_and_gradient_finite_and_nonzero(self):
with self.cached_session() as sess:
# On the lower branch, log_cdf_laplace(x) = x, so we know this will be
diff --git a/tensorflow/python/kernel_tests/distributions/util_test.py b/tensorflow/python/kernel_tests/distributions/util_test.py
index d3fa513f059..030ad601bf4 100644
--- a/tensorflow/python/kernel_tests/distributions/util_test.py
+++ b/tensorflow/python/kernel_tests/distributions/util_test.py
@@ -59,6 +59,7 @@ def _logit(x):
class AssertCloseTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testAssertIntegerForm(self):
# This should only be detected as an integer.
x = array_ops.placeholder(dtypes.float32)
@@ -112,6 +113,7 @@ class MaybeGetStaticTest(test.TestCase):
self.assertAllClose(
np.array(2.), du.maybe_get_static_value(x, dtype=np.float64))
+ @test_util.run_deprecated_v1
def testGetStaticPlaceholder(self):
x = array_ops.placeholder(dtype=dtypes.int32, shape=[1])
self.assertEqual(None, du.maybe_get_static_value(x))
@@ -235,6 +237,7 @@ class GetLogitsAndProbsTest(test.TestCase):
probs=p4, multidimensional=True, validate_args=False)
self.evaluate(prob)
+ @test_util.run_deprecated_v1
def testProbsMultidimShape(self):
with self.cached_session():
with self.assertRaises(ValueError):
@@ -249,6 +252,7 @@ class GetLogitsAndProbsTest(test.TestCase):
probs=p, multidimensional=True, validate_args=True)
prob.eval(feed_dict={p: np.ones([int(2**11+1)])})
+ @test_util.run_deprecated_v1
def testLogitsMultidimShape(self):
with self.cached_session():
with self.assertRaises(ValueError):
@@ -266,6 +270,7 @@ class GetLogitsAndProbsTest(test.TestCase):
class EmbedCheckCategoricalEventShapeTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testTooSmall(self):
with self.cached_session():
with self.assertRaises(ValueError):
@@ -280,6 +285,7 @@ class EmbedCheckCategoricalEventShapeTest(test.TestCase):
param)
checked_param.eval(feed_dict={param: np.ones([1])})
+ @test_util.run_deprecated_v1
def testTooLarge(self):
with self.cached_session():
with self.assertRaises(ValueError):
@@ -305,6 +311,7 @@ class EmbedCheckCategoricalEventShapeTest(test.TestCase):
class EmbedCheckIntegerCastingClosedTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testCorrectlyAssertsNonnegative(self):
with self.cached_session():
with self.assertRaisesOpError("Elements must be non-negative"):
@@ -313,6 +320,7 @@ class EmbedCheckIntegerCastingClosedTest(test.TestCase):
x, target_dtype=dtypes.int16)
x_checked.eval(feed_dict={x: np.array([1, -1], dtype=np.float16)})
+ @test_util.run_deprecated_v1
def testCorrectlyAssersIntegerForm(self):
with self.cached_session():
with self.assertRaisesOpError("Elements must be int16-equivalent."):
@@ -321,6 +329,7 @@ class EmbedCheckIntegerCastingClosedTest(test.TestCase):
x, target_dtype=dtypes.int16)
x_checked.eval(feed_dict={x: np.array([1, 1.5], dtype=np.float16)})
+ @test_util.run_deprecated_v1
def testCorrectlyAssertsLargestPossibleInteger(self):
with self.cached_session():
with self.assertRaisesOpError("Elements cannot exceed 32767."):
@@ -329,6 +338,7 @@ class EmbedCheckIntegerCastingClosedTest(test.TestCase):
x, target_dtype=dtypes.int16)
x_checked.eval(feed_dict={x: np.array([1, 2**15], dtype=np.int32)})
+ @test_util.run_deprecated_v1
def testCorrectlyAssertsSmallestPossibleInteger(self):
with self.cached_session():
with self.assertRaisesOpError("Elements cannot be smaller than 0."):
@@ -369,6 +379,7 @@ class LogCombinationsTest(test.TestCase):
class DynamicShapeTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testSameDynamicShape(self):
with self.cached_session():
scalar = constant_op.constant(2.0)
@@ -493,6 +504,7 @@ class RotateTransposeTest(test.TestCase):
self._np_rotate_transpose(x, shift), self.evaluate(y))
self.assertAllEqual(np.roll(x.shape, shift), y.get_shape().as_list())
+ @test_util.run_deprecated_v1
def testRollDynamic(self):
with self.cached_session() as sess:
x = array_ops.placeholder(dtypes.float32)
@@ -511,6 +523,7 @@ class RotateTransposeTest(test.TestCase):
class PickVectorTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testCorrectlyPicksVector(self):
with self.cached_session():
x = np.arange(10, 12)
@@ -529,36 +542,42 @@ class PickVectorTest(test.TestCase):
class PreferStaticRankTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testNonEmptyConstantTensor(self):
x = array_ops.zeros((2, 3, 4))
rank = du.prefer_static_rank(x)
self.assertIsInstance(rank, np.ndarray)
self.assertEqual(3, rank)
+ @test_util.run_deprecated_v1
def testEmptyConstantTensor(self):
x = constant_op.constant([])
rank = du.prefer_static_rank(x)
self.assertIsInstance(rank, np.ndarray)
self.assertEqual(1, rank)
+ @test_util.run_deprecated_v1
def testScalarTensor(self):
x = constant_op.constant(1.)
rank = du.prefer_static_rank(x)
self.assertIsInstance(rank, np.ndarray)
self.assertEqual(0, rank)
+ @test_util.run_deprecated_v1
def testDynamicRankEndsUpBeingNonEmpty(self):
x = array_ops.placeholder(np.float64, shape=None)
rank = du.prefer_static_rank(x)
with self.cached_session():
self.assertAllEqual(2, rank.eval(feed_dict={x: np.zeros((2, 3))}))
+ @test_util.run_deprecated_v1
def testDynamicRankEndsUpBeingEmpty(self):
x = array_ops.placeholder(np.int32, shape=None)
rank = du.prefer_static_rank(x)
with self.cached_session():
self.assertAllEqual(1, rank.eval(feed_dict={x: []}))
+ @test_util.run_deprecated_v1
def testDynamicRankEndsUpBeingScalar(self):
x = array_ops.placeholder(np.int32, shape=None)
rank = du.prefer_static_rank(x)
@@ -568,36 +587,42 @@ class PreferStaticRankTest(test.TestCase):
class PreferStaticShapeTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testNonEmptyConstantTensor(self):
x = array_ops.zeros((2, 3, 4))
shape = du.prefer_static_shape(x)
self.assertIsInstance(shape, np.ndarray)
self.assertAllEqual(np.array([2, 3, 4]), shape)
+ @test_util.run_deprecated_v1
def testEmptyConstantTensor(self):
x = constant_op.constant([])
shape = du.prefer_static_shape(x)
self.assertIsInstance(shape, np.ndarray)
self.assertAllEqual(np.array([0]), shape)
+ @test_util.run_deprecated_v1
def testScalarTensor(self):
x = constant_op.constant(1.)
shape = du.prefer_static_shape(x)
self.assertIsInstance(shape, np.ndarray)
self.assertAllEqual(np.array([]), shape)
+ @test_util.run_deprecated_v1
def testDynamicShapeEndsUpBeingNonEmpty(self):
x = array_ops.placeholder(np.float64, shape=None)
shape = du.prefer_static_shape(x)
with self.cached_session():
self.assertAllEqual((2, 3), shape.eval(feed_dict={x: np.zeros((2, 3))}))
+ @test_util.run_deprecated_v1
def testDynamicShapeEndsUpBeingEmpty(self):
x = array_ops.placeholder(np.int32, shape=None)
shape = du.prefer_static_shape(x)
with self.cached_session():
self.assertAllEqual(np.array([0]), shape.eval(feed_dict={x: []}))
+ @test_util.run_deprecated_v1
def testDynamicShapeEndsUpBeingScalar(self):
x = array_ops.placeholder(np.int32, shape=None)
shape = du.prefer_static_shape(x)
@@ -607,24 +632,28 @@ class PreferStaticShapeTest(test.TestCase):
class PreferStaticValueTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testNonEmptyConstantTensor(self):
x = array_ops.zeros((2, 3, 4))
value = du.prefer_static_value(x)
self.assertIsInstance(value, np.ndarray)
self.assertAllEqual(np.zeros((2, 3, 4)), value)
+ @test_util.run_deprecated_v1
def testEmptyConstantTensor(self):
x = constant_op.constant([])
value = du.prefer_static_value(x)
self.assertIsInstance(value, np.ndarray)
self.assertAllEqual(np.array([]), value)
+ @test_util.run_deprecated_v1
def testScalarTensor(self):
x = constant_op.constant(1.)
value = du.prefer_static_value(x)
self.assertIsInstance(value, np.ndarray)
self.assertAllEqual(np.array(1.), value)
+ @test_util.run_deprecated_v1
def testDynamicValueEndsUpBeingNonEmpty(self):
x = array_ops.placeholder(np.float64, shape=None)
value = du.prefer_static_value(x)
@@ -632,12 +661,14 @@ class PreferStaticValueTest(test.TestCase):
self.assertAllEqual(np.zeros((2, 3)),
value.eval(feed_dict={x: np.zeros((2, 3))}))
+ @test_util.run_deprecated_v1
def testDynamicValueEndsUpBeingEmpty(self):
x = array_ops.placeholder(np.int32, shape=None)
value = du.prefer_static_value(x)
with self.cached_session():
self.assertAllEqual(np.array([]), value.eval(feed_dict={x: []}))
+ @test_util.run_deprecated_v1
def testDynamicValueEndsUpBeingScalar(self):
x = array_ops.placeholder(np.int32, shape=None)
value = du.prefer_static_value(x)
@@ -698,43 +729,55 @@ class FillTriangularTest(test.TestCase):
self.assertAllClose(expected, actual_, rtol=1e-8, atol=1e-9)
self.assertAllClose(x_, grad_actual_, rtol=1e-8, atol=1e-9)
+ @test_util.run_deprecated_v1
def testCorrectlyMakes1x1TriLower(self):
self._run_test(self._rng.randn(3, int(1*2/2)))
+ @test_util.run_deprecated_v1
def testCorrectlyMakesNoBatchTriLower(self):
self._run_test(self._rng.randn(int(4*5/2)))
+ @test_util.run_deprecated_v1
def testCorrectlyMakesBatchTriLower(self):
self._run_test(self._rng.randn(2, 3, int(3*4/2)))
+ @test_util.run_deprecated_v1
def testCorrectlyMakesBatchTriLowerUnknownShape(self):
self._run_test(self._rng.randn(2, 3, int(3*4/2)), use_deferred_shape=True)
+ @test_util.run_deprecated_v1
def testCorrectlyMakesBatch7x7TriLowerUnknownShape(self):
self._run_test(self._rng.randn(2, 3, int(7*8/2)), use_deferred_shape=True)
+ @test_util.run_deprecated_v1
def testCorrectlyMakesBatch7x7TriLower(self):
self._run_test(self._rng.randn(2, 3, int(7*8/2)))
+ @test_util.run_deprecated_v1
def testCorrectlyMakes1x1TriUpper(self):
self._run_test(self._rng.randn(3, int(1*2/2)), upper=True)
+ @test_util.run_deprecated_v1
def testCorrectlyMakesNoBatchTriUpper(self):
self._run_test(self._rng.randn(int(4*5/2)), upper=True)
+ @test_util.run_deprecated_v1
def testCorrectlyMakesBatchTriUpper(self):
self._run_test(self._rng.randn(2, 2, int(3*4/2)), upper=True)
+ @test_util.run_deprecated_v1
def testCorrectlyMakesBatchTriUpperUnknownShape(self):
self._run_test(self._rng.randn(2, 2, int(3*4/2)),
use_deferred_shape=True,
upper=True)
+ @test_util.run_deprecated_v1
def testCorrectlyMakesBatch7x7TriUpperUnknownShape(self):
self._run_test(self._rng.randn(2, 3, int(7*8/2)),
use_deferred_shape=True,
upper=True)
+ @test_util.run_deprecated_v1
def testCorrectlyMakesBatch7x7TriUpper(self):
self._run_test(self._rng.randn(2, 3, int(7*8/2)), upper=True)
@@ -773,6 +816,7 @@ class ReduceWeightedLogSumExp(test.TestCase):
m = np.squeeze(m, axis=axis)
return m + np.log(sgn * sum_), sgn
+ @test_util.run_deprecated_v1
def testNoWeights(self):
logx_ = np.array([[0., -1, 1000.],
[0, 1, -1000.],
@@ -903,6 +947,7 @@ class SoftplusTest(test.TestCase):
self.assertAllEqual(np.ones_like(tf_softplus_inverse).astype(np.bool),
np.isfinite(tf_softplus_inverse))
+ @test_util.run_deprecated_v1
def testNumbers(self):
for t in [np.float16, np.float32, np.float64]:
lower = {np.float16: -15, np.float32: -50, np.float64: -50}.get(t, -100)
@@ -933,6 +978,7 @@ class SoftplusTest(test.TestCase):
],
use_gpu=True)
+ @test_util.run_deprecated_v1
def testGradient(self):
with self.cached_session():
x = constant_op.constant(
@@ -949,6 +995,7 @@ class SoftplusTest(test.TestCase):
tf_logging.vlog(2, "softplus (float) gradient err = ", err)
self.assertLess(err, 1e-4)
+ @test_util.run_deprecated_v1
def testInverseSoftplusGradientNeverNan(self):
with self.cached_session():
# Note that this range contains both zero and inf.
@@ -958,6 +1005,7 @@ class SoftplusTest(test.TestCase):
# Equivalent to `assertAllFalse` (if it existed).
self.assertAllEqual(np.zeros_like(grads).astype(np.bool), np.isnan(grads))
+ @test_util.run_deprecated_v1
def testInverseSoftplusGradientFinite(self):
with self.cached_session():
# This range of x is all finite, and so is 1 / x. So the
diff --git a/tensorflow/python/kernel_tests/duplicate_op_test.py b/tensorflow/python/kernel_tests/duplicate_op_test.py
index 654267a5825..fef3127d4a8 100644
--- a/tensorflow/python/kernel_tests/duplicate_op_test.py
+++ b/tensorflow/python/kernel_tests/duplicate_op_test.py
@@ -20,6 +20,7 @@ from __future__ import print_function
import os
from tensorflow.python.framework import load_library
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import math_ops
from tensorflow.python.platform import resource_loader
from tensorflow.python.platform import test
@@ -27,6 +28,7 @@ from tensorflow.python.platform import test
class DuplicateOpTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testBasic(self):
library_filename = os.path.join(resource_loader.get_data_files_path(),
'duplicate_op.so')
diff --git a/tensorflow/python/kernel_tests/dynamic_partition_op_test.py b/tensorflow/python/kernel_tests/dynamic_partition_op_test.py
index 3622fde3f3a..8c448194076 100644
--- a/tensorflow/python/kernel_tests/dynamic_partition_op_test.py
+++ b/tensorflow/python/kernel_tests/dynamic_partition_op_test.py
@@ -25,6 +25,7 @@ from six.moves import xrange # pylint: disable=redefined-builtin
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import data_flow_ops
from tensorflow.python.ops import gradients_impl
@@ -34,6 +35,7 @@ from tensorflow.python.platform import test
class DynamicPartitionTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testSimpleOneDimensional(self):
with self.session(use_gpu=True) as sess:
data = constant_op.constant([0, 13, 2, 39, 4, 17], dtype=dtypes.float32)
@@ -54,6 +56,7 @@ class DynamicPartitionTest(test.TestCase):
self.assertEqual([None], partitions[2].get_shape().as_list())
self.assertEqual([None], partitions[3].get_shape().as_list())
+ @test_util.run_deprecated_v1
def testSimpleTwoDimensional(self):
with self.session(use_gpu=True) as sess:
data = constant_op.constant([[0, 1, 2], [3, 4, 5], [6, 7, 8], [9, 10, 11],
@@ -151,6 +154,7 @@ class DynamicPartitionTest(test.TestCase):
dtype=np.float64).reshape(-1, 4),
partition_vals[3])
+ @test_util.run_deprecated_v1
def testHigherRank(self):
np.random.seed(7)
with self.session(use_gpu=True) as sess:
@@ -287,6 +291,7 @@ class DynamicPartitionTest(test.TestCase):
for i in range(40):
self.assertAllEqual([], partition_vals[i])
+ @test_util.run_deprecated_v1
def testErrorIndexOutOfRange(self):
with self.cached_session() as sess:
data = constant_op.constant([[0, 1, 2], [3, 4, 5], [6, 7, 8], [9, 10, 11],
@@ -297,6 +302,7 @@ class DynamicPartitionTest(test.TestCase):
with self.assertRaisesOpError(r"partitions\[2\] = 99 is not in \[0, 4\)"):
self.evaluate(partitions)
+ @test_util.run_deprecated_v1
def testScalarIndexOutOfRange(self):
with self.cached_session() as sess:
bad = 17
@@ -305,6 +311,7 @@ class DynamicPartitionTest(test.TestCase):
with self.assertRaisesOpError(r"partitions = 17 is not in \[0, 7\)"):
self.evaluate(partitions)
+ @test_util.run_deprecated_v1
def testHigherRankIndexOutOfRange(self):
with self.cached_session() as sess:
shape = (2, 3)
@@ -320,6 +327,7 @@ class DynamicPartitionTest(test.TestCase):
r"partitions\[%d,%d\] = 17 is not in \[0, 7\)" % (i, j)):
sess.run(partitions, feed_dict={indices: bad})
+ @test_util.run_deprecated_v1
def testErrorWrongDimsIndices(self):
data = constant_op.constant([[0], [1], [2]])
indices = constant_op.constant([[0], [0]])
diff --git a/tensorflow/python/kernel_tests/dynamic_stitch_op_test.py b/tensorflow/python/kernel_tests/dynamic_stitch_op_test.py
index 3d063c4e0ec..4f338880aa3 100644
--- a/tensorflow/python/kernel_tests/dynamic_stitch_op_test.py
+++ b/tensorflow/python/kernel_tests/dynamic_stitch_op_test.py
@@ -47,6 +47,7 @@ class DynamicStitchTestBase(object):
# Dimension 0 is max(flatten(indices))+1.
self.assertEqual([2], stitched_t.get_shape().as_list())
+ @test_util.run_deprecated_v1
def testShapeInferenceForScalarWithNonConstantIndices(self):
with test_util.use_gpu():
indices = [
@@ -134,6 +135,7 @@ class DynamicStitchTestBase(object):
# Dimension 0 is max(flatten(indices))+1.
self.assertEqual([8, 2], stitched_t.get_shape().as_list())
+ @test_util.run_deprecated_v1
def testHigherRank(self):
with self.session(use_gpu=True) as sess:
indices = [
@@ -160,6 +162,7 @@ class DynamicStitchTestBase(object):
for datum, grad in zip(data, sess.run(grads[3:])):
self.assertAllEqual(7. * self.evaluate(datum), grad)
+ @test_util.run_deprecated_v1
def testErrorIndicesMultiDimensional(self):
indices = [
constant_op.constant([0, 4, 7]),
@@ -172,6 +175,7 @@ class DynamicStitchTestBase(object):
with self.assertRaises(ValueError):
self.stitch_op(indices, data)
+ @test_util.run_deprecated_v1
def testErrorDataNumDimsMismatch(self):
indices = [
constant_op.constant([0, 4, 7]),
@@ -184,6 +188,7 @@ class DynamicStitchTestBase(object):
with self.assertRaises(ValueError):
self.stitch_op(indices, data)
+ @test_util.run_deprecated_v1
def testErrorDataDimSizeMismatch(self):
indices = [
constant_op.constant([0, 4, 5]),
@@ -196,6 +201,7 @@ class DynamicStitchTestBase(object):
with self.assertRaises(ValueError):
self.stitch_op(indices, data)
+ @test_util.run_deprecated_v1
def testErrorDataAndIndicesSizeMismatch(self):
indices = [
constant_op.constant([0, 4, 7]),
@@ -233,6 +239,7 @@ class ParallelDynamicStitchTest(DynamicStitchTestBase, test.TestCase):
# Dimension 0 is max(flatten(indices))+1.
self.assertEqual([2], stitched_t.get_shape().as_list())
+ @test_util.run_deprecated_v1
def testHigherRank(self):
with self.session(use_gpu=True) as sess:
indices = [
@@ -271,6 +278,7 @@ class ParallelDynamicStitchTest(DynamicStitchTestBase, test.TestCase):
# Dimension 0 is max(flatten(indices))+1.
self.assertEqual([2], stitched_t.get_shape().as_list())
+ @test_util.run_deprecated_v1
def testHigherRankGPU(self):
with self.cached_session() as sess:
indices = [
diff --git a/tensorflow/python/kernel_tests/embedding_ops_test.py b/tensorflow/python/kernel_tests/embedding_ops_test.py
index 39c0575cd55..6019245d0f8 100644
--- a/tensorflow/python/kernel_tests/embedding_ops_test.py
+++ b/tensorflow/python/kernel_tests/embedding_ops_test.py
@@ -28,6 +28,7 @@ from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
from tensorflow.python.framework import sparse_tensor
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import data_flow_ops
from tensorflow.python.ops import embedding_ops
@@ -87,16 +88,19 @@ class ScatterAddSubTest(test.TestCase):
vals_shape[0], -1)[i, :])
self.assertTrue(all((p_init == result).ravel()))
+ @test_util.run_deprecated_v1
def testNoRepetitions(self):
self._TestCase([2, 2], [1])
self._TestCase([4, 4, 4], [2, 0])
self._TestCase([43, 20, 10, 10], [42, 5, 6, 1, 3, 5, 7, 9])
+ @test_util.run_deprecated_v1
def testWithRepetitions(self):
self._TestCase([2, 2], [1, 1])
self._TestCase([5, 3, 9, 5], [2, 0, 4, 1, 3, 1, 4, 0, 4, 3])
self._TestCase([32, 4, 4], [31] * 8)
+ @test_util.run_deprecated_v1
def testRandom(self):
# Random shapes of rank 4, random indices
for _ in range(5):
@@ -104,6 +108,7 @@ class ScatterAddSubTest(test.TestCase):
indices = np.random.randint(shape[0], size=2 * shape[0])
self._TestCase(_AsLong(list(shape)), list(indices))
+ @test_util.run_deprecated_v1
def testSubRandom(self):
# Random shapes of rank 4, random indices
for _ in range(5):
@@ -111,6 +116,7 @@ class ScatterAddSubTest(test.TestCase):
indices = np.random.randint(shape[0], size=2 * shape[0])
self._TestCase(_AsLong(list(shape)), list(indices), state_ops.scatter_sub)
+ @test_util.run_deprecated_v1
def testWrongShape(self):
# Indices and values mismatch.
var = variables.Variable(
@@ -241,6 +247,7 @@ class EmbeddingLookupTest(test.TestCase):
# both the ids are in the first shard, one of the resulting lookup
# vector is going to be empty. The subsequent DivOp fails because of that.
# TODO(keveman): Disabling the test until the underlying problem is fixed.
+ @test_util.run_deprecated_v1
def testSimpleSharded(self):
with self.cached_session():
num_shards = 2
@@ -257,6 +264,7 @@ class EmbeddingLookupTest(test.TestCase):
self.assertAllEqual(np_result, tf_result)
self.assertShapeEqual(np_result, embedding)
+ @test_util.run_deprecated_v1
def testMaxNorm(self):
with self.cached_session():
embeddings = constant_op.constant([[2.0]])
@@ -267,6 +275,7 @@ class EmbeddingLookupTest(test.TestCase):
self.assertAllEqual(embedding.eval(), [[1.0]])
+ @test_util.run_deprecated_v1
def testMaxNormNontrivial(self):
with self.cached_session():
embeddings = constant_op.constant([[2.0, 4.0], [3.0, 1.0]])
@@ -280,6 +289,7 @@ class EmbeddingLookupTest(test.TestCase):
normalized = embeddings / array_ops.stack([norms, norms], axis=1)
self.assertAllEqual(embedding.eval(), 2 * self.evaluate(normalized))
+ @test_util.run_deprecated_v1
def testSimpleShardedPartitionedVariable(self):
with self.cached_session() as sess:
num_shards = 2
@@ -302,6 +312,7 @@ class EmbeddingLookupTest(test.TestCase):
self.assertAllEqual(np_result, tf_result)
self.assertShapeEqual(np_result, embedding)
+ @test_util.run_deprecated_v1
def testSimpleShardedPartitionedResourceVariable(self):
with self.cached_session() as sess:
num_shards = 2
@@ -325,6 +336,7 @@ class EmbeddingLookupTest(test.TestCase):
self.assertAllEqual(np_result, tf_result)
self.assertShapeEqual(np_result, embedding)
+ @test_util.run_deprecated_v1
def testShardedModPartitioningInt32Ids(self):
with self.cached_session():
num_shards = 5
@@ -347,6 +359,7 @@ class EmbeddingLookupTest(test.TestCase):
self.assertAllEqual(np_result, tf_result)
self.assertShapeEqual(np_result, embedding)
+ @test_util.run_deprecated_v1
def testShardedModPartitioningInt64Ids(self):
with self.cached_session():
num_shards = 5
@@ -369,6 +382,7 @@ class EmbeddingLookupTest(test.TestCase):
self.assertAllEqual(np_result, tf_result)
self.assertShapeEqual(np_result, embedding)
+ @test_util.run_deprecated_v1
def testShardedDivPartitioningInt32Ids(self):
with self.cached_session():
num_shards = 5
@@ -393,6 +407,7 @@ class EmbeddingLookupTest(test.TestCase):
self.assertAllEqual(np_result, tf_result)
self.assertShapeEqual(np_result, embedding)
+ @test_util.run_deprecated_v1
def testShardedDivPartitioningInt32IdsPartitionedVariable(self):
with self.cached_session():
num_shards = 5
@@ -418,6 +433,7 @@ class EmbeddingLookupTest(test.TestCase):
self.assertAllEqual(np_result, tf_result)
self.assertShapeEqual(np_result, embedding)
+ @test_util.run_deprecated_v1
def testShardedDivPartitioningInt64Ids(self):
with self.cached_session():
num_shards = 5
@@ -442,6 +458,7 @@ class EmbeddingLookupTest(test.TestCase):
self.assertAllEqual(np_result, tf_result)
self.assertShapeEqual(np_result, embedding)
+ @test_util.run_deprecated_v1
def testShardedDivPartitioningUnknownParamShape(self):
with self.cached_session():
num_shards = 5
@@ -468,6 +485,7 @@ class EmbeddingLookupTest(test.TestCase):
params, id_vals, num_shards, vocab_size, partition_strategy="div")
self.assertAllEqual(np_result, tf_result)
+ @test_util.run_deprecated_v1
def testGradientsEmbeddingLookup(self):
vocab_size = 9
num_ids = 10
@@ -488,6 +506,7 @@ class EmbeddingLookupTest(test.TestCase):
x, x_shape, y, y_shape, x_init_value=x_init_value)
self.assertLess(err, 1e-4)
+ @test_util.run_deprecated_v1
def testGradientsEmbeddingLookupWithComputedParams(self):
vocab_size = 9
num_ids = 5
@@ -526,6 +545,7 @@ class EmbeddingLookupTest(test.TestCase):
ids = constant_op.constant([0, 1, 1, 17], dtype=dtypes.int32)
embedding_ops.embedding_lookup(p, ids)
+ @test_util.run_deprecated_v1
def testHigherRank(self):
np.random.seed(8)
with self.cached_session():
@@ -546,6 +566,7 @@ class EmbeddingLookupTest(test.TestCase):
sharded = embedding_ops.embedding_lookup(split_params, ids).eval()
self.assertAllEqual(simple, sharded)
+ @test_util.run_deprecated_v1
def testHigherRankMaxNorm(self):
np.random.seed(8)
with self.cached_session():
@@ -574,6 +595,7 @@ class EmbeddingLookupTest(test.TestCase):
split_params, ids, max_norm=1.0).eval()
self.assertAllEqual(simple, sharded)
+ @test_util.run_deprecated_v1
def testTransform(self):
# This tests all combinations of:
# - ids rank 0, 1, >1
@@ -648,6 +670,7 @@ class EmbeddingLookupSparseTest(test.TestCase):
index += num_val
return grouped_vals
+ @test_util.run_deprecated_v1
def testEmbeddingLookupSparse(self):
vocab_size = 13
batch_size = 10
@@ -706,6 +729,7 @@ class EmbeddingLookupSparseTest(test.TestCase):
atol = rtol
self.assertAllClose(np_embedding_sum, tf_embedding_sum, rtol, atol)
+ @test_util.run_deprecated_v1
def testGradientsEmbeddingLookupSparse(self):
vocab_size = 12
batch_size = 4
@@ -733,6 +757,7 @@ class EmbeddingLookupSparseTest(test.TestCase):
x, x_shape, y, y_shape, x_init_value=x_init_value)
self.assertLess(err, 1e-5 if dtype == dtypes.float64 else 2e-3)
+ @test_util.run_deprecated_v1
def testIncompatibleShapes(self):
with self.cached_session():
x, _, _ = _EmbeddingParams(1, 10, dtype=dtypes.float32)
@@ -820,6 +845,7 @@ class SafeEmbeddingLookupSparseTest(test.TestCase):
return sparse_ids, sparse_weights
+ @test_util.run_deprecated_v1
def test_safe_embedding_lookup_sparse_return_zero_vector(self):
with self.cached_session():
embedding_weights = self._random_weights()
@@ -833,6 +859,7 @@ class SafeEmbeddingLookupSparseTest(test.TestCase):
[(1.0 * embedding_weights[0][0] + 2.0 * embedding_weights[0][1]) /
3.0, [0] * 4, [0] * 4, embedding_weights[0][2], [0] * 4])
+ @test_util.run_deprecated_v1
def test_safe_embedding_lookup_sparse_return_special_vector(self):
with self.cached_session():
embedding_weights = self._random_weights()
@@ -847,6 +874,7 @@ class SafeEmbeddingLookupSparseTest(test.TestCase):
3.0, embedding_weights[0][3], embedding_weights[0][3],
embedding_weights[0][2], embedding_weights[0][3]])
+ @test_util.run_deprecated_v1
def test_safe_embedding_lookup_sparse_no_weights(self):
with self.cached_session():
embedding_weights = self._random_weights()
@@ -861,6 +889,7 @@ class SafeEmbeddingLookupSparseTest(test.TestCase):
[0] * 4, embedding_weights[0][2], (
embedding_weights[0][0] + embedding_weights[0][1]) / 2.0])
+ @test_util.run_deprecated_v1
def test_safe_embedding_lookup_sparse_partitioned(self):
with self.cached_session():
embedding_weights = self._random_weights(num_shards=3)
@@ -875,6 +904,7 @@ class SafeEmbeddingLookupSparseTest(test.TestCase):
[0] * 4, [0] * 4, embedding_weights[2],
(embedding_weights[0] + embedding_weights[1]) / 2.0])
+ @test_util.run_deprecated_v1
def test_safe_embedding_lookup_sparse_partitioned_inconsistent_weights(self):
with self.cached_session():
embedding_weights = self._random_weights(num_shards=3)
@@ -890,6 +920,7 @@ class SafeEmbeddingLookupSparseTest(test.TestCase):
self.assertRaises(ValueError, embedding_ops.safe_embedding_lookup_sparse,
embedding_weights, sparse_ids, sparse_weights)
+ @test_util.run_deprecated_v1
def test_safe_embedding_lookup_sparse_3d_return_zero_vector(self):
with self.cached_session():
embedding_weights = self._random_weights()
@@ -903,6 +934,7 @@ class SafeEmbeddingLookupSparseTest(test.TestCase):
[0] * 4, [0] * 4
], [embedding_weights[0][2], [0] * 4, [0] * 4]])
+ @test_util.run_deprecated_v1
def test_safe_embedding_lookup_sparse_3d_return_special_vector(self):
with self.cached_session():
embedding_weights = self._random_weights()
@@ -919,6 +951,7 @@ class SafeEmbeddingLookupSparseTest(test.TestCase):
embedding_weights[0][3]
]])
+ @test_util.run_deprecated_v1
def test_safe_embedding_lookup_sparse_3d_no_weights(self):
with self.cached_session():
embedding_weights = self._random_weights()
@@ -935,6 +968,7 @@ class SafeEmbeddingLookupSparseTest(test.TestCase):
(embedding_weights[0][0] + embedding_weights[0][1]) / 2.0, [0] * 4
]])
+ @test_util.run_deprecated_v1
def test_safe_embedding_lookup_sparse_3d_partitioned(self):
with self.cached_session():
embedding_weights = self._random_weights(num_shards=3)
@@ -951,6 +985,7 @@ class SafeEmbeddingLookupSparseTest(test.TestCase):
(embedding_weights[0] + embedding_weights[1]) / 2.0, [0] * 4
]])
+ @test_util.run_deprecated_v1
def test_safe_embedding_lookup_sparse_3d_partitioned_inconsistent_weights(
self):
with self.cached_session():
@@ -970,6 +1005,7 @@ class SafeEmbeddingLookupSparseTest(test.TestCase):
class DynamicStitchOpTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testCint32Cpu(self):
with self.session(use_gpu=False):
indices = [
@@ -983,6 +1019,7 @@ class DynamicStitchOpTest(test.TestCase):
self.assertAllEqual(
data_flow_ops.dynamic_stitch(indices, values).eval(), [12, 23, 1, 2])
+ @test_util.run_deprecated_v1
def testCint32Gpu(self):
with self.session(use_gpu=True):
indices = [
@@ -996,6 +1033,7 @@ class DynamicStitchOpTest(test.TestCase):
self.assertAllEqual(
data_flow_ops.dynamic_stitch(indices, values).eval(), [12, 23, 1, 2])
+ @test_util.run_deprecated_v1
def testInt32Cpu(self):
with self.session(use_gpu=False):
indices = [
@@ -1009,6 +1047,7 @@ class DynamicStitchOpTest(test.TestCase):
self.assertAllEqual(
data_flow_ops.dynamic_stitch(indices, values).eval(), [12, 23, 1, 2])
+ @test_util.run_deprecated_v1
def testInt32Gpu(self):
with self.session(use_gpu=True):
indices = [
@@ -1022,6 +1061,7 @@ class DynamicStitchOpTest(test.TestCase):
self.assertAllEqual(
data_flow_ops.dynamic_stitch(indices, values).eval(), [12, 23, 1, 2])
+ @test_util.run_deprecated_v1
def testSumGradArgs(self):
with self.session(use_gpu=False):
indices = [
@@ -1036,6 +1076,7 @@ class DynamicStitchOpTest(test.TestCase):
data_flow_ops.dynamic_stitch(indices, values).eval(), [2, 3, 1, 1])
# We expect that the values are merged in order.
+ @test_util.run_deprecated_v1
def testStitchOrder(self):
with self.cached_session():
indices = []
@@ -1051,6 +1092,7 @@ class DynamicStitchOpTest(test.TestCase):
class ParallelDynamicStitchOpTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testCint32Cpu(self):
with self.session(use_gpu=False):
indices = [
@@ -1065,6 +1107,7 @@ class ParallelDynamicStitchOpTest(test.TestCase):
data_flow_ops.parallel_dynamic_stitch(indices, values).eval(),
[12, 23, 1, 2, 34, 3, 45])
+ @test_util.run_deprecated_v1
def testInt32Cpu(self):
with self.session(use_gpu=False):
indices = [
@@ -1079,6 +1122,7 @@ class ParallelDynamicStitchOpTest(test.TestCase):
data_flow_ops.parallel_dynamic_stitch(indices, values).eval(),
[12, 23, 1, 2, 3, 34, 45, 56])
+ @test_util.run_deprecated_v1
def testSimple(self):
with self.session(use_gpu=False):
indices = [ops.convert_to_tensor([0, 1]), ops.convert_to_tensor([2, 3])]
diff --git a/tensorflow/python/kernel_tests/extract_image_patches_grad_test.py b/tensorflow/python/kernel_tests/extract_image_patches_grad_test.py
index 7d9d4e51752..7ba2dc6c209 100644
--- a/tensorflow/python/kernel_tests/extract_image_patches_grad_test.py
+++ b/tensorflow/python/kernel_tests/extract_image_patches_grad_test.py
@@ -23,6 +23,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import random_seed as random_seed_lib
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import gradients_impl
@@ -78,6 +79,7 @@ class ExtractImagePatchesGradTest(test.TestCase):
},
]
+ @test_util.run_deprecated_v1
def testGradient(self):
# Set graph seed for determinism.
random_seed = 42
@@ -102,6 +104,7 @@ class ExtractImagePatchesGradTest(test.TestCase):
print('extract_image_patches gradient err: %.4e' % err)
self.assertLess(err, 1e-4)
+ @test_util.run_deprecated_v1
def testConstructGradientWithLargeImages(self):
batch_size = 4
height = 1024
diff --git a/tensorflow/python/kernel_tests/fractional_avg_pool_op_test.py b/tensorflow/python/kernel_tests/fractional_avg_pool_op_test.py
index 272adecfb8a..0d5928aefac 100644
--- a/tensorflow/python/kernel_tests/fractional_avg_pool_op_test.py
+++ b/tensorflow/python/kernel_tests/fractional_avg_pool_op_test.py
@@ -24,6 +24,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gen_nn_ops
from tensorflow.python.ops import gradient_checker
@@ -281,6 +282,7 @@ class FractionalAvgTest(test.TestCase):
self._ValidateFractionalAvgPoolResult(rand_mat, [1, 2, 2, 1], pseudo_random,
overlapping)
+ @test_util.run_deprecated_v1
def testDifferentInputTensorShape(self):
"""Runs the operation in one session with different input tensor shapes."""
with self.cached_session() as sess:
@@ -427,6 +429,7 @@ class FractionalAvgPoolGradTest(test.TestCase):
self.assertShapeEqual(input_backprop, fap_input_backprop_tensor)
self.assertAllClose(input_backprop, fap_input_backprop)
+ @test_util.run_deprecated_v1
def testAllInputOptionsThroughGradientError(self):
input_shape = (1, 7, 13, 1)
input_data = self._GenerateRandomInputTensor(input_shape)
@@ -455,6 +458,7 @@ class FractionalAvgPoolGradTest(test.TestCase):
delta=1e-2)
self.assertLess(gradient_error, error_margin)
+ @test_util.run_deprecated_v1
def testDifferentTensorShapesThroughGradientError(self):
pseudo_random = True
overlapping = True
@@ -486,6 +490,7 @@ class FractionalAvgPoolGradTest(test.TestCase):
delta=1e-2)
self.assertLess(gradient_error, error_margin)
+ @test_util.run_deprecated_v1
def testLargePoolingRatioThroughGradientError(self):
input_shape = (1, 17, 23, 1)
input_data = self._GenerateRandomInputTensor(input_shape)
diff --git a/tensorflow/python/kernel_tests/fractional_max_pool_op_test.py b/tensorflow/python/kernel_tests/fractional_max_pool_op_test.py
index 9b1e73b318c..fa886cc215a 100644
--- a/tensorflow/python/kernel_tests/fractional_max_pool_op_test.py
+++ b/tensorflow/python/kernel_tests/fractional_max_pool_op_test.py
@@ -24,6 +24,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gen_nn_ops
from tensorflow.python.ops import gradient_checker
@@ -278,6 +279,7 @@ class FractionalMaxPoolTest(test.TestCase):
self._ValidateFractionalMaxPoolResult(rand_mat, [1, 2, 2, 1], pseudo_random,
overlapping)
+ @test_util.run_deprecated_v1
def testDifferentInputTensorShape(self):
"""Runs the operation in one session with different input tensor shapes."""
with self.cached_session() as sess:
@@ -430,6 +432,7 @@ class FractionalMaxPoolGradTest(test.TestCase):
self.assertShapeEqual(input_backprop, fmp_input_backprop_tensor)
self.assertAllClose(input_backprop, fmp_input_backprop)
+ @test_util.run_deprecated_v1
def testAllInputOptionsThroughGradientError(self):
input_shape = (1, 7, 13, 1)
input_data = self._GenerateUniqueRandomInputTensor(input_shape)
@@ -460,6 +463,7 @@ class FractionalMaxPoolGradTest(test.TestCase):
delta=1e-2)
self.assertLess(gradient_error, error_margin)
+ @test_util.run_deprecated_v1
def testDifferentTensorShapesThroughGradientError(self):
pseudo_random = True
overlapping = True
@@ -493,6 +497,7 @@ class FractionalMaxPoolGradTest(test.TestCase):
delta=1e-2)
self.assertLess(gradient_error, error_margin)
+ @test_util.run_deprecated_v1
def testLargePoolingRatioThroughGradientError(self):
input_shape = (1, 17, 23, 1)
input_data = self._GenerateUniqueRandomInputTensor(input_shape)
diff --git a/tensorflow/python/kernel_tests/functional_ops_test.py b/tensorflow/python/kernel_tests/functional_ops_test.py
index 23b3c7e1cc2..c489623fe56 100644
--- a/tensorflow/python/kernel_tests/functional_ops_test.py
+++ b/tensorflow/python/kernel_tests/functional_ops_test.py
@@ -101,6 +101,7 @@ class FunctionalOpsTest(test.TestCase):
(elems, other_elems), initializer)
self.assertAllEqual([1.0, 2.0, 3.0], self.evaluate(r))
+ @test_util.run_deprecated_v1
def testFoldl_Scoped(self):
with self.cached_session() as sess:
with variable_scope.variable_scope("root") as varscope:
@@ -153,6 +154,7 @@ class FunctionalOpsTest(test.TestCase):
initializer)
self.assertAllEqual(1, self.evaluate(r))
+ @test_util.run_deprecated_v1
def testFoldr_Scoped(self):
with self.cached_session() as sess:
with variable_scope.variable_scope("root") as varscope:
@@ -173,6 +175,7 @@ class FunctionalOpsTest(test.TestCase):
self.assertAllEqual(1282, self.evaluate(r))
# pylint: disable=unnecessary-lambda
+ @test_util.run_deprecated_v1
def testFold_Grad(self):
with self.cached_session():
elems = constant_op.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], name="data")
@@ -214,6 +217,7 @@ class FunctionalOpsTest(test.TestCase):
with self.assertRaisesRegexp(ValueError, "not a scalar"):
functional_ops.map_fn(lambda x: x, 1)
+ @test_util.run_deprecated_v1
def testMap_Scoped(self):
with self.cached_session() as sess:
@@ -245,6 +249,7 @@ class FunctionalOpsTest(test.TestCase):
self.assertEqual(len(variables.trainable_variables()), 1)
self.assertAllEqual(doubles, self.evaluate(r))
+ @test_util.run_deprecated_v1
def testMap_Grad(self):
with self.cached_session():
param = constant_op.constant(2.0)
@@ -381,6 +386,7 @@ class FunctionalOpsTest(test.TestCase):
ValueError, "two structures don't have the same nested structure"):
functional_ops.scan(lambda a, x: (a, -a), elems, initializer)
+ @test_util.run_deprecated_v1
def testScan_Scoped(self):
with self.cached_session() as sess:
with variable_scope.variable_scope("root") as varscope:
@@ -425,6 +431,7 @@ class FunctionalOpsTest(test.TestCase):
# t_1 == 1, b == 4.5, y == 0.5, returns b * y * x = 9
self.assertAllClose([1., 1., 2.25, 9.], self.evaluate(r))
+ @test_util.run_deprecated_v1
def testScan_Control(self):
with self.cached_session() as sess:
s = array_ops.placeholder(dtypes.float32, shape=[None])
@@ -436,6 +443,7 @@ class FunctionalOpsTest(test.TestCase):
np.array([1.0, 3.0, 9.0]), sess.run(c, {s: [1, 3, 3],
b: True}))
+ @test_util.run_deprecated_v1
def testScan_Grad(self):
with self.cached_session():
elems = constant_op.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], name="data")
@@ -448,6 +456,7 @@ class FunctionalOpsTest(test.TestCase):
r = gradients_impl.gradients(r, v)[0]
self.assertAllEqual(873.0, self.evaluate(r))
+ @test_util.run_deprecated_v1
def testScanGradientWithPartStopGradient(self):
a = variables.Variable(0.0, name="a")
b = variables.Variable(0.0, name="b")
@@ -477,6 +486,7 @@ class FunctionalOpsTest(test.TestCase):
y = functional_ops.map_fn(lambda e: e, x)
self.assertAllEqual(y.get_shape(), self.evaluate(y).shape)
+ @test_util.run_deprecated_v1
def testMapUnknownShape(self):
x = array_ops.placeholder(dtypes.float32)
y = functional_ops.map_fn(lambda e: e, x)
@@ -484,6 +494,7 @@ class FunctionalOpsTest(test.TestCase):
@test_util.disable_control_flow_v2("b/119323354")
@test_util.run_in_graph_and_eager_modes
+ @test_util.run_deprecated_v1
def testMapEmptyScalar(self):
map_return = functional_ops.map_fn(lambda x: 1, constant_op.constant([]))
self.assertAllEqual([0], map_return.get_shape().dims)
@@ -492,6 +503,7 @@ class FunctionalOpsTest(test.TestCase):
# TODO(akshayka): this test fails in eager: the iterable is of length 0 so
# so the body of the while loop never executes
@test_util.disable_control_flow_v2("b/119323354")
+ @test_util.run_deprecated_v1
def testMapEmptyTensor(self):
with self.cached_session():
map_return = functional_ops.map_fn(lambda x: array_ops.zeros([3, 2]),
@@ -512,6 +524,7 @@ class FunctionalOpsTest(test.TestCase):
# TODO(akshayka): this test fails in eager: the iterable is of length 0 so
# so the body of the while loop never executes
+ @test_util.run_deprecated_v1
def testScanEmptyTensor(self):
with self.cached_session():
x = functional_ops.scan(
@@ -519,6 +532,7 @@ class FunctionalOpsTest(test.TestCase):
self.assertAllEqual([0, 2, 4], x.get_shape())
self.assertAllEqual(x.get_shape(), self.evaluate(x).shape)
+ @test_util.run_deprecated_v1
def testScanUnknownShape(self):
x = array_ops.placeholder(dtypes.float32)
initializer = array_ops.placeholder(dtypes.float32)
@@ -529,6 +543,7 @@ class FunctionalOpsTest(test.TestCase):
y = functional_ops.scan(fn, x, initializer=initializer)
self.assertIs(None, y.get_shape().dims)
+ @test_util.run_deprecated_v1
def testScanVaryingShape(self):
with self.cached_session() as sess:
x = array_ops.placeholder(dtype=dtypes.float32, shape=[None, 2])
@@ -545,6 +560,7 @@ class FunctionalOpsTest(test.TestCase):
sess.run([result, result_t, result_grad, result_t_grad],
feed_dict={x: [[1.0, 2.0]]})
+ @test_util.run_deprecated_v1
def testRemoteFunction(self):
worker_config = config_pb2.ConfigProto()
worker_config.device_count["CPU"] = 2
@@ -571,6 +587,7 @@ class FunctionalOpsTest(test.TestCase):
mul = self.evaluate(remote_op)
self.assertEqual(mul, [6])
+ @test_util.run_deprecated_v1
def testRemoteFunctionDirectSession(self):
worker_config = config_pb2.ConfigProto()
worker_config.device_count["CPU"] = 2
@@ -595,6 +612,7 @@ class FunctionalOpsTest(test.TestCase):
mul = self.evaluate(remote_op)
self.assertEqual(mul, [6])
+ @test_util.run_deprecated_v1
def testRemoteFunctionSameDeviceDirectSession(self):
@function.Defun(dtypes.int32, dtypes.int32)
@@ -680,6 +698,7 @@ class FunctionalOpsTest(test.TestCase):
ret = self.evaluate(remote_op)
self.assertAllEqual(ret, [b"a"])
+ @test_util.run_deprecated_v1
def testRemoteFunctionCrossProcess(self):
workers, _ = test_util.create_local_cluster(2, 1)
@@ -703,6 +722,7 @@ class FunctionalOpsTest(test.TestCase):
mul = self.evaluate(remote_op)
self.assertEqual(mul, 9)
+ @test_util.run_deprecated_v1
def testIf(self):
@function.Defun(dtypes.float32)
@@ -742,6 +762,7 @@ class FunctionalOpsTest(test.TestCase):
self.assertAllEqual(Run(sess, 20.), 210.)
self.assertAllEqual(Run(sess, 100.), 5050.)
+ @test_util.run_deprecated_v1
def testWhileLowering(self):
def Run(n, fetch_by_name):
@@ -776,6 +797,7 @@ class FunctionalOpsTest(test.TestCase):
self.assertAllEqual(Run(100., False), 5050.)
self.assertAllEqual(Run(100., True), 5050.)
+ @test_util.run_deprecated_v1
def testWhileError(self):
for use_gpu in (True, False):
with ops.Graph().as_default() as g:
@@ -922,6 +944,7 @@ class FunctionalOpsTest(test.TestCase):
self.assertTrue("TestBody_Cond" in names)
self.assertTrue("TestBody_Body" in names)
+ @test_util.run_deprecated_v1
def testForCapturedInputs(self):
v = variables.Variable(1.0)
@@ -996,12 +1019,15 @@ class FunctionalOpsTest(test.TestCase):
tf_for_ans = self._tfMLP(xval, wsval, bsval, rewrite_with_while)
self.assertAllClose(np_ans, tf_for_ans)
+ @test_util.run_deprecated_v1
def testForMLP(self):
self._testForMLP(False)
+ @test_util.run_deprecated_v1
def testForMLPWhile(self):
self._testForMLP(True)
+ @test_util.run_deprecated_v1
def testForError(self):
@function.Defun(dtypes.int32, dtypes.float32)
@@ -1024,6 +1050,7 @@ class FunctionalOpsTest(test.TestCase):
"For loop body returned 2 arguments. Expected: 1"):
functional_ops.For(0, 10, 1, [0.0], ReturnsTooManyArgs)[0].eval()
+ @test_util.run_deprecated_v1
def testGradient(self):
@function.Defun(dtypes.float32)
@@ -1049,6 +1076,7 @@ class FunctionalOpsTest(test.TestCase):
# below test cases.
class PartitionedCallTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testBasicSingleDevice(self):
@function.Defun(*[dtypes.float32] * 2)
@@ -1064,6 +1092,7 @@ class PartitionedCallTest(test.TestCase):
constant_op.constant(2.)], f=Body))
self.assertEqual(output, 6.)
+ @test_util.run_deprecated_v1
def testBasicMultiDevice(self):
config = config_pb2.ConfigProto(device_count={"CPU": 3})
@@ -1107,6 +1136,7 @@ class PartitionedCallTest(test.TestCase):
constant_op.constant(2.)], f=Body))
self.assertEqual(output, 6.)
+ @test_util.run_deprecated_v1
def testBasicNoDeviceAnnotations(self):
@function.Defun(*[dtypes.float32] * 2)
@@ -1121,6 +1151,7 @@ class PartitionedCallTest(test.TestCase):
constant_op.constant(2.)], f=Body))
self.assertEqual(output, 6.)
+ @test_util.run_deprecated_v1
def testShardsRunOnRequestedDevices(self):
config = config_pb2.ConfigProto(device_count={"CPU": 4})
@@ -1150,6 +1181,7 @@ class PartitionedCallTest(test.TestCase):
self.assertIn(compat.as_bytes("CPU:1"), outputs[1])
self.assertIn(compat.as_bytes("CPU:2"), outputs[2])
+ @test_util.run_deprecated_v1
def testAssignAddResourceVariable(self):
v = resource_variable_ops.ResourceVariable(1.0)
@@ -1201,6 +1233,7 @@ class PartitionedCallTest(test.TestCase):
self.assertAllEqual(expected, result)
# Use an invalid executor name to test the plumbing of the executor_type attr.
+ @test_util.run_deprecated_v1
def testExecutorTypeAttrExecutorNotFound(self):
@function.Defun(dtypes.int32)
def AddFive(x):
diff --git a/tensorflow/python/kernel_tests/gather_nd_op_test.py b/tensorflow/python/kernel_tests/gather_nd_op_test.py
index 532d8903ee1..320ffc9674b 100644
--- a/tensorflow/python/kernel_tests/gather_nd_op_test.py
+++ b/tensorflow/python/kernel_tests/gather_nd_op_test.py
@@ -27,6 +27,7 @@ from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
from tensorflow.python.framework import tensor_shape
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradients_impl
from tensorflow.python.ops import variables
@@ -54,6 +55,7 @@ class GatherNdTest(test.TestCase):
self._testSimpleDtype(np.complex128)
self._testSimpleDtype("|S") # byte strings in python2 + 3
+ @test_util.run_deprecated_v1
def testEmptyIndicesAndParamsOKButJustEmptyParamsFails(self):
with self.session(use_gpu=True):
params = np.ones((3, 3), dtype=np.float32)
@@ -190,6 +192,7 @@ class GatherNdTest(test.TestCase):
def assertIndexedSlices(self, t):
self.assertIsInstance(t, ops.IndexedSlices)
+ @test_util.run_deprecated_v1
def testUnknownIndices(self):
params = constant_op.constant([[0, 1, 2]])
indices = array_ops.placeholder(dtypes.int32)
@@ -198,6 +201,7 @@ class GatherNdTest(test.TestCase):
self.assertEqual(None, shape.ndims)
self.assertEqual(None, tensor_shape.dimension_value(shape[0]))
+ @test_util.run_deprecated_v1
def testBadIndicesCPU(self):
with self.session(use_gpu=False):
params = [0, 1, 2]
@@ -220,6 +224,7 @@ class GatherNdTest(test.TestCase):
r"indices\[0,1\] = \[7\] does not index into param shape \[3\]"):
self.evaluate(gather_nd)
+ @test_util.run_deprecated_v1
def testBadIndicesWithSlicesCPU(self):
with self.session(use_gpu=False):
params = [[0, 1, 2]]
@@ -242,6 +247,7 @@ class GatherNdTest(test.TestCase):
r"indices\[0,2\] = \[1\] does not index into param shape \[1,3\]"):
self.evaluate(gather_nd)
+ @test_util.run_deprecated_v1
def testGradientsRank2Elements(self):
indices = constant_op.constant([[0, 0], [1, 1]], dtype=dtypes.int32)
inputs = constant_op.constant([[1, 2], [3, 4]], dtype=dtypes.float64)
@@ -253,6 +259,7 @@ class GatherNdTest(test.TestCase):
with self.session(use_gpu=True):
assert np.array_equal(expected_grads, self.evaluate(grads))
+ @test_util.run_deprecated_v1
def testGradientsRank2Slices(self):
indices = constant_op.constant([[1], [0]], dtype=dtypes.int32)
inputs = constant_op.constant([[1, 2], [3, 4]], dtype=dtypes.float64)
@@ -265,6 +272,7 @@ class GatherNdTest(test.TestCase):
self.assertIndexedSlices(grads)
self.assertAllEqual(expected_grads, ops.convert_to_tensor(grads).eval())
+ @test_util.run_deprecated_v1
def testGradientsRank3Elements(self):
indices = constant_op.constant(
[[[0, 1], [1, 0]], [[0, 0], [1, 1]]], dtype=dtypes.int32)
@@ -280,6 +288,7 @@ class GatherNdTest(test.TestCase):
with self.session(use_gpu=True):
self.assertAllEqual(expected_grads, self.evaluate(grads))
+ @test_util.run_deprecated_v1
def testGradientsRank7Elements(self):
# Shape [1,1,2,1,1,2,2]
indices = constant_op.constant(
@@ -309,6 +318,7 @@ class GatherNdTest(test.TestCase):
with self.session(use_gpu=True):
self.assertAllEqual(expected_grads, self.evaluate(grads))
+ @test_util.run_deprecated_v1
def testGradientsInt64Indices(self):
indices = constant_op.constant(
[[[0, 1], [1, 0]], [[0, 0], [1, 1]]], dtype=dtypes.int64)
@@ -324,6 +334,7 @@ class GatherNdTest(test.TestCase):
with self.session(use_gpu=True):
self.assertAllEqual(expected_grads, self.evaluate(grads))
+ @test_util.run_deprecated_v1
def testGradientsRank2SlicesWithEmptySpace(self):
indices = constant_op.constant([[2], [0], [5]], dtype=dtypes.int32)
inputs = constant_op.constant(
diff --git a/tensorflow/python/kernel_tests/gather_op_test.py b/tensorflow/python/kernel_tests/gather_op_test.py
index 326e4aacd20..fc86068c3fc 100644
--- a/tensorflow/python/kernel_tests/gather_op_test.py
+++ b/tensorflow/python/kernel_tests/gather_op_test.py
@@ -23,6 +23,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradients_impl
from tensorflow.python.platform import test
@@ -87,6 +88,7 @@ class GatherTest(test.TestCase):
expected_shape = data.shape[:axis] + (4,) + data.shape[axis + 1:]
self.assertEqual(expected_shape, gather_t.get_shape())
+ @test_util.run_deprecated_v1
def testHigherRank(self):
# We check that scalar and empty indices shapes work as well
shape = (2, 1, 3, 2)
@@ -148,6 +150,7 @@ class GatherTest(test.TestCase):
atol=2e-6,
rtol=2e-6)
+ @test_util.run_deprecated_v1
def testString(self):
params = np.array([[b"asdf", b"zxcv"], [b"qwer", b"uiop"]])
with self.cached_session():
@@ -156,6 +159,7 @@ class GatherTest(test.TestCase):
self.assertAllEqual([b"asdf", b"qwer"],
array_ops.gather(params, 0, axis=1).eval())
+ @test_util.run_deprecated_v1
def testUInt32AndUInt64(self):
for unsigned_type in (dtypes.uint32, dtypes.uint64):
params = self._buildParams(
@@ -165,12 +169,14 @@ class GatherTest(test.TestCase):
array_ops.gather(params, 1, axis=0).eval())
self.assertAllEqual([1, 7], array_ops.gather(params, 0, axis=1).eval())
+ @test_util.run_deprecated_v1
def testUnknownIndices(self):
params = constant_op.constant([[0, 1, 2]])
indices = array_ops.placeholder(dtypes.int32)
gather_t = array_ops.gather(params, indices)
self.assertEqual(None, gather_t.get_shape())
+ @test_util.run_deprecated_v1
def testUnknownAxis(self):
params = constant_op.constant([[0, 1, 2]])
indices = constant_op.constant([[0, 0], [0, 0]])
@@ -204,6 +210,7 @@ class GatherTest(test.TestCase):
with self.assertRaisesOpError(r"indices\[0,0\] = 7 is not in \[0, 3\)"):
array_ops.gather(params, [[7]], axis=1).eval()
+ @test_util.run_deprecated_v1
def testBadAxis(self):
with self.session(use_gpu=True):
params = [0, 1, 2]
@@ -220,6 +227,7 @@ class GatherTest(test.TestCase):
array_ops.gather(params_ph, indices, axis=bad_axis).eval(
feed_dict={params_ph: params})
+ @test_util.run_deprecated_v1
def testEmptySlices(self):
with self.session(use_gpu=True):
for dtype in _TEST_TYPES:
diff --git a/tensorflow/python/kernel_tests/gradient_correctness_test.py b/tensorflow/python/kernel_tests/gradient_correctness_test.py
index 12b8a4c8e3b..0148de5047a 100644
--- a/tensorflow/python/kernel_tests/gradient_correctness_test.py
+++ b/tensorflow/python/kernel_tests/gradient_correctness_test.py
@@ -22,6 +22,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import gradients_impl
from tensorflow.python.ops import math_ops
from tensorflow.python.platform import test
@@ -29,6 +30,7 @@ from tensorflow.python.platform import test
class GradientCorrectnessTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testMultipleOutputChainedGradients(self):
with self.cached_session() as sess:
x = constant_op.constant(1.0, dtype=dtypes.float32)
@@ -40,18 +42,21 @@ class GradientCorrectnessTest(test.TestCase):
# [dexp(x)/dx + d(log(exp(x)))/dx] @ x=1 == exp(1) + 1
self.assertAllClose(grad_vals[0], exp1_plus_one)
+ @test_util.run_deprecated_v1
def testIdentityGradient(self):
x = constant_op.constant(3.)
dx_dx, = gradients_impl.gradients(x, x)
with self.cached_session() as sess:
self.assertAllClose(1., self.evaluate(dx_dx))
+ @test_util.run_deprecated_v1
def testIntegerIdentityGradient(self):
x = constant_op.constant(3)
dx_dx, = gradients_impl.gradients(x, x)
with self.cached_session() as sess:
self.assertAllClose(1, self.evaluate(dx_dx))
+ @test_util.run_deprecated_v1
def testGradientWithIntegerPath(self):
x = constant_op.constant([3.9, 4.1])
k = math_ops.to_float(math_ops.to_int32(x))
@@ -60,6 +65,7 @@ class GradientCorrectnessTest(test.TestCase):
with self.cached_session() as sess:
self.assertAllClose([3., 4.], self.evaluate(dy_dx))
+ @test_util.run_deprecated_v1
def testNoIntegerGradient1(self):
x = constant_op.constant([3.9, 4.1])
k = math_ops.to_float(math_ops.to_int32(x))
@@ -67,6 +73,7 @@ class GradientCorrectnessTest(test.TestCase):
dy_dx, = gradients_impl.gradients(y, x)
self.assertIsNone(dy_dx)
+ @test_util.run_deprecated_v1
def testNoIntegerGradient2(self):
k = constant_op.constant([3, 4])
x = math_ops.to_float(k)
@@ -74,18 +81,21 @@ class GradientCorrectnessTest(test.TestCase):
dy_dk, = gradients_impl.gradients(y, k)
self.assertIsNone(dy_dk)
+ @test_util.run_deprecated_v1
def testNoIntegerGradient3(self):
k = constant_op.constant([3, 4])
m = k * k
dm_dk, = gradients_impl.gradients(m, k)
self.assertIsNone(dm_dk)
+ @test_util.run_deprecated_v1
def testNoIntegerGradient4(self):
k = constant_op.constant([3, 4])
m = k * k * k
dm_dk, = gradients_impl.gradients(m, k)
self.assertIsNone(dm_dk)
+ @test_util.run_deprecated_v1
def testNoIntegerGradient5(self):
k = constant_op.constant([3, 4])
m = k * k
@@ -93,6 +103,7 @@ class GradientCorrectnessTest(test.TestCase):
dn_dk, = gradients_impl.gradients(n, k)
self.assertIsNone(dn_dk)
+ @test_util.run_deprecated_v1
def testNoIntegerGradient6(self):
k = constant_op.constant(3)
x = math_ops.to_float(k)
diff --git a/tensorflow/python/kernel_tests/identity_n_op_py_test.py b/tensorflow/python/kernel_tests/identity_n_op_py_test.py
index 518733cd8e9..a1110d640f0 100644
--- a/tensorflow/python/kernel_tests/identity_n_op_py_test.py
+++ b/tensorflow/python/kernel_tests/identity_n_op_py_test.py
@@ -21,12 +21,14 @@ from __future__ import print_function
import numpy as np
from tensorflow.python.framework import constant_op
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.platform import test
class IdentityNOpTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testInt32String_6(self):
with self.cached_session() as sess:
[value0, value1] = sess.run(
@@ -36,6 +38,7 @@ class IdentityNOpTest(test.TestCase):
self.assertAllEqual(
np.array([b"a", b"b", b"C", b"d", b"E", b"f", b"g"]), value1)
+ @test_util.run_deprecated_v1
def testInt32_shapes(self):
with self.cached_session() as sess:
inp0 = constant_op.constant([10, 20, 30, 40, 50, 60], shape=[2, 3])
@@ -50,6 +53,7 @@ class IdentityNOpTest(test.TestCase):
np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12], [13, 14, 15]]),
value2)
+ @test_util.run_deprecated_v1
def testString(self):
source = [b"A", b"b", b"C", b"d", b"E", b"f"]
with self.cached_session() as sess:
diff --git a/tensorflow/python/kernel_tests/identity_op_py_test.py b/tensorflow/python/kernel_tests/identity_op_py_test.py
index 88ea10c22a3..1a6794e896f 100644
--- a/tensorflow/python/kernel_tests/identity_op_py_test.py
+++ b/tensorflow/python/kernel_tests/identity_op_py_test.py
@@ -22,6 +22,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gen_array_ops
from tensorflow.python.ops import variables
@@ -30,17 +31,20 @@ from tensorflow.python.platform import test
class IdentityOpTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testInt32_6(self):
with self.cached_session():
value = array_ops.identity([1, 2, 3, 4, 5, 6]).eval()
self.assertAllEqual(np.array([1, 2, 3, 4, 5, 6]), value)
+ @test_util.run_deprecated_v1
def testInt32_2_3(self):
with self.cached_session():
inp = constant_op.constant([10, 20, 30, 40, 50, 60], shape=[2, 3])
value = array_ops.identity(inp).eval()
self.assertAllEqual(np.array([[10, 20, 30], [40, 50, 60]]), value)
+ @test_util.run_deprecated_v1
def testString(self):
source = [b"A", b"b", b"C", b"d", b"E", b"f"]
with self.cached_session():
@@ -58,6 +62,7 @@ class IdentityOpTest(test.TestCase):
self.assertEquals(shape,
array_ops.identity(np.array(array_2x3)).get_shape())
+ @test_util.run_deprecated_v1
def testRefIdentityShape(self):
with self.cached_session():
shape = [2, 3]
diff --git a/tensorflow/python/kernel_tests/init_ops_test.py b/tensorflow/python/kernel_tests/init_ops_test.py
index 87c7bbef3cf..09b9944baa1 100644
--- a/tensorflow/python/kernel_tests/init_ops_test.py
+++ b/tensorflow/python/kernel_tests/init_ops_test.py
@@ -25,6 +25,7 @@ from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
from tensorflow.python.framework import random_seed
+from tensorflow.python.framework import test_util
from tensorflow.python.layers import convolutional
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import init_ops
@@ -106,6 +107,7 @@ def _init_sampler(tc, init, num):
class ConstantInitializersTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testZerosInitializer(self):
with self.session(use_gpu=True):
shape = [2, 3]
@@ -114,6 +116,7 @@ class ConstantInitializersTest(test.TestCase):
x.initializer.run()
self.assertAllEqual(x.eval(), np.zeros(shape))
+ @test_util.run_deprecated_v1
def testOnesInitializer(self):
with self.session(use_gpu=True):
shape = [2, 3]
@@ -122,6 +125,7 @@ class ConstantInitializersTest(test.TestCase):
x.initializer.run()
self.assertAllEqual(x.eval(), np.ones(shape))
+ @test_util.run_deprecated_v1
def testConstantZeroInitializer(self):
with self.session(use_gpu=True):
shape = [2, 3]
@@ -130,6 +134,7 @@ class ConstantInitializersTest(test.TestCase):
x.initializer.run()
self.assertAllEqual(x.eval(), np.zeros(shape))
+ @test_util.run_deprecated_v1
def testConstantOneInitializer(self):
with self.session(use_gpu=True):
shape = [2, 3]
@@ -138,6 +143,7 @@ class ConstantInitializersTest(test.TestCase):
x.initializer.run()
self.assertAllEqual(x.eval(), np.ones(shape))
+ @test_util.run_deprecated_v1
def testConstantIntInitializer(self):
with self.session(use_gpu=True):
shape = [2, 3]
@@ -150,6 +156,7 @@ class ConstantInitializersTest(test.TestCase):
self.assertEqual(x.dtype.base_dtype, dtypes.int32)
self.assertAllEqual(x.eval(), 7 * np.ones(shape, dtype=np.int32))
+ @test_util.run_deprecated_v1
def testConstantTupleInitializer(self):
with self.session(use_gpu=True):
shape = [3]
@@ -173,6 +180,7 @@ class ConstantInitializersTest(test.TestCase):
for a, e in zip(actual, expected):
self.assertEqual(a, e)
+ @test_util.run_deprecated_v1
def testNDimConstantInitializer(self):
value = [0, 1, 2, 3, 4, 5]
shape = [2, 3]
@@ -199,6 +207,7 @@ class ConstantInitializersTest(test.TestCase):
e = expected[i] if i < len(expected) else expected[-1]
self.assertEqual(a, e)
+ @test_util.run_deprecated_v1
def testNDimConstantInitializerLessValues(self):
value = [0, 1, 2, 3, 4, 5]
shape = [2, 4]
@@ -222,6 +231,7 @@ class ConstantInitializersTest(test.TestCase):
shape=shape,
initializer=init)
+ @test_util.run_deprecated_v1
def testNDimConstantInitializerMoreValues(self):
value = [0, 1, 2, 3, 4, 5, 6, 7]
shape = [2, 3]
@@ -243,18 +253,21 @@ class ConstantInitializersTest(test.TestCase):
class RandomNormalInitializationTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testInitializerIdentical(self):
for dtype in [dtypes.float32, dtypes.float64]:
init1 = init_ops.random_normal_initializer(0.0, 1.0, seed=1, dtype=dtype)
init2 = init_ops.random_normal_initializer(0.0, 1.0, seed=1, dtype=dtype)
self.assertTrue(identicaltest(self, init1, init2))
+ @test_util.run_deprecated_v1
def testInitializerDifferent(self):
for dtype in [dtypes.float32, dtypes.float64]:
init1 = init_ops.random_normal_initializer(0.0, 1.0, seed=1, dtype=dtype)
init2 = init_ops.random_normal_initializer(0.0, 1.0, seed=2, dtype=dtype)
self.assertFalse(identicaltest(self, init1, init2))
+ @test_util.run_deprecated_v1
def testDuplicatedInitializer(self):
init = init_ops.random_normal_initializer(0.0, 1.0)
self.assertFalse(duplicated_initializer(self, init, 1))
@@ -270,6 +283,7 @@ class RandomNormalInitializationTest(test.TestCase):
class TruncatedNormalInitializationTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testInitializerIdentical(self):
for dtype in [dtypes.float32, dtypes.float64]:
init1 = init_ops.truncated_normal_initializer(
@@ -278,6 +292,7 @@ class TruncatedNormalInitializationTest(test.TestCase):
0.0, 1.0, seed=1, dtype=dtype)
self.assertTrue(identicaltest(self, init1, init2))
+ @test_util.run_deprecated_v1
def testInitializerDifferent(self):
for dtype in [dtypes.float32, dtypes.float64]:
init1 = init_ops.truncated_normal_initializer(
@@ -286,6 +301,7 @@ class TruncatedNormalInitializationTest(test.TestCase):
0.0, 1.0, seed=2, dtype=dtype)
self.assertFalse(identicaltest(self, init1, init2))
+ @test_util.run_deprecated_v1
def testDuplicatedInitializer(self):
init = init_ops.truncated_normal_initializer(0.0, 1.0)
self.assertFalse(duplicated_initializer(self, init, 1))
@@ -301,18 +317,21 @@ class TruncatedNormalInitializationTest(test.TestCase):
class RandomUniformInitializationTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testInitializerIdentical(self):
for dtype in [dtypes.float32, dtypes.float64, dtypes.int64]:
init1 = init_ops.random_uniform_initializer(0, 7, seed=1, dtype=dtype)
init2 = init_ops.random_uniform_initializer(0, 7, seed=1, dtype=dtype)
self.assertTrue(identicaltest(self, init1, init2))
+ @test_util.run_deprecated_v1
def testInitializerDifferent(self):
for dtype in [dtypes.float32, dtypes.float64, dtypes.int32, dtypes.int64]:
init1 = init_ops.random_uniform_initializer(0, 7, seed=1, dtype=dtype)
init2 = init_ops.random_uniform_initializer(0, 7, seed=2, dtype=dtype)
self.assertFalse(identicaltest(self, init1, init2))
+ @test_util.run_deprecated_v1
def testDuplicatedInitializer(self):
init = init_ops.random_uniform_initializer(0.0, 1.0)
self.assertFalse(duplicated_initializer(self, init, 1))
@@ -320,6 +339,7 @@ class RandomUniformInitializationTest(test.TestCase):
class UniformUnitScalingInitializationTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testInitializerIdentical(self):
for dtype in [dtypes.float32, dtypes.float64]:
init1 = init_ops.uniform_unit_scaling_initializer(seed=1, dtype=dtype)
@@ -331,6 +351,7 @@ class UniformUnitScalingInitializationTest(test.TestCase):
1.5, seed=1, dtype=dtype)
self.assertTrue(identicaltest(self, init3, init4))
+ @test_util.run_deprecated_v1
def testInitializerDifferent(self):
for dtype in [dtypes.float32, dtypes.float64]:
init1 = init_ops.uniform_unit_scaling_initializer(seed=1, dtype=dtype)
@@ -341,6 +362,7 @@ class UniformUnitScalingInitializationTest(test.TestCase):
self.assertFalse(identicaltest(self, init1, init3))
self.assertFalse(identicaltest(self, init2, init3))
+ @test_util.run_deprecated_v1
def testZeroSize(self):
shape = [0, 2]
with self.cached_session():
@@ -351,6 +373,7 @@ class UniformUnitScalingInitializationTest(test.TestCase):
variables.global_variables_initializer().run()
self.assertAllEqual(shape, self.evaluate(x).shape)
+ @test_util.run_deprecated_v1
def testDuplicatedInitializer(self):
init = init_ops.uniform_unit_scaling_initializer()
self.assertFalse(duplicated_initializer(self, init, 1))
@@ -364,6 +387,7 @@ class UniformUnitScalingInitializationTest(test.TestCase):
class VarianceScalingInitializationTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testTruncatedNormalDistribution(self):
shape = [100, 100]
expect_mean = 0.
@@ -381,6 +405,7 @@ class VarianceScalingInitializationTest(test.TestCase):
self.assertNear(np.mean(x), expect_mean, err=1e-2)
self.assertNear(np.var(x), expect_var, err=1e-2)
+ @test_util.run_deprecated_v1
def testNormalDistribution(self):
shape = [100, 100]
expect_mean = 0.
@@ -397,6 +422,7 @@ class VarianceScalingInitializationTest(test.TestCase):
self.assertNear(np.mean(x), expect_mean, err=1e-2)
self.assertNear(np.var(x), expect_var, err=1e-2)
+ @test_util.run_deprecated_v1
def testUntruncatedNormalDistribution(self):
shape = [100, 100]
expect_mean = 0.
@@ -414,6 +440,7 @@ class VarianceScalingInitializationTest(test.TestCase):
self.assertNear(np.mean(x), expect_mean, err=1e-2)
self.assertNear(np.var(x), expect_var, err=1e-2)
+ @test_util.run_deprecated_v1
def testUniformDistribution(self):
shape = [100, 100]
expect_mean = 0.
@@ -449,6 +476,7 @@ class RangeTest(test.TestCase):
self._Range(100, 500, 100), np.array([100, 200, 300, 400])))
self.assertEqual(math_ops.range(0, 5, 1).dtype, dtypes.int32)
+ @test_util.run_deprecated_v1
def testLimitOnly(self):
with self.session(use_gpu=True):
self.assertAllEqual(np.arange(5), math_ops.range(5).eval())
@@ -583,18 +611,21 @@ class DeviceTest(test.TestCase):
class OrthogonalInitializerTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testInitializerIdentical(self):
for dtype in [dtypes.float32, dtypes.float64]:
init1 = init_ops.orthogonal_initializer(seed=1, dtype=dtype)
init2 = init_ops.orthogonal_initializer(seed=1, dtype=dtype)
self.assertTrue(identicaltest(self, init1, init2, (10, 10)))
+ @test_util.run_deprecated_v1
def testInitializerDifferent(self):
for dtype in [dtypes.float32, dtypes.float64]:
init1 = init_ops.orthogonal_initializer(seed=1, dtype=dtype)
init2 = init_ops.orthogonal_initializer(seed=2, dtype=dtype)
self.assertFalse(identicaltest(self, init1, init2, (10, 10)))
+ @test_util.run_deprecated_v1
def testDuplicatedInitializer(self):
init = init_ops.orthogonal_initializer()
self.assertFalse(duplicated_initializer(self, init, 1, (10, 10)))
@@ -608,6 +639,7 @@ class OrthogonalInitializerTest(test.TestCase):
with self.session(graph=ops.Graph(), use_gpu=True):
self.assertRaises(ValueError, init1, shape=[5])
+ @test_util.run_deprecated_v1
def testGain(self):
shape = (10, 10)
for dtype in [dtypes.float32, dtypes.float64]:
@@ -618,6 +650,7 @@ class OrthogonalInitializerTest(test.TestCase):
t2 = init2(shape).eval()
self.assertAllClose(t1, t2 / 3.14)
+ @test_util.run_deprecated_v1
def testShapesValues(self):
for dtype in [dtypes.float32, dtypes.float64]:
for shape in [(10, 10), (10, 9, 8), (100, 5, 5), (50, 40), (40, 50)]:
@@ -639,18 +672,21 @@ class OrthogonalInitializerTest(test.TestCase):
class ConvolutionDeltaOrthogonalInitializerTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testInitializerIdentical(self):
for dtype in [dtypes.float32, dtypes.float64]:
init1 = init_ops.convolutional_delta_orthogonal(seed=1, dtype=dtype)
init2 = init_ops.convolutional_delta_orthogonal(seed=1, dtype=dtype)
self.assertTrue(identicaltest(self, init1, init2, (3, 3, 10, 10)))
+ @test_util.run_deprecated_v1
def testInitializerDifferent(self):
for dtype in [dtypes.float32, dtypes.float64]:
init1 = init_ops.convolutional_delta_orthogonal(seed=1, dtype=dtype)
init2 = init_ops.convolutional_delta_orthogonal(seed=2, dtype=dtype)
self.assertFalse(identicaltest(self, init1, init2, (3, 3, 10, 10)))
+ @test_util.run_deprecated_v1
def testDuplicatedInitializer(self):
init = init_ops.convolutional_delta_orthogonal()
self.assertFalse(duplicated_initializer(self, init, 1, (3, 3, 10, 10)))
@@ -665,6 +701,7 @@ class ConvolutionDeltaOrthogonalInitializerTest(test.TestCase):
with self.session(graph=ops.Graph(), use_gpu=True):
self.assertRaises(ValueError, init1, shape=[3, 3, 6, 5])
+ @test_util.run_deprecated_v1
def testGain(self):
shape = (3, 3, 10, 10)
for dtype in [dtypes.float32, dtypes.float64]:
@@ -676,6 +713,7 @@ class ConvolutionDeltaOrthogonalInitializerTest(test.TestCase):
t2 = init2(shape).eval()
self.assertAllClose(t1, t2 / 3.14)
+ @test_util.run_deprecated_v1
def testShapesValues(self):
gain = 3.14
for dtype in [dtypes.float32]:
@@ -711,6 +749,7 @@ class ConvolutionDeltaOrthogonalInitializerTest(test.TestCase):
# Check isometry of the delta-orthogonal kernel.
self.assertAllClose(self.evaluate(ratio), gain, rtol=tol, atol=tol)
+ @test_util.run_deprecated_v1
def testNonuniformity(self):
value = 0
abs_value = 0
@@ -738,18 +777,21 @@ class ConvolutionDeltaOrthogonalInitializerTest(test.TestCase):
class ConvolutionOrthogonal1dInitializerTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testInitializerIdentical(self):
for dtype in [dtypes.float32, dtypes.float64]:
init1 = init_ops.convolutional_orthogonal_1d(seed=1, dtype=dtype)
init2 = init_ops.convolutional_orthogonal_1d(seed=1, dtype=dtype)
self.assertTrue(identicaltest(self, init1, init2, (3, 10, 10)))
+ @test_util.run_deprecated_v1
def testInitializerDifferent(self):
for dtype in [dtypes.float32, dtypes.float64]:
init1 = init_ops.convolutional_orthogonal_1d(seed=1, dtype=dtype)
init2 = init_ops.convolutional_orthogonal_1d(seed=2, dtype=dtype)
self.assertFalse(identicaltest(self, init1, init2, (3, 10, 10)))
+ @test_util.run_deprecated_v1
def testDuplicatedInitializer(self):
init = init_ops.convolutional_orthogonal_1d()
self.assertFalse(duplicated_initializer(self, init, 1, (3, 10, 10)))
@@ -764,6 +806,7 @@ class ConvolutionOrthogonal1dInitializerTest(test.TestCase):
with self.session(graph=ops.Graph(), use_gpu=True):
self.assertRaises(ValueError, init1, shape=[3, 6, 5])
+ @test_util.run_deprecated_v1
def testGain(self):
shape = (3, 10, 10)
for dtype in [dtypes.float32, dtypes.float64]:
@@ -775,6 +818,7 @@ class ConvolutionOrthogonal1dInitializerTest(test.TestCase):
t2 = init2(shape).eval()
self.assertAllClose(t1, t2 / 3.14)
+ @test_util.run_deprecated_v1
def testNonuniformity(self):
value = 0
abs_value = 0
@@ -799,6 +843,7 @@ class ConvolutionOrthogonal1dInitializerTest(test.TestCase):
# Compute the sum of the absolute values of 'count' determinants
self.assertAllClose(abs_value, count, rtol=tol, atol=tol)
+ @test_util.run_deprecated_v1
def testShapesValues(self):
def circular_pad(input_, width, kernel_size):
"""Pad input_ for computing (circular) convolution.
@@ -852,18 +897,21 @@ class ConvolutionOrthogonal1dInitializerTest(test.TestCase):
class ConvolutionOrthogonal2dInitializerTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testInitializerIdentical(self):
for dtype in [dtypes.float32, dtypes.float64]:
init1 = init_ops.convolutional_orthogonal_2d(seed=1, dtype=dtype)
init2 = init_ops.convolutional_orthogonal_2d(seed=1, dtype=dtype)
self.assertTrue(identicaltest(self, init1, init2, (3, 3, 10, 10)))
+ @test_util.run_deprecated_v1
def testInitializerDifferent(self):
for dtype in [dtypes.float32, dtypes.float64]:
init1 = init_ops.convolutional_orthogonal_2d(seed=1, dtype=dtype)
init2 = init_ops.convolutional_orthogonal_2d(seed=2, dtype=dtype)
self.assertFalse(identicaltest(self, init1, init2, (3, 3, 10, 10)))
+ @test_util.run_deprecated_v1
def testDuplicatedInitializer(self):
init = init_ops.convolutional_orthogonal_2d()
self.assertFalse(duplicated_initializer(self, init, 1, (3, 3, 10, 10)))
@@ -878,6 +926,7 @@ class ConvolutionOrthogonal2dInitializerTest(test.TestCase):
with self.session(graph=ops.Graph(), use_gpu=True):
self.assertRaises(ValueError, init1, shape=[3, 3, 6, 5])
+ @test_util.run_deprecated_v1
def testGain(self):
shape = (3, 3, 10, 10)
for dtype in [dtypes.float32, dtypes.float64]:
@@ -889,6 +938,7 @@ class ConvolutionOrthogonal2dInitializerTest(test.TestCase):
t2 = init2(shape).eval()
self.assertAllClose(t1, t2 / 3.14)
+ @test_util.run_deprecated_v1
def testShapesValues(self):
def circular_pad(input_, width, kernel_size):
"""Pad input_ for computing (circular) convolution.
@@ -947,18 +997,21 @@ class ConvolutionOrthogonal2dInitializerTest(test.TestCase):
class ConvolutionOrthogonal3dInitializerTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testInitializerIdentical(self):
for dtype in [dtypes.float32, dtypes.float64]:
init1 = init_ops.convolutional_orthogonal_3d(seed=1, dtype=dtype)
init2 = init_ops.convolutional_orthogonal_3d(seed=1, dtype=dtype)
self.assertTrue(identicaltest(self, init1, init2, (3, 3, 3, 10, 10)))
+ @test_util.run_deprecated_v1
def testInitializerDifferent(self):
for dtype in [dtypes.float32, dtypes.float64]:
init1 = init_ops.convolutional_orthogonal_3d(seed=1, dtype=dtype)
init2 = init_ops.convolutional_orthogonal_3d(seed=2, dtype=dtype)
self.assertFalse(identicaltest(self, init1, init2, (3, 3, 3, 10, 10)))
+ @test_util.run_deprecated_v1
def testDuplicatedInitializer(self):
init = init_ops.convolutional_orthogonal_3d()
self.assertFalse(duplicated_initializer(self, init, 1, (3, 3, 3, 10, 10)))
@@ -973,6 +1026,7 @@ class ConvolutionOrthogonal3dInitializerTest(test.TestCase):
with self.session(graph=ops.Graph(), use_gpu=True):
self.assertRaises(ValueError, init1, shape=[3, 3, 3, 6, 5])
+ @test_util.run_deprecated_v1
def testGain(self):
shape = (3, 3, 3, 10, 10)
for dtype in [dtypes.float32, dtypes.float64]:
@@ -984,6 +1038,7 @@ class ConvolutionOrthogonal3dInitializerTest(test.TestCase):
t2 = init2(shape).eval()
self.assertAllClose(t1, t2 / 3.14)
+ @test_util.run_deprecated_v1
def testNonuniformity(self):
value = 0
abs_value = 0
@@ -1008,6 +1063,7 @@ class ConvolutionOrthogonal3dInitializerTest(test.TestCase):
# Compute the sum of the absolute values of 'count' determinants
self.assertAllClose(abs_value, count, rtol=tol, atol=tol)
+ @test_util.run_deprecated_v1
def testShapesValues(self):
def circular_pad(input_, width, kernel_size):
"""Padding input_ for computing circular convolution.
@@ -1083,12 +1139,14 @@ class IdentityInitializerTest(test.TestCase):
self.assertRaises(ValueError, init, shape=[5])
self.assertRaises(ValueError, init, shape=[])
+ @test_util.run_deprecated_v1
def testNonSquare(self):
init = init_ops.identity_initializer()
shape = (10, 5)
with self.session(graph=ops.Graph(), use_gpu=True):
self.assertAllClose(init(shape).eval(), np.eye(*shape))
+ @test_util.run_deprecated_v1
def testGain(self):
shape = (10, 10)
for dtype in [dtypes.float32, dtypes.float64]:
@@ -1099,6 +1157,7 @@ class IdentityInitializerTest(test.TestCase):
with self.session(graph=ops.Graph(), use_gpu=True):
self.assertAllClose(init_custom(shape).eval(), np.eye(*shape) * 0.9)
+ @test_util.run_deprecated_v1
def testPartitions(self):
shape = (10, 10)
init = init_ops.identity_initializer()
diff --git a/tensorflow/python/kernel_tests/inplace_ops_test.py b/tensorflow/python/kernel_tests/inplace_ops_test.py
index e0c36d3d2e9..9eaaac7a248 100644
--- a/tensorflow/python/kernel_tests/inplace_ops_test.py
+++ b/tensorflow/python/kernel_tests/inplace_ops_test.py
@@ -31,6 +31,7 @@ from tensorflow.python.platform import test as test_lib
class InplaceOpsTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testBasicUpdate(self):
for dtype in [dtypes.float32, dtypes.int32, dtypes.int64]:
with self.session(use_gpu=True):
@@ -48,6 +49,7 @@ class InplaceOpsTest(test_util.TensorFlowTestCase):
y[5, :] = 7
self.assertAllClose(x.eval(), y)
+ @test_util.run_deprecated_v1
def testBasicUpdateBool(self):
with self.session(use_gpu=True):
x = array_ops.ones([7, 3], dtypes.bool)
@@ -65,6 +67,7 @@ class InplaceOpsTest(test_util.TensorFlowTestCase):
y[5, :] = False
self.assertAllClose(x.eval(), y)
+ @test_util.run_deprecated_v1
def testBasicAdd(self):
for dtype in [dtypes.float32, dtypes.int32, dtypes.int64]:
with self.cached_session(use_gpu=True):
@@ -84,6 +87,7 @@ class InplaceOpsTest(test_util.TensorFlowTestCase):
y[:, :] += 99
self.assertAllClose(x.eval(), y)
+ @test_util.run_deprecated_v1
def testBasicSub(self):
for dtype in [dtypes.float32, dtypes.int32, dtypes.int64]:
with self.cached_session(use_gpu=True):
@@ -103,6 +107,7 @@ class InplaceOpsTest(test_util.TensorFlowTestCase):
y[:, :] -= 99
self.assertAllClose(x.eval(), y)
+ @test_util.run_deprecated_v1
def testRandom(self):
with self.session(use_gpu=True):
d0, d1, d2 = 100, 3, 5
@@ -123,6 +128,7 @@ class InplaceOpsTest(test_util.TensorFlowTestCase):
y[idx, :] -= val
self.assertAllClose(x.eval(), y)
+ @test_util.run_deprecated_v1
def testRandom1D(self):
with self.session(use_gpu=True):
d0 = 100
@@ -164,6 +170,7 @@ class InplaceOpsTest(test_util.TensorFlowTestCase):
"i and x shape doesn't match"):
_ = inplace_ops.inplace_update([[1.]], [0, 1], [[10]]).eval()
+ @test_util.run_deprecated_v1
def testEmpty(self):
for dtype in [
dtypes.float32, dtypes.float64, dtypes.int32, dtypes.int64, dtypes.bool,
diff --git a/tensorflow/python/kernel_tests/io_ops_test.py b/tensorflow/python/kernel_tests/io_ops_test.py
index a6b477062eb..c5df5231bf6 100644
--- a/tensorflow/python/kernel_tests/io_ops_test.py
+++ b/tensorflow/python/kernel_tests/io_ops_test.py
@@ -23,6 +23,7 @@ import os
import shutil
import tempfile
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import io_ops
from tensorflow.python.platform import test
from tensorflow.python.util import compat
@@ -30,6 +31,7 @@ from tensorflow.python.util import compat
class IoOpsTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testReadFile(self):
cases = ['', 'Some contents', 'Неки садржаји на српском']
for contents in cases:
@@ -78,6 +80,7 @@ class IoOpsTest(test.TestCase):
compat.as_bytes(files[i].name) for i in range(len(files))
if i in indices)
+ @test_util.run_deprecated_v1
def testMatchingFiles(self):
cases = [
'ABcDEF.GH', 'ABzDEF.GH', 'ABasdfjklDEF.GH', 'AB3DEF.GH', 'AB4DEF.GH',
diff --git a/tensorflow/python/kernel_tests/linalg/linear_operator_addition_test.py b/tensorflow/python/kernel_tests/linalg/linear_operator_addition_test.py
index 628ed998c54..627349c69b3 100644
--- a/tensorflow/python/kernel_tests/linalg/linear_operator_addition_test.py
+++ b/tensorflow/python/kernel_tests/linalg/linear_operator_addition_test.py
@@ -19,6 +19,7 @@ from __future__ import print_function
import numpy as np
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import linalg_ops
from tensorflow.python.ops.linalg import linalg as linalg_lib
from tensorflow.python.ops.linalg import linear_operator_addition
@@ -69,6 +70,7 @@ class LinearOperatorAdditionCorrectnessTest(test.TestCase):
with self.assertRaisesRegexp(TypeError, "contain only LinearOperator"):
add_operators([1, 2])
+ @test_util.run_deprecated_v1
def test_two_diag_operators(self):
op_a = linalg.LinearOperatorDiag(
[1., 1.], is_positive_definite=True, name="A")
@@ -89,6 +91,7 @@ class LinearOperatorAdditionCorrectnessTest(test.TestCase):
# Enforce particular name for this simple case
self.assertEqual("Add/B__A/", op.name)
+ @test_util.run_deprecated_v1
def test_three_diag_operators(self):
op1 = linalg.LinearOperatorDiag(
[1., 1.], is_positive_definite=True, name="op1")
@@ -109,6 +112,7 @@ class LinearOperatorAdditionCorrectnessTest(test.TestCase):
# Positive definite ==> non-singular
self.assertTrue(op.is_non_singular)
+ @test_util.run_deprecated_v1
def test_diag_tril_diag(self):
op1 = linalg.LinearOperatorDiag(
[1., 1.], is_non_singular=True, name="diag_a")
@@ -134,6 +138,7 @@ class LinearOperatorAdditionCorrectnessTest(test.TestCase):
# Since no custom hint was provided, we default to None (unknown).
self.assertEqual(None, op.is_non_singular)
+ @test_util.run_deprecated_v1
def test_matrix_diag_tril_diag_uses_custom_name(self):
op0 = linalg.LinearOperatorFullMatrix(
[[-1., -1.], [-1., -1.]], name="matrix")
@@ -217,6 +222,7 @@ class LinearOperatorOrderOfAdditionTest(test.TestCase):
self.assertEqual(1, len(op_sum))
self.assertIsInstance(op_sum[0], linalg.LinearOperatorLowerTriangular)
+ @test_util.run_deprecated_v1
def test_cannot_add_everything_so_return_more_than_one_operator(self):
diag1 = linalg.LinearOperatorDiag([1.])
diag2 = linalg.LinearOperatorDiag([2.])
@@ -261,6 +267,7 @@ class AddAndReturnScaledIdentityTest(test.TestCase):
def setUp(self):
self._adder = linear_operator_addition._AddAndReturnScaledIdentity()
+ @test_util.run_deprecated_v1
def test_identity_plus_identity(self):
id1 = linalg.LinearOperatorIdentity(num_rows=2)
id2 = linalg.LinearOperatorIdentity(num_rows=2, batch_shape=[3])
@@ -279,6 +286,7 @@ class AddAndReturnScaledIdentityTest(test.TestCase):
self.assertTrue(operator.is_non_singular)
self.assertEqual("my_operator", operator.name)
+ @test_util.run_deprecated_v1
def test_identity_plus_scaled_identity(self):
id1 = linalg.LinearOperatorIdentity(num_rows=2, batch_shape=[3])
id2 = linalg.LinearOperatorScaledIdentity(num_rows=2, multiplier=2.2)
@@ -297,6 +305,7 @@ class AddAndReturnScaledIdentityTest(test.TestCase):
self.assertTrue(operator.is_non_singular)
self.assertEqual("my_operator", operator.name)
+ @test_util.run_deprecated_v1
def test_scaled_identity_plus_scaled_identity(self):
id1 = linalg.LinearOperatorScaledIdentity(
num_rows=2, multiplier=[2.2, 2.2, 2.2])
@@ -322,6 +331,7 @@ class AddAndReturnDiagTest(test.TestCase):
def setUp(self):
self._adder = linear_operator_addition._AddAndReturnDiag()
+ @test_util.run_deprecated_v1
def test_identity_plus_identity_returns_diag(self):
id1 = linalg.LinearOperatorIdentity(num_rows=2)
id2 = linalg.LinearOperatorIdentity(num_rows=2, batch_shape=[3])
@@ -340,6 +350,7 @@ class AddAndReturnDiagTest(test.TestCase):
self.assertTrue(operator.is_non_singular)
self.assertEqual("my_operator", operator.name)
+ @test_util.run_deprecated_v1
def test_diag_plus_diag(self):
diag1 = rng.rand(2, 3, 4)
diag2 = rng.rand(4)
@@ -366,6 +377,7 @@ class AddAndReturnTriLTest(test.TestCase):
def setUp(self):
self._adder = linear_operator_addition._AddAndReturnTriL()
+ @test_util.run_deprecated_v1
def test_diag_plus_tril(self):
diag = linalg.LinearOperatorDiag([1., 2.])
tril = linalg.LinearOperatorLowerTriangular([[10., 0.], [30., 0.]])
@@ -389,6 +401,7 @@ class AddAndReturnMatrixTest(test.TestCase):
def setUp(self):
self._adder = linear_operator_addition._AddAndReturnMatrix()
+ @test_util.run_deprecated_v1
def test_diag_plus_diag(self):
diag1 = linalg.LinearOperatorDiag([1., 2.])
diag2 = linalg.LinearOperatorDiag([-1., 3.])
diff --git a/tensorflow/python/kernel_tests/linalg/linear_operator_circulant_test.py b/tensorflow/python/kernel_tests/linalg/linear_operator_circulant_test.py
index 09867435a73..6366083ac5b 100644
--- a/tensorflow/python/kernel_tests/linalg/linear_operator_circulant_test.py
+++ b/tensorflow/python/kernel_tests/linalg/linear_operator_circulant_test.py
@@ -21,6 +21,7 @@ import contextlib
import numpy as np
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import spectral_ops_test_util
@@ -129,6 +130,7 @@ class LinearOperatorCirculantTestSelfAdjointOperator(
return operator, mat
+ @test_util.run_deprecated_v1
def test_simple_hermitian_spectrum_gives_operator_with_zero_imag_part(self):
with self.cached_session():
spectrum = math_ops.cast([1., 1j, -1j], dtypes.complex64)
@@ -196,6 +198,7 @@ class LinearOperatorCirculantTestHermitianSpectrum(
return operator, mat
+ @test_util.run_deprecated_v1
def test_simple_hermitian_spectrum_gives_operator_with_zero_imag_part(self):
with self.cached_session():
spectrum = math_ops.cast([1., 1j, -1j], dtypes.complex64)
@@ -251,6 +254,7 @@ class LinearOperatorCirculantTestNonHermitianSpectrum(
return operator, mat
+ @test_util.run_deprecated_v1
def test_simple_hermitian_spectrum_gives_operator_with_zero_imag_part(self):
with self.cached_session():
spectrum = math_ops.cast([1., 1j, -1j], dtypes.complex64)
@@ -262,6 +266,7 @@ class LinearOperatorCirculantTestNonHermitianSpectrum(
np.testing.assert_allclose(
0, self.evaluate(imag_matrix), rtol=0, atol=eps * 3)
+ @test_util.run_deprecated_v1
def test_simple_positive_real_spectrum_gives_self_adjoint_pos_def_oper(self):
with self.cached_session() as sess:
spectrum = math_ops.cast([6., 4, 2], dtypes.complex64)
@@ -274,6 +279,7 @@ class LinearOperatorCirculantTestNonHermitianSpectrum(
operator.assert_positive_definite().run() # Should not fail
operator.assert_self_adjoint().run() # Should not fail
+ @test_util.run_deprecated_v1
def test_defining_operator_using_real_convolution_kernel(self):
with self.cached_session():
convolution_kernel = [1., 2., 1.]
@@ -304,6 +310,7 @@ class LinearOperatorCirculantTestNonHermitianSpectrum(
np.testing.assert_allclose(
0, self.evaluate(imag_matrix), rtol=0, atol=eps * 3 * 4)
+ @test_util.run_deprecated_v1
def test_convolution_kernel_same_as_first_row_of_to_dense(self):
spectrum = [[3., 2., 1.], [2., 1.5, 1.]]
with self.cached_session():
@@ -315,6 +322,7 @@ class LinearOperatorCirculantTestNonHermitianSpectrum(
self.assertAllEqual((2, 3, 3), c.get_shape())
self.assertAllClose(h.eval(), self.evaluate(c)[:, :, 0])
+ @test_util.run_deprecated_v1
def test_assert_non_singular_fails_for_singular_operator(self):
spectrum = math_ops.cast([0, 4, 2j + 2], dtypes.complex64)
operator = linalg.LinearOperatorCirculant(spectrum)
@@ -322,12 +330,14 @@ class LinearOperatorCirculantTestNonHermitianSpectrum(
with self.assertRaisesOpError("Singular operator"):
operator.assert_non_singular().run()
+ @test_util.run_deprecated_v1
def test_assert_non_singular_does_not_fail_for_non_singular_operator(self):
spectrum = math_ops.cast([-3j, 4, 2j + 2], dtypes.complex64)
operator = linalg.LinearOperatorCirculant(spectrum)
with self.cached_session():
operator.assert_non_singular().run() # Should not fail
+ @test_util.run_deprecated_v1
def test_assert_positive_definite_fails_for_non_positive_definite(self):
spectrum = math_ops.cast([6., 4, 2j], dtypes.complex64)
operator = linalg.LinearOperatorCirculant(spectrum)
@@ -335,6 +345,7 @@ class LinearOperatorCirculantTestNonHermitianSpectrum(
with self.assertRaisesOpError("Not positive definite"):
operator.assert_positive_definite().run()
+ @test_util.run_deprecated_v1
def test_assert_positive_definite_does_not_fail_when_pos_def(self):
spectrum = math_ops.cast([6., 4, 2j + 2], dtypes.complex64)
operator = linalg.LinearOperatorCirculant(spectrum)
@@ -529,6 +540,7 @@ class LinearOperatorCirculant2DTestNonHermitianSpectrum(
return operator, mat
+ @test_util.run_deprecated_v1
def test_real_hermitian_spectrum_gives_real_symmetric_operator(self):
with self.cached_session() as sess:
# This is a real and hermitian spectrum.
@@ -546,6 +558,7 @@ class LinearOperatorCirculant2DTestNonHermitianSpectrum(
np.testing.assert_allclose(0, imag_matrix, atol=1e-6)
self.assertAllClose(matrix, matrix_transpose, atol=0)
+ @test_util.run_deprecated_v1
def test_real_spectrum_gives_self_adjoint_operator(self):
with self.cached_session() as sess:
# This is a real and hermitian spectrum.
@@ -560,6 +573,7 @@ class LinearOperatorCirculant2DTestNonHermitianSpectrum(
matrix, matrix_h = self.evaluate([matrix_tensor, matrix_h])
self.assertAllClose(matrix, matrix_h, atol=0)
+ @test_util.run_deprecated_v1
def test_assert_non_singular_fails_for_singular_operator(self):
spectrum = math_ops.cast([[0, 4], [2j + 2, 3.]], dtypes.complex64)
operator = linalg.LinearOperatorCirculant2D(spectrum)
@@ -567,12 +581,14 @@ class LinearOperatorCirculant2DTestNonHermitianSpectrum(
with self.assertRaisesOpError("Singular operator"):
operator.assert_non_singular().run()
+ @test_util.run_deprecated_v1
def test_assert_non_singular_does_not_fail_for_non_singular_operator(self):
spectrum = math_ops.cast([[-3j, 4], [2j + 2, 3.]], dtypes.complex64)
operator = linalg.LinearOperatorCirculant2D(spectrum)
with self.cached_session():
operator.assert_non_singular().run() # Should not fail
+ @test_util.run_deprecated_v1
def test_assert_positive_definite_fails_for_non_positive_definite(self):
spectrum = math_ops.cast([[6., 4], [2j, 3.]], dtypes.complex64)
operator = linalg.LinearOperatorCirculant2D(spectrum)
@@ -580,6 +596,7 @@ class LinearOperatorCirculant2DTestNonHermitianSpectrum(
with self.assertRaisesOpError("Not positive definite"):
operator.assert_positive_definite().run()
+ @test_util.run_deprecated_v1
def test_assert_positive_definite_does_not_fail_when_pos_def(self):
spectrum = math_ops.cast([[6., 4], [2j + 2, 3.]], dtypes.complex64)
operator = linalg.LinearOperatorCirculant2D(spectrum)
@@ -618,6 +635,7 @@ class LinearOperatorCirculant3DTest(test.TestCase):
with spectral_ops_test_util.fft_kernel_label_map():
yield sess
+ @test_util.run_deprecated_v1
def test_real_spectrum_gives_self_adjoint_operator(self):
with self.cached_session() as sess:
# This is a real and hermitian spectrum.
@@ -635,6 +653,7 @@ class LinearOperatorCirculant3DTest(test.TestCase):
self.assertAllEqual((2, 2 * 3 * 5, 2 * 3 * 5), matrix.shape)
self.assertAllClose(matrix, matrix_h)
+ @test_util.run_deprecated_v1
def test_defining_operator_using_real_convolution_kernel(self):
with self.cached_session():
convolution_kernel = linear_operator_test_util.random_normal(
@@ -653,6 +672,7 @@ class LinearOperatorCirculant3DTest(test.TestCase):
self.assertAllEqual((2, 2 * 3 * 5, 2 * 3 * 5), matrix.shape)
np.testing.assert_allclose(0, np.imag(matrix), atol=1e-6)
+ @test_util.run_deprecated_v1
def test_defining_spd_operator_by_taking_real_part(self):
with self.cached_session() as sess:
# S is real and positive.
diff --git a/tensorflow/python/kernel_tests/linalg/linear_operator_composition_test.py b/tensorflow/python/kernel_tests/linalg/linear_operator_composition_test.py
index 3f19dc4bffe..214b73aa2f3 100644
--- a/tensorflow/python/kernel_tests/linalg/linear_operator_composition_test.py
+++ b/tensorflow/python/kernel_tests/linalg/linear_operator_composition_test.py
@@ -21,6 +21,7 @@ import numpy as np
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.ops.linalg import linalg as linalg_lib
@@ -179,6 +180,7 @@ class NonSquareLinearOperatorCompositionTest(
return operator, mat
+ @test_util.run_deprecated_v1
def test_static_shapes(self):
operators = [
linalg.LinearOperatorFullMatrix(rng.rand(2, 3, 4)),
@@ -187,6 +189,7 @@ class NonSquareLinearOperatorCompositionTest(
operator = linalg.LinearOperatorComposition(operators)
self.assertAllEqual((2, 3, 5), operator.shape)
+ @test_util.run_deprecated_v1
def test_shape_tensors_when_statically_available(self):
operators = [
linalg.LinearOperatorFullMatrix(rng.rand(2, 3, 4)),
@@ -196,6 +199,7 @@ class NonSquareLinearOperatorCompositionTest(
with self.cached_session():
self.assertAllEqual((2, 3, 5), operator.shape_tensor().eval())
+ @test_util.run_deprecated_v1
def test_shape_tensors_when_only_dynamically_available(self):
mat_1 = rng.rand(1, 2, 3, 4)
mat_2 = rng.rand(1, 2, 4, 5)
diff --git a/tensorflow/python/kernel_tests/linalg/linear_operator_diag_test.py b/tensorflow/python/kernel_tests/linalg/linear_operator_diag_test.py
index 80889a162f8..dcbc0dd7c97 100644
--- a/tensorflow/python/kernel_tests/linalg/linear_operator_diag_test.py
+++ b/tensorflow/python/kernel_tests/linalg/linear_operator_diag_test.py
@@ -17,6 +17,7 @@ from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import linalg_ops
from tensorflow.python.ops import math_ops
@@ -80,6 +81,7 @@ class LinearOperatorDiagTest(
with self.assertRaisesOpError("non-positive real.*not positive definite"):
operator.assert_positive_definite().run()
+ @test_util.run_deprecated_v1
def test_assert_positive_definite_does_not_raise_if_pd_and_complex(self):
with self.cached_session():
x = [1., 2.]
@@ -96,6 +98,7 @@ class LinearOperatorDiagTest(
with self.assertRaisesOpError("Singular operator"):
operator.assert_non_singular().run()
+ @test_util.run_deprecated_v1
def test_assert_non_singular_does_not_raise_for_complex_nonsingular(self):
with self.cached_session():
x = [1., 0.]
@@ -113,6 +116,7 @@ class LinearOperatorDiagTest(
with self.assertRaisesOpError("imaginary.*not self-adjoint"):
operator.assert_self_adjoint().run()
+ @test_util.run_deprecated_v1
def test_assert_self_adjoint_does_not_raise_for_diag_with_zero_imag(self):
with self.cached_session():
x = [1., 0.]
diff --git a/tensorflow/python/kernel_tests/linalg/linear_operator_full_matrix_test.py b/tensorflow/python/kernel_tests/linalg/linear_operator_full_matrix_test.py
index 36575ceec36..aff0b1ae14c 100644
--- a/tensorflow/python/kernel_tests/linalg/linear_operator_full_matrix_test.py
+++ b/tensorflow/python/kernel_tests/linalg/linear_operator_full_matrix_test.py
@@ -20,6 +20,7 @@ from __future__ import print_function
import numpy as np
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.ops.linalg import linalg as linalg_lib
@@ -69,6 +70,7 @@ class SquareLinearOperatorFullMatrixTest(
# Auto-detected.
self.assertTrue(operator.is_square)
+ @test_util.run_deprecated_v1
def test_assert_non_singular_raises_if_cond_too_big_but_finite(self):
with self.cached_session():
tril = linear_operator_test_util.random_tril_matrix(
diff --git a/tensorflow/python/kernel_tests/linalg/linear_operator_identity_test.py b/tensorflow/python/kernel_tests/linalg/linear_operator_identity_test.py
index e9fd91c6cf0..2da5e712d77 100644
--- a/tensorflow/python/kernel_tests/linalg/linear_operator_identity_test.py
+++ b/tensorflow/python/kernel_tests/linalg/linear_operator_identity_test.py
@@ -20,6 +20,7 @@ from __future__ import print_function
import numpy as np
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import linalg_ops
from tensorflow.python.ops import math_ops
@@ -60,16 +61,19 @@ class LinearOperatorIdentityTest(
return operator, mat
+ @test_util.run_deprecated_v1
def test_assert_positive_definite(self):
with self.cached_session():
operator = linalg_lib.LinearOperatorIdentity(num_rows=2)
operator.assert_positive_definite().run() # Should not fail
+ @test_util.run_deprecated_v1
def test_assert_non_singular(self):
with self.cached_session():
operator = linalg_lib.LinearOperatorIdentity(num_rows=2)
operator.assert_non_singular().run() # Should not fail
+ @test_util.run_deprecated_v1
def test_assert_self_adjoint(self):
with self.cached_session():
operator = linalg_lib.LinearOperatorIdentity(num_rows=2)
@@ -109,6 +113,7 @@ class LinearOperatorIdentityTest(
with self.assertRaisesRegexp(ValueError, "must be non-negative"):
linalg_lib.LinearOperatorIdentity(num_rows=2, batch_shape=[-2])
+ @test_util.run_deprecated_v1
def test_non_scalar_num_rows_raises_dynamic(self):
with self.cached_session():
num_rows = array_ops.placeholder(dtypes.int32)
@@ -117,6 +122,7 @@ class LinearOperatorIdentityTest(
with self.assertRaisesOpError("must be a 0-D Tensor"):
operator.to_dense().eval(feed_dict={num_rows: [2]})
+ @test_util.run_deprecated_v1
def test_negative_num_rows_raises_dynamic(self):
with self.cached_session():
num_rows = array_ops.placeholder(dtypes.int32)
@@ -125,6 +131,7 @@ class LinearOperatorIdentityTest(
with self.assertRaisesOpError("must be non-negative"):
operator.to_dense().eval(feed_dict={num_rows: -2})
+ @test_util.run_deprecated_v1
def test_non_1d_batch_shape_raises_dynamic(self):
with self.cached_session():
batch_shape = array_ops.placeholder(dtypes.int32)
@@ -133,6 +140,7 @@ class LinearOperatorIdentityTest(
with self.assertRaisesOpError("must be a 1-D"):
operator.to_dense().eval(feed_dict={batch_shape: 2})
+ @test_util.run_deprecated_v1
def test_negative_batch_shape_raises_dynamic(self):
with self.cached_session():
batch_shape = array_ops.placeholder(dtypes.int32)
@@ -147,6 +155,7 @@ class LinearOperatorIdentityTest(
with self.assertRaisesRegexp(ValueError, "Dimensions.*not compatible"):
operator.matmul(x)
+ @test_util.run_deprecated_v1
def test_wrong_matrix_dimensions_raises_dynamic(self):
num_rows = array_ops.placeholder(dtypes.int32)
x = array_ops.placeholder(dtypes.float32)
@@ -172,6 +181,7 @@ class LinearOperatorIdentityTest(
self.assertAllEqual(operator_matmul.get_shape(), expected.get_shape())
self.assertAllClose(*self.evaluate([operator_matmul, expected]))
+ @test_util.run_deprecated_v1
def test_default_batch_shape_broadcasts_with_everything_dynamic(self):
# These cannot be done in the automated (base test class) tests since they
# test shapes that tf.batch_matmul cannot handle.
@@ -209,6 +219,7 @@ class LinearOperatorIdentityTest(
self.assertAllEqual(operator_matmul.get_shape(), expected.get_shape())
self.assertAllClose(*self.evaluate([operator_matmul, expected]))
+ @test_util.run_deprecated_v1
def test_broadcast_matmul_dynamic_shapes(self):
# These cannot be done in the automated (base test class) tests since they
# test shapes that tf.batch_matmul cannot handle.
@@ -309,6 +320,7 @@ class LinearOperatorScaledIdentityTest(
return operator, matrix
+ @test_util.run_deprecated_v1
def test_assert_positive_definite_does_not_raise_when_positive(self):
with self.cached_session():
operator = linalg_lib.LinearOperatorScaledIdentity(
@@ -322,6 +334,7 @@ class LinearOperatorScaledIdentityTest(
with self.assertRaisesOpError("not positive definite"):
operator.assert_positive_definite().run()
+ @test_util.run_deprecated_v1
def test_assert_non_singular_does_not_raise_when_non_singular(self):
with self.cached_session():
operator = linalg_lib.LinearOperatorScaledIdentity(
@@ -335,6 +348,7 @@ class LinearOperatorScaledIdentityTest(
with self.assertRaisesOpError("was singular"):
operator.assert_non_singular().run()
+ @test_util.run_deprecated_v1
def test_assert_self_adjoint_does_not_raise_when_self_adjoint(self):
with self.cached_session():
operator = linalg_lib.LinearOperatorScaledIdentity(
@@ -372,6 +386,7 @@ class LinearOperatorScaledIdentityTest(
with self.assertRaisesRegexp(ValueError, "Dimensions.*not compatible"):
operator.matmul(x)
+ @test_util.run_deprecated_v1
def test_wrong_matrix_dimensions_raises_dynamic(self):
num_rows = array_ops.placeholder(dtypes.int32)
x = array_ops.placeholder(dtypes.float32)
diff --git a/tensorflow/python/kernel_tests/linalg/linear_operator_kronecker_test.py b/tensorflow/python/kernel_tests/linalg/linear_operator_kronecker_test.py
index 2b1ae6e1f5a..513b2468032 100644
--- a/tensorflow/python/kernel_tests/linalg/linear_operator_kronecker_test.py
+++ b/tensorflow/python/kernel_tests/linalg/linear_operator_kronecker_test.py
@@ -21,6 +21,7 @@ import numpy as np
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops.linalg import linalg as linalg_lib
from tensorflow.python.ops.linalg import linear_operator_kronecker as kronecker
@@ -53,6 +54,7 @@ def _kronecker_dense(factors):
class KroneckerDenseTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testKroneckerDenseMatrix(self):
x = ops.convert_to_tensor([[2., 3.], [1., 2.]], dtype=dtypes.float32)
y = ops.convert_to_tensor([[1., 2.], [5., -1.]], dtype=dtypes.float32)
diff --git a/tensorflow/python/kernel_tests/linalg/linear_operator_test.py b/tensorflow/python/kernel_tests/linalg/linear_operator_test.py
index 2f67df408cb..8f8b15e8ed8 100644
--- a/tensorflow/python/kernel_tests/linalg/linear_operator_test.py
+++ b/tensorflow/python/kernel_tests/linalg/linear_operator_test.py
@@ -22,6 +22,7 @@ from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
from tensorflow.python.framework import tensor_shape
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import linalg_ops
from tensorflow.python.ops import math_ops
@@ -107,6 +108,7 @@ class LinearOperatorTest(test.TestCase):
self.assertAllEqual(4, operator.domain_dimension)
self.assertAllEqual(3, operator.range_dimension)
+ @test_util.run_deprecated_v1
def test_all_shape_methods_defined_by_the_one_method_shape(self):
with self.cached_session():
shape = (1, 2, 3, 4)
@@ -136,6 +138,7 @@ class LinearOperatorTest(test.TestCase):
self.assertAllEqual((2, 3, 4), operator_dense.get_shape())
self.assertAllClose(matrix, self.evaluate(operator_dense))
+ @test_util.run_deprecated_v1
def test_generic_to_dense_method_non_square_matrix_tensor(self):
matrix = rng.randn(2, 3, 4)
matrix_ph = array_ops.placeholder(dtypes.float64)
@@ -175,6 +178,7 @@ class LinearOperatorTest(test.TestCase):
with self.assertRaisesRegexp(ValueError, "but.*was square"):
_ = LinearOperatorShape(shape=(2, 4, 4), is_square=False).is_square
+ @test_util.run_deprecated_v1
def test_is_square_set_inconsistent_with_other_hints_raises(self):
with self.assertRaisesRegexp(ValueError, "is always square"):
matrix = array_ops.placeholder(dtypes.float32)
@@ -185,6 +189,7 @@ class LinearOperatorTest(test.TestCase):
LinearOperatorMatmulSolve(
matrix, is_positive_definite=True, is_square=False)
+ @test_util.run_deprecated_v1
def test_non_square_operators_raise_on_determinant_and_solve(self):
operator = LinearOperatorShape((2, 3))
with self.assertRaisesRegexp(NotImplementedError, "not be square"):
@@ -199,6 +204,7 @@ class LinearOperatorTest(test.TestCase):
LinearOperatorMatmulSolve(
matrix, is_positive_definite=True, is_square=False)
+ @test_util.run_deprecated_v1
def test_is_square_manual_set_works(self):
matrix = array_ops.placeholder(dtypes.float32)
# Default is None.
@@ -208,6 +214,7 @@ class LinearOperatorTest(test.TestCase):
operator = LinearOperatorMatmulSolve(matrix, is_square=True)
self.assertTrue(operator.is_square)
+ @test_util.run_deprecated_v1
def test_linear_operator_matmul_hints_closed(self):
matrix = array_ops.placeholder(dtypes.float32)
operator1 = LinearOperatorMatmulSolve(matrix)
@@ -234,6 +241,7 @@ class LinearOperatorTest(test.TestCase):
self.assertTrue(operator_matmul.is_self_adjoint)
self.assertEqual(None, operator_matmul.is_positive_definite)
+ @test_util.run_deprecated_v1
def test_linear_operator_matmul_hints_false(self):
matrix = array_ops.placeholder(dtypes.float32)
operator1 = LinearOperatorMatmulSolve(
@@ -266,6 +274,7 @@ class LinearOperatorTest(test.TestCase):
self.assertEqual(None, operator_matmul.is_self_adjoint)
self.assertEqual(None, operator_matmul.is_positive_definite)
+ @test_util.run_deprecated_v1
def test_linear_operator_matmul_hint_infer_square(self):
matrix1 = array_ops.placeholder(shape=[2, 3], dtype=dtypes.float32)
matrix2 = array_ops.placeholder(shape=[3, 2], dtype=dtypes.float32)
diff --git a/tensorflow/python/kernel_tests/linalg/linear_operator_util_test.py b/tensorflow/python/kernel_tests/linalg/linear_operator_util_test.py
index f12714677e2..d1e6c37e35a 100644
--- a/tensorflow/python/kernel_tests/linalg/linear_operator_util_test.py
+++ b/tensorflow/python/kernel_tests/linalg/linear_operator_util_test.py
@@ -21,6 +21,7 @@ import numpy as np
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import linalg_ops
from tensorflow.python.ops import math_ops
@@ -32,12 +33,14 @@ rng = np.random.RandomState(0)
class AssertZeroImagPartTest(test.TestCase):
+ @test_util.run_deprecated_v1
def test_real_tensor_doesnt_raise(self):
x = ops.convert_to_tensor([0., 2, 3])
with self.cached_session():
# Should not raise.
linear_operator_util.assert_zero_imag_part(x, message="ABC123").run()
+ @test_util.run_deprecated_v1
def test_complex_tensor_with_imag_zero_doesnt_raise(self):
x = ops.convert_to_tensor([1., 0, 3])
y = ops.convert_to_tensor([0., 0, 0])
@@ -57,6 +60,7 @@ class AssertZeroImagPartTest(test.TestCase):
class AssertNoEntriesWithModulusZeroTest(test.TestCase):
+ @test_util.run_deprecated_v1
def test_nonzero_real_tensor_doesnt_raise(self):
x = ops.convert_to_tensor([1., 2, 3])
with self.cached_session():
@@ -64,6 +68,7 @@ class AssertNoEntriesWithModulusZeroTest(test.TestCase):
linear_operator_util.assert_no_entries_with_modulus_zero(
x, message="ABC123").run()
+ @test_util.run_deprecated_v1
def test_nonzero_complex_tensor_doesnt_raise(self):
x = ops.convert_to_tensor([1., 0, 3])
y = ops.convert_to_tensor([1., 2, 0])
@@ -104,6 +109,7 @@ class BroadcastMatrixBatchDimsTest(test.TestCase):
with self.cached_session():
self.assertAllClose(arr, self.evaluate(tensor))
+ @test_util.run_deprecated_v1
def test_static_dims_broadcast(self):
# x.batch_shape = [3, 1, 2]
# y.batch_shape = [4, 1]
@@ -142,6 +148,7 @@ class BroadcastMatrixBatchDimsTest(test.TestCase):
self.assertAllClose(x_bc_expected, x_bc_)
self.assertAllClose(y_bc_expected, y_bc_)
+ @test_util.run_deprecated_v1
def test_dynamic_dims_broadcast_32bit(self):
# x.batch_shape = [3, 1, 2]
# y.batch_shape = [4, 1]
@@ -162,6 +169,7 @@ class BroadcastMatrixBatchDimsTest(test.TestCase):
self.assertAllClose(x_bc_expected, x_bc_)
self.assertAllClose(y_bc_expected, y_bc_)
+ @test_util.run_deprecated_v1
def test_dynamic_dims_broadcast_32bit_second_arg_higher_rank(self):
# x.batch_shape = [1, 2]
# y.batch_shape = [3, 4, 1]
@@ -195,6 +203,7 @@ class BroadcastMatrixBatchDimsTest(test.TestCase):
class CholeskySolveWithBroadcastTest(test.TestCase):
+ @test_util.run_deprecated_v1
def test_static_dims_broadcast(self):
# batch_shape = [2]
chol = rng.rand(3, 3)
@@ -207,6 +216,7 @@ class CholeskySolveWithBroadcastTest(test.TestCase):
expected = linalg_ops.cholesky_solve(chol_broadcast, rhs)
self.assertAllClose(expected.eval(), self.evaluate(result))
+ @test_util.run_deprecated_v1
def test_dynamic_dims_broadcast_64bit(self):
# batch_shape = [2, 2]
chol = rng.rand(2, 3, 3)
@@ -233,6 +243,7 @@ class CholeskySolveWithBroadcastTest(test.TestCase):
class MatmulWithBroadcastTest(test.TestCase):
+ @test_util.run_deprecated_v1
def test_static_dims_broadcast_x_has_extra_dims(self):
# batch_shape = [2]
# for each batch member, we have a 1x3 matrix times a 3x7 matrix ==> 1x7
@@ -246,6 +257,7 @@ class MatmulWithBroadcastTest(test.TestCase):
expected = math_ops.matmul(x, y_broadcast)
self.assertAllClose(expected.eval(), self.evaluate(result))
+ @test_util.run_deprecated_v1
def test_static_dims_broadcast_y_has_extra_dims(self):
# Since the second arg has extra dims, and the domain dim of the first arg
# is larger than the number of linear equations, code will "flip" the extra
@@ -263,6 +275,7 @@ class MatmulWithBroadcastTest(test.TestCase):
expected = math_ops.matmul(x_broadcast, y)
self.assertAllClose(expected.eval(), self.evaluate(result))
+ @test_util.run_deprecated_v1
def test_static_dims_broadcast_y_has_extra_dims_transpose_a_and_b(self):
# Since the second arg has extra dims, and the domain dim of the first arg
# is larger than the number of linear equations, code will "flip" the extra
@@ -282,6 +295,7 @@ class MatmulWithBroadcastTest(test.TestCase):
x_broadcast, y, transpose_a=True, transpose_b=True)
self.assertAllClose(expected.eval(), self.evaluate(result))
+ @test_util.run_deprecated_v1
def test_static_dims_broadcast_y_has_extra_dims_transpose_dynamic(self):
# Since the second arg has extra dims, and the domain dim of the first arg
# is larger than the number of linear equations, code will "flip" the extra
@@ -308,6 +322,7 @@ class MatmulWithBroadcastTest(test.TestCase):
y_ph: y
}))
+ @test_util.run_deprecated_v1
def test_dynamic_dims_broadcast_64bit(self):
# batch_shape = [2]
# for each batch member, we have a 1x3 matrix times a 3x7 matrix ==> 1x7
@@ -333,6 +348,7 @@ class MatmulWithBroadcastTest(test.TestCase):
class MatrixSolveWithBroadcastTest(test.TestCase):
+ @test_util.run_deprecated_v1
def test_static_dims_broadcast_matrix_has_extra_dims(self):
# batch_shape = [2]
matrix = rng.rand(2, 3, 3)
@@ -346,6 +362,7 @@ class MatrixSolveWithBroadcastTest(test.TestCase):
expected = linalg_ops.matrix_solve(matrix, rhs_broadcast)
self.assertAllClose(expected.eval(), self.evaluate(result))
+ @test_util.run_deprecated_v1
def test_static_dims_broadcast_rhs_has_extra_dims(self):
# Since the second arg has extra dims, and the domain dim of the first arg
# is larger than the number of linear equations, code will "flip" the extra
@@ -364,6 +381,7 @@ class MatrixSolveWithBroadcastTest(test.TestCase):
expected = linalg_ops.matrix_solve(matrix_broadcast, rhs)
self.assertAllClose(expected.eval(), self.evaluate(result))
+ @test_util.run_deprecated_v1
def test_static_dims_broadcast_rhs_has_extra_dims_dynamic(self):
# Since the second arg has extra dims, and the domain dim of the first arg
# is larger than the number of linear equations, code will "flip" the extra
@@ -391,6 +409,7 @@ class MatrixSolveWithBroadcastTest(test.TestCase):
rhs_ph: rhs
}))
+ @test_util.run_deprecated_v1
def test_static_dims_broadcast_rhs_has_extra_dims_and_adjoint(self):
# Since the second arg has extra dims, and the domain dim of the first arg
# is larger than the number of linear equations, code will "flip" the extra
@@ -410,6 +429,7 @@ class MatrixSolveWithBroadcastTest(test.TestCase):
expected = linalg_ops.matrix_solve(matrix_broadcast, rhs, adjoint=True)
self.assertAllClose(expected.eval(), self.evaluate(result))
+ @test_util.run_deprecated_v1
def test_dynamic_dims_broadcast_64bit(self):
# batch_shape = [2, 2]
matrix = rng.rand(2, 3, 3)
@@ -436,6 +456,7 @@ class MatrixSolveWithBroadcastTest(test.TestCase):
class MatrixTriangularSolveWithBroadcastTest(test.TestCase):
+ @test_util.run_deprecated_v1
def test_static_dims_broadcast_matrix_has_extra_dims(self):
# batch_shape = [2]
matrix = rng.rand(2, 3, 3)
@@ -449,6 +470,7 @@ class MatrixTriangularSolveWithBroadcastTest(test.TestCase):
expected = linalg_ops.matrix_triangular_solve(matrix, rhs_broadcast)
self.assertAllClose(expected.eval(), self.evaluate(result))
+ @test_util.run_deprecated_v1
def test_static_dims_broadcast_rhs_has_extra_dims(self):
# Since the second arg has extra dims, and the domain dim of the first arg
# is larger than the number of linear equations, code will "flip" the extra
@@ -468,6 +490,7 @@ class MatrixTriangularSolveWithBroadcastTest(test.TestCase):
expected = linalg_ops.matrix_triangular_solve(matrix_broadcast, rhs)
self.assertAllClose(expected.eval(), self.evaluate(result))
+ @test_util.run_deprecated_v1
def test_static_dims_broadcast_rhs_has_extra_dims_and_adjoint(self):
# Since the second arg has extra dims, and the domain dim of the first arg
# is larger than the number of linear equations, code will "flip" the extra
@@ -488,6 +511,7 @@ class MatrixTriangularSolveWithBroadcastTest(test.TestCase):
matrix_broadcast, rhs, adjoint=True)
self.assertAllClose(expected.eval(), self.evaluate(result))
+ @test_util.run_deprecated_v1
def test_dynamic_dims_broadcast_64bit(self):
# batch_shape = [2]
matrix = rng.rand(2, 3, 3)
@@ -522,6 +546,7 @@ class DomainDimensionStubOperator(object):
class AssertCompatibleMatrixDimensionsTest(test.TestCase):
+ @test_util.run_deprecated_v1
def test_compatible_dimensions_do_not_raise(self):
with self.cached_session():
x = ops.convert_to_tensor(rng.rand(2, 3, 4))
diff --git a/tensorflow/python/kernel_tests/linalg/linear_operator_zeros_test.py b/tensorflow/python/kernel_tests/linalg/linear_operator_zeros_test.py
index e875579a7af..eb0b8ef1277 100644
--- a/tensorflow/python/kernel_tests/linalg/linear_operator_zeros_test.py
+++ b/tensorflow/python/kernel_tests/linalg/linear_operator_zeros_test.py
@@ -20,6 +20,7 @@ from __future__ import print_function
import numpy as np
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops.linalg import linalg as linalg_lib
from tensorflow.python.ops.linalg import linear_operator_test_util
@@ -73,6 +74,7 @@ class LinearOperatorZerosTest(
operator = linalg_lib.LinearOperatorZeros(num_rows=2)
operator.assert_non_singular()
+ @test_util.run_deprecated_v1
def test_assert_self_adjoint(self):
with self.cached_session():
operator = linalg_lib.LinearOperatorZeros(num_rows=2)
@@ -108,6 +110,7 @@ class LinearOperatorZerosTest(
with self.assertRaisesRegexp(ValueError, "must be non-negative"):
linalg_lib.LinearOperatorZeros(num_rows=2, batch_shape=[-2])
+ @test_util.run_deprecated_v1
def test_non_scalar_num_rows_raises_dynamic(self):
with self.cached_session():
num_rows = array_ops.placeholder(dtypes.int32)
@@ -116,6 +119,7 @@ class LinearOperatorZerosTest(
with self.assertRaisesOpError("must be a 0-D Tensor"):
operator.to_dense().eval(feed_dict={num_rows: [2]})
+ @test_util.run_deprecated_v1
def test_negative_num_rows_raises_dynamic(self):
with self.cached_session():
n = array_ops.placeholder(dtypes.int32)
@@ -129,6 +133,7 @@ class LinearOperatorZerosTest(
with self.assertRaisesOpError("must be non-negative"):
operator.to_dense().eval(feed_dict={n: -2})
+ @test_util.run_deprecated_v1
def test_non_1d_batch_shape_raises_dynamic(self):
with self.cached_session():
batch_shape = array_ops.placeholder(dtypes.int32)
@@ -137,6 +142,7 @@ class LinearOperatorZerosTest(
with self.assertRaisesOpError("must be a 1-D"):
operator.to_dense().eval(feed_dict={batch_shape: 2})
+ @test_util.run_deprecated_v1
def test_negative_batch_shape_raises_dynamic(self):
with self.cached_session():
batch_shape = array_ops.placeholder(dtypes.int32)
@@ -151,6 +157,7 @@ class LinearOperatorZerosTest(
with self.assertRaisesRegexp(ValueError, "Dimensions.*not compatible"):
operator.matmul(x)
+ @test_util.run_deprecated_v1
def test_wrong_matrix_dimensions_raises_dynamic(self):
num_rows = array_ops.placeholder(dtypes.int32)
x = array_ops.placeholder(dtypes.float32)
diff --git a/tensorflow/python/kernel_tests/linalg_grad_test.py b/tensorflow/python/kernel_tests/linalg_grad_test.py
index 709ecbfc35f..28e1d7e1684 100644
--- a/tensorflow/python/kernel_tests/linalg_grad_test.py
+++ b/tensorflow/python/kernel_tests/linalg_grad_test.py
@@ -21,6 +21,7 @@ from __future__ import print_function
import numpy as np
from tensorflow.python.framework import constant_op
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import gradients_impl
@@ -39,6 +40,7 @@ def _AddTest(test, op_name, testcase_name, fn):
class ShapeTest(test_lib.TestCase):
+ @test_util.run_deprecated_v1
def testBatchGradientUnknownSize(self):
with self.cached_session():
batch_size = constant_op.constant(3)
diff --git a/tensorflow/python/kernel_tests/linalg_ops_test.py b/tensorflow/python/kernel_tests/linalg_ops_test.py
index b5eeee09980..028167a7860 100644
--- a/tensorflow/python/kernel_tests/linalg_ops_test.py
+++ b/tensorflow/python/kernel_tests/linalg_ops_test.py
@@ -25,6 +25,7 @@ import numpy as np
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import linalg_ops
from tensorflow.python.ops import math_ops
@@ -52,6 +53,7 @@ class CholeskySolveTest(test.TestCase):
def setUp(self):
self.rng = np.random.RandomState(0)
+ @test_util.run_deprecated_v1
def test_works_with_five_different_random_pos_def_matrices(self):
for n in range(1, 6):
for np_type, atol in [(np.float32, 0.05), (np.float64, 1e-5)]:
@@ -73,6 +75,7 @@ class LogdetTest(test.TestCase):
def setUp(self):
self.rng = np.random.RandomState(42)
+ @test_util.run_deprecated_v1
def test_works_with_five_different_random_pos_def_matrices(self):
for n in range(1, 6):
for np_dtype, atol in [(np.float32, 0.05), (np.float64, 1e-5),
@@ -102,6 +105,7 @@ class SlogdetTest(test.TestCase):
def setUp(self):
self.rng = np.random.RandomState(42)
+ @test_util.run_deprecated_v1
def test_works_with_five_different_random_pos_def_matrices(self):
for n in range(1, 6):
for np_dtype, atol in [(np.float32, 0.05), (np.float64, 1e-5),
@@ -232,6 +236,7 @@ class EyeTest(parameterized.TestCase, test.TestCase):
dtypes.complex128
])
)
+ @test_util.run_deprecated_v1
def test_eye_with_placeholder(
self, num_rows, num_columns, batch_shape, dtype):
eye_np = np.eye(num_rows, M=num_columns, dtype=dtype.as_numpy_dtype)
diff --git a/tensorflow/python/kernel_tests/list_ops_test.py b/tensorflow/python/kernel_tests/list_ops_test.py
index 1d9f4032d1a..8df11564389 100644
--- a/tensorflow/python/kernel_tests/list_ops_test.py
+++ b/tensorflow/python/kernel_tests/list_ops_test.py
@@ -66,6 +66,7 @@ class ListOpsTest(test_util.TensorFlowTestCase, parameterized.TestCase):
with context.device("gpu:0"):
self._testPushPop(max_num_elements)
+ @test_util.run_deprecated_v1
def testPushInFullListFails(self):
l = list_ops.empty_tensor_list(
element_dtype=dtypes.float32, element_shape=[], max_num_elements=1)
@@ -77,6 +78,7 @@ class ListOpsTest(test_util.TensorFlowTestCase, parameterized.TestCase):
@parameterized.named_parameters(("NoMaxNumElements", None),
("WithMaxNumElements", 2))
+ @test_util.run_deprecated_v1
def testPopFromEmptyTensorListFails(self, max_num_elements):
l = list_ops.empty_tensor_list(
element_dtype=dtypes.float32,
@@ -114,6 +116,7 @@ class ListOpsTest(test_util.TensorFlowTestCase, parameterized.TestCase):
@parameterized.named_parameters(("NoMaxNumElements", None),
("WithMaxNumElements", 3))
+ @test_util.run_deprecated_v1
def testStackWithUnknownElementShape(self, max_num_elements):
l = list_ops.empty_tensor_list(
element_dtype=dtypes.float32,
@@ -134,6 +137,7 @@ class ListOpsTest(test_util.TensorFlowTestCase, parameterized.TestCase):
@parameterized.named_parameters(("NoMaxNumElements", None),
("WithMaxNumElements", 3))
+ @test_util.run_deprecated_v1
def testStackWithPartiallyDefinedElementShape(self, max_num_elements):
l = list_ops.empty_tensor_list(
element_dtype=dtypes.float32,
@@ -154,6 +158,7 @@ class ListOpsTest(test_util.TensorFlowTestCase, parameterized.TestCase):
@parameterized.named_parameters(("NoMaxNumElements", None),
("WithMaxNumElements", 2))
+ @test_util.run_deprecated_v1
def testStackEmptyList(self, max_num_elements):
# Should be able to stack empty lists with fully defined element_shape.
l = list_ops.empty_tensor_list(
@@ -204,6 +209,7 @@ class ListOpsTest(test_util.TensorFlowTestCase, parameterized.TestCase):
@parameterized.named_parameters(("NoMaxNumElements", None),
("WithMaxNumElements", 3))
+ @test_util.run_deprecated_v1
def testGatherWithUnknownElementShape(self, max_num_elements):
l = list_ops.empty_tensor_list(
element_dtype=dtypes.float32,
@@ -227,6 +233,7 @@ class ListOpsTest(test_util.TensorFlowTestCase, parameterized.TestCase):
@parameterized.named_parameters(("NoMaxNumElements", None),
("WithMaxNumElements", 3))
+ @test_util.run_deprecated_v1
def testGatherWithPartiallyDefinedElementShape(self, max_num_elements):
l = list_ops.empty_tensor_list(
element_dtype=dtypes.float32,
@@ -250,6 +257,7 @@ class ListOpsTest(test_util.TensorFlowTestCase, parameterized.TestCase):
@parameterized.named_parameters(("NoMaxNumElements", None),
("WithMaxNumElements", 3))
+ @test_util.run_deprecated_v1
def testGatherEmptyList(self, max_num_elements):
# Should be able to gather from empty lists with fully defined
# element_shape.
@@ -337,6 +345,7 @@ class ListOpsTest(test_util.TensorFlowTestCase, parameterized.TestCase):
self.assertAllEqual(self.evaluate(e), 10.0)
self.assertAllEqual(self.evaluate(tape.gradient(e, t)), 2.0)
+ @test_util.run_deprecated_v1
def testSetOnEmptyListWithMaxNumElementsFails(self):
l = list_ops.empty_tensor_list(
element_dtype=dtypes.float32, element_shape=[], max_num_elements=3)
@@ -572,12 +581,14 @@ class ListOpsTest(test_util.TensorFlowTestCase, parameterized.TestCase):
self.assertAllEqual(self.evaluate(grad_c), [0.0, 4.0])
self.assertAllEqual(self.evaluate(grad_c2), 6.0)
+ @test_util.run_deprecated_v1
def testSetOutOfBounds(self):
c = constant_op.constant([1.0, 2.0])
l = list_ops.tensor_list_from_tensor(c, element_shape=[])
with self.assertRaises(errors.InvalidArgumentError):
self.evaluate(list_ops.tensor_list_set_item(l, 20, 3.0))
+ @test_util.run_deprecated_v1
def testSkipEagerSetItemWithMismatchedShapeFails(self):
with self.cached_session() as sess:
ph = array_ops.placeholder(dtypes.float32)
@@ -612,6 +623,7 @@ class ListOpsTest(test_util.TensorFlowTestCase, parameterized.TestCase):
[[1.0, 2.0]] * 4)
self.assertAllEqual(self.evaluate(updated_v_stacked), expected)
+ @test_util.run_deprecated_v1
def testConcat(self):
c = constant_op.constant([1.0, 2.0], dtype=dtypes.float32)
l0 = list_ops.tensor_list_from_tensor(c, element_shape=[])
@@ -670,6 +682,7 @@ class ListOpsTest(test_util.TensorFlowTestCase, parameterized.TestCase):
list_ops.tensor_list_concat_lists(l_batch_0, l_batch_of_int_tls,
element_dtype=dtypes.float32))
+ @test_util.run_deprecated_v1
def testPushBackBatch(self):
c = constant_op.constant([1.0, 2.0], dtype=dtypes.float32)
l0 = list_ops.tensor_list_from_tensor(c, element_shape=[])
@@ -797,6 +810,7 @@ class ListOpsTest(test_util.TensorFlowTestCase, parameterized.TestCase):
self.assertAllEqual(self.evaluate(res_1), [0.])
self.assertAllEqual(self.evaluate(res_2), [0., 0.])
+ @test_util.run_deprecated_v1
def testSkipEagerTensorListGetItemGradAggregation(self):
l = list_ops.tensor_list_reserve(
element_shape=[], num_elements=1, element_dtype=dtypes.float32)
@@ -808,6 +822,7 @@ class ListOpsTest(test_util.TensorFlowTestCase, parameterized.TestCase):
with self.cached_session() as sess:
self.assertSequenceEqual(self.evaluate(grad), [2.])
+ @test_util.run_deprecated_v1
def testSkipEagerBuildElementShape(self):
fn = list_ops._build_element_shape
# Unknown shape -> -1.
diff --git a/tensorflow/python/kernel_tests/logging_ops_test.py b/tensorflow/python/kernel_tests/logging_ops_test.py
index e8fa1cfa28d..85035e5f7d3 100644
--- a/tensorflow/python/kernel_tests/logging_ops_test.py
+++ b/tensorflow/python/kernel_tests/logging_ops_test.py
@@ -39,6 +39,7 @@ from tensorflow.python.platform import test
class LoggingOpsTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testAssertDivideByZero(self):
with self.cached_session() as sess:
epsilon = ops.convert_to_tensor(1e-20)
@@ -305,12 +306,14 @@ class PrintV2Test(test.TestCase):
tensor, output_stream="unknown")
self.evaluate(print_op)
+ @test_util.run_deprecated_v1
def testPrintOpName(self):
with self.cached_session():
tensor = math_ops.range(10)
print_op = logging_ops.print_v2(tensor, name="print_name")
self.assertEqual(print_op.name, "print_name")
+ @test_util.run_deprecated_v1
def testNoDuplicateFormatOpGraphModeAfterExplicitFormat(self):
with self.cached_session():
tensor = math_ops.range(10)
@@ -379,6 +382,7 @@ class PrintGradientTest(test.TestCase):
inp_printed = logging_ops.Print(inp, ["hello"])
self.assertEqual(inp.get_shape(), inp_printed.get_shape())
+ @test_util.run_deprecated_v1
def testPrintGradient(self):
with self.cached_session():
inp = constant_op.constant(2.0, shape=[100, 32], name="in")
diff --git a/tensorflow/python/kernel_tests/lookup_ops_test.py b/tensorflow/python/kernel_tests/lookup_ops_test.py
index 79961d8dd1d..ad81e0be649 100644
--- a/tensorflow/python/kernel_tests/lookup_ops_test.py
+++ b/tensorflow/python/kernel_tests/lookup_ops_test.py
@@ -37,6 +37,7 @@ from tensorflow.python.training import server_lib
class HashTableOpTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testHashTable(self):
with self.cached_session():
default_val = -1
@@ -61,6 +62,7 @@ class HashTableOpTest(test.TestCase):
self.evaluate(exported_keys_tensor))
self.assertItemsEqual([0, 1, 2], self.evaluate(exported_values_tensor))
+ @test_util.run_deprecated_v1
def testHashTableFindHighRank(self):
with self.cached_session():
default_val = -1
@@ -79,6 +81,7 @@ class HashTableOpTest(test.TestCase):
result = self.evaluate(output)
self.assertAllEqual([[0, 1], [-1, -1]], result)
+ @test_util.run_deprecated_v1
def testHashTableInitWithPythonArrays(self):
with self.cached_session():
default_val = -1
@@ -97,6 +100,7 @@ class HashTableOpTest(test.TestCase):
result = self.evaluate(output)
self.assertAllEqual([0, 1, -1], result)
+ @test_util.run_deprecated_v1
def testHashTableInitWithNumPyArrays(self):
with self.cached_session():
default_val = -1
@@ -114,6 +118,7 @@ class HashTableOpTest(test.TestCase):
result = self.evaluate(output)
self.assertAllEqual([0, 1, -1], result)
+ @test_util.run_deprecated_v1
def testMultipleHashTables(self):
with self.cached_session() as sess:
default_val = -1
@@ -142,6 +147,7 @@ class HashTableOpTest(test.TestCase):
self.assertAllEqual([0, 1, -1], out2)
self.assertAllEqual([0, 1, -1], out3)
+ @test_util.run_deprecated_v1
def testHashTableWithTensorDefault(self):
with self.cached_session():
default_val = constant_op.constant(-1, dtypes.int64)
@@ -157,6 +163,7 @@ class HashTableOpTest(test.TestCase):
result = self.evaluate(output)
self.assertAllEqual([0, 1, -1], result)
+ @test_util.run_deprecated_v1
def testHashTableWithSparseTensorInput(self):
with self.cached_session() as sess:
default_val = constant_op.constant(-1, dtypes.int64)
@@ -180,6 +187,7 @@ class HashTableOpTest(test.TestCase):
self.assertAllEqual(sp_indices, out_indices)
self.assertAllEqual(sp_shape, out_shape)
+ @test_util.run_deprecated_v1
def testSignatureMismatch(self):
with self.cached_session():
default_val = -1
@@ -210,6 +218,7 @@ class HashTableOpTest(test.TestCase):
lookup_ops.KeyValueTensorInitializer(["a"], [1], [dtypes.string],
dtypes.int64), default_val)
+ @test_util.run_deprecated_v1
def testNotInitialized(self):
with self.cached_session():
default_val = -1
@@ -223,6 +232,7 @@ class HashTableOpTest(test.TestCase):
with self.assertRaisesOpError("Table not initialized"):
self.evaluate(output)
+ @test_util.run_deprecated_v1
def testInitializeTwice(self):
with self.cached_session():
default_val = -1
@@ -235,6 +245,7 @@ class HashTableOpTest(test.TestCase):
with self.assertRaisesOpError("Table already initialized"):
table.initializer.run()
+ @test_util.run_deprecated_v1
def testInitializationWithInvalidDimensions(self):
with self.cached_session():
default_val = -1
@@ -245,6 +256,7 @@ class HashTableOpTest(test.TestCase):
lookup_ops.HashTable(
lookup_ops.KeyValueTensorInitializer(keys, values), default_val)
+ @test_util.run_deprecated_v1
def testMultipleSessions(self):
# Start a server
server = server_lib.Server(
@@ -274,6 +286,7 @@ class HashTableOpTest(test.TestCase):
table.initializer.run()
self.assertAllEqual(3, table.size().eval())
+ @test_util.run_deprecated_v1
def testHashTableInt32String(self):
with self.cached_session():
default_val = "n/a"
@@ -298,6 +311,7 @@ class IndexTableFromFile(test.TestCase):
f.write("\n".join(values) + "\n")
return vocabulary_file
+ @test_util.run_deprecated_v1
def test_string_index_table_from_file(self):
vocabulary_file = self._createVocabFile("f2i_vocab1.txt")
with self.cached_session():
@@ -310,6 +324,7 @@ class IndexTableFromFile(test.TestCase):
lookup_ops.tables_initializer().run()
self.assertAllEqual((1, 2, 3), self.evaluate(ids))
+ @test_util.run_deprecated_v1
def test_string_index_table_from_multicolumn_file(self):
vocabulary_file = self._createVocabFile(
"f2i_vocab1.txt", values=("brain\t300", "salad\t20", "surgery\t1"))
@@ -326,6 +341,7 @@ class IndexTableFromFile(test.TestCase):
lookup_ops.tables_initializer().run()
self.assertAllEqual((1, 2, 3), self.evaluate(ids))
+ @test_util.run_deprecated_v1
def test_string_index_table_from_multicolumn_file_custom_delimiter(self):
vocabulary_file = self._createVocabFile(
"f2i_vocab1.txt", values=("brain 300", "salad 20", "surgery 1"))
@@ -343,6 +359,7 @@ class IndexTableFromFile(test.TestCase):
lookup_ops.tables_initializer().run()
self.assertAllEqual((1, 2, 3), self.evaluate(ids))
+ @test_util.run_deprecated_v1
def test_string_index_table_from_file_tensor_filename(self):
vocabulary_file = self._createVocabFile("f2i_vocab1.txt")
with self.cached_session():
@@ -358,6 +375,7 @@ class IndexTableFromFile(test.TestCase):
self.assertEqual(1,
len(ops.get_collection(ops.GraphKeys.ASSET_FILEPATHS)))
+ @test_util.run_deprecated_v1
def test_string_index_table_from_file_placeholder_filename(self):
vocabulary_file = self._createVocabFile("f2i_vocab1.txt")
with self.cached_session():
@@ -375,6 +393,7 @@ class IndexTableFromFile(test.TestCase):
self.assertEqual(0,
len(ops.get_collection(ops.GraphKeys.ASSET_FILEPATHS)))
+ @test_util.run_deprecated_v1
def test_int32_index_table_from_file(self):
vocabulary_file = self._createVocabFile(
"f2i_vocab2.txt", values=("42", "1", "-1000"))
@@ -391,6 +410,7 @@ class IndexTableFromFile(test.TestCase):
lookup_ops.tables_initializer().run()
self.assertAllEqual((1, 2, 3), self.evaluate(ids))
+ @test_util.run_deprecated_v1
def test_int64_index_table_from_file(self):
vocabulary_file = self._createVocabFile(
"f2i_vocab3.txt", values=("42", "1", "-1000"))
@@ -407,6 +427,7 @@ class IndexTableFromFile(test.TestCase):
lookup_ops.tables_initializer().run()
self.assertAllEqual((1, 2, 3), self.evaluate(ids))
+ @test_util.run_deprecated_v1
def test_index_table_from_file_with_default_value(self):
default_value = -42
vocabulary_file = self._createVocabFile("f2i_vocab4.txt")
@@ -420,6 +441,7 @@ class IndexTableFromFile(test.TestCase):
lookup_ops.tables_initializer().run()
self.assertAllEqual((1, 2, default_value), self.evaluate(ids))
+ @test_util.run_deprecated_v1
def test_index_table_from_file_with_oov_buckets(self):
vocabulary_file = self._createVocabFile("f2i_vocab5.txt")
with self.cached_session():
@@ -468,6 +490,7 @@ class IndexTableFromFile(test.TestCase):
vocabulary_file=vocabulary_file,
vocab_size=0)
+ @test_util.run_deprecated_v1
def test_index_table_from_file_with_vocab_size_too_small(self):
vocabulary_file = self._createVocabFile("f2i_vocab6.txt")
with self.cached_session():
@@ -481,6 +504,7 @@ class IndexTableFromFile(test.TestCase):
self.assertAllEqual((1, -1, -1), self.evaluate(ids))
self.assertEqual(2, table.size().eval())
+ @test_util.run_deprecated_v1
def test_index_table_from_file_with_vocab_size_too_large(self):
vocabulary_file = self._createVocabFile("f2i_vocab7.txt")
with self.cached_session():
@@ -489,6 +513,7 @@ class IndexTableFromFile(test.TestCase):
self.assertRaisesRegexp(errors_impl.InvalidArgumentError,
"Invalid vocab_size", table.initializer.run)
+ @test_util.run_deprecated_v1
def test_index_table_from_file_with_vocab_size(self):
vocabulary_file = self._createVocabFile("f2i_vocab8.txt")
@@ -577,6 +602,7 @@ class KeyValueTensorInitializerTest(test.TestCase):
table = lookup_ops.HashTable(init, default_value=-1)
table.initializer.run()
+ @test_util.run_deprecated_v1
def test_int32(self):
with ops.Graph().as_default(), self.cached_session():
init = lookup_ops.KeyValueTensorInitializer((42, 1, -1000), (0, 1, 2),
@@ -590,6 +616,7 @@ class KeyValueTensorInitializerTest(test.TestCase):
class IndexTableFromTensor(test.TestCase):
@test_util.run_in_graph_and_eager_modes
+ @test_util.run_deprecated_v1
def test_index_table_from_tensor_with_tensor_init(self):
table = lookup_ops.index_table_from_tensor(
vocabulary_list=("brain", "salad", "surgery"), num_oov_buckets=1)
@@ -606,6 +633,7 @@ class IndexTableFromTensor(test.TestCase):
ids = table.lookup(constant_op.constant(("salad", "surgery", "tarkus")))
self.assertAllEqual((1, 2, 3), self.evaluate(ids))
+ @test_util.run_deprecated_v1
def test_int32_index_table_from_tensor_with_tensor_init(self):
with self.cached_session():
table = lookup_ops.index_table_from_tensor(
@@ -618,6 +646,7 @@ class IndexTableFromTensor(test.TestCase):
lookup_ops.tables_initializer().run()
self.assertAllEqual((1, 2, 3), self.evaluate(ids))
+ @test_util.run_deprecated_v1
def test_int64_index_table_from_tensor_with_tensor_init(self):
with self.cached_session():
table = lookup_ops.index_table_from_tensor(
@@ -630,6 +659,7 @@ class IndexTableFromTensor(test.TestCase):
lookup_ops.tables_initializer().run()
self.assertAllEqual((1, 2, 3), self.evaluate(ids))
+ @test_util.run_deprecated_v1
def test_index_table_from_tensor_with_default_value(self):
default_value = -42
with self.cached_session():
@@ -650,6 +680,7 @@ class IndexTableFromTensor(test.TestCase):
lookup_ops.index_table_from_tensor(
vocabulary_list=None, num_oov_buckets=1)
+ @test_util.run_deprecated_v1
def test_index_table_from_tensor_empty_vocabulary_list(self):
with self.cached_session():
table = lookup_ops.index_table_from_tensor(
@@ -686,6 +717,7 @@ class IndexToStringTableFromFileTest(test.TestCase):
f.write("\n".join(values) + "\n")
return vocabulary_file
+ @test_util.run_deprecated_v1
def test_index_to_string_table(self):
vocabulary_path = self._createVocabFile("i2f_vocab1.txt")
# vocabulary_file supports string and tensor
@@ -703,6 +735,7 @@ class IndexToStringTableFromFileTest(test.TestCase):
self.assertAllEqual((b"brain", b"salad", b"surgery", b"UNK"),
self.evaluate(features))
+ @test_util.run_deprecated_v1
def test_index_to_string_table_from_multicolumn_file(self):
vocabulary_file = self._createVocabFile(
"f2i_vocab1.txt", values=("brain\t300", "salad\t20", "surgery\t1"))
@@ -718,6 +751,7 @@ class IndexToStringTableFromFileTest(test.TestCase):
self.assertAllEqual((b"brain", b"salad", b"surgery", b"UNK"),
self.evaluate(features))
+ @test_util.run_deprecated_v1
def test_index_to_string_table_from_multicolumn_file_custom_delimiter(self):
vocabulary_file = self._createVocabFile(
"f2i_vocab1.txt", values=("brain 300", "salad 20", "surgery 1"))
@@ -734,6 +768,7 @@ class IndexToStringTableFromFileTest(test.TestCase):
self.assertAllEqual((b"brain", b"salad", b"surgery", b"UNK"),
self.evaluate(features))
+ @test_util.run_deprecated_v1
def test_index_to_string_table_with_default_value(self):
default_value = b"NONE"
vocabulary_file = self._createVocabFile("f2i_vocab2.txt")
@@ -747,6 +782,7 @@ class IndexToStringTableFromFileTest(test.TestCase):
self.assertAllEqual((b"salad", b"surgery", default_value),
self.evaluate(features))
+ @test_util.run_deprecated_v1
def test_index_to_string_table_with_vocab_size_too_small(self):
default_value = b"NONE"
vocabulary_file = self._createVocabFile("f2i_vocab2.txt")
@@ -762,6 +798,7 @@ class IndexToStringTableFromFileTest(test.TestCase):
self.assertAllEqual((b"salad", default_value, default_value),
self.evaluate(features))
+ @test_util.run_deprecated_v1
def test_index_to_string_table_with_vocab_size_too_large(self):
vocabulary_file = self._createVocabFile("f2i_vocab6.txt")
with self.cached_session():
@@ -775,6 +812,7 @@ class IndexToStringTableFromFileTest(test.TestCase):
self.assertRaisesRegexp(errors_impl.InvalidArgumentError,
"Invalid vocab_size", init.run)
+ @test_util.run_deprecated_v1
def test_index_to_string_table_with_vocab_size(self):
vocabulary_file = self._createVocabFile("f2i_vocab7.txt")
with self.cached_session():
@@ -791,6 +829,7 @@ class IndexToStringTableFromFileTest(test.TestCase):
class IndexToStringTableFromTensorTest(test.TestCase):
+ @test_util.run_deprecated_v1
def test_index_to_string_table_from_tensor(self):
with self.cached_session():
vocabulary_list = constant_op.constant(["brain", "salad", "surgery"])
@@ -806,6 +845,7 @@ class IndexToStringTableFromTensorTest(test.TestCase):
self.assertAllEqual((b"brain", b"salad", b"surgery", b"UNK"),
self.evaluate(features))
+ @test_util.run_deprecated_v1
def test_duplicate_entries(self):
with self.cached_session():
vocabulary_list = constant_op.constant(["hello", "hello"])
@@ -816,6 +856,7 @@ class IndexToStringTableFromTensorTest(test.TestCase):
lookup_ops.tables_initializer().run()
self.assertAllEqual((b"hello", b"hello", b"UNK"), self.evaluate(features))
+ @test_util.run_deprecated_v1
def test_index_to_string_with_default_value(self):
default_value = b"NONE"
with self.cached_session():
@@ -855,6 +896,7 @@ class InitializeTableFromFileOpTest(test.TestCase):
result = self.evaluate(output)
self.assertAllEqual([0, 1, -1], result)
+ @test_util.run_deprecated_v1
def testInitializeInt64Table(self):
vocabulary_file = self._createVocabFile(
"one_column_int64.txt", values=("42", "1", "-1000"))
@@ -874,6 +916,7 @@ class InitializeTableFromFileOpTest(test.TestCase):
result = self.evaluate(output)
self.assertAllEqual([0, 1, -1], result)
+ @test_util.run_deprecated_v1
def testInitializeIndexTable(self):
vocabulary_file = self._createVocabFile("one_column_2.txt")
@@ -893,6 +936,7 @@ class InitializeTableFromFileOpTest(test.TestCase):
result = self.evaluate(output)
self.assertAllEqual([b"brain", b"salad", b"surgery", b"UNK"], result)
+ @test_util.run_deprecated_v1
def testMultiColumn(self):
vocabulary_file = os.path.join(self.get_temp_dir(), "three_columns.txt")
with open(vocabulary_file, "w") as f:
@@ -915,6 +959,7 @@ class InitializeTableFromFileOpTest(test.TestCase):
result = self.evaluate(output)
self.assertAllEqual([1, 5, 6], result)
+ @test_util.run_deprecated_v1
def testInvalidDataTypeInMultiColumn(self):
vocabulary_file = os.path.join(self.get_temp_dir(), "three_columns.txt")
with open(vocabulary_file, "w") as f:
@@ -945,6 +990,7 @@ class InitializeTableFromFileOpTest(test.TestCase):
key_index, dtypes.string,
value_index), default_value)
+ @test_util.run_deprecated_v1
def testInvalidIndex(self):
vocabulary_file = self._createVocabFile("one_column_4.txt")
with self.cached_session():
@@ -959,6 +1005,7 @@ class InitializeTableFromFileOpTest(test.TestCase):
with self.assertRaisesOpError("Invalid number of columns"):
table.initializer.run()
+ @test_util.run_deprecated_v1
def testInitializeSameTableWithMultipleNodes(self):
vocabulary_file = self._createVocabFile("one_column_5.txt")
@@ -1010,6 +1057,7 @@ class InitializeTableFromFileOpTest(test.TestCase):
dtypes.int64, lookup_ops.TextFileIndex.LINE_NUMBER),
default_value)
+ @test_util.run_deprecated_v1
def testInitializeWithVocabSize(self):
with self.cached_session():
default_value = -1
@@ -1056,6 +1104,7 @@ class InitializeTableFromFileOpTest(test.TestCase):
table3.initializer.run()
self.assertEquals(vocab_size, table3.size().eval())
+ @test_util.run_deprecated_v1
def testFeedVocabularyName(self):
vocabulary_file = self._createVocabFile("feed_vocabulary.txt")
@@ -1082,6 +1131,7 @@ class InitializeTableFromFileOpTest(test.TestCase):
result = self.evaluate(output)
self.assertAllEqual([0, 1, -1], result)
+ @test_util.run_deprecated_v1
def testInvalidFilenames(self):
vocabulary_file = self._createVocabFile("filename_shape.txt")
@@ -1106,6 +1156,7 @@ class InitializeTableFromFileOpTest(test.TestCase):
dtypes.int64, lookup_ops.TextFileIndex.LINE_NUMBER),
default_value)
+ @test_util.run_deprecated_v1
def testIdToStringTable(self):
vocab_file = self._createVocabFile("feat_to_id_1.txt")
with self.cached_session():
@@ -1124,6 +1175,7 @@ class InitializeTableFromFileOpTest(test.TestCase):
self.evaluate(out))
self.assertEquals(vocab_size, table.size().eval())
+ @test_util.run_deprecated_v1
def testStringToIdTable(self):
vocab_file = self._createVocabFile("feat_to_id_2.txt")
with self.cached_session():
@@ -1140,6 +1192,7 @@ class InitializeTableFromFileOpTest(test.TestCase):
self.assertAllEqual([0, 1, 2, -1], self.evaluate(out))
self.assertEquals(vocab_size, table.size().eval())
+ @test_util.run_deprecated_v1
def testInt64ToIdTable(self):
vocab_file = self._createVocabFile(
"feat_to_id_3.txt", values=("42", "1", "-1000"))
@@ -1166,6 +1219,7 @@ class IdTableWithHashBucketsTest(test.TestCase):
f.write("\n".join(values) + "\n")
return vocabulary_file
+ @test_util.run_deprecated_v1
def testStringIdTableWithHashBuckets(self):
vocab_file = self._createVocabFile("feat_to_id_1.txt")
with self.cached_session():
@@ -1186,6 +1240,7 @@ class IdTableWithHashBucketsTest(test.TestCase):
self.assertAllEqual([0, 1, 2, 3], self.evaluate(out))
self.assertEquals(vocab_size + oov_buckets, table.size().eval())
+ @test_util.run_deprecated_v1
def testInt32IdTableWithHashBuckets(self):
vocab_file = self._createVocabFile("feat_to_id_2.txt", ("42", "1", "-1000"))
with self.cached_session():
@@ -1208,6 +1263,7 @@ class IdTableWithHashBucketsTest(test.TestCase):
self.assertAllEqual([0, 1, 2, 3], self.evaluate(out))
self.assertEquals(vocab_size + oov_buckets, table.size().eval())
+ @test_util.run_deprecated_v1
def testInt64IdTableWithHashBuckets(self):
vocab_file = self._createVocabFile("feat_to_id_3.txt", ("42", "1", "-1000"))
with self.cached_session():
@@ -1228,6 +1284,7 @@ class IdTableWithHashBucketsTest(test.TestCase):
self.assertAllEqual([0, 1, 2, 3], self.evaluate(out))
self.assertEquals(vocab_size + oov_buckets, table.size().eval())
+ @test_util.run_deprecated_v1
def testStringIdTableWithOnlyHashBucket(self):
with self.cached_session():
oov_buckets = 5
@@ -1249,6 +1306,7 @@ class IdTableWithHashBucketsTest(test.TestCase):
self.evaluate(out))
self.assertEquals(oov_buckets, table.size().eval())
+ @test_util.run_deprecated_v1
def testInt32IdTableWithOnlyHashBucket(self):
with self.cached_session():
oov_buckets = 5
@@ -1283,6 +1341,7 @@ class IdTableWithHashBucketsTest(test.TestCase):
lookup_ops.IdTableWithHashBuckets(
None, num_oov_buckets=5, key_dtype=dtypes.bool)
+ @test_util.run_deprecated_v1
def testIdTableWithHashBucketsWithMultipleInitializers(self):
vocab_file = self._createVocabFile("feat_to_id_4.txt")
with self.cached_session() as sess:
@@ -1323,6 +1382,7 @@ class IdTableWithHashBucketsTest(test.TestCase):
"table2_Lookup/hash_bucket": "StringToHashBucketStrong",
}, sess.graph)
+ @test_util.run_deprecated_v1
def testIdTableWithHashBucketsInitializationAcrossSessions(self):
vocab_file = self._createVocabFile("feat_to_id_5.txt")
shared_name = "across-sessions"
@@ -1368,6 +1428,7 @@ class IdTableWithHashBucketsTest(test.TestCase):
self.assertAllEqual([3, 1, 3], self.evaluate(out2))
self.assertEquals(vocab_size + oov_buckets, table2.size().eval())
+ @test_util.run_deprecated_v1
def testIdTableWithHashBucketsWithMultipleInitializersDifferentDefault(self):
vocab_file = self._createVocabFile("feat_to_id_6.txt")
with self.cached_session() as sess:
@@ -1402,6 +1463,7 @@ class IdTableWithHashBucketsTest(test.TestCase):
self.assertEquals(vocab_size + oov_buckets, table1.size().eval())
self.assertEquals(vocab_size + oov_buckets, table2.size().eval())
+ @test_util.run_deprecated_v1
def testSparseTensor(self):
vocab_file = self._createVocabFile("feat_to_id_7.txt")
input_indices = [[0, 0], [0, 1], [2, 0], [2, 2], [3, 0]]
@@ -1430,6 +1492,7 @@ class IdTableWithHashBucketsTest(test.TestCase):
self.assertAllEqual([0, 1, 0, 2, 3], sp_ids_val)
self.assertAllEqual(input_shape, sp_ids_shape)
+ @test_util.run_deprecated_v1
def testInt32SparseTensor(self):
input_indices = [[0, 0], [0, 1], [2, 0], [2, 2], [3, 0]]
input_shape = [4, 4]
@@ -1458,6 +1521,7 @@ class IdTableWithHashBucketsTest(test.TestCase):
self.assertAllEqual([0, 1, 0, 2, 3], sp_ids_val)
self.assertAllEqual(input_shape, sp_ids_shape)
+ @test_util.run_deprecated_v1
def testInt64SparseTensor(self):
input_indices = [[0, 0], [0, 1], [2, 0], [2, 2], [3, 0]]
input_shape = [4, 4]
diff --git a/tensorflow/python/kernel_tests/losses_test.py b/tensorflow/python/kernel_tests/losses_test.py
index bda63bcaa92..abff61f81b0 100644
--- a/tensorflow/python/kernel_tests/losses_test.py
+++ b/tensorflow/python/kernel_tests/losses_test.py
@@ -51,22 +51,26 @@ class AbsoluteDifferenceLossTest(test.TestCase):
losses.absolute_difference(
self._predictions, self._predictions, weights=None)
+ @test_util.run_deprecated_v1
def testAllCorrectNoLossWeight(self):
loss = losses.absolute_difference(self._predictions, self._predictions)
with self.cached_session():
self.assertAlmostEqual(0.0, self.evaluate(loss), 3)
+ @test_util.run_deprecated_v1
def testNonZeroLoss(self):
loss = losses.absolute_difference(self._labels, self._predictions)
with self.cached_session():
self.assertAlmostEqual(5.5, self.evaluate(loss), 3)
+ @test_util.run_deprecated_v1
def testNonZeroLossWithPythonScalarWeight(self):
weights = 2.3
loss = losses.absolute_difference(self._labels, self._predictions, weights)
with self.cached_session():
self.assertAlmostEqual(5.5 * weights, self.evaluate(loss), 3)
+ @test_util.run_deprecated_v1
def testNonZeroLossWithScalarTensorWeight(self):
weights = 2.3
loss = losses.absolute_difference(self._labels, self._predictions,
@@ -123,6 +127,7 @@ class SoftmaxCrossEntropyLossTest(test.TestCase):
with self.assertRaises(ValueError):
losses.softmax_cross_entropy(labels, logits, weights=None)
+ @test_util.run_deprecated_v1
def testAllCorrect(self):
with self.cached_session():
logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
@@ -132,6 +137,7 @@ class SoftmaxCrossEntropyLossTest(test.TestCase):
self.assertEquals('softmax_cross_entropy_loss/value', loss.op.name)
self.assertAlmostEqual(loss.eval(), 0.0, 3)
+ @test_util.run_deprecated_v1
def testAllWrong(self):
logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
[0.0, 0.0, 10.0]])
@@ -142,6 +148,7 @@ class SoftmaxCrossEntropyLossTest(test.TestCase):
self.assertEquals(loss.op.name, 'softmax_cross_entropy_loss/value')
self.assertAlmostEqual(loss.eval(), 10.0, 3)
+ @test_util.run_deprecated_v1
def testNonZeroLossWithPythonScalarWeight(self):
logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
[0.0, 0.0, 10.0]])
@@ -151,6 +158,7 @@ class SoftmaxCrossEntropyLossTest(test.TestCase):
loss = losses.softmax_cross_entropy(labels, logits, weights)
self.assertAlmostEqual(weights * 10.0, self.evaluate(loss), 3)
+ @test_util.run_deprecated_v1
def testNonZeroLossWithScalarTensorWeight(self):
logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
[0.0, 0.0, 10.0]])
@@ -200,6 +208,7 @@ class SoftmaxCrossEntropyLossTest(test.TestCase):
with self.assertRaises(ValueError):
losses.softmax_cross_entropy(labels, logits, weights=weights).eval()
+ @test_util.run_deprecated_v1
def testSoftmaxLabelSmoothing(self):
with self.cached_session():
# Softmax Cross Entropy Loss is:
@@ -232,6 +241,7 @@ class SparseSoftmaxCrossEntropyLossTest(test.TestCase):
with self.assertRaises(ValueError):
losses.sparse_softmax_cross_entropy(labels, logits, weights=None)
+ @test_util.run_deprecated_v1
def testAllCorrectInt32Labels(self):
with self.cached_session():
logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
@@ -248,6 +258,7 @@ class SparseSoftmaxCrossEntropyLossTest(test.TestCase):
labels = constant_op.constant([[0], [1], [2]], dtype=dtypes.int32)
losses.sparse_softmax_cross_entropy(labels, logits)
+ @test_util.run_deprecated_v1
def testAllCorrectInt64Labels(self):
with self.cached_session():
logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
@@ -257,6 +268,7 @@ class SparseSoftmaxCrossEntropyLossTest(test.TestCase):
self.assertEquals(loss.op.name, 'sparse_softmax_cross_entropy_loss/value')
self.assertAlmostEqual(loss.eval(), 0.0, 3)
+ @test_util.run_deprecated_v1
def testAllCorrectNonColumnLabels(self):
with self.cached_session():
logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
@@ -266,6 +278,7 @@ class SparseSoftmaxCrossEntropyLossTest(test.TestCase):
self.assertEquals(loss.op.name, 'sparse_softmax_cross_entropy_loss/value')
self.assertAlmostEqual(loss.eval(), 0.0, 3)
+ @test_util.run_deprecated_v1
def testAllWrongInt32Labels(self):
logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
[0.0, 0.0, 10.0]])
@@ -276,6 +289,7 @@ class SparseSoftmaxCrossEntropyLossTest(test.TestCase):
self.assertEquals(loss.op.name, 'sparse_softmax_cross_entropy_loss/value')
self.assertAlmostEqual(loss.eval(), 10.0, 3)
+ @test_util.run_deprecated_v1
def testAllWrongInt64Labels(self):
logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
[0.0, 0.0, 10.0]])
@@ -286,6 +300,7 @@ class SparseSoftmaxCrossEntropyLossTest(test.TestCase):
self.assertEquals(loss.op.name, 'sparse_softmax_cross_entropy_loss/value')
self.assertAlmostEqual(loss.eval(), 10.0, 3)
+ @test_util.run_deprecated_v1
def testAllWrongNonColumnLabels(self):
logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
[0.0, 0.0, 10.0]])
@@ -296,6 +311,7 @@ class SparseSoftmaxCrossEntropyLossTest(test.TestCase):
self.assertEquals(loss.op.name, 'sparse_softmax_cross_entropy_loss/value')
self.assertAlmostEqual(loss.eval(), 10.0, 3)
+ @test_util.run_deprecated_v1
def testNonZeroLossWithPythonScalarWeight(self):
logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
[0.0, 0.0, 10.0]])
@@ -305,6 +321,7 @@ class SparseSoftmaxCrossEntropyLossTest(test.TestCase):
loss = losses.sparse_softmax_cross_entropy(labels, logits, weights)
self.assertAlmostEqual(weights * 10.0, self.evaluate(loss), 3)
+ @test_util.run_deprecated_v1
def testNonZeroLossWithScalarTensorWeight(self):
logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
[0.0, 0.0, 10.0]])
@@ -325,6 +342,7 @@ class SparseSoftmaxCrossEntropyLossTest(test.TestCase):
labels, logits, constant_op.constant((weights,)))
self.assertAlmostEqual(weights * 10.0, self.evaluate(loss), 3)
+ @test_util.run_deprecated_v1
def testNonZeroLossWithPlaceholderForWeights(self):
logits = constant_op.constant([[10.0, 0.0, 0.0],
[0.0, 10.0, 0.0],
@@ -337,6 +355,7 @@ class SparseSoftmaxCrossEntropyLossTest(test.TestCase):
feed_dict={weights: ((1.2,), (3.4,), (5.6,))})
self.assertAlmostEqual((1.2 + 3.4 + 5.6) * 10.0 / 3.0, loss_val, 3)
+ @test_util.run_deprecated_v1
def testUnknownShapePlaceholderForLogitsLabelsButScalarWeights(self):
logits = array_ops.placeholder(dtypes.float32)
labels = array_ops.placeholder(dtypes.int32)
@@ -352,6 +371,7 @@ class SparseSoftmaxCrossEntropyLossTest(test.TestCase):
})
self.assertAlmostEqual((1.0 + 1.0 + 1.0) * 10.0 / 3.0, loss_val, 3)
+ @test_util.run_deprecated_v1
def testNonZeroLossWithPlaceholderForLogitsLabelsAndWeights(self):
logits = array_ops.placeholder(dtypes.float32, shape=(None, 3))
labels = array_ops.placeholder(dtypes.int32, shape=(None, 1))
@@ -406,6 +426,7 @@ class SparseSoftmaxCrossEntropyLossTest(test.TestCase):
loss = losses.sparse_softmax_cross_entropy(labels, logits, weights)
self.assertAlmostEqual(12.0, self.evaluate(loss), 3)
+ @test_util.run_deprecated_v1
def testMeasurementSpecificWeightsRaisesException(self):
with self.cached_session():
logits = constant_op.constant([[100.0, -100.0, -100.0],
@@ -444,6 +465,7 @@ class SparseSoftmaxCrossEntropyLossTest(test.TestCase):
losses.sparse_softmax_cross_entropy(
labels, logits, weights=weights).eval()
+ @test_util.run_deprecated_v1
def testInconsistentWeightShapeRaisesException(self):
"""The weight tensor has incorrect shape."""
with self.cached_session():
@@ -458,6 +480,7 @@ class SparseSoftmaxCrossEntropyLossTest(test.TestCase):
losses.sparse_softmax_cross_entropy(
labels, logits, weights=weights).eval()
+ @test_util.run_deprecated_v1
def testInconsistentLabelShapeRaisesException(self):
"""The label tensor has incorrect shape."""
with self.cached_session():
@@ -475,6 +498,7 @@ class SparseSoftmaxCrossEntropyLossTest(test.TestCase):
class SigmoidCrossEntropyLossTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testAllCorrectSigmoid(self):
with self.cached_session():
logits = constant_op.constant([[100.0, -100.0, -100.0],
@@ -486,6 +510,7 @@ class SigmoidCrossEntropyLossTest(test.TestCase):
self.assertEquals('sigmoid_cross_entropy_loss/value', loss.op.name)
self.assertAlmostEqual(0.0, self.evaluate(loss), 3)
+ @test_util.run_deprecated_v1
def testLossWithSingleDimPlaceholderForLogitsAndWeights1(self):
logits = array_ops.placeholder(dtypes.float32, shape=(None, 1))
labels = array_ops.placeholder(dtypes.float32, shape=(None, 1))
@@ -502,6 +527,7 @@ class SigmoidCrossEntropyLossTest(test.TestCase):
})
self.assertAlmostEqual(0.313, loss, 3)
+ @test_util.run_deprecated_v1
def testLossWithSingleDimPlaceholderForLogitsAndWeights2(self):
logits = array_ops.placeholder(dtypes.float32, shape=(None, 2))
labels = array_ops.placeholder(dtypes.float32, shape=(None, 2))
@@ -518,6 +544,7 @@ class SigmoidCrossEntropyLossTest(test.TestCase):
})
self.assertAlmostEqual(0.313, loss, 3)
+ @test_util.run_deprecated_v1
def testAllWrongSigmoid(self):
with self.cached_session():
logits = constant_op.constant([[100.0, -100.0, -100.0],
@@ -529,6 +556,7 @@ class SigmoidCrossEntropyLossTest(test.TestCase):
self.assertEquals('sigmoid_cross_entropy_loss/value', loss.op.name)
self.assertAlmostEqual(loss.eval(), 600.0 / 9.0, 3)
+ @test_util.run_deprecated_v1
def testAllWrongSigmoidWithMeasurementSpecificWeights(self):
with self.cached_session():
logits = constant_op.constant([[100.0, -100.0, -100.0],
@@ -541,6 +569,7 @@ class SigmoidCrossEntropyLossTest(test.TestCase):
self.assertEquals('sigmoid_cross_entropy_loss/value', loss.op.name)
self.assertAlmostEqual(1700.0 / 7.0, self.evaluate(loss), 3)
+ @test_util.run_deprecated_v1
def testMultiCorrectSigmoid(self):
logits = constant_op.constant([[100.0, -100.0, 100.0],
[100.0, 100.0, -100.0],
@@ -582,6 +611,7 @@ class SigmoidCrossEntropyLossTest(test.TestCase):
self.assertAllClose(((0., 0., 0.), (0., 100., 100.), (100., 0., 100.)),
self.evaluate(loss), 3)
+ @test_util.run_deprecated_v1
def testSigmoidLabelSmoothingCorrect(self):
with self.cached_session():
logits = constant_op.constant([[100.0, -100.0, -100.0]])
@@ -605,6 +635,7 @@ class SigmoidCrossEntropyLossTest(test.TestCase):
expected_value = (100.0 + 50.0 * label_smoothing) / 3.0
self.assertAlmostEqual(loss.eval(), expected_value, 3)
+ @test_util.run_deprecated_v1
def testSigmoidLabelSmoothingEqualsSoftmaxTwoLabel(self):
with self.cached_session():
label_smoothing = 0.1
@@ -646,11 +677,13 @@ class LogLossTest(test.TestCase):
with self.assertRaises(ValueError):
losses.log_loss(self._labels, self._labels, weights=None)
+ @test_util.run_deprecated_v1
def testAllCorrectNoLossWeight(self):
loss = losses.log_loss(self._labels, self._labels)
with self.cached_session():
self.assertAlmostEqual(0.0, self.evaluate(loss), 3)
+ @test_util.run_deprecated_v1
def testAllCorrectNoLossWeightWithPlaceholder(self):
tf_predictions = array_ops.placeholder(
dtypes.float32, shape=self._np_labels.shape)
@@ -659,12 +692,14 @@ class LogLossTest(test.TestCase):
self.assertAlmostEqual(
0.0, loss.eval(feed_dict={tf_predictions: self._np_labels}), 3)
+ @test_util.run_deprecated_v1
def testNonZeroLoss(self):
loss = losses.log_loss(self._labels, self._predictions)
with self.cached_session():
self.assertAlmostEqual(-np.sum(self._expected_losses) / 6.0,
self.evaluate(loss), 3)
+ @test_util.run_deprecated_v1
def testNonZeroLossWithPythonScalarWeight(self):
weights = 2.3
loss = losses.log_loss(self._labels, self._predictions, weights)
@@ -672,6 +707,7 @@ class LogLossTest(test.TestCase):
self.assertAlmostEqual(weights * -np.sum(self._expected_losses) / 6.0,
self.evaluate(loss), 3)
+ @test_util.run_deprecated_v1
def testNonZeroLossWithScalarTensorWeight(self):
weights = 2.3
loss = losses.log_loss(self._labels, self._predictions,
@@ -680,6 +716,7 @@ class LogLossTest(test.TestCase):
self.assertAlmostEqual(weights * -np.sum(self._expected_losses) / 6.0,
self.evaluate(loss), 3)
+ @test_util.run_deprecated_v1
def testNonZeroLossWithScalarTensorWeightAndPlaceholder(self):
tf_predictions = array_ops.placeholder(
dtypes.float32, shape=self._np_predictions.shape)
@@ -691,6 +728,7 @@ class LogLossTest(test.TestCase):
self.assertAlmostEqual(weights * -np.sum(self._expected_losses) / 6.0,
loss, 3)
+ @test_util.run_deprecated_v1
def testNonZeroLossWithScalarTensorWeightAndPlaceholderWithRankOnly(self):
tf_predictions = array_ops.placeholder(dtypes.float32, shape=[None, None])
weights = 2.3
@@ -750,6 +788,7 @@ class LogLossTest(test.TestCase):
self.assertAlmostEqual(-np.sum(expected_losses) / 5.0,
self.evaluate(loss), 3)
+ @test_util.run_deprecated_v1
def testNonZeroLossWithMeasurementSpecificWeightsWithPlaceholder(self):
weights = np.array([3, 6, 5, 0, 4, 2]).reshape((2, 3))
expected_losses = np.multiply(self._expected_losses, weights)
@@ -777,6 +816,7 @@ class LogLossTest(test.TestCase):
with self.cached_session():
self.assertAlmostEqual(-np.sum(expected_losses), self.evaluate(loss), 3)
+ @test_util.run_deprecated_v1
def testNonZeroLossWithSampleSpecificWeightsMostZeroWithPlaceholder(self):
weights = np.array([0, 0, 0, 0, 0, 2]).reshape((2, 3))
expected_losses = np.multiply(self._expected_losses, weights)
@@ -805,6 +845,7 @@ class HingeLossTest(test.TestCase):
with self.assertRaises(ValueError):
_ = losses.hinge_loss(labels, logits).eval()
+ @test_util.run_deprecated_v1
def testAllOutsideMargin(self):
with self.cached_session():
logits = constant_op.constant([1.2, -1.4, -1.0, 2.1])
@@ -812,6 +853,7 @@ class HingeLossTest(test.TestCase):
loss = losses.hinge_loss(labels, logits)
self.assertAllClose(loss.eval(), 0.0, atol=1e-3)
+ @test_util.run_deprecated_v1
def testSomeInsideMargin(self):
with self.cached_session():
logits = constant_op.constant([[-0.7], [-1.4], [1.4], [0.6]])
@@ -821,6 +863,7 @@ class HingeLossTest(test.TestCase):
# the margin so they incur some (small) loss.
self.assertAllClose(loss.eval(), 0.175, atol=1e-3)
+ @test_util.run_deprecated_v1
def testSomeMisclassified(self):
with self.cached_session():
logits = constant_op.constant([[[1.2], [0.4], [-1.0], [-1.1]]])
@@ -840,6 +883,7 @@ class HuberLossTest(test.TestCase):
with self.assertRaises(ValueError):
_ = losses.huber_loss(labels, predictions).eval()
+ @test_util.run_deprecated_v1
def testAllQuadratic(self):
with self.cached_session():
predictions = constant_op.constant([1.5, -1.4, -1.0, 0.0])
@@ -848,6 +892,7 @@ class HuberLossTest(test.TestCase):
self.assertAllClose(loss.eval(),
0.5 * (0.25 + 0.16 + 1.0 + 0.25) / 4., atol=1e-5)
+ @test_util.run_deprecated_v1
def testAllLinear(self):
with self.cached_session():
predictions = constant_op.constant([1.5, -1.4, -1.0, 0.0])
@@ -856,6 +901,7 @@ class HuberLossTest(test.TestCase):
self.assertAllClose(loss.eval(),
(1.5 + 2.4 + 1.0 + 1.5) / 4. - 0.5, atol=1e-5)
+ @test_util.run_deprecated_v1
def testMixedQuadraticLinear(self):
with self.cached_session():
predictions = constant_op.constant([[1.5, -1.4, -1.0, 0.0],
@@ -901,6 +947,7 @@ class MeanSquaredErrorTest(test.TestCase):
losses.mean_squared_error(
self._predictions, self._predictions, weights=None)
+ @test_util.run_deprecated_v1
def testScalar(self):
with self.cached_session():
self.assertEqual(
@@ -908,22 +955,26 @@ class MeanSquaredErrorTest(test.TestCase):
losses.mean_squared_error(predictions=constant_op.constant(0),
labels=constant_op.constant(0)).eval())
+ @test_util.run_deprecated_v1
def testAllCorrectNoLossWeight(self):
loss = losses.mean_squared_error(self._predictions, self._predictions)
with self.cached_session():
self.assertAlmostEqual(0.0, self.evaluate(loss), 3)
+ @test_util.run_deprecated_v1
def testNonZeroLoss(self):
loss = losses.mean_squared_error(self._labels, self._predictions)
with self.cached_session():
self.assertAlmostEqual(49.5, self.evaluate(loss), 3)
+ @test_util.run_deprecated_v1
def testNonZeroLossWithPythonScalarWeight(self):
weights = 2.3
loss = losses.mean_squared_error(self._labels, self._predictions, weights)
with self.cached_session():
self.assertAlmostEqual(49.5 * weights, self.evaluate(loss), 3)
+ @test_util.run_deprecated_v1
def testNonZeroLossWithScalarTensorWeight(self):
weights = 2.3
loss = losses.mean_squared_error(self._labels, self._predictions,
@@ -1017,10 +1068,12 @@ class MeanPairwiseSquaredErrorTest(test.TestCase):
self.assertAlmostEqual(
expected_loss, dynamic_inputs_op.eval(feed_dict=feed_dict), places=3)
+ @test_util.run_deprecated_v1
def testAllCorrectNoLossWeight(self):
self._test_valid_weights(
self._labels, self._labels, expected_loss=0.0)
+ @test_util.run_deprecated_v1
def testNonZeroLoss(self):
self._test_valid_weights(
self._labels, self._predictions,
@@ -1051,6 +1104,7 @@ class MeanPairwiseSquaredErrorTest(test.TestCase):
np_grad = self.evaluate(grad)
self.assertFalse(np.isnan(np_grad).any())
+ @test_util.run_deprecated_v1
def testNonZeroLossWithPythonScalarWeight(self):
weight = 2.3
self._test_valid_weights(
@@ -1058,6 +1112,7 @@ class MeanPairwiseSquaredErrorTest(test.TestCase):
expected_loss=weight * np.sum(self._expected_losses),
weights=weight)
+ @test_util.run_deprecated_v1
def testNonZeroLossWithScalarTensorWeight(self):
weights = 2.3
loss = losses.mean_pairwise_squared_error(
@@ -1068,10 +1123,12 @@ class MeanPairwiseSquaredErrorTest(test.TestCase):
self.assertAlmostEqual(weights * np.sum(self._expected_losses),
self.evaluate(loss), 3)
+ @test_util.run_deprecated_v1
def testNonZeroLossWithScalarZeroWeight(self):
self._test_valid_weights(
self._labels, self._predictions, expected_loss=0.0, weights=0.0)
+ @test_util.run_deprecated_v1
def test3d(self):
labels = np.array([
[[1, 9, 2], [12, 11, 10], [9, 8, 7]],
@@ -1083,6 +1140,7 @@ class MeanPairwiseSquaredErrorTest(test.TestCase):
])
self._test_valid_weights(labels, predictions, expected_loss=137.5)
+ @test_util.run_deprecated_v1
def test3dWeightedScalar(self):
labels = np.array([
[[1, 9, 2], [12, 11, 10], [9, 8, 7]],
@@ -1121,6 +1179,7 @@ class MeanPairwiseSquaredErrorTest(test.TestCase):
weights_placeholder: weights,
})
+ @test_util.run_deprecated_v1
def testInvalid3dWeighted2x0(self):
labels = np.array([
[[1, 9, 2], [12, 11, 10], [9, 8, 7]],
@@ -1133,6 +1192,7 @@ class MeanPairwiseSquaredErrorTest(test.TestCase):
self._test_invalid_weights(
labels, predictions, weights=np.asarray((1.2, 3.4)))
+ @test_util.run_deprecated_v1
def test3dWeighted2x3x3(self):
labels = np.array([
[[1, 9, 2], [12, 11, 10], [9, 8, 7]],
@@ -1149,6 +1209,7 @@ class MeanPairwiseSquaredErrorTest(test.TestCase):
expected_loss=9 * 137.5,
weights=np.ones((2, 3, 3)))
+ @test_util.run_deprecated_v1
def testLossWithAllZeroBatchSpecificWeights(self):
self._test_valid_weights(
self._labels, self._predictions, expected_loss=0.0,
@@ -1268,6 +1329,7 @@ class CosineDistanceLossTest(test.TestCase):
with self.cached_session():
self.assertEqual(3.0 / 4.0, self.evaluate(loss))
+ @test_util.run_deprecated_v1
def testMeasurementSpecificWeightsWithPlaceholderWithShape(self):
tf_predictions = array_ops.placeholder(
dtypes.float32, shape=self._labels.shape)
diff --git a/tensorflow/python/kernel_tests/lrn_op_test.py b/tensorflow/python/kernel_tests/lrn_op_test.py
index 7ebeb91d90e..fbe628c3944 100644
--- a/tensorflow/python/kernel_tests/lrn_op_test.py
+++ b/tensorflow/python/kernel_tests/lrn_op_test.py
@@ -24,6 +24,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import gradients_impl
@@ -92,6 +93,7 @@ class LRNOpTest(test.TestCase):
self.assertTrue(err < 1e-2)
self.assertShapeEqual(expected, lrn_t)
+ @test_util.run_deprecated_v1
def testCompute(self):
for _ in range(2):
self._RunAndVerify(dtypes.float32)
@@ -99,6 +101,7 @@ class LRNOpTest(test.TestCase):
if not test.is_gpu_available():
self._RunAndVerify(dtypes.float16)
+ @test_util.run_deprecated_v1
def testGradientsZeroInput(self):
with self.session(use_gpu=True):
shape = [4, 4, 4, 4]
@@ -147,6 +150,7 @@ class LRNOpTest(test.TestCase):
else:
self.assertLess(err, 1.0)
+ @test_util.run_deprecated_v1
def testGradients(self):
for _ in range(2):
self._RunAndVerifyGradients(dtypes.float32)
diff --git a/tensorflow/python/kernel_tests/manip_ops_test.py b/tensorflow/python/kernel_tests/manip_ops_test.py
index f71857a3cba..5700db4b950 100644
--- a/tensorflow/python/kernel_tests/manip_ops_test.py
+++ b/tensorflow/python/kernel_tests/manip_ops_test.py
@@ -62,6 +62,7 @@ class RollTest(test_util.TensorFlowTestCase):
if np_input.dtype == np.float32:
self._testGradient(np_input, shift, axis)
+ @test_util.run_deprecated_v1
def testIntTypes(self):
for t in [np.int32, np.int64]:
self._testAll(np.random.randint(-100, 100, (5)).astype(t), 3, 0)
@@ -73,6 +74,7 @@ class RollTest(test_util.TensorFlowTestCase):
np.random.randint(-100, 100, (4, 2, 1, 3)).astype(t), [0, 1, -2],
[1, 2, 3])
+ @test_util.run_deprecated_v1
def testFloatTypes(self):
for t in [np.float32, np.float64]:
self._testAll(np.random.rand(5).astype(t), 2, 0)
@@ -80,6 +82,7 @@ class RollTest(test_util.TensorFlowTestCase):
self._testAll(np.random.rand(3, 4).astype(t), [1, 2], [1, 0])
self._testAll(np.random.rand(1, 3, 4).astype(t), [1, 0, -3], [0, 1, 2])
+ @test_util.run_deprecated_v1
def testComplexTypes(self):
for t in [np.complex64, np.complex128]:
x = np.random.rand(4, 4).astype(t)
@@ -90,6 +93,7 @@ class RollTest(test_util.TensorFlowTestCase):
x = np.random.rand(3, 2, 1, 1).astype(t)
self._testAll(x + 1j * x, [2, 1, 1, 0], [0, 3, 1, 2])
+ @test_util.run_deprecated_v1
def testNegativeAxis(self):
self._testAll(np.random.randint(-100, 100, (5)).astype(np.int32), 3, -1)
self._testAll(np.random.randint(-100, 100, (4, 4)).astype(np.int32), 3, -2)
@@ -100,12 +104,14 @@ class RollTest(test_util.TensorFlowTestCase):
manip_ops.roll(np.random.randint(-100, 100, (4, 4)).astype(np.int32),
3, -10).eval()
+ @test_util.run_deprecated_v1
def testInvalidInputShape(self):
# The input should be 1-D or higher, checked in shape function.
with self.assertRaisesRegexp(
ValueError, "Shape must be at least rank 1 but is rank 0"):
manip_ops.roll(7, 1, 0)
+ @test_util.run_deprecated_v1
def testRollInputMustVectorHigherRaises(self):
# The input should be 1-D or higher, checked in kernel.
tensor = array_ops.placeholder(dtype=dtypes.int32)
@@ -116,12 +122,14 @@ class RollTest(test_util.TensorFlowTestCase):
"input must be 1-D or higher"):
manip_ops.roll(tensor, shift, axis).eval(feed_dict={tensor: 7})
+ @test_util.run_deprecated_v1
def testInvalidAxisShape(self):
# The axis should be a scalar or 1-D, checked in shape function.
with self.assertRaisesRegexp(
ValueError, "Shape must be at most rank 1 but is rank 2"):
manip_ops.roll([[1, 2], [3, 4]], 1, [[0, 1]])
+ @test_util.run_deprecated_v1
def testRollAxisMustBeScalarOrVectorRaises(self):
# The axis should be a scalar or 1-D, checked in kernel.
tensor = [[1, 2], [3, 4]]
@@ -132,12 +140,14 @@ class RollTest(test_util.TensorFlowTestCase):
"axis must be a scalar or a 1-D vector"):
manip_ops.roll(tensor, shift, axis).eval(feed_dict={axis: [[0, 1]]})
+ @test_util.run_deprecated_v1
def testInvalidShiftShape(self):
# The shift should be a scalar or 1-D, checked in shape function.
with self.assertRaisesRegexp(
ValueError, "Shape must be at most rank 1 but is rank 2"):
manip_ops.roll([[1, 2], [3, 4]], [[0, 1]], 1)
+ @test_util.run_deprecated_v1
def testRollShiftMustBeScalarOrVectorRaises(self):
# The shift should be a scalar or 1-D, checked in kernel.
tensor = [[1, 2], [3, 4]]
@@ -148,11 +158,13 @@ class RollTest(test_util.TensorFlowTestCase):
"shift must be a scalar or a 1-D vector"):
manip_ops.roll(tensor, shift, axis).eval(feed_dict={shift: [[0, 1]]})
+ @test_util.run_deprecated_v1
def testInvalidShiftAndAxisNotEqualShape(self):
# The shift and axis must be same size, checked in shape function.
with self.assertRaisesRegexp(ValueError, "both shapes must be equal"):
manip_ops.roll([[1, 2], [3, 4]], [1], [0, 1])
+ @test_util.run_deprecated_v1
def testRollShiftAndAxisMustBeSameSizeRaises(self):
# The shift and axis must be same size, checked in kernel.
tensor = [[1, 2], [3, 4]]
diff --git a/tensorflow/python/kernel_tests/map_stage_op_test.py b/tensorflow/python/kernel_tests/map_stage_op_test.py
index d503f3d7c9f..dd16fad6904 100644
--- a/tensorflow/python/kernel_tests/map_stage_op_test.py
+++ b/tensorflow/python/kernel_tests/map_stage_op_test.py
@@ -19,6 +19,7 @@ from __future__ import print_function
from tensorflow.python.framework import errors
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import data_flow_ops
from tensorflow.python.ops import math_ops
@@ -29,6 +30,7 @@ TIMEOUT = 1
class MapStageTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testSimple(self):
with ops.Graph().as_default() as G:
with ops.device('/cpu:0'):
@@ -50,6 +52,7 @@ class MapStageTest(test.TestCase):
_, yval = sess.run([stage, y], feed_dict={x: i, pi: i + 1, gi: i})
self.assertAllClose(4 * (i - 1) * (i - 1) * 128, yval, rtol=1e-4)
+ @test_util.run_deprecated_v1
def testMultiple(self):
with ops.Graph().as_default() as G:
with ops.device('/cpu:0'):
@@ -72,6 +75,7 @@ class MapStageTest(test.TestCase):
self.assertAllClose(
4 * (i - 1) * (i - 1) * (i - 1) * 128, yval, rtol=1e-4)
+ @test_util.run_deprecated_v1
def testDictionary(self):
with ops.Graph().as_default() as G:
with ops.device('/cpu:0'):
@@ -121,6 +125,7 @@ class MapStageTest(test.TestCase):
G.finalize()
+ @test_util.run_deprecated_v1
def testPeek(self):
with ops.Graph().as_default() as G:
with ops.device('/cpu:0'):
@@ -150,6 +155,7 @@ class MapStageTest(test.TestCase):
self.assertTrue(sess.run(size) == 10)
+ @test_util.run_deprecated_v1
def testSizeAndClear(self):
with ops.Graph().as_default() as G:
with ops.device('/cpu:0'):
@@ -176,6 +182,7 @@ class MapStageTest(test.TestCase):
sess.run(clear)
self.assertEqual(sess.run(size), 0)
+ @test_util.run_deprecated_v1
def testCapacity(self):
capacity = 3
@@ -239,6 +246,7 @@ class MapStageTest(test.TestCase):
self.assertTrue(sess.run(size) == 0)
+ @test_util.run_deprecated_v1
def testMemoryLimit(self):
memory_limit = 512 * 1024 # 512K
chunk = 200 * 1024 # 256K
@@ -303,6 +311,7 @@ class MapStageTest(test.TestCase):
self.assertTrue(sess.run(size) == 0)
+ @test_util.run_deprecated_v1
def testOrdering(self):
import six
import random
@@ -341,6 +350,7 @@ class MapStageTest(test.TestCase):
self.assertTrue(sess.run(size) == 0)
+ @test_util.run_deprecated_v1
def testPartialDictInsert(self):
with ops.Graph().as_default() as G:
with ops.device('/cpu:0'):
@@ -400,6 +410,7 @@ class MapStageTest(test.TestCase):
'v': 3
}])
+ @test_util.run_deprecated_v1
def testPartialIndexInsert(self):
with ops.Graph().as_default() as G:
with ops.device('/cpu:0'):
@@ -443,6 +454,7 @@ class MapStageTest(test.TestCase):
# We can now obtain tuple associated with key 1
self.assertTrue(sess.run([key, ret], feed_dict={gi: 1}) == [1, [1, 3, 2]])
+ @test_util.run_deprecated_v1
def testPartialDictGetsAndPeeks(self):
with ops.Graph().as_default() as G:
with ops.device('/cpu:0'):
@@ -540,6 +552,7 @@ class MapStageTest(test.TestCase):
# Nothing is left
self.assertTrue(sess.run([size, isize]) == [0, 0])
+ @test_util.run_deprecated_v1
def testPartialIndexGets(self):
with ops.Graph().as_default() as G:
with ops.device('/cpu:0'):
diff --git a/tensorflow/python/kernel_tests/matmul_op_test.py b/tensorflow/python/kernel_tests/matmul_op_test.py
index 6167e01864d..983f463f5e3 100644
--- a/tensorflow/python/kernel_tests/matmul_op_test.py
+++ b/tensorflow/python/kernel_tests/matmul_op_test.py
@@ -194,6 +194,7 @@ except AttributeError:
class MatMulInfixOperatorTest(test_lib.TestCase):
+ @test_util.run_deprecated_v1
def testMismatchedShape(self):
with self.assertRaisesWithPredicateMatch(ValueError,
lambda e: "Shape must" in str(e)):
@@ -201,6 +202,7 @@ class MatMulInfixOperatorTest(test_lib.TestCase):
ops.convert_to_tensor([10.0, 20.0, 30.0]),
ops.convert_to_tensor([[40.0, 50.0], [60.0, 70.0]]))
+ @test_util.run_deprecated_v1
def testMismatchedDimensions(self):
with self.assertRaisesWithPredicateMatch(
ValueError, lambda e: "Dimensions must" in str(e)):
@@ -208,12 +210,14 @@ class MatMulInfixOperatorTest(test_lib.TestCase):
ops.convert_to_tensor([[10.0, 20.0, 30.0]]),
ops.convert_to_tensor([[40.0, 50.0], [60.0, 70.0]]))
+ @test_util.run_deprecated_v1
def testInfixMatmulIsTfMatmul(self):
a = ops.convert_to_tensor([[10.0, 20.0, 30.0]])
b = ops.convert_to_tensor([[40.0, 50.0], [60.0, 70.0], [80.0, 90.0]])
c = infix_matmul(a, b)
self.assertEqual(c.op.type, "MatMul")
+ @test_util.run_deprecated_v1
def testInfixMatmulDoesDotProduct(self):
a = ops.convert_to_tensor([[10.0, 20.0, 30.0]])
b = ops.convert_to_tensor([[40.0, 50.0], [60.0, 70.0], [80.0, 90.0]])
diff --git a/tensorflow/python/kernel_tests/matrix_exponential_op_test.py b/tensorflow/python/kernel_tests/matrix_exponential_op_test.py
index 83f4216e4d0..372b6dc17f4 100644
--- a/tensorflow/python/kernel_tests/matrix_exponential_op_test.py
+++ b/tensorflow/python/kernel_tests/matrix_exponential_op_test.py
@@ -122,12 +122,14 @@ class ExponentialOpTest(test.TestCase):
# Complex batch
self._verifyExponentialComplex(self._makeBatch(matrix1, matrix2))
+ @test_util.run_deprecated_v1
def testNonSquareMatrix(self):
# When the exponential of a non-square matrix is attempted we should return
# an error
with self.assertRaises(ValueError):
linalg_impl.matrix_exponential(np.array([[1., 2., 3.], [3., 4., 5.]]))
+ @test_util.run_deprecated_v1
def testWrongDimensions(self):
# The input to the exponential should be at least a 2-dimensional tensor.
tensor3 = constant_op.constant([1., 2.])
@@ -138,6 +140,7 @@ class ExponentialOpTest(test.TestCase):
self._verifyExponentialReal(np.empty([0, 2, 2]))
self._verifyExponentialReal(np.empty([2, 0, 0]))
+ @test_util.run_deprecated_v1
def testDynamic(self):
with self.session(use_gpu=True) as sess:
inp = array_ops.placeholder(ops.dtypes.float32)
@@ -145,6 +148,7 @@ class ExponentialOpTest(test.TestCase):
matrix = np.array([[1., 2.], [3., 4.]])
sess.run(expm, feed_dict={inp: matrix})
+ @test_util.run_deprecated_v1
def testConcurrentExecutesWithoutError(self):
with self.session(use_gpu=True) as sess:
matrix1 = random_ops.random_normal([5, 5], seed=42)
diff --git a/tensorflow/python/kernel_tests/matrix_solve_ls_op_test.py b/tensorflow/python/kernel_tests/matrix_solve_ls_op_test.py
index 13a7df7f95d..a6f5da9d3d7 100644
--- a/tensorflow/python/kernel_tests/matrix_solve_ls_op_test.py
+++ b/tensorflow/python/kernel_tests/matrix_solve_ls_op_test.py
@@ -24,6 +24,7 @@ from tensorflow.python.client import session
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import control_flow_ops
from tensorflow.python.ops import linalg_ops
@@ -133,6 +134,7 @@ class MatrixSolveLsOpTest(test_lib.TestCase):
self.assertEqual(np_ans.shape, tf_ans_val.shape)
self.assertAllClose(np_ans, tf_ans_val, atol=2 * tol, rtol=2 * tol)
+ @test_util.run_deprecated_v1
def testWrongDimensions(self):
# The matrix and right-hand sides should have the same number of rows.
with self.session(use_gpu=True):
@@ -141,6 +143,7 @@ class MatrixSolveLsOpTest(test_lib.TestCase):
with self.assertRaises(ValueError):
linalg_ops.matrix_solve_ls(matrix, rhs)
+ @test_util.run_deprecated_v1
def testEmpty(self):
full = np.array([[1., 2.], [3., 4.], [5., 6.]])
empty0 = np.empty([3, 0])
@@ -156,6 +159,7 @@ class MatrixSolveLsOpTest(test_lib.TestCase):
tf_ans = linalg_ops.matrix_solve_ls(empty1, empty1, fast=fast).eval()
self.assertEqual(tf_ans.shape, (2, 2))
+ @test_util.run_deprecated_v1
def testBatchResultSize(self):
# 3x3x3 matrices, 3x3x1 right-hand sides.
matrix = np.array([1., 2., 3., 4., 5., 6., 7., 8., 9.] * 3).reshape(3, 3, 3)
diff --git a/tensorflow/python/kernel_tests/matrix_solve_op_test.py b/tensorflow/python/kernel_tests/matrix_solve_op_test.py
index 80badee8962..db7c4802f69 100644
--- a/tensorflow/python/kernel_tests/matrix_solve_op_test.py
+++ b/tensorflow/python/kernel_tests/matrix_solve_op_test.py
@@ -24,6 +24,7 @@ from tensorflow.python.client import session
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import control_flow_ops
from tensorflow.python.ops import linalg_ops
@@ -75,6 +76,7 @@ class MatrixSolveOpTest(test.TestCase):
[m, n]))
return matrix
+ @test_util.run_deprecated_v1
def testSolve(self):
for n in 1, 2, 4, 9:
matrix = self._generateMatrix(n, n)
@@ -82,6 +84,7 @@ class MatrixSolveOpTest(test.TestCase):
rhs = self._generateMatrix(n, nrhs)
self._verifySolve(matrix, rhs)
+ @test_util.run_deprecated_v1
def testSolveBatch(self):
for n in 2, 5:
matrix = self._generateMatrix(n, n)
@@ -90,6 +93,7 @@ class MatrixSolveOpTest(test.TestCase):
for batch_dims in [[2], [2, 2], [7, 4]]:
self._verifySolve(matrix, rhs, batch_dims=batch_dims)
+ @test_util.run_deprecated_v1
def testNonSquareMatrix(self):
# When the solve of a non-square matrix is attempted we should return
# an error
@@ -98,6 +102,7 @@ class MatrixSolveOpTest(test.TestCase):
matrix = constant_op.constant([[1., 2., 3.], [3., 4., 5.]])
linalg_ops.matrix_solve(matrix, matrix)
+ @test_util.run_deprecated_v1
def testWrongDimensions(self):
# The matrix and right-hand sides should have the same number of rows.
with self.session(use_gpu=True):
@@ -115,6 +120,7 @@ class MatrixSolveOpTest(test.TestCase):
[0., -1., 1.]])
linalg_ops.matrix_solve(matrix, matrix).eval()
+ @test_util.run_deprecated_v1
def testConcurrent(self):
with self.session(use_gpu=True) as sess:
all_ops = []
diff --git a/tensorflow/python/kernel_tests/matrix_triangular_solve_op_test.py b/tensorflow/python/kernel_tests/matrix_triangular_solve_op_test.py
index 317b8f8716e..dde83f12f3c 100644
--- a/tensorflow/python/kernel_tests/matrix_triangular_solve_op_test.py
+++ b/tensorflow/python/kernel_tests/matrix_triangular_solve_op_test.py
@@ -21,6 +21,7 @@ from __future__ import print_function
import numpy as np
from tensorflow.python.framework import constant_op
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import linalg_ops
from tensorflow.python.platform import test
@@ -93,6 +94,7 @@ class MatrixTriangularSolveOpTest(test.TestCase):
self.assertEqual(np_ans.shape, tf_val.shape)
self.assertAllClose(np_ans, tf_val)
+ @test_util.run_deprecated_v1
def testSolve(self):
# 1x1 matrix, single rhs.
matrix = np.array([[0.1]])
@@ -106,6 +108,7 @@ class MatrixTriangularSolveOpTest(test.TestCase):
rhs1 = np.array([[1., 0., 1.], [0., 1., 1.]])
self._verifySolveAllWaysReal(matrix, rhs1)
+ @test_util.run_deprecated_v1
def testSolveComplex(self):
# 1x1 matrix, single rhs.
matrix = np.array([[0.1 + 1j * 0.1]])
@@ -122,6 +125,7 @@ class MatrixTriangularSolveOpTest(test.TestCase):
rhs1 += 1j * rhs1
self._verifySolveAllWaysComplex(matrix, rhs1)
+ @test_util.run_deprecated_v1
def testSolveBatch(self):
matrix = np.array([[1., 2.], [3., 4.]])
rhs = np.array([[1., 0., 1.], [0., 1., 1.]])
@@ -130,6 +134,7 @@ class MatrixTriangularSolveOpTest(test.TestCase):
# Batch of 3x2x2x2 matrices, 3x2x2x3 right-hand sides.
self._verifySolveAllWaysReal(matrix, rhs, batch_dims=[3, 2])
+ @test_util.run_deprecated_v1
def testSolveBatchComplex(self):
matrix = np.array([[1., 2.], [3., 4.]]).astype(np.complex64)
matrix += 1j * matrix
@@ -140,6 +145,7 @@ class MatrixTriangularSolveOpTest(test.TestCase):
# Batch of 3x2x2x2 matrices, 3x2x2x3 right-hand sides.
self._verifySolveAllWaysComplex(matrix, rhs, batch_dims=[3, 2])
+ @test_util.run_deprecated_v1
def testNonSquareMatrix(self):
# A non-square matrix should cause an error.
matrix = np.array([[1., 2., 3.], [3., 4., 5.]])
@@ -149,6 +155,7 @@ class MatrixTriangularSolveOpTest(test.TestCase):
with self.assertRaises(ValueError):
self._verifySolve(matrix, matrix, batch_dims=[2, 3])
+ @test_util.run_deprecated_v1
def testWrongDimensions(self):
# The matrix should have the same number of rows as the
# right-hand sides.
diff --git a/tensorflow/python/kernel_tests/metrics_test.py b/tensorflow/python/kernel_tests/metrics_test.py
index eb5f99582ca..64dd5914552 100644
--- a/tensorflow/python/kernel_tests/metrics_test.py
+++ b/tensorflow/python/kernel_tests/metrics_test.py
@@ -29,6 +29,7 @@ from tensorflow.python.framework import dtypes as dtypes_lib
from tensorflow.python.framework import errors_impl
from tensorflow.python.framework import ops
from tensorflow.python.framework import sparse_tensor
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import data_flow_ops
from tensorflow.python.ops import math_ops
@@ -175,22 +176,26 @@ class MeanTest(test.TestCase):
def setUp(self):
ops.reset_default_graph()
+ @test_util.run_deprecated_v1
def testVars(self):
metrics.mean(array_ops.ones([4, 3]))
_assert_metric_variables(self, ('mean/count:0', 'mean/total:0'))
+ @test_util.run_deprecated_v1
def testMetricsCollection(self):
my_collection_name = '__metrics__'
mean, _ = metrics.mean(
array_ops.ones([4, 3]), metrics_collections=[my_collection_name])
self.assertListEqual(ops.get_collection(my_collection_name), [mean])
+ @test_util.run_deprecated_v1
def testUpdatesCollection(self):
my_collection_name = '__updates__'
_, update_op = metrics.mean(
array_ops.ones([4, 3]), updates_collections=[my_collection_name])
self.assertListEqual(ops.get_collection(my_collection_name), [update_op])
+ @test_util.run_deprecated_v1
def testBasic(self):
with self.cached_session() as sess:
values_queue = data_flow_ops.FIFOQueue(
@@ -208,6 +213,7 @@ class MeanTest(test.TestCase):
self.evaluate(update_op)
self.assertAlmostEqual(1.65, self.evaluate(mean), 5)
+ @test_util.run_deprecated_v1
def testUpdateOpsReturnsCurrentValue(self):
with self.cached_session() as sess:
values_queue = data_flow_ops.FIFOQueue(
@@ -229,6 +235,7 @@ class MeanTest(test.TestCase):
self.assertAlmostEqual(1.65, self.evaluate(mean), 5)
+ @test_util.run_deprecated_v1
def testUnweighted(self):
values = _test_values((3, 2, 4, 1))
mean_results = (
@@ -271,37 +278,44 @@ class MeanTest(test.TestCase):
self.assertAlmostEqual(expected, update_op.eval(), places=5)
self.assertAlmostEqual(expected, mean.eval(), places=5)
+ @test_util.run_deprecated_v1
def test1x1x1Weighted(self):
self._test_3d_weighted(
_test_values((3, 2, 4)),
weights=np.asarray((5,)).reshape((1, 1, 1)))
+ @test_util.run_deprecated_v1
def test1x1xNWeighted(self):
self._test_3d_weighted(
_test_values((3, 2, 4)),
weights=np.asarray((5, 7, 11, 3)).reshape((1, 1, 4)))
+ @test_util.run_deprecated_v1
def test1xNx1Weighted(self):
self._test_3d_weighted(
_test_values((3, 2, 4)),
weights=np.asarray((5, 11)).reshape((1, 2, 1)))
+ @test_util.run_deprecated_v1
def test1xNxNWeighted(self):
self._test_3d_weighted(
_test_values((3, 2, 4)),
weights=np.asarray((5, 7, 11, 3, 2, 13, 7, 5)).reshape((1, 2, 4)))
+ @test_util.run_deprecated_v1
def testNx1x1Weighted(self):
self._test_3d_weighted(
_test_values((3, 2, 4)),
weights=np.asarray((5, 7, 11)).reshape((3, 1, 1)))
+ @test_util.run_deprecated_v1
def testNx1xNWeighted(self):
self._test_3d_weighted(
_test_values((3, 2, 4)),
weights=np.asarray((
5, 7, 11, 3, 2, 12, 7, 5, 2, 17, 11, 3)).reshape((3, 1, 4)))
+ @test_util.run_deprecated_v1
def testNxNxNWeighted(self):
self._test_3d_weighted(
_test_values((3, 2, 4)),
@@ -309,6 +323,7 @@ class MeanTest(test.TestCase):
5, 7, 11, 3, 2, 12, 7, 5, 2, 17, 11, 3,
2, 17, 11, 3, 5, 7, 11, 3, 2, 12, 7, 5)).reshape((3, 2, 4)))
+ @test_util.run_deprecated_v1
def testInvalidWeights(self):
values_placeholder = array_ops.placeholder(dtype=dtypes_lib.float32)
values = _test_values((3, 2, 4, 1))
@@ -341,23 +356,27 @@ class MeanTensorTest(test.TestCase):
def setUp(self):
ops.reset_default_graph()
+ @test_util.run_deprecated_v1
def testVars(self):
metrics.mean_tensor(array_ops.ones([4, 3]))
_assert_metric_variables(self,
('mean/total_tensor:0', 'mean/count_tensor:0'))
+ @test_util.run_deprecated_v1
def testMetricsCollection(self):
my_collection_name = '__metrics__'
mean, _ = metrics.mean_tensor(
array_ops.ones([4, 3]), metrics_collections=[my_collection_name])
self.assertListEqual(ops.get_collection(my_collection_name), [mean])
+ @test_util.run_deprecated_v1
def testUpdatesCollection(self):
my_collection_name = '__updates__'
_, update_op = metrics.mean_tensor(
array_ops.ones([4, 3]), updates_collections=[my_collection_name])
self.assertListEqual(ops.get_collection(my_collection_name), [update_op])
+ @test_util.run_deprecated_v1
def testBasic(self):
with self.cached_session() as sess:
values_queue = data_flow_ops.FIFOQueue(
@@ -375,6 +394,7 @@ class MeanTensorTest(test.TestCase):
self.evaluate(update_op)
self.assertAllClose([[-0.9 / 4., 3.525]], self.evaluate(mean))
+ @test_util.run_deprecated_v1
def testMultiDimensional(self):
with self.cached_session() as sess:
values_queue = data_flow_ops.FIFOQueue(
@@ -397,6 +417,7 @@ class MeanTensorTest(test.TestCase):
self.assertAllClose([[[1, 2], [1, 2]], [[2, 3], [5, 6]]],
self.evaluate(mean))
+ @test_util.run_deprecated_v1
def testUpdateOpsReturnsCurrentValue(self):
with self.cached_session() as sess:
values_queue = data_flow_ops.FIFOQueue(
@@ -418,6 +439,7 @@ class MeanTensorTest(test.TestCase):
self.assertAllClose([[-0.9 / 4., 3.525]], self.evaluate(mean), 5)
+ @test_util.run_deprecated_v1
def testBinaryWeighted1d(self):
with self.cached_session() as sess:
# Create the queue that populates the values.
@@ -445,6 +467,7 @@ class MeanTensorTest(test.TestCase):
self.evaluate(update_op)
self.assertAllClose([[3.25, 0.5]], self.evaluate(mean), 5)
+ @test_util.run_deprecated_v1
def testWeighted1d(self):
with self.cached_session() as sess:
# Create the queue that populates the values.
@@ -472,6 +495,7 @@ class MeanTensorTest(test.TestCase):
self.evaluate(update_op)
self.assertAllClose([[0.8, 3.52]], self.evaluate(mean), 5)
+ @test_util.run_deprecated_v1
def testWeighted2d_1(self):
with self.cached_session() as sess:
# Create the queue that populates the values.
@@ -499,6 +523,7 @@ class MeanTensorTest(test.TestCase):
self.evaluate(update_op)
self.assertAllClose([[-2.1, 0.5]], self.evaluate(mean), 5)
+ @test_util.run_deprecated_v1
def testWeighted2d_2(self):
with self.cached_session() as sess:
# Create the queue that populates the values.
@@ -532,6 +557,7 @@ class AccuracyTest(test.TestCase):
def setUp(self):
ops.reset_default_graph()
+ @test_util.run_deprecated_v1
def testVars(self):
metrics.accuracy(
predictions=array_ops.ones((10, 1)),
@@ -540,6 +566,7 @@ class AccuracyTest(test.TestCase):
_assert_metric_variables(self,
('my_accuracy/count:0', 'my_accuracy/total:0'))
+ @test_util.run_deprecated_v1
def testMetricsCollection(self):
my_collection_name = '__metrics__'
mean, _ = metrics.accuracy(
@@ -548,6 +575,7 @@ class AccuracyTest(test.TestCase):
metrics_collections=[my_collection_name])
self.assertListEqual(ops.get_collection(my_collection_name), [mean])
+ @test_util.run_deprecated_v1
def testUpdatesCollection(self):
my_collection_name = '__updates__'
_, update_op = metrics.accuracy(
@@ -556,12 +584,14 @@ class AccuracyTest(test.TestCase):
updates_collections=[my_collection_name])
self.assertListEqual(ops.get_collection(my_collection_name), [update_op])
+ @test_util.run_deprecated_v1
def testPredictionsAndLabelsOfDifferentSizeRaisesValueError(self):
predictions = array_ops.ones((10, 3))
labels = array_ops.ones((10, 4))
with self.assertRaises(ValueError):
metrics.accuracy(labels, predictions)
+ @test_util.run_deprecated_v1
def testPredictionsAndWeightsOfDifferentSizeRaisesValueError(self):
predictions = array_ops.ones((10, 3))
labels = array_ops.ones((10, 3))
@@ -569,6 +599,7 @@ class AccuracyTest(test.TestCase):
with self.assertRaises(ValueError):
metrics.accuracy(labels, predictions, weights)
+ @test_util.run_deprecated_v1
def testValueTensorIsIdempotent(self):
predictions = random_ops.random_uniform(
(10, 3), maxval=3, dtype=dtypes_lib.int64, seed=1)
@@ -588,6 +619,7 @@ class AccuracyTest(test.TestCase):
for _ in range(10):
self.assertEqual(initial_accuracy, accuracy.eval())
+ @test_util.run_deprecated_v1
def testMultipleUpdates(self):
with self.cached_session() as sess:
# Create the queue that populates the predictions.
@@ -616,6 +648,7 @@ class AccuracyTest(test.TestCase):
self.assertEqual(0.5, self.evaluate(update_op))
self.assertEqual(0.5, accuracy.eval())
+ @test_util.run_deprecated_v1
def testEffectivelyEquivalentSizes(self):
predictions = array_ops.ones((40, 1))
labels = array_ops.ones((40,))
@@ -626,6 +659,7 @@ class AccuracyTest(test.TestCase):
self.assertEqual(1.0, update_op.eval())
self.assertEqual(1.0, accuracy.eval())
+ @test_util.run_deprecated_v1
def testEffectivelyEquivalentSizesWithScalarWeight(self):
predictions = array_ops.ones((40, 1))
labels = array_ops.ones((40,))
@@ -636,6 +670,7 @@ class AccuracyTest(test.TestCase):
self.assertEqual(1.0, update_op.eval())
self.assertEqual(1.0, accuracy.eval())
+ @test_util.run_deprecated_v1
def testEffectivelyEquivalentSizesWithStaticShapedWeight(self):
predictions = ops.convert_to_tensor([1, 1, 1]) # shape 3,
labels = array_ops.expand_dims(ops.convert_to_tensor([1, 0, 0]),
@@ -653,6 +688,7 @@ class AccuracyTest(test.TestCase):
self.assertGreater(update_op.eval(), .95)
self.assertGreater(accuracy.eval(), .95)
+ @test_util.run_deprecated_v1
def testEffectivelyEquivalentSizesWithDynamicallyShapedWeight(self):
predictions = ops.convert_to_tensor([1, 1, 1]) # shape 3,
labels = array_ops.expand_dims(ops.convert_to_tensor([1, 0, 0]),
@@ -674,6 +710,7 @@ class AccuracyTest(test.TestCase):
self.assertGreater(update_op.eval(feed_dict=feed_dict), .95)
self.assertGreater(accuracy.eval(feed_dict=feed_dict), .95)
+ @test_util.run_deprecated_v1
def testMultipleUpdatesWithWeightedValues(self):
with self.cached_session() as sess:
# Create the queue that populates the predictions.
@@ -718,12 +755,14 @@ class PrecisionTest(test.TestCase):
np.random.seed(1)
ops.reset_default_graph()
+ @test_util.run_deprecated_v1
def testVars(self):
metrics.precision(
predictions=array_ops.ones((10, 1)), labels=array_ops.ones((10, 1)))
_assert_metric_variables(self, ('precision/false_positives/count:0',
'precision/true_positives/count:0'))
+ @test_util.run_deprecated_v1
def testMetricsCollection(self):
my_collection_name = '__metrics__'
mean, _ = metrics.precision(
@@ -732,6 +771,7 @@ class PrecisionTest(test.TestCase):
metrics_collections=[my_collection_name])
self.assertListEqual(ops.get_collection(my_collection_name), [mean])
+ @test_util.run_deprecated_v1
def testUpdatesCollection(self):
my_collection_name = '__updates__'
_, update_op = metrics.precision(
@@ -740,6 +780,7 @@ class PrecisionTest(test.TestCase):
updates_collections=[my_collection_name])
self.assertListEqual(ops.get_collection(my_collection_name), [update_op])
+ @test_util.run_deprecated_v1
def testValueTensorIsIdempotent(self):
predictions = random_ops.random_uniform(
(10, 3), maxval=1, dtype=dtypes_lib.int64, seed=1)
@@ -759,6 +800,7 @@ class PrecisionTest(test.TestCase):
for _ in range(10):
self.assertEqual(initial_precision, precision.eval())
+ @test_util.run_deprecated_v1
def testAllCorrect(self):
inputs = np.random.randint(0, 2, size=(100, 1))
@@ -771,6 +813,7 @@ class PrecisionTest(test.TestCase):
self.assertAlmostEqual(1, self.evaluate(update_op))
self.assertAlmostEqual(1, precision.eval())
+ @test_util.run_deprecated_v1
def testSomeCorrect_multipleInputDtypes(self):
for dtype in (dtypes_lib.bool, dtypes_lib.int32, dtypes_lib.float32):
predictions = math_ops.cast(
@@ -784,6 +827,7 @@ class PrecisionTest(test.TestCase):
self.assertAlmostEqual(0.5, update_op.eval())
self.assertAlmostEqual(0.5, precision.eval())
+ @test_util.run_deprecated_v1
def testWeighted1d(self):
predictions = constant_op.constant([[1, 0, 1, 0], [1, 0, 1, 0]])
labels = constant_op.constant([[0, 1, 1, 0], [1, 0, 0, 1]])
@@ -798,6 +842,7 @@ class PrecisionTest(test.TestCase):
self.assertAlmostEqual(expected_precision, update_op.eval())
self.assertAlmostEqual(expected_precision, precision.eval())
+ @test_util.run_deprecated_v1
def testWeightedScalar_placeholders(self):
predictions = array_ops.placeholder(dtype=dtypes_lib.float32)
labels = array_ops.placeholder(dtype=dtypes_lib.float32)
@@ -817,6 +862,7 @@ class PrecisionTest(test.TestCase):
self.assertAlmostEqual(
expected_precision, precision.eval(feed_dict=feed_dict))
+ @test_util.run_deprecated_v1
def testWeighted1d_placeholders(self):
predictions = array_ops.placeholder(dtype=dtypes_lib.float32)
labels = array_ops.placeholder(dtype=dtypes_lib.float32)
@@ -837,6 +883,7 @@ class PrecisionTest(test.TestCase):
self.assertAlmostEqual(
expected_precision, precision.eval(feed_dict=feed_dict))
+ @test_util.run_deprecated_v1
def testWeighted2d(self):
predictions = constant_op.constant([[1, 0, 1, 0], [1, 0, 1, 0]])
labels = constant_op.constant([[0, 1, 1, 0], [1, 0, 0, 1]])
@@ -853,6 +900,7 @@ class PrecisionTest(test.TestCase):
self.assertAlmostEqual(expected_precision, update_op.eval())
self.assertAlmostEqual(expected_precision, precision.eval())
+ @test_util.run_deprecated_v1
def testWeighted2d_placeholders(self):
predictions = array_ops.placeholder(dtype=dtypes_lib.float32)
labels = array_ops.placeholder(dtype=dtypes_lib.float32)
@@ -875,6 +923,7 @@ class PrecisionTest(test.TestCase):
self.assertAlmostEqual(
expected_precision, precision.eval(feed_dict=feed_dict))
+ @test_util.run_deprecated_v1
def testAllIncorrect(self):
inputs = np.random.randint(0, 2, size=(100, 1))
@@ -887,6 +936,7 @@ class PrecisionTest(test.TestCase):
self.evaluate(update_op)
self.assertAlmostEqual(0, precision.eval())
+ @test_util.run_deprecated_v1
def testZeroTrueAndFalsePositivesGivesZeroPrecision(self):
predictions = constant_op.constant([0, 0, 0, 0])
labels = constant_op.constant([0, 0, 0, 0])
@@ -904,6 +954,7 @@ class RecallTest(test.TestCase):
np.random.seed(1)
ops.reset_default_graph()
+ @test_util.run_deprecated_v1
def testVars(self):
metrics.recall(
predictions=array_ops.ones((10, 1)), labels=array_ops.ones((10, 1)))
@@ -911,6 +962,7 @@ class RecallTest(test.TestCase):
self,
('recall/false_negatives/count:0', 'recall/true_positives/count:0'))
+ @test_util.run_deprecated_v1
def testMetricsCollection(self):
my_collection_name = '__metrics__'
mean, _ = metrics.recall(
@@ -919,6 +971,7 @@ class RecallTest(test.TestCase):
metrics_collections=[my_collection_name])
self.assertListEqual(ops.get_collection(my_collection_name), [mean])
+ @test_util.run_deprecated_v1
def testUpdatesCollection(self):
my_collection_name = '__updates__'
_, update_op = metrics.recall(
@@ -927,6 +980,7 @@ class RecallTest(test.TestCase):
updates_collections=[my_collection_name])
self.assertListEqual(ops.get_collection(my_collection_name), [update_op])
+ @test_util.run_deprecated_v1
def testValueTensorIsIdempotent(self):
predictions = random_ops.random_uniform(
(10, 3), maxval=1, dtype=dtypes_lib.int64, seed=1)
@@ -946,6 +1000,7 @@ class RecallTest(test.TestCase):
for _ in range(10):
self.assertEqual(initial_recall, recall.eval())
+ @test_util.run_deprecated_v1
def testAllCorrect(self):
np_inputs = np.random.randint(0, 2, size=(100, 1))
@@ -958,6 +1013,7 @@ class RecallTest(test.TestCase):
self.evaluate(update_op)
self.assertEqual(1, recall.eval())
+ @test_util.run_deprecated_v1
def testSomeCorrect_multipleInputDtypes(self):
for dtype in (dtypes_lib.bool, dtypes_lib.int32, dtypes_lib.float32):
predictions = math_ops.cast(
@@ -971,6 +1027,7 @@ class RecallTest(test.TestCase):
self.assertAlmostEqual(0.5, update_op.eval())
self.assertAlmostEqual(0.5, recall.eval())
+ @test_util.run_deprecated_v1
def testWeighted1d(self):
predictions = constant_op.constant([[1, 0, 1, 0], [0, 1, 0, 1]])
labels = constant_op.constant([[0, 1, 1, 0], [1, 0, 0, 1]])
@@ -985,6 +1042,7 @@ class RecallTest(test.TestCase):
self.assertAlmostEqual(expected_precision, update_op.eval())
self.assertAlmostEqual(expected_precision, recall.eval())
+ @test_util.run_deprecated_v1
def testWeighted2d(self):
predictions = constant_op.constant([[1, 0, 1, 0], [0, 1, 0, 1]])
labels = constant_op.constant([[0, 1, 1, 0], [1, 0, 0, 1]])
@@ -999,6 +1057,7 @@ class RecallTest(test.TestCase):
self.assertAlmostEqual(expected_precision, update_op.eval())
self.assertAlmostEqual(expected_precision, recall.eval())
+ @test_util.run_deprecated_v1
def testAllIncorrect(self):
np_inputs = np.random.randint(0, 2, size=(100, 1))
@@ -1011,6 +1070,7 @@ class RecallTest(test.TestCase):
self.evaluate(update_op)
self.assertEqual(0, recall.eval())
+ @test_util.run_deprecated_v1
def testZeroTruePositivesAndFalseNegativesGivesZeroRecall(self):
predictions = array_ops.zeros((1, 4))
labels = array_ops.zeros((1, 4))
@@ -1028,6 +1088,7 @@ class AUCTest(test.TestCase):
np.random.seed(1)
ops.reset_default_graph()
+ @test_util.run_deprecated_v1
def testVars(self):
metrics.auc(predictions=array_ops.ones((10, 1)),
labels=array_ops.ones((10, 1)))
@@ -1035,6 +1096,7 @@ class AUCTest(test.TestCase):
('auc/true_positives:0', 'auc/false_negatives:0',
'auc/false_positives:0', 'auc/true_negatives:0'))
+ @test_util.run_deprecated_v1
def testMetricsCollection(self):
my_collection_name = '__metrics__'
mean, _ = metrics.auc(predictions=array_ops.ones((10, 1)),
@@ -1042,6 +1104,7 @@ class AUCTest(test.TestCase):
metrics_collections=[my_collection_name])
self.assertListEqual(ops.get_collection(my_collection_name), [mean])
+ @test_util.run_deprecated_v1
def testUpdatesCollection(self):
my_collection_name = '__updates__'
_, update_op = metrics.auc(predictions=array_ops.ones((10, 1)),
@@ -1049,6 +1112,7 @@ class AUCTest(test.TestCase):
updates_collections=[my_collection_name])
self.assertListEqual(ops.get_collection(my_collection_name), [update_op])
+ @test_util.run_deprecated_v1
def testValueTensorIsIdempotent(self):
predictions = random_ops.random_uniform(
(10, 3), maxval=1, dtype=dtypes_lib.float32, seed=1)
@@ -1068,6 +1132,7 @@ class AUCTest(test.TestCase):
for _ in range(10):
self.assertAlmostEqual(initial_auc, auc.eval(), 5)
+ @test_util.run_deprecated_v1
def testAllCorrect(self):
self.allCorrectAsExpected('ROC')
@@ -1084,6 +1149,7 @@ class AUCTest(test.TestCase):
self.assertEqual(1, auc.eval())
+ @test_util.run_deprecated_v1
def testSomeCorrect_multipleLabelDtypes(self):
with self.cached_session() as sess:
for label_dtype in (
@@ -1099,6 +1165,7 @@ class AUCTest(test.TestCase):
self.assertAlmostEqual(0.5, auc.eval())
+ @test_util.run_deprecated_v1
def testWeighted1d(self):
with self.cached_session() as sess:
predictions = constant_op.constant(
@@ -1112,6 +1179,7 @@ class AUCTest(test.TestCase):
self.assertAlmostEqual(0.5, auc.eval(), 5)
+ @test_util.run_deprecated_v1
def testWeighted2d(self):
with self.cached_session() as sess:
predictions = constant_op.constant(
@@ -1127,6 +1195,7 @@ class AUCTest(test.TestCase):
# Regarding the AUC-PR tests: note that the preferred method when
# calculating AUC-PR is summation_method='careful_interpolation'.
+ @test_util.run_deprecated_v1
def testCorrectAUCPRSpecialCase(self):
with self.cached_session() as sess:
predictions = constant_op.constant(
@@ -1141,6 +1210,7 @@ class AUCTest(test.TestCase):
self.assertAlmostEqual(expected, self.evaluate(update_op), delta=1e-3)
self.assertAlmostEqual(expected, auc.eval(), delta=1e-3)
+ @test_util.run_deprecated_v1
def testCorrectAnotherAUCPRSpecialCase(self):
with self.cached_session() as sess:
predictions = constant_op.constant(
@@ -1157,6 +1227,7 @@ class AUCTest(test.TestCase):
self.assertAlmostEqual(expected, self.evaluate(update_op), delta=1e-3)
self.assertAlmostEqual(expected, auc.eval(), delta=1e-3)
+ @test_util.run_deprecated_v1
def testThirdCorrectAUCPRSpecialCase(self):
with self.cached_session() as sess:
predictions = constant_op.constant(
@@ -1173,6 +1244,7 @@ class AUCTest(test.TestCase):
self.assertAlmostEqual(expected, self.evaluate(update_op), delta=1e-3)
self.assertAlmostEqual(expected, auc.eval(), delta=1e-3)
+ @test_util.run_deprecated_v1
def testIncorrectAUCPRSpecialCase(self):
with self.cached_session() as sess:
predictions = constant_op.constant(
@@ -1186,6 +1258,7 @@ class AUCTest(test.TestCase):
self.assertAlmostEqual(0.79166, auc.eval(), delta=1e-3)
+ @test_util.run_deprecated_v1
def testAnotherIncorrectAUCPRSpecialCase(self):
with self.cached_session() as sess:
predictions = constant_op.constant(
@@ -1201,6 +1274,7 @@ class AUCTest(test.TestCase):
self.assertAlmostEqual(0.610317, auc.eval(), delta=1e-3)
+ @test_util.run_deprecated_v1
def testThirdIncorrectAUCPRSpecialCase(self):
with self.cached_session() as sess:
predictions = constant_op.constant(
@@ -1216,6 +1290,7 @@ class AUCTest(test.TestCase):
self.assertAlmostEqual(0.90277, auc.eval(), delta=1e-3)
+ @test_util.run_deprecated_v1
def testAllIncorrect(self):
inputs = np.random.randint(0, 2, size=(100, 1))
@@ -1229,6 +1304,7 @@ class AUCTest(test.TestCase):
self.assertAlmostEqual(0, auc.eval())
+ @test_util.run_deprecated_v1
def testZeroTruePositivesAndFalseNegativesGivesOneAUC(self):
with self.cached_session() as sess:
predictions = array_ops.zeros([4], dtype=dtypes_lib.float32)
@@ -1240,6 +1316,7 @@ class AUCTest(test.TestCase):
self.assertAlmostEqual(1, auc.eval(), 6)
+ @test_util.run_deprecated_v1
def testRecallOneAndPrecisionOneGivesOnePRAUC(self):
with self.cached_session() as sess:
predictions = array_ops.ones([4], dtype=dtypes_lib.float32)
@@ -1278,6 +1355,7 @@ class AUCTest(test.TestCase):
tp = np.cumsum(sorted_weights * is_positive) / num_positives
return np.sum((sorted_weights * tp)[~is_positive]) / num_negatives
+ @test_util.run_deprecated_v1
def testWithMultipleUpdates(self):
num_samples = 1000
batch_size = 10
@@ -1334,6 +1412,7 @@ class SpecificityAtSensitivityTest(test.TestCase):
np.random.seed(1)
ops.reset_default_graph()
+ @test_util.run_deprecated_v1
def testVars(self):
metrics.specificity_at_sensitivity(
predictions=array_ops.ones((10, 1)),
@@ -1345,6 +1424,7 @@ class SpecificityAtSensitivityTest(test.TestCase):
'specificity_at_sensitivity/false_positives:0',
'specificity_at_sensitivity/true_negatives:0'))
+ @test_util.run_deprecated_v1
def testMetricsCollection(self):
my_collection_name = '__metrics__'
mean, _ = metrics.specificity_at_sensitivity(
@@ -1354,6 +1434,7 @@ class SpecificityAtSensitivityTest(test.TestCase):
metrics_collections=[my_collection_name])
self.assertListEqual(ops.get_collection(my_collection_name), [mean])
+ @test_util.run_deprecated_v1
def testUpdatesCollection(self):
my_collection_name = '__updates__'
_, update_op = metrics.specificity_at_sensitivity(
@@ -1363,6 +1444,7 @@ class SpecificityAtSensitivityTest(test.TestCase):
updates_collections=[my_collection_name])
self.assertListEqual(ops.get_collection(my_collection_name), [update_op])
+ @test_util.run_deprecated_v1
def testValueTensorIsIdempotent(self):
predictions = random_ops.random_uniform(
(10, 3), maxval=1, dtype=dtypes_lib.float32, seed=1)
@@ -1383,6 +1465,7 @@ class SpecificityAtSensitivityTest(test.TestCase):
for _ in range(10):
self.assertAlmostEqual(initial_specificity, specificity.eval(), 5)
+ @test_util.run_deprecated_v1
def testAllCorrect(self):
inputs = np.random.randint(0, 2, size=(100, 1))
@@ -1396,6 +1479,7 @@ class SpecificityAtSensitivityTest(test.TestCase):
self.assertEqual(1, self.evaluate(update_op))
self.assertEqual(1, specificity.eval())
+ @test_util.run_deprecated_v1
def testSomeCorrectHighSensitivity(self):
predictions_values = [0.1, 0.2, 0.4, 0.3, 0.0, 0.1, 0.45, 0.5, 0.8, 0.9]
labels_values = [0, 0, 0, 0, 0, 1, 1, 1, 1, 1]
@@ -1411,6 +1495,7 @@ class SpecificityAtSensitivityTest(test.TestCase):
self.assertAlmostEqual(1.0, self.evaluate(update_op))
self.assertAlmostEqual(1.0, specificity.eval())
+ @test_util.run_deprecated_v1
def testSomeCorrectLowSensitivity(self):
predictions_values = [0.1, 0.2, 0.4, 0.3, 0.0, 0.1, 0.2, 0.2, 0.26, 0.26]
labels_values = [0, 0, 0, 0, 0, 1, 1, 1, 1, 1]
@@ -1427,6 +1512,7 @@ class SpecificityAtSensitivityTest(test.TestCase):
self.assertAlmostEqual(0.6, self.evaluate(update_op))
self.assertAlmostEqual(0.6, specificity.eval())
+ @test_util.run_deprecated_v1
def testWeighted1d_multipleLabelDtypes(self):
for label_dtype in (dtypes_lib.bool, dtypes_lib.int32, dtypes_lib.float32):
predictions_values = [0.1, 0.2, 0.4, 0.3, 0.0, 0.1, 0.2, 0.2, 0.26, 0.26]
@@ -1446,6 +1532,7 @@ class SpecificityAtSensitivityTest(test.TestCase):
self.assertAlmostEqual(0.6, self.evaluate(update_op))
self.assertAlmostEqual(0.6, specificity.eval())
+ @test_util.run_deprecated_v1
def testWeighted2d(self):
predictions_values = [0.1, 0.2, 0.4, 0.3, 0.0, 0.1, 0.2, 0.2, 0.26, 0.26]
labels_values = [0, 0, 0, 0, 0, 1, 1, 1, 1, 1]
@@ -1471,6 +1558,7 @@ class SensitivityAtSpecificityTest(test.TestCase):
np.random.seed(1)
ops.reset_default_graph()
+ @test_util.run_deprecated_v1
def testVars(self):
metrics.sensitivity_at_specificity(
predictions=array_ops.ones((10, 1)),
@@ -1482,6 +1570,7 @@ class SensitivityAtSpecificityTest(test.TestCase):
'sensitivity_at_specificity/false_positives:0',
'sensitivity_at_specificity/true_negatives:0'))
+ @test_util.run_deprecated_v1
def testMetricsCollection(self):
my_collection_name = '__metrics__'
mean, _ = metrics.sensitivity_at_specificity(
@@ -1491,6 +1580,7 @@ class SensitivityAtSpecificityTest(test.TestCase):
metrics_collections=[my_collection_name])
self.assertListEqual(ops.get_collection(my_collection_name), [mean])
+ @test_util.run_deprecated_v1
def testUpdatesCollection(self):
my_collection_name = '__updates__'
_, update_op = metrics.sensitivity_at_specificity(
@@ -1500,6 +1590,7 @@ class SensitivityAtSpecificityTest(test.TestCase):
updates_collections=[my_collection_name])
self.assertListEqual(ops.get_collection(my_collection_name), [update_op])
+ @test_util.run_deprecated_v1
def testValueTensorIsIdempotent(self):
predictions = random_ops.random_uniform(
(10, 3), maxval=1, dtype=dtypes_lib.float32, seed=1)
@@ -1520,6 +1611,7 @@ class SensitivityAtSpecificityTest(test.TestCase):
for _ in range(10):
self.assertAlmostEqual(initial_sensitivity, sensitivity.eval(), 5)
+ @test_util.run_deprecated_v1
def testAllCorrect(self):
inputs = np.random.randint(0, 2, size=(100, 1))
@@ -1533,6 +1625,7 @@ class SensitivityAtSpecificityTest(test.TestCase):
self.assertEqual(1, self.evaluate(update_op))
self.assertEqual(1, specificity.eval())
+ @test_util.run_deprecated_v1
def testSomeCorrectHighSpecificity(self):
predictions_values = [0.0, 0.1, 0.2, 0.3, 0.4, 0.1, 0.45, 0.5, 0.8, 0.9]
labels_values = [0, 0, 0, 0, 0, 1, 1, 1, 1, 1]
@@ -1548,6 +1641,7 @@ class SensitivityAtSpecificityTest(test.TestCase):
self.assertAlmostEqual(0.8, self.evaluate(update_op))
self.assertAlmostEqual(0.8, specificity.eval())
+ @test_util.run_deprecated_v1
def testSomeCorrectLowSpecificity(self):
predictions_values = [0.0, 0.1, 0.2, 0.3, 0.4, 0.01, 0.02, 0.25, 0.26, 0.26]
labels_values = [0, 0, 0, 0, 0, 1, 1, 1, 1, 1]
@@ -1563,6 +1657,7 @@ class SensitivityAtSpecificityTest(test.TestCase):
self.assertAlmostEqual(0.6, self.evaluate(update_op))
self.assertAlmostEqual(0.6, specificity.eval())
+ @test_util.run_deprecated_v1
def testWeighted_multipleLabelDtypes(self):
for label_dtype in (dtypes_lib.bool, dtypes_lib.int32, dtypes_lib.float32):
predictions_values = [
@@ -1590,6 +1685,7 @@ class PrecisionRecallThresholdsTest(test.TestCase):
np.random.seed(1)
ops.reset_default_graph()
+ @test_util.run_deprecated_v1
def testVars(self):
metrics.precision_at_thresholds(
predictions=array_ops.ones((10, 1)),
@@ -1600,6 +1696,7 @@ class PrecisionRecallThresholdsTest(test.TestCase):
'precision_at_thresholds/false_positives:0',
))
+ @test_util.run_deprecated_v1
def testMetricsCollection(self):
my_collection_name = '__metrics__'
prec, _ = metrics.precision_at_thresholds(
@@ -1614,6 +1711,7 @@ class PrecisionRecallThresholdsTest(test.TestCase):
metrics_collections=[my_collection_name])
self.assertListEqual(ops.get_collection(my_collection_name), [prec, rec])
+ @test_util.run_deprecated_v1
def testUpdatesCollection(self):
my_collection_name = '__updates__'
_, precision_op = metrics.precision_at_thresholds(
@@ -1629,6 +1727,7 @@ class PrecisionRecallThresholdsTest(test.TestCase):
self.assertListEqual(
ops.get_collection(my_collection_name), [precision_op, recall_op])
+ @test_util.run_deprecated_v1
def testValueTensorIsIdempotent(self):
predictions = random_ops.random_uniform(
(10, 3), maxval=1, dtype=dtypes_lib.float32, seed=1)
@@ -1652,6 +1751,7 @@ class PrecisionRecallThresholdsTest(test.TestCase):
self.assertAllClose(initial_rec, rec.eval())
# TODO(nsilberman): fix tests (passing but incorrect).
+ @test_util.run_deprecated_v1
def testAllCorrect(self):
inputs = np.random.randint(0, 2, size=(100, 1))
@@ -1670,6 +1770,7 @@ class PrecisionRecallThresholdsTest(test.TestCase):
self.assertEqual(1, prec.eval())
self.assertEqual(1, rec.eval())
+ @test_util.run_deprecated_v1
def testSomeCorrect_multipleLabelDtypes(self):
with self.cached_session() as sess:
for label_dtype in (
@@ -1690,6 +1791,7 @@ class PrecisionRecallThresholdsTest(test.TestCase):
self.assertAlmostEqual(0.5, prec.eval())
self.assertAlmostEqual(0.5, rec.eval())
+ @test_util.run_deprecated_v1
def testAllIncorrect(self):
inputs = np.random.randint(0, 2, size=(100, 1))
@@ -1708,6 +1810,7 @@ class PrecisionRecallThresholdsTest(test.TestCase):
self.assertAlmostEqual(0, prec.eval())
self.assertAlmostEqual(0, rec.eval())
+ @test_util.run_deprecated_v1
def testWeights1d(self):
with self.cached_session() as sess:
predictions = constant_op.constant(
@@ -1738,6 +1841,7 @@ class PrecisionRecallThresholdsTest(test.TestCase):
self.assertAlmostEqual(1.0, rec_low.eval(), places=5)
self.assertAlmostEqual(0.0, rec_high.eval(), places=5)
+ @test_util.run_deprecated_v1
def testWeights2d(self):
with self.cached_session() as sess:
predictions = constant_op.constant(
@@ -1768,6 +1872,7 @@ class PrecisionRecallThresholdsTest(test.TestCase):
self.assertAlmostEqual(1.0, rec_low.eval(), places=5)
self.assertAlmostEqual(0.0, rec_high.eval(), places=5)
+ @test_util.run_deprecated_v1
def testExtremeThresholds(self):
with self.cached_session() as sess:
predictions = constant_op.constant(
@@ -1792,6 +1897,7 @@ class PrecisionRecallThresholdsTest(test.TestCase):
self.assertAlmostEqual(1.0, rec_low.eval())
self.assertAlmostEqual(0.0, rec_high.eval())
+ @test_util.run_deprecated_v1
def testZeroLabelsPredictions(self):
with self.cached_session() as sess:
predictions = array_ops.zeros([4], dtype=dtypes_lib.float32)
@@ -1808,6 +1914,7 @@ class PrecisionRecallThresholdsTest(test.TestCase):
self.assertAlmostEqual(0, prec.eval(), 6)
self.assertAlmostEqual(0, rec.eval(), 6)
+ @test_util.run_deprecated_v1
def testWithMultipleUpdates(self):
num_samples = 1000
batch_size = 10
@@ -1990,6 +2097,7 @@ class SingleLabelPrecisionAtKTest(test.TestCase):
self._test_average_precision_at_k = functools.partial(
_test_average_precision_at_k, test_case=self)
+ @test_util.run_deprecated_v1
def test_at_k1_nan(self):
for labels in self._labels:
# Classes 0,1,2 have 0 predictions, classes -1 and 4 are out of range.
@@ -1999,6 +2107,7 @@ class SingleLabelPrecisionAtKTest(test.TestCase):
self._test_precision_at_top_k(
self._predictions_idx, labels, k=1, expected=NAN, class_id=class_id)
+ @test_util.run_deprecated_v1
def test_at_k1(self):
for labels in self._labels:
# Class 3: 1 label, 2 predictions, 1 correct.
@@ -2026,6 +2135,7 @@ class MultiLabelPrecisionAtKTest(test.TestCase):
self._test_average_precision_at_k = functools.partial(
_test_average_precision_at_k, test_case=self)
+ @test_util.run_deprecated_v1
def test_average_precision(self):
# Example 1.
# Matches example here:
@@ -2101,6 +2211,7 @@ class MultiLabelPrecisionAtKTest(test.TestCase):
expected=streaming_average_precision[i],
weights=weights)
+ @test_util.run_deprecated_v1
def test_average_precision_some_labels_out_of_range(self):
"""Tests that labels outside the [0, n_classes) range are ignored."""
labels_ex1 = (-1, 0, 1, 2, 3, 4, 7)
@@ -2120,6 +2231,7 @@ class MultiLabelPrecisionAtKTest(test.TestCase):
self._test_average_precision_at_k(
predictions, labels, k, expected=avg_precision_ex1[i])
+ @test_util.run_deprecated_v1
def test_three_labels_at_k5_no_predictions(self):
predictions = [[0.5, 0.1, 0.6, 0.3, 0.8, 0.0, 0.7, 0.2, 0.4, 0.9],
[0.3, 0.0, 0.7, 0.2, 0.4, 0.9, 0.5, 0.8, 0.1, 0.6]]
@@ -2136,6 +2248,7 @@ class MultiLabelPrecisionAtKTest(test.TestCase):
self._test_precision_at_top_k(
predictions_idx, labels, k=5, expected=NAN, class_id=class_id)
+ @test_util.run_deprecated_v1
def test_three_labels_at_k5_no_labels(self):
predictions = [[0.5, 0.1, 0.6, 0.3, 0.8, 0.0, 0.7, 0.2, 0.4, 0.9],
[0.3, 0.0, 0.7, 0.2, 0.4, 0.9, 0.5, 0.8, 0.1, 0.6]]
@@ -2152,6 +2265,7 @@ class MultiLabelPrecisionAtKTest(test.TestCase):
self._test_precision_at_top_k(
predictions_idx, labels, k=5, expected=0.0, class_id=class_id)
+ @test_util.run_deprecated_v1
def test_three_labels_at_k5(self):
predictions = [[0.5, 0.1, 0.6, 0.3, 0.8, 0.0, 0.7, 0.2, 0.4, 0.9],
[0.3, 0.0, 0.7, 0.2, 0.4, 0.9, 0.5, 0.8, 0.1, 0.6]]
@@ -2185,6 +2299,7 @@ class MultiLabelPrecisionAtKTest(test.TestCase):
self._test_precision_at_top_k(
predictions_idx, labels, k=5, expected=3.0 / 10)
+ @test_util.run_deprecated_v1
def test_three_labels_at_k5_some_out_of_range(self):
"""Tests that labels outside the [0, n_classes) range are ignored."""
predictions = [[0.5, 0.1, 0.6, 0.3, 0.8, 0.0, 0.7, 0.2, 0.4, 0.9],
@@ -2221,6 +2336,7 @@ class MultiLabelPrecisionAtKTest(test.TestCase):
self._test_precision_at_top_k(
predictions_idx, sp_labels, k=5, expected=3.0 / 10)
+ @test_util.run_deprecated_v1
def test_3d_nan(self):
predictions = [[[0.5, 0.1, 0.6, 0.3, 0.8, 0.0, 0.7, 0.2, 0.4, 0.9],
[0.3, 0.0, 0.7, 0.2, 0.4, 0.9, 0.5, 0.8, 0.1, 0.6]],
@@ -2239,6 +2355,7 @@ class MultiLabelPrecisionAtKTest(test.TestCase):
self._test_precision_at_top_k(
predictions_idx, labels, k=5, expected=NAN, class_id=class_id)
+ @test_util.run_deprecated_v1
def test_3d_no_labels(self):
predictions = [[[0.5, 0.1, 0.6, 0.3, 0.8, 0.0, 0.7, 0.2, 0.4, 0.9],
[0.3, 0.0, 0.7, 0.2, 0.4, 0.9, 0.5, 0.8, 0.1, 0.6]],
@@ -2257,6 +2374,7 @@ class MultiLabelPrecisionAtKTest(test.TestCase):
self._test_precision_at_top_k(
predictions_idx, labels, k=5, expected=0.0, class_id=class_id)
+ @test_util.run_deprecated_v1
def test_3d(self):
predictions = [[[0.5, 0.1, 0.6, 0.3, 0.8, 0.0, 0.7, 0.2, 0.4, 0.9],
[0.3, 0.0, 0.7, 0.2, 0.4, 0.9, 0.5, 0.8, 0.1, 0.6]],
@@ -2292,6 +2410,7 @@ class MultiLabelPrecisionAtKTest(test.TestCase):
self._test_precision_at_top_k(
predictions_idx, labels, k=5, expected=7.0 / 20)
+ @test_util.run_deprecated_v1
def test_3d_ignore_some(self):
predictions = [[[0.5, 0.1, 0.6, 0.3, 0.8, 0.0, 0.7, 0.2, 0.4, 0.9],
[0.3, 0.0, 0.7, 0.2, 0.4, 0.9, 0.5, 0.8, 0.1, 0.6]],
@@ -2433,6 +2552,7 @@ class SingleLabelRecallAtKTest(test.TestCase):
self._test_recall_at_top_k = functools.partial(
_test_recall_at_top_k, test_case=self)
+ @test_util.run_deprecated_v1
def test_at_k1_nan(self):
# Classes 0,1 have 0 labels, 0 predictions, classes -1 and 4 are out of
# range.
@@ -2443,6 +2563,7 @@ class SingleLabelRecallAtKTest(test.TestCase):
self._test_recall_at_top_k(
self._predictions_idx, labels, k=1, expected=NAN, class_id=class_id)
+ @test_util.run_deprecated_v1
def test_at_k1_no_predictions(self):
for labels in self._labels:
# Class 2: 0 predictions.
@@ -2451,6 +2572,7 @@ class SingleLabelRecallAtKTest(test.TestCase):
self._test_recall_at_top_k(
self._predictions_idx, labels, k=1, expected=0.0, class_id=2)
+ @test_util.run_deprecated_v1
def test_one_label_at_k1(self):
for labels in self._labels:
# Class 3: 1 label, 2 predictions, 1 correct.
@@ -2464,6 +2586,7 @@ class SingleLabelRecallAtKTest(test.TestCase):
self._test_recall_at_top_k(
self._predictions_idx, labels, k=1, expected=1.0 / 2)
+ @test_util.run_deprecated_v1
def test_one_label_at_k1_weighted_class_id3(self):
predictions = self._predictions
predictions_idx = self._predictions_idx
@@ -2505,6 +2628,7 @@ class SingleLabelRecallAtKTest(test.TestCase):
predictions_idx, labels, k=1, expected=2.0 / 2, class_id=3,
weights=(2.0, 3.0))
+ @test_util.run_deprecated_v1
def test_one_label_at_k1_weighted(self):
predictions = self._predictions
predictions_idx = self._predictions_idx
@@ -2554,6 +2678,7 @@ class MultiLabel2dRecallAtKTest(test.TestCase):
self._test_recall_at_top_k = functools.partial(
_test_recall_at_top_k, test_case=self)
+ @test_util.run_deprecated_v1
def test_at_k5_nan(self):
for labels in self._labels:
# Classes 0,3,4,6,9 have 0 labels, class 10 is out of range.
@@ -2563,6 +2688,7 @@ class MultiLabel2dRecallAtKTest(test.TestCase):
self._test_recall_at_top_k(
self._predictions_idx, labels, k=5, expected=NAN, class_id=class_id)
+ @test_util.run_deprecated_v1
def test_at_k5_no_predictions(self):
for labels in self._labels:
# Class 8: 1 label, no predictions.
@@ -2571,6 +2697,7 @@ class MultiLabel2dRecallAtKTest(test.TestCase):
self._test_recall_at_top_k(
self._predictions_idx, labels, k=5, expected=0.0 / 1, class_id=8)
+ @test_util.run_deprecated_v1
def test_at_k5(self):
for labels in self._labels:
# Class 2: 2 labels, both correct.
@@ -2596,6 +2723,7 @@ class MultiLabel2dRecallAtKTest(test.TestCase):
self._test_recall_at_top_k(
self._predictions_idx, labels, k=5, expected=3.0 / 6)
+ @test_util.run_deprecated_v1
def test_at_k5_some_out_of_range(self):
"""Tests that labels outside the [0, n_classes) count in denominator."""
labels = sparse_tensor.SparseTensorValue(
@@ -2648,6 +2776,7 @@ class MultiLabel3dRecallAtKTest(test.TestCase):
self._test_recall_at_top_k = functools.partial(
_test_recall_at_top_k, test_case=self)
+ @test_util.run_deprecated_v1
def test_3d_nan(self):
# Classes 0,3,4,6,9 have 0 labels, class 10 is out of range.
for class_id in (0, 3, 4, 6, 9, 10):
@@ -2657,6 +2786,7 @@ class MultiLabel3dRecallAtKTest(test.TestCase):
self._predictions_idx, self._labels, k=5, expected=NAN,
class_id=class_id)
+ @test_util.run_deprecated_v1
def test_3d_no_predictions(self):
# Classes 1,8 have 0 predictions, >=1 label.
for class_id in (1, 8):
@@ -2666,6 +2796,7 @@ class MultiLabel3dRecallAtKTest(test.TestCase):
self._predictions_idx, self._labels, k=5, expected=0.0,
class_id=class_id)
+ @test_util.run_deprecated_v1
def test_3d(self):
# Class 2: 4 labels, all correct.
self._test_recall_at_k(
@@ -2694,6 +2825,7 @@ class MultiLabel3dRecallAtKTest(test.TestCase):
self._test_recall_at_top_k(
self._predictions_idx, self._labels, k=5, expected=7.0 / 12)
+ @test_util.run_deprecated_v1
def test_3d_ignore_all(self):
for class_id in xrange(10):
self._test_recall_at_k(
@@ -2720,6 +2852,7 @@ class MultiLabel3dRecallAtKTest(test.TestCase):
self._predictions_idx, self._labels, k=5, expected=NAN,
weights=[[0, 0], [0, 0]])
+ @test_util.run_deprecated_v1
def test_3d_ignore_some(self):
# Class 2: 2 labels, both correct.
self._test_recall_at_k(
@@ -2775,12 +2908,14 @@ class MeanAbsoluteErrorTest(test.TestCase):
def setUp(self):
ops.reset_default_graph()
+ @test_util.run_deprecated_v1
def testVars(self):
metrics.mean_absolute_error(
predictions=array_ops.ones((10, 1)), labels=array_ops.ones((10, 1)))
_assert_metric_variables(
self, ('mean_absolute_error/count:0', 'mean_absolute_error/total:0'))
+ @test_util.run_deprecated_v1
def testMetricsCollection(self):
my_collection_name = '__metrics__'
mean, _ = metrics.mean_absolute_error(
@@ -2789,6 +2924,7 @@ class MeanAbsoluteErrorTest(test.TestCase):
metrics_collections=[my_collection_name])
self.assertListEqual(ops.get_collection(my_collection_name), [mean])
+ @test_util.run_deprecated_v1
def testUpdatesCollection(self):
my_collection_name = '__updates__'
_, update_op = metrics.mean_absolute_error(
@@ -2797,6 +2933,7 @@ class MeanAbsoluteErrorTest(test.TestCase):
updates_collections=[my_collection_name])
self.assertListEqual(ops.get_collection(my_collection_name), [update_op])
+ @test_util.run_deprecated_v1
def testValueTensorIsIdempotent(self):
predictions = random_ops.random_normal((10, 3), seed=1)
labels = random_ops.random_normal((10, 3), seed=2)
@@ -2814,6 +2951,7 @@ class MeanAbsoluteErrorTest(test.TestCase):
for _ in range(10):
self.assertEqual(initial_error, error.eval())
+ @test_util.run_deprecated_v1
def testSingleUpdateWithErrorAndWeights(self):
predictions = constant_op.constant(
[2, 4, 6, 8], shape=(1, 4), dtype=dtypes_lib.float32)
@@ -2834,6 +2972,7 @@ class MeanRelativeErrorTest(test.TestCase):
def setUp(self):
ops.reset_default_graph()
+ @test_util.run_deprecated_v1
def testVars(self):
metrics.mean_relative_error(
predictions=array_ops.ones((10, 1)),
@@ -2842,6 +2981,7 @@ class MeanRelativeErrorTest(test.TestCase):
_assert_metric_variables(
self, ('mean_relative_error/count:0', 'mean_relative_error/total:0'))
+ @test_util.run_deprecated_v1
def testMetricsCollection(self):
my_collection_name = '__metrics__'
mean, _ = metrics.mean_relative_error(
@@ -2851,6 +2991,7 @@ class MeanRelativeErrorTest(test.TestCase):
metrics_collections=[my_collection_name])
self.assertListEqual(ops.get_collection(my_collection_name), [mean])
+ @test_util.run_deprecated_v1
def testUpdatesCollection(self):
my_collection_name = '__updates__'
_, update_op = metrics.mean_relative_error(
@@ -2860,6 +3001,7 @@ class MeanRelativeErrorTest(test.TestCase):
updates_collections=[my_collection_name])
self.assertListEqual(ops.get_collection(my_collection_name), [update_op])
+ @test_util.run_deprecated_v1
def testValueTensorIsIdempotent(self):
predictions = random_ops.random_normal((10, 3), seed=1)
labels = random_ops.random_normal((10, 3), seed=2)
@@ -2879,6 +3021,7 @@ class MeanRelativeErrorTest(test.TestCase):
for _ in range(10):
self.assertEqual(initial_error, error.eval())
+ @test_util.run_deprecated_v1
def testSingleUpdateNormalizedByLabels(self):
np_predictions = np.asarray([2, 4, 6, 8], dtype=np.float32)
np_labels = np.asarray([1, 3, 2, 3], dtype=np.float32)
@@ -2897,6 +3040,7 @@ class MeanRelativeErrorTest(test.TestCase):
self.assertEqual(expected_error, self.evaluate(update_op))
self.assertEqual(expected_error, error.eval())
+ @test_util.run_deprecated_v1
def testSingleUpdateNormalizedByZeros(self):
np_predictions = np.asarray([2, 4, 6, 8], dtype=np.float32)
@@ -2919,12 +3063,14 @@ class MeanSquaredErrorTest(test.TestCase):
def setUp(self):
ops.reset_default_graph()
+ @test_util.run_deprecated_v1
def testVars(self):
metrics.mean_squared_error(
predictions=array_ops.ones((10, 1)), labels=array_ops.ones((10, 1)))
_assert_metric_variables(
self, ('mean_squared_error/count:0', 'mean_squared_error/total:0'))
+ @test_util.run_deprecated_v1
def testMetricsCollection(self):
my_collection_name = '__metrics__'
mean, _ = metrics.mean_squared_error(
@@ -2933,6 +3079,7 @@ class MeanSquaredErrorTest(test.TestCase):
metrics_collections=[my_collection_name])
self.assertListEqual(ops.get_collection(my_collection_name), [mean])
+ @test_util.run_deprecated_v1
def testUpdatesCollection(self):
my_collection_name = '__updates__'
_, update_op = metrics.mean_squared_error(
@@ -2941,6 +3088,7 @@ class MeanSquaredErrorTest(test.TestCase):
updates_collections=[my_collection_name])
self.assertListEqual(ops.get_collection(my_collection_name), [update_op])
+ @test_util.run_deprecated_v1
def testValueTensorIsIdempotent(self):
predictions = random_ops.random_normal((10, 3), seed=1)
labels = random_ops.random_normal((10, 3), seed=2)
@@ -2958,6 +3106,7 @@ class MeanSquaredErrorTest(test.TestCase):
for _ in range(10):
self.assertEqual(initial_error, error.eval())
+ @test_util.run_deprecated_v1
def testSingleUpdateZeroError(self):
predictions = array_ops.zeros((1, 3), dtype=dtypes_lib.float32)
labels = array_ops.zeros((1, 3), dtype=dtypes_lib.float32)
@@ -2969,6 +3118,7 @@ class MeanSquaredErrorTest(test.TestCase):
self.assertEqual(0, self.evaluate(update_op))
self.assertEqual(0, error.eval())
+ @test_util.run_deprecated_v1
def testSingleUpdateWithError(self):
predictions = constant_op.constant(
[2, 4, 6], shape=(1, 3), dtype=dtypes_lib.float32)
@@ -2982,6 +3132,7 @@ class MeanSquaredErrorTest(test.TestCase):
self.assertEqual(6, self.evaluate(update_op))
self.assertEqual(6, error.eval())
+ @test_util.run_deprecated_v1
def testSingleUpdateWithErrorAndWeights(self):
predictions = constant_op.constant(
[2, 4, 6, 8], shape=(1, 4), dtype=dtypes_lib.float32)
@@ -2996,6 +3147,7 @@ class MeanSquaredErrorTest(test.TestCase):
self.assertEqual(13, self.evaluate(update_op))
self.assertEqual(13, error.eval())
+ @test_util.run_deprecated_v1
def testMultipleBatchesOfSizeOne(self):
with self.cached_session() as sess:
# Create the queue that populates the predictions.
@@ -3020,6 +3172,7 @@ class MeanSquaredErrorTest(test.TestCase):
self.assertAlmostEqual(208.0 / 6, error.eval(), 5)
+ @test_util.run_deprecated_v1
def testMetricsComputedConcurrently(self):
with self.cached_session() as sess:
# Create the queue that populates one set of predictions.
@@ -3063,6 +3216,7 @@ class MeanSquaredErrorTest(test.TestCase):
self.assertAlmostEqual(208.0 / 6, mse0, 5)
self.assertAlmostEqual(79.0 / 6, mse1, 5)
+ @test_util.run_deprecated_v1
def testMultipleMetricsOnMultipleBatchesOfSizeOne(self):
with self.cached_session() as sess:
# Create the queue that populates the predictions.
@@ -3095,6 +3249,7 @@ class RootMeanSquaredErrorTest(test.TestCase):
def setUp(self):
ops.reset_default_graph()
+ @test_util.run_deprecated_v1
def testVars(self):
metrics.root_mean_squared_error(
predictions=array_ops.ones((10, 1)), labels=array_ops.ones((10, 1)))
@@ -3102,6 +3257,7 @@ class RootMeanSquaredErrorTest(test.TestCase):
self,
('root_mean_squared_error/count:0', 'root_mean_squared_error/total:0'))
+ @test_util.run_deprecated_v1
def testMetricsCollection(self):
my_collection_name = '__metrics__'
mean, _ = metrics.root_mean_squared_error(
@@ -3110,6 +3266,7 @@ class RootMeanSquaredErrorTest(test.TestCase):
metrics_collections=[my_collection_name])
self.assertListEqual(ops.get_collection(my_collection_name), [mean])
+ @test_util.run_deprecated_v1
def testUpdatesCollection(self):
my_collection_name = '__updates__'
_, update_op = metrics.root_mean_squared_error(
@@ -3118,6 +3275,7 @@ class RootMeanSquaredErrorTest(test.TestCase):
updates_collections=[my_collection_name])
self.assertListEqual(ops.get_collection(my_collection_name), [update_op])
+ @test_util.run_deprecated_v1
def testValueTensorIsIdempotent(self):
predictions = random_ops.random_normal((10, 3), seed=1)
labels = random_ops.random_normal((10, 3), seed=2)
@@ -3135,6 +3293,7 @@ class RootMeanSquaredErrorTest(test.TestCase):
for _ in range(10):
self.assertEqual(initial_error, error.eval())
+ @test_util.run_deprecated_v1
def testSingleUpdateZeroError(self):
with self.cached_session() as sess:
predictions = constant_op.constant(
@@ -3148,6 +3307,7 @@ class RootMeanSquaredErrorTest(test.TestCase):
self.assertEqual(0, rmse.eval())
+ @test_util.run_deprecated_v1
def testSingleUpdateWithError(self):
with self.cached_session() as sess:
predictions = constant_op.constant(
@@ -3161,6 +3321,7 @@ class RootMeanSquaredErrorTest(test.TestCase):
self.assertAlmostEqual(math.sqrt(6), update_op.eval(), 5)
self.assertAlmostEqual(math.sqrt(6), rmse.eval(), 5)
+ @test_util.run_deprecated_v1
def testSingleUpdateWithErrorAndWeights(self):
with self.cached_session() as sess:
predictions = constant_op.constant(
@@ -3188,6 +3349,7 @@ class MeanCosineDistanceTest(test.TestCase):
def setUp(self):
ops.reset_default_graph()
+ @test_util.run_deprecated_v1
def testVars(self):
metrics.mean_cosine_distance(
predictions=array_ops.ones((10, 3)),
@@ -3198,6 +3360,7 @@ class MeanCosineDistanceTest(test.TestCase):
'mean_cosine_distance/total:0',
))
+ @test_util.run_deprecated_v1
def testMetricsCollection(self):
my_collection_name = '__metrics__'
mean, _ = metrics.mean_cosine_distance(
@@ -3207,6 +3370,7 @@ class MeanCosineDistanceTest(test.TestCase):
metrics_collections=[my_collection_name])
self.assertListEqual(ops.get_collection(my_collection_name), [mean])
+ @test_util.run_deprecated_v1
def testUpdatesCollection(self):
my_collection_name = '__updates__'
_, update_op = metrics.mean_cosine_distance(
@@ -3216,6 +3380,7 @@ class MeanCosineDistanceTest(test.TestCase):
updates_collections=[my_collection_name])
self.assertListEqual(ops.get_collection(my_collection_name), [update_op])
+ @test_util.run_deprecated_v1
def testValueTensorIsIdempotent(self):
predictions = random_ops.random_normal((10, 3), seed=1)
labels = random_ops.random_normal((10, 3), seed=2)
@@ -3233,6 +3398,7 @@ class MeanCosineDistanceTest(test.TestCase):
for _ in range(10):
self.assertEqual(initial_error, error.eval())
+ @test_util.run_deprecated_v1
def testSingleUpdateZeroError(self):
np_labels = np.matrix(('1 0 0;' '0 0 1;' '0 1 0'))
@@ -3248,6 +3414,7 @@ class MeanCosineDistanceTest(test.TestCase):
self.assertEqual(0, self.evaluate(update_op))
self.assertEqual(0, error.eval())
+ @test_util.run_deprecated_v1
def testSingleUpdateWithError1(self):
np_labels = np.matrix(('1 0 0;' '0 0 1;' '0 1 0'))
np_predictions = np.matrix(('1 0 0;' '0 0 -1;' '1 0 0'))
@@ -3264,6 +3431,7 @@ class MeanCosineDistanceTest(test.TestCase):
self.assertAlmostEqual(1, self.evaluate(update_op), 5)
self.assertAlmostEqual(1, error.eval(), 5)
+ @test_util.run_deprecated_v1
def testSingleUpdateWithError2(self):
np_predictions = np.matrix(
('0.819031913261206 0.567041924552012 0.087465312324590;'
@@ -3285,6 +3453,7 @@ class MeanCosineDistanceTest(test.TestCase):
self.assertAlmostEqual(1.0, self.evaluate(update_op), 5)
self.assertAlmostEqual(1.0, error.eval(), 5)
+ @test_util.run_deprecated_v1
def testSingleUpdateWithErrorAndWeights1(self):
np_predictions = np.matrix(('1 0 0;' '0 0 -1;' '1 0 0'))
np_labels = np.matrix(('1 0 0;' '0 0 1;' '0 1 0'))
@@ -3304,6 +3473,7 @@ class MeanCosineDistanceTest(test.TestCase):
self.assertEqual(0, self.evaluate(update_op))
self.assertEqual(0, error.eval())
+ @test_util.run_deprecated_v1
def testSingleUpdateWithErrorAndWeights2(self):
np_predictions = np.matrix(('1 0 0;' '0 0 -1;' '1 0 0'))
np_labels = np.matrix(('1 0 0;' '0 0 1;' '0 1 0'))
@@ -3329,6 +3499,7 @@ class PcntBelowThreshTest(test.TestCase):
def setUp(self):
ops.reset_default_graph()
+ @test_util.run_deprecated_v1
def testVars(self):
metrics.percentage_below(values=array_ops.ones((10,)), threshold=2)
_assert_metric_variables(self, (
@@ -3336,6 +3507,7 @@ class PcntBelowThreshTest(test.TestCase):
'percentage_below_threshold/total:0',
))
+ @test_util.run_deprecated_v1
def testMetricsCollection(self):
my_collection_name = '__metrics__'
mean, _ = metrics.percentage_below(
@@ -3344,6 +3516,7 @@ class PcntBelowThreshTest(test.TestCase):
metrics_collections=[my_collection_name])
self.assertListEqual(ops.get_collection(my_collection_name), [mean])
+ @test_util.run_deprecated_v1
def testUpdatesCollection(self):
my_collection_name = '__updates__'
_, update_op = metrics.percentage_below(
@@ -3352,6 +3525,7 @@ class PcntBelowThreshTest(test.TestCase):
updates_collections=[my_collection_name])
self.assertListEqual(ops.get_collection(my_collection_name), [update_op])
+ @test_util.run_deprecated_v1
def testOneUpdate(self):
with self.cached_session() as sess:
values = constant_op.constant(
@@ -3369,6 +3543,7 @@ class PcntBelowThreshTest(test.TestCase):
self.assertAlmostEqual(0.75, pcnt1, 5)
self.assertAlmostEqual(0.0, pcnt2, 5)
+ @test_util.run_deprecated_v1
def testSomePresentOneUpdate(self):
with self.cached_session() as sess:
values = constant_op.constant(
@@ -3399,6 +3574,7 @@ class MeanIOUTest(test.TestCase):
np.random.seed(1)
ops.reset_default_graph()
+ @test_util.run_deprecated_v1
def testVars(self):
metrics.mean_iou(
predictions=array_ops.ones([10, 1]),
@@ -3406,6 +3582,7 @@ class MeanIOUTest(test.TestCase):
num_classes=2)
_assert_metric_variables(self, ('mean_iou/total_confusion_matrix:0',))
+ @test_util.run_deprecated_v1
def testMetricsCollections(self):
my_collection_name = '__metrics__'
mean_iou, _ = metrics.mean_iou(
@@ -3415,6 +3592,7 @@ class MeanIOUTest(test.TestCase):
metrics_collections=[my_collection_name])
self.assertListEqual(ops.get_collection(my_collection_name), [mean_iou])
+ @test_util.run_deprecated_v1
def testUpdatesCollection(self):
my_collection_name = '__updates__'
_, update_op = metrics.mean_iou(
@@ -3424,12 +3602,14 @@ class MeanIOUTest(test.TestCase):
updates_collections=[my_collection_name])
self.assertListEqual(ops.get_collection(my_collection_name), [update_op])
+ @test_util.run_deprecated_v1
def testPredictionsAndLabelsOfDifferentSizeRaisesValueError(self):
predictions = array_ops.ones([10, 3])
labels = array_ops.ones([10, 4])
with self.assertRaises(ValueError):
metrics.mean_iou(labels, predictions, num_classes=2)
+ @test_util.run_deprecated_v1
def testLabelsAndWeightsOfDifferentSizeRaisesValueError(self):
predictions = array_ops.ones([10])
labels = array_ops.ones([10])
@@ -3437,6 +3617,7 @@ class MeanIOUTest(test.TestCase):
with self.assertRaises(ValueError):
metrics.mean_iou(labels, predictions, num_classes=2, weights=weights)
+ @test_util.run_deprecated_v1
def testValueTensorIsIdempotent(self):
num_classes = 3
predictions = random_ops.random_uniform(
@@ -3458,6 +3639,7 @@ class MeanIOUTest(test.TestCase):
for _ in range(10):
self.assertEqual(initial_mean_iou, mean_iou.eval())
+ @test_util.run_deprecated_v1
def testMultipleUpdates(self):
num_classes = 3
with self.cached_session() as sess:
@@ -3489,6 +3671,7 @@ class MeanIOUTest(test.TestCase):
desired_output = np.mean([1.0 / 2.0, 1.0 / 4.0, 0.])
self.assertEqual(desired_output, miou.eval())
+ @test_util.run_deprecated_v1
def testMultipleUpdatesWithWeights(self):
num_classes = 2
with self.cached_session() as sess:
@@ -3534,6 +3717,7 @@ class MeanIOUTest(test.TestCase):
desired_output = np.mean([2.0 / 3.0, 1.0 / 2.0])
self.assertAlmostEqual(desired_output, mean_iou.eval())
+ @test_util.run_deprecated_v1
def testMultipleUpdatesWithMissingClass(self):
# Test the case where there are no predicions and labels for
# one class, and thus there is one row and one column with
@@ -3570,6 +3754,7 @@ class MeanIOUTest(test.TestCase):
desired_output = np.mean([1.0 / 3.0, 2.0 / 4.0])
self.assertAlmostEqual(desired_output, miou.eval())
+ @test_util.run_deprecated_v1
def testUpdateOpEvalIsAccumulatedConfusionMatrix(self):
predictions = array_ops.concat(
[
@@ -3594,6 +3779,7 @@ class MeanIOUTest(test.TestCase):
desired_miou = np.mean([3. / 5., 5. / 7.])
self.assertAlmostEqual(desired_miou, miou.eval())
+ @test_util.run_deprecated_v1
def testAllCorrect(self):
predictions = array_ops.zeros([40])
labels = array_ops.zeros([40])
@@ -3604,6 +3790,7 @@ class MeanIOUTest(test.TestCase):
self.assertEqual(40, update_op.eval()[0])
self.assertEqual(1.0, miou.eval())
+ @test_util.run_deprecated_v1
def testAllWrong(self):
predictions = array_ops.zeros([40])
labels = array_ops.ones([40])
@@ -3614,6 +3801,7 @@ class MeanIOUTest(test.TestCase):
self.assertAllEqual([[0, 0], [40, 0]], update_op.eval())
self.assertEqual(0., miou.eval())
+ @test_util.run_deprecated_v1
def testResultsWithSomeMissing(self):
predictions = array_ops.concat(
[
@@ -3646,6 +3834,7 @@ class MeanIOUTest(test.TestCase):
desired_miou = np.mean([2. / 4., 4. / 6.])
self.assertAlmostEqual(desired_miou, miou.eval())
+ @test_util.run_deprecated_v1
def testMissingClassInLabels(self):
labels = constant_op.constant([
[[0, 0, 1, 1, 0, 0],
@@ -3666,6 +3855,7 @@ class MeanIOUTest(test.TestCase):
1 / 3 * (7 / (7 + 3 + 7) + 5 / (5 + 4 + 5) + 0 / (0 + 5 + 0)),
miou.eval())
+ @test_util.run_deprecated_v1
def testMissingClassOverallSmall(self):
labels = constant_op.constant([0])
predictions = constant_op.constant([0])
@@ -3676,6 +3866,7 @@ class MeanIOUTest(test.TestCase):
self.assertAllEqual([[1, 0], [0, 0]], update_op.eval())
self.assertAlmostEqual(1, miou.eval())
+ @test_util.run_deprecated_v1
def testMissingClassOverallLarge(self):
labels = constant_op.constant([
[[0, 0, 1, 1, 0, 0],
@@ -3702,6 +3893,7 @@ class MeanPerClassAccuracyTest(test.TestCase):
np.random.seed(1)
ops.reset_default_graph()
+ @test_util.run_deprecated_v1
def testVars(self):
metrics.mean_per_class_accuracy(
predictions=array_ops.ones([10, 1]),
@@ -3710,6 +3902,7 @@ class MeanPerClassAccuracyTest(test.TestCase):
_assert_metric_variables(self, ('mean_accuracy/count:0',
'mean_accuracy/total:0'))
+ @test_util.run_deprecated_v1
def testMetricsCollections(self):
my_collection_name = '__metrics__'
mean_accuracy, _ = metrics.mean_per_class_accuracy(
@@ -3720,6 +3913,7 @@ class MeanPerClassAccuracyTest(test.TestCase):
self.assertListEqual(
ops.get_collection(my_collection_name), [mean_accuracy])
+ @test_util.run_deprecated_v1
def testUpdatesCollection(self):
my_collection_name = '__updates__'
_, update_op = metrics.mean_per_class_accuracy(
@@ -3729,12 +3923,14 @@ class MeanPerClassAccuracyTest(test.TestCase):
updates_collections=[my_collection_name])
self.assertListEqual(ops.get_collection(my_collection_name), [update_op])
+ @test_util.run_deprecated_v1
def testPredictionsAndLabelsOfDifferentSizeRaisesValueError(self):
predictions = array_ops.ones([10, 3])
labels = array_ops.ones([10, 4])
with self.assertRaises(ValueError):
metrics.mean_per_class_accuracy(labels, predictions, num_classes=2)
+ @test_util.run_deprecated_v1
def testLabelsAndWeightsOfDifferentSizeRaisesValueError(self):
predictions = array_ops.ones([10])
labels = array_ops.ones([10])
@@ -3743,6 +3939,7 @@ class MeanPerClassAccuracyTest(test.TestCase):
metrics.mean_per_class_accuracy(
labels, predictions, num_classes=2, weights=weights)
+ @test_util.run_deprecated_v1
def testValueTensorIsIdempotent(self):
num_classes = 3
predictions = random_ops.random_uniform(
@@ -3795,6 +3992,7 @@ class MeanPerClassAccuracyTest(test.TestCase):
desired_output = np.mean([1.0, 1.0 / 3.0, 0.0])
self.assertAlmostEqual(desired_output, mean_accuracy.eval())
+ @test_util.run_deprecated_v1
def testMultipleUpdatesWithWeights(self):
num_classes = 2
with self.cached_session() as sess:
@@ -3840,6 +4038,7 @@ class MeanPerClassAccuracyTest(test.TestCase):
desired_output = np.mean([2.0 / 2.0, 0.5 / 1.5])
self.assertAlmostEqual(desired_output, mean_accuracy.eval())
+ @test_util.run_deprecated_v1
def testMultipleUpdatesWithMissingClass(self):
# Test the case where there are no predicions and labels for
# one class, and thus there is one row and one column with
@@ -3877,6 +4076,7 @@ class MeanPerClassAccuracyTest(test.TestCase):
desired_output = np.mean([1.0 / 2.0, 2.0 / 3.0, 0.])
self.assertAlmostEqual(desired_output, mean_accuracy.eval())
+ @test_util.run_deprecated_v1
def testAllCorrect(self):
predictions = array_ops.zeros([40])
labels = array_ops.zeros([40])
@@ -3888,6 +4088,7 @@ class MeanPerClassAccuracyTest(test.TestCase):
self.assertEqual(1.0, update_op.eval()[0])
self.assertEqual(1.0, mean_accuracy.eval())
+ @test_util.run_deprecated_v1
def testAllWrong(self):
predictions = array_ops.zeros([40])
labels = array_ops.ones([40])
@@ -3899,6 +4100,7 @@ class MeanPerClassAccuracyTest(test.TestCase):
self.assertAllEqual([0.0, 0.0], update_op.eval())
self.assertEqual(0., mean_accuracy.eval())
+ @test_util.run_deprecated_v1
def testResultsWithSomeMissing(self):
predictions = array_ops.concat([
constant_op.constant(0, shape=[5]), constant_op.constant(1, shape=[5])
@@ -3927,12 +4129,14 @@ class FalseNegativesTest(test.TestCase):
np.random.seed(1)
ops.reset_default_graph()
+ @test_util.run_deprecated_v1
def testVars(self):
metrics.false_negatives(
labels=(0, 1, 0, 1),
predictions=(0, 0, 1, 1))
_assert_metric_variables(self, ('false_negatives/count:0',))
+ @test_util.run_deprecated_v1
def testUnweighted(self):
labels = constant_op.constant(((0, 1, 0, 1, 0),
(0, 0, 1, 1, 1),
@@ -3951,6 +4155,7 @@ class FalseNegativesTest(test.TestCase):
self.assertAllClose(3., tn_update_op.eval())
self.assertAllClose(3., tn.eval())
+ @test_util.run_deprecated_v1
def testWeighted(self):
labels = constant_op.constant(((0, 1, 0, 1, 0),
(0, 0, 1, 1, 1),
@@ -3977,6 +4182,7 @@ class FalseNegativesAtThresholdsTest(test.TestCase):
np.random.seed(1)
ops.reset_default_graph()
+ @test_util.run_deprecated_v1
def testVars(self):
metrics.false_negatives_at_thresholds(
predictions=array_ops.ones((10, 1)),
@@ -3984,6 +4190,7 @@ class FalseNegativesAtThresholdsTest(test.TestCase):
thresholds=[0.15, 0.5, 0.85])
_assert_metric_variables(self, ('false_negatives/false_negatives:0',))
+ @test_util.run_deprecated_v1
def testUnweighted(self):
predictions = constant_op.constant(((0.9, 0.2, 0.8, 0.1),
(0.2, 0.9, 0.7, 0.6),
@@ -4000,6 +4207,7 @@ class FalseNegativesAtThresholdsTest(test.TestCase):
self.assertAllEqual((0, 2, 3), fn_update_op.eval())
self.assertAllEqual((0, 2, 3), fn.eval())
+ @test_util.run_deprecated_v1
def testWeighted(self):
predictions = constant_op.constant(((0.9, 0.2, 0.8, 0.1),
(0.2, 0.9, 0.7, 0.6),
@@ -4026,12 +4234,14 @@ class FalsePositivesTest(test.TestCase):
np.random.seed(1)
ops.reset_default_graph()
+ @test_util.run_deprecated_v1
def testVars(self):
metrics.false_positives(
labels=(0, 1, 0, 1),
predictions=(0, 0, 1, 1))
_assert_metric_variables(self, ('false_positives/count:0',))
+ @test_util.run_deprecated_v1
def testUnweighted(self):
labels = constant_op.constant(((0, 1, 0, 1, 0),
(0, 0, 1, 1, 1),
@@ -4050,6 +4260,7 @@ class FalsePositivesTest(test.TestCase):
self.assertAllClose(7., tn_update_op.eval())
self.assertAllClose(7., tn.eval())
+ @test_util.run_deprecated_v1
def testWeighted(self):
labels = constant_op.constant(((0, 1, 0, 1, 0),
(0, 0, 1, 1, 1),
@@ -4076,6 +4287,7 @@ class FalsePositivesAtThresholdsTest(test.TestCase):
np.random.seed(1)
ops.reset_default_graph()
+ @test_util.run_deprecated_v1
def testVars(self):
metrics.false_positives_at_thresholds(
predictions=array_ops.ones((10, 1)),
@@ -4083,6 +4295,7 @@ class FalsePositivesAtThresholdsTest(test.TestCase):
thresholds=[0.15, 0.5, 0.85])
_assert_metric_variables(self, ('false_positives/false_positives:0',))
+ @test_util.run_deprecated_v1
def testUnweighted(self):
predictions = constant_op.constant(((0.9, 0.2, 0.8, 0.1),
(0.2, 0.9, 0.7, 0.6),
@@ -4099,6 +4312,7 @@ class FalsePositivesAtThresholdsTest(test.TestCase):
self.assertAllEqual((7, 4, 2), fp_update_op.eval())
self.assertAllEqual((7, 4, 2), fp.eval())
+ @test_util.run_deprecated_v1
def testWeighted(self):
predictions = constant_op.constant(((0.9, 0.2, 0.8, 0.1),
(0.2, 0.9, 0.7, 0.6),
@@ -4127,12 +4341,14 @@ class TrueNegativesTest(test.TestCase):
np.random.seed(1)
ops.reset_default_graph()
+ @test_util.run_deprecated_v1
def testVars(self):
metrics.true_negatives(
labels=(0, 1, 0, 1),
predictions=(0, 0, 1, 1))
_assert_metric_variables(self, ('true_negatives/count:0',))
+ @test_util.run_deprecated_v1
def testUnweighted(self):
labels = constant_op.constant(((0, 1, 0, 1, 0),
(0, 0, 1, 1, 1),
@@ -4151,6 +4367,7 @@ class TrueNegativesTest(test.TestCase):
self.assertAllClose(3., tn_update_op.eval())
self.assertAllClose(3., tn.eval())
+ @test_util.run_deprecated_v1
def testWeighted(self):
labels = constant_op.constant(((0, 1, 0, 1, 0),
(0, 0, 1, 1, 1),
@@ -4177,6 +4394,7 @@ class TrueNegativesAtThresholdsTest(test.TestCase):
np.random.seed(1)
ops.reset_default_graph()
+ @test_util.run_deprecated_v1
def testVars(self):
metrics.true_negatives_at_thresholds(
predictions=array_ops.ones((10, 1)),
@@ -4184,6 +4402,7 @@ class TrueNegativesAtThresholdsTest(test.TestCase):
thresholds=[0.15, 0.5, 0.85])
_assert_metric_variables(self, ('true_negatives/true_negatives:0',))
+ @test_util.run_deprecated_v1
def testUnweighted(self):
predictions = constant_op.constant(((0.9, 0.2, 0.8, 0.1),
(0.2, 0.9, 0.7, 0.6),
@@ -4200,6 +4419,7 @@ class TrueNegativesAtThresholdsTest(test.TestCase):
self.assertAllEqual((2, 5, 7), tn_update_op.eval())
self.assertAllEqual((2, 5, 7), tn.eval())
+ @test_util.run_deprecated_v1
def testWeighted(self):
predictions = constant_op.constant(((0.9, 0.2, 0.8, 0.1),
(0.2, 0.9, 0.7, 0.6),
@@ -4226,12 +4446,14 @@ class TruePositivesTest(test.TestCase):
np.random.seed(1)
ops.reset_default_graph()
+ @test_util.run_deprecated_v1
def testVars(self):
metrics.true_positives(
labels=(0, 1, 0, 1),
predictions=(0, 0, 1, 1))
_assert_metric_variables(self, ('true_positives/count:0',))
+ @test_util.run_deprecated_v1
def testUnweighted(self):
labels = constant_op.constant(((0, 1, 0, 1, 0),
(0, 0, 1, 1, 1),
@@ -4250,6 +4472,7 @@ class TruePositivesTest(test.TestCase):
self.assertAllClose(7., tn_update_op.eval())
self.assertAllClose(7., tn.eval())
+ @test_util.run_deprecated_v1
def testWeighted(self):
labels = constant_op.constant(((0, 1, 0, 1, 0),
(0, 0, 1, 1, 1),
@@ -4276,6 +4499,7 @@ class TruePositivesAtThresholdsTest(test.TestCase):
np.random.seed(1)
ops.reset_default_graph()
+ @test_util.run_deprecated_v1
def testVars(self):
metrics.true_positives_at_thresholds(
predictions=array_ops.ones((10, 1)),
@@ -4283,6 +4507,7 @@ class TruePositivesAtThresholdsTest(test.TestCase):
thresholds=[0.15, 0.5, 0.85])
_assert_metric_variables(self, ('true_positives/true_positives:0',))
+ @test_util.run_deprecated_v1
def testUnweighted(self):
predictions = constant_op.constant(((0.9, 0.2, 0.8, 0.1),
(0.2, 0.9, 0.7, 0.6),
@@ -4299,6 +4524,7 @@ class TruePositivesAtThresholdsTest(test.TestCase):
self.assertAllEqual((3, 1, 0), tp_update_op.eval())
self.assertAllEqual((3, 1, 0), tp.eval())
+ @test_util.run_deprecated_v1
def testWeighted(self):
predictions = constant_op.constant(((0.9, 0.2, 0.8, 0.1),
(0.2, 0.9, 0.7, 0.6),
diff --git a/tensorflow/python/kernel_tests/morphological_ops_test.py b/tensorflow/python/kernel_tests/morphological_ops_test.py
index 4ee04209ccb..f54aaf30d0a 100644
--- a/tensorflow/python/kernel_tests/morphological_ops_test.py
+++ b/tensorflow/python/kernel_tests/morphological_ops_test.py
@@ -21,6 +21,7 @@ from __future__ import print_function
import numpy as np
from tensorflow.python.framework import constant_op
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import nn_ops
import tensorflow.python.ops.nn_grad # pylint: disable=unused-import
@@ -291,6 +292,7 @@ class DilationTest(test.TestCase):
padding="SAME",
use_gpu=use_gpu)
+ @test_util.run_deprecated_v1
def testDilationGrad(self):
for use_gpu in True, False:
self._testDilationGradValidPadding_1x1x1(use_gpu)
@@ -566,6 +568,7 @@ class ErosionTest(test.TestCase):
padding="SAME",
use_gpu=use_gpu)
+ @test_util.run_deprecated_v1
def testErosionGrad(self):
for use_gpu in True, False:
self._testErosionGradValidPadding_1x1x1(use_gpu)
diff --git a/tensorflow/python/kernel_tests/neon_depthwise_conv_op_test.py b/tensorflow/python/kernel_tests/neon_depthwise_conv_op_test.py
index 87f1991aa78..380d2860da4 100644
--- a/tensorflow/python/kernel_tests/neon_depthwise_conv_op_test.py
+++ b/tensorflow/python/kernel_tests/neon_depthwise_conv_op_test.py
@@ -21,6 +21,7 @@ from __future__ import print_function
import numpy as np
from tensorflow.python.framework import constant_op
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import nn_impl
from tensorflow.python.ops import nn_ops
@@ -153,6 +154,7 @@ class DepthwiseConv2DTest(test.TestCase):
self.assertShapeEqual(native_result, conv_native)
self.assertShapeEqual(native_result, conv_interface)
+ @test_util.run_deprecated_v1
def testDepthwiseConv2D(self):
for index, (input_size, filter_size, _, stride,
padding) in enumerate(ConfigsToTest()):
@@ -216,6 +218,7 @@ class DepthwiseConv2DTest(test.TestCase):
self.assertAllClose(expected, np.ravel(value), 1e-5)
self.assertShapeEqual(value, conv)
+ @test_util.run_deprecated_v1
def testConv2D2x2Filter(self):
# The inputs look like this (it's a 3 x 2 matrix, each of depth 2):
#
diff --git a/tensorflow/python/kernel_tests/nth_element_op_test.py b/tensorflow/python/kernel_tests/nth_element_op_test.py
index 6cd49746710..4be78b2d5ca 100644
--- a/tensorflow/python/kernel_tests/nth_element_op_test.py
+++ b/tensorflow/python/kernel_tests/nth_element_op_test.py
@@ -22,6 +22,7 @@ import numpy as np
import tensorflow.python.ops.nn_grad # pylint: disable=unused-import
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import nn_ops
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradients_impl
@@ -111,17 +112,20 @@ class NthElementTest(test.TestCase):
self._testEnumerateN([10, 10, 10])
self._testEnumerateN([10, 10, 10, 10])
+ @test_util.run_deprecated_v1
def testInvalidInput(self):
with self.assertRaisesRegexp(ValueError,
"at least rank 1 but is rank 0"):
nn_ops.nth_element(5, 0)
+ @test_util.run_deprecated_v1
def testInvalidInputAtEval(self):
with self.session(use_gpu=False):
v = array_ops.placeholder(dtype=dtypes.float32)
with self.assertRaisesOpError("Input must be >= 1-D"):
nn_ops.nth_element(v, 0).eval(feed_dict={v: 5.0})
+ @test_util.run_deprecated_v1
def testInvalidN(self):
with self.assertRaisesRegexp(ValueError,
"non-negative but is -1"):
@@ -130,6 +134,7 @@ class NthElementTest(test.TestCase):
"scalar but has rank 1"):
nn_ops.nth_element([5, 6, 3], [1])
+ @test_util.run_deprecated_v1
def testInvalidNAtEval(self):
inputs = [[0.1, 0.2], [0.3, 0.4]]
with self.session(use_gpu=False):
@@ -138,12 +143,14 @@ class NthElementTest(test.TestCase):
with self.assertRaisesOpError("Need n >= 0, got -7"):
values.eval(feed_dict={n: -7})
+ @test_util.run_deprecated_v1
def testNTooLarge(self):
inputs = [[0.1, 0.2], [0.3, 0.4]]
with self.assertRaisesRegexp(ValueError,
"must have last dimension > n = 2"):
nn_ops.nth_element(inputs, 2)
+ @test_util.run_deprecated_v1
def testNTooLargeAtEval(self):
inputs = [[0.1, 0.2], [0.3, 0.4]]
with self.session(use_gpu=False):
@@ -152,6 +159,7 @@ class NthElementTest(test.TestCase):
with self.assertRaisesOpError(r"Input must have at least n\+1 columns"):
values.eval(feed_dict={n: 2})
+ @test_util.run_deprecated_v1
def testGradients(self):
with self.session(use_gpu=False) as sess:
inputs = array_ops.placeholder(dtypes.float32, shape=[3, 5])
diff --git a/tensorflow/python/kernel_tests/numerics_test.py b/tensorflow/python/kernel_tests/numerics_test.py
index e3210dcddc4..5751f3fe767 100644
--- a/tensorflow/python/kernel_tests/numerics_test.py
+++ b/tensorflow/python/kernel_tests/numerics_test.py
@@ -66,6 +66,7 @@ class VerifyTensorAllFiniteTest(test.TestCase):
class NumericsTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testInf(self):
with self.session(graph=ops.Graph()):
t1 = constant_op.constant(1.0)
@@ -76,6 +77,7 @@ class NumericsTest(test.TestCase):
with self.assertRaisesOpError("Inf"):
self.evaluate(a)
+ @test_util.run_deprecated_v1
def testNaN(self):
with self.session(graph=ops.Graph()):
t1 = constant_op.constant(0.0)
@@ -86,6 +88,7 @@ class NumericsTest(test.TestCase):
with self.assertRaisesOpError("NaN"):
self.evaluate(a)
+ @test_util.run_deprecated_v1
def testBoth(self):
with self.session(graph=ops.Graph()):
t1 = constant_op.constant([1.0, 0.0])
@@ -104,6 +107,7 @@ class NumericsTest(test.TestCase):
self.assertAllEqual(np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]]), value)
self.assertEqual([2, 3], checked.get_shape())
+ @test_util.run_deprecated_v1
def testControlFlowCond(self):
predicate = array_ops.placeholder(dtypes.bool, shape=[])
_ = control_flow_ops.cond(predicate,
@@ -116,6 +120,7 @@ class NumericsTest(test.TestCase):
r"or `tf.while_loop\(\)`\."):
numerics.add_check_numerics_ops()
+ @test_util.run_deprecated_v1
def testControlFlowWhile(self):
predicate = array_ops.placeholder(dtypes.bool, shape=[])
_ = control_flow_ops.while_loop(lambda _: predicate,
diff --git a/tensorflow/python/kernel_tests/pad_op_test.py b/tensorflow/python/kernel_tests/pad_op_test.py
index 6fe98d2559a..7b1b054ae06 100644
--- a/tensorflow/python/kernel_tests/pad_op_test.py
+++ b/tensorflow/python/kernel_tests/pad_op_test.py
@@ -23,6 +23,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradient_checker
from tensorflow.python.platform import test
@@ -116,6 +117,7 @@ class PadOpTest(test.TestCase):
self._testGradient(np_inputs, paddings, mode=mode,
constant_values=constant_values)
+ @test_util.run_deprecated_v1
def testInputDims(self):
with self.session(use_gpu=True):
with self.assertRaises(ValueError):
@@ -124,6 +126,7 @@ class PadOpTest(test.TestCase):
array_ops.reshape(
[1, 2], shape=[1, 2]))
+ @test_util.run_deprecated_v1
def testPaddingsDim(self):
with self.session(use_gpu=True):
with self.assertRaises(ValueError):
@@ -132,6 +135,7 @@ class PadOpTest(test.TestCase):
array_ops.reshape(
[1, 2], shape=[2]))
+ @test_util.run_deprecated_v1
def testPaddingsDim2(self):
with self.session(use_gpu=True):
with self.assertRaises(ValueError):
@@ -140,6 +144,7 @@ class PadOpTest(test.TestCase):
array_ops.reshape(
[1, 2], shape=[2, 1]))
+ @test_util.run_deprecated_v1
def testPaddingsDim3(self):
with self.session(use_gpu=True):
with self.assertRaises(ValueError):
@@ -148,6 +153,7 @@ class PadOpTest(test.TestCase):
array_ops.reshape(
[1, 2], shape=[1, 2]))
+ @test_util.run_deprecated_v1
def testPaddingsDim4(self):
with self.session(use_gpu=True):
with self.assertRaises(ValueError):
@@ -156,6 +162,7 @@ class PadOpTest(test.TestCase):
array_ops.reshape(
[1, 2, 3, 4, 5, 6], shape=[3, 2]))
+ @test_util.run_deprecated_v1
def testPaddingsNonNegative(self):
with self.session(use_gpu=True):
with self.assertRaisesRegexp(ValueError, "must be non-negative"):
@@ -164,6 +171,7 @@ class PadOpTest(test.TestCase):
constant_op.constant(
[-1, 0], shape=[1, 2]))
+ @test_util.run_deprecated_v1
def testPaddingsNonNegative2(self):
with self.session(use_gpu=True):
with self.assertRaisesRegexp(ValueError, "must be non-negative"):
@@ -223,6 +231,7 @@ class PadOpTest(test.TestCase):
np.random.randint(-100, 100, (4, 2, 1, 3)).astype(t),
[[0, 0], [0, 0], [0, 0], [0, 0]], -123)
+ @test_util.run_deprecated_v1
def testFloatTypes(self):
for t in [np.float32, np.float64]:
self._testAll(np.random.rand(2, 5).astype(t), [[1, 0], [2, 0]], 0.0)
@@ -261,6 +270,7 @@ class PadOpTest(test.TestCase):
[[b"Hello", b"World", b"World"], [b"Hello", b"World", b"World"],
[b"Goodnight", b"Moon", b"Moon"]], self.evaluate(symmetric))
+ @test_util.run_deprecated_v1
def testShapeFunctionEdgeCases(self):
# Unknown paddings shape.
inp = constant_op.constant(0.0, shape=[4, 4, 4, 4])
@@ -277,6 +287,7 @@ class PadOpTest(test.TestCase):
padded = array_ops.pad(inp, array_ops.placeholder(dtypes.int32))
self.assertAllEqual(None, padded.get_shape().ndims)
+ @test_util.run_deprecated_v1
def testPartialShapeInformation(self):
unknown = array_ops.placeholder(dtypes.int32)
@@ -341,6 +352,7 @@ class PadOpTest(test.TestCase):
self.assertAllEqual(inp, out)
self.assertShapeEqual(inp, tf_val)
+ @test_util.run_deprecated_v1
def testCollapseAdjacentNonPaddedDimensions(self):
# pyformat: disable
paddings_values = [[[0, 0], [0, 0], [0, 0], [0, 1]],
diff --git a/tensorflow/python/kernel_tests/parameterized_truncated_normal_op_test.py b/tensorflow/python/kernel_tests/parameterized_truncated_normal_op_test.py
index c9221f8c209..f87f5170539 100644
--- a/tensorflow/python/kernel_tests/parameterized_truncated_normal_op_test.py
+++ b/tensorflow/python/kernel_tests/parameterized_truncated_normal_op_test.py
@@ -29,6 +29,7 @@ from tensorflow.core.protobuf import config_pb2
from tensorflow.python.client import session
from tensorflow.python.framework import ops
from tensorflow.python.framework import random_seed
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import control_flow_ops
from tensorflow.python.ops import random_ops
from tensorflow.python.platform import test
@@ -166,30 +167,39 @@ class ParameterizedTruncatedNormalTest(test.TestCase):
except ImportError as e:
tf_logging.warn("Cannot test truncated normal op: %s" % str(e))
+ @test_util.run_deprecated_v1
def testDefaults(self):
self.validateMoments([10**5], 0.0, 1.0, -2.0, 2.0)
+ @test_util.run_deprecated_v1
def testShifted(self):
self.validateMoments([10**5], -1.0, 1.0, -2.0, 2.0)
+ @test_util.run_deprecated_v1
def testRightTail(self):
self.validateMoments([10**5], 0.0, 1.0, 4.0, np.infty)
+ @test_util.run_deprecated_v1
def testLeftTail(self):
self.validateMoments([10**5], 0.0, 1.0, -np.infty, -4.0)
+ @test_util.run_deprecated_v1
def testLeftTailTwoSidedBounds(self):
self.validateMoments([10**5], 0.0, 1.0, -6.0, -3.0)
+ @test_util.run_deprecated_v1
def testTwoSidedLeftTailShifted(self):
self.validateKolmogorovSmirnov([10**5], 6.0, 1.0, -1.0, 1.0)
+ @test_util.run_deprecated_v1
def testRightTailShifted(self):
self.validateMoments([10**5], -5.0, 1.0, 2.0, np.infty)
+ @test_util.run_deprecated_v1
def testSmallStddev(self):
self.validateKolmogorovSmirnov([10**5], 0.0, 0.1, 0.05, 0.10)
+ @test_util.run_deprecated_v1
def testSamplingWithSmallStdDevFarFromBound(self):
sample_op = random_ops.parameterized_truncated_normal(
shape=(int(1e5),), means=0.8, stddevs=0.05, minvals=-1., maxvals=1.)
@@ -202,6 +212,7 @@ class ParameterizedTruncatedNormalTest(test.TestCase):
no_neg_samples = np.sum(samples < 0.)
self.assertEqual(no_neg_samples, 0.)
+ @test_util.run_deprecated_v1
def testSamplingAtRandnSwitchover(self):
# The randn sampler is used as the bounds are moved farther from the mean,
# and the probability of accepting a sample increases the farther the
diff --git a/tensorflow/python/kernel_tests/parse_single_example_op_test.py b/tensorflow/python/kernel_tests/parse_single_example_op_test.py
index 3f500872827..43c8fa4ab5c 100644
--- a/tensorflow/python/kernel_tests/parse_single_example_op_test.py
+++ b/tensorflow/python/kernel_tests/parse_single_example_op_test.py
@@ -29,6 +29,7 @@ from tensorflow.python.framework import errors_impl
from tensorflow.python.framework import ops
from tensorflow.python.framework import sparse_tensor
from tensorflow.python.framework import tensor_shape
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import parsing_ops
from tensorflow.python.platform import test
from tensorflow.python.platform import tf_logging
@@ -121,6 +122,7 @@ class ParseExampleTest(test.TestCase):
self.assertEqual(
tuple(out[k].dense_shape.get_shape().as_list()), (1,))
+ @test_util.run_deprecated_v1
def testEmptySerializedWithAllDefaults(self):
sparse_name = "st_a"
a_name = "a"
@@ -229,6 +231,7 @@ class ParseExampleTest(test.TestCase):
},
expected_err=(ValueError, "Missing shape for feature a"))
+ @test_util.run_deprecated_v1
def testSerializedContainingSparse(self):
original = [
example(features=features({
@@ -552,6 +555,7 @@ class ParseExampleTest(test.TestCase):
}
}, expected_output)
+ @test_util.run_deprecated_v1
def testSerializedContainingSparseAndSparseFeatureAndDenseWithNoDefault(self):
original = [
example(features=features({
@@ -618,6 +622,7 @@ class ParseExampleTest(test.TestCase):
},
expected_output)
+ @test_util.run_deprecated_v1
def testSerializedContainingSparseAndSparseFeatureWithReuse(self):
original = [
example(features=features({
@@ -658,6 +663,7 @@ class ParseExampleTest(test.TestCase):
}
}, expected_output)
+ @test_util.run_deprecated_v1
def testSerializedContainingVarLenDense(self):
aname = "a"
bname = "b"
@@ -869,6 +875,7 @@ class ParseSingleExampleTest(test.TestCase):
self.assertEqual(
tuple(out[k].dense_shape.get_shape().as_list()), (1,))
+ @test_util.run_deprecated_v1
def testSingleExampleWithSparseAndSparseFeatureAndDense(self):
original = example(features=features({
"c": float_feature([3, 4]),
diff --git a/tensorflow/python/kernel_tests/parsing_ops_test.py b/tensorflow/python/kernel_tests/parsing_ops_test.py
index 1f677103dc6..af76e09f393 100644
--- a/tensorflow/python/kernel_tests/parsing_ops_test.py
+++ b/tensorflow/python/kernel_tests/parsing_ops_test.py
@@ -33,6 +33,7 @@ from tensorflow.python.framework import errors_impl
from tensorflow.python.framework import ops
from tensorflow.python.framework import sparse_tensor
from tensorflow.python.framework import tensor_shape
+from tensorflow.python.framework import test_util
from tensorflow.python.framework import tensor_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import parsing_ops
@@ -121,6 +122,7 @@ class ParseExampleTest(test.TestCase):
self.assertEqual(
tuple(out[k].dense_shape.get_shape().as_list()), (2,))
+ @test_util.run_deprecated_v1
def testEmptySerializedWithAllDefaults(self):
sparse_name = "st_a"
a_name = "a"
@@ -243,6 +245,7 @@ class ParseExampleTest(test.TestCase):
},
expected_err=(ValueError, "Missing shape for feature a"))
+ @test_util.run_deprecated_v1
def testSerializedContainingSparse(self):
original = [
example(features=features({
@@ -571,6 +574,7 @@ class ParseExampleTest(test.TestCase):
}
}, expected_output)
+ @test_util.run_deprecated_v1
def testSerializedContainingSparseAndSparseFeatureAndDenseWithNoDefault(self):
expected_st_a = ( # indices, values, shape
np.empty((0, 2), dtype=np.int64), # indices
@@ -631,6 +635,7 @@ class ParseExampleTest(test.TestCase):
},
expected_output)
+ @test_util.run_deprecated_v1
def testSerializedContainingSparseAndSparseFeatureWithReuse(self):
expected_idx = ( # indices, values, shape
np.array([[0, 0], [0, 1], [1, 0], [1, 1]], dtype=np.int64),
@@ -740,6 +745,7 @@ class ParseExampleTest(test.TestCase):
for batch_size in (1, 10, 20, 100, 256):
self._testSerializedContainingVarLenDenseLargerBatch(batch_size)
+ @test_util.run_deprecated_v1
def testSerializedContainingVarLenDense(self):
aname = "a"
bname = "b"
@@ -962,6 +968,7 @@ class ParseSingleExampleTest(test.TestCase):
self.assertEqual(
tuple(out[k].dense_shape.get_shape().as_list()), (1,))
+ @test_util.run_deprecated_v1
def testSingleExampleWithSparseAndSparseFeatureAndDense(self):
original = example(
features=features({
@@ -1180,6 +1187,7 @@ class ParseSequenceExampleTest(test.TestCase):
expected_err=expected_err,
batch=True)
+ @test_util.run_deprecated_v1
def testSequenceExampleWithSparseAndDenseContext(self):
original = sequence_example(
context=features({
@@ -1223,6 +1231,7 @@ class ParseSequenceExampleTest(test.TestCase):
},
expected_context_values=expected_context_output)
+ @test_util.run_deprecated_v1
def testSequenceExampleWithMultipleSizeFeatureLists(self):
original = sequence_example(
feature_lists=feature_lists({
@@ -1286,6 +1295,7 @@ class ParseSequenceExampleTest(test.TestCase):
},
expected_feat_list_values=expected_feature_list_output)
+ @test_util.run_deprecated_v1
def testSequenceExampleWithoutDebugName(self):
original = sequence_example(
feature_lists=feature_lists({
@@ -1343,6 +1353,7 @@ class ParseSequenceExampleTest(test.TestCase):
},
expected_feat_list_values=expected_feature_list_output)
+ @test_util.run_deprecated_v1
def testSequenceExampleWithSparseAndDenseFeatureLists(self):
original = sequence_example(
feature_lists=feature_lists({
@@ -1401,6 +1412,7 @@ class ParseSequenceExampleTest(test.TestCase):
},
expected_feat_list_values=expected_feature_list_output)
+ @test_util.run_deprecated_v1
def testSequenceExampleWithEmptyFeatureInFeatureLists(self):
original = sequence_example(
feature_lists=feature_lists({
@@ -1541,6 +1553,7 @@ class ParseSequenceExampleTest(test.TestCase):
" feature_list_dense_missing_assumed_empty or"
" feature_list_dense_defaults?"))
+ @test_util.run_deprecated_v1
def testSequenceExampleBatch(self):
first = sequence_example(
feature_lists=feature_lists({
@@ -1695,6 +1708,7 @@ class DecodeJSONExampleTest(test.TestCase):
})),
])
+ @test_util.run_deprecated_v1
def testInvalidSyntax(self):
with self.cached_session() as sess:
json_tensor = constant_op.constant(["{]"])
@@ -1705,6 +1719,7 @@ class DecodeJSONExampleTest(test.TestCase):
class ParseTensorOpTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testToFloat32(self):
with self.cached_session():
expected = np.random.rand(3, 4, 5).astype(np.float32)
@@ -1718,6 +1733,7 @@ class ParseTensorOpTest(test.TestCase):
self.assertAllEqual(expected, result)
+ @test_util.run_deprecated_v1
def testToUint8(self):
with self.cached_session():
expected = np.random.rand(3, 4, 5).astype(np.uint8)
@@ -1731,6 +1747,7 @@ class ParseTensorOpTest(test.TestCase):
self.assertAllEqual(expected, result)
+ @test_util.run_deprecated_v1
def testTypeMismatch(self):
with self.cached_session():
expected = np.random.rand(3, 4, 5).astype(np.uint8)
@@ -1744,6 +1761,7 @@ class ParseTensorOpTest(test.TestCase):
r"\(uint16\)"):
tensor.eval(feed_dict={serialized: tensor_proto.SerializeToString()})
+ @test_util.run_deprecated_v1
def testInvalidInput(self):
with self.cached_session():
serialized = array_ops.placeholder(dtypes.string)
diff --git a/tensorflow/python/kernel_tests/partitioned_variables_test.py b/tensorflow/python/kernel_tests/partitioned_variables_test.py
index 0c046561969..48655391fa7 100644
--- a/tensorflow/python/kernel_tests/partitioned_variables_test.py
+++ b/tensorflow/python/kernel_tests/partitioned_variables_test.py
@@ -26,6 +26,7 @@ from six.moves import xrange # pylint: disable=redefined-builtin
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import init_ops
from tensorflow.python.ops import partitioned_variables
@@ -322,6 +323,7 @@ class PartitionedVariablesTestCase(test.TestCase):
for i in xrange(len(expected_specs)):
self.assertEquals(expected_specs[i], slices[i]._save_slice_info.spec)
+ @test_util.run_deprecated_v1
def testVecConstantInit(self):
with self.cached_session():
rnd_par = constant_op.constant([1, 2, 3, 4])
@@ -333,6 +335,7 @@ class PartitionedVariablesTestCase(test.TestCase):
self.assertEqual([dtypes.int32] * 4, [v.dtype.base_dtype for v in vs])
self._TestSaveSpec(vs, ["4 0,1", "4 1,1", "4 2,1", "4 3,1"])
+ @test_util.run_deprecated_v1
def testConstantInit(self):
with self.cached_session():
rnd_par = constant_op.constant([[1, 2, 3, 4], [5, 6, 7, 8]])
@@ -401,12 +404,15 @@ class PartitionedVariablesTestCase(test.TestCase):
self.assertEqual(var2_name + "/part_0:0", vs2[0].name)
self.assertEqual(var2_name + "/part_1:0", vs2[1].name)
+ @test_util.run_deprecated_v1
def testName(self):
self._testNameHelper(use_resource=False)
+ @test_util.run_deprecated_v1
def testResourceName(self):
self._testNameHelper(use_resource=True)
+ @test_util.run_deprecated_v1
def testRandomInitValue(self):
with self.cached_session():
rnd = variables.Variable(random_ops.random_uniform([200, 40]))
@@ -424,6 +430,7 @@ class PartitionedVariablesTestCase(test.TestCase):
"200 40 0,200:36,4"
])
+ @test_util.run_deprecated_v1
def testRandomInitUnevenPartitions(self):
with self.cached_session():
rnd = variables.Variable(
@@ -462,6 +469,7 @@ class PartitionedVariablesTestCase(test.TestCase):
if i < len(save_specs):
self._TestSaveSpec(vs, save_specs[i])
+ @test_util.run_deprecated_v1
def testDegenerate(self):
with self.cached_session():
rnd = variables.Variable(random_ops.random_uniform([10, 43]))
@@ -473,6 +481,7 @@ class PartitionedVariablesTestCase(test.TestCase):
self.assertAllClose(rnd, val)
self._TestSaveSpec(vs, ["10 43 0,10:0,43"])
+ @test_util.run_deprecated_v1
def testSliceSizeOne(self):
with self.cached_session():
rnd = variables.Variable(random_ops.random_uniform([10, 43]))
@@ -488,6 +497,7 @@ class PartitionedVariablesTestCase(test.TestCase):
"10 43 6,1:0,43", "10 43 7,1:0,43", "10 43 8,1:0,43", "10 43 9,1:0,43"
])
+ @test_util.run_deprecated_v1
def testIotaInitializer(self):
self.assertAllClose([0., 1., 2., 3.], _IotaInitializer([4]))
self.assertAllClose([[0., 1.], [0., 10.], [0., 100.], [0., 1000.]],
@@ -503,6 +513,7 @@ class PartitionedVariablesTestCase(test.TestCase):
self.assertAllClose(slice0 + slice1 + slice2, val)
self._TestSaveSpec(vs, ["13 5 0,5:0,5", "13 5 5,4:0,5", "13 5 9,4:0,5"])
+ @test_util.run_deprecated_v1
def testRandomInitializer(self):
# Sanity check that the slices uses a different seed when using a random
# initializer function.
@@ -546,6 +557,7 @@ class PartitionedVariablesTestCase(test.TestCase):
partitioned_variables.create_partitioned_variables(
[10, 43], [1, 50], rnd.initialized_value())
+ @test_util.run_deprecated_v1
def testControlDepsNone(self):
with self.cached_session() as session:
c = constant_op.constant(1.0)
@@ -572,6 +584,7 @@ class PartitionedVariablesTestCase(test.TestCase):
for op in reading_ops:
self.assertEqual([], op.control_inputs)
+ @test_util.run_deprecated_v1
def testConcat(self):
with self.cached_session() as session:
var_x = variable_scope.get_variable(
diff --git a/tensorflow/python/kernel_tests/pool_test.py b/tensorflow/python/kernel_tests/pool_test.py
index 92016a49a27..78e786f01ca 100644
--- a/tensorflow/python/kernel_tests/pool_test.py
+++ b/tensorflow/python/kernel_tests/pool_test.py
@@ -24,6 +24,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import nn_ops
import tensorflow.python.ops.nn_grad # pylint: disable=unused-import
@@ -301,6 +302,7 @@ class PoolingTest(test.TestCase):
err_tolerance = 1e-2
self.assertLess(err, err_tolerance)
+ @test_util.run_deprecated_v1
def testGradient1D(self):
with self.session(use_gpu=test.is_gpu_available()):
for padding in ["SAME", "VALID"]:
@@ -327,6 +329,7 @@ class PoolingTest(test.TestCase):
dilation_rate=[1],
strides=strides)
+ @test_util.run_deprecated_v1
def testGradient2D(self):
with self.session(use_gpu=test.is_gpu_available()):
for padding in ["SAME", "VALID"]:
@@ -353,6 +356,7 @@ class PoolingTest(test.TestCase):
dilation_rate=[1, 1],
strides=strides)
+ @test_util.run_deprecated_v1
def testGradient3D(self):
with self.session(use_gpu=test.is_gpu_available()):
for padding in ["SAME", "VALID"]:
diff --git a/tensorflow/python/kernel_tests/pooling_ops_3d_test.py b/tensorflow/python/kernel_tests/pooling_ops_3d_test.py
index a8e962bc3a6..24fb51fc477 100644
--- a/tensorflow/python/kernel_tests/pooling_ops_3d_test.py
+++ b/tensorflow/python/kernel_tests/pooling_ops_3d_test.py
@@ -294,6 +294,7 @@ class PoolingTest(test.TestCase):
use_gpu=use_gpu,
**kwargs)
+ @test_util.run_deprecated_v1
def testMaxPoolGradValidPadding1_1_3d(self):
self._ConstructAndTestGradient(
nn_ops.max_pool3d,
@@ -303,6 +304,7 @@ class PoolingTest(test.TestCase):
strides=(1, 1, 1),
padding="VALID")
+ @test_util.run_deprecated_v1
def testMaxPoolGradValidPadding2_1_6_3d(self):
self._ConstructAndTestGradient(
nn_ops.max_pool3d,
@@ -312,6 +314,7 @@ class PoolingTest(test.TestCase):
strides=(1, 1, 1),
padding="VALID")
+ @test_util.run_deprecated_v1
def testMaxPoolGradValidPadding2_1_7_3d(self):
self._ConstructAndTestGradient(
nn_ops.max_pool3d,
@@ -321,6 +324,7 @@ class PoolingTest(test.TestCase):
strides=(1, 1, 1),
padding="VALID")
+ @test_util.run_deprecated_v1
def testMaxPoolGradValidPadding1_2_3d(self):
self._ConstructAndTestGradient(
nn_ops.max_pool3d,
@@ -330,6 +334,7 @@ class PoolingTest(test.TestCase):
strides=(2, 2, 2),
padding="VALID")
+ @test_util.run_deprecated_v1
def testMaxPoolGradValidPadding2_2_3d(self):
self._ConstructAndTestGradient(
nn_ops.max_pool3d,
@@ -339,6 +344,7 @@ class PoolingTest(test.TestCase):
strides=(2, 2, 2),
padding="VALID")
+ @test_util.run_deprecated_v1
def testMaxPoolGradSamePadding1_1_3d(self):
self._ConstructAndTestGradient(
nn_ops.max_pool3d,
@@ -348,6 +354,7 @@ class PoolingTest(test.TestCase):
strides=(1, 1, 1),
padding="SAME")
+ @test_util.run_deprecated_v1
def testMaxPoolGradSamePadding1_2_3d(self):
self._ConstructAndTestGradient(
nn_ops.max_pool3d,
@@ -357,6 +364,7 @@ class PoolingTest(test.TestCase):
strides=(2, 2, 2),
padding="SAME")
+ @test_util.run_deprecated_v1
def testMaxPoolGradSamePadding2_1_3d(self):
self._ConstructAndTestGradient(
nn_ops.max_pool3d,
@@ -366,6 +374,7 @@ class PoolingTest(test.TestCase):
strides=(1, 1, 1),
padding="SAME")
+ @test_util.run_deprecated_v1
def testMaxPoolGradSamePadding2_2_3d(self):
self._ConstructAndTestGradient(
nn_ops.max_pool3d,
@@ -375,6 +384,7 @@ class PoolingTest(test.TestCase):
strides=(2, 2, 2),
padding="SAME")
+ @test_util.run_deprecated_v1
def testMaxPoolGradSamePadding3_1_3d(self):
self._ConstructAndTestGradient(
nn_ops.max_pool3d,
@@ -384,6 +394,7 @@ class PoolingTest(test.TestCase):
strides=(1, 1, 1),
padding="SAME")
+ @test_util.run_deprecated_v1
def testAvgPoolGradValidPadding1_1_3d(self):
self._ConstructAndTestGradient(
nn_ops.avg_pool3d,
@@ -393,6 +404,7 @@ class PoolingTest(test.TestCase):
strides=(1, 1, 1),
padding="VALID")
+ @test_util.run_deprecated_v1
def testAvgPoolGradValidPadding1_2_3d(self):
self._ConstructAndTestGradient(
nn_ops.avg_pool3d,
@@ -402,6 +414,7 @@ class PoolingTest(test.TestCase):
strides=(2, 2, 2),
padding="VALID")
+ @test_util.run_deprecated_v1
def testAvgPoolGradValidPadding2_1_3d(self):
self._ConstructAndTestGradient(
nn_ops.avg_pool3d,
@@ -411,6 +424,7 @@ class PoolingTest(test.TestCase):
strides=(1, 1, 1),
padding="VALID")
+ @test_util.run_deprecated_v1
def testAvgPoolGradValidPadding2_2_3d(self):
self._ConstructAndTestGradient(
nn_ops.avg_pool3d,
@@ -420,6 +434,7 @@ class PoolingTest(test.TestCase):
strides=(2, 2, 2),
padding="VALID")
+ @test_util.run_deprecated_v1
def testAvgPoolGradSamePadding1_1_3d(self):
self._ConstructAndTestGradient(
nn_ops.avg_pool3d,
@@ -429,6 +444,7 @@ class PoolingTest(test.TestCase):
strides=(1, 1, 1),
padding="SAME")
+ @test_util.run_deprecated_v1
def testAvgPoolGradSamePadding1_2_3d(self):
self._ConstructAndTestGradient(
nn_ops.avg_pool3d,
@@ -438,6 +454,7 @@ class PoolingTest(test.TestCase):
strides=(2, 2, 2),
padding="SAME")
+ @test_util.run_deprecated_v1
def testAvgPoolGradSamePadding2_1_3d(self):
self._ConstructAndTestGradient(
nn_ops.avg_pool3d,
@@ -447,6 +464,7 @@ class PoolingTest(test.TestCase):
strides=(1, 1, 1),
padding="SAME")
+ @test_util.run_deprecated_v1
def testAvgPoolGradSamePadding2_2_3d(self):
self._ConstructAndTestGradient(
nn_ops.avg_pool3d,
@@ -456,6 +474,7 @@ class PoolingTest(test.TestCase):
strides=(2, 2, 2),
padding="SAME")
+ @test_util.run_deprecated_v1
def testAvgPoolGradSamePadding3_1_3d(self):
self._ConstructAndTestGradient(
nn_ops.avg_pool3d,
diff --git a/tensorflow/python/kernel_tests/pooling_ops_test.py b/tensorflow/python/kernel_tests/pooling_ops_test.py
index 81222719f2a..c33b59bb99b 100644
--- a/tensorflow/python/kernel_tests/pooling_ops_test.py
+++ b/tensorflow/python/kernel_tests/pooling_ops_test.py
@@ -384,6 +384,7 @@ class PoolingTest(test.TestCase):
expected=[],
use_gpu=use_gpu)
+ @test_util.run_deprecated_v1
def testAvgPooling(self):
for use_gpu in True, False:
self._testAvgPoolValidPadding(use_gpu)
@@ -577,6 +578,7 @@ class PoolingTest(test.TestCase):
expected=[],
use_gpu=use_gpu)
+ @test_util.run_deprecated_v1
def testMaxPooling(self):
for use_gpu in True, False:
self._testMaxPoolValidPadding(use_gpu)
@@ -588,6 +590,7 @@ class PoolingTest(test.TestCase):
self._testMaxPoolEmptyInput(use_gpu)
# Tests for DepthwiseMaxPooling on CPU only.
+ @test_util.run_deprecated_v1
def testDepthwiseMaxPool1x1DepthWindow1(self):
# input is:
# [1.0, ..., 10.0] along depth,
@@ -613,6 +616,7 @@ class PoolingTest(test.TestCase):
use_gpu=False,
v2=v2)
+ @test_util.run_deprecated_v1
def testDepthwiseMaxPool2x2DepthWindow3(self):
# input is:
#
@@ -639,6 +643,7 @@ class PoolingTest(test.TestCase):
use_gpu=False,
v2=v2)
+ @test_util.run_deprecated_v1
def testKernelSmallerThanStrideValid(self):
for use_gpu in [True, False]:
self._VerifyValues(
@@ -670,6 +675,7 @@ class PoolingTest(test.TestCase):
expected=[5, 8, 26, 29],
use_gpu=use_gpu)
+ @test_util.run_deprecated_v1
def testKernelSmallerThanStrideSame(self):
for use_gpu in [True, False]:
for pool_func in [nn_ops.max_pool, nn_ops.avg_pool]:
@@ -1167,6 +1173,7 @@ class PoolingTest(test.TestCase):
data_format=data_format,
use_gpu=use_gpu)
+ @test_util.run_deprecated_v1
def testMaxPoolGrad(self):
for (data_format, use_gpu) in GetTestConfigs():
self._testMaxPoolGradValidPadding1_1(data_format, use_gpu)
@@ -1497,6 +1504,7 @@ class PoolingTest(test.TestCase):
else:
del os.environ["TF_ENABLE_MAXPOOL_NANPROP"]
+ @test_util.run_deprecated_v1
def testMaxPoolGradDirect(self):
self._testMaxPoolGradDirect1_1()
self._testMaxPoolGradDirect1_2()
@@ -1616,6 +1624,7 @@ class PoolingTest(test.TestCase):
data_format=data_format,
use_gpu=use_gpu)
+ @test_util.run_deprecated_v1
def testMaxPoolGradGrad(self):
for (data_format, use_gpu) in GetTestConfigs():
self._testMaxPoolGradGradValidPadding1_1(data_format, use_gpu)
@@ -1649,6 +1658,7 @@ class PoolingTest(test.TestCase):
orig_input, orig_output, grad, [1, window_rows, window_cols, 1],
[1, row_stride, col_stride, 1], padding)
+ @test_util.run_deprecated_v1
def testAvgPoolGrad(self):
for (data_format, use_gpu) in GetTestConfigs():
self._testAvgPoolGradValidPadding1_1(data_format, use_gpu)
@@ -1778,6 +1788,7 @@ class PoolingTest(test.TestCase):
data_format=data_format,
use_gpu=use_gpu)
+ @test_util.run_deprecated_v1
def testShapeFunctionEdgeCases(self):
# All shapes unknown.
for pool_func in [nn_ops.max_pool, nn_ops.avg_pool]:
@@ -1806,6 +1817,7 @@ class PoolingTest(test.TestCase):
strides=[1, 1, 1, 1],
padding="SAME")
+ @test_util.run_deprecated_v1
def testOpEdgeCases(self):
with self.session(use_gpu=test.is_gpu_available()) as sess:
pool_funcs = [nn_ops.max_pool, nn_ops.avg_pool]
diff --git a/tensorflow/python/kernel_tests/py_func_test.py b/tensorflow/python/kernel_tests/py_func_test.py
index c9cbe44a7f3..1f3f02a9f01 100644
--- a/tensorflow/python/kernel_tests/py_func_test.py
+++ b/tensorflow/python/kernel_tests/py_func_test.py
@@ -514,6 +514,7 @@ class PyFuncTest(test.TestCase):
self.assertAllEqual(ret, [[3.0], [3.0], [3.0]])
@test_util.run_in_graph_and_eager_modes
+ @test_util.run_deprecated_v1
def testEagerExceptionHandling(self):
with test_util.device(use_gpu=True):
self._testExceptionHandling(
@@ -533,6 +534,7 @@ class PyFuncTest(test.TestCase):
self._testExceptionHandling(WeirdError, errors.UnknownError, eager=True)
@test_util.run_in_graph_and_eager_modes
+ @test_util.run_deprecated_v1
def testEagerReturningVariableRaisesError(self):
def return_variable():
return resource_variable_ops.ResourceVariable(0.0)
diff --git a/tensorflow/python/kernel_tests/qr_op_test.py b/tensorflow/python/kernel_tests/qr_op_test.py
index 305b5aa3645..0f2537b3711 100644
--- a/tensorflow/python/kernel_tests/qr_op_test.py
+++ b/tensorflow/python/kernel_tests/qr_op_test.py
@@ -21,6 +21,7 @@ from __future__ import print_function
import numpy as np
from tensorflow.python.framework import constant_op
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import linalg_ops
@@ -49,6 +50,7 @@ class QrOpTest(test.TestCase):
"Shape must be at least rank 2 but is rank 1"):
linalg_ops.qr(vector)
+ @test_util.run_deprecated_v1
def testConcurrentExecutesWithoutError(self):
with self.session(use_gpu=True) as sess:
all_ops = []
diff --git a/tensorflow/python/kernel_tests/random/multinomial_op_big_test.py b/tensorflow/python/kernel_tests/random/multinomial_op_big_test.py
index cab841741e7..576720528e2 100644
--- a/tensorflow/python/kernel_tests/random/multinomial_op_big_test.py
+++ b/tensorflow/python/kernel_tests/random/multinomial_op_big_test.py
@@ -23,6 +23,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import random_seed
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import random_ops
from tensorflow.python.platform import test
@@ -66,6 +67,7 @@ class MultinomialTest(test.TestCase):
counts_by_indices[index] = count
self.assertEqual(counts_by_indices[0], 100000000)
+ @test_util.run_deprecated_v1
def testLargeDynamicRange3(self):
random_seed.set_random_seed(10)
counts_by_indices = {}
diff --git a/tensorflow/python/kernel_tests/random/multinomial_op_test.py b/tensorflow/python/kernel_tests/random/multinomial_op_test.py
index 031a1c281c2..5d123307a8e 100644
--- a/tensorflow/python/kernel_tests/random/multinomial_op_test.py
+++ b/tensorflow/python/kernel_tests/random/multinomial_op_test.py
@@ -66,6 +66,7 @@ class MultinomialTest(test.TestCase):
logits, num_samples, output_dtype=output_dtype))
self.assertAllEqual([[1] * num_samples, [2] * num_samples], samples)
+ @test_util.run_deprecated_v1
def testOneOpMultipleStepsIndependent(self):
with test_util.use_gpu():
sample_op1, _ = self._make_ops(10)
@@ -88,6 +89,7 @@ class MultinomialTest(test.TestCase):
# 1 in 2^32 chance of this assertion failing.
self.assertFalse(np.equal(sample1, sample2).all())
+ @test_util.run_deprecated_v1
def testTwoOpsSameSeedDrawSameSequences(self):
with test_util.use_gpu():
sample_op1, sample_op2 = self._make_ops(1000, seed=1)
@@ -194,6 +196,7 @@ class MultinomialTest(test.TestCase):
array_ops.zeros([batch, classes]), samples))
self.assertEqual(x.shape, (batch, samples))
+ @test_util.run_deprecated_v1
def testEmptyClasses(self):
with test_util.use_gpu():
x = random_ops.multinomial(array_ops.zeros([5, 0]), 7)
diff --git a/tensorflow/python/kernel_tests/random/random_crop_test.py b/tensorflow/python/kernel_tests/random/random_crop_test.py
index 491d19d6a00..724bee07157 100644
--- a/tensorflow/python/kernel_tests/random/random_crop_test.py
+++ b/tensorflow/python/kernel_tests/random/random_crop_test.py
@@ -20,12 +20,14 @@ from __future__ import print_function
import numpy as np
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import random_ops
from tensorflow.python.platform import test
class RandomCropTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testNoOp(self):
# No random cropping is performed since the size is value.shape.
for shape in (2, 1, 1), (2, 1, 3), (4, 5, 3):
@@ -48,6 +50,7 @@ class RandomCropTest(test.TestCase):
self.assertAllEqual(y.shape, target)
self.assertTrue(tuple(y.ravel()) in value_set)
+ @test_util.run_deprecated_v1
def testRandomization(self):
# Run 1x1 crop num_samples times in an image and ensure that one finds each
# pixel 1/size of the time.
diff --git a/tensorflow/python/kernel_tests/random/random_gamma_test.py b/tensorflow/python/kernel_tests/random/random_gamma_test.py
index d18e3feb045..a5952a21968 100644
--- a/tensorflow/python/kernel_tests/random/random_gamma_test.py
+++ b/tensorflow/python/kernel_tests/random/random_gamma_test.py
@@ -26,6 +26,7 @@ from six.moves import xrange # pylint: disable=redefined-builtin
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
from tensorflow.python.framework import random_seed
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import random_ops
@@ -53,9 +54,11 @@ class RandomGammaTest(test.TestCase):
return func
+ @test_util.run_deprecated_v1
def testMomentsFloat32(self):
self._testMoments(dtypes.float32)
+ @test_util.run_deprecated_v1
def testMomentsFloat64(self):
self._testMoments(dtypes.float64)
@@ -208,6 +211,7 @@ class RandomGammaTest(test.TestCase):
sy = self._Sampler(1000, 0.0, 1.0, dt, use_gpu=use_gpu, seed=345)
self.assertAllEqual(sx(), sy())
+ @test_util.run_deprecated_v1
def testNoCSE(self):
"""CSE = constant subexpression eliminator.
@@ -222,6 +226,7 @@ class RandomGammaTest(test.TestCase):
diff = rnd2 - rnd1
self.assertGreater(np.linalg.norm(diff.eval()), 0.1)
+ @test_util.run_deprecated_v1
def testShape(self):
# Fully known shape.
rnd = random_ops.random_gamma([150], 2.0)
@@ -253,6 +258,7 @@ class RandomGammaTest(test.TestCase):
rnd = random_ops.random_gamma([50], array_ops.placeholder(dtypes.float32))
self.assertIs(None, rnd.get_shape().ndims)
+ @test_util.run_deprecated_v1
def testPositive(self):
n = int(10e3)
for dt in [dtypes.float16, dtypes.float32, dtypes.float64]:
diff --git a/tensorflow/python/kernel_tests/random/random_grad_test.py b/tensorflow/python/kernel_tests/random/random_grad_test.py
index d89056c485a..aac6eeac06a 100644
--- a/tensorflow/python/kernel_tests/random/random_grad_test.py
+++ b/tensorflow/python/kernel_tests/random/random_grad_test.py
@@ -22,6 +22,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradients_impl
from tensorflow.python.ops import math_ops
@@ -45,6 +46,7 @@ class AddLeadingUnitDimensionsTest(test.TestCase):
ret = random_grad.add_leading_unit_dimensions(1.0, 2)
self.assertAllEqual(ret.shape, [1, 1])
+ @test_util.run_deprecated_v1
def testUnknownShape(self):
x = array_ops.placeholder(dtypes.float32)
num_dimensions = array_ops.placeholder(dtypes.int32)
@@ -72,6 +74,7 @@ class RandomGammaGradTest(test.TestCase):
some statistical properties of the derivative.
"""
+ @test_util.run_deprecated_v1
def testGradientsShape(self):
shape = [2, 3]
alpha = array_ops.ones([2, 2])
@@ -81,6 +84,7 @@ class RandomGammaGradTest(test.TestCase):
self.assertAllEqual(grads_alpha.shape, alpha.shape)
self.assertAllEqual(grads_beta.shape, beta.shape)
+ @test_util.run_deprecated_v1
def testGradientsShapeWithOneSamplePerParameter(self):
shape = []
alpha = array_ops.ones([2, 2])
@@ -90,6 +94,7 @@ class RandomGammaGradTest(test.TestCase):
self.assertAllEqual(grads_alpha.shape, alpha.shape)
self.assertAllEqual(grads_beta.shape, beta.shape)
+ @test_util.run_deprecated_v1
def testGradientsUnknownShape(self):
shape = array_ops.placeholder(dtypes.int32)
alpha = array_ops.placeholder(dtypes.float32)
@@ -138,9 +143,11 @@ class RandomGammaGradTest(test.TestCase):
except ImportError as e:
tf_logging.warn("Cannot use special functions in a test: %s" % str(e))
+ @test_util.run_deprecated_v1
def testCompareToExplicitDerivativeFloat(self):
self._testCompareToExplicitDerivative(dtypes.float32)
+ @test_util.run_deprecated_v1
def testCompareToExplicitDerivativeDouble(self):
self._testCompareToExplicitDerivative(dtypes.float64)
@@ -182,12 +189,15 @@ class RandomGammaGradTest(test.TestCase):
self.assertAllClose(actual_val, expected_val, rtol=1e-3, atol=1e-3)
+ @test_util.run_deprecated_v1
def testCompareToImplicitDerivativeFloat(self):
self._testCompareToImplicitDerivative(dtypes.float32)
+ @test_util.run_deprecated_v1
def testCompareToImplicitDerivativeDouble(self):
self._testCompareToImplicitDerivative(dtypes.float64)
+ @test_util.run_deprecated_v1
def testAverageAlphaGradient(self):
"""Statistical test for the gradient.
@@ -207,6 +217,7 @@ class RandomGammaGradTest(test.TestCase):
dsample_dalpha_val = self.evaluate(dsample_dalpha)
self.assertAllClose(dsample_dalpha_val, [1.0] * 3, atol=1e-1, rtol=1e-1)
+ @test_util.run_deprecated_v1
def testQuadraticLoss(self):
"""Statistical test for the gradient.
diff --git a/tensorflow/python/kernel_tests/random/random_ops_test.py b/tensorflow/python/kernel_tests/random/random_ops_test.py
index 76618316b24..1384c3f446f 100644
--- a/tensorflow/python/kernel_tests/random/random_ops_test.py
+++ b/tensorflow/python/kernel_tests/random/random_ops_test.py
@@ -25,6 +25,7 @@ from tensorflow.python.eager import context
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
from tensorflow.python.framework import random_seed
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import random_ops
from tensorflow.python.ops import variables
@@ -92,6 +93,7 @@ class RandomNormalTest(RandomOpTestCommon):
# Checks that the CPU and GPU implementation returns the same results,
# given the same random seed
+ @test_util.run_deprecated_v1
def testCPUGPUMatch(self):
for dt in dtypes.float16, dtypes.float32, dtypes.float64:
results = {}
@@ -104,12 +106,14 @@ class RandomNormalTest(RandomOpTestCommon):
else:
self.assertAllClose(results[False], results[True], rtol=1e-6, atol=1e-6)
+ @test_util.run_deprecated_v1
def testSeed(self):
for dt in dtypes.float16, dtypes.float32, dtypes.float64:
sx = self._Sampler(1000, 0.0, 1.0, dt, use_gpu=True, seed=345)
sy = self._Sampler(1000, 0.0, 1.0, dt, use_gpu=True, seed=345)
self.assertAllEqual(sx(), sy())
+ @test_util.run_deprecated_v1
def testNoCSE(self):
for use_gpu in [False, True]:
with self.session(use_gpu=use_gpu):
@@ -119,12 +123,14 @@ class RandomNormalTest(RandomOpTestCommon):
diff = rnd2 - rnd1
self.assertTrue(np.linalg.norm(diff.eval()) > 0.1)
+ @test_util.run_deprecated_v1
def testSingleSessionNotConstant(self):
for use_gpu in [False, True]:
for dt in dtypes.float16, dtypes.float32, dtypes.float64:
self._testSingleSessionNotConstant(
random_ops.random_normal, 100, dt, 0.0, 1.0, use_gpu=use_gpu)
+ @test_util.run_deprecated_v1
def testSingleSessionOpSeedNotConstant(self):
for use_gpu in [False, True]:
for dt in dtypes.float16, dtypes.float32, dtypes.float64:
@@ -137,6 +143,7 @@ class RandomNormalTest(RandomOpTestCommon):
use_gpu=use_gpu,
op_seed=1345)
+ @test_util.run_deprecated_v1
def testSingleSessionGraphSeedNotConstant(self):
for use_gpu in [False, True]:
for dt in dtypes.float16, dtypes.float32, dtypes.float64:
@@ -185,6 +192,7 @@ class TruncatedNormalTest(test.TestCase):
# Checks that the CPU and GPU implementation returns the same results,
# given the same random seed
+ @test_util.run_deprecated_v1
def testCPUGPUMatch(self):
# Skip the test if there is no GPU.
if not test.is_gpu_available():
@@ -203,6 +211,7 @@ class TruncatedNormalTest(test.TestCase):
else:
self.assertAllClose(results[False], results[True], rtol=1e-6, atol=1e-6)
+ @test_util.run_deprecated_v1
def testSeed(self):
for dt in dtypes.float16, dtypes.float32, dtypes.float64:
sx = self._Sampler(1000, 0.0, 1.0, dt, use_gpu=True, seed=345)
@@ -219,6 +228,7 @@ class TruncatedNormalTest(test.TestCase):
print("std(x)", np.std(x), abs(np.std(x) / stddev - 0.85))
self.assertTrue(abs(np.std(x) / stddev - 0.85) < 0.04)
+ @test_util.run_deprecated_v1
def testLargeShape(self):
with self.session(use_gpu=True):
v = variables.Variable(
@@ -226,6 +236,7 @@ class TruncatedNormalTest(test.TestCase):
n = random_ops.truncated_normal(v.shape)
self.assertEqual([8589934592, 1], n.shape.as_list())
+ @test_util.run_deprecated_v1
def testNoCSE(self):
with self.session(use_gpu=True):
shape = [2, 3, 4]
@@ -287,6 +298,7 @@ class RandomUniformTest(RandomOpTestCommon):
print("count = ", count)
self.assertTrue(count < count_limit)
+ @test_util.run_deprecated_v1
def testUniformIntsWithInvalidShape(self):
for dtype in dtypes.int32, dtypes.int64:
with self.assertRaisesRegexp(
@@ -299,6 +311,7 @@ class RandomUniformTest(RandomOpTestCommon):
[1000], minval=1, maxval=[2, 3], dtype=dtype)
# Check that uniform ints actually follow a uniform distribution.
+ @test_util.run_deprecated_v1
def testUniformInts(self):
minv = -2
maxv = 15
@@ -331,6 +344,7 @@ class RandomUniformTest(RandomOpTestCommon):
# Checks that the CPU and GPU implementation returns the same results,
# given the same random seed
+ @test_util.run_deprecated_v1
def testCPUGPUMatch(self):
for dt in (dtypes.float16, dtypes.float32, dtypes.float64, dtypes.int32,
dtypes.int64):
@@ -342,6 +356,7 @@ class RandomUniformTest(RandomOpTestCommon):
results[use_gpu] = sampler()
self.assertAllEqual(results[False], results[True])
+ @test_util.run_deprecated_v1
def testSeed(self):
for dt in (dtypes.float16, dtypes.float32, dtypes.float64, dtypes.int32,
dtypes.int64):
@@ -350,6 +365,7 @@ class RandomUniformTest(RandomOpTestCommon):
sy = self._Sampler(1000, 0, 17, dtype=dt, use_gpu=True, seed=seed)
self.assertAllEqual(sx(), sy())
+ @test_util.run_deprecated_v1
def testNoCSE(self):
shape = [2, 3, 4]
for dtype in dtypes.float16, dtypes.float32, dtypes.int32:
@@ -359,6 +375,7 @@ class RandomUniformTest(RandomOpTestCommon):
diff = (rnd2 - rnd1).eval()
self.assertTrue(np.linalg.norm(diff) > 0.1)
+ @test_util.run_deprecated_v1
def testSingleSessionNotConstant(self):
for use_gpu in [False, True]:
for dt in (dtypes.float16, dtypes.float32, dtypes.float64, dtypes.int32,
@@ -366,6 +383,7 @@ class RandomUniformTest(RandomOpTestCommon):
self._testSingleSessionNotConstant(
random_ops.random_uniform, 100, dt, 0, 17, use_gpu=use_gpu)
+ @test_util.run_deprecated_v1
def testSingleSessionOpSeedNotConstant(self):
for use_gpu in [False, True]:
for dt in (dtypes.float16, dtypes.float32, dtypes.float64, dtypes.int32,
@@ -379,6 +397,7 @@ class RandomUniformTest(RandomOpTestCommon):
use_gpu=use_gpu,
op_seed=1345)
+ @test_util.run_deprecated_v1
def testSingleSessionGraphSeedNotConstant(self):
for use_gpu in [False, True]:
for dt in (dtypes.float16, dtypes.float32, dtypes.float64, dtypes.int32,
@@ -395,6 +414,7 @@ class RandomUniformTest(RandomOpTestCommon):
class RandomShapeTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testTruncatedNormal(self):
# Fully known shape.
rnd1 = random_ops.truncated_normal([1, 2, 3])
@@ -407,6 +427,7 @@ class RandomShapeTest(test.TestCase):
rnd3 = random_ops.truncated_normal(array_ops.placeholder(dtypes.int32))
self.assertIs(None, rnd3.get_shape().ndims)
+ @test_util.run_deprecated_v1
def testRandomNormal(self):
# Fully known shape.
rnd1 = random_ops.random_normal([1, 2, 3])
@@ -419,6 +440,7 @@ class RandomShapeTest(test.TestCase):
rnd3 = random_ops.random_normal(array_ops.placeholder(dtypes.int32))
self.assertIs(None, rnd3.get_shape().ndims)
+ @test_util.run_deprecated_v1
def testRandomUniform(self):
# Fully known shape.
rnd1 = random_ops.random_uniform([1, 2, 3])
diff --git a/tensorflow/python/kernel_tests/random/random_poisson_test.py b/tensorflow/python/kernel_tests/random/random_poisson_test.py
index 47c0858db74..0a6b004d682 100644
--- a/tensorflow/python/kernel_tests/random/random_poisson_test.py
+++ b/tensorflow/python/kernel_tests/random/random_poisson_test.py
@@ -23,6 +23,7 @@ from six.moves import xrange # pylint: disable=redefined-builtin
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import random_ops
from tensorflow.python.platform import test
@@ -104,6 +105,7 @@ class RandomPoissonTest(test.TestCase):
# Checks that the CPU and GPU implementation returns the same results,
# given the same random seed
+ @test_util.run_deprecated_v1
def testCPUGPUMatch(self):
for dt in _SUPPORTED_DTYPES:
results = {}
@@ -115,12 +117,14 @@ class RandomPoissonTest(test.TestCase):
else:
self.assertAllClose(results[False], results[True], rtol=1e-6, atol=1e-6)
+ @test_util.run_deprecated_v1
def testSeed(self):
for dt in dtypes.float16, dtypes.float32, dtypes.float64:
sx = self._Sampler(1000, 1.0, dt, use_gpu=True, seed=345)
sy = self._Sampler(1000, 1.0, dt, use_gpu=True, seed=345)
self.assertAllEqual(sx(), sy())
+ @test_util.run_deprecated_v1
def testNoCSE(self):
"""CSE = constant subexpression eliminator.
@@ -142,6 +146,7 @@ class RandomPoissonTest(test.TestCase):
self.assertEqual([0], rnd.get_shape().as_list())
self.assertAllClose(np.array([], dtype=np.float32), self.evaluate(rnd))
+ @test_util.run_deprecated_v1
def testShape(self):
# Fully known shape
rnd = random_ops.random_poisson(2.0, [150], seed=12345)
@@ -184,6 +189,7 @@ class RandomPoissonTest(test.TestCase):
seed=12345)
self.assertIs(None, rnd.get_shape().ndims)
+ @test_util.run_deprecated_v1
def testDTypeCombinationsV2(self):
"""Tests random_poisson_v2() for all supported dtype combinations."""
with self.cached_session():
diff --git a/tensorflow/python/kernel_tests/random/stateless_random_ops_test.py b/tensorflow/python/kernel_tests/random/stateless_random_ops_test.py
index 071d6c29984..898f38444b7 100644
--- a/tensorflow/python/kernel_tests/random/stateless_random_ops_test.py
+++ b/tensorflow/python/kernel_tests/random/stateless_random_ops_test.py
@@ -129,23 +129,29 @@ class StatelessOpsTest(test.TestCase):
yield (functools.partial(stateless.stateless_multinomial, **kwds),
functools.partial(random_ops.multinomial, **kwds))
+ @test_util.run_deprecated_v1
def testMatchFloat(self):
self._test_match(self._float_cases())
+ @test_util.run_deprecated_v1
def testMatchInt(self):
self._test_match(self._int_cases())
+ @test_util.run_deprecated_v1
def testMatchMultinomial(self):
self._test_match(self._multinomial_cases())
+ @test_util.run_deprecated_v1
def testDeterminismFloat(self):
self._test_determinism(
self._float_cases(shape_dtypes=(dtypes.int32, dtypes.int64)))
+ @test_util.run_deprecated_v1
def testDeterminismInt(self):
self._test_determinism(
self._int_cases(shape_dtypes=(dtypes.int32, dtypes.int64)))
+ @test_util.run_deprecated_v1
def testDeterminismMultinomial(self):
self._test_determinism(self._multinomial_cases())
diff --git a/tensorflow/python/kernel_tests/reader_ops_test.py b/tensorflow/python/kernel_tests/reader_ops_test.py
index a4a18c52194..43d15817e97 100644
--- a/tensorflow/python/kernel_tests/reader_ops_test.py
+++ b/tensorflow/python/kernel_tests/reader_ops_test.py
@@ -28,6 +28,7 @@ import zlib
from tensorflow.core.protobuf import config_pb2
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors_impl
+from tensorflow.python.framework import test_util
from tensorflow.python.lib.io import tf_record
from tensorflow.python.ops import data_flow_ops
from tensorflow.python.ops import io_ops
@@ -145,6 +146,7 @@ class IdentityReaderTest(test.TestCase):
self.assertAllEqual(expected, k)
self.assertAllEqual(expected, v)
+ @test_util.run_deprecated_v1
def testOneEpoch(self):
reader = io_ops.IdentityReader("test_reader")
work_completed = reader.num_work_units_completed()
@@ -178,6 +180,7 @@ class IdentityReaderTest(test.TestCase):
self.assertAllEqual(3, self.evaluate(produced))
self.assertAllEqual(0, self.evaluate(queued_length))
+ @test_util.run_deprecated_v1
def testMultipleEpochs(self):
reader = io_ops.IdentityReader("test_reader")
queue = data_flow_ops.FIFOQueue(99, [dtypes.string], shapes=())
@@ -198,6 +201,7 @@ class IdentityReaderTest(test.TestCase):
"\\(requested 1, current size 0\\)"):
self.evaluate([key, value])
+ @test_util.run_deprecated_v1
def testSerializeRestore(self):
reader = io_ops.IdentityReader("test_reader")
produced = reader.num_records_produced()
@@ -252,6 +256,7 @@ class IdentityReaderTest(test.TestCase):
"Could not parse state for IdentityReader 'test_reader'"):
self.evaluate(reader.restore_state(b"BOGUS" + state[5:]))
+ @test_util.run_deprecated_v1
def testReset(self):
reader = io_ops.IdentityReader("test_reader")
work_completed = reader.num_work_units_completed()
@@ -302,6 +307,7 @@ class WholeFileReaderTest(test.TestCase):
self.assertAllEqual(compat.as_bytes(self._filenames[index]), k)
self.assertAllEqual(self._content[index], v)
+ @test_util.run_deprecated_v1
def testOneEpoch(self):
reader = io_ops.WholeFileReader("test_reader")
queue = data_flow_ops.FIFOQueue(99, [dtypes.string], shapes=())
@@ -317,6 +323,7 @@ class WholeFileReaderTest(test.TestCase):
"\\(requested 1, current size 0\\)"):
self.evaluate([key, value])
+ @test_util.run_deprecated_v1
def testInfiniteEpochs(self):
reader = io_ops.WholeFileReader("test_reader")
queue = data_flow_ops.FIFOQueue(99, [dtypes.string], shapes=())
@@ -376,12 +383,15 @@ class TextLineReaderTest(test.TestCase):
"\\(requested 1, current size 0\\)"):
k, v = self.evaluate([key, value])
+ @test_util.run_deprecated_v1
def testOneEpochLF(self):
self._testOneEpoch(self._CreateFiles(crlf=False))
+ @test_util.run_deprecated_v1
def testOneEpochCRLF(self):
self._testOneEpoch(self._CreateFiles(crlf=True))
+ @test_util.run_deprecated_v1
def testSkipHeaderLines(self):
files = self._CreateFiles()
reader = io_ops.TextLineReader(skip_header_lines=1, name="test_reader")
@@ -562,6 +572,7 @@ class FixedLengthRecordReaderTest(TFCompressionTestCase):
"\\(requested 1, current size 0\\)"):
k, v = self.evaluate([key, value])
+ @test_util.run_deprecated_v1
def testOneEpoch(self):
for num_records in [0, 7]:
# gap_bytes=0: hop_bytes=0
@@ -570,6 +581,7 @@ class FixedLengthRecordReaderTest(TFCompressionTestCase):
files = self._CreateFiles(num_records, gap_bytes)
self._TestOneEpoch(files, num_records, gap_bytes)
+ @test_util.run_deprecated_v1
def testGzipOneEpoch(self):
for num_records in [0, 7]:
# gap_bytes=0: hop_bytes=0
@@ -578,6 +590,7 @@ class FixedLengthRecordReaderTest(TFCompressionTestCase):
files = self._CreateGzipFiles(num_records, gap_bytes)
self._TestOneEpoch(files, num_records, gap_bytes, encoding="GZIP")
+ @test_util.run_deprecated_v1
def testZlibOneEpoch(self):
for num_records in [0, 7]:
# gap_bytes=0: hop_bytes=0
@@ -586,17 +599,20 @@ class FixedLengthRecordReaderTest(TFCompressionTestCase):
files = self._CreateZlibFiles(num_records, gap_bytes)
self._TestOneEpoch(files, num_records, gap_bytes, encoding="ZLIB")
+ @test_util.run_deprecated_v1
def testOneEpochWithHopBytes(self):
for num_overlapped_records in [0, 2]:
files = self._CreateOverlappedRecordFiles(num_overlapped_records)
self._TestOneEpochWithHopBytes(files, num_overlapped_records)
+ @test_util.run_deprecated_v1
def testGzipOneEpochWithHopBytes(self):
for num_overlapped_records in [0, 2]:
files = self._CreateGzipOverlappedRecordFiles(num_overlapped_records,)
self._TestOneEpochWithHopBytes(
files, num_overlapped_records, encoding="GZIP")
+ @test_util.run_deprecated_v1
def testZlibOneEpochWithHopBytes(self):
for num_overlapped_records in [0, 2]:
files = self._CreateZlibOverlappedRecordFiles(num_overlapped_records)
@@ -609,6 +625,7 @@ class TFRecordReaderTest(TFCompressionTestCase):
def setUp(self):
super(TFRecordReaderTest, self).setUp()
+ @test_util.run_deprecated_v1
def testOneEpoch(self):
files = self._CreateFiles()
reader = io_ops.TFRecordReader(name="test_reader")
@@ -627,6 +644,7 @@ class TFRecordReaderTest(TFCompressionTestCase):
"\\(requested 1, current size 0\\)"):
k, v = self.evaluate([key, value])
+ @test_util.run_deprecated_v1
def testReadUpTo(self):
files = self._CreateFiles()
reader = io_ops.TFRecordReader(name="test_reader")
@@ -654,6 +672,7 @@ class TFRecordReaderTest(TFCompressionTestCase):
self.assertEqual(self._num_files * self._num_records, num_k)
self.assertEqual(self._num_files * self._num_records, num_v)
+ @test_util.run_deprecated_v1
def testReadZlibFiles(self):
options = tf_record.TFRecordOptions(TFRecordCompressionType.ZLIB)
files = self._CreateFiles(options)
@@ -670,6 +689,7 @@ class TFRecordReaderTest(TFCompressionTestCase):
self.assertTrue(compat.as_text(k).startswith("%s:" % files[i]))
self.assertAllEqual(self._Record(i, j), v)
+ @test_util.run_deprecated_v1
def testReadGzipFiles(self):
options = tf_record.TFRecordOptions(TFRecordCompressionType.GZIP)
files = self._CreateFiles(options)
@@ -689,6 +709,7 @@ class TFRecordReaderTest(TFCompressionTestCase):
class AsyncReaderTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testNoDeadlockFromQueue(self):
"""Tests that reading does not block main execution threads."""
config = config_pb2.ConfigProto(
@@ -737,6 +758,7 @@ class LMDBReaderTest(test.TestCase):
self.db_path = os.path.join(self.get_temp_dir(), "data.mdb")
shutil.copy(path, self.db_path)
+ @test_util.run_deprecated_v1
def testReadFromFile(self):
reader = io_ops.LMDBReader(name="test_read_from_file")
queue = data_flow_ops.FIFOQueue(99, [dtypes.string], shapes=())
@@ -754,6 +776,7 @@ class LMDBReaderTest(test.TestCase):
"\\(requested 1, current size 0\\)"):
k, v = self.evaluate([key, value])
+ @test_util.run_deprecated_v1
def testReadFromSameFile(self):
with self.cached_session() as sess:
reader1 = io_ops.LMDBReader(name="test_read_from_same_file1")
@@ -773,6 +796,7 @@ class LMDBReaderTest(test.TestCase):
coord.request_stop()
coord.join(threads)
+ @test_util.run_deprecated_v1
def testReadFromFolder(self):
reader = io_ops.LMDBReader(name="test_read_from_folder")
queue = data_flow_ops.FIFOQueue(99, [dtypes.string], shapes=())
@@ -790,6 +814,7 @@ class LMDBReaderTest(test.TestCase):
"\\(requested 1, current size 0\\)"):
k, v = self.evaluate([key, value])
+ @test_util.run_deprecated_v1
def testReadFromFileRepeatedly(self):
with self.cached_session() as sess:
reader = io_ops.LMDBReader(name="test_read_from_file_repeated")
diff --git a/tensorflow/python/kernel_tests/record_input_test.py b/tensorflow/python/kernel_tests/record_input_test.py
index 74020667d93..ad8188b372f 100644
--- a/tensorflow/python/kernel_tests/record_input_test.py
+++ b/tensorflow/python/kernel_tests/record_input_test.py
@@ -20,6 +20,7 @@ from __future__ import print_function
import os
+from tensorflow.python.framework import test_util
from tensorflow.python.framework.errors_impl import NotFoundError
from tensorflow.python.lib.io import tf_record
from tensorflow.python.ops import data_flow_ops
@@ -94,6 +95,7 @@ class RecordInputOpTest(test.TestCase):
self.assertEqual(self.evaluate(yield_op), b"0000000000")
+ @test_util.run_deprecated_v1
def testRecordInputEpochs(self):
files = 100
records_per_file = 100
@@ -140,6 +142,7 @@ class RecordInputOpTest(test.TestCase):
for _ in range(50):
self.evaluate(yield_op)
+ @test_util.run_deprecated_v1
def testEmptyGlob(self):
with self.cached_session() as sess:
record_input = data_flow_ops.RecordInput(file_pattern="foo")
@@ -148,6 +151,7 @@ class RecordInputOpTest(test.TestCase):
with self.assertRaises(NotFoundError):
self.evaluate(yield_op)
+ @test_util.run_deprecated_v1
def testBufferTooSmall(self):
files = 10
records_per_file = 10
diff --git a/tensorflow/python/kernel_tests/reduce_join_op_test.py b/tensorflow/python/kernel_tests/reduce_join_op_test.py
index c26e62738c1..49b6620779e 100644
--- a/tensorflow/python/kernel_tests/reduce_join_op_test.py
+++ b/tensorflow/python/kernel_tests/reduce_join_op_test.py
@@ -25,6 +25,7 @@ from six.moves import xrange # pylint: disable=redefined-builtin
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import string_ops
from tensorflow.python.platform import test
@@ -230,6 +231,7 @@ class ReduceJoinTest(UnicodeTestCase):
axis=1,
separator=" ")
+ @test_util.run_deprecated_v1
def testUnknownShape(self):
input_array = [["a"], ["b"]]
truth = ["ab"]
@@ -241,6 +243,7 @@ class ReduceJoinTest(UnicodeTestCase):
self.assertAllEqualUnicode(truth, output_array)
self.assertAllEqual(truth_shape, reduced.get_shape())
+ @test_util.run_deprecated_v1
def testUnknownIndices(self):
input_array = [["this", "is", "a", "test"],
["please", "do", "not", "panic"]]
@@ -297,6 +300,7 @@ class ReduceJoinTest(UnicodeTestCase):
for permutation in itertools.permutations(xrange(num_dims), i):
self._testMultipleReduceJoin(input_array, axis=permutation)
+ @test_util.run_deprecated_v1
def testInvalidReductionIndices(self):
with self.cached_session():
with self.assertRaisesRegexp(ValueError, "Invalid reduction dim"):
@@ -325,6 +329,7 @@ class ReduceJoinTest(UnicodeTestCase):
output_shape = self.evaluate(output).shape
self.assertAllEqual([0], output_shape)
+ @test_util.run_deprecated_v1
def testInvalidArgsUnknownShape(self):
with self.cached_session():
placeholder = array_ops.placeholder(dtypes.string, name="placeholder")
@@ -335,6 +340,7 @@ class ReduceJoinTest(UnicodeTestCase):
with self.assertRaisesOpError("Duplicate reduction dimension 1"):
duplicate_index.eval(feed_dict={placeholder.name: [[""]]})
+ @test_util.run_deprecated_v1
def testInvalidArgsUnknownIndices(self):
with self.cached_session():
placeholder = array_ops.placeholder(dtypes.int32, name="placeholder")
diff --git a/tensorflow/python/kernel_tests/reduction_ops_test.py b/tensorflow/python/kernel_tests/reduction_ops_test.py
index 4eb329796e1..67a89461f3a 100644
--- a/tensorflow/python/kernel_tests/reduction_ops_test.py
+++ b/tensorflow/python/kernel_tests/reduction_ops_test.py
@@ -27,6 +27,7 @@ from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
from tensorflow.python.framework import tensor_shape
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import math_ops
@@ -60,6 +61,7 @@ class ReducedShapeTest(test.TestCase):
output = math_ops.reduced_shape(shape, axes=axes)
self.assertAllEqual(output.eval(), result)
+ @test_util.run_deprecated_v1
def testSimple(self):
with self.cached_session():
self._check([3], [], [3])
@@ -69,6 +71,7 @@ class ReducedShapeTest(test.TestCase):
self._check([5, 3], [1], [5, 1])
self._check([5, 3], [0, 1], [1, 1])
+ @test_util.run_deprecated_v1
def testZeros(self):
"""Check that reduced_shape does the right thing with zero dimensions."""
with self.cached_session():
@@ -83,6 +86,7 @@ class ReducedShapeTest(test.TestCase):
self._check([3, 0], [1], [3, 1])
self._check([3, 0], [0, 1], [1, 1])
+ @test_util.run_deprecated_v1
def testNegAxes(self):
with self.cached_session():
self._check([10, 10, 10], [-1], [10, 10, 1])
@@ -94,6 +98,7 @@ class ReducedShapeTest(test.TestCase):
class ReductionUnknownShape(test.TestCase):
+ @test_util.run_deprecated_v1
def testBasic(self):
with self.cached_session():
for dtype, reductions in [(dtypes.float32,
@@ -188,6 +193,7 @@ class SumReductionTest(BaseReductionTest):
tf_v = self.evaluate(v)
self.assertAllEqual(tf_v, 0)
+ @test_util.run_deprecated_v1
def testInfinity(self):
for dtype in [np.float32, np.float64]:
for special_value_x in [-np.inf, np.inf]:
@@ -195,11 +201,13 @@ class SumReductionTest(BaseReductionTest):
np_arr = np.array([special_value_x, special_value_y]).astype(dtype)
self._compareAll(np_arr, None)
+ @test_util.run_deprecated_v1
def testInt32(self):
for rank in range(1, _MAX_RANK + 1):
np_arr = self._makeIncremental((2,) * rank, dtypes.int32)
self._compareAllAxes(np_arr)
+ @test_util.run_deprecated_v1
def testFloat16(self):
for rank in range(1, _MAX_RANK + 1):
np_arr = self._makeIncremental((2,) * rank, dtypes.float16)
@@ -219,6 +227,7 @@ class SumReductionTest(BaseReductionTest):
tf_out_mean = self.evaluate(tf_mean)
self.assertAllClose(tf_out_mean, 1.)
+ @test_util.run_deprecated_v1
def testFloat32(self):
for rank in range(1, _MAX_RANK + 1):
np_arr = self._makeIncremental((2,) * rank, dtypes.float32)
@@ -256,21 +265,25 @@ class SumReductionTest(BaseReductionTest):
self.assertAllClose(sum_y, tf_out_sum_y)
self.assertAllClose(sum_xz, tf_out_sum_xz)
+ @test_util.run_deprecated_v1
def testFloat64(self):
for rank in range(1, _MAX_RANK + 1):
np_arr = self._makeIncremental((2,) * rank, dtypes.float64)
self._compareAllAxes(np_arr)
+ @test_util.run_deprecated_v1
def testComplex64(self):
for rank in range(1, _MAX_RANK + 1):
np_arr = self._makeIncremental((2,) * rank, dtypes.complex64)
self._compareAllAxes(np_arr)
+ @test_util.run_deprecated_v1
def testComplex128(self):
for rank in range(1, _MAX_RANK + 1):
np_arr = self._makeIncremental((2,) * rank, dtypes.complex128)
self._compareAllAxes(np_arr)
+ @test_util.run_deprecated_v1
def testInvalidIndex(self):
np_arr = np.arange(0, 10).reshape([2, 5]).astype(np.float32)
input_tensor = ops.convert_to_tensor(np_arr)
@@ -284,6 +297,7 @@ class SumReductionTest(BaseReductionTest):
ValueError, lambda e: "Invalid reduction dimension" in str(e)):
math_ops.reduce_sum(input_tensor, [0, 2])
+ @test_util.run_deprecated_v1
def testPartialShapes(self):
np.random.seed(1618)
@@ -317,6 +331,7 @@ class SumReductionTest(BaseReductionTest):
c_unknown_indices, unknown_indices, keepdims=True)
self.assertEqual(2, s_unknown_indices_keep.get_shape().rank)
+ @test_util.run_deprecated_v1
def testWrongShapeForReductionIndices(self):
reduction_axes = [[1], [2]]
c_unknown = array_ops.placeholder(dtypes.float32)
@@ -326,6 +341,7 @@ class SumReductionTest(BaseReductionTest):
# Int64??
+ @test_util.run_deprecated_v1
def testGradient(self):
for dtype in [
dtypes.float32, dtypes.float64, dtypes.complex64, dtypes.complex128
@@ -333,6 +349,7 @@ class SumReductionTest(BaseReductionTest):
x = self._makeIncremental([2, 3, 4, 2], dtype)
self._compareGradientAxes(x)
+ @test_util.run_deprecated_v1
def testHighRank(self):
# Do a bunch of random high dimensional reductions
np.random.seed(42)
@@ -350,11 +367,13 @@ class SumReductionTest(BaseReductionTest):
np.arange(1, rank, 2)):
self._compareAll(data, axes)
+ @test_util.run_deprecated_v1
def testExpand(self):
# Reduce an empty tensor to a nonempty tensor
x = np.zeros((5, 0))
self._compareAll(x, [1])
+ @test_util.run_deprecated_v1
def testEmptyGradients(self):
with self.session(use_gpu=True):
x = array_ops.zeros([0, 3])
@@ -362,6 +381,7 @@ class SumReductionTest(BaseReductionTest):
error = gradient_checker.compute_gradient_error(x, [0, 3], y, [0])
self.assertEqual(error, 0)
+ @test_util.run_deprecated_v1
def testDegenerate(self):
with self.session(use_gpu=True):
for dtype in (dtypes.float16, dtypes.float32, dtypes.float64,
@@ -403,6 +423,7 @@ class MeanReductionTest(BaseReductionTest):
tf_v = self.evaluate(v)
self.assertAllEqual(tf_v, 0)
+ @test_util.run_deprecated_v1
def testInfinity(self):
for dtype in [np.float32, np.float64]:
for special_value_x in [-np.inf, np.inf]:
@@ -410,37 +431,44 @@ class MeanReductionTest(BaseReductionTest):
np_arr = np.array([special_value_x, special_value_y]).astype(dtype)
self._compareAll(np_arr, None)
+ @test_util.run_deprecated_v1
def testInt32(self):
for rank in range(1, _MAX_RANK + 1):
np_arr = self._makeIncremental((2,) * rank, dtypes.int32)
self._compareAllAxes(np_arr)
+ @test_util.run_deprecated_v1
def testFloat32(self):
for rank in range(1, _MAX_RANK + 1):
np_arr = self._makeIncremental((2,) * rank, dtypes.float32)
self._compareAllAxes(np_arr)
+ @test_util.run_deprecated_v1
def testFloat64(self):
for rank in range(1, _MAX_RANK + 1):
np_arr = self._makeIncremental((2,) * rank, dtypes.float64)
self._compareAllAxes(np_arr)
+ @test_util.run_deprecated_v1
def testComplex64(self):
for rank in range(1, _MAX_RANK + 1):
np_arr = self._makeIncremental((2,) * rank, dtypes.complex64)
self._compareAllAxes(np_arr)
+ @test_util.run_deprecated_v1
def testComplex128(self):
for rank in range(1, _MAX_RANK + 1):
np_arr = self._makeIncremental((2,) * rank, dtypes.complex128)
self._compareAllAxes(np_arr)
+ @test_util.run_deprecated_v1
def testGradient(self):
s = [2, 3, 4, 2]
for dtype in [dtypes.float32, dtypes.float64]:
x = self._makeIncremental(s, dtype)
self._compareGradientAxes(x, rtol=1e-3, atol=1e-3)
+ @test_util.run_deprecated_v1
def testEmptyGradients(self):
with self.session(use_gpu=True):
x = array_ops.zeros([0, 3])
@@ -448,6 +476,7 @@ class MeanReductionTest(BaseReductionTest):
error = gradient_checker.compute_gradient_error(x, [0, 3], y, [0])
self.assertEqual(error, 0)
+ @test_util.run_deprecated_v1
def testDegenerate(self):
with self.session(use_gpu=True):
for dtype in (dtypes.float16, dtypes.float32, dtypes.float64):
@@ -476,6 +505,7 @@ class ProdReductionTest(BaseReductionTest):
tf_v = self.evaluate(v)
self.assertAllEqual(tf_v, 0)
+ @test_util.run_deprecated_v1
def testInfinity(self):
for dtype in [np.float32, np.float64]:
for special_value_x in [-np.inf, np.inf]:
@@ -483,6 +513,7 @@ class ProdReductionTest(BaseReductionTest):
np_arr = np.array([special_value_x, special_value_y]).astype(dtype)
self._compareAll(np_arr, None)
+ @test_util.run_deprecated_v1
def testInt32(self):
# Numpy automatically upgrades the type of np.prod from int32 to int64, so
# Numpy does not overflow an int32 np.prod while TensorFlow does. To avoid
@@ -491,26 +522,31 @@ class ProdReductionTest(BaseReductionTest):
np_arr = self._makeIncremental((2,) * rank, dtypes.int32) / 2
self._compareAllAxes(np_arr)
+ @test_util.run_deprecated_v1
def testFloat32(self):
for rank in range(1, _MAX_RANK + 1):
np_arr = self._makeIncremental((2,) * rank, dtypes.float32)
self._compareAllAxes(np_arr)
+ @test_util.run_deprecated_v1
def testFloat64(self):
for rank in range(1, _MAX_RANK + 1):
np_arr = self._makeIncremental((2,) * rank, dtypes.float64)
self._compareAllAxes(np_arr)
+ @test_util.run_deprecated_v1
def testComplex64(self):
for rank in range(1, _MAX_RANK + 1):
np_arr = self._makeIncremental((2,) * rank, dtypes.complex64)
self._compareAllAxes(np_arr)
+ @test_util.run_deprecated_v1
def testComplex128(self):
for rank in range(1, _MAX_RANK + 1):
np_arr = self._makeIncremental((2,) * rank, dtypes.complex128)
self._compareAllAxes(np_arr)
+ @test_util.run_deprecated_v1
def testGradientWithZeros(self):
s = [2, 3, 4, 2]
x = self._makeIncremental(s, dtypes.float32) / 20.
@@ -533,6 +569,7 @@ class ProdReductionTest(BaseReductionTest):
x4[:, :, :, :] = 0
self._compareGradientAxes(x4, rtol=1e-3, atol=1e-3)
+ @test_util.run_deprecated_v1
def testEmptyGradients(self):
with self.session(use_gpu=True):
x = array_ops.zeros([0, 3])
@@ -540,6 +577,7 @@ class ProdReductionTest(BaseReductionTest):
error = gradient_checker.compute_gradient_error(x, [0, 3], y, [0])
self.assertEqual(error, 0)
+ @test_util.run_deprecated_v1
def testDegenerate(self):
with self.session(use_gpu=True):
for dtype in (dtypes.float16, dtypes.float32, dtypes.float64):
@@ -579,6 +617,7 @@ class MinReductionTest(test.TestCase):
tf_v = self.evaluate(v)
self.assertAllEqual(tf_v, 0)
+ @test_util.run_deprecated_v1
def testInfinity(self):
for dtype in [np.float32, np.float64]:
for special_value_x in [-np.inf, np.inf]:
@@ -614,6 +653,7 @@ class MinReductionTest(test.TestCase):
self._compareAll(np_arr, [0, 2])
self._compareAll(np_arr, [0, 1, 2])
+ @test_util.run_deprecated_v1
def testGradient(self):
s = [2, 3, 4, 2]
x = np.arange(1.0, 49.0).reshape(s).astype(np.float64)
@@ -624,6 +664,7 @@ class MinReductionTest(test.TestCase):
t, s, su, [2, 2], x_init_value=x, delta=1)
self.assertAllClose(jacob_t, jacob_n, rtol=1e-8, atol=1e-8)
+ @test_util.run_deprecated_v1
def testGradient2(self):
s = [2, 3, 4, 2]
x = np.arange(1.0, 49.0).reshape(s).astype(np.float64)
@@ -634,6 +675,7 @@ class MinReductionTest(test.TestCase):
t, s, su, [2, 4, 2], x_init_value=x, delta=1)
self.assertAllClose(jacob_t, jacob_n, rtol=1e-8, atol=1e-8)
+ @test_util.run_deprecated_v1
def testGradient3(self):
s = [2, 3, 4, 2]
x = np.arange(1.0, 49.0).reshape(s).astype(np.float64)
@@ -644,6 +686,7 @@ class MinReductionTest(test.TestCase):
t, s, su, [2, 3, 2], x_init_value=x, delta=1)
self.assertAllClose(jacob_t, jacob_n, rtol=1e-8, atol=1e-8)
+ @test_util.run_deprecated_v1
def testGradient4(self):
s = [2, 3, 4, 2]
x = np.arange(1.0, 49.0).reshape(s).astype(np.float64)
@@ -654,6 +697,7 @@ class MinReductionTest(test.TestCase):
t, s, su, [1], x_init_value=x, delta=1)
self.assertAllClose(jacob_t, jacob_n, rtol=1e-8, atol=1e-8)
+ @test_util.run_deprecated_v1
def testEmptyGradients(self):
with self.cached_session():
x = array_ops.zeros([0, 3])
@@ -692,6 +736,7 @@ class MaxReductionTest(test.TestCase):
tf_v = self.evaluate(v)
self.assertAllEqual(tf_v, 0)
+ @test_util.run_deprecated_v1
def testInfinity(self):
for dtype in [np.float32, np.float64]:
for special_value_x in [-np.inf, np.inf]:
@@ -741,6 +786,7 @@ class MaxReductionTest(test.TestCase):
self._compareAll(np_arr, [0, 2])
self._compareAll(np_arr, [0, 1, 2])
+ @test_util.run_deprecated_v1
def testGradient(self):
s = [2, 3, 4, 2]
x = np.arange(-49.0, -1.0).reshape(s).astype(np.float64)
@@ -751,6 +797,7 @@ class MaxReductionTest(test.TestCase):
t, s, su, [2, 2], x_init_value=x, delta=1)
self.assertAllClose(jacob_t, jacob_n, rtol=1e-8, atol=1e-8)
+ @test_util.run_deprecated_v1
def testGradient2(self):
s = [2, 3, 4, 2]
x = np.arange(-49.0, -1.0).reshape(s).astype(np.float64)
@@ -761,6 +808,7 @@ class MaxReductionTest(test.TestCase):
t, s, su, [2, 4, 2], x_init_value=x, delta=1)
self.assertAllClose(jacob_t, jacob_n, rtol=1e-8, atol=1e-8)
+ @test_util.run_deprecated_v1
def testGradient3(self):
s = [2, 3, 4, 2]
x = np.arange(-49.0, -1.0).reshape(s).astype(np.float64)
@@ -771,6 +819,7 @@ class MaxReductionTest(test.TestCase):
t, s, su, [2, 3, 2], x_init_value=x, delta=1)
self.assertAllClose(jacob_t, jacob_n, rtol=1e-8, atol=1e-8)
+ @test_util.run_deprecated_v1
def testGradient4(self):
s = [2, 3, 4, 2]
x = np.arange(-49.0, -1.0).reshape(s).astype(np.float64)
@@ -781,6 +830,7 @@ class MaxReductionTest(test.TestCase):
t, s, su, [1], x_init_value=x, delta=1)
self.assertAllClose(jacob_t, jacob_n, rtol=1e-8, atol=1e-8)
+ @test_util.run_deprecated_v1
def testEmptyGradients(self):
with self.cached_session():
x = array_ops.zeros([0, 3])
@@ -913,6 +963,7 @@ class CountNonzeroReductionTest(test.TestCase):
self._compare(x, reduction_axes, True, use_gpu=True, feed_dict=feed_dict)
self._compare(x, reduction_axes, True, use_gpu=False, feed_dict=feed_dict)
+ @test_util.run_deprecated_v1
def testBoolReduce1D(self):
# Create a 1D array of floats
np_arr = np.asarray([False, False, True, False, False, True])
@@ -920,11 +971,13 @@ class CountNonzeroReductionTest(test.TestCase):
self._compareAll(np_arr, [])
self._compareAll(np_arr, [0])
+ @test_util.run_deprecated_v1
def testFloatReduce1D(self):
# Create a 1D array of floats
np_arr = np.asarray([0.0, 1.0, -1.0, 0.0, 0.0, 3.0]).astype(np.float32)
self._compareAll(np_arr, [0])
+ @test_util.run_deprecated_v1
def testFloatReduce4D(self):
# Create a 4D array of floats and reduce across some
# dimensions
@@ -944,11 +997,13 @@ class CountNonzeroReductionTest(test.TestCase):
self._compareAll(np_arr, [1, 2, 3])
self._compareAll(np_arr, [0, 1, 2, 3])
+ @test_util.run_deprecated_v1
def testExpand(self):
# Reduce an empty tensor to a nonempty tensor
x = np.zeros((5, 0))
self._compareAll(x, [1])
+ @test_util.run_deprecated_v1
def testDegenerate(self):
for use_gpu in False, True:
with self.cached_session(use_gpu=use_gpu):
@@ -964,6 +1019,7 @@ class CountNonzeroReductionTest(test.TestCase):
v = math_ops.count_nonzero(constant_op.constant(["test"]))
self.assertAllClose(self.evaluate(v), 1)
+ @test_util.run_deprecated_v1
def testStringReduce1D(self):
# Create a 1D array of strings
x = np.asarray(["", "", "a", "", "", "b"])
@@ -974,6 +1030,7 @@ class CountNonzeroReductionTest(test.TestCase):
self._compare(x, [], keepdims=True, zero=np.str(""))
self._compare(x, [0], keepdims=True, zero=np.str(""))
+ @test_util.run_deprecated_v1
def testStringReduce2D(self):
# Create a 2D array of strings
x = np.asarray([["", "", "a", "", "", "b"],
diff --git a/tensorflow/python/kernel_tests/regex_full_match_op_test.py b/tensorflow/python/kernel_tests/regex_full_match_op_test.py
index 4edd3e98d9b..488ec85ab2c 100644
--- a/tensorflow/python/kernel_tests/regex_full_match_op_test.py
+++ b/tensorflow/python/kernel_tests/regex_full_match_op_test.py
@@ -23,6 +23,7 @@ from absl.testing import parameterized
from tensorflow.python.compat import compat
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import gen_string_ops
from tensorflow.python.ops import string_ops
from tensorflow.python.platform import test
@@ -33,6 +34,7 @@ from tensorflow.python.platform import test
(gen_string_ops.static_regex_full_match))
class RegexFullMatchOpVariantsTest(test.TestCase, parameterized.TestCase):
+ @test_util.run_deprecated_v1
def testRegexFullMatch(self, op):
values = ["abaaba", "abcdabcde"]
with self.cached_session():
@@ -40,6 +42,7 @@ class RegexFullMatchOpVariantsTest(test.TestCase, parameterized.TestCase):
matched = op(input_tensor, "a.*a").eval()
self.assertAllEqual([True, False], matched)
+ @test_util.run_deprecated_v1
def testRegexFullMatchTwoDims(self, op):
values = [["abaaba", "abcdabcde"], ["acdcba", "ebcda"]]
with self.cached_session():
@@ -47,6 +50,7 @@ class RegexFullMatchOpVariantsTest(test.TestCase, parameterized.TestCase):
matched = op(input_tensor, "a.*a").eval()
self.assertAllEqual([[True, False], [True, False]], matched)
+ @test_util.run_deprecated_v1
def testEmptyMatch(self, op):
values = ["abc", "1"]
with self.cached_session():
@@ -54,6 +58,7 @@ class RegexFullMatchOpVariantsTest(test.TestCase, parameterized.TestCase):
matched = op(input_tensor, "").eval()
self.assertAllEqual([False, False], matched)
+ @test_util.run_deprecated_v1
def testInvalidPattern(self, op):
values = ["abc", "1"]
with self.cached_session():
@@ -66,6 +71,7 @@ class RegexFullMatchOpVariantsTest(test.TestCase, parameterized.TestCase):
class RegexFullMatchOpTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testRegexFullMatchDelegation(self):
with compat.forward_compatibility_horizon(2018, 11, 1):
with self.cached_session():
@@ -78,6 +84,7 @@ class RegexFullMatchOpTest(test.TestCase):
op_tensor = string_ops.regex_full_match(input_tensor, pattern_tensor)
self.assertTrue(op_tensor.name.startswith("RegexFullMatch"), op.name)
+ @test_util.run_deprecated_v1
def testStaticRegexFullMatchDelegation(self):
with compat.forward_compatibility_horizon(2018, 11, 20):
with self.cached_session():
diff --git a/tensorflow/python/kernel_tests/regex_replace_op_test.py b/tensorflow/python/kernel_tests/regex_replace_op_test.py
index ce9a1b5279f..6c7dfee7b40 100644
--- a/tensorflow/python/kernel_tests/regex_replace_op_test.py
+++ b/tensorflow/python/kernel_tests/regex_replace_op_test.py
@@ -22,6 +22,7 @@ from absl.testing import parameterized
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import gen_string_ops
from tensorflow.python.ops import string_ops
from tensorflow.python.platform import test
@@ -32,6 +33,7 @@ from tensorflow.python.platform import test
(gen_string_ops.static_regex_replace))
class RegexReplaceOpVariantsTest(test.TestCase, parameterized.TestCase):
+ @test_util.run_deprecated_v1
def testForwarding(self, op):
with self.cached_session():
# Generate an input that is uniquely consumed by the regex op.
@@ -45,6 +47,7 @@ class RegexReplaceOpVariantsTest(test.TestCase, parameterized.TestCase):
stripped = op(inp, "\\p{Ll}", ".").eval()
self.assertAllEqual([b"A.C.E", b"H.J.L"], stripped)
+ @test_util.run_deprecated_v1
def testRemovePrefix(self, op):
values = ["a:foo", "a:bar", "a:foo", "b:baz", "b:qux", "ca:b"]
with self.cached_session():
@@ -53,6 +56,7 @@ class RegexReplaceOpVariantsTest(test.TestCase, parameterized.TestCase):
self.assertAllEqual([b"foo", b"bar", b"foo", b"baz", b"qux", b"ca:b"],
stripped)
+ @test_util.run_deprecated_v1
def testRegexReplace(self, op):
values = ["aba\naba", "abcdabcde"]
with self.cached_session():
@@ -60,6 +64,7 @@ class RegexReplaceOpVariantsTest(test.TestCase, parameterized.TestCase):
stripped = op(input_vector, "a.*a", "(\\0)").eval()
self.assertAllEqual([b"(aba)\n(aba)", b"(abcda)bcde"], stripped)
+ @test_util.run_deprecated_v1
def testEmptyMatch(self, op):
values = ["abc", "1"]
with self.cached_session():
@@ -67,6 +72,7 @@ class RegexReplaceOpVariantsTest(test.TestCase, parameterized.TestCase):
stripped = op(input_vector, "", "x").eval()
self.assertAllEqual([b"xaxbxcx", b"x1x"], stripped)
+ @test_util.run_deprecated_v1
def testInvalidPattern(self, op):
values = ["abc", "1"]
with self.cached_session():
@@ -76,6 +82,7 @@ class RegexReplaceOpVariantsTest(test.TestCase, parameterized.TestCase):
with self.assertRaisesOpError("Invalid pattern"):
self.evaluate(replace)
+ @test_util.run_deprecated_v1
def testGlobal(self, op):
values = ["ababababab", "abcabcabc", ""]
with self.cached_session():
@@ -98,6 +105,7 @@ class RegexReplaceTest(test.TestCase, parameterized.TestCase):
(as_string, as_tensor),
(as_tensor, as_string),
(as_tensor, as_tensor))
+ @test_util.run_deprecated_v1
def testRegexReplaceDelegation(self, pattern_fn, rewrite_fn):
with self.cached_session():
input_vector = constant_op.constant("foo", dtypes.string)
@@ -106,6 +114,7 @@ class RegexReplaceTest(test.TestCase, parameterized.TestCase):
op = string_ops.regex_replace(input_vector, pattern, replace)
self.assertTrue(op.name.startswith("RegexReplace"))
+ @test_util.run_deprecated_v1
def testStaticRegexReplaceDelegation(self):
with self.cached_session():
input_vector = constant_op.constant("foo", dtypes.string)
diff --git a/tensorflow/python/kernel_tests/relu_op_test.py b/tensorflow/python/kernel_tests/relu_op_test.py
index 30cef908853..55e68f4884c 100644
--- a/tensorflow/python/kernel_tests/relu_op_test.py
+++ b/tensorflow/python/kernel_tests/relu_op_test.py
@@ -26,6 +26,7 @@ from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import gradients_impl
@@ -105,6 +106,7 @@ class ReluTest(test.TestCase):
# The gradient test for ReLU is a bit tricky as the derivative is not well
# defined at around zero and we want to avoid that in terms of input values.
+ @test_util.run_deprecated_v1
def testGradientFloat32(self):
with self.cached_session():
x = constant_op.constant(
@@ -124,6 +126,7 @@ class ReluTest(test.TestCase):
# The gradient for fp16 is inaccurate due to the low-precision.
# Instead of relying on compute_gradient_error, we compare the fp16 analytical
# gradient against their fp32 counterpart.
+ @test_util.run_deprecated_v1
def testGradientFloat16(self):
with self.session(use_gpu=True) as sess:
# Randomly construct a 1D shape from [1, 40)
@@ -150,6 +153,7 @@ class ReluTest(test.TestCase):
dx_f32_v, dx_f16_v = self.evaluate([dx_f32, dx_f16])
self.assertAllClose(dx_f32_v, dx_f16_v, atol=3e-4)
+ @test_util.run_deprecated_v1
def testGradientFloat64(self):
with self.cached_session():
x = constant_op.constant(
@@ -167,6 +171,7 @@ class ReluTest(test.TestCase):
print("relu (float64) gradient err = ", err)
self.assertLess(err, 1e-10)
+ @test_util.run_deprecated_v1
def testGradGradFloat32(self):
with self.cached_session():
x = constant_op.constant(
@@ -184,6 +189,7 @@ class ReluTest(test.TestCase):
print("relu (float32) gradient of gradient err = ", err)
self.assertLess(err, 1e-4)
+ @test_util.run_deprecated_v1
def testGradGradFloat64(self):
with self.cached_session():
x = constant_op.constant(
@@ -252,6 +258,7 @@ class Relu6Test(test.TestCase):
# The gradient test for ReLU6 is a bit tricky as the derivative is
# not well defined at around zero and six and we want to avoid that
# in terms of input values.
+ @test_util.run_deprecated_v1
def testGradientFloat32(self):
with self.cached_session():
x = constant_op.constant(
@@ -268,6 +275,7 @@ class Relu6Test(test.TestCase):
print("relu6 (float32) gradient err = ", err)
self.assertLess(err, 1e-4)
+ @test_util.run_deprecated_v1
def testGradientFloat64(self):
with self.cached_session():
x = constant_op.constant(
@@ -325,6 +333,7 @@ class LeakyReluTest(test.TestCase):
# The gradient test for Leaky ReLU is a bit tricky as the derivative is not
# well defined at around zero and we want to avoid that in terms of input
# values.
+ @test_util.run_deprecated_v1
def testGradientFloat32(self):
with self.test_session():
x = constant_op.constant(
@@ -341,6 +350,7 @@ class LeakyReluTest(test.TestCase):
print("leaky_relu (float32) gradient err = ", err)
self.assertLess(err, 1e-4)
+ @test_util.run_deprecated_v1
def testGradientFloat64(self):
with self.test_session():
x = constant_op.constant(
@@ -358,6 +368,7 @@ class LeakyReluTest(test.TestCase):
print("leaky_relu (float64) gradient err = ", err)
self.assertLess(err, 1e-10)
+ @test_util.run_deprecated_v1
def testGradGradFloat32(self):
with compat.forward_compatibility_horizon(2018, 11, 2):
with self.test_session():
@@ -376,6 +387,7 @@ class LeakyReluTest(test.TestCase):
print("leaky_relu (float32) gradient of gradient err = ", err)
self.assertLess(err, 1e-4)
+ @test_util.run_deprecated_v1
def testGradGradFloat64(self):
with compat.forward_compatibility_horizon(2018, 11, 2):
with self.test_session():
@@ -439,6 +451,7 @@ class EluTest(test.TestCase):
for t in [np.float16, np.float32, np.float64]:
self._testElu(np.array([[-9, 7, -5, 3, -1], [1, -3, 5, -7, 9]]).astype(t))
+ @test_util.run_deprecated_v1
def testGradientFloat32(self):
with self.cached_session():
x_val = [[-0.9, -0.7, -0.5, -0.3, -0.1], [0.1, 0.3, 0.5, 0.7, 0.9]]
@@ -450,6 +463,7 @@ class EluTest(test.TestCase):
print("elu (float32) gradient err = ", err)
self.assertLess(err, 1e-4)
+ @test_util.run_deprecated_v1
def testGradientFloat64(self):
with self.cached_session():
x_val = [[-0.9, -0.7, -0.5, -0.3, -0.1], [0.1, 0.3, 0.5, 0.7, 0.9]]
@@ -461,6 +475,7 @@ class EluTest(test.TestCase):
print("elu (float64) gradient err = ", err)
self.assertLess(err, 1e-6)
+ @test_util.run_deprecated_v1
def testGradGrad(self):
with self.cached_session():
x = array_ops.placeholder(dtype=dtypes.float32)
@@ -472,6 +487,7 @@ class EluTest(test.TestCase):
err = np.abs(gg.eval(feed_dict={x: x_val}) - _elu_grad_grad(x_val))
self.assertLess(err, 1e-4)
+ @test_util.run_deprecated_v1
def testGradGradFloat32(self):
with self.cached_session():
x = constant_op.constant(
@@ -489,6 +505,7 @@ class EluTest(test.TestCase):
print("elu (float32) gradient of gradient err = ", err)
self.assertLess(err, 1e-4)
+ @test_util.run_deprecated_v1
def testGradGradFloat64(self):
with self.cached_session():
x = constant_op.constant(
@@ -539,6 +556,7 @@ class SeluTest(test.TestCase):
self._testSelu(
np.array([[-9, 7, -5, 3, -1], [1, -3, 5, -7, 9]]).astype(t))
+ @test_util.run_deprecated_v1
def testGradientFloat32(self):
with self.cached_session():
x_val = [[-0.9, -0.7, -0.5, -0.3, -0.1], [0.1, 0.3, 0.5, 0.7, 0.9]]
@@ -550,6 +568,7 @@ class SeluTest(test.TestCase):
print("selu (float32) gradient err = ", err)
self.assertLess(err, 1e-4)
+ @test_util.run_deprecated_v1
def testGradientFloat64(self):
with self.cached_session():
x_val = [[-0.9, -0.7, -0.5, -0.3, -0.1], [0.1, 0.3, 0.5, 0.7, 0.9]]
@@ -561,6 +580,7 @@ class SeluTest(test.TestCase):
print("selu (float64) gradient err = ", err)
self.assertLess(err, 1e-6)
+ @test_util.run_deprecated_v1
def testGradGradFloat32(self):
with self.cached_session():
x = constant_op.constant(
@@ -578,6 +598,7 @@ class SeluTest(test.TestCase):
print("selu (float32) gradient of gradient err = ", err)
self.assertLess(err, 1e-4)
+ @test_util.run_deprecated_v1
def testGradGradFloat64(self):
with self.cached_session():
x = constant_op.constant(
diff --git a/tensorflow/python/kernel_tests/reshape_op_test.py b/tensorflow/python/kernel_tests/reshape_op_test.py
index 84539c2b02a..db3e88a104f 100644
--- a/tensorflow/python/kernel_tests/reshape_op_test.py
+++ b/tensorflow/python/kernel_tests/reshape_op_test.py
@@ -22,6 +22,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradient_checker
from tensorflow.python.platform import test
@@ -91,6 +92,7 @@ class ReshapeTest(test.TestCase):
# TODO(vrv): Add tests for failure conditions once python test_util
# reports errors.
+ @test_util.run_deprecated_v1
def testFloatReshapeGradThreeDimensions(self):
x = np.arange(1., 25.).reshape([2, 3, 4]).astype(np.float32)
s = list(np.shape(x))
@@ -111,6 +113,7 @@ class ReshapeTest(test.TestCase):
self._testBothReshape(x, [0, 0, 0])
self._testBothReshape(x, [1, -1, 5])
+ @test_util.run_deprecated_v1
def testErrors(self):
y = constant_op.constant(0.0, shape=[23, 29, 31])
with self.assertRaisesRegexp(ValueError, "must be evenly divisible by 17"):
@@ -121,6 +124,7 @@ class ReshapeTest(test.TestCase):
"Cannot reshape a tensor with 4096 elements"):
array_ops.reshape(z, [4095])
+ @test_util.run_deprecated_v1
def testPartialShapes(self):
x = array_ops.placeholder(dtypes.float32)
diff --git a/tensorflow/python/kernel_tests/resource_variable_ops_test.py b/tensorflow/python/kernel_tests/resource_variable_ops_test.py
index d30ab6a9c29..b57d9d47aa3 100644
--- a/tensorflow/python/kernel_tests/resource_variable_ops_test.py
+++ b/tensorflow/python/kernel_tests/resource_variable_ops_test.py
@@ -54,6 +54,7 @@ class ResourceVariableOpsTest(test_util.TensorFlowTestCase):
# involving objects with __del__ defined.
self.assertEqual(0, len(gc.garbage))
+ @test_util.run_deprecated_v1
def testHandleDtypeShapeMatch(self):
with self.cached_session():
handle = resource_variable_ops.var_handle_op(dtype=dtypes.int32, shape=[])
@@ -123,6 +124,7 @@ class ResourceVariableOpsTest(test_util.TensorFlowTestCase):
# values.
self.assertFalse(np.allclose(variable.numpy(), copied_variable.numpy()))
+ @test_util.run_deprecated_v1
def testGraphDeepCopy(self):
with self.cached_session():
init_value = np.ones((4, 4, 4))
@@ -146,6 +148,7 @@ class ResourceVariableOpsTest(test_util.TensorFlowTestCase):
resource_variable_ops.variable_shape(v.handle)),
[2])
+ @test_util.run_deprecated_v1
def testDifferentAssignGraph(self):
with ops.Graph().as_default():
v = resource_variable_ops.ResourceVariable(1.0)
@@ -153,12 +156,14 @@ class ResourceVariableOpsTest(test_util.TensorFlowTestCase):
v.assign(2.0) # Note: this fails if we run convert_to_tensor on not the
# variable graph.
+ @test_util.run_deprecated_v1
def testFetchHandle(self):
with self.cached_session():
handle = resource_variable_ops.var_handle_op(
dtype=dtypes.int32, shape=[1], name="foo")
self.assertGreater(len(handle.eval()), 0)
+ @test_util.run_deprecated_v1
def testCachedValueReadBeforeWrite(self):
with self.cached_session() as sess:
v = resource_variable_ops.ResourceVariable(0.0, caching_device="cpu:0")
@@ -435,6 +440,7 @@ class ResourceVariableOpsTest(test_util.TensorFlowTestCase):
read = resource_variable_ops.read_variable_op(handle, dtype=dtypes.int32)
self.assertEqual(self.evaluate(read), [[6]])
+ @test_util.run_deprecated_v1
def testScatterUpdateString(self):
handle = resource_variable_ops.var_handle_op(
dtype=dtypes.string, shape=[1, 1])
@@ -446,6 +452,7 @@ class ResourceVariableOpsTest(test_util.TensorFlowTestCase):
self.assertEqual(compat.as_bytes(self.evaluate(read)[0][0]),
compat.as_bytes("b"))
+ @test_util.run_deprecated_v1
def testScatterUpdateStringScalar(self):
handle = resource_variable_ops.var_handle_op(
dtype=dtypes.string, shape=[1, 1])
@@ -500,6 +507,7 @@ class ResourceVariableOpsTest(test_util.TensorFlowTestCase):
initial_value=lambda: 1, constraint=constraint, name="var1")
# TODO(alive): how should this work in Eager mode?
+ @test_util.run_deprecated_v1
def testInitFn(self):
with self.cached_session():
v = resource_variable_ops.ResourceVariable(
@@ -591,6 +599,7 @@ class ResourceVariableOpsTest(test_util.TensorFlowTestCase):
variable_def=other_v_def)
self.assertTrue(other_v_prime._cached_value is not None)
+ @test_util.run_deprecated_v1
def testVariableDefInitializedInstances(self):
with ops.Graph().as_default(), self.cached_session() as sess:
v_def = resource_variable_ops.ResourceVariable(
@@ -646,6 +655,7 @@ class ResourceVariableOpsTest(test_util.TensorFlowTestCase):
value = self.evaluate(v.sparse_read([0, 3, 1, 2]))
self.assertAllEqual(init_value[[0, 3, 1, 2], ...], value)
+ @test_util.run_deprecated_v1
def testToFromProto(self):
with self.cached_session():
v = resource_variable_ops.ResourceVariable(1.0)
@@ -694,6 +704,7 @@ class ResourceVariableOpsTest(test_util.TensorFlowTestCase):
self.assertEqual(0.0, self.evaluate(v.value()))
@test_util.run_in_graph_and_eager_modes
+ @test_util.run_deprecated_v1
def testDestroyResource(self):
v = resource_variable_ops.ResourceVariable(3.0, name="var0")
self.evaluate(variables.global_variables_initializer())
@@ -707,6 +718,7 @@ class ResourceVariableOpsTest(test_util.TensorFlowTestCase):
self.evaluate(resource_variable_ops.destroy_resource_op(
handle, ignore_lookup_error=True))
+ @test_util.run_deprecated_v1
def testAssignDifferentShapes(self):
with self.cached_session() as sess, variable_scope.variable_scope(
"foo", use_resource=True):
@@ -727,6 +739,7 @@ class ResourceVariableOpsTest(test_util.TensorFlowTestCase):
assign = var.assign(np.zeros(shape=[2, 2]))
self.evaluate(assign)
+ @test_util.run_deprecated_v1
def testDtypeAfterFromProto(self):
v = resource_variable_ops.ResourceVariable(2.0)
w = resource_variable_ops.ResourceVariable.from_proto(v.to_proto())
@@ -734,6 +747,7 @@ class ResourceVariableOpsTest(test_util.TensorFlowTestCase):
self.assertEqual(v.dtype, w.dtype)
# TODO(alive): get caching to work in eager mode.
+ @test_util.run_deprecated_v1
def testCachingDevice(self):
with ops.device("/job:server/task:1"):
v = resource_variable_ops.ResourceVariable(
@@ -749,6 +763,7 @@ class ResourceVariableOpsTest(test_util.TensorFlowTestCase):
with self.assertRaises(ValueError):
_ = w.value().op.get_attr("_class")
+ @test_util.run_deprecated_v1
def testSharedName(self):
with self.cached_session():
v = resource_variable_ops.ResourceVariable(300.0, name="var4")
@@ -767,6 +782,7 @@ class ResourceVariableOpsTest(test_util.TensorFlowTestCase):
with self.assertRaisesOpError("Resource .*/var5/.* does not exist"):
resource_variable_ops.read_variable_op(x, v.dtype.base_dtype).eval()
+ @test_util.run_deprecated_v1
def testSharedNameWithNamescope(self):
with self.cached_session():
with ops.name_scope("foo"):
@@ -795,6 +811,7 @@ class ResourceVariableOpsTest(test_util.TensorFlowTestCase):
"<unknown>",
str(v.sparse_read(array_ops.placeholder(dtypes.int32)).shape))
+ @test_util.run_deprecated_v1
def testSetInitialValue(self):
with self.cached_session():
# Initialize variable with a value different from the initial value passed
@@ -803,6 +820,7 @@ class ResourceVariableOpsTest(test_util.TensorFlowTestCase):
v.initializer.run(feed_dict={v.initial_value: 3.0})
self.assertEqual(3.0, v.value().eval())
+ @test_util.run_deprecated_v1
def testControlFlowInitialization(self):
"""Expects an error if an initializer is in a control-flow scope."""
@@ -939,6 +957,7 @@ class ResourceVariableOpsTest(test_util.TensorFlowTestCase):
self.assertAllEqual(self.evaluate(v.assign_add(1)), [1, 2, 3, 4])
@test_util.run_in_graph_and_eager_modes
+ @test_util.run_deprecated_v1
def testCopyToGraphUninitialized(self):
v = resource_variable_ops.ResourceVariable([0, 1, 2, 3])
copy_to_graph = ops.Graph()
diff --git a/tensorflow/python/kernel_tests/reverse_sequence_op_test.py b/tensorflow/python/kernel_tests/reverse_sequence_op_test.py
index 91d054ad9ad..05307c9834a 100644
--- a/tensorflow/python/kernel_tests/reverse_sequence_op_test.py
+++ b/tensorflow/python/kernel_tests/reverse_sequence_op_test.py
@@ -23,6 +23,7 @@ from six.moves import xrange # pylint: disable=redefined-builtin
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradient_checker
from tensorflow.python.platform import test
@@ -107,6 +108,7 @@ class ReverseSequenceTest(test.TestCase):
def testComplex128Basic(self):
self._testBasic(np.complex128)
+ @test_util.run_deprecated_v1
def testFloatReverseSequenceGrad(self):
x = np.asarray(
[[[1, 2, 3, 4], [5, 6, 7, 8]], [[9, 10, 11, 12], [13, 14, 15, 16]],
@@ -133,6 +135,7 @@ class ReverseSequenceTest(test.TestCase):
print("ReverseSequence gradient error = %g" % err)
self.assertLess(err, 1e-8)
+ @test_util.run_deprecated_v1
def testShapeFunctionEdgeCases(self):
t = array_ops.reverse_sequence(
array_ops.placeholder(
diff --git a/tensorflow/python/kernel_tests/rnn_test.py b/tensorflow/python/kernel_tests/rnn_test.py
index 0090b7332f9..3bc457f8fb6 100644
--- a/tensorflow/python/kernel_tests/rnn_test.py
+++ b/tensorflow/python/kernel_tests/rnn_test.py
@@ -262,6 +262,7 @@ class RNNTest(test.TestCase):
rnn.dynamic_rnn(cell, inputs, dtype=dtypes.float32, sequence_length=[4])
@test_util.run_in_graph_and_eager_modes
+ @test_util.run_deprecated_v1
def testTensorArrayStateIsAccepted(self):
cell = TensorArrayStateRNNCell()
in_eager_mode = context.executing_eagerly()
@@ -285,6 +286,7 @@ class RNNTest(test.TestCase):
self.assertAllEqual(4, state[0])
self.assertAllEqual([[[1]], [[2]], [[3]], [[4]]], state[1])
+ @test_util.run_deprecated_v1
def testCellGetInitialState(self):
cell = rnn_cell_impl.BasicRNNCell(5)
with self.assertRaisesRegexp(
@@ -345,6 +347,7 @@ class RNNTest(test.TestCase):
self._assert_cell_builds(contrib_rnn.IndyLSTMCell, f32, 5, 7, 3)
self._assert_cell_builds(contrib_rnn.IndyLSTMCell, f64, 5, 7, 3)
+ @test_util.run_deprecated_v1
def testRNNWithKerasSimpleRNNCell(self):
with self.cached_session() as sess:
input_shape = 10
@@ -378,6 +381,7 @@ class RNNTest(test.TestCase):
self.assertEqual(len(outputs), batch)
self.assertEqual(len(state), batch)
+ @test_util.run_deprecated_v1
def testRNNWithKerasGRUCell(self):
with self.cached_session() as sess:
input_shape = 10
@@ -411,6 +415,7 @@ class RNNTest(test.TestCase):
self.assertEqual(len(outputs), batch)
self.assertEqual(len(state), batch)
+ @test_util.run_deprecated_v1
def testRNNWithKerasLSTMCell(self):
with self.cached_session() as sess:
input_shape = 10
@@ -448,6 +453,7 @@ class RNNTest(test.TestCase):
self.assertEqual(len(state[0]), batch)
self.assertEqual(len(state[1]), batch)
+ @test_util.run_deprecated_v1
def testRNNWithStackKerasCell(self):
with self.cached_session() as sess:
input_shape = 10
@@ -491,6 +497,7 @@ class RNNTest(test.TestCase):
for s in state:
self.assertEqual(len(s), batch)
+ @test_util.run_deprecated_v1
def testStaticRNNWithKerasSimpleRNNCell(self):
with self.cached_session() as sess:
input_shape = 10
@@ -529,6 +536,7 @@ class RNNTest(test.TestCase):
self.assertEqual(len(outputs[0]), batch)
self.assertEqual(len(state), batch)
+ @test_util.run_deprecated_v1
def testKerasAndTFRNNLayerOutputComparison(self):
input_shape = 10
output_shape = 5
@@ -562,6 +570,7 @@ class RNNTest(test.TestCase):
self.assertAllClose(tf_out, k_out)
self.assertAllClose(tf_state, k_state)
+ @test_util.run_deprecated_v1
def testSimpleRNNCellAndBasicRNNCellComparison(self):
input_shape = 10
output_shape = 5
@@ -601,6 +610,7 @@ class RNNTest(test.TestCase):
self.assertAllClose(tf_out, k_out, atol=1e-5)
self.assertAllClose(tf_state, k_state, atol=1e-5)
+ @test_util.run_deprecated_v1
def testBasicLSTMCellInterchangeWithLSTMCell(self):
with self.session(graph=ops_lib.Graph()) as sess:
basic_cell = rnn_cell_impl.BasicLSTMCell(1)
diff --git a/tensorflow/python/kernel_tests/save_restore_ops_test.py b/tensorflow/python/kernel_tests/save_restore_ops_test.py
index be117c4350c..fecc9a3800f 100644
--- a/tensorflow/python/kernel_tests/save_restore_ops_test.py
+++ b/tensorflow/python/kernel_tests/save_restore_ops_test.py
@@ -55,6 +55,7 @@ class ShardedFileOpsTest(test.TestCase):
class ShapeInferenceTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testRestoreV2WithSliceInput(self):
op = io_ops.restore_v2("model", ["var1", "var2"], ["", "3 4 0,1:-"],
[dtypes.float32, dtypes.float32])
@@ -62,11 +63,13 @@ class ShapeInferenceTest(test.TestCase):
self.assertFalse(op[0].get_shape().is_fully_defined())
self.assertEqual([1, 4], op[1].get_shape())
+ @test_util.run_deprecated_v1
def testRestoreV2NumSlicesNotMatch(self):
with self.assertRaises(ValueError):
io_ops.restore_v2("model", ["var1", "var2", "var3"], ["", "3 4 0,1:-"],
[dtypes.float32, dtypes.float32])
+ @test_util.run_deprecated_v1
def testRestoreSlice(self):
op = gen_io_ops.restore_slice("model", "var", "3 4 0,1:-", dtypes.float32)
self.assertEqual([1, 4], op.get_shape())
diff --git a/tensorflow/python/kernel_tests/scan_ops_test.py b/tensorflow/python/kernel_tests/scan_ops_test.py
index c48e0e2e674..33e491fee1d 100644
--- a/tensorflow/python/kernel_tests/scan_ops_test.py
+++ b/tensorflow/python/kernel_tests/scan_ops_test.py
@@ -24,6 +24,7 @@ from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors_impl
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import math_ops
from tensorflow.python.platform import test
@@ -88,12 +89,14 @@ class CumsumTest(test.TestCase):
for reverse in [True, False]:
self._compare(x, axis, exclusive, reverse)
+ @test_util.run_deprecated_v1
def testEmpty(self):
for dtype in self.valid_dtypes:
x = np.zeros([0]).astype(dtype)
for axis in (-1, 0):
self._compareAll(x, axis)
+ @test_util.run_deprecated_v1
def testAxisType(self):
for dtype in self.valid_dtypes:
x = np.arange(1, 6).reshape([5]).astype(dtype)
@@ -102,30 +105,35 @@ class CumsumTest(test.TestCase):
axis = constant_op.constant(0, axis_dtype)
tf_out = math_ops.cumsum(x, axis).eval()
+ @test_util.run_deprecated_v1
def test1D(self):
for dtype in self.valid_dtypes:
x = np.arange(1, 6).reshape([5]).astype(dtype)
for axis in (-1, 0):
self._compareAll(x, axis)
+ @test_util.run_deprecated_v1
def test2D(self):
for dtype in self.valid_dtypes:
x = np.arange(0, 10).reshape([2, 5]).astype(dtype)
for axis in (-2, -1, 0, 1):
self._compareAll(x, axis)
+ @test_util.run_deprecated_v1
def test3D(self):
for dtype in self.valid_dtypes:
x = np.arange(0, 20).reshape([2, 2, 5]).astype(dtype)
for axis in (-3, -2, -1, 0, 1, 2):
self._compareAll(x, axis)
+ @test_util.run_deprecated_v1
def test6D(self):
for dtype in self.valid_dtypes:
x = np.arange(1, 145).reshape([2, 2, 3, 3, 2, 2]).astype(dtype)
for axis in range(-6, 6, 3):
self._compareAll(x, axis)
+ @test_util.run_deprecated_v1
def testLarge(self):
for dtype in self.valid_dtypes:
x = np.ones([1000000], dtype=dtype) / 1024
@@ -157,22 +165,27 @@ class CumsumTest(test.TestCase):
t, shape, result, shape, x_init_value=x, delta=1)
self.assertAllClose(jacob_t, jacob_n, rtol=1e-8, atol=1e-8)
+ @test_util.run_deprecated_v1
def testGradient(self):
for axis in (-1, 0):
self._compareGradient([50], axis, False, False)
+ @test_util.run_deprecated_v1
def testGradientReverse(self):
for axis in (-1, 0):
self._compareGradient([50], axis, False, True)
+ @test_util.run_deprecated_v1
def testGradientExclusive(self):
for axis in (-1, 0):
self._compareGradient([50], axis, True, False)
+ @test_util.run_deprecated_v1
def testGradientExclusiveReverse(self):
for axis in (-1, 0):
self._compareGradient([50], axis, True, True)
+ @test_util.run_deprecated_v1
def testGradient2D(self):
for axis in (-1, 0, 1):
for exclusive in [True, False]:
@@ -199,12 +212,14 @@ class CumprodTest(test.TestCase):
for reverse in [True, False]:
self._compare(x, axis, exclusive, reverse)
+ @test_util.run_deprecated_v1
def testEmpty(self):
for dtype in self.valid_dtypes:
x = np.zeros([0]).astype(dtype)
for axis in (-1, 0):
self._compareAll(x, axis)
+ @test_util.run_deprecated_v1
def testAxisType(self):
for dtype in self.valid_dtypes:
x = np.arange(1, 6).reshape([5]).astype(dtype)
@@ -213,24 +228,28 @@ class CumprodTest(test.TestCase):
axis = constant_op.constant(0, axis_dtype)
tf_out = math_ops.cumprod(x, axis).eval()
+ @test_util.run_deprecated_v1
def test1D(self):
for dtype in self.valid_dtypes:
x = np.arange(1, 6).reshape([5]).astype(dtype)
for axis in (-1, 0):
self._compareAll(x, axis)
+ @test_util.run_deprecated_v1
def test2D(self):
for dtype in self.valid_dtypes:
x = np.arange(1, 11).reshape([2, 5]).astype(dtype)
for axis in (-2, -1, 0, 1):
self._compareAll(x, axis)
+ @test_util.run_deprecated_v1
def test3D(self):
for dtype in self.valid_dtypes:
x = np.arange(1, 21).reshape([2, 2, 5]).astype(dtype)
for axis in (-3, -2, -1, 0, 1, 2):
self._compareAll(x, axis)
+ @test_util.run_deprecated_v1
def test6D(self):
for dtype in self.valid_dtypes:
x = np.arange(1, 145).reshape([2, 2, 3, 3, 2, 2]).astype(dtype)
@@ -263,22 +282,27 @@ class CumprodTest(test.TestCase):
t, shape, result, shape, x_init_value=x, delta=1)
self.assertAllClose(jacob_t, jacob_n, rtol=1e-8, atol=1e-8)
+ @test_util.run_deprecated_v1
def testGradient(self):
for axis in (-1, 0):
self._compareGradient([8], axis, False, False)
+ @test_util.run_deprecated_v1
def testGradientReverse(self):
for axis in (-1, 0):
self._compareGradient([8], axis, False, True)
+ @test_util.run_deprecated_v1
def testGradientExclusive(self):
for axis in (-1, 0):
self._compareGradient([8], axis, True, False)
+ @test_util.run_deprecated_v1
def testGradientExclusiveReverse(self):
for axis in (-1, 0):
self._compareGradient([8], axis, True, True)
+ @test_util.run_deprecated_v1
def testGradient2D(self):
for axis in (-2, -1, 0, 1):
for exclusive in [True, False]:
diff --git a/tensorflow/python/kernel_tests/scatter_nd_ops_test.py b/tensorflow/python/kernel_tests/scatter_nd_ops_test.py
index c3881219828..298db1547ad 100644
--- a/tensorflow/python/kernel_tests/scatter_nd_ops_test.py
+++ b/tensorflow/python/kernel_tests/scatter_nd_ops_test.py
@@ -165,6 +165,7 @@ class StatefulScatterNdTest(test.TestCase):
result = self.evaluate(scatter)
self.assertAllClose(result, expected)
+ @test_util.run_deprecated_v1
def testSimpleResource(self):
indices = constant_op.constant([[4], [3], [1], [7]], dtype=dtypes.int32)
updates = constant_op.constant([9, 10, 11, 12], dtype=dtypes.float32)
@@ -207,12 +208,15 @@ class StatefulScatterNdTest(test.TestCase):
result = self.evaluate(scatter)
self.assertAllClose(result, expected)
+ @test_util.run_deprecated_v1
def testVariableRankUpdate(self):
self._VariableRankTests(_NumpyUpdate, state_ops.scatter_nd_update)
+ @test_util.run_deprecated_v1
def testVariableRankAdd(self):
self._VariableRankTests(_NumpyAdd, state_ops.scatter_nd_add)
+ @test_util.run_deprecated_v1
def testVariableRankSub(self):
self._VariableRankTests(_NumpySub, state_ops.scatter_nd_sub)
@@ -230,6 +234,7 @@ class StatefulScatterNdTest(test.TestCase):
self._VariableRankTest(
np_scatter, tf_scatter, vtype, itype, repeat_indices=True)
+ @test_util.run_deprecated_v1
def testScatterRepeatIndices(self):
"""This tests scatter_add using indices that repeat."""
self._ScatterRepeatIndicesTest(_NumpyAdd, state_ops.scatter_nd_add)
@@ -251,6 +256,7 @@ class StatefulScatterNdTest(test.TestCase):
# session.run([update0, update1])
# self.assertAllEqual([False, True], self.evaluate(var))
+ @test_util.run_deprecated_v1
def testScatterOutOfRangeCpu(self):
# TODO(simister): Re-enable once binary size increase due to
# scatter_nd ops is under control.
@@ -287,6 +293,7 @@ class StatefulScatterNdTest(test.TestCase):
state_ops.scatter_nd_update(ref, indices,
updates).get_shape().as_list(), shape)
+ @test_util.run_deprecated_v1
def testResVarInvalidOutputShape(self):
res = variables.Variable(
initial_value=lambda: array_ops.zeros(shape=[], dtype=dtypes.float32),
@@ -296,6 +303,7 @@ class StatefulScatterNdTest(test.TestCase):
with self.assertRaisesOpError("Output must be at least 1-D"):
state_ops.scatter_nd_update(res, [[0]], [0.22]).eval()
+ @test_util.run_deprecated_v1
def testExtraIndicesDimensions(self):
indices = array_ops.zeros([1, 1, 2], dtypes.int32)
updates = array_ops.zeros([1, 1], dtypes.int32)
@@ -309,6 +317,7 @@ class StatefulScatterNdTest(test.TestCase):
ref.initializer.run()
self.assertAllEqual(expected_result, self.evaluate(scatter_update))
+ @test_util.run_deprecated_v1
def testRank3InvalidShape1(self):
indices = array_ops.zeros([3, 2, 2], dtypes.int32)
updates = array_ops.zeros([2, 2, 2], dtypes.int32)
@@ -318,6 +327,7 @@ class StatefulScatterNdTest(test.TestCase):
ValueError, "The outer \\d+ dimensions of indices\\.shape="):
state_ops.scatter_nd_update(ref, indices, updates)
+ @test_util.run_deprecated_v1
def testRank3InvalidShape2(self):
indices = array_ops.zeros([2, 2, 1], dtypes.int32)
updates = array_ops.zeros([2, 2], dtypes.int32)
@@ -327,6 +337,7 @@ class StatefulScatterNdTest(test.TestCase):
ValueError, "The inner \\d+ dimensions of input\\.shape="):
state_ops.scatter_nd_update(ref, indices, updates)
+ @test_util.run_deprecated_v1
def testConcurrentUpdates(self):
num_updates = 10000
update_values = np.random.rand(num_updates)
@@ -455,6 +466,7 @@ class ScatterNdTest(test.TestCase):
self.assertAllEqual(
self.scatter_nd(indices, updates, shape).get_shape().as_list(), shape)
+ @test_util.run_deprecated_v1
def testExtraIndicesDimensions(self):
indices = array_ops.zeros([1, 1, 2], dtypes.int32)
updates = array_ops.zeros([1, 1], dtypes.int32)
@@ -465,24 +477,28 @@ class ScatterNdTest(test.TestCase):
with self.cached_session():
self.assertAllEqual(expected_result, self.evaluate(scatter))
+ @test_util.run_deprecated_v1
def testUndefinedIndicesShape(self):
indices = array_ops.placeholder(dtypes.int32, shape=None)
updates = array_ops.placeholder(dtypes.int32, shape=[2, 2, 2])
shape = constant_op.constant([2, 2, 2], dtypes.int32)
self.scatter_nd(indices, updates, shape)
+ @test_util.run_deprecated_v1
def testUndefinedUpdatesShape(self):
indices = array_ops.placeholder(dtypes.int32, shape=[2, 2, 2])
updates = array_ops.placeholder(dtypes.int32, shape=None)
shape = constant_op.constant([2, 2, 2], dtypes.int32)
self.scatter_nd(indices, updates, shape)
+ @test_util.run_deprecated_v1
def testUndefinedOutputShape(self):
indices = array_ops.placeholder(dtypes.int32, shape=[2, 2, 2])
updates = array_ops.placeholder(dtypes.int32, shape=[2, 2, 2])
shape = array_ops.placeholder(dtypes.int32, shape=[None])
self.scatter_nd(indices, updates, shape)
+ @test_util.run_deprecated_v1
def testEmptyOutputShape1(self):
indices = array_ops.zeros([2, 2, 2], dtypes.int32)
updates = array_ops.zeros([2, 2, 2], dtypes.int32)
@@ -492,6 +508,7 @@ class ScatterNdTest(test.TestCase):
ValueError, "Indices and updates specified for empty output shape"):
self.scatter_nd(indices, updates, shape)
+ @test_util.run_deprecated_v1
def testEmptyOutputShape2(self):
indices = array_ops.placeholder(dtypes.int32, shape=None)
updates = array_ops.placeholder(dtypes.int32, shape=None)
@@ -505,6 +522,7 @@ class ScatterNdTest(test.TestCase):
updates: np.zeros([2, 2, 2], dtype=np.int32)
})
+ @test_util.run_deprecated_v1
def testEmptyOutputShape3(self):
indices = array_ops.zeros([0], dtypes.int32)
updates = array_ops.zeros([0], dtypes.int32)
@@ -514,6 +532,7 @@ class ScatterNdTest(test.TestCase):
with self.cached_session():
self.assertEqual(scatter.eval().size, 0)
+ @test_util.run_deprecated_v1
def testRank3InvalidShape1(self):
indices = array_ops.zeros([3, 2, 2], dtypes.int32)
updates = array_ops.zeros([2, 2, 2], dtypes.int32)
@@ -522,6 +541,7 @@ class ScatterNdTest(test.TestCase):
ValueError, "The outer \\d+ dimensions of indices\\.shape="):
self.scatter_nd(indices, updates, shape)
+ @test_util.run_deprecated_v1
def testRank3InvalidShape2(self):
indices = array_ops.zeros([2, 2, 1], dtypes.int32)
updates = array_ops.zeros([2, 2], dtypes.int32)
@@ -530,6 +550,7 @@ class ScatterNdTest(test.TestCase):
ValueError, "The inner \\d+ dimensions of (input|output)\\.shape="):
self.scatter_nd(indices, updates, shape)
+ @test_util.run_deprecated_v1
def testGradientsRank2ElementUpdate(self):
for dtype in GRADIENT_TESTS_DTYPES:
indices = constant_op.constant([[0, 0], [1, 1]], dtype=dtypes.int32)
@@ -549,6 +570,7 @@ class ScatterNdTest(test.TestCase):
if self.non_aliasing_add_test:
self.assertAllEqual(expected_input_grad, self.evaluate(input_grad))
+ @test_util.run_deprecated_v1
def testGradientsRank2SliceUpdate(self):
for dtype in GRADIENT_TESTS_DTYPES:
indices = constant_op.constant([[1], [0]], dtype=dtypes.int32)
@@ -569,6 +591,7 @@ class ScatterNdTest(test.TestCase):
if self.non_aliasing_add_test:
self.assertAllEqual(expected_input_grad, self.evaluate(input_grad))
+ @test_util.run_deprecated_v1
def testGradientsRank3SliceUpdate(self):
for dtype in GRADIENT_TESTS_DTYPES:
indices = constant_op.constant([[[0, 1], [1, 0]], [[0, 0], [1, 1]]],
@@ -592,6 +615,7 @@ class ScatterNdTest(test.TestCase):
if self.non_aliasing_add_test:
self.assertAllEqual(expected_input_grad, self.evaluate(input_grad))
+ @test_util.run_deprecated_v1
def testGradientsRank7SliceUpdate(self):
for dtype in GRADIENT_TESTS_DTYPES:
indices = constant_op.constant(
@@ -619,6 +643,7 @@ class ScatterNdTest(test.TestCase):
if self.non_aliasing_add_test:
self.assertAllEqual(expected_input_grad, self.evaluate(input_grad))
+ @test_util.run_deprecated_v1
def testScatterNdRepatedIndicesAdd(self):
indices = array_ops.zeros([100000, 1], dtypes.int32)
values = np.random.randn(100000)
@@ -627,6 +652,7 @@ class ScatterNdTest(test.TestCase):
val = self.scatter_nd(indices, values, shape).eval()
self.assertAllClose([np.sum(values)], val)
+ @test_util.run_deprecated_v1
def testSmokeScatterNdBatch2DSliceDim2(self):
with self.cached_session():
indices = array_ops.zeros([3, 5, 2], dtype=dtypes.int32)
@@ -634,6 +660,7 @@ class ScatterNdTest(test.TestCase):
shape = [4, 6, 7]
self.scatter_nd(indices, values, shape).eval()
+ @test_util.run_deprecated_v1
def testSmokeScatterNdBatch1DSliceDim2(self):
with self.cached_session():
indices = array_ops.zeros([0, 2], dtype=dtypes.int32)
@@ -641,6 +668,7 @@ class ScatterNdTest(test.TestCase):
shape = [4, 6, 7]
self.scatter_nd(indices, values, shape).eval()
+ @test_util.run_deprecated_v1
def testSmokeScatterNdBatch1DSliceDim3ShapeRank7(self):
with self.cached_session():
indices = array_ops.zeros([1, 3], dtype=dtypes.int32)
@@ -648,6 +676,7 @@ class ScatterNdTest(test.TestCase):
shape = [3, 4, 5, 6, 7, 8, 9]
self.scatter_nd(indices, values, shape).eval()
+ @test_util.run_deprecated_v1
def testSmokeScatterNdBatch2DSliceDim3ShapeRank7(self):
with self.cached_session():
indices = array_ops.zeros([1, 2, 3], dtype=dtypes.int32)
diff --git a/tensorflow/python/kernel_tests/scatter_ops_test.py b/tensorflow/python/kernel_tests/scatter_ops_test.py
index a4daad7adcc..623c17d373c 100644
--- a/tensorflow/python/kernel_tests/scatter_ops_test.py
+++ b/tensorflow/python/kernel_tests/scatter_ops_test.py
@@ -197,84 +197,111 @@ class ScatterTest(test.TestCase):
self._VariableRankTest(tf_scatter, vtype, itype, repeat_indices,
updates_are_scalar)
+ @test_util.run_deprecated_v1
def testVariableRankUpdate(self):
self._VariableRankTests(state_ops.scatter_update, False)
+ @test_util.run_deprecated_v1
def testVariableRankAdd(self):
self._VariableRankTests(state_ops.scatter_add, False)
+ @test_util.run_deprecated_v1
def testVariableRankSub(self):
self._VariableRankTests(state_ops.scatter_sub, False)
+ @test_util.run_deprecated_v1
def testVariableRankMul(self):
self._VariableRankTests(state_ops.scatter_mul, False)
+ @test_util.run_deprecated_v1
def testVariableRankDiv(self):
self._VariableRankTests(state_ops.scatter_div, False)
+ @test_util.run_deprecated_v1
def testVariableRankMin(self):
self._VariableRankTests(state_ops.scatter_min, False)
+ @test_util.run_deprecated_v1
def testVariableRankMax(self):
self._VariableRankTests(state_ops.scatter_max, False)
+ @test_util.run_deprecated_v1
def testRepeatIndicesAdd(self):
self._VariableRankTests(state_ops.scatter_add, True)
+ @test_util.run_deprecated_v1
def testRepeatIndicesSub(self):
self._VariableRankTests(state_ops.scatter_sub, True)
+ @test_util.run_deprecated_v1
def testRepeatIndicesMul(self):
self._VariableRankTests(state_ops.scatter_mul, True)
+ @test_util.run_deprecated_v1
def testRepeatIndicesDiv(self):
self._VariableRankTests(state_ops.scatter_div, True)
+ @test_util.run_deprecated_v1
def testRepeatIndicesMin(self):
self._VariableRankTests(state_ops.scatter_min, True)
+ @test_util.run_deprecated_v1
def testRepeatIndicesMax(self):
self._VariableRankTests(state_ops.scatter_max, True)
+ @test_util.run_deprecated_v1
def testVariableRankUpdateScalar(self):
self._VariableRankTests(state_ops.scatter_update, False, True)
+ @test_util.run_deprecated_v1
def testVariableRankAddScalar(self):
self._VariableRankTests(state_ops.scatter_add, False, True)
+ @test_util.run_deprecated_v1
def testVariableRankSubScalar(self):
self._VariableRankTests(state_ops.scatter_sub, False, True)
+ @test_util.run_deprecated_v1
def testVariableRankMulScalar(self):
self._VariableRankTests(state_ops.scatter_mul, False, True)
+ @test_util.run_deprecated_v1
def testVariableRankDivScalar(self):
self._VariableRankTests(state_ops.scatter_div, False, True)
+ @test_util.run_deprecated_v1
def testVariableRankMinScalar(self):
self._VariableRankTests(state_ops.scatter_min, False, True)
+ @test_util.run_deprecated_v1
def testVariableRankMaxScalar(self):
self._VariableRankTests(state_ops.scatter_max, False, True)
+ @test_util.run_deprecated_v1
def testRepeatIndicesAddScalar(self):
self._VariableRankTests(state_ops.scatter_add, True, True)
+ @test_util.run_deprecated_v1
def testRepeatIndicesSubScalar(self):
self._VariableRankTests(state_ops.scatter_sub, True, True)
+ @test_util.run_deprecated_v1
def testRepeatIndicesMulScalar(self):
self._VariableRankTests(state_ops.scatter_mul, True, True)
+ @test_util.run_deprecated_v1
def testRepeatIndicesDivScalar(self):
self._VariableRankTests(state_ops.scatter_div, True, True)
+ @test_util.run_deprecated_v1
def testRepeatIndicesMinScalar(self):
self._VariableRankTests(state_ops.scatter_min, True, True)
+ @test_util.run_deprecated_v1
def testRepeatIndicesMaxScalar(self):
self._VariableRankTests(state_ops.scatter_max, True, True)
+ @test_util.run_deprecated_v1
def testBooleanScatterUpdate(self):
if not test.is_gpu_available():
with self.session(use_gpu=False) as session:
@@ -289,6 +316,7 @@ class ScatterTest(test.TestCase):
self.assertAllEqual([False, True], self.evaluate(var))
+ @test_util.run_deprecated_v1
def testScatterOutOfRangeCpu(self):
for op, _ in _TF_OPS_TO_NUMPY.items():
params = np.array([1, 2, 3, 4, 5, 6]).astype(np.float32)
diff --git a/tensorflow/python/kernel_tests/segment_reduction_ops_test.py b/tensorflow/python/kernel_tests/segment_reduction_ops_test.py
index 5ab889895ec..8af1b47e83c 100644
--- a/tensorflow/python/kernel_tests/segment_reduction_ops_test.py
+++ b/tensorflow/python/kernel_tests/segment_reduction_ops_test.py
@@ -26,6 +26,7 @@ from tensorflow.python.client import session
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes as dtypes_lib
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import variables
@@ -126,6 +127,7 @@ class SegmentReductionOpTest(SegmentReductionHelper):
# and may therefore vary dynamically.
self.assertAllEqual(np_ans.shape[1:], tf_ans.shape[1:])
+ @test_util.run_deprecated_v1
def testSegmentIdsShape(self):
shape = [4, 4]
tf_x, _ = self._input(shape)
@@ -133,6 +135,7 @@ class SegmentReductionOpTest(SegmentReductionHelper):
with self.assertRaises(ValueError):
math_ops.segment_sum(data=tf_x, segment_ids=indices)
+ @test_util.run_deprecated_v1
def testSegmentIdsSize(self):
shape = [4, 4]
for use_gpu in [True, False]:
@@ -143,6 +146,7 @@ class SegmentReductionOpTest(SegmentReductionHelper):
with self.assertRaisesOpError("segment_ids should be the same size"):
self.evaluate(s)
+ @test_util.run_deprecated_v1
def testSegmentIdsValid(self):
# This is a baseline for the following SegmentIdsInvalid* tests.
shape = [4, 4]
@@ -175,6 +179,7 @@ class SegmentReductionOpTest(SegmentReductionHelper):
tf_ans = self.evaluate(s)
self.assertAllClose(np_ans, tf_ans)
+ @test_util.run_deprecated_v1
def testSegmentIdsInvalid1(self):
shape = [4, 4]
with self.cached_session():
@@ -186,6 +191,7 @@ class SegmentReductionOpTest(SegmentReductionHelper):
"'segment_ids' input is not sorted."):
self.evaluate(s)
+ @test_util.run_deprecated_v1
def testSegmentIdsInvalid2(self):
shape = [4, 4]
with self.cached_session():
@@ -195,6 +201,7 @@ class SegmentReductionOpTest(SegmentReductionHelper):
with self.assertRaisesOpError("segment ids are not increasing"):
self.evaluate(s)
+ @test_util.run_deprecated_v1
def testSegmentIdsInvalid3(self):
shape = [4, 4]
with self.cached_session():
@@ -206,6 +213,7 @@ class SegmentReductionOpTest(SegmentReductionHelper):
"because 'segment_ids' input is not sorted."):
self.evaluate(s)
+ @test_util.run_deprecated_v1
def testSegmentIdsInvalid4(self):
shape = [4, 4]
for use_gpu in [True, False]:
@@ -216,6 +224,7 @@ class SegmentReductionOpTest(SegmentReductionHelper):
with self.assertRaisesOpError("segment ids must be >= 0"):
self.evaluate(s)
+ @test_util.run_deprecated_v1
def testSegmentIdsInvalid5(self):
shape = [4, 4]
for use_gpu in [True, False]:
@@ -226,6 +235,7 @@ class SegmentReductionOpTest(SegmentReductionHelper):
with self.assertRaisesOpError("segment ids must be >= 0"):
self.evaluate(s)
+ @test_util.run_deprecated_v1
def testGradient(self):
shape = [4, 4]
indices = [0, 1, 2, 2]
@@ -324,6 +334,7 @@ class UnsortedSegmentTest(SegmentReductionHelper):
self.assertAllClose(np_ans, tf_ans)
self.assertShapeEqual(np_ans, s)
+ @test_util.run_deprecated_v1
def testGradients(self):
num_cols = 2
indices_flat = np.array([0, 4, 0, -1, 3, -1, 4, 7, 7, 3])
@@ -346,6 +357,7 @@ class UnsortedSegmentTest(SegmentReductionHelper):
delta=1)
self.assertAllClose(jacob_t, jacob_n)
+ @test_util.run_deprecated_v1
def testProdGrad(self):
# additional test for the prod gradient to ensure correct handling of zeros
values = np.array([0, 0, 1, 0, 2, 2, 3, 3, 3], dtype=np.float32)
@@ -370,6 +382,7 @@ class UnsortedSegmentTest(SegmentReductionHelper):
self.assertAllClose(jacob_t, jacob_n)
self.assertAllClose(jacob_t, grad_gt)
+ @test_util.run_deprecated_v1
def testGradientMatchesSegmentSum(self):
# Strategy: compute the gradient for UnsortedSegmentSum and SegmentSum
# and compare the outputs, which should be identical.
@@ -403,6 +416,7 @@ class UnsortedSegmentTest(SegmentReductionHelper):
self.assertAllClose(unsorted_jacob_t, sorted_jacob_t)
self.assertAllClose(unsorted_jacob_n, sorted_jacob_n)
+ @test_util.run_deprecated_v1
def testBadIndices(self):
# Note: GPU kernel does not return the out-of-range error needed for this
# test, so this test is marked as cpu-only.
@@ -414,6 +428,7 @@ class UnsortedSegmentTest(SegmentReductionHelper):
r"segment_ids\[0,0\] = %d is out of range \[0, 2\)" % bad[0][0]):
self.evaluate(unsorted)
+ @test_util.run_deprecated_v1
def testEmptySecondDimension(self):
dtypes = [np.float16, np.float32, np.float64, np.int64, np.int32,
np.complex64, np.complex128]
@@ -590,6 +605,7 @@ class SparseSegmentReductionOpTest(SparseSegmentReductionHelper):
s = tf_op(data=tf_x, indices=tf_indices, segment_ids=segment_indices)
self.evaluate(s)
+ @test_util.run_deprecated_v1
def testIndicesInvalid1(self):
tf_x, _ = self._input([10, 4], dtype=dtypes_lib.float32)
ops_list = [math_ops.sparse_segment_sum, math_ops.sparse_segment_mean]
@@ -602,6 +618,7 @@ class SparseSegmentReductionOpTest(SparseSegmentReductionHelper):
r"indices\[1\] == -1 out of range \[0, 10\)"):
self.evaluate(s)
+ @test_util.run_deprecated_v1
def testIndicesInvalid2(self):
tf_x, _ = self._input([10, 4], dtype=dtypes_lib.float32)
ops_list = [math_ops.sparse_segment_sum, math_ops.sparse_segment_mean]
@@ -614,6 +631,7 @@ class SparseSegmentReductionOpTest(SparseSegmentReductionHelper):
r"indices\[3\] == 10 out of range \[0, 10\)"):
self.evaluate(s)
+ @test_util.run_deprecated_v1
def testSegmentsInvalid2(self):
tf_x, _ = self._input([10, 4], dtype=dtypes_lib.float32)
ops_list = [math_ops.sparse_segment_sum, math_ops.sparse_segment_mean]
@@ -625,6 +643,7 @@ class SparseSegmentReductionOpTest(SparseSegmentReductionHelper):
with self.assertRaisesOpError("segment ids are not increasing"):
self.evaluate(s)
+ @test_util.run_deprecated_v1
def testSegmentsInvalid3(self):
tf_x, _ = self._input([10, 4], dtype=dtypes_lib.float32)
ops_list = [math_ops.sparse_segment_sum, math_ops.sparse_segment_mean]
@@ -638,6 +657,7 @@ class SparseSegmentReductionOpTest(SparseSegmentReductionHelper):
"'segment_ids' input is not sorted"):
self.evaluate(s)
+ @test_util.run_deprecated_v1
def testSegmentsInvalid4(self):
tf_x, _ = self._input([10, 4], dtype=dtypes_lib.float32)
ops_list = [math_ops.sparse_segment_sum, math_ops.sparse_segment_mean]
@@ -651,6 +671,7 @@ class SparseSegmentReductionOpTest(SparseSegmentReductionHelper):
"'segment_ids' input is not sorted"):
self.evaluate(s)
+ @test_util.run_deprecated_v1
def testSegmentsInvalid6(self):
tf_x, _ = self._input([10, 4], dtype=dtypes_lib.float32)
ops_list = [math_ops.sparse_segment_sum, math_ops.sparse_segment_mean]
@@ -662,6 +683,7 @@ class SparseSegmentReductionOpTest(SparseSegmentReductionHelper):
with self.assertRaisesOpError("segment ids must be >= 0"):
self.evaluate(s)
+ @test_util.run_deprecated_v1
def testSegmentsInvalid7(self):
tf_x, _ = self._input([10, 4], dtype=dtypes_lib.float32)
ops_list = [math_ops.sparse_segment_sum, math_ops.sparse_segment_mean]
@@ -692,6 +714,7 @@ class SparseSegmentReductionOpTest(SparseSegmentReductionHelper):
num_segments=num_segments)
self.evaluate(s)
+ @test_util.run_deprecated_v1
def testSegmentWithNumSegmentsInvalid1(self):
tf_x, _ = self._input([10, 4], dtype=dtypes_lib.float32)
ops_list = [
@@ -711,6 +734,7 @@ class SparseSegmentReductionOpTest(SparseSegmentReductionHelper):
with self.assertRaisesOpError("segment ids must be < num_segments"):
self.evaluate(s)
+ @test_util.run_deprecated_v1
def testSegmentWithNumSegmentsInvalid2(self):
tf_x, _ = self._input([10, 4], dtype=dtypes_lib.float32)
ops_list = [
@@ -730,6 +754,7 @@ class SparseSegmentReductionOpTest(SparseSegmentReductionHelper):
segment_ids=segment_indices,
num_segments=num_segments)
+ @test_util.run_deprecated_v1
def testGradient(self):
shape = [10, 4]
@@ -748,6 +773,7 @@ class SparseSegmentReductionOpTest(SparseSegmentReductionHelper):
delta=1)
self.assertAllClose(jacob_t, jacob_n)
+ @test_util.run_deprecated_v1
def testGradientWithEmptySegmentsAtEnd(self):
shape = [10, 4]
@@ -787,6 +813,7 @@ class SparseSegmentReductionOpTest(SparseSegmentReductionHelper):
s = tf_op(tf_x, tf_indices, segment_indices, 10)
self.evaluate(s)
+ @test_util.run_deprecated_v1
def testGradientIndicesInvalid1(self):
tf_x, _ = self._input([3, 4], dtype=dtypes_lib.float32)
ops_list = [
@@ -800,6 +827,7 @@ class SparseSegmentReductionOpTest(SparseSegmentReductionHelper):
with self.assertRaisesOpError(r"Index 10 out of range \[0, 10\)"):
self.evaluate(s)
+ @test_util.run_deprecated_v1
def testGradientIndicesInvalid2(self):
tf_x, _ = self._input([3, 4], dtype=dtypes_lib.float32)
ops_list = [
@@ -813,6 +841,7 @@ class SparseSegmentReductionOpTest(SparseSegmentReductionHelper):
with self.assertRaisesOpError(r"Index -1 out of range \[0, 10\)"):
self.evaluate(s)
+ @test_util.run_deprecated_v1
def testGradientSegmentsInvalid1(self):
tf_x, _ = self._input(
[3, 4], dtype=dtypes_lib.float32) # expecting 3 segments
@@ -827,6 +856,7 @@ class SparseSegmentReductionOpTest(SparseSegmentReductionHelper):
with self.assertRaisesOpError("Invalid number of segments"):
self.evaluate(s)
+ @test_util.run_deprecated_v1
def testGradientSegmentsInvalid2(self):
tf_x, _ = self._input([1, 4], dtype=dtypes_lib.float32)
ops_list = [
@@ -840,6 +870,7 @@ class SparseSegmentReductionOpTest(SparseSegmentReductionHelper):
with self.assertRaisesOpError(r"Segment id 1 out of range \[0, 1\)"):
self.evaluate(s)
+ @test_util.run_deprecated_v1
def testGradientSegmentsInvalid3(self):
tf_x, _ = self._input([2, 4], dtype=dtypes_lib.float32)
ops_list = [
@@ -853,6 +884,7 @@ class SparseSegmentReductionOpTest(SparseSegmentReductionHelper):
with self.assertRaisesOpError(r"Segment id -1 out of range \[0, 2\)"):
self.evaluate(s)
+ @test_util.run_deprecated_v1
def testGradientSegmentsInvalid4(self):
tf_x, _ = self._input([0, 4], dtype=dtypes_lib.float32)
ops_list = [
diff --git a/tensorflow/python/kernel_tests/sets_test.py b/tensorflow/python/kernel_tests/sets_test.py
index ba3d32b192d..b4f23229348 100644
--- a/tensorflow/python/kernel_tests/sets_test.py
+++ b/tensorflow/python/kernel_tests/sets_test.py
@@ -70,6 +70,7 @@ def _dense_to_sparse(dense, dtype):
class SetOpsTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def test_set_size_2d(self):
for dtype in _DTYPES:
self._test_set_size_2d(dtype)
@@ -83,6 +84,7 @@ class SetOpsTest(test_util.TensorFlowTestCase):
self.assertAllEqual(
[0, 3], self._set_size(_dense_to_sparse([[], [1, 9, 2]], dtype)))
+ @test_util.run_deprecated_v1
def test_set_size_duplicates_2d(self):
for dtype in _DTYPES:
self._test_set_size_duplicates_2d(dtype)
@@ -96,6 +98,7 @@ class SetOpsTest(test_util.TensorFlowTestCase):
6, 7, 8, 8, 6, 7, 5, 3, 3, 0, 6, 6, 9, 0, 0, 0
], [999, 1, -1000], [], [-1]], dtype)))
+ @test_util.run_deprecated_v1
def test_set_size_3d(self):
for dtype in _DTYPES:
self._test_set_size_3d(dtype)
@@ -163,6 +166,7 @@ class SetOpsTest(test_util.TensorFlowTestCase):
self.assertAllEqual(results[0], results[1])
return results[0]
+ @test_util.run_deprecated_v1
def test_set_intersection_multirow_2d(self):
for dtype in _DTYPES:
self._test_set_intersection_multirow_2d(dtype)
@@ -199,6 +203,7 @@ class SetOpsTest(test_util.TensorFlowTestCase):
self.assertAllEqual(expected_counts,
self._set_intersection_count(sp_a, sp_b))
+ @test_util.run_deprecated_v1
def test_dense_set_intersection_multirow_2d(self):
for dtype in _DTYPES:
self._test_dense_set_intersection_multirow_2d(dtype)
@@ -223,6 +228,7 @@ class SetOpsTest(test_util.TensorFlowTestCase):
dtype=dtype)
self.assertAllEqual(expected_counts, self._set_intersection_count(a, b))
+ @test_util.run_deprecated_v1
def test_set_intersection_duplicates_2d(self):
for dtype in _DTYPES:
self._test_set_intersection_duplicates_2d(dtype)
@@ -270,6 +276,7 @@ class SetOpsTest(test_util.TensorFlowTestCase):
self.assertAllEqual(expected_counts,
self._set_intersection_count(sp_a, sp_b))
+ @test_util.run_deprecated_v1
def test_set_intersection_3d(self):
for dtype in _DTYPES:
self._test_set_intersection_3d(dtype=dtype)
@@ -536,6 +543,7 @@ class SetOpsTest(test_util.TensorFlowTestCase):
with self.cached_session() as sess:
return self.evaluate(op)
+ @test_util.run_deprecated_v1
def test_set_difference_multirow_2d(self):
for dtype in _DTYPES:
self._test_set_difference_multirow_2d(dtype)
@@ -604,6 +612,7 @@ class SetOpsTest(test_util.TensorFlowTestCase):
self.assertAllEqual(expected_counts,
self._set_difference_count(sp_a, sp_b, False))
+ @test_util.run_deprecated_v1
def test_dense_set_difference_multirow_2d(self):
for dtype in _DTYPES:
self._test_dense_set_difference_multirow_2d(dtype)
@@ -647,6 +656,7 @@ class SetOpsTest(test_util.TensorFlowTestCase):
self.assertAllEqual(expected_counts,
self._set_difference_count(a, b, False))
+ @test_util.run_deprecated_v1
def test_sparse_set_difference_multirow_2d(self):
for dtype in _DTYPES:
self._test_sparse_set_difference_multirow_2d(dtype)
@@ -688,6 +698,7 @@ class SetOpsTest(test_util.TensorFlowTestCase):
self.assertAllEqual(expected_counts,
self._set_difference_count(sp_a, sp_b, False))
+ @test_util.run_deprecated_v1
def test_set_difference_duplicates_2d(self):
for dtype in _DTYPES:
self._test_set_difference_duplicates_2d(dtype)
@@ -755,6 +766,7 @@ class SetOpsTest(test_util.TensorFlowTestCase):
self.assertAllEqual(expected_counts,
self._set_difference_count(a, sp_b, False))
+ @test_util.run_deprecated_v1
def test_sparse_set_difference_3d(self):
for dtype in _DTYPES:
self._test_sparse_set_difference_3d(dtype)
@@ -974,6 +986,7 @@ class SetOpsTest(test_util.TensorFlowTestCase):
with self.cached_session() as sess:
return self.evaluate(op)
+ @test_util.run_deprecated_v1
def test_set_union_multirow_2d(self):
for dtype in _DTYPES:
self._test_set_union_multirow_2d(dtype)
@@ -1001,6 +1014,7 @@ class SetOpsTest(test_util.TensorFlowTestCase):
expected_indices, expected_values, expected_shape, union, dtype=dtype)
self.assertAllEqual(expected_counts, self._set_union_count(sp_a, sp_b))
+ @test_util.run_deprecated_v1
def test_dense_set_union_multirow_2d(self):
for dtype in _DTYPES:
self._test_dense_set_union_multirow_2d(dtype)
@@ -1021,6 +1035,7 @@ class SetOpsTest(test_util.TensorFlowTestCase):
expected_indices, expected_values, expected_shape, union, dtype=dtype)
self.assertAllEqual(expected_counts, self._set_union_count(a, b))
+ @test_util.run_deprecated_v1
def test_set_union_duplicates_2d(self):
for dtype in _DTYPES:
self._test_set_union_duplicates_2d(dtype)
@@ -1047,6 +1062,7 @@ class SetOpsTest(test_util.TensorFlowTestCase):
expected_indices, expected_values, expected_shape, union, dtype=dtype)
self.assertAllEqual([2], self._set_union_count(sp_a, sp_b))
+ @test_util.run_deprecated_v1
def test_sparse_set_union_3d(self):
for dtype in _DTYPES:
self._test_sparse_set_union_3d(dtype)
diff --git a/tensorflow/python/kernel_tests/shape_ops_test.py b/tensorflow/python/kernel_tests/shape_ops_test.py
index a0506fbfc57..c8e7c143ade 100644
--- a/tensorflow/python/kernel_tests/shape_ops_test.py
+++ b/tensorflow/python/kernel_tests/shape_ops_test.py
@@ -26,6 +26,7 @@ from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors_impl
from tensorflow.python.framework import importer
from tensorflow.python.framework import sparse_tensor
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import gradients_impl
@@ -227,6 +228,7 @@ class ShapeOpsTest(test.TestCase):
self._compareExpandDimsAll(choice([2, 3, 5]), -3)
self._compareExpandDimsAll(choice([2, 3, 5]), -4)
+ @test_util.run_deprecated_v1
def testExpandDimsErrors(self):
with self.cached_session():
self.assertRaises(ValueError, array_ops.expand_dims,
@@ -238,6 +240,7 @@ class ShapeOpsTest(test.TestCase):
self.assertRaises(ValueError, array_ops.expand_dims,
[False, True, True], 4)
+ @test_util.run_deprecated_v1
def testExpandDimsGradient(self):
with self.cached_session():
inp = constant_op.constant(
@@ -248,6 +251,7 @@ class ShapeOpsTest(test.TestCase):
[4, 1, 2])
self.assertLess(err, 1e-3)
+ @test_util.run_deprecated_v1
def testExpandDimsScalar(self):
with self.cached_session():
inp = constant_op.constant(7)
@@ -353,6 +357,7 @@ class ShapeOpsTest(test.TestCase):
tf_ans = self.evaluate(tensor)
self.assertEqual(np.shape(1), tf_ans.shape)
+ @test_util.run_deprecated_v1
def testSqueezeOnlyOnes(self):
for use_gpu in [False, True]:
with self.cached_session(use_gpu=use_gpu):
@@ -362,6 +367,7 @@ class ShapeOpsTest(test.TestCase):
self._compareSqueezeAll(input_1x1x3, [1])
self.assertRaises(ValueError, array_ops.squeeze, input_1x1x3, [2])
+ @test_util.run_deprecated_v1
def testSqueezeErrors(self):
for use_gpu in [False, True]:
with self.cached_session(use_gpu=use_gpu):
@@ -374,6 +380,7 @@ class ShapeOpsTest(test.TestCase):
self.assertRaises(ValueError, array_ops.squeeze,
np.zeros([1, 2, 1]), [2, 3])
+ @test_util.run_deprecated_v1
def testSqueezeGradient(self):
with self.cached_session():
inp = np.random.rand(4, 2).astype("f")
@@ -384,6 +391,7 @@ class ShapeOpsTest(test.TestCase):
[4, 2])
self.assertLess(err, 1e-3)
+ @test_util.run_deprecated_v1
def testSqueezeGradientWithSqueezeDims(self):
with self.cached_session():
inp = np.random.rand(4, 2).astype("f")
@@ -394,6 +402,7 @@ class ShapeOpsTest(test.TestCase):
[4, 2, 1])
self.assertLess(err, 1e-3)
+ @test_util.run_deprecated_v1
def testSqueezeWithUnknownShape(self):
with self.cached_session():
a = array_ops.placeholder(dtypes.float32, shape=[2, None])
@@ -451,6 +460,7 @@ class TileTest(test.TestCase):
self.assertEqual(result.shape, (10, 0))
self.assertEqual([10, 0], tiled.get_shape())
+ @test_util.run_deprecated_v1
def testUnknownInputShape(self):
"""Importing can call _TileShape without shape of <multiples> known."""
with self.cached_session():
@@ -502,6 +512,7 @@ class TileTest(test.TestCase):
self.assertEqual([4, 4], tiled.get_shape())
self.assertAllEqual(result, np.tile(inp, (1, 4)))
+ @test_util.run_deprecated_v1
def testInvalidDim(self):
with self.cached_session():
inp = np.random.rand(4, 1).astype("f")
@@ -545,6 +556,7 @@ class TileTest(test.TestCase):
for _ in range(5):
self._RunAndVerifyResult(10, use_gpu=True)
+ @test_util.run_deprecated_v1
def testGradientSimpleReduction(self):
with self.cached_session():
inp = np.random.rand(4, 1).astype("f")
@@ -560,6 +572,7 @@ class TileTest(test.TestCase):
result = self.evaluate(grad)
self.assertAllClose(np.sum(grad_inp, axis=1).reshape(4, 1), result, 1e-3)
+ @test_util.run_deprecated_v1
def testGradientStridedReduction(self):
with self.cached_session():
inp = np.random.rand(4, 2).astype("f")
@@ -579,6 +592,7 @@ class TileTest(test.TestCase):
expected[:, 1] = grad_inp[:, 1] + grad_inp[:, 3]
self.assertTrue((np.abs(expected - result) < 1e-3).all())
+ @test_util.run_deprecated_v1
def testGradientSimpleReductionOnGPU(self):
with self.session(use_gpu=True):
inp = np.random.rand(4, 1).astype("f")
@@ -593,6 +607,7 @@ class TileTest(test.TestCase):
result = self.evaluate(grad)
self.assertAllClose(np.sum(grad_inp, axis=1).reshape(4, 1), result, 1e-3)
+ @test_util.run_deprecated_v1
def testGradientStridedReductionOnGPU(self):
with self.session(use_gpu=True):
inp = np.random.rand(4, 2).astype("f")
@@ -624,15 +639,18 @@ class TileTest(test.TestCase):
print("tile(float) error = ", err)
self.assertLess(err, 1e-3)
+ @test_util.run_deprecated_v1
def testGradientRandomScalar(self):
self._RunAndVerifyGradientResult([], [])
+ @test_util.run_deprecated_v1
def testGradientRandom(self):
self._RunAndVerifyGradientResult([2, 2, 1, 1, 3], [1, 1, 1, 1, 1])
self._RunAndVerifyGradientResult([2, 2, 1, 1, 3], [1, 2, 1, 3, 1])
self._RunAndVerifyGradientResult([2, 3, 1, 1, 3], [3, 1, 1, 2, 2])
self._RunAndVerifyGradientResult([2, 1, 3, 3, 2], [1, 3, 3, 1, 2])
+ @test_util.run_deprecated_v1
def testGradientStridedReductionGC(self):
with self.cached_session():
inp = np.random.rand(4, 2).astype("f")
@@ -642,6 +660,7 @@ class TileTest(test.TestCase):
err = gradient_checker.compute_gradient_error(a, [4, 2], tiled, [4, 4])
self.assertLess(err, 1e-3)
+ @test_util.run_deprecated_v1
def testGradientWithSparseGradWithRank1(self):
inputs = constant_op.constant([1.0, 2.0, 3.0, 4.0],
dtype=dtypes.float32)
@@ -653,6 +672,7 @@ class TileTest(test.TestCase):
outputs, outputs.get_shape().as_list())
self.assertLess(error, 1e-4)
+ @test_util.run_deprecated_v1
def testGradientWithSparseGradWithRank3(self):
inputs = constant_op.constant([1.0, 2.0, 3.0, 4.0],
dtype=dtypes.float32)
@@ -665,6 +685,7 @@ class TileTest(test.TestCase):
outputs, outputs.get_shape().as_list())
self.assertLess(error, 1e-4)
+ @test_util.run_deprecated_v1
def testShapeFunctionEdgeCases(self):
# Unknown multiples shape.
inp = constant_op.constant(0.0, shape=[4, 4, 4, 4])
diff --git a/tensorflow/python/kernel_tests/signal/dct_ops_test.py b/tensorflow/python/kernel_tests/signal/dct_ops_test.py
index af4939332fd..a3ac15bab8a 100644
--- a/tensorflow/python/kernel_tests/signal/dct_ops_test.py
+++ b/tensorflow/python/kernel_tests/signal/dct_ops_test.py
@@ -23,6 +23,7 @@ import importlib
from absl.testing import parameterized
import numpy as np
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import spectral_ops_test_util
from tensorflow.python.ops.signal import dct_ops
from tensorflow.python.platform import test
@@ -132,6 +133,7 @@ class DCTOpsTest(parameterized.TestCase, test.TestCase):
@parameterized.parameters([
[[2]], [[3]], [[10]], [[2, 20]], [[2, 3, 25]]])
+ @test_util.run_deprecated_v1
def test_random(self, shape):
"""Test randomly generated batches of data."""
with spectral_ops_test_util.fft_kernel_label_map():
diff --git a/tensorflow/python/kernel_tests/signal/fft_ops_test.py b/tensorflow/python/kernel_tests/signal/fft_ops_test.py
index 3eeecc12a88..5b1053428c0 100644
--- a/tensorflow/python/kernel_tests/signal/fft_ops_test.py
+++ b/tensorflow/python/kernel_tests/signal/fft_ops_test.py
@@ -25,6 +25,7 @@ from tensorflow.core.protobuf import config_pb2
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gen_spectral_ops
from tensorflow.python.ops import gradient_checker
@@ -157,6 +158,7 @@ class FFTOpsTest(BaseFFTOpsTest):
else:
raise ValueError("invalid rank")
+ @test_util.run_deprecated_v1
def testEmpty(self):
with spectral_ops_test_util.fft_kernel_label_map():
for np_type in (np.complex64, np.complex128):
@@ -166,6 +168,7 @@ class FFTOpsTest(BaseFFTOpsTest):
self.assertEqual(x.shape, self._tfFFT(x, rank).shape)
self.assertEqual(x.shape, self._tfIFFT(x, rank).shape)
+ @test_util.run_deprecated_v1
def testBasic(self):
with spectral_ops_test_util.fft_kernel_label_map():
for np_type, tol in ((np.complex64, 1e-4), (np.complex128, 1e-8)):
@@ -194,6 +197,7 @@ class FFTOpsTest(BaseFFTOpsTest):
# np.mod(np.arange(np.power(128, dims)), 64).reshape(
# (128,) * dims).astype(np.complex64), rank)
+ @test_util.run_deprecated_v1
def testBasicPlaceholder(self):
with spectral_ops_test_util.fft_kernel_label_map():
for np_type, tol in ((np.complex64, 1e-4), (np.complex128, 1e-8)):
@@ -204,6 +208,7 @@ class FFTOpsTest(BaseFFTOpsTest):
(4,) * dims).astype(np_type),
rank, use_placeholder=True, rtol=tol, atol=tol)
+ @test_util.run_deprecated_v1
def testRandom(self):
with spectral_ops_test_util.fft_kernel_label_map():
for np_type, tol in ((np.complex64, 1e-4), (np.complex128, 5e-6)):
@@ -218,6 +223,7 @@ class FFTOpsTest(BaseFFTOpsTest):
self._compare(gen((4,) * dims).astype(np_type), rank,
rtol=tol, atol=tol)
+ @test_util.run_deprecated_v1
def testRandom1D(self):
with spectral_ops_test_util.fft_kernel_label_map():
for np_type in (np.complex64, np.complex128):
@@ -240,6 +246,7 @@ class FFTOpsTest(BaseFFTOpsTest):
for dim in (127, 255, 511, 1023):
self._compare(gen((dim,)).astype(np_type), 1, rtol=tol, atol=tol)
+ @test_util.run_deprecated_v1
def testError(self):
for rank in VALID_FFT_RANKS:
for dims in xrange(0, rank):
@@ -251,6 +258,7 @@ class FFTOpsTest(BaseFFTOpsTest):
ValueError, "Shape must be .*rank {}.*".format(rank)):
self._tfIFFT(x, rank)
+ @test_util.run_deprecated_v1
def testGrad_Simple(self):
with spectral_ops_test_util.fft_kernel_label_map():
for np_type, tol in ((np.float32, 1e-4), (np.float64, 1e-10)):
@@ -263,6 +271,7 @@ class FFTOpsTest(BaseFFTOpsTest):
self._checkGradComplex(self._tfIFFTForRank(rank), re, im,
rtol=tol, atol=tol)
+ @test_util.run_deprecated_v1
def testGrad_Random(self):
with spectral_ops_test_util.fft_kernel_label_map():
for np_type, tol in ((np.float32, 1e-2), (np.float64, 1e-10)):
@@ -330,6 +339,7 @@ class RFFTOpsTest(BaseFFTOpsTest):
else:
raise ValueError("invalid rank")
+ @test_util.run_deprecated_v1
def testEmpty(self):
with spectral_ops_test_util.fft_kernel_label_map():
for rank in VALID_FFT_RANKS:
@@ -339,6 +349,7 @@ class RFFTOpsTest(BaseFFTOpsTest):
x = np.zeros((0,) * dims).astype(np.complex64)
self.assertEqual(x.shape, self._tfIFFT(x, rank).shape)
+ @test_util.run_deprecated_v1
def testBasic(self):
with spectral_ops_test_util.fft_kernel_label_map():
for rank in VALID_FFT_RANKS:
@@ -366,6 +377,7 @@ class RFFTOpsTest(BaseFFTOpsTest):
10).reshape((size,) * (dims - 1) + (inner_dim,))
self._compareBackward(c2r.astype(np.complex64), rank, (size,) * rank)
+ @test_util.run_deprecated_v1
def testBasicPlaceholder(self):
with spectral_ops_test_util.fft_kernel_label_map():
for rank in VALID_FFT_RANKS:
@@ -427,6 +439,7 @@ class RFFTOpsTest(BaseFFTOpsTest):
fft_length,
use_placeholder=True)
+ @test_util.run_deprecated_v1
def testRandom(self):
with spectral_ops_test_util.fft_kernel_label_map():
def gen_real(shape):
@@ -451,6 +464,7 @@ class RFFTOpsTest(BaseFFTOpsTest):
self._compareBackward(
gen_complex(complex_dims), rank, (size,) * rank)
+ @test_util.run_deprecated_v1
def testError(self):
with spectral_ops_test_util.fft_kernel_label_map():
for rank in VALID_FFT_RANKS:
@@ -507,6 +521,7 @@ class RFFTOpsTest(BaseFFTOpsTest):
with self.cached_session():
irfft_fn(x, fft_length).eval()
+ @test_util.run_deprecated_v1
def testGrad_Simple(self):
with spectral_ops_test_util.fft_kernel_label_map():
for rank in VALID_FFT_RANKS:
@@ -521,6 +536,7 @@ class RFFTOpsTest(BaseFFTOpsTest):
self._checkGradComplex(
self._tfIFFTForRank(rank), re, im, result_is_complex=False)
+ @test_util.run_deprecated_v1
def testGrad_Random(self):
with spectral_ops_test_util.fft_kernel_label_map():
for rank in VALID_FFT_RANKS:
diff --git a/tensorflow/python/kernel_tests/signal/mel_ops_test.py b/tensorflow/python/kernel_tests/signal/mel_ops_test.py
index 2b3dde30f39..3134503daec 100644
--- a/tensorflow/python/kernel_tests/signal/mel_ops_test.py
+++ b/tensorflow/python/kernel_tests/signal/mel_ops_test.py
@@ -22,6 +22,7 @@ import numpy as np
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util as tf_test_util
from tensorflow.python.kernel_tests.signal import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops.signal import mel_ops
@@ -143,12 +144,14 @@ class LinearToMelTest(test.TestCase):
mel_matrix = mel_ops.linear_to_mel_weight_matrix(*config)
self.assertAllClose(mel_matrix_np, self.evaluate(mel_matrix), atol=3e-6)
+ @tf_test_util.run_deprecated_v1
def test_dtypes(self):
# LinSpace is not supported for tf.float16.
for dtype in (dtypes.bfloat16, dtypes.float32, dtypes.float64):
self.assertEqual(dtype,
mel_ops.linear_to_mel_weight_matrix(dtype=dtype).dtype)
+ @tf_test_util.run_deprecated_v1
def test_error(self):
with self.assertRaises(ValueError):
mel_ops.linear_to_mel_weight_matrix(num_mel_bins=0)
@@ -177,6 +180,7 @@ class LinearToMelTest(test.TestCase):
rewritten_graph = test_util.grappler_optimize(g, [mel_matrix])
self.assertEqual(1, len(rewritten_graph.node))
+ @tf_test_util.run_deprecated_v1
def test_num_spectrogram_bins_dynamic(self):
with self.session(use_gpu=True):
num_spectrogram_bins = array_ops.placeholder(shape=(),
diff --git a/tensorflow/python/kernel_tests/signal/mfcc_ops_test.py b/tensorflow/python/kernel_tests/signal/mfcc_ops_test.py
index 79d23d77d1e..935922657cd 100644
--- a/tensorflow/python/kernel_tests/signal/mfcc_ops_test.py
+++ b/tensorflow/python/kernel_tests/signal/mfcc_ops_test.py
@@ -20,6 +20,7 @@ from __future__ import print_function
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import tensor_shape
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import random_ops
from tensorflow.python.ops import spectral_ops_test_util
@@ -32,6 +33,7 @@ from tensorflow.python.platform import test
# HTK conventions.
class MFCCTest(test.TestCase):
+ @test_util.run_deprecated_v1
def test_error(self):
# num_mel_bins must be positive.
with self.assertRaises(ValueError):
@@ -43,6 +45,7 @@ class MFCCTest(test.TestCase):
signal = array_ops.zeros((2, 3, 5), dtype=dtypes.float64)
mfcc_ops.mfccs_from_log_mel_spectrograms(signal)
+ @test_util.run_deprecated_v1
def test_basic(self):
"""A basic test that the op runs on random input."""
with spectral_ops_test_util.fft_kernel_label_map():
@@ -50,6 +53,7 @@ class MFCCTest(test.TestCase):
signal = random_ops.random_normal((2, 3, 5))
mfcc_ops.mfccs_from_log_mel_spectrograms(signal).eval()
+ @test_util.run_deprecated_v1
def test_unknown_shape(self):
"""A test that the op runs when shape and rank are unknown."""
with spectral_ops_test_util.fft_kernel_label_map():
diff --git a/tensorflow/python/kernel_tests/signal/reconstruction_ops_test.py b/tensorflow/python/kernel_tests/signal/reconstruction_ops_test.py
index de3351e543c..d9b45f67c3b 100644
--- a/tensorflow/python/kernel_tests/signal/reconstruction_ops_test.py
+++ b/tensorflow/python/kernel_tests/signal/reconstruction_ops_test.py
@@ -22,6 +22,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradients_impl
from tensorflow.python.ops import math_ops
@@ -62,6 +63,7 @@ class ReconstructionOpsTest(test.TestCase):
self.assertAllClose(output, expected_output)
+ @test_util.run_deprecated_v1
def test_simple(self):
def make_input(frame_length, num_frames=3):
"""Generate a tensor of num_frames frames of frame_length."""
@@ -133,6 +135,7 @@ class ReconstructionOpsTest(test.TestCase):
self.assertEqual(output.shape, (1, 9))
self.assertEqual(string_output, self.expected_string)
+ @test_util.run_deprecated_v1
def test_gradient(self):
configurations = [
((1, 128), 1),
@@ -154,6 +157,7 @@ class ReconstructionOpsTest(test.TestCase):
gradient = sess.run(gradients_impl.gradients([loss], [signal])[0])
self.assertTrue((gradient == 1.0).all())
+ @test_util.run_deprecated_v1
def test_gradient_batch(self):
with self.session(use_gpu=True) as sess:
signal = array_ops.zeros((2, 10, 10))
@@ -176,6 +180,7 @@ class ReconstructionOpsTest(test.TestCase):
np.reshape(np.arange(100).astype(np.float32), (10, 10))])
self.assertAllEqual(expected_gradient, gradient)
+ @test_util.run_deprecated_v1
def test_gradient_numerical(self):
with self.session(use_gpu=True):
shape = (2, 10, 10)
diff --git a/tensorflow/python/kernel_tests/signal/shape_ops_test.py b/tensorflow/python/kernel_tests/signal/shape_ops_test.py
index 21a6b23b304..32ac76e80d0 100644
--- a/tensorflow/python/kernel_tests/signal/shape_ops_test.py
+++ b/tensorflow/python/kernel_tests/signal/shape_ops_test.py
@@ -23,6 +23,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util as tf_test_util
from tensorflow.python.kernel_tests.signal import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import math_ops
@@ -32,6 +33,7 @@ from tensorflow.python.platform import test
class FrameTest(test.TestCase):
+ @tf_test_util.run_deprecated_v1
def test_mapping_of_indices_without_padding(self):
with self.session(use_gpu=True):
tensor = constant_op.constant(np.arange(9152), dtypes.int32)
@@ -47,6 +49,7 @@ class FrameTest(test.TestCase):
self.assertAllEqual(expected, result)
+ @tf_test_util.run_deprecated_v1
def test_mapping_of_indices_with_padding(self):
with self.session(use_gpu=True):
tensor = constant_op.constant(np.arange(10000), dtypes.int32)
@@ -64,6 +67,7 @@ class FrameTest(test.TestCase):
self.assertAllEqual(expected, result)
+ @tf_test_util.run_deprecated_v1
def test_invalid_inputs(self):
# Rank 0 input signal.
with self.assertRaises(ValueError):
@@ -84,6 +88,7 @@ class FrameTest(test.TestCase):
with self.assertRaises(ValueError):
shape_ops.frame([1], 1, 1, pad_end=True, pad_value=[1])
+ @tf_test_util.run_deprecated_v1
def test_length_zero(self):
signal = constant_op.constant([], dtype=dtypes.float32)
frame_length = 2
@@ -98,6 +103,7 @@ class FrameTest(test.TestCase):
pad_end=False).eval()
self.assertEqual((0, 2), result.shape)
+ @tf_test_util.run_deprecated_v1
def test_shape_inference(self):
signal = array_ops.placeholder(dtypes.int32, shape=[1, 1])
frame_length = 2
@@ -153,6 +159,7 @@ class FrameTest(test.TestCase):
result = self.evaluate(op)
self.assertEqual(op.shape.as_list(), list(result.shape))
+ @tf_test_util.run_deprecated_v1
def test_basic_mono(self):
signal = np.arange(6)
frame_length = 3
@@ -178,6 +185,7 @@ class FrameTest(test.TestCase):
pad_end=False).eval()
self.assertAllEqual(expected, result)
+ @tf_test_util.run_deprecated_v1
def test_basic_stereo(self):
signal = np.vstack([np.arange(6),
np.arange(6) + 10])
@@ -207,6 +215,7 @@ class FrameTest(test.TestCase):
pad_end=False).eval()
self.assertAllEqual(expected, result)
+ @tf_test_util.run_deprecated_v1
def test_complex_shape(self):
signal = np.vstack([np.arange(6),
np.arange(6) + 10,
@@ -274,6 +283,7 @@ class FrameTest(test.TestCase):
[[14, 15], [0, 0], [0, 0]]]]
self.assertAllEqual(expected, self.evaluate(result))
+ @tf_test_util.run_deprecated_v1
def test_window_larger_than_signal(self):
signal = constant_op.constant([[1, 2], [11, 12]], dtype=dtypes.float32)
frame_length = 4
@@ -307,6 +317,7 @@ class FrameTest(test.TestCase):
result = shape_ops.frame(signal, frame_length, frame_step)
self.assertEqual(result.dtype, signal.dtype)
+ @tf_test_util.run_deprecated_v1
def test_dynamic_tensor(self):
# Show that frame works even when the dimensions of its input are
# not known at graph creation time.
@@ -325,6 +336,7 @@ class FrameTest(test.TestCase):
[[10, 11], [12, 13]],
[[20, 21], [22, 23]]], result)
+ @tf_test_util.run_deprecated_v1
def test_gradient_numerical(self):
with self.session(use_gpu=True):
signal_shape = (2, 128)
diff --git a/tensorflow/python/kernel_tests/signal/window_ops_test.py b/tensorflow/python/kernel_tests/signal/window_ops_test.py
index 2f19134f5a8..a72cdb288bb 100644
--- a/tensorflow/python/kernel_tests/signal/window_ops_test.py
+++ b/tensorflow/python/kernel_tests/signal/window_ops_test.py
@@ -24,6 +24,7 @@ import numpy as np
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util as tf_test_util
from tensorflow.python.kernel_tests.signal import test_util
from tensorflow.python.ops.signal import window_ops
from tensorflow.python.platform import test
@@ -75,6 +76,7 @@ class WindowOpsTest(test.TestCase):
dtype=tf_dtype).eval()
self.assertAllClose(expected, actual, tol, tol)
+ @tf_test_util.run_deprecated_v1
def test_hann_window(self):
"""Check that hann_window matches scipy.signal.hann behavior."""
# The Hann window is a raised cosine window with parameters alpha=0.5 and
@@ -84,6 +86,7 @@ class WindowOpsTest(test.TestCase):
functools.partial(_scipy_raised_cosine, a=0.5, b=0.5),
window_ops.hann_window)
+ @tf_test_util.run_deprecated_v1
def test_hamming_window(self):
"""Check that hamming_window matches scipy.signal.hamming's behavior."""
# The Hamming window is a raised cosine window with parameters alpha=0.54
diff --git a/tensorflow/python/kernel_tests/slice_op_test.py b/tensorflow/python/kernel_tests/slice_op_test.py
index ee48c6eb0ed..8f7245214a2 100644
--- a/tensorflow/python/kernel_tests/slice_op_test.py
+++ b/tensorflow/python/kernel_tests/slice_op_test.py
@@ -24,6 +24,7 @@ from six.moves import xrange # pylint: disable=redefined-builtin
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors_impl
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradients_impl
from tensorflow.python.ops import math_ops
@@ -145,6 +146,7 @@ class SliceTest(test.TestCase):
slice_val = self.evaluate(slice_t)
self.assertAllEqual(slice_val, inp[lo:hi])
+ @test_util.run_deprecated_v1
def testScalarInput(self):
input_val = 0
with self.cached_session() as sess:
@@ -159,6 +161,7 @@ class SliceTest(test.TestCase):
"out of range"):
sess.run([slice_t], feed_dict={input_t: input_val})
+ @test_util.run_deprecated_v1
def testInvalidIndex(self):
input_val = [1, 2]
with self.cached_session() as sess:
@@ -179,6 +182,7 @@ class SliceTest(test.TestCase):
np_ans = x[begin:begin + size, :]
self.assertAllEqual(tf_ans, np_ans)
+ @test_util.run_deprecated_v1
def testSliceMatrixDim0(self):
x = np.random.rand(8, 4).astype("f")
self._testSliceMatrixDim0(x, 1, 2)
@@ -213,6 +217,7 @@ class SliceTest(test.TestCase):
self.assertEqual(slice_val.shape, slice_t.get_shape())
self.assertEqual(slice2_val.shape, slice2_t.get_shape())
+ @test_util.run_deprecated_v1
def testComplex(self):
with self.session(use_gpu=True):
inp = np.random.rand(4, 10, 10, 4).astype("f")
@@ -316,6 +321,7 @@ class SliceTest(test.TestCase):
g1_val, g2_val = self.evaluate([g1, g2])
self.assertAllEqual(g1_val, g2_val)
+ @test_util.run_deprecated_v1
def testGradientsAll(self):
# Slice the middle square out of a 4x4 input
self._testGradientSlice([4, 4], [1, 1], [2, 2])
@@ -335,6 +341,7 @@ class SliceTest(test.TestCase):
# Use -1 as a slice dimension on a 2D tensor.
self._testGradientVariableSize2D()
+ @test_util.run_deprecated_v1
def testNotIterable(self):
# NOTE(mrry): If we register __getitem__ as an overloaded
# operator, Python will valiantly attempt to iterate over the
@@ -346,6 +353,7 @@ class SliceTest(test.TestCase):
for _ in c:
pass
+ @test_util.run_deprecated_v1
def testComputedShape(self):
# NOTE(mrry): We cannot currently handle partially-known values,
# because `tf.slice()` uses -1 to specify a wildcard size, and
diff --git a/tensorflow/python/kernel_tests/softmax_op_test.py b/tensorflow/python/kernel_tests/softmax_op_test.py
index 8b1a2e4c4e3..707b8a429f2 100644
--- a/tensorflow/python/kernel_tests/softmax_op_test.py
+++ b/tensorflow/python/kernel_tests/softmax_op_test.py
@@ -24,6 +24,7 @@ import numpy as np
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors_impl
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import nn_ops
from tensorflow.python.platform import test
@@ -206,6 +207,7 @@ class SoftmaxTest(test.TestCase):
[[5., 4., 3., 2.], [1., 2., 3., 4.]]])
self.assertEqual([3, 2, 4], op.get_shape())
+ @test_util.run_deprecated_v1
def testEmptyInput(self):
with self.cached_session():
x = array_ops.placeholder(dtypes.float32, shape=[0, 3])
@@ -229,6 +231,7 @@ class SoftmaxTest(test.TestCase):
with self.assertRaises(errors_impl.InvalidArgumentError):
nn_ops.softmax(ones, axis=2).eval()
+ @test_util.run_deprecated_v1
def testLargeDims(self):
# Make sure that we properly handle large inputs. See
# https://github.com/tensorflow/tensorflow/issues/4425 for details
diff --git a/tensorflow/python/kernel_tests/softplus_op_test.py b/tensorflow/python/kernel_tests/softplus_op_test.py
index 48445a73808..5273dd7ffc7 100644
--- a/tensorflow/python/kernel_tests/softplus_op_test.py
+++ b/tensorflow/python/kernel_tests/softplus_op_test.py
@@ -21,6 +21,7 @@ from __future__ import print_function
import numpy as np
from tensorflow.python.framework import constant_op
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import gradients_impl
from tensorflow.python.ops import nn_ops
@@ -70,6 +71,7 @@ class SoftplusTest(test.TestCase):
],
use_gpu=True)
+ @test_util.run_deprecated_v1
def testGradient(self):
with self.cached_session():
x = constant_op.constant(
@@ -86,6 +88,7 @@ class SoftplusTest(test.TestCase):
print("softplus (float) gradient err = ", err)
self.assertLess(err, 1e-4)
+ @test_util.run_deprecated_v1
def testGradGrad(self):
with self.cached_session():
x = constant_op.constant(
@@ -103,6 +106,7 @@ class SoftplusTest(test.TestCase):
print("softplus (float) gradient of gradient err = ", err)
self.assertLess(err, 5e-5)
+ @test_util.run_deprecated_v1
def testGradGradGrad(self):
with self.cached_session():
x = constant_op.constant(
@@ -121,6 +125,7 @@ class SoftplusTest(test.TestCase):
print("softplus (float) third-order gradient err = ", err)
self.assertLess(err, 5e-5)
+ @test_util.run_deprecated_v1
def testNoInts(self):
with self.cached_session():
with self.assertRaisesRegexp(
diff --git a/tensorflow/python/kernel_tests/softsign_op_test.py b/tensorflow/python/kernel_tests/softsign_op_test.py
index 71aac7e48e1..5554240c826 100644
--- a/tensorflow/python/kernel_tests/softsign_op_test.py
+++ b/tensorflow/python/kernel_tests/softsign_op_test.py
@@ -21,6 +21,7 @@ from __future__ import print_function
import numpy as np
from tensorflow.python.framework import constant_op
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import nn_ops
import tensorflow.python.ops.nn_grad # pylint: disable=unused-import
@@ -49,6 +50,7 @@ class SoftsignTest(test.TestCase):
np.array([[-9, 7, -5, 3, -1], [1, -3, 5, -7, 9]]).astype(t),
use_gpu=True)
+ @test_util.run_deprecated_v1
def testGradient(self):
with self.cached_session():
x = constant_op.constant(
@@ -65,6 +67,7 @@ class SoftsignTest(test.TestCase):
print("softsign (float) gradient err = ", err)
self.assertLess(err, 1e-4)
+ @test_util.run_deprecated_v1
def testNoInts(self):
with self.cached_session():
with self.assertRaisesRegexp(
diff --git a/tensorflow/python/kernel_tests/spacetobatch_op_test.py b/tensorflow/python/kernel_tests/spacetobatch_op_test.py
index 21134adf2ca..8641156604c 100644
--- a/tensorflow/python/kernel_tests/spacetobatch_op_test.py
+++ b/tensorflow/python/kernel_tests/spacetobatch_op_test.py
@@ -23,6 +23,7 @@ import numpy as np
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
from tensorflow.python.framework import tensor_util
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gen_array_ops
from tensorflow.python.ops import gradient_checker
@@ -115,6 +116,7 @@ class SpaceToBatchTest(test.TestCase, PythonOpImpl):
self._testPad(inputs, paddings, block_size, outputs)
# [1, 2, 2, 1] <-> [4, 1, 1, 1]
+ @test_util.run_deprecated_v1
def testSmallInput2x2(self):
x_np = [[[[1], [2]], [[3], [4]]]]
block_size = 2
@@ -122,6 +124,7 @@ class SpaceToBatchTest(test.TestCase, PythonOpImpl):
self._testOne(x_np, block_size, x_out)
# [1, 2, 2, 1] <-> [1, 3, 3, 1] (padding) <-> [9, 1, 1, 1]
+ @test_util.run_deprecated_v1
def testSmallInput2x2Pad1x0(self):
x_np = [[[[1], [2]], [[3], [4]]]]
paddings = np.array([[1, 0], [1, 0]], dtype=np.int32)
@@ -132,6 +135,7 @@ class SpaceToBatchTest(test.TestCase, PythonOpImpl):
# Test with depth larger than 1.
# [1, 2, 2, 3] <-> [4, 1, 1, 3]
+ @test_util.run_deprecated_v1
def testDepthInput2x2(self):
x_np = [[[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]]]
block_size = 2
@@ -140,6 +144,7 @@ class SpaceToBatchTest(test.TestCase, PythonOpImpl):
# Test for larger input dimensions.
# [1, 4, 4, 1] <-> [4, 2, 2, 1]
+ @test_util.run_deprecated_v1
def testLargerInput2x2(self):
x_np = [[[[1], [2], [3], [4]], [[5], [6], [7], [8]],
[[9], [10], [11], [12]], [[13], [14], [15], [16]]]]
@@ -150,6 +155,7 @@ class SpaceToBatchTest(test.TestCase, PythonOpImpl):
# Test with batch larger than 1.
# [2, 2, 4, 1] <-> [8, 1, 2, 1]
+ @test_util.run_deprecated_v1
def testBatchInput2x2(self):
x_np = [[[[1], [2], [3], [4]], [[5], [6], [7], [8]]],
[[[9], [10], [11], [12]], [[13], [14], [15], [16]]]]
@@ -162,6 +168,7 @@ class SpaceToBatchTest(test.TestCase, PythonOpImpl):
# that elements are correctly laid out spatially and properly interleaved
# along the batch dimension.
# [2, 4, 4, 1] <-> [8, 2, 2, 1]
+ @test_util.run_deprecated_v1
def testLargerInputBatch2x2(self):
x_np = [[[[1], [2], [3], [4]], [[5], [6], [7], [8]],
[[9], [10], [11], [12]], [[13], [14], [15], [16]]],
@@ -206,6 +213,7 @@ class SpaceToBatchNDTest(test.TestCase):
self._testPad(inputs, block_shape, paddings,
space_to_batch_direct(inputs, block_shape, paddings))
+ @test_util.run_deprecated_v1
def testZeroBlockDimsZeroRemainingDims(self):
self._testPad(
inputs=[1, 2],
@@ -213,6 +221,7 @@ class SpaceToBatchNDTest(test.TestCase):
paddings=[],
outputs=[1, 2],)
+ @test_util.run_deprecated_v1
def testZeroBlockDimsOneRemainingDim(self):
self._testPad(
inputs=[[1, 2], [3, 4]],
@@ -227,6 +236,7 @@ class SpaceToBatchNDTest(test.TestCase):
paddings=[[0, 0]],
outputs=[[1, 2], [3, 4]])
+ @test_util.run_deprecated_v1
def testZeroBlockDimsTwoRemainingDims(self):
self._testPad(
inputs=[[[1, 2], [3, 4]], [[5, 6], [7, 8]]],
@@ -248,6 +258,7 @@ class SpaceToBatchNDTest(test.TestCase):
paddings=[[0, 0], [0, 0]],
outputs=[[[1, 2], [3, 4]], [[5, 6], [7, 8]]])
+ @test_util.run_deprecated_v1
def testOneBlockDimZeroRemainingDims(self):
self._testPad(
inputs=[[1, 2, 3], [4, 5, 6]],
@@ -255,6 +266,7 @@ class SpaceToBatchNDTest(test.TestCase):
paddings=[1, 0],
outputs=[[0, 2], [0, 5], [1, 3], [4, 6]])
+ @test_util.run_deprecated_v1
def testOneBlockDimOneRemainingDim(self):
self._testPad(
inputs=[[[1, 11], [2, 21], [3, 31]], [[4, 41], [5, 51], [6, 61]]],
@@ -263,6 +275,7 @@ class SpaceToBatchNDTest(test.TestCase):
outputs=[[[0, 0], [2, 21]], [[0, 0], [5, 51]], [[1, 11], [3, 31]],
[[4, 41], [6, 61]]])
+ @test_util.run_deprecated_v1
def testDirect(self):
# Test with zero-size remaining dimension.
self._testDirect(
@@ -300,6 +313,7 @@ class SpaceToBatchNDTest(test.TestCase):
class SpaceToBatchSpaceToDepth(test.TestCase, PythonOpImpl):
# Verifies that: space_to_batch(x) = transpose(space_to_depth(transpose(x)))
+ @test_util.run_deprecated_v1
def testSpaceToDepthTranspose(self):
x = np.arange(5 * 10 * 16 * 7, dtype=np.float32).reshape([5, 10, 16, 7])
block_size = 2
@@ -319,6 +333,7 @@ class SpaceToBatchSpaceToDepthCpp(SpaceToBatchSpaceToDepth, CppOpImpl):
class SpaceToBatchErrorHandlingTest(test.TestCase, PythonOpImpl):
+ @test_util.run_deprecated_v1
def testInputWrongDimMissingBatch(self):
# The input is missing the first dimension ("batch")
x_np = [[[1], [2]], [[3], [4]]]
@@ -327,6 +342,7 @@ class SpaceToBatchErrorHandlingTest(test.TestCase, PythonOpImpl):
with self.assertRaises(ValueError):
_ = self.space_to_batch(x_np, paddings, block_size)
+ @test_util.run_deprecated_v1
def testBlockSize0(self):
# The block size is 0.
x_np = [[[[1], [2]], [[3], [4]]]]
@@ -336,6 +352,7 @@ class SpaceToBatchErrorHandlingTest(test.TestCase, PythonOpImpl):
out_tf = self.space_to_batch(x_np, paddings, block_size)
out_tf.eval()
+ @test_util.run_deprecated_v1
def testBlockSizeOne(self):
# The block size is 1. The block size needs to be > 1.
x_np = [[[[1], [2]], [[3], [4]]]]
@@ -345,6 +362,7 @@ class SpaceToBatchErrorHandlingTest(test.TestCase, PythonOpImpl):
out_tf = self.space_to_batch(x_np, paddings, block_size)
out_tf.eval()
+ @test_util.run_deprecated_v1
def testBlockSizeLarger(self):
# The block size is too large for this input.
x_np = [[[[1], [2]], [[3], [4]]]]
@@ -354,6 +372,7 @@ class SpaceToBatchErrorHandlingTest(test.TestCase, PythonOpImpl):
out_tf = self.space_to_batch(x_np, paddings, block_size)
out_tf.eval()
+ @test_util.run_deprecated_v1
def testBlockSizeNotDivisibleWidth(self):
# The block size divides width but not height.
x_np = [[[[1], [2], [3]], [[3], [4], [7]]]]
@@ -362,6 +381,7 @@ class SpaceToBatchErrorHandlingTest(test.TestCase, PythonOpImpl):
with self.assertRaises(ValueError):
_ = self.space_to_batch(x_np, paddings, block_size)
+ @test_util.run_deprecated_v1
def testBlockSizeNotDivisibleHeight(self):
# The block size divides height but not width.
x_np = [[[[1], [2]], [[3], [4]], [[5], [6]]]]
@@ -370,6 +390,7 @@ class SpaceToBatchErrorHandlingTest(test.TestCase, PythonOpImpl):
with self.assertRaises(ValueError):
_ = self.space_to_batch(x_np, paddings, block_size)
+ @test_util.run_deprecated_v1
def testBlockSizeNotDivisibleBoth(self):
# The block size does not divide neither width or height.
x_np = [[[[1], [2]], [[3], [4]]]]
@@ -378,6 +399,7 @@ class SpaceToBatchErrorHandlingTest(test.TestCase, PythonOpImpl):
with self.assertRaises(ValueError):
_ = self.space_to_batch(x_np, paddings, block_size)
+ @test_util.run_deprecated_v1
def testUnknownShape(self):
t = self.space_to_batch(
array_ops.placeholder(dtypes.float32),
@@ -424,25 +446,31 @@ class SpaceToBatchNDErrorHandlingTest(test.TestCase):
self._testStaticShape(input_shape, block_shape, paddings, error)
self._testDynamicShape(input_shape, block_shape, paddings)
+ @test_util.run_deprecated_v1
def testBlockSize0(self):
# The block size is 0.
self._testShape([1, 2, 2], [0, 2], [[0, 0], [0, 0]], ValueError)
+ @test_util.run_deprecated_v1
def testBlockSizeNegative(self):
self._testShape([1, 2, 2], [-1, 2], [[0, 0], [0, 0]], ValueError)
+ @test_util.run_deprecated_v1
def testNegativePadding(self):
# The padding is negative.
self._testShape([1, 2, 2], [1, 1], [[0, -1], [0, 0]], ValueError)
+ @test_util.run_deprecated_v1
def testBlockSizeNotDivisible(self):
# The padded size is not divisible by the block size.
self._testShape([1, 2, 3, 1], [3, 3], [[0, 0], [0, 0]], ValueError)
+ @test_util.run_deprecated_v1
def testBlockDimsMismatch(self):
# Shape of block_shape does not match shape of paddings.
self._testStaticShape([1, 3, 3, 1], [3, 3], [[0, 0]], ValueError)
+ @test_util.run_deprecated_v1
def testUnknown(self):
# Verify that input shape and paddings shape can be unknown.
_ = array_ops.space_to_batch_nd(
@@ -522,18 +550,21 @@ class SpaceToBatchGradientTest(test.TestCase, PythonOpImpl):
# Don't use very large numbers as dimensions here as the result is tensor
# with cartesian product of the dimensions.
+ @test_util.run_deprecated_v1
def testSmall(self):
block_size = 2
pad_beg = 0
pad_end = 0
self._compare(1, 2, 3, 5, block_size, pad_beg, pad_end)
+ @test_util.run_deprecated_v1
def testSmall2(self):
block_size = 2
pad_beg = 0
pad_end = 0
self._compare(2, 4, 3, 2, block_size, pad_beg, pad_end)
+ @test_util.run_deprecated_v1
def testSmallPad1x1(self):
block_size = 2
pad_beg = 1
@@ -572,15 +603,19 @@ class SpaceToBatchNDGradientTest(test.TestCase):
# Don't use very large numbers as dimensions here as the result is tensor
# with cartesian product of the dimensions.
+ @test_util.run_deprecated_v1
def testSmall(self):
self._compare([1, 4, 6, 5], [2, 2], [[0, 0], [0, 0]])
+ @test_util.run_deprecated_v1
def testSmall2(self):
self._compare([2, 8, 6, 2], [2, 2], [[0, 0], [0, 0]])
+ @test_util.run_deprecated_v1
def testSmallPad1(self):
self._compare([2, 4, 6, 2], [2, 2], [[1, 1], [1, 1]])
+ @test_util.run_deprecated_v1
def testSmallPadThreeBlockDims(self):
self._compare([2, 2, 4, 3, 2], [2, 2, 2], [[1, 1], [1, 1], [1, 0]])
@@ -644,6 +679,7 @@ class RequiredSpaceToBatchPaddingsTest(test.TestCase):
self.assertAllEqual(paddings_result, paddings_const)
self.assertAllEqual(crops_result, crops_const)
+ @test_util.run_deprecated_v1
def testSimple(self):
self._test(
input_shape=np.zeros((0,), np.int32),
diff --git a/tensorflow/python/kernel_tests/spacetodepth_op_test.py b/tensorflow/python/kernel_tests/spacetodepth_op_test.py
index c9aaa68971a..e96bc09f365 100644
--- a/tensorflow/python/kernel_tests/spacetodepth_op_test.py
+++ b/tensorflow/python/kernel_tests/spacetodepth_op_test.py
@@ -159,6 +159,7 @@ class SpaceToDepthTest(test.TestCase):
# Error handling:
+ @test_util.run_deprecated_v1
def testInputWrongDimMissingDepth(self):
# The input is missing the last dimension ("depth")
x_np = [[[1, 2], [3, 4]]]
@@ -167,6 +168,7 @@ class SpaceToDepthTest(test.TestCase):
out_tf = array_ops.space_to_depth(x_np, block_size)
self.evaluate(out_tf)
+ @test_util.run_deprecated_v1
def testInputWrongDimMissingBatch(self):
# The input is missing the first dimension ("batch")
x_np = [[[1], [2]], [[3], [4]]]
@@ -174,6 +176,7 @@ class SpaceToDepthTest(test.TestCase):
with self.assertRaises(ValueError):
_ = array_ops.space_to_depth(x_np, block_size)
+ @test_util.run_deprecated_v1
def testBlockSize0(self):
# The block size is 0.
x_np = [[[[1], [2]], [[3], [4]]]]
@@ -182,6 +185,7 @@ class SpaceToDepthTest(test.TestCase):
out_tf = array_ops.space_to_depth(x_np, block_size)
self.evaluate(out_tf)
+ @test_util.run_deprecated_v1
def testBlockSizeOne(self):
# The block size is 1. The block size needs to be > 1.
x_np = [[[[1], [2]], [[3], [4]]]]
@@ -190,6 +194,7 @@ class SpaceToDepthTest(test.TestCase):
out_tf = array_ops.space_to_depth(x_np, block_size)
self.evaluate(out_tf)
+ @test_util.run_deprecated_v1
def testBlockSizeLarger(self):
# The block size is too large for this input.
x_np = [[[[1], [2]], [[3], [4]]]]
@@ -198,6 +203,7 @@ class SpaceToDepthTest(test.TestCase):
out_tf = array_ops.space_to_depth(x_np, block_size)
self.evaluate(out_tf)
+ @test_util.run_deprecated_v1
def testBlockSizeNotDivisibleWidth(self):
# The block size divides width but not height.
x_np = [[[[1], [2], [3]], [[3], [4], [7]]]]
@@ -205,6 +211,7 @@ class SpaceToDepthTest(test.TestCase):
with self.assertRaises(ValueError):
_ = array_ops.space_to_depth(x_np, block_size)
+ @test_util.run_deprecated_v1
def testBlockSizeNotDivisibleHeight(self):
# The block size divides height but not width.
x_np = [[[[1], [2]], [[3], [4]], [[5], [6]]]]
@@ -212,6 +219,7 @@ class SpaceToDepthTest(test.TestCase):
with self.assertRaises(ValueError):
_ = array_ops.space_to_depth(x_np, block_size)
+ @test_util.run_deprecated_v1
def testBlockSizeNotDivisibleBoth(self):
# The block size does not divide neither width or height.
x_np = [[[[1], [2]], [[3], [4]]]]
@@ -219,6 +227,7 @@ class SpaceToDepthTest(test.TestCase):
with self.assertRaises(ValueError):
_ = array_ops.space_to_depth(x_np, block_size)
+ @test_util.run_deprecated_v1
def testUnknownShape(self):
t = array_ops.space_to_depth(
array_ops.placeholder(dtypes.float32), block_size=4)
@@ -334,11 +343,13 @@ class SpaceToDepthGradientTest(test.TestCase):
# Don't use very large numbers as dimensions here as the result is tensor
# with cartesian product of the dimensions.
+ @test_util.run_deprecated_v1
def testSmall(self):
block_size = 2
self._compare(1, 2, 3, 5, block_size, "NHWC")
self._compare(1, 2, 3, 5, block_size, "NCHW")
+ @test_util.run_deprecated_v1
def testSmall2(self):
block_size = 2
self._compare(2, 4, 3, 2, block_size, "NHWC")
diff --git a/tensorflow/python/kernel_tests/sparse_add_op_test.py b/tensorflow/python/kernel_tests/sparse_add_op_test.py
index c61f8633558..00eff54077c 100644
--- a/tensorflow/python/kernel_tests/sparse_add_op_test.py
+++ b/tensorflow/python/kernel_tests/sparse_add_op_test.py
@@ -140,6 +140,7 @@ class SparseAddTest(test.TestCase):
self.assertAllClose(sum_out.values, [2, 6, -.2])
self.assertAllEqual(sum_out.dense_shape, [3, 3])
+ @test_util.run_deprecated_v1
def testGradients(self):
np.random.seed(1618) # Make it reproducible.
with self.session(use_gpu=False):
@@ -176,6 +177,7 @@ class SparseAddTest(test.TestCase):
self.assertAllEqual(dense_np + rand_vals_np, s)
self.assertTrue(s.dtype == dtype)
+ @test_util.run_deprecated_v1
def testSparseTensorDenseAddGradients(self):
np.random.seed(1618) # Make it reproducible.
n, m = np.random.randint(30, size=2)
@@ -191,6 +193,7 @@ class SparseAddTest(test.TestCase):
[(nnz,), (n, m)], s, (n, m))
self.assertLess(err, 1e-3)
+ @test_util.run_deprecated_v1
def testInvalidSparseTensor(self):
with test_util.force_cpu():
shape = [2, 2]
diff --git a/tensorflow/python/kernel_tests/sparse_concat_op_test.py b/tensorflow/python/kernel_tests/sparse_concat_op_test.py
index 368a533e569..04b6b9b8d20 100644
--- a/tensorflow/python/kernel_tests/sparse_concat_op_test.py
+++ b/tensorflow/python/kernel_tests/sparse_concat_op_test.py
@@ -23,6 +23,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import sparse_tensor
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import sparse_ops
from tensorflow.python.platform import test
@@ -253,6 +254,7 @@ class SparseConcatTest(test.TestCase):
[b"a", b"b", b"e", b"c", b"d", b"f", b"g", b"h"])
self.assertAllEqual(concat_out.dense_shape, [3, 8])
+ @test_util.run_deprecated_v1
def testMismatchedRank(self):
with self.session(use_gpu=False):
sp_a = self._SparseTensor_3x3()
@@ -263,6 +265,7 @@ class SparseConcatTest(test.TestCase):
with self.assertRaises(ValueError):
sparse_ops.sparse_concat(concat_dim, [sp_a, sp_e])
+ @test_util.run_deprecated_v1
def testMismatchedRankExpandNonconcatDim(self):
with self.session(use_gpu=False):
sp_a = self._SparseTensor_3x3()
@@ -275,6 +278,7 @@ class SparseConcatTest(test.TestCase):
sparse_ops.sparse_concat(
concat_dim, [sp_a, sp_e], expand_nonconcat_dim=True)
+ @test_util.run_deprecated_v1
def testMismatchedShapes(self):
with self.session(use_gpu=False) as sess:
sp_a = self._SparseTensor_3x3()
@@ -321,6 +325,7 @@ class SparseConcatTest(test.TestCase):
[1, 1, 2, 1, 1, 1, 2, 3, 4, 2, 1, 0, 2])
self.assertAllEqual(sp_concat_dim1_out.dense_shape, [3, 13])
+ @test_util.run_deprecated_v1
def testShapeInferenceUnknownShapes(self):
with self.session(use_gpu=False):
sp_inputs = [
diff --git a/tensorflow/python/kernel_tests/sparse_conditional_accumulator_test.py b/tensorflow/python/kernel_tests/sparse_conditional_accumulator_test.py
index 66589fa315d..275c86e5349 100644
--- a/tensorflow/python/kernel_tests/sparse_conditional_accumulator_test.py
+++ b/tensorflow/python/kernel_tests/sparse_conditional_accumulator_test.py
@@ -26,6 +26,7 @@ from tensorflow.python.framework import dtypes as dtypes_lib
from tensorflow.python.framework import errors_impl
from tensorflow.python.framework import ops
from tensorflow.python.framework import tensor_shape
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import data_flow_ops
from tensorflow.python.platform import test
@@ -98,12 +99,14 @@ class IndexedSlicesConditionalAccumulatorTest(test.TestCase):
attr { key: 'reduction_type' value {s: 'MEAN'} }
""", q.accumulator_ref.op.node_def)
+ @test_util.run_deprecated_v1
def testAccumulatorSizeEmpty(self):
with self.cached_session():
q = data_flow_ops.SparseConditionalAccumulator(
dtypes_lib.float32, name="Q")
self.assertEqual(q.num_accumulated().eval(), 0)
+ @test_util.run_deprecated_v1
def testAccumulatorSetGlobalStep(self):
with self.cached_session():
q = data_flow_ops.SparseConditionalAccumulator(
@@ -111,6 +114,7 @@ class IndexedSlicesConditionalAccumulatorTest(test.TestCase):
set_global_step_op = q.set_global_step(1)
set_global_step_op.run()
+ @test_util.run_deprecated_v1
def testAccumulatorApplyGradFloat32(self):
with self.cached_session():
q = data_flow_ops.SparseConditionalAccumulator(
@@ -122,6 +126,7 @@ class IndexedSlicesConditionalAccumulatorTest(test.TestCase):
accum_op.run()
self.assertEqual(q.num_accumulated().eval(), 1)
+ @test_util.run_deprecated_v1
def testDtypes(self):
with self.cached_session() as sess:
dtypes = [dtypes_lib.float16, dtypes_lib.float32, dtypes_lib.float64]
@@ -144,6 +149,7 @@ class IndexedSlicesConditionalAccumulatorTest(test.TestCase):
self._assertEqual_nparray(sum_elems / len(elems), result, sess)
+ @test_util.run_deprecated_v1
def testAccumulatorMultipleAccumulators(self):
with self.cached_session() as sess:
q_f32_0 = data_flow_ops.SparseConditionalAccumulator(
@@ -174,6 +180,7 @@ class IndexedSlicesConditionalAccumulatorTest(test.TestCase):
result = sess.run(accums[i].take_indexed_slices_grad(1))
self._assertEqual_indexedslices(expected_tensors[i], result)
+ @test_util.run_deprecated_v1
def testAccumulatorTakeGradMean(self):
with self.cached_session() as sess:
q = data_flow_ops.SparseConditionalAccumulator(
@@ -194,6 +201,7 @@ class IndexedSlicesConditionalAccumulatorTest(test.TestCase):
self.assertAllEqual([[0.5, 0.5], [0, 2], [3, 0]], val.values)
self.assertAllEqual([-1, 2], val.dense_shape)
+ @test_util.run_deprecated_v1
def testAccumulatorTakeGradSum(self):
with self.cached_session() as sess:
q = data_flow_ops.SparseConditionalAccumulator(
@@ -214,11 +222,13 @@ class IndexedSlicesConditionalAccumulatorTest(test.TestCase):
self.assertAllEqual([[1, 1], [0, 2], [3, 0]], val.values)
self.assertAllEqual([-1, 2], val.dense_shape)
+ @test_util.run_deprecated_v1
def testAccumulatorTakeGradInvalidReductionType(self):
with self.assertRaises(ValueError):
data_flow_ops.SparseConditionalAccumulator(
dtypes_lib.float32, name="Q", shape=(), reduction_type="Invalid")
+ @test_util.run_deprecated_v1
def testAccumulatorRepeatedTakeGrad(self):
with self.cached_session() as sess:
q = data_flow_ops.SparseConditionalAccumulator(
@@ -257,6 +267,7 @@ class IndexedSlicesConditionalAccumulatorTest(test.TestCase):
self.assertAllEqual(val.values, [[5, 5], [0, 20], [30, 0]])
self.assertAllEqual(val.dense_shape, [-1, 2])
+ @test_util.run_deprecated_v1
def testParallelApplyGradMean(self):
with self.cached_session() as sess:
q = data_flow_ops.SparseConditionalAccumulator(
@@ -288,6 +299,7 @@ class IndexedSlicesConditionalAccumulatorTest(test.TestCase):
np.array([[expected_val, 0], [0, expected_val]]).astype(np.float32),
val, sess)
+ @test_util.run_deprecated_v1
def testParallelApplyGradSum(self):
with self.cached_session() as sess:
q = data_flow_ops.SparseConditionalAccumulator(
@@ -322,6 +334,7 @@ class IndexedSlicesConditionalAccumulatorTest(test.TestCase):
np.array([[expected_val, 0], [0, expected_val]]).astype(np.float32),
val, sess)
+ @test_util.run_deprecated_v1
def testParallelTakeGrad(self):
with self.cached_session() as sess:
q = data_flow_ops.SparseConditionalAccumulator(
@@ -361,6 +374,7 @@ class IndexedSlicesConditionalAccumulatorTest(test.TestCase):
self._assertEqual_nparray(
np.array([[0, 0], [elems[i], 0]]), results[i], sess)
+ @test_util.run_deprecated_v1
def testAccumulatorApplyAndBlockingTake(self):
with self.cached_session() as sess:
q = data_flow_ops.SparseConditionalAccumulator(
@@ -396,6 +410,7 @@ class IndexedSlicesConditionalAccumulatorTest(test.TestCase):
with self.assertRaisesOpError("was cancelled"):
self.evaluate(takeg_op)
+ @test_util.run_deprecated_v1
def testAccumulatorCancel(self):
with self.cached_session() as sess:
q = data_flow_ops.SparseConditionalAccumulator(
@@ -415,6 +430,7 @@ class IndexedSlicesConditionalAccumulatorTest(test.TestCase):
takeg_thread.join()
+ @test_util.run_deprecated_v1
def testNonVectorIndices(self):
with self.cached_session():
q = data_flow_ops.SparseConditionalAccumulator(
@@ -427,6 +443,7 @@ class IndexedSlicesConditionalAccumulatorTest(test.TestCase):
grad_indices=[[0, 1], [1, 0]],
grad_values=np.array([1, 2]).astype(np.float32)).run()
+ @test_util.run_deprecated_v1
def testZeroDimensionValues(self):
with self.cached_session():
q = data_flow_ops.SparseConditionalAccumulator(
@@ -437,6 +454,7 @@ class IndexedSlicesConditionalAccumulatorTest(test.TestCase):
q.apply_grad(
grad_indices=[0], grad_values=np.array(1).astype(np.float32)).run()
+ @test_util.run_deprecated_v1
def testWrongNonEmptyInputValues(self):
with self.cached_session():
q = data_flow_ops.SparseConditionalAccumulator(
@@ -448,6 +466,7 @@ class IndexedSlicesConditionalAccumulatorTest(test.TestCase):
grad_indices=[0, 1],
grad_values=np.array([[0, 1, 1]]).astype(np.float32)).run()
+ @test_util.run_deprecated_v1
def testDynamicNonVectorIndices(self):
with self.cached_session() as sess:
q = data_flow_ops.SparseConditionalAccumulator(
@@ -467,6 +486,7 @@ class IndexedSlicesConditionalAccumulatorTest(test.TestCase):
x_values: np.array([1, 2]).astype(np.float32)
})
+ @test_util.run_deprecated_v1
def testDynamicWrongNonEmptyInputValues(self):
with self.cached_session() as sess:
q = data_flow_ops.SparseConditionalAccumulator(
@@ -485,6 +505,7 @@ class IndexedSlicesConditionalAccumulatorTest(test.TestCase):
x_values: np.array([[0, 1, 1]]).astype(np.float32)
})
+ @test_util.run_deprecated_v1
def testEmptyShapeApply(self):
with self.cached_session():
q = data_flow_ops.SparseConditionalAccumulator(
@@ -510,6 +531,7 @@ class IndexedSlicesConditionalAccumulatorTest(test.TestCase):
q.apply_grad(grad_indices=[0], grad_values=[1.0], grad_shape=[]).run()
q.apply_grad(grad_indices=[0], grad_values=[1.0]).run()
+ @test_util.run_deprecated_v1
def testValidateShape(self):
with self.cached_session() as sess:
q = data_flow_ops.SparseConditionalAccumulator(
@@ -605,6 +627,7 @@ class IndexedSlicesConditionalAccumulatorTest(test.TestCase):
[[[[1, 2], [3, 4]], [[5, 6], [7, 8]]]]).astype(np.float32),
local_step=1).run()
+ @test_util.run_deprecated_v1
def testReturnShape(self):
with self.cached_session() as sess:
q = data_flow_ops.SparseConditionalAccumulator(
@@ -630,6 +653,7 @@ class IndexedSlicesConditionalAccumulatorTest(test.TestCase):
val = self.evaluate(q.take_indexed_slices_grad(1))
self.assertAllEqual(val.dense_shape, [-1, 2, 2, 3])
+ @test_util.run_deprecated_v1
def testApplyGradtInt32IndicesAndShape(self):
with self.cached_session() as sess:
q = data_flow_ops.SparseConditionalAccumulator(
diff --git a/tensorflow/python/kernel_tests/sparse_cross_op_test.py b/tensorflow/python/kernel_tests/sparse_cross_op_test.py
index 8451b96c564..566bbb56f00 100644
--- a/tensorflow/python/kernel_tests/sparse_cross_op_test.py
+++ b/tensorflow/python/kernel_tests/sparse_cross_op_test.py
@@ -24,12 +24,14 @@ from tensorflow.python.client import session
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import sparse_tensor
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import sparse_ops
from tensorflow.python.platform import test
class SparseCrossOpTest(test.TestCase):
+ @test_util.run_deprecated_v1
def test_simple(self):
"""Tests a simple scenario."""
op = sparse_ops.sparse_cross([
@@ -45,6 +47,7 @@ class SparseCrossOpTest(test.TestCase):
with self.cached_session() as sess:
self._assert_sparse_tensor_equals(expected_out, self.evaluate(op))
+ @test_util.run_deprecated_v1
def test_dense(self):
"""Tests only dense inputs."""
op = sparse_ops.sparse_cross([
@@ -65,6 +68,7 @@ class SparseCrossOpTest(test.TestCase):
with self.cached_session() as sess:
self._assert_sparse_tensor_equals(expected_out, self.evaluate(op))
+ @test_util.run_deprecated_v1
def test_integer_mixed_string_sparse(self):
"""Tests mixed type."""
op = sparse_ops.sparse_cross([
@@ -79,6 +83,7 @@ class SparseCrossOpTest(test.TestCase):
with self.cached_session() as sess:
self._assert_sparse_tensor_equals(expected_out, self.evaluate(op))
+ @test_util.run_deprecated_v1
def test_integer_mixed_string_dense(self):
"""Tests mixed dense inputs."""
op = sparse_ops.sparse_cross([
@@ -97,6 +102,7 @@ class SparseCrossOpTest(test.TestCase):
with self.cached_session() as sess:
self._assert_sparse_tensor_equals(expected_out, self.evaluate(op))
+ @test_util.run_deprecated_v1
def test_sparse_cross_dense(self):
"""Tests sparse and dense inputs."""
op = sparse_ops.sparse_cross([
@@ -114,6 +120,7 @@ class SparseCrossOpTest(test.TestCase):
with self.cached_session() as sess:
self._assert_sparse_tensor_equals(expected_out, self.evaluate(op))
+ @test_util.run_deprecated_v1
def test_integer_sparse_input(self):
"""Tests mixed type sparse and dense inputs."""
op = sparse_ops.sparse_cross([
@@ -130,6 +137,7 @@ class SparseCrossOpTest(test.TestCase):
with self.cached_session() as sess:
self._assert_sparse_tensor_equals(expected_out, self.evaluate(op))
+ @test_util.run_deprecated_v1
def test_permutation_3x3x3(self):
"""Tests 3x3x3 permutation."""
op = sparse_ops.sparse_cross([
@@ -172,6 +180,7 @@ class SparseCrossOpTest(test.TestCase):
with self.cached_session() as sess:
self._assert_sparse_tensor_equals(expected_out, self.evaluate(op))
+ @test_util.run_deprecated_v1
def test_permutation_3x1x2(self):
"""Tests 3x1x2 permutation."""
op = sparse_ops.sparse_cross([
@@ -191,6 +200,7 @@ class SparseCrossOpTest(test.TestCase):
with self.cached_session() as sess:
self._assert_sparse_tensor_equals(expected_out, self.evaluate(op))
+ @test_util.run_deprecated_v1
def test_large_batch(self):
"""Tests with large batch size to force multithreading."""
batch_size = 5000
@@ -224,6 +234,7 @@ class SparseCrossOpTest(test.TestCase):
with self.cached_session() as sess:
self._assert_sparse_tensor_equals(expected_out, self.evaluate(op))
+ @test_util.run_deprecated_v1
def test_one_column_empty(self):
"""Tests when one column is empty.
@@ -237,6 +248,7 @@ class SparseCrossOpTest(test.TestCase):
with self.cached_session() as sess:
self._assert_sparse_tensor_empty(self.evaluate(op))
+ @test_util.run_deprecated_v1
def test_some_columns_empty(self):
"""Tests when more than one columns are empty.
@@ -256,6 +268,7 @@ class SparseCrossOpTest(test.TestCase):
with self.cached_session() as sess:
self._assert_sparse_tensor_equals(expected_out, self.evaluate(op))
+ @test_util.run_deprecated_v1
def test_all_columns_empty(self):
"""Tests when all columns are empty.
@@ -269,6 +282,7 @@ class SparseCrossOpTest(test.TestCase):
with self.cached_session() as sess:
self._assert_sparse_tensor_empty(self.evaluate(op))
+ @test_util.run_deprecated_v1
def test_hashed_zero_bucket_no_hash_key(self):
op = sparse_ops.sparse_cross_hashed([
self._sparse_tensor([['batch1-FC1-F1']]),
@@ -280,6 +294,7 @@ class SparseCrossOpTest(test.TestCase):
with self.cached_session() as sess:
self._assert_sparse_tensor_equals(expected_out, self.evaluate(op))
+ @test_util.run_deprecated_v1
def test_hashed_zero_bucket(self):
op = sparse_ops.sparse_cross_hashed(
[
@@ -294,6 +309,7 @@ class SparseCrossOpTest(test.TestCase):
self._assert_sparse_tensor_equals(expected_out, self.evaluate(op))
# TODO(sibyl-Aix6ihai): Add benchmark to compare Hashed vs Non-hashed.
+ @test_util.run_deprecated_v1
def test_hashed_no_hash_key(self):
op = sparse_ops.sparse_cross_hashed(
[
@@ -307,6 +323,7 @@ class SparseCrossOpTest(test.TestCase):
with self.cached_session() as sess:
self._assert_sparse_tensor_equals(expected_out, self.evaluate(op))
+ @test_util.run_deprecated_v1
def test_hashed_output(self):
op = sparse_ops.sparse_cross_hashed(
[
@@ -321,6 +338,7 @@ class SparseCrossOpTest(test.TestCase):
with self.cached_session() as sess:
self._assert_sparse_tensor_equals(expected_out, self.evaluate(op))
+ @test_util.run_deprecated_v1
def test_hashed__has_no_collision(self):
"""Tests that fingerprint concatenation has no collisions."""
# Although the last 10 bits of 359 and 1024+359 are identical.
diff --git a/tensorflow/python/kernel_tests/sparse_matmul_op_test.py b/tensorflow/python/kernel_tests/sparse_matmul_op_test.py
index 4de69a26e32..2e17a9c608f 100644
--- a/tensorflow/python/kernel_tests/sparse_matmul_op_test.py
+++ b/tensorflow/python/kernel_tests/sparse_matmul_op_test.py
@@ -22,6 +22,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import math_ops
from tensorflow.python.platform import test
@@ -71,6 +72,7 @@ class SparseMatMulTest(test.TestCase):
self.assertShapeEqual(np_ans, tf_ans)
self.assertAllCloseAccordingToType(np_ans, out, rtol=1e-4, atol=1e-4)
+ @test_util.run_deprecated_v1
def testBasic(self):
x = np.arange(0., 4.).reshape([4, 1]).astype(np.float32)
y = np.arange(-1., 1.).reshape([1, 2]).astype(np.float32)
@@ -78,6 +80,7 @@ class SparseMatMulTest(test.TestCase):
for y_dtype in (dtypes.float32, dtypes.bfloat16):
self._testCpuMatmul(x, y, x_dtype=x_dtype, y_dtype=y_dtype)
+ @test_util.run_deprecated_v1
def testZeroDim(self):
x = np.ones((4, 0)).astype(np.float32)
y = np.ones((0, 3)).astype(np.float32)
@@ -85,6 +88,7 @@ class SparseMatMulTest(test.TestCase):
for y_dtype in (dtypes.float32, dtypes.bfloat16):
self._testCpuMatmul(x, y, x_dtype=x_dtype, y_dtype=y_dtype)
+ @test_util.run_deprecated_v1
def testEmpty(self):
x = np.ones((0, 0)).astype(np.float32)
y = np.ones((0, 0)).astype(np.float32)
@@ -93,6 +97,7 @@ class SparseMatMulTest(test.TestCase):
self._testCpuMatmul(x, y, x_dtype=x_dtype, y_dtype=y_dtype)
# Tests setting one dimension to be a high value.
+ @test_util.run_deprecated_v1
def testLarge(self):
r1 = np.random.randint(6000, 20000)
r2 = np.random.randint(1, 10)
@@ -105,6 +110,7 @@ class SparseMatMulTest(test.TestCase):
self._testCpuMatmul(x, y, x_dtype=x_dtype, y_dtype=y_dtype)
# Tests random sized matrices.
+ @test_util.run_deprecated_v1
def testRandom(self):
for tr_a in [True, False]:
for tr_b in [True, False]:
@@ -159,6 +165,7 @@ class MatMulGradientTest(test.TestCase):
delta=delta))
self.assertLessEqual(err, delta / 2.)
+ @test_util.run_deprecated_v1
def testGradientInput(self):
for tr_a in [True, False]:
for tr_b in [True, False]:
diff --git a/tensorflow/python/kernel_tests/sparse_ops_test.py b/tensorflow/python/kernel_tests/sparse_ops_test.py
index 605aaf3dd12..75f65e62517 100644
--- a/tensorflow/python/kernel_tests/sparse_ops_test.py
+++ b/tensorflow/python/kernel_tests/sparse_ops_test.py
@@ -71,6 +71,7 @@ class SparseToIndicatorTest(test_util.TensorFlowTestCase):
constant_op.constant(val, dtype),
constant_op.constant(shape, dtypes.int64))
+ @test_util.run_deprecated_v1
def testInt32(self):
with self.session(use_gpu=False):
sp_input = self._SparseTensor_5x6(dtypes.int32)
@@ -83,6 +84,7 @@ class SparseToIndicatorTest(test_util.TensorFlowTestCase):
self.assertAllEqual(output, expected_output)
+ @test_util.run_deprecated_v1
def testInt64(self):
with self.session(use_gpu=False):
sp_input = self._SparseTensor_5x6(dtypes.int64)
@@ -95,6 +97,7 @@ class SparseToIndicatorTest(test_util.TensorFlowTestCase):
self.assertAllEqual(output, expected_output)
+ @test_util.run_deprecated_v1
def testHigherRank(self):
with self.session(use_gpu=False):
sp_input = self._SparseTensor_2x3x4(dtypes.int64)
@@ -296,6 +299,7 @@ class SparseRetainTest(test_util.TensorFlowTestCase):
def _SparseTensor_5x6(self):
return sparse_tensor.SparseTensor.from_value(self._SparseTensorValue_5x6())
+ @test_util.run_deprecated_v1
def testBasic(self):
with self.session(use_gpu=False) as sess:
for sp_input in (self._SparseTensorValue_5x6(), self._SparseTensor_5x6()):
@@ -353,12 +357,14 @@ class SparseResetShapeTest(test_util.TensorFlowTestCase):
return sparse_tensor.SparseTensorValue(self._IND_2_5_6, self._VAL_2_5_6,
self._SHP_2_5_6)
+ @test_util.run_deprecated_v1
def testStaticShapeInfoPreservedWhenNewShapeIsProvidedAndStatic(self):
sp_input = self._SparseTensor_2x5x6()
new_shape = np.array([3, 6, 7], dtype=np.int64)
sp_output = sparse_ops.sparse_reset_shape(sp_input, new_shape)
self.assertAllEqual([3, 6, 7], sp_output.get_shape())
+ @test_util.run_deprecated_v1
def testBasic(self):
with self.session(use_gpu=False) as sess:
sp_input = self._SparseTensor_2x5x6()
@@ -372,6 +378,7 @@ class SparseResetShapeTest(test_util.TensorFlowTestCase):
self.assertAllEqual(output.values, [0, 10, 13, 14, 32, 33])
self.assertAllEqual(output.dense_shape, [3, 6, 7])
+ @test_util.run_deprecated_v1
def testInputUnavailableInGraphConstructionOk(self):
with self.session(use_gpu=False) as sess:
sp_input = self._SparseTensorValue_2x5x6()
@@ -385,6 +392,7 @@ class SparseResetShapeTest(test_util.TensorFlowTestCase):
self.assertAllEqual(output.values, [0, 10, 13, 14, 32, 33])
self.assertAllEqual(output.dense_shape, [3, 6, 7])
+ @test_util.run_deprecated_v1
def testFeedInputUnavailableInGraphConstructionOk(self):
with self.session(use_gpu=False) as sess:
sp_input = array_ops.sparse_placeholder(dtype=dtypes.int32)
@@ -422,6 +430,7 @@ class SparseResetShapeTest(test_util.TensorFlowTestCase):
self.assertAllEqual(output.values.shape, [0])
self.assertAllEqual(output.dense_shape, [0, 0, 0])
+ @test_util.run_deprecated_v1
def testInvalidRank(self):
with self.session(use_gpu=False):
sp_input = self._SparseTensor_2x5x6()
@@ -430,6 +439,7 @@ class SparseResetShapeTest(test_util.TensorFlowTestCase):
with self.assertRaises(ValueError):
sparse_ops.sparse_reset_shape(sp_input, new_shape)
+ @test_util.run_deprecated_v1
def testInvalidRankNewShapeUnavailableInGraphConstruction(self):
with self.session(use_gpu=False) as sess:
new_shape = array_ops.placeholder(dtype=dtypes.int64)
@@ -439,6 +449,7 @@ class SparseResetShapeTest(test_util.TensorFlowTestCase):
with self.assertRaisesOpError("x == y did not hold element-wise"):
sess.run(out, feed_dict={new_shape: np.array([3, 7], dtype=np.int64)})
+ @test_util.run_deprecated_v1
def testInvalidDimensionSizeStatic(self):
sp_input = self._SparseTensor_2x5x6()
new_shape = np.array([3, 7, 5], dtype=np.int64)
@@ -446,6 +457,7 @@ class SparseResetShapeTest(test_util.TensorFlowTestCase):
with self.assertRaisesRegexp(ValueError, "should have dimension sizes"):
sparse_ops.sparse_reset_shape(sp_input, new_shape)
+ @test_util.run_deprecated_v1
def testInvalidDimensionSizeDynamic(self):
with self.session(use_gpu=False) as sess:
sp_input = self._SparseTensor_2x5x6()
@@ -455,6 +467,7 @@ class SparseResetShapeTest(test_util.TensorFlowTestCase):
with self.assertRaisesOpError("x <= y did not hold element-wise"):
sess.run(out, feed_dict={new_shape: [3, 7, 5]})
+ @test_util.run_deprecated_v1
def testInvalidDimensionSizeInputUnavailableInGraphConstruction(self):
sp_input = array_ops.sparse_placeholder(dtype=dtypes.int32)
with self.session(use_gpu=False) as sess:
@@ -496,6 +509,7 @@ class SparseFillEmptyRowsTest(test_util.TensorFlowTestCase):
constant_op.constant(val, dtypes.int32),
constant_op.constant(shape, dtypes.int64))
+ @test_util.run_deprecated_v1
def testFillNumber(self):
with self.session(use_gpu=False) as sess:
for sp_input in (self._SparseTensorValue_5x6(), self._SparseTensor_5x6()):
@@ -513,6 +527,7 @@ class SparseFillEmptyRowsTest(test_util.TensorFlowTestCase):
self.assertAllEqual(empty_row_indicator_out,
np.array([0, 0, 1, 0, 1]).astype(np.bool))
+ @test_util.run_deprecated_v1
def testFillFloat(self):
with self.session(use_gpu=False) as sess:
values = constant_op.constant(
@@ -547,6 +562,7 @@ class SparseFillEmptyRowsTest(test_util.TensorFlowTestCase):
self.assertGreater(default_value_grad_err, 0)
self.assertLess(default_value_grad_err, 1e-8)
+ @test_util.run_deprecated_v1
def testFillString(self):
with self.session(use_gpu=False) as sess:
sp_input = self._SparseTensor_String5x6()
@@ -565,6 +581,7 @@ class SparseFillEmptyRowsTest(test_util.TensorFlowTestCase):
self.assertAllEqual(empty_row_indicator_out,
np.array([0, 0, 1, 0, 1]).astype(np.bool))
+ @test_util.run_deprecated_v1
def testNoEmptyRows(self):
with self.session(use_gpu=False) as sess:
sp_input = self._SparseTensor_2x6()
@@ -582,6 +599,7 @@ class SparseFillEmptyRowsTest(test_util.TensorFlowTestCase):
class SparseAddTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testValuesInVariable(self):
indices = constant_op.constant([[1]], dtype=dtypes.int64)
values = variables.Variable([1], trainable=False, dtype=dtypes.float32)
@@ -657,6 +675,7 @@ class SparseReduceTest(test_util.TensorFlowTestCase):
self._compare(sp_t, reduction_axes, ndims, True, False)
self._compare(sp_t, reduction_axes, ndims, True, True)
+ @test_util.run_deprecated_v1
def testSimpleAndRandomInputs(self):
if np.__version__ == "1.13.0":
self.skipTest("numpy 1.13.0 bug")
@@ -696,6 +715,7 @@ class SparseReduceTest(test_util.TensorFlowTestCase):
with self.assertRaisesOpError("Invalid reduction dimension 2"):
sparse_ops.sparse_reduce_max(sp_t, 2).eval()
+ @test_util.run_deprecated_v1
def testGradient(self):
if np.__version__ == "1.13.0":
self.skipTest("numpy 1.13.0 bug")
@@ -778,6 +798,7 @@ class SparseMathOpsTest(test_util.TensorFlowTestCase):
result_tensor.values).eval()
self.assertAllEqual(result_np, res_densified)
+ @test_util.run_deprecated_v1
def testCwiseDivAndMul(self):
np.random.seed(1618)
sp_shapes = [(10, 10, 10), (5, 5), (1618,), (3, 3, 7)]
@@ -801,6 +822,7 @@ class SparseMathOpsTest(test_util.TensorFlowTestCase):
res = sp_t / dense_t # should invoke "__truediv__"
self.assertEqual(res.values.eval().dtype, np.float64)
+ @test_util.run_deprecated_v1
def testCwiseAdd(self):
with self.session(use_gpu=False):
# Identity(2) + AllOnes(2,2). Should be equal to 2 * Identity(2).
@@ -820,6 +842,7 @@ class SparseMathOpsTest(test_util.TensorFlowTestCase):
sparse_ops.sparse_dense_cwise_add(sp_t, dense_t),
np.identity(2) * 2, sp_t)
+ @test_util.run_deprecated_v1
def testGradients(self):
np.random.seed(1618)
sp_shapes = [(10, 10, 10), (5, 5), (1618,), (3, 3, 7)]
@@ -853,6 +876,7 @@ class SparseMathOpsTest(test_util.TensorFlowTestCase):
class SparseSoftmaxTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testEquivalentToDensified(self):
np.random.seed(1618)
n, m = np.random.choice(20, size=2)
@@ -872,6 +896,7 @@ class SparseSoftmaxTest(test_util.TensorFlowTestCase):
self.assertAllClose(dense_result.eval(), sp_result)
+ @test_util.run_deprecated_v1
def testHigherRanks(self):
# For the first shape:
# First batch:
@@ -901,6 +926,7 @@ class SparseSoftmaxTest(test_util.TensorFlowTestCase):
self.assertAllEqual(sp_t.indices.eval(), result.indices)
self.assertAllEqual(shape, result.dense_shape)
+ @test_util.run_deprecated_v1
def testGradient(self):
x_shape = [2, 5, 10]
with self.cached_session(use_gpu=False):
@@ -920,6 +946,7 @@ class SparseMinimumMaximumTest(test_util.TensorFlowTestCase):
self.assertAllEqual(a.values, b.values)
self.assertAllEqual(a.dense_shape, b.dense_shape)
+ @test_util.run_deprecated_v1
def testBasic(self):
with self.cached_session(use_gpu=False):
# 1-D, values at index 0.
@@ -939,6 +966,7 @@ class SparseMinimumMaximumTest(test_util.TensorFlowTestCase):
self._assertSparseTensorValueEqual(expected.eval(), max_tf)
self._assertSparseTensorValueEqual(expected.eval(), min_tf)
+ @test_util.run_deprecated_v1
def testRandom(self):
np.random.seed(1618)
shapes = [(13,), (6, 8), (1, 7, 1)]
@@ -980,6 +1008,7 @@ class SparseMinimumMaximumTest(test_util.TensorFlowTestCase):
class SparseTransposeTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testTranspose(self):
if np.__version__ == "1.13.0":
self.skipTest("numpy 1.13.0 bug")
@@ -1002,16 +1031,19 @@ class SparseTransposeTest(test.TestCase):
class SparsePlaceholderTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testPlaceholder(self):
foo = array_ops.sparse_placeholder(dtypes.float32, shape=(10, 47))
self.assertAllEqual([10, 47], foo.get_shape())
self.assertAllEqual([None, 2], foo.indices.get_shape().as_list())
+ @test_util.run_deprecated_v1
def testPartialShapePlaceholder(self):
foo = array_ops.sparse_placeholder(dtypes.float32, shape=(None, 47))
self.assertAllEqual([None, None], foo.get_shape().as_list())
self.assertAllEqual([None, 2], foo.indices.get_shape().as_list())
+ @test_util.run_deprecated_v1
def testNoShapePlaceholder(self):
foo = array_ops.sparse_placeholder(dtypes.float32, shape=None)
self.assertAllEqual(None, foo.get_shape())
diff --git a/tensorflow/python/kernel_tests/sparse_reorder_op_test.py b/tensorflow/python/kernel_tests/sparse_reorder_op_test.py
index bbf2f392026..93fcc6a18e6 100644
--- a/tensorflow/python/kernel_tests/sparse_reorder_op_test.py
+++ b/tensorflow/python/kernel_tests/sparse_reorder_op_test.py
@@ -22,6 +22,7 @@ import numpy as np
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import sparse_tensor
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import sparse_ops
@@ -65,6 +66,7 @@ class SparseReorderTest(test.TestCase):
self.assertAllEqual(output_val.values, input_val.values)
self.assertAllEqual(output_val.dense_shape, input_val.dense_shape)
+ @test_util.run_deprecated_v1
def testFeedAlreadyInOrder(self):
with self.session(use_gpu=False) as sess:
sp_input = self._SparseTensorPlaceholder()
@@ -89,6 +91,7 @@ class SparseReorderTest(test.TestCase):
self.assertAllEqual(output_val.dense_shape,
expected_output_val.dense_shape)
+ @test_util.run_deprecated_v1
def testFeedOutOfOrder(self):
expected_output_val = self._SparseTensorValue_5x6(np.arange(6))
with self.session(use_gpu=False) as sess:
@@ -103,6 +106,7 @@ class SparseReorderTest(test.TestCase):
self.assertAllEqual(output_val.dense_shape,
expected_output_val.dense_shape)
+ @test_util.run_deprecated_v1
def testGradients(self):
with self.session(use_gpu=False):
for _ in range(5): # To test various random permutations
diff --git a/tensorflow/python/kernel_tests/sparse_reshape_op_test.py b/tensorflow/python/kernel_tests/sparse_reshape_op_test.py
index 918af27091b..9341228d57e 100644
--- a/tensorflow/python/kernel_tests/sparse_reshape_op_test.py
+++ b/tensorflow/python/kernel_tests/sparse_reshape_op_test.py
@@ -22,6 +22,7 @@ import numpy as np
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import sparse_tensor
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import sparse_ops
from tensorflow.python.platform import test
@@ -64,12 +65,14 @@ class SparseReshapeTest(test.TestCase):
sp_output = sparse_ops.sparse_reshape(sp_input, shape=(2, -1))
self.assertAllEqual((2, 3 * 4), sp_output.get_shape())
+ @test_util.run_deprecated_v1
def testRaisesIfMoreThanOneInferredDim(self):
sp_input = sparse_tensor.SparseTensor.from_value(
self._SparseTensorValue_2x3x4())
with self.assertRaisesRegexp(ValueError, "At most one dimension can"):
sparse_ops.sparse_reshape(sp_input, shape=(-1, 2, -1))
+ @test_util.run_deprecated_v1
def testRaisesIfInferredShapeNotPossible(self):
sp_input = sparse_tensor.SparseTensor.from_value(
self._SparseTensorValue_2x3x4())
@@ -86,6 +89,7 @@ class SparseReshapeTest(test.TestCase):
self.assertAllEqual(output_val.values, input_val.values)
self.assertAllEqual(output_val.dense_shape, input_val.dense_shape)
+ @test_util.run_deprecated_v1
def testFeedSameShape(self):
with self.session(use_gpu=False) as sess:
sp_input = self._SparseTensorPlaceholder()
@@ -97,6 +101,7 @@ class SparseReshapeTest(test.TestCase):
self.assertAllEqual(output_val.values, input_val.values)
self.assertAllEqual(output_val.dense_shape, input_val.dense_shape)
+ @test_util.run_deprecated_v1
def testWorksWellWithTfShape(self):
with self.session(use_gpu=False) as sess:
sp_input = self._SparseTensorPlaceholder()
@@ -109,6 +114,7 @@ class SparseReshapeTest(test.TestCase):
self.assertAllEqual(output_val.values, input_val.values)
self.assertAllEqual(output_val.dense_shape, input_val.dense_shape)
+ @test_util.run_deprecated_v1
def testFeedSameShapeWithInferredDim(self):
with self.session(use_gpu=False) as sess:
sp_input = self._SparseTensorPlaceholder()
@@ -120,6 +126,7 @@ class SparseReshapeTest(test.TestCase):
self.assertAllEqual(output_val.values, input_val.values)
self.assertAllEqual(output_val.dense_shape, input_val.dense_shape)
+ @test_util.run_deprecated_v1
def testFeedNewShapeSameRank(self):
with self.session(use_gpu=False) as sess:
sp_input = self._SparseTensorPlaceholder()
@@ -133,6 +140,7 @@ class SparseReshapeTest(test.TestCase):
self.assertAllEqual(output_val.values, input_val.values)
self.assertAllEqual(output_val.dense_shape, [3, 10])
+ @test_util.run_deprecated_v1
def testFeedNewShapeSameRankWithInferredDim(self):
with self.session(use_gpu=False) as sess:
sp_input = self._SparseTensorPlaceholder()
@@ -158,6 +166,7 @@ class SparseReshapeTest(test.TestCase):
self.assertAllEqual(output_val.values, input_val.values)
self.assertAllEqual(output_val.dense_shape, [2, 3, 5])
+ @test_util.run_deprecated_v1
def testFeedUpRank(self):
with self.session(use_gpu=False) as sess:
sp_input = self._SparseTensorPlaceholder()
@@ -171,6 +180,7 @@ class SparseReshapeTest(test.TestCase):
self.assertAllEqual(output_val.values, input_val.values)
self.assertAllEqual(output_val.dense_shape, [2, 3, 5])
+ @test_util.run_deprecated_v1
def testFeedUpRankWithInferredDim(self):
with self.session(use_gpu=False) as sess:
sp_input = self._SparseTensorPlaceholder()
@@ -184,6 +194,7 @@ class SparseReshapeTest(test.TestCase):
self.assertAllEqual(output_val.values, input_val.values)
self.assertAllEqual(output_val.dense_shape, [2, 3, 5])
+ @test_util.run_deprecated_v1
def testFeedDownRank(self):
with self.session(use_gpu=False) as sess:
sp_input = self._SparseTensorPlaceholder()
@@ -197,6 +208,7 @@ class SparseReshapeTest(test.TestCase):
self.assertAllEqual(output_val.values, input_val.values)
self.assertAllEqual(output_val.dense_shape, [6, 4])
+ @test_util.run_deprecated_v1
def testFeedDownRankWithInferredDim(self):
with self.session(use_gpu=False) as sess:
sp_input = self._SparseTensorPlaceholder()
@@ -210,6 +222,7 @@ class SparseReshapeTest(test.TestCase):
self.assertAllEqual(output_val.values, input_val.values)
self.assertAllEqual(output_val.dense_shape, [6, 4])
+ @test_util.run_deprecated_v1
def testFeedMultipleInferredDims(self):
with self.session(use_gpu=False) as sess:
sp_input = self._SparseTensorPlaceholder()
@@ -218,12 +231,14 @@ class SparseReshapeTest(test.TestCase):
with self.assertRaisesOpError("only one output dimension may be -1"):
sess.run(sp_output, {sp_input: input_val})
+ @test_util.run_deprecated_v1
def testProvideStaticallyMismatchedSizes(self):
input_val = self._SparseTensorValue_5x6()
sp_input = sparse_tensor.SparseTensor.from_value(input_val)
with self.assertRaisesRegexp(ValueError, "Cannot reshape"):
sparse_ops.sparse_reshape(sp_input, [4, 7])
+ @test_util.run_deprecated_v1
def testFeedMismatchedSizes(self):
with self.session(use_gpu=False) as sess:
sp_input = self._SparseTensorPlaceholder()
@@ -233,6 +248,7 @@ class SparseReshapeTest(test.TestCase):
"Input to reshape is a tensor with 30 dense values"):
sess.run(sp_output, {sp_input: input_val})
+ @test_util.run_deprecated_v1
def testFeedMismatchedSizesWithInferredDim(self):
with self.session(use_gpu=False) as sess:
sp_input = self._SparseTensorPlaceholder()
@@ -241,6 +257,7 @@ class SparseReshapeTest(test.TestCase):
with self.assertRaisesOpError("requested shape requires a multiple"):
sess.run(sp_output, {sp_input: input_val})
+ @test_util.run_deprecated_v1
def testFeedPartialShapes(self):
with self.session(use_gpu=False):
# Incorporate new rank into shape information if known
@@ -266,6 +283,7 @@ class SparseReshapeTest(test.TestCase):
self.assertListEqual(sp_output.indices.get_shape().as_list(), [5, None])
self.assertListEqual(sp_output.dense_shape.get_shape().as_list(), [None])
+ @test_util.run_deprecated_v1
def testFeedDenseReshapeSemantics(self):
with self.session(use_gpu=False) as sess:
# Compute a random rank-5 initial shape and new shape, randomly sparsify
diff --git a/tensorflow/python/kernel_tests/sparse_serialization_ops_test.py b/tensorflow/python/kernel_tests/sparse_serialization_ops_test.py
index 39a9ab9b491..5a48eb825db 100644
--- a/tensorflow/python/kernel_tests/sparse_serialization_ops_test.py
+++ b/tensorflow/python/kernel_tests/sparse_serialization_ops_test.py
@@ -22,6 +22,7 @@ import numpy as np
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import sparse_tensor as sparse_tensor_lib
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import sparse_ops
from tensorflow.python.platform import test
@@ -110,14 +111,17 @@ class SerializeSparseTest(test.TestCase):
self.assertAllEqual(combined_values[6:], sp_input[1])
self.assertAllEqual(combined_shape, [2, 5, 6])
+ @test_util.run_deprecated_v1
def testSerializeDeserializeBatch(self):
self._testSerializeDeserializeBatchHelper(sparse_ops.serialize_sparse,
sparse_ops.deserialize_sparse)
+ @test_util.run_deprecated_v1
def testSerializeDeserializeManyBatch(self):
self._testSerializeDeserializeBatchHelper(
sparse_ops.serialize_sparse, sparse_ops.deserialize_many_sparse)
+ @test_util.run_deprecated_v1
def testVariantSerializeDeserializeBatch(self):
self._testSerializeDeserializeBatchHelper(sparse_ops.serialize_sparse,
sparse_ops.deserialize_sparse,
@@ -145,10 +149,12 @@ class SerializeSparseTest(test.TestCase):
self.assertAllEqual(combined_values[6:], sp_input1[1])
self.assertAllEqual(combined_shape, [2, 5, 6])
+ @test_util.run_deprecated_v1
def testSerializeDeserializeBatchInconsistentShape(self):
self._testSerializeDeserializeBatchInconsistentShapeHelper(
sparse_ops.serialize_sparse, sparse_ops.deserialize_sparse)
+ @test_util.run_deprecated_v1
def testVariantSerializeDeserializeBatchInconsistentShape(self):
self._testSerializeDeserializeBatchInconsistentShapeHelper(
sparse_ops.serialize_sparse, sparse_ops.deserialize_sparse,
@@ -188,10 +194,12 @@ class SerializeSparseTest(test.TestCase):
self.assertAllEqual(combined_shape, [2, 2, 5, 6])
+ @test_util.run_deprecated_v1
def testSerializeDeserializeNestedBatch(self):
self._testSerializeDeserializeNestedBatchHelper(
sparse_ops.serialize_sparse, sparse_ops.deserialize_sparse)
+ @test_util.run_deprecated_v1
def testVariantSerializeDeserializeNestedBatch(self):
self._testSerializeDeserializeNestedBatchHelper(
sparse_ops.serialize_sparse, sparse_ops.deserialize_sparse,
@@ -224,14 +232,17 @@ class SerializeSparseTest(test.TestCase):
self.assertAllEqual(combined_values[6:], input1_val[1])
self.assertAllEqual(combined_shape, [2, 5, 6])
+ @test_util.run_deprecated_v1
def testFeedSerializeDeserializeBatch(self):
self._testFeedSerializeDeserializeBatchHelper(sparse_ops.serialize_sparse,
sparse_ops.deserialize_sparse)
+ @test_util.run_deprecated_v1
def testFeedSerializeDeserializeManyBatch(self):
self._testFeedSerializeDeserializeBatchHelper(
sparse_ops.serialize_sparse, sparse_ops.deserialize_many_sparse)
+ @test_util.run_deprecated_v1
def testFeedVariantSerializeDeserializeBatch(self):
self._testFeedSerializeDeserializeBatchHelper(sparse_ops.serialize_sparse,
sparse_ops.deserialize_sparse,
@@ -256,6 +267,7 @@ class SerializeSparseTest(test.TestCase):
})
self.assertEqual(serialized_value.shape, (4, 3))
+ @test_util.run_deprecated_v1
def testSerializeManyShape(self):
self._testSerializeManyShapeHelper(sparse_ops.serialize_many_sparse)
@@ -287,19 +299,23 @@ class SerializeSparseTest(test.TestCase):
self.assertAllEqual(deserialized_value.values, values_value)
self.assertAllEqual(deserialized_value.dense_shape, shape_value)
+ @test_util.run_deprecated_v1
def testSerializeManyDeserializeBatch(self):
self._testSerializeManyDeserializeBatchHelper(
sparse_ops.serialize_many_sparse, sparse_ops.deserialize_sparse)
+ @test_util.run_deprecated_v1
def testSerializeManyDeserializeManyBatch(self):
self._testSerializeManyDeserializeBatchHelper(
sparse_ops.serialize_many_sparse, sparse_ops.deserialize_many_sparse)
+ @test_util.run_deprecated_v1
def testVariantSerializeManyDeserializeBatch(self):
self._testSerializeManyDeserializeBatchHelper(
sparse_ops.serialize_many_sparse, sparse_ops.deserialize_sparse,
dtypes.variant)
+ @test_util.run_deprecated_v1
def testVariantSerializeDeserializeScalar(self):
with self.session(use_gpu=False) as sess:
indices_value = np.array([[]], dtype=np.int64)
@@ -321,6 +337,7 @@ class SerializeSparseTest(test.TestCase):
self.assertAllEqual(deserialized_value.values, values_value)
self.assertAllEqual(deserialized_value.dense_shape, shape_value)
+ @test_util.run_deprecated_v1
def testVariantSerializeDeserializeScalarBatch(self):
with self.session(use_gpu=False) as sess:
indices_value = np.array([[]], dtype=np.int64)
@@ -367,14 +384,17 @@ class SerializeSparseTest(test.TestCase):
{sp_input0: input0_val,
sp_input1: input1_val})
+ @test_util.run_deprecated_v1
def testDeserializeFailsWrongType(self):
self._testDeserializeFailsWrongTypeHelper(sparse_ops.serialize_sparse,
sparse_ops.deserialize_sparse)
+ @test_util.run_deprecated_v1
def testDeserializeManyFailsWrongType(self):
self._testDeserializeFailsWrongTypeHelper(
sparse_ops.serialize_sparse, sparse_ops.deserialize_many_sparse)
+ @test_util.run_deprecated_v1
def testVariantDeserializeFailsWrongType(self):
self._testDeserializeFailsWrongTypeHelper(sparse_ops.serialize_sparse,
sparse_ops.deserialize_sparse,
@@ -402,14 +422,17 @@ class SerializeSparseTest(test.TestCase):
{sp_input0: input0_val,
sp_input1: input1_val})
+ @test_util.run_deprecated_v1
def testDeserializeFailsInconsistentRank(self):
self._testDeserializeFailsInconsistentRankHelper(
sparse_ops.serialize_sparse, sparse_ops.deserialize_sparse)
+ @test_util.run_deprecated_v1
def testDeserializeManyFailsInconsistentRank(self):
self._testDeserializeFailsInconsistentRankHelper(
sparse_ops.serialize_sparse, sparse_ops.deserialize_many_sparse)
+ @test_util.run_deprecated_v1
def testVariantDeserializeFailsInconsistentRank(self):
self._testDeserializeFailsInconsistentRankHelper(
sparse_ops.serialize_sparse, sparse_ops.deserialize_sparse,
@@ -431,10 +454,12 @@ class SerializeSparseTest(test.TestCase):
with self.assertRaisesOpError(r"Could not parse serialized proto"):
sess.run(sp_deserialized, {sp_input0: input0_val})
+ @test_util.run_deprecated_v1
def testDeserializeFailsInvalidProto(self):
self._testDeserializeFailsInvalidProtoHelper(sparse_ops.serialize_sparse,
sparse_ops.deserialize_sparse)
+ @test_util.run_deprecated_v1
def testDeserializeManyFailsInvalidProto(self):
self._testDeserializeFailsInvalidProtoHelper(
sparse_ops.serialize_sparse, sparse_ops.deserialize_many_sparse)
diff --git a/tensorflow/python/kernel_tests/sparse_slice_op_test.py b/tensorflow/python/kernel_tests/sparse_slice_op_test.py
index 098353741f3..7f8c91bde67 100644
--- a/tensorflow/python/kernel_tests/sparse_slice_op_test.py
+++ b/tensorflow/python/kernel_tests/sparse_slice_op_test.py
@@ -21,6 +21,7 @@ from __future__ import print_function
import numpy as np
from tensorflow.python.framework import sparse_tensor
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import sparse_ops
import tensorflow.python.ops.sparse_grad # pylint: disable=unused-import
@@ -79,6 +80,7 @@ class SparseSliceOpTest(test.TestCase):
return sparse_tensor.SparseTensor.from_value(
self._SparseTensorValue_3x4x2())
+ @test_util.run_deprecated_v1
def testSliceMatrixRows(self):
with self.session(use_gpu=False):
sp_input = self._SparseTensor_4x6()
@@ -96,6 +98,7 @@ class SparseSliceOpTest(test.TestCase):
[20, 23, 25, 30, 32, 33, 35])
self.assertAllEqual(sp_tensor1.dense_shape.eval(), [2, 6])
+ @test_util.run_deprecated_v1
def testSliceMatrixUnevenCols(self):
with self.session(use_gpu=False):
sp_input = self._SparseTensor_5x7()
@@ -137,6 +140,7 @@ class SparseSliceOpTest(test.TestCase):
self.assertAllEqual(sp_tensor3.values.eval(), [16, 46])
self.assertAllEqual(sp_tensor3.dense_shape.eval(), [5, 1])
+ @test_util.run_deprecated_v1
def testSliceMatrixUnevenRows(self):
with self.session(use_gpu=False):
sp_input = self._SparseTensor_5x7()
@@ -173,6 +177,7 @@ class SparseSliceOpTest(test.TestCase):
self.assertAllEqual(sp_tensor2.dense_shape.eval(), [1, 7])
return
+ @test_util.run_deprecated_v1
def testSliceAllRows(self):
with self.session(use_gpu=False):
sp_input = self._SparseTensor_4x6()
@@ -195,6 +200,7 @@ class SparseSliceOpTest(test.TestCase):
self.assertAllEqual(sp_tensor3.values.eval(), [30, 32, 33, 35])
self.assertAllEqual(sp_tensor3.dense_shape.eval(), [1, 6])
+ @test_util.run_deprecated_v1
def testSliceColumns(self):
with self.session(use_gpu=False):
sp_input = self._SparseTensor_4x6()
@@ -215,6 +221,7 @@ class SparseSliceOpTest(test.TestCase):
self.assertAllEqual(sparse_tensor2.values.eval(), [4, 5, 14, 25, 35])
self.assertAllEqual(sparse_tensor2.dense_shape.eval(), [4, 2])
+ @test_util.run_deprecated_v1
def testSliceAllColumns(self):
with self.session(use_gpu=False):
sp_input = self._SparseTensor_4x6()
@@ -246,6 +253,7 @@ class SparseSliceOpTest(test.TestCase):
self.assertAllEqual(sparse_tensor5.values.eval(), [5, 25, 35])
self.assertAllEqual(sparse_tensor5.dense_shape.eval(), [4, 1])
+ @test_util.run_deprecated_v1
def testGradients(self):
sp_input = self._SparseTensor_4x6(val_dtype=np.float32)
start_and_size = [([0, 0], [4, 2]),
diff --git a/tensorflow/python/kernel_tests/sparse_split_op_test.py b/tensorflow/python/kernel_tests/sparse_split_op_test.py
index 95661ded4be..f4bb7498b02 100644
--- a/tensorflow/python/kernel_tests/sparse_split_op_test.py
+++ b/tensorflow/python/kernel_tests/sparse_split_op_test.py
@@ -21,6 +21,7 @@ from __future__ import print_function
import numpy as np
from tensorflow.python.framework import sparse_tensor
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import sparse_ops
from tensorflow.python.platform import test
@@ -75,6 +76,7 @@ class SparseSplitOpTest(test.TestCase):
return sparse_tensor.SparseTensor.from_value(self._SparseTensorValue_3x4x2(
))
+ @test_util.run_deprecated_v1
def testSplitMatrixRows(self):
with self.session(use_gpu=False):
sp_tensors = sparse_ops.sparse_split(
@@ -92,6 +94,7 @@ class SparseSplitOpTest(test.TestCase):
[20, 23, 25, 30, 32, 33, 35])
self.assertAllEqual(sp_tensors[1].dense_shape.eval(), [2, 6])
+ @test_util.run_deprecated_v1
def testSplitMatrixUnevenCols(self):
with self.session(use_gpu=False):
sp_tensors_3 = sparse_ops.sparse_split(
@@ -131,6 +134,7 @@ class SparseSplitOpTest(test.TestCase):
self.assertAllEqual(sp_tensors_4[3].values.eval(), [16, 46])
self.assertAllEqual(sp_tensors_4[3].dense_shape.eval(), [5, 1])
+ @test_util.run_deprecated_v1
def testSplitMatrixUnevenRows(self):
with self.session(use_gpu=False):
sp_tensors_2 = sparse_ops.sparse_split(
@@ -167,6 +171,7 @@ class SparseSplitOpTest(test.TestCase):
self.assertAllEqual(sp_tensors_3[2].dense_shape.eval(), [1, 7])
return
+ @test_util.run_deprecated_v1
def testSplitAllRows(self):
with self.session(use_gpu=False):
sp_tensors = sparse_ops.sparse_split(
@@ -189,6 +194,7 @@ class SparseSplitOpTest(test.TestCase):
self.assertAllEqual(sp_tensors[3].values.eval(), [30, 32, 33, 35])
self.assertAllEqual(sp_tensors[3].dense_shape.eval(), [1, 6])
+ @test_util.run_deprecated_v1
def testSplitColumns(self):
with self.session(use_gpu=False):
sparse_tensors = sparse_ops.sparse_split(
@@ -207,6 +213,7 @@ class SparseSplitOpTest(test.TestCase):
self.assertAllEqual(sparse_tensors[2].values.eval(), [4, 5, 14, 25, 35])
self.assertAllEqual(sparse_tensors[2].dense_shape.eval(), [4, 2])
+ @test_util.run_deprecated_v1
def testSplitAllColumns(self):
with self.session(use_gpu=False):
sparse_tensors = sparse_ops.sparse_split(
@@ -234,6 +241,7 @@ class SparseSplitOpTest(test.TestCase):
self.assertAllEqual(sparse_tensors[5].values.eval(), [5, 25, 35])
self.assertAllEqual(sparse_tensors[5].dense_shape.eval(), [4, 1])
+ @test_util.run_deprecated_v1
def testSliceConcat(self):
for sp_input in (self._SparseTensorValue_3x4x2(),
self._SparseTensor_3x4x2()):
diff --git a/tensorflow/python/kernel_tests/sparse_tensor_dense_matmul_grad_test.py b/tensorflow/python/kernel_tests/sparse_tensor_dense_matmul_grad_test.py
index b8f33d6a813..fa2bab1fca6 100644
--- a/tensorflow/python/kernel_tests/sparse_tensor_dense_matmul_grad_test.py
+++ b/tensorflow/python/kernel_tests/sparse_tensor_dense_matmul_grad_test.py
@@ -22,6 +22,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import sparse_tensor
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import sparse_ops
import tensorflow.python.ops.sparse_grad # pylint: disable=unused-import
@@ -89,6 +90,7 @@ class SparseTensorDenseMatMulGradientTest(test.TestCase):
self._testGradients(adjoint_a, adjoint_b, name, values_dtype,
indices_dtype)
+ @test_util.run_deprecated_v1
def testGradients(self):
np.random.seed(5) # Fix seed to avoid flakiness
self._testGradientsType(np.float32, np.int64)
diff --git a/tensorflow/python/kernel_tests/sparse_tensor_dense_matmul_op_test.py b/tensorflow/python/kernel_tests/sparse_tensor_dense_matmul_op_test.py
index e605cb1c358..637cfaec990 100644
--- a/tensorflow/python/kernel_tests/sparse_tensor_dense_matmul_op_test.py
+++ b/tensorflow/python/kernel_tests/sparse_tensor_dense_matmul_op_test.py
@@ -30,6 +30,7 @@ from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
from tensorflow.python.framework import sparse_tensor
from tensorflow.python.framework import tensor_shape
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import control_flow_ops
from tensorflow.python.ops import math_ops
@@ -96,6 +97,7 @@ class SparseTensorDenseMatMulTest(test.TestCase):
self._testMatmul(x, y, indices_dtype=indices_dtype)
+ @test_util.run_deprecated_v1
def testBasic(self):
np.random.seed(127) # Repeatable results
self._testBasic(np.int32)
@@ -106,6 +108,7 @@ class SparseTensorDenseMatMulTest(test.TestCase):
self._testBasic(np.int32, indices_dtype=np.int32)
self._testBasic(np.float32, indices_dtype=np.int32)
+ @test_util.run_deprecated_v1
def testShapeInference(self):
x = np.random.rand(10, 10)
x[np.abs(x) < 0.5] = 0 # Make it sparse
@@ -229,6 +232,7 @@ class SparseTensorDenseMatMulTest(test.TestCase):
self._testLarge(np.complex128)
# Tests random sized matrices.
+ @test_util.run_deprecated_v1
def testFloatRandom(self):
np.random.seed(127) # Repeatable results
for _ in range(8):
diff --git a/tensorflow/python/kernel_tests/sparse_tensors_map_ops_test.py b/tensorflow/python/kernel_tests/sparse_tensors_map_ops_test.py
index 538e7c69b57..6039ff1afa7 100644
--- a/tensorflow/python/kernel_tests/sparse_tensors_map_ops_test.py
+++ b/tensorflow/python/kernel_tests/sparse_tensors_map_ops_test.py
@@ -24,6 +24,7 @@ from tensorflow.python.client import session
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
from tensorflow.python.framework import sparse_tensor as sparse_tensor_lib
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import sparse_ops
from tensorflow.python.ops import variables
@@ -76,6 +77,7 @@ class SparseTensorsMapTest(test.TestCase):
shape = np.array([3, 4, 5]).astype(np.int64)
return sparse_tensor_lib.SparseTensorValue(ind, val, shape)
+ @test_util.run_deprecated_v1
def testAddTakeMany(self):
with self.session(graph=ops.Graph(), use_gpu=False) as sess:
sp_input0 = self._SparseTensorValue_5x6(np.arange(6))
@@ -98,6 +100,7 @@ class SparseTensorsMapTest(test.TestCase):
self.assertAllEqual(combined_values[6:], sp_input1[1])
self.assertAllEqual(combined_shape, [2, 5, 6])
+ @test_util.run_deprecated_v1
def testFeedAddTakeMany(self):
with self.session(use_gpu=False) as sess:
sp_input = self._SparseTensorPlaceholder()
@@ -125,6 +128,7 @@ class SparseTensorsMapTest(test.TestCase):
self.assertAllEqual(combined_values[6:], input1_val[1])
self.assertAllEqual(combined_shape, [2, 5, 6])
+ @test_util.run_deprecated_v1
def testAddManyTakeManyRoundTrip(self):
with self.session(use_gpu=False) as sess:
# N == 4 because shape_value == [4, 5]
@@ -147,6 +151,7 @@ class SparseTensorsMapTest(test.TestCase):
self.assertAllEqual(roundtrip_value.values, values_value)
self.assertAllEqual(roundtrip_value.dense_shape, shape_value)
+ @test_util.run_deprecated_v1
def testDeserializeFailsInconsistentRank(self):
with self.session(use_gpu=False) as sess:
sp_input = self._SparseTensorPlaceholder()
@@ -168,6 +173,7 @@ class SparseTensorsMapTest(test.TestCase):
r"SparseTensor\[1\] was: 3 but rank of SparseTensor\[1\] is: 4"):
self.evaluate(sp_roundtrip)
+ @test_util.run_deprecated_v1
def testTakeManyFailsWrongInputOp(self):
with self.session(use_gpu=False) as sess:
input_val = self._SparseTensorValue_5x6(np.arange(6))
diff --git a/tensorflow/python/kernel_tests/sparse_to_dense_op_py_test.py b/tensorflow/python/kernel_tests/sparse_to_dense_op_py_test.py
index fa6cb134327..c6c45db4f9a 100644
--- a/tensorflow/python/kernel_tests/sparse_to_dense_op_py_test.py
+++ b/tensorflow/python/kernel_tests/sparse_to_dense_op_py_test.py
@@ -21,6 +21,7 @@ from __future__ import print_function
import numpy as np
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import sparse_ops
from tensorflow.python.platform import test
@@ -41,36 +42,42 @@ def _SparseToDense(sparse_indices,
class SparseToDenseTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testInt(self):
with self.session(use_gpu=False):
tf_ans = _SparseToDense([1, 3], [5], 1, 0).eval()
np_ans = np.array([0, 1, 0, 1, 0]).astype(np.int32)
self.assertAllClose(np_ans, tf_ans)
+ @test_util.run_deprecated_v1
def testFloat(self):
with self.session(use_gpu=False):
tf_ans = _SparseToDense([1, 3], [5], 1.0, 0.0).eval()
np_ans = np.array([0, 1, 0, 1, 0]).astype(np.float32)
self.assertAllClose(np_ans, tf_ans)
+ @test_util.run_deprecated_v1
def testString(self):
with self.session(use_gpu=False):
tf_ans = _SparseToDense([1, 3], [5], "a", "b").eval()
np_ans = np.array(["b", "a", "b", "a", "b"]).astype(np.string_)
self.assertAllEqual(np_ans, tf_ans)
+ @test_util.run_deprecated_v1
def testSetValue(self):
with self.session(use_gpu=False):
tf_ans = _SparseToDense([1, 3], [5], [1, 2], -1).eval()
np_ans = np.array([-1, 1, -1, 2, -1]).astype(np.int32)
self.assertAllClose(np_ans, tf_ans)
+ @test_util.run_deprecated_v1
def testSetSingleValue(self):
with self.session(use_gpu=False):
tf_ans = _SparseToDense([1, 3], [5], 1, -1).eval()
np_ans = np.array([-1, 1, -1, 1, -1]).astype(np.int32)
self.assertAllClose(np_ans, tf_ans)
+ @test_util.run_deprecated_v1
def test2d(self):
# pylint: disable=bad-whitespace
with self.session(use_gpu=False):
@@ -80,11 +87,13 @@ class SparseToDenseTest(test.TestCase):
[ 1, -1, -1, -1]]).astype(np.int32)
self.assertAllClose(np_ans, tf_ans)
+ @test_util.run_deprecated_v1
def testZeroDefault(self):
with self.cached_session():
x = sparse_ops.sparse_to_dense(2, [4], 7).eval()
self.assertAllEqual(x, [0, 0, 7, 0])
+ @test_util.run_deprecated_v1
def test3d(self):
with self.session(use_gpu=False):
tf_ans = _SparseToDense([[1, 3, 0], [2, 0, 1]], [3, 4, 2], 1, -1).eval()
@@ -93,11 +102,13 @@ class SparseToDenseTest(test.TestCase):
np_ans[2, 0, 1] = 1
self.assertAllClose(np_ans, tf_ans)
+ @test_util.run_deprecated_v1
def testBadShape(self):
with self.cached_session():
with self.assertRaisesWithPredicateMatch(ValueError, "must be rank 1"):
_SparseToDense([1, 3], [[5], [3]], 1, -1)
+ @test_util.run_deprecated_v1
def testBadValue(self):
with self.cached_session():
dense = _SparseToDense([1, 3], [5], [[5], [3]], -1)
@@ -106,6 +117,7 @@ class SparseToDenseTest(test.TestCase):
r"should be \[\] or \[2\]"):
self.evaluate(dense)
+ @test_util.run_deprecated_v1
def testBadNumValues(self):
with self.cached_session():
dense = _SparseToDense([1, 3], [5], [1, 2, 3], -1)
@@ -113,12 +125,14 @@ class SparseToDenseTest(test.TestCase):
r"sparse_values has incorrect shape \[3\], should be \[\] or \[2\]"):
self.evaluate(dense)
+ @test_util.run_deprecated_v1
def testBadDefault(self):
with self.cached_session():
dense = _SparseToDense([1, 3], [5], [1, 2], [0])
with self.assertRaisesOpError("default_value should be a scalar"):
self.evaluate(dense)
+ @test_util.run_deprecated_v1
def testOutOfBoundsIndicesWithWithoutValidation(self):
with self.cached_session():
dense = _SparseToDense(
@@ -139,6 +153,7 @@ class SparseToDenseTest(test.TestCase):
validate_indices=False)
self.evaluate(dense_without_validation)
+ @test_util.run_deprecated_v1
def testRepeatingIndicesWithWithoutValidation(self):
with self.cached_session():
dense = _SparseToDense(
@@ -157,6 +172,7 @@ class SparseToDenseTest(test.TestCase):
validate_indices=False)
self.evaluate(dense_without_validation)
+ @test_util.run_deprecated_v1
def testUnsortedIndicesWithWithoutValidation(self):
with self.cached_session():
dense = _SparseToDense(
@@ -175,6 +191,7 @@ class SparseToDenseTest(test.TestCase):
validate_indices=False)
self.evaluate(dense_without_validation)
+ @test_util.run_deprecated_v1
def testShapeInferenceKnownShape(self):
with self.session(use_gpu=False):
indices = array_ops.placeholder(dtypes.int64)
@@ -187,6 +204,7 @@ class SparseToDenseTest(test.TestCase):
output = sparse_ops.sparse_to_dense(indices, shape, 1, 0)
self.assertEqual(output.get_shape().as_list(), [None, None, None])
+ @test_util.run_deprecated_v1
def testShapeInferenceUnknownShape(self):
with self.session(use_gpu=False):
indices = array_ops.placeholder(dtypes.int64)
diff --git a/tensorflow/python/kernel_tests/sparse_xent_op_test.py b/tensorflow/python/kernel_tests/sparse_xent_op_test.py
index cc8c7c238f9..8f0842f7f50 100644
--- a/tensorflow/python/kernel_tests/sparse_xent_op_test.py
+++ b/tensorflow/python/kernel_tests/sparse_xent_op_test.py
@@ -29,6 +29,7 @@ from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors_impl
from tensorflow.python.framework import ops as ops_lib
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gen_nn_ops
from tensorflow.python.ops import gradient_checker
@@ -80,6 +81,7 @@ class SparseXentTest(test.TestCase):
self.assertAllClose([0.0, 0.0, 0.0], tf_loss)
self.assertAllClose([[0.0], [0.0], [0.0]], tf_backprop)
+ @test_util.run_deprecated_v1
def testInvalidLabel(self):
features = [[1., 1., 1., 1.], [1., 1., 1., 1.], [1., 2., 3., 4.],
[1., 2., 3., 4.]]
@@ -152,6 +154,7 @@ class SparseXentTest(test.TestCase):
nn_ops.sparse_softmax_cross_entropy_with_logits(
labels=constant_op.constant(0), logits=constant_op.constant(1.0))
+ @test_util.run_deprecated_v1
def testLabelsPlaceholderScalar(self):
with self.session(use_gpu=True):
labels = array_ops.placeholder(np.int32)
@@ -187,6 +190,7 @@ class SparseXentTest(test.TestCase):
def testEmpty(self):
self._testXent(np.zeros((0, 3)), np.zeros((0,), dtype=np.int32))
+ @test_util.run_deprecated_v1
def testGradient(self):
with self.session(use_gpu=True):
l = constant_op.constant([3, 0, 1], name="l")
@@ -201,6 +205,7 @@ class SparseXentTest(test.TestCase):
print("cross entropy gradient err = ", err)
self.assertLess(err, 5e-8)
+ @test_util.run_deprecated_v1
def testSecondGradient(self):
images_placeholder = array_ops.placeholder(dtypes.float32, shape=(3, 2))
labels_placeholder = array_ops.placeholder(dtypes.int32, shape=(3))
@@ -230,17 +235,20 @@ class SparseXentTest(test.TestCase):
self.assertAllCloseAccordingToType(np_loss, tf_loss)
self.assertAllCloseAccordingToType(np_backprop, tf_backprop)
+ @test_util.run_deprecated_v1
def testHighDim(self):
features = [[[1., 1., 1., 1.]], [[1., 2., 3., 4.]]]
labels = [[3], [0]]
self._testHighDim(features, labels)
+ @test_util.run_deprecated_v1
def testHighDim2(self):
features = [[[1., 1., 1., 1.], [2., 2., 2., 2.]],
[[1., 2., 3., 4.], [5., 6., 7., 8.]]]
labels = [[3, 2], [0, 3]]
self._testHighDim(features, labels)
+ @test_util.run_deprecated_v1
def testScalarHandling(self):
with self.session(use_gpu=False) as sess:
with self.assertRaisesRegexp(errors_impl.InvalidArgumentError,
@@ -318,7 +326,7 @@ def sparse_vs_dense_xent_benchmark(batch_size, num_entries, use_gpu):
# Using sparse_softmax_cross_entropy_with_logits
with session.Session(config=config) as sess:
if not use_gpu:
- with ops_lib.device("/cpu:0"):
+ with test_util.device("/cpu:0"):
ops = _sparse_vs_dense_xent_benchmark_sparse(labels, logits)
else:
ops = _sparse_vs_dense_xent_benchmark_sparse(labels, logits)
diff --git a/tensorflow/python/kernel_tests/sparsemask_op_test.py b/tensorflow/python/kernel_tests/sparsemask_op_test.py
index 6f5dd45b616..b1cd0227bc0 100644
--- a/tensorflow/python/kernel_tests/sparsemask_op_test.py
+++ b/tensorflow/python/kernel_tests/sparsemask_op_test.py
@@ -20,12 +20,14 @@ from __future__ import print_function
import numpy as np
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.platform import test
class SparseMaskTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testBasic(self):
values = np.random.rand(4, 4).astype(np.single)
indices = np.array([0, 2, 3, 4], dtype=np.int32)
diff --git a/tensorflow/python/kernel_tests/split_op_test.py b/tensorflow/python/kernel_tests/split_op_test.py
index af90e03966e..517db3450f3 100644
--- a/tensorflow/python/kernel_tests/split_op_test.py
+++ b/tensorflow/python/kernel_tests/split_op_test.py
@@ -42,6 +42,7 @@ class SplitOpTest(test.TestCase):
data -= 1j * data
return data
+ @test_util.run_deprecated_v1
def testShapeInference(self):
model_input = array_ops.placeholder(dtypes.float32, shape=(1, 10))
@@ -85,6 +86,7 @@ class SplitOpTest(test.TestCase):
with self.cached_session(use_gpu=True) as sess:
sess.run(result, feed_dict={model_input2: np.ones([4, 2])})
+ @test_util.run_deprecated_v1
def testFailWithoutExplicitNum(self):
size_splits = array_ops.placeholder(dtype=dtypes.int32, shape=[None])
@@ -209,6 +211,7 @@ class SplitOpTest(test.TestCase):
self.assertAllEqual(result[:, 0:1], inp_grads[0])
self.assertAllEqual(result[:, 1:4], inp_grads[1])
+ @test_util.run_deprecated_v1
def testOutputShape(self):
for axis in [1, -1]:
with self.cached_session(use_gpu=True):
@@ -322,11 +325,13 @@ class SplitOpTest(test.TestCase):
for i in range(4):
self.assertAllEqual(result[:, i:i + 1], inp_grads[i])
+ @test_util.run_deprecated_v1
def testGradientsAll(self):
for dtype in _TEST_DTYPES:
self._testGradientsSimple(dtype)
self._testGradientsSimpleVariable(dtype)
+ @test_util.run_deprecated_v1
def testShapeFunctionEdgeCases(self):
# split_dim greater than rank of input.
with self.assertRaises(ValueError):
@@ -356,6 +361,7 @@ class SplitOpTest(test.TestCase):
for s in splits:
self.assertEqual(None, s.get_shape().ndims)
+ @test_util.run_deprecated_v1
def testVariableShapeFunction(self):
# size_splits too big
with self.assertRaises(ValueError):
@@ -366,6 +372,7 @@ class SplitOpTest(test.TestCase):
assert s0.shape.as_list() == [2]
assert s1.shape.as_list() == [1]
+ @test_util.run_deprecated_v1
def testNonexistentDimTensor(self):
x = array_ops.placeholder(dtypes.int32)
values = np.zeros([5, 30])
diff --git a/tensorflow/python/kernel_tests/stack_op_test.py b/tensorflow/python/kernel_tests/stack_op_test.py
index 0f1fa97c384..ca3357a0ed8 100644
--- a/tensorflow/python/kernel_tests/stack_op_test.py
+++ b/tensorflow/python/kernel_tests/stack_op_test.py
@@ -24,6 +24,7 @@ from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors_impl
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import variables
@@ -41,6 +42,7 @@ def np_split_squeeze(array, axis):
class StackOpTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testSimple(self):
np.random.seed(7)
with self.session(use_gpu=True):
@@ -54,6 +56,7 @@ class StackOpTest(test.TestCase):
c = array_ops.stack(xs)
self.assertAllEqual(c.eval(), data)
+ @test_util.run_deprecated_v1
def testSimpleParallelCPU(self):
np.random.seed(7)
with self.session(use_gpu=False):
@@ -63,6 +66,7 @@ class StackOpTest(test.TestCase):
c = array_ops.parallel_stack(xs)
self.assertAllEqual(c.eval(), data)
+ @test_util.run_deprecated_v1
def testSimpleParallelGPU(self):
np.random.seed(7)
with self.session(use_gpu=True):
@@ -72,6 +76,7 @@ class StackOpTest(test.TestCase):
c = array_ops.parallel_stack(xs)
self.assertAllEqual(c.eval(), data)
+ @test_util.run_deprecated_v1
def testConst(self):
np.random.seed(7)
with self.session(use_gpu=True):
@@ -96,6 +101,7 @@ class StackOpTest(test.TestCase):
b = array_ops.reshape(a, array_ops.stack([2, 3]))
self.assertAllEqual(b.get_shape(), [2, 3])
+ @test_util.run_deprecated_v1
def testConstParallelCPU(self):
np.random.seed(7)
with self.session(use_gpu=False):
@@ -110,6 +116,7 @@ class StackOpTest(test.TestCase):
c = array_ops.parallel_stack(data)
self.assertAllEqual(c.eval(), data)
+ @test_util.run_deprecated_v1
def testConstParallelGPU(self):
np.random.seed(7)
with self.session(use_gpu=True):
@@ -124,6 +131,7 @@ class StackOpTest(test.TestCase):
c = array_ops.parallel_stack(data)
self.assertAllEqual(c.eval(), data)
+ @test_util.run_deprecated_v1
def testGradientsAxis0(self):
np.random.seed(7)
for shape in (2,), (3,), (2, 3), (3, 2), (4, 3, 2):
@@ -136,6 +144,7 @@ class StackOpTest(test.TestCase):
err = gradient_checker.compute_gradient_error(xs, shapes, c, shape)
self.assertLess(err, 1e-6)
+ @test_util.run_deprecated_v1
def testGradientsAxis1(self):
np.random.seed(7)
for shape in (2, 3), (3, 2), (4, 3, 2):
@@ -150,6 +159,7 @@ class StackOpTest(test.TestCase):
err = gradient_checker.compute_gradient_error(xs, shapes, c, out_shape)
self.assertLess(err, 1e-6)
+ @test_util.run_deprecated_v1
def testZeroSizeCPU(self):
# Verify that stack doesn't crash for zero size inputs
with self.session(use_gpu=False):
@@ -161,6 +171,7 @@ class StackOpTest(test.TestCase):
p = array_ops.parallel_stack(list(x)).eval()
self.assertAllEqual(p, x)
+ @test_util.run_deprecated_v1
def testZeroSizeGPU(self):
# Verify that stack doesn't crash for zero size inputs
with self.session(use_gpu=True):
@@ -172,6 +183,7 @@ class StackOpTest(test.TestCase):
p = array_ops.parallel_stack(list(x)).eval()
self.assertAllEqual(p, x)
+ @test_util.run_deprecated_v1
def testAxis0DefaultCPU(self):
with self.session(use_gpu=False):
t = [constant_op.constant([1, 2, 3]), constant_op.constant([4, 5, 6])]
@@ -182,6 +194,7 @@ class StackOpTest(test.TestCase):
self.assertAllEqual(stacked, expected)
self.assertAllEqual(parallel_stacked, expected)
+ @test_util.run_deprecated_v1
def testAxis0DefaultGPU(self):
with self.session(use_gpu=True):
t = [constant_op.constant([1, 2, 3]), constant_op.constant([4, 5, 6])]
@@ -225,6 +238,7 @@ class StackOpTest(test.TestCase):
class AutomaticStackingTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testSimple(self):
with self.session(use_gpu=True):
self.assertAllEqual(
@@ -255,6 +269,7 @@ class AutomaticStackingTest(test.TestCase):
self.assertAllEqual([[[0., 0.], [1., 1.]], [[2., 2.], [3., 3.]]],
self.evaluate(result))
+ @test_util.run_deprecated_v1
def testVariable(self):
with self.session(use_gpu=True):
v = variables.Variable(17)
@@ -308,6 +323,7 @@ class AutomaticStackingTest(test.TestCase):
t_2 = ops.convert_to_tensor([t_0, t_0, t_1], dtype=dtypes.float64)
self.assertEqual(dtypes.float64, t_2.dtype)
+ @test_util.run_deprecated_v1
def testPlaceholder(self):
with self.session(use_gpu=True):
# Test using placeholder with a defined shape.
@@ -326,6 +342,7 @@ class AutomaticStackingTest(test.TestCase):
self.assertAllEqual(
[[0, 0, 0], [0, 2, 0], [0, 0, 0]], result_1.eval(feed_dict={ph_1: 2}))
+ @test_util.run_deprecated_v1
def testShapeErrors(self):
# Static shape error.
ph_0 = array_ops.placeholder(dtypes.int32, shape=[1])
diff --git a/tensorflow/python/kernel_tests/stack_ops_test.py b/tensorflow/python/kernel_tests/stack_ops_test.py
index dffb260b5fa..d50f3f46806 100644
--- a/tensorflow/python/kernel_tests/stack_ops_test.py
+++ b/tensorflow/python/kernel_tests/stack_ops_test.py
@@ -24,6 +24,7 @@ from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
from tensorflow.python.framework import tensor_shape
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import control_flow_ops
from tensorflow.python.ops import gen_data_flow_ops
from tensorflow.python.ops import math_ops
@@ -41,6 +42,7 @@ class StackOpTest(test.TestCase):
c1 = gen_data_flow_ops.stack_pop_v2(h, dtypes.float32)
self.assertAllClose([[4.0, 5.0]], self.evaluate(c1))
+ @test_util.run_deprecated_v1
def testStackPushPop(self):
self._testStackPushPop(use_gpu=False)
self._testStackPushPop(use_gpu=True)
@@ -56,6 +58,7 @@ class StackOpTest(test.TestCase):
c1 = gen_data_flow_ops.stack_pop_v2(h, dtypes.float32)
self.assertAllClose(a, self.evaluate(c1))
+ @test_util.run_deprecated_v1
def testStackPushPopSwap(self):
self._testStackPushPopSwap(use_gpu=False)
self._testStackPushPopSwap(use_gpu=True)
@@ -93,6 +96,7 @@ class StackOpTest(test.TestCase):
c1, b1, [r, v], [r.get_shape(), tensor_shape.unknown_shape()])
self.assertAllClose(np.ones(2000) * 10.0, self.evaluate(ry))
+ @test_util.run_deprecated_v1
def testStackWhileSwap(self):
self._testStackWhileSwap(use_gpu=False)
self._testStackWhileSwap(use_gpu=True)
@@ -112,6 +116,7 @@ class StackOpTest(test.TestCase):
r = c1 + c2
self.assertAllClose(9.0, self.evaluate(r))
+ @test_util.run_deprecated_v1
def testMultiStack(self):
self._testMultiStack(use_gpu=False)
self._testMultiStack(use_gpu=True)
@@ -135,6 +140,7 @@ class StackOpTest(test.TestCase):
self.assertAllClose(out1, 4.0)
self.assertAllClose(out2, 5.0)
+ @test_util.run_deprecated_v1
def testSameNameStacks(self):
self._testSameNameStacks(use_gpu=False)
self._testSameNameStacks(use_gpu=True)
@@ -146,6 +152,7 @@ class StackOpTest(test.TestCase):
c1 = gen_data_flow_ops.stack_close_v2(h)
self.evaluate(c1)
+ @test_util.run_deprecated_v1
def testCloseStack(self):
self._testCloseStack(use_gpu=False)
self._testCloseStack(use_gpu=True)
@@ -159,6 +166,7 @@ class StackOpTest(test.TestCase):
c1 = gen_data_flow_ops.stack_close_v2(h)
self.evaluate(c1)
+ @test_util.run_deprecated_v1
def testPushCloseStack(self):
self._testPushCloseStack(use_gpu=False)
self._testPushCloseStack(use_gpu=True)
@@ -175,6 +183,7 @@ class StackOpRefTest(test.TestCase):
c1 = gen_data_flow_ops.stack_pop(h, dtypes.float32)
self.assertAllClose([[4.0, 5.0]], self.evaluate(c1))
+ @test_util.run_deprecated_v1
def testStackPushPop(self):
self._testStackPushPop(use_gpu=False)
self._testStackPushPop(use_gpu=True)
@@ -189,6 +198,7 @@ class StackOpRefTest(test.TestCase):
c1 = gen_data_flow_ops.stack_pop(h, dtypes.float32)
self.assertAllClose(a, self.evaluate(c1))
+ @test_util.run_deprecated_v1
def testStackPushPopSwap(self):
self._testStackPushPopSwap(use_gpu=False)
self._testStackPushPopSwap(use_gpu=True)
@@ -238,10 +248,12 @@ class StackOpRefTest(test.TestCase):
c1, b1, [r, v], [r.get_shape(), tensor_shape.unknown_shape()])
self.assertAllClose(np.ones(2000) * 10.0, self.evaluate(ry))
+ @test_util.run_deprecated_v1
def testStackWhileSwap(self):
self._testStackWhileSwap(use_gpu=False)
self._testStackWhileSwap(use_gpu=True)
+ @test_util.run_deprecated_v1
def testMultiStack(self):
self._testMultiStack(use_gpu=False)
self._testMultiStack(use_gpu=True)
@@ -255,6 +267,7 @@ class StackOpRefTest(test.TestCase):
_ = c1 + c2
self.assertNotEqual(h1.eval()[1], self.evaluate(h2)[1])
+ @test_util.run_deprecated_v1
def testSameNameStacks(self):
self._testSameNameStacks(use_gpu=False)
self._testSameNameStacks(use_gpu=True)
@@ -265,6 +278,7 @@ class StackOpRefTest(test.TestCase):
c1 = gen_data_flow_ops.stack_close(h)
self.evaluate(c1)
+ @test_util.run_deprecated_v1
def testCloseStack(self):
self._testCloseStack(use_gpu=False)
self._testCloseStack(use_gpu=True)
@@ -277,6 +291,7 @@ class StackOpRefTest(test.TestCase):
c1 = gen_data_flow_ops.stack_close(h)
self.evaluate(c1)
+ @test_util.run_deprecated_v1
def testPushCloseStack(self):
self._testPushCloseStack(use_gpu=False)
self._testPushCloseStack(use_gpu=True)
diff --git a/tensorflow/python/kernel_tests/stage_op_test.py b/tensorflow/python/kernel_tests/stage_op_test.py
index b814843b86c..83e06ba48bd 100644
--- a/tensorflow/python/kernel_tests/stage_op_test.py
+++ b/tensorflow/python/kernel_tests/stage_op_test.py
@@ -18,6 +18,7 @@ from __future__ import print_function
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import data_flow_ops
from tensorflow.python.ops import math_ops
@@ -28,6 +29,7 @@ TIMEOUT = 1
class StageTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testSimple(self):
with ops.Graph().as_default() as G:
with ops.device('/cpu:0'):
@@ -47,6 +49,7 @@ class StageTest(test.TestCase):
_, yval = sess.run([stage, y], feed_dict={x: i})
self.assertAllClose(4 * (i - 1) * (i - 1) * 128, yval, rtol=1e-4)
+ @test_util.run_deprecated_v1
def testMultiple(self):
with ops.Graph().as_default() as G:
with ops.device('/cpu:0'):
@@ -67,6 +70,7 @@ class StageTest(test.TestCase):
self.assertAllClose(
4 * (i - 1) * (i - 1) * (i - 1) * 128, yval, rtol=1e-4)
+ @test_util.run_deprecated_v1
def testDictionary(self):
with ops.Graph().as_default() as G:
with ops.device('/cpu:0'):
@@ -110,6 +114,7 @@ class StageTest(test.TestCase):
G.finalize()
+ @test_util.run_deprecated_v1
def testPeek(self):
with ops.Graph().as_default() as G:
with ops.device('/cpu:0'):
@@ -133,6 +138,7 @@ class StageTest(test.TestCase):
for i in range(10):
self.assertTrue(sess.run(peek, feed_dict={p: i}) == [i])
+ @test_util.run_deprecated_v1
def testSizeAndClear(self):
with ops.Graph().as_default() as G:
with ops.device('/cpu:0'):
@@ -158,6 +164,7 @@ class StageTest(test.TestCase):
sess.run(clear)
self.assertEqual(sess.run(size), 0)
+ @test_util.run_deprecated_v1
def testCapacity(self):
capacity = 3
@@ -219,6 +226,7 @@ class StageTest(test.TestCase):
# It should now be empty
self.assertTrue(sess.run(size) == 0)
+ @test_util.run_deprecated_v1
def testMemoryLimit(self):
memory_limit = 512 * 1024 # 512K
chunk = 200 * 1024 # 256K
diff --git a/tensorflow/python/kernel_tests/string_join_op_test.py b/tensorflow/python/kernel_tests/string_join_op_test.py
index e4371ab5b93..2548e8695fe 100644
--- a/tensorflow/python/kernel_tests/string_join_op_test.py
+++ b/tensorflow/python/kernel_tests/string_join_op_test.py
@@ -17,12 +17,14 @@ from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import string_ops
from tensorflow.python.platform import test
class StringJoinOpTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testStringJoin(self):
input0 = ["a", "b"]
input1 = "a"
diff --git a/tensorflow/python/kernel_tests/string_length_op_test.py b/tensorflow/python/kernel_tests/string_length_op_test.py
index 06bf28ebcee..bfa6ac2454a 100644
--- a/tensorflow/python/kernel_tests/string_length_op_test.py
+++ b/tensorflow/python/kernel_tests/string_length_op_test.py
@@ -18,6 +18,7 @@ from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import string_ops
from tensorflow.python.platform import test
@@ -32,6 +33,7 @@ class StringLengthOpTest(test.TestCase):
values = self.evaluate(lengths)
self.assertAllEqual(values, [[[1, 2], [3, 4], [5, 6]]])
+ @test_util.run_deprecated_v1
def testUnit(self):
unicode_strings = [u"H\xc3llo", u"\U0001f604"]
utf8_strings = [s.encode("utf-8") for s in unicode_strings]
@@ -51,6 +53,7 @@ class StringLengthOpTest(test.TestCase):
'not in: "BYTE", "UTF8_CHAR"'):
string_ops.string_length(utf8_strings, unit="XYZ")
+ @test_util.run_deprecated_v1
def testLegacyPositionalName(self):
# Code that predates the 'unit' parameter may have used a positional
# argument for the 'name' parameter. Check that we don't break such code.
diff --git a/tensorflow/python/kernel_tests/string_split_op_test.py b/tensorflow/python/kernel_tests/string_split_op_test.py
index 92e13db0f73..0c91deb5220 100644
--- a/tensorflow/python/kernel_tests/string_split_op_test.py
+++ b/tensorflow/python/kernel_tests/string_split_op_test.py
@@ -22,6 +22,7 @@ import numpy as np
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors_impl
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import string_ops
from tensorflow.python.platform import test
@@ -39,6 +40,7 @@ class StringSplitOpTest(test.TestCase):
self.assertAllEqual(values, [b"pigs", b"on", b"the", b"wing", b"animals"])
self.assertAllEqual(shape, [2, 4])
+ @test_util.run_deprecated_v1
def testStringSplitEmptyDelimiter(self):
strings = ["hello", "hola", b"\xF0\x9F\x98\x8E"] # Last string is U+1F60E
@@ -81,6 +83,7 @@ class StringSplitOpTest(test.TestCase):
self.assertAllEqual(values, [b"a", b"b", b"c", b"d", b"e", b"f", b"g"])
self.assertAllEqual(shape, [10, 1])
+ @test_util.run_deprecated_v1
def testStringSplitWithDelimiter(self):
strings = ["hello|world", "hello world"]
@@ -103,6 +106,7 @@ class StringSplitOpTest(test.TestCase):
self.assertAllEqual(values, [b"hello", b"world", b"hello", b"world"])
self.assertAllEqual(shape, [2, 2])
+ @test_util.run_deprecated_v1
def testStringSplitWithDelimiterTensor(self):
strings = ["hello|world", "hello world"]
@@ -121,6 +125,7 @@ class StringSplitOpTest(test.TestCase):
self.assertAllEqual(values, [b"hello", b"world", b"hello world"])
self.assertAllEqual(shape, [2, 2])
+ @test_util.run_deprecated_v1
def testStringSplitWithDelimitersTensor(self):
strings = ["hello.cruel,world", "hello cruel world"]
diff --git a/tensorflow/python/kernel_tests/string_to_hash_bucket_op_test.py b/tensorflow/python/kernel_tests/string_to_hash_bucket_op_test.py
index 2cc87008da0..25f573fc144 100644
--- a/tensorflow/python/kernel_tests/string_to_hash_bucket_op_test.py
+++ b/tensorflow/python/kernel_tests/string_to_hash_bucket_op_test.py
@@ -19,6 +19,7 @@ from __future__ import print_function
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import string_ops
from tensorflow.python.platform import test
@@ -26,6 +27,7 @@ from tensorflow.python.platform import test
class StringToHashBucketOpTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testStringToOneHashBucketFast(self):
with self.cached_session():
input_string = array_ops.placeholder(dtypes.string)
@@ -34,6 +36,7 @@ class StringToHashBucketOpTest(test.TestCase):
self.assertAllEqual([0, 0, 0], result)
+ @test_util.run_deprecated_v1
def testStringToHashBucketsFast(self):
with self.cached_session():
input_string = array_ops.placeholder(dtypes.string)
@@ -46,6 +49,7 @@ class StringToHashBucketOpTest(test.TestCase):
# Fingerprint64('d') -> 4470636696479570465 -> mod 10 -> 5
self.assertAllEqual([9, 2, 2, 5], result)
+ @test_util.run_deprecated_v1
def testStringToOneHashBucketLegacyHash(self):
with self.cached_session():
input_string = array_ops.placeholder(dtypes.string)
@@ -54,6 +58,7 @@ class StringToHashBucketOpTest(test.TestCase):
self.assertAllEqual([0, 0, 0], result)
+ @test_util.run_deprecated_v1
def testStringToHashBucketsLegacyHash(self):
with self.cached_session():
input_string = array_ops.placeholder(dtypes.string)
diff --git a/tensorflow/python/kernel_tests/string_to_number_op_test.py b/tensorflow/python/kernel_tests/string_to_number_op_test.py
index 99ee25e1253..49ccfd1028f 100644
--- a/tensorflow/python/kernel_tests/string_to_number_op_test.py
+++ b/tensorflow/python/kernel_tests/string_to_number_op_test.py
@@ -19,6 +19,7 @@ from __future__ import division
from __future__ import print_function
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import parsing_ops
from tensorflow.python.platform import test
@@ -45,6 +46,7 @@ class StringToNumberOpTest(test.TestCase):
with self.assertRaisesOpError(outstr):
output.eval(feed_dict={input_string: [instr]})
+ @test_util.run_deprecated_v1
def testToFloat(self):
self._test(dtypes.float32,
[("0", 0), ("3", 3), ("-1", -1),
@@ -58,6 +60,7 @@ class StringToNumberOpTest(test.TestCase):
("INF", float("INF"))],
[("10foobar", _ERROR_MESSAGE + "10foobar")])
+ @test_util.run_deprecated_v1
def testToDouble(self):
self._test(dtypes.float64,
[("0", 0), ("3", 3), ("-1", -1),
@@ -71,6 +74,7 @@ class StringToNumberOpTest(test.TestCase):
("INF", float("INF"))],
[("10foobar", _ERROR_MESSAGE + "10foobar")])
+ @test_util.run_deprecated_v1
def testToInt32(self):
self._test(dtypes.int32,
[("0", 0), ("3", 3), ("-1", -1),
@@ -84,6 +88,7 @@ class StringToNumberOpTest(test.TestCase):
("2.9", _ERROR_MESSAGE + "2.9"),
("10foobar", _ERROR_MESSAGE + "10foobar")])
+ @test_util.run_deprecated_v1
def testToInt64(self):
self._test(dtypes.int64,
[("0", 0), ("3", 3), ("-1", -1),
diff --git a/tensorflow/python/kernel_tests/substr_op_test.py b/tensorflow/python/kernel_tests/substr_op_test.py
index bb2d4a79131..9302152e82b 100644
--- a/tensorflow/python/kernel_tests/substr_op_test.py
+++ b/tensorflow/python/kernel_tests/substr_op_test.py
@@ -22,6 +22,7 @@ from absl.testing import parameterized
import numpy as np
from tensorflow.python.framework import errors_impl
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import string_ops
from tensorflow.python.platform import test
@@ -319,6 +320,7 @@ class SubstrOpTest(test.TestCase, parameterized.TestCase):
(np.int32, "UTF8_CHAR"),
(np.int64, "UTF8_CHAR"),
)
+ @test_util.run_deprecated_v1
def testBadBroadcast(self, dtype, unit):
test_string = [[b"ten", b"eleven", b"twelve"],
[b"thirteen", b"fourteen", b"fifteen"],
@@ -338,6 +340,7 @@ class SubstrOpTest(test.TestCase, parameterized.TestCase):
(np.int32, -6, "UTF8_CHAR"),
(np.int64, -6, "UTF8_CHAR"),
)
+ @test_util.run_deprecated_v1
def testOutOfRangeError_Scalar(self, dtype, pos, unit):
# Scalar/Scalar
test_string = {
@@ -361,6 +364,7 @@ class SubstrOpTest(test.TestCase, parameterized.TestCase):
(np.int32, -4, "UTF8_CHAR"),
(np.int64, -4, "UTF8_CHAR"),
)
+ @test_util.run_deprecated_v1
def testOutOfRangeError_VectorScalar(self, dtype, pos, unit):
# Vector/Scalar
test_string = {
@@ -381,6 +385,7 @@ class SubstrOpTest(test.TestCase, parameterized.TestCase):
(np.int32, "UTF8_CHAR"),
(np.int64, "UTF8_CHAR"),
)
+ @test_util.run_deprecated_v1
def testOutOfRangeError_MatrixMatrix(self, dtype, unit):
# Matrix/Matrix
test_string = {
@@ -414,6 +419,7 @@ class SubstrOpTest(test.TestCase, parameterized.TestCase):
(np.int32, "UTF8_CHAR"),
(np.int64, "UTF8_CHAR"),
)
+ @test_util.run_deprecated_v1
def testOutOfRangeError_Broadcast(self, dtype, unit):
# Broadcast
test_string = {
@@ -444,6 +450,7 @@ class SubstrOpTest(test.TestCase, parameterized.TestCase):
(np.int32, "UTF8_CHAR"),
(np.int64, "UTF8_CHAR"),
)
+ @test_util.run_deprecated_v1
def testMismatchPosLenShapes(self, dtype, unit):
test_string = {
"BYTE": [[b"ten", b"eleven", b"twelve"],
@@ -471,6 +478,7 @@ class SubstrOpTest(test.TestCase, parameterized.TestCase):
with self.assertRaises(ValueError):
string_ops.substr(test_string, position, length)
+ @test_util.run_deprecated_v1
def testWrongDtype(self):
with self.cached_session():
with self.assertRaises(TypeError):
@@ -478,6 +486,7 @@ class SubstrOpTest(test.TestCase, parameterized.TestCase):
with self.assertRaises(TypeError):
string_ops.substr(b"test", 3, 1.0)
+ @test_util.run_deprecated_v1
def testInvalidUnit(self):
with self.cached_session():
with self.assertRaises(ValueError):
diff --git a/tensorflow/python/kernel_tests/summary_v1_image_op_test.py b/tensorflow/python/kernel_tests/summary_v1_image_op_test.py
index e1b24756f3f..56de2e933db 100644
--- a/tensorflow/python/kernel_tests/summary_v1_image_op_test.py
+++ b/tensorflow/python/kernel_tests/summary_v1_image_op_test.py
@@ -24,6 +24,7 @@ from six.moves import xrange # pylint: disable=redefined-builtin
from tensorflow.core.framework import summary_pb2
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import image_ops
import tensorflow.python.ops.nn_grad # pylint: disable=unused-import
from tensorflow.python.platform import test
@@ -49,6 +50,7 @@ class SummaryV1ImageOpTest(test.TestCase):
}""" % ((i,) + shape[1:]) for i in xrange(3))
self.assertProtoEquals(expected, image_summ)
+ @test_util.run_deprecated_v1
def testImageSummary(self):
for depth in (1, 3, 4):
for positive in False, True:
@@ -84,6 +86,7 @@ class SummaryV1ImageOpTest(test.TestCase):
# Check the rest of the proto
self._CheckProto(image_summ, shape)
+ @test_util.run_deprecated_v1
def testImageSummaryUint8(self):
np.random.seed(7)
for depth in (1, 3, 4):
diff --git a/tensorflow/python/kernel_tests/summary_v1_ops_test.py b/tensorflow/python/kernel_tests/summary_v1_ops_test.py
index 1206cb7013f..e070f5bf6f5 100644
--- a/tensorflow/python/kernel_tests/summary_v1_ops_test.py
+++ b/tensorflow/python/kernel_tests/summary_v1_ops_test.py
@@ -26,6 +26,7 @@ from __future__ import print_function
from tensorflow.core.framework import summary_pb2
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import logging_ops
from tensorflow.python.platform import test
from tensorflow.python.summary import summary
@@ -60,6 +61,7 @@ class SummaryV1OpsTest(test.TestCase):
value { tag: "c2" simple_value: 20.0 }
""", self._AsSummary(value))
+ @test_util.run_deprecated_v1
def testMergeSummary(self):
with self.cached_session() as sess:
const = constant_op.constant(10.0)
diff --git a/tensorflow/python/kernel_tests/template_test.py b/tensorflow/python/kernel_tests/template_test.py
index a187fa115ce..3b2a56bd1ff 100644
--- a/tensorflow/python/kernel_tests/template_test.py
+++ b/tensorflow/python/kernel_tests/template_test.py
@@ -72,6 +72,7 @@ def variable_scoped_function_with_local_variable():
class TemplateTest(test.TestCase):
+ @test_util.run_deprecated_v1
def test_end_to_end(self):
"""This test shows a very simple line model with test_loss.
@@ -172,6 +173,7 @@ class TemplateTest(test.TestCase):
self.assertEqual("s1/dummy:0", v1.name)
self.assertEqual("s1_1/dummy:0", v3.name)
+ @test_util.run_deprecated_v1
def test_same_unique_name_raise_error(self):
tmpl1 = template.make_template(
"_", variable_scoped_function, unique_name_="s1")
@@ -190,6 +192,7 @@ class TemplateTest(test.TestCase):
template.make_template(
"_", variable_scoped_function, unique_name_="s1")
+ @test_util.run_deprecated_v1
def test_unique_name_and_reuse(self):
tmpl1 = template.make_template(
"_", variable_scoped_function, unique_name_="s1")
@@ -260,6 +263,7 @@ class TemplateTest(test.TestCase):
self.assertEqual("s1/test/dummy:0", v1.name)
self.assertEqual("s1_1/test/dummy:0", v3.name)
+ @test_util.run_deprecated_v1
def test_enforces_no_extra_trainable_variables(self):
tmpl = template.make_template("s", function_with_create, trainable=True)
@@ -675,6 +679,7 @@ class TemplateTest(test.TestCase):
self.assertEqual(1, len(tb.variables))
# TODO(apassos) handle local variables in Eager
+ @test_util.run_deprecated_v1
def test_local_variables(self):
# Make sure trainable_variables are created.
with variable_scope.variable_scope("foo3"):
diff --git a/tensorflow/python/kernel_tests/tensor_array_ops_test.py b/tensorflow/python/kernel_tests/tensor_array_ops_test.py
index bb8645e2d54..76e90ffea39 100644
--- a/tensorflow/python/kernel_tests/tensor_array_ops_test.py
+++ b/tensorflow/python/kernel_tests/tensor_array_ops_test.py
@@ -165,6 +165,7 @@ class TensorArrayTest(test.TestCase):
[106.0, 107.0], [8.0, 9.0]]), c0)
@test_util.disable_control_flow_v2("b/118343594 (TensorArray.concat)")
+ @test_util.run_deprecated_v1
def testTensorArrayWriteConcat(self):
self._testTensorArrayWriteConcat(dtypes.float32)
self._testTensorArrayWriteConcat(dtypes.float64)
@@ -188,6 +189,7 @@ class TensorArrayTest(test.TestCase):
self.evaluate(ta.write(1, [[4.0, 5.0]]).concat()))
@test_util.disable_control_flow_v2("b/118890905")
+ @test_util.run_deprecated_v1
def testTensorArrayReadOrPackNotAllValuesAvailableFillsZeros(self):
self._testTensorArrayReadOrPackNotAllValuesAvailableFillsZeros()
@@ -204,6 +206,7 @@ class TensorArrayTest(test.TestCase):
self.evaluate(ta.write(1, [[4.0, 5.0]]).concat()))
@test_util.disable_control_flow_v2("b/118890905")
+ @test_util.run_deprecated_v1
def testTensorArrayReadOrPackNotAllValuesAvailableInferShapeFillsZeros(self):
self._testTensorArrayReadOrPackNotAllValuesAvailableInferShapeFillsZeros()
@@ -303,6 +306,7 @@ class TensorArrayTest(test.TestCase):
self.assertAllEqual(convert([[3.0, 301.0]]), d2)
@test_util.disable_control_flow_v2("b/118343962 (TensorArray.split)")
+ @test_util.run_deprecated_v1
def testTensorArraySplitRead(self):
self._testTensorArraySplitRead(dtypes.float32)
self._testTensorArraySplitRead(dtypes.float64)
@@ -313,6 +317,7 @@ class TensorArrayTest(test.TestCase):
self._testTensorArraySplitRead(dtypes.string)
@test_util.disable_control_flow_v2("v2 does not support TensorArray.grad.")
+ @test_util.run_deprecated_v1
def testSkipEagerTensorGradArrayWriteRead(self):
with self.session(use_gpu=True) as session:
ta = tensor_array_ops.TensorArray(
@@ -346,6 +351,7 @@ class TensorArrayTest(test.TestCase):
self.assertAllEqual([[2.0]], g_d1)
self.assertAllEqual(-2.0, g_d2)
+ @test_util.run_deprecated_v1
def testSkipEagerTensorArrayGradGrad(self):
if not tensor_array_ops.ENABLE_TENSOR_ARRAY_V2:
self.skipTest("Legacy TensorArray does not support double derivatives.")
@@ -366,6 +372,7 @@ class TensorArrayTest(test.TestCase):
self.assertAllEqual([2.0], session.run(g2))
@test_util.disable_control_flow_v2("v2 does not support TensorArray.grad.")
+ @test_util.run_deprecated_v1
def testSkipEagerTensorGradArrayDynamicWriteRead(self):
with self.session(use_gpu=True) as session:
ta = tensor_array_ops.TensorArray(
@@ -408,6 +415,7 @@ class TensorArrayTest(test.TestCase):
self.assertAllEqual(3, g_vs)
@test_util.disable_control_flow_v2("v2 does not support TensorArray.grad.")
+ @test_util.run_deprecated_v1
def testSkipEagerTensorGradAccessTwiceReceiveSameObject(self):
with self.session(use_gpu=True) as session:
ta = tensor_array_ops.TensorArray(
@@ -424,6 +432,7 @@ class TensorArrayTest(test.TestCase):
self.assertAllEqual(t_g_ta_0, t_g_ta_1)
self.assertAllEqual([[4.0, 5.0]], d_r1_0)
+ @test_util.run_deprecated_v1
def testTensorArrayWriteWrongIndexOrDataTypeFails(self):
with self.session(use_gpu=True):
ta = _make_ta(3, "foo", dtype=dtypes.float32)
@@ -457,6 +466,7 @@ class TensorArrayTest(test.TestCase):
with self.assertRaisesOpError(error_msg):
self.evaluate(ta.write(3, 3.0).flow)
+ @test_util.run_deprecated_v1
def testTensorArrayReadWrongIndexOrDataTypeFails(self):
with self.session(use_gpu=True):
ta = _make_ta(3, "foo", dtype=dtypes.float32)
@@ -491,6 +501,7 @@ class TensorArrayTest(test.TestCase):
self.evaluate(ta.read(3))
@test_util.disable_control_flow_v2("v2 allows multiple writes.")
+ @test_util.run_deprecated_v1
def testSkipEagerTensorArrayWriteMultipleFails(self):
with self.session(use_gpu=True):
ta = tensor_array_ops.TensorArray(
@@ -502,6 +513,7 @@ class TensorArrayTest(test.TestCase):
self.evaluate(ta.write(2, 3.0).write(2, 3.0).flow)
@test_util.disable_control_flow_v2("b/118343594 (TensorArray.concat)")
+ @test_util.run_deprecated_v1
def testTensorArrayConcatIncompatibleShapesFails(self):
with self.session(use_gpu=True):
ta = tensor_array_ops.TensorArray(
@@ -534,6 +546,7 @@ class TensorArrayTest(test.TestCase):
self.evaluate(w3.concat())
@test_util.disable_control_flow_v2("b/118343962 (TensorArray.split)")
+ @test_util.run_deprecated_v1
def testTensorArraySplitIncompatibleShapesFails(self):
with self.session(use_gpu=True):
in_eager_mode = context.executing_eagerly()
@@ -598,12 +611,14 @@ class TensorArrayTest(test.TestCase):
wb1_grad.flow.eval()
@test_util.disable_control_flow_v2("v2 does not support TensorArray.grad.")
+ @test_util.run_deprecated_v1
def testSkipEagerTensorArrayWriteGradientAddMultipleAdds(self):
for dtype in (dtypes.int32, dtypes.int64, dtypes.float32, dtypes.float64,
dtypes.complex64, dtypes.complex128):
self._testTensorArrayWriteGradientAddMultipleAdds(dtype)
@test_util.disable_control_flow_v2("Low level legacy TA op test.")
+ @test_util.run_deprecated_v1
def testSkipEagerTensorArrayGradWithShapeKnownElementShape(self):
with self.session(use_gpu=True) as sess:
ta = tensor_array_ops.TensorArray(
@@ -634,6 +649,7 @@ class TensorArrayTest(test.TestCase):
sess.run(read_value, feed_dict={value: fed_value}))
@test_util.disable_control_flow_v2("Low level legacy TA op test.")
+ @test_util.run_deprecated_v1
def testSkipEagerTensorArrayGradWithShapeUnknownElementShape(self):
with self.session(use_gpu=True) as sess:
ta = tensor_array_ops.TensorArray(
@@ -720,6 +736,7 @@ class TensorArrayTest(test.TestCase):
self.assertAllEqual(c([[3.0, 2.0]]), grad_vals[0])
self.assertAllEqual(c(-2.0), grad_vals[1])
+ @test_util.run_deprecated_v1
def testSkipEagerTensorArrayGradientWriteRead(self):
for dtype in (np.float32, np.float64, np.complex64, np.complex128):
self._testTensorArrayGradientWriteReadType(dtype)
@@ -757,10 +774,12 @@ class TensorArrayTest(test.TestCase):
self.assertAllEqual([4.0 + 40.0, 5.0 + 50.0], grad_vals[1])
@test_util.disable_control_flow_v2("b/118343594 (TensorArray.concat)")
+ @test_util.run_deprecated_v1
def testSkipEagerTensorArrayGradientWritePackConcatAndRead(self):
self._testTensorArrayGradientWritePackConcatAndRead()
@test_util.disable_control_flow_v2("v2 does not support clear_after_read.")
+ @test_util.run_deprecated_v1
def testTensorArrayReadTwice(self):
with self.session(use_gpu=True):
value = constant_op.constant([[1.0, -1.0], [10.0, -10.0]])
@@ -814,10 +833,12 @@ class TensorArrayTest(test.TestCase):
self.assertEqual(len(grad_vals), 1)
self.assertAllEqual([[2.0 - 1.5, 3.0 + 1.5], [4.0, 5.0]], grad_vals[0])
+ @test_util.run_deprecated_v1
def testSkipEagerTensorArrayGradientUnpackRead(self):
self._testTensorArrayGradientUnpackRead()
@test_util.disable_control_flow_v2("b/118343962 (TensorArray.split)")
+ @test_util.run_deprecated_v1
def testSkipEagerTensorArrayGradientSplitConcat(self):
with self.session(use_gpu=True) as session:
ta = tensor_array_ops.TensorArray(
@@ -863,6 +884,7 @@ class TensorArrayTest(test.TestCase):
self.assertEqual(len(grad_vals), 1)
self.assertAllEqual([[2.0, 3.0], [4.0, 5.0]], grad_vals[0])
+ @test_util.run_deprecated_v1
def testSkipEagerTensorArrayGradientDynamicUnpackRead(self):
self._testTensorArrayGradientDynamicUnpackRead()
@@ -1043,6 +1065,7 @@ class TensorArrayTest(test.TestCase):
grad = gradients_impl.gradients(loop(x), [x])[0]
self.assertAllClose(31.0, self.evaluate(grad))
+ @test_util.run_deprecated_v1
def testSkipEagerSumOfTwoReadVariablesWithoutRepeatGrad(self):
with self.session(use_gpu=True) as session:
a = array_ops.identity(
@@ -1078,6 +1101,7 @@ class TensorArrayTest(test.TestCase):
def _grad_source_for_name(self, name):
return tensor_array_grad._GetGradSource(constant_op.constant(0, name=name))
+ @test_util.run_deprecated_v1
def testSkipEagerGetGradSource_Invalid(self):
with self.assertRaises(ValueError):
self._grad_source_for_name("")
@@ -1086,6 +1110,7 @@ class TensorArrayTest(test.TestCase):
with self.assertRaises(ValueError):
self._grad_source_for_name("foo/bar")
+ @test_util.run_deprecated_v1
def testSkipEagerGetGradSource_NoEnclosingScope(self):
self.assertEqual("gradients:0", self._grad_source_for_name("gradients"))
self.assertEqual("gradients_0:0", self._grad_source_for_name("gradients_0"))
@@ -1097,6 +1122,7 @@ class TensorArrayTest(test.TestCase):
self.assertEqual("gradients_0",
self._grad_source_for_name("gradients_0/foo/bar"))
+ @test_util.run_deprecated_v1
def testSkipEagerGetGradSource_EnclosingScope(self):
self.assertEqual("foo/gradients:0",
self._grad_source_for_name("foo/gradients"))
@@ -1111,11 +1137,13 @@ class TensorArrayTest(test.TestCase):
self.assertEqual("foo/bar/gradients_0",
self._grad_source_for_name("foo/bar/gradients_0/baz"))
+ @test_util.run_deprecated_v1
def testSkipEagerGetGradSource_NestedUsesInnermost(self):
self.assertEqual(
"foo/gradients/bar/gradients_0",
self._grad_source_for_name("foo/gradients/bar/gradients_0/baz"))
+ @test_util.run_deprecated_v1
def testSkipEagerWriteShape(self):
with self.session(use_gpu=True):
ta = tensor_array_ops.TensorArray(
@@ -1141,6 +1169,7 @@ class TensorArrayTest(test.TestCase):
w0.write(0, c2)
@test_util.disable_control_flow_v2("b/118343962 (TensorArray.split)")
+ @test_util.run_deprecated_v1
def testSkipEagerPartlyUnknownShape(self):
with self.session(use_gpu=True):
ta = tensor_array_ops.TensorArray(
@@ -1212,10 +1241,12 @@ class TensorArrayTest(test.TestCase):
w1.write(4, c2)
@test_util.disable_control_flow_v2("b/117943489 (dynamic_size)")
+ @test_util.run_deprecated_v1
def testUnpackShape(self):
self._testUnpackShape()
@test_util.disable_control_flow_v2("b/118343962 (TensorArray.split)")
+ @test_util.run_deprecated_v1
def testSplitShape(self):
with self.session(use_gpu=True):
ta = tensor_array_ops.TensorArray(
@@ -1246,6 +1277,7 @@ class TensorArrayTest(test.TestCase):
tensor_shape.TensorShape(
ta1.handle.op.get_attr("element_shape")).ndims, None)
+ @test_util.run_deprecated_v1
def testSkipEagerWriteUnknownShape(self):
with self.session(use_gpu=True):
ta = tensor_array_ops.TensorArray(
@@ -1289,10 +1321,12 @@ class TensorArrayTest(test.TestCase):
self.assertAllEqual(np.array([1.0, 1.0, 1.0]), self.evaluate(grad)[0])
@test_util.disable_control_flow_v2("b/117943489")
+ @test_util.run_deprecated_v1
def testSkipEagerTensorArrayUnpackDynamic(self):
self._testTensorArrayUnpackDynamic()
@test_util.disable_control_flow_v2("b/118343594 (TensorArray.concat)")
+ @test_util.run_deprecated_v1
def testSkipEagerTensorArraySplitDynamic(self):
with self.session(use_gpu=True) as sess:
ta = tensor_array_ops.TensorArray(
@@ -1319,6 +1353,7 @@ class TensorArrayTest(test.TestCase):
.ENABLE_TENSOR_ARRAY_V2 else v1_msg):
ta.stack().eval()
+ @test_util.run_deprecated_v1
def testSkipEagerTensorArrayEvalEmpty(self):
self._testTensorArrayEvalEmpty()
@@ -1339,10 +1374,12 @@ class TensorArrayTest(test.TestCase):
self.assertAllEqual([0, 5], self.evaluate(concatenated).shape)
@test_util.disable_control_flow_v2("b/117943489")
+ @test_util.run_deprecated_v1
def testSkipEagerTensorArrayEvalEmptyWithDefault(self):
self._testTensorArrayEvalEmptyWithDefault()
@test_util.disable_control_flow_v2("b/117943489")
+ @test_util.run_deprecated_v1
def testSkipEagerTensorArrayScatterReadAndGradients(self):
with self.session(use_gpu=True) as session:
ta = tensor_array_ops.TensorArray(
@@ -1370,6 +1407,7 @@ class TensorArrayTest(test.TestCase):
self.assertAllEqual([[2.0, 3.0], [4.0, 5.0]], grad_vals[0])
@test_util.disable_control_flow_v2("b/117943286")
+ @test_util.run_deprecated_v1
def testTensorArrayWriteGatherAndGradients(self):
with self.session(use_gpu=True) as session:
ta = tensor_array_ops.TensorArray(
@@ -1407,6 +1445,7 @@ class TensorArrayTest(test.TestCase):
self.assertAllEqual(expected_grad, grad_vals[0])
@test_util.disable_control_flow_v2("colocate_with not supported in v2.")
+ @test_util.run_deprecated_v1
def testSkipEagerTensorArrayGetsDeviceFromFirstWrite(self):
with ops.device("/job:worker/task:0/cpu:0"):
# this initial device will be ignored.
@@ -1456,6 +1495,7 @@ class TensorArrayTest(test.TestCase):
[s for s in dev_stats[d] if "/TensorArray" in s.node_name])
@test_util.disable_control_flow_v2("colocate_with not supported in v2.")
+ @test_util.run_deprecated_v1
def testSkipEagerTensorArrayGetsDeviceFromFirstWriteInWhileLoop(self):
with ops.device("/job:worker/task:0/cpu:0"):
ta = tensor_array_ops.TensorArray(dtype=dtypes.float32, size=2)
@@ -1486,6 +1526,7 @@ class TensorArrayTest(test.TestCase):
[s for s in dev_stats[d] if "TensorArray" == s.node_name])
@test_util.disable_control_flow_v2("colocate_with not supported in v2.")
+ @test_util.run_deprecated_v1
def testSkipEagerTensorArrayDisabledColocateWithFirstWriteCall(self):
with ops.device("/job:worker/task:0/cpu:0"):
ta = tensor_array_ops.TensorArray(
@@ -1568,6 +1609,7 @@ class TensorArrayTest(test.TestCase):
self.assertEqual(size0_v, 2)
self.assertEqual(size1_v, 4)
+ @test_util.run_deprecated_v1
def testSkipEagerTensorArrayGradYsInCorrectScope(self):
n_time = 1
n_dim = 1
diff --git a/tensorflow/python/kernel_tests/topk_op_test.py b/tensorflow/python/kernel_tests/topk_op_test.py
index a72888c2567..5d46176bce8 100644
--- a/tensorflow/python/kernel_tests/topk_op_test.py
+++ b/tensorflow/python/kernel_tests/topk_op_test.py
@@ -27,6 +27,7 @@ from tensorflow.python.client import session
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradients_impl
from tensorflow.python.ops import nn_ops
@@ -181,6 +182,7 @@ class TopKTest(test.TestCase):
k = constant_op.constant(3)
self._validateTopK(inputs, k, [19, 18, 17], [11, 3, 7])
+ @test_util.run_deprecated_v1
def testKNegative(self):
inputs = [[0.1, 0.2], [0.3, 0.4]]
with self.session(use_gpu=True):
@@ -189,12 +191,14 @@ class TopKTest(test.TestCase):
with self.assertRaisesOpError("Need k >= 0, got -7"):
values.eval(feed_dict={k: -7})
+ @test_util.run_deprecated_v1
def testKTooLarge(self):
inputs = [[0.1, 0.2], [0.3, 0.4]]
with self.assertRaisesRegexp(ValueError,
r"must have last dimension >= k = 4"):
nn_ops.top_k(inputs, 4)
+ @test_util.run_deprecated_v1
def testTopKGradients(self):
with self.session(use_gpu=True) as sess:
inputs = array_ops.placeholder(dtypes.float32, shape=[2, 5])
diff --git a/tensorflow/python/kernel_tests/trace_op_test.py b/tensorflow/python/kernel_tests/trace_op_test.py
index f1abaefb66b..52640c02c22 100644
--- a/tensorflow/python/kernel_tests/trace_op_test.py
+++ b/tensorflow/python/kernel_tests/trace_op_test.py
@@ -19,6 +19,7 @@ from __future__ import print_function
import numpy as np
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import math_ops
from tensorflow.python.platform import test
@@ -34,6 +35,7 @@ class TraceTest(test.TestCase):
tf_ans = math_ops.trace(x).eval()
self.assertAllClose(tf_ans, np_ans)
+ @test_util.run_deprecated_v1
def testTrace(self):
for dtype in [np.int32, np.float32, np.float64]:
for shape in [[2, 2], [2, 3], [3, 2], [2, 3, 2], [2, 2, 2, 3]]:
diff --git a/tensorflow/python/kernel_tests/unicode_decode_op_test.py b/tensorflow/python/kernel_tests/unicode_decode_op_test.py
index c34145bff17..c165021eea3 100644
--- a/tensorflow/python/kernel_tests/unicode_decode_op_test.py
+++ b/tensorflow/python/kernel_tests/unicode_decode_op_test.py
@@ -21,6 +21,7 @@ from __future__ import print_function
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import errors_impl as errors
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import gen_string_ops
from tensorflow.python.platform import test
@@ -79,6 +80,7 @@ class UnicodeDecodeTest(test.TestCase):
self.assertAllEqual(self.evaluate(row_splits).tolist(), [0, 4])
self.assertAllEqual(self.evaluate(starts).tolist(), [0, 3, 6, 9])
+ @test_util.run_deprecated_v1
def testStrictError(self):
text = constant_op.constant([b"\xFEED"])
_, error, _ = gen_string_ops.unicode_decode_with_offsets(
@@ -97,6 +99,7 @@ class UnicodeDecodeTest(test.TestCase):
with self.test_session():
self.assertAllEqual(self.evaluate(utf8_text).tolist(), [65533])
+ @test_util.run_deprecated_v1
def testBadReplacementChar(self):
text = constant_op.constant([b"\xFE"])
_, error, _ = gen_string_ops.unicode_decode_with_offsets(
@@ -121,6 +124,7 @@ class UnicodeDecodeTest(test.TestCase):
codepoint("o")
])
+ @test_util.run_deprecated_v1
def testBadErrorPolicy(self):
text = constant_op.constant(["hippopotamus"])
diff --git a/tensorflow/python/kernel_tests/unicode_script_op_test.py b/tensorflow/python/kernel_tests/unicode_script_op_test.py
index 927e5459ed2..83cfeb20216 100644
--- a/tensorflow/python/kernel_tests/unicode_script_op_test.py
+++ b/tensorflow/python/kernel_tests/unicode_script_op_test.py
@@ -20,12 +20,14 @@ from __future__ import print_function
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import string_ops
from tensorflow.python.platform import test
class UnicodeScriptOpTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testValidScripts(self):
inputs = [
ord("a"),
@@ -45,6 +47,7 @@ class UnicodeScriptOpTest(test.TestCase):
0 # USCRIPT_COMMON (ZYYY)
])
+ @test_util.run_deprecated_v1
def testInvalidScript(self):
inputs = [-100, 0xffffff]
with self.cached_session():
diff --git a/tensorflow/python/kernel_tests/unicode_transcode_op_test.py b/tensorflow/python/kernel_tests/unicode_transcode_op_test.py
index 037ecd104b0..a3b4fd03474 100644
--- a/tensorflow/python/kernel_tests/unicode_transcode_op_test.py
+++ b/tensorflow/python/kernel_tests/unicode_transcode_op_test.py
@@ -22,6 +22,7 @@ from absl.testing import parameterized
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import string_ops
from tensorflow.python.platform import test
@@ -133,6 +134,7 @@ class UnicodeTranscodeOpTest(test.TestCase, parameterized.TestCase):
values = self.evaluate(outputs)
self.assertAllEqual(values, b"\x00 ")
+ @test_util.run_deprecated_v1
def test_transcode_bad_utf8_with_strict_errors(self):
bad_string = b"\x00\xff"
with self.cached_session() as sess:
@@ -145,6 +147,7 @@ class UnicodeTranscodeOpTest(test.TestCase, parameterized.TestCase):
"Invalid formatting on input string"):
self.evaluate(outputs)
+ @test_util.run_deprecated_v1
def test_transcode_bad_utf8_start_with_strict_errors(self):
bad_string = b"\xffabcd"
with self.cached_session() as sess:
@@ -317,12 +320,14 @@ class UnicodeTranscodeOpTest(test.TestCase, parameterized.TestCase):
(b"\xfe\xff\x00<\xfe\xff\x00>", "UTF-16", b"<\xef\xbb\xbf>"),
(b"\xff\xfe<\x00\xff\xfe>\x00", "UTF-16", b"<\xef\xbb\xbf>"),
)
+ @test_util.run_deprecated_v1
def test_bom_handling(self, string, input_encoding, expected):
with self.test_session():
output = string_ops.unicode_transcode(
string, input_encoding=input_encoding, output_encoding="UTF-8")
self.assertAllEqual(output.eval(), expected)
+ @test_util.run_deprecated_v1
def test_invalid_encoding_causes_errors(self):
strings = [[b"a", b"abc"], [b"ABC", b"DEF"]]
@@ -349,6 +354,7 @@ class UnicodeTranscodeOpTest(test.TestCase, parameterized.TestCase):
replace_control_characters=False)
self.evaluate(outputs)
+ @test_util.run_deprecated_v1
def test_invalid_error_policy_causes_errors(self):
strings = [[b"a", b"abc"], [b"ABC", b"DEF"]]
@@ -378,6 +384,7 @@ class UnicodeTranscodeOpTest(test.TestCase, parameterized.TestCase):
self.assertAllEqual([b"AbCdE", b"HiJkL"], transcoded)
+ @test_util.run_deprecated_v1
def test_cjk_encodings(self):
strings_ja = [
b"\x5c\x5c", # Yen sign
diff --git a/tensorflow/python/kernel_tests/unstack_op_test.py b/tensorflow/python/kernel_tests/unstack_op_test.py
index d314e1eaf93..f5ba475e7ad 100644
--- a/tensorflow/python/kernel_tests/unstack_op_test.py
+++ b/tensorflow/python/kernel_tests/unstack_op_test.py
@@ -74,6 +74,7 @@ class UnstackOpTest(test.TestCase):
cs = [self.evaluate(c) for c in cs]
self.assertAllEqual(cs, data)
+ @test_util.run_deprecated_v1
def testGradientsAxis0(self):
for shape in (2,), (3,), (2, 3), (3, 2), (4, 3, 2):
data = np.random.randn(*shape)
@@ -86,6 +87,7 @@ class UnstackOpTest(test.TestCase):
shapes[i])
self.assertLess(err, 1e-6)
+ @test_util.run_deprecated_v1
def testGradientsAxis1(self):
for shape in (2, 3), (3, 2), (4, 3, 2):
data = np.random.randn(*shape)
@@ -99,6 +101,7 @@ class UnstackOpTest(test.TestCase):
out_shape)
self.assertLess(err, 1e-6)
+ @test_util.run_deprecated_v1
def testInferNum(self):
with self.cached_session():
for shape in (2,), (3,), (2, 3), (3, 2), (4, 3, 2):
@@ -107,16 +110,19 @@ class UnstackOpTest(test.TestCase):
self.assertEqual(type(cs), list)
self.assertEqual(len(cs), shape[0])
+ @test_util.run_deprecated_v1
def testCannotInferNumFromUnknownShape(self):
x = array_ops.placeholder(np.float32)
with self.assertRaisesRegexp(ValueError,
r'Cannot infer num from shape <unknown>'):
array_ops.unstack(x)
+ @test_util.run_deprecated_v1
def testUnknownShapeOkWithNum(self):
x = array_ops.placeholder(np.float32)
array_ops.unstack(x, num=2)
+ @test_util.run_deprecated_v1
def testCannotInferNumFromNoneShape(self):
x = array_ops.placeholder(np.float32, shape=(None,))
with self.assertRaisesRegexp(ValueError,
diff --git a/tensorflow/python/kernel_tests/variable_ops_test.py b/tensorflow/python/kernel_tests/variable_ops_test.py
index c63d7f89c73..0f3e2619925 100644
--- a/tensorflow/python/kernel_tests/variable_ops_test.py
+++ b/tensorflow/python/kernel_tests/variable_ops_test.py
@@ -60,15 +60,18 @@ class VariableOpTest(test.TestCase):
# that Variable and Assign have GPU implementations for matching tf.
self.assertAllEqual(x, self._initFetch(x, tftype, use_gpu=True))
+ @test_util.run_deprecated_v1
def testBasic(self):
self._testTypes(np.arange(0, 20).reshape([4, 5]))
+ @test_util.run_deprecated_v1
def testset_shape(self):
p = state_ops.variable_op([1, 2], dtypes.float32)
self.assertEqual([1, 2], p.get_shape())
p = state_ops.variable_op([1, 2], dtypes.float32, set_shape=False)
self.assertEqual(tensor_shape.unknown_shape(), p.get_shape())
+ @test_util.run_deprecated_v1
def testAssign(self):
value = np.array([[42.0, 43.0]])
var = state_ops.variable_op(value.shape, dtypes.float32)
@@ -76,6 +79,7 @@ class VariableOpTest(test.TestCase):
assigned = state_ops.assign(var, value)
self.assertShapeEqual(value, assigned)
+ @test_util.run_deprecated_v1
def testAssignNoValidateShape(self):
value = np.array([[42.0, 43.0]])
var = state_ops.variable_op(value.shape, dtypes.float32)
@@ -83,6 +87,7 @@ class VariableOpTest(test.TestCase):
assigned = state_ops.assign(var, value, validate_shape=False)
self.assertShapeEqual(value, assigned)
+ @test_util.run_deprecated_v1
def testAssignNoVarShape(self):
value = np.array([[42.0, 43.0]])
var = state_ops.variable_op(value.shape, dtypes.float32, set_shape=False)
@@ -90,6 +95,7 @@ class VariableOpTest(test.TestCase):
assigned = state_ops.assign(var, value)
self.assertShapeEqual(value, assigned)
+ @test_util.run_deprecated_v1
def testAssignNoVarShapeNoValidateShape(self):
value = np.array([[42.0, 43.0]])
var = state_ops.variable_op(value.shape, dtypes.float32, set_shape=False)
@@ -102,6 +108,7 @@ class VariableOpTest(test.TestCase):
self.assertEqual(tensor_shape.unknown_shape(), tensor.get_shape())
return tensor
+ @test_util.run_deprecated_v1
def testAssignNoValueShape(self):
value = self._NewShapelessTensor()
shape = [1, 2]
@@ -110,6 +117,7 @@ class VariableOpTest(test.TestCase):
self.assertEqual(shape, var.get_shape())
self.assertEqual(shape, assigned.get_shape())
+ @test_util.run_deprecated_v1
def testAssignNoValueShapeNoValidateShape(self):
value = self._NewShapelessTensor()
shape = [1, 2]
@@ -118,6 +126,7 @@ class VariableOpTest(test.TestCase):
assigned = state_ops.assign(var, value, validate_shape=False)
self.assertEqual(tensor_shape.unknown_shape(), assigned.get_shape())
+ @test_util.run_deprecated_v1
def testAssignNoShape(self):
with self.cached_session():
value = self._NewShapelessTensor()
@@ -126,6 +135,7 @@ class VariableOpTest(test.TestCase):
self.assertEqual(tensor_shape.unknown_shape(),
state_ops.assign(var, value).get_shape())
+ @test_util.run_deprecated_v1
def testAssignNoShapeNoValidateShape(self):
with self.cached_session():
value = self._NewShapelessTensor()
@@ -136,6 +146,7 @@ class VariableOpTest(test.TestCase):
state_ops.assign(
var, value, validate_shape=False).get_shape())
+ @test_util.run_deprecated_v1
def testAssignUpdate(self):
var = state_ops.variable_op([1, 2], dtypes.float32)
added = state_ops.assign_add(var, [[2.0, 3.0]])
@@ -143,6 +154,7 @@ class VariableOpTest(test.TestCase):
subbed = state_ops.assign_sub(var, [[12.0, 13.0]])
self.assertEqual([1, 2], subbed.get_shape())
+ @test_util.run_deprecated_v1
def testAssignUpdateNoVarShape(self):
var = state_ops.variable_op([1, 2], dtypes.float32, set_shape=False)
added = state_ops.assign_add(var, [[2.0, 3.0]])
@@ -150,6 +162,7 @@ class VariableOpTest(test.TestCase):
subbed = state_ops.assign_sub(var, [[12.0, 13.0]])
self.assertEqual([1, 2], subbed.get_shape())
+ @test_util.run_deprecated_v1
def testAssignUpdateNoValueShape(self):
var = state_ops.variable_op([1, 2], dtypes.float32)
added = state_ops.assign_add(var, self._NewShapelessTensor())
@@ -157,6 +170,7 @@ class VariableOpTest(test.TestCase):
subbed = state_ops.assign_sub(var, self._NewShapelessTensor())
self.assertEqual([1, 2], subbed.get_shape())
+ @test_util.run_deprecated_v1
def testAssignUpdateNoShape(self):
var = state_ops.variable_op([1, 2], dtypes.float32, set_shape=False)
added = state_ops.assign_add(var, self._NewShapelessTensor())
@@ -164,6 +178,7 @@ class VariableOpTest(test.TestCase):
subbed = state_ops.assign_sub(var, self._NewShapelessTensor())
self.assertEqual(tensor_shape.unknown_shape(), subbed.get_shape())
+ @test_util.run_deprecated_v1
def testTemporaryVariable(self):
with test_util.use_gpu():
var = gen_state_ops.temporary_variable(
@@ -173,6 +188,7 @@ class VariableOpTest(test.TestCase):
final = gen_state_ops.destroy_temporary_variable(var, var_name="foo")
self.assertAllClose([[10.0, 12.0]], self.evaluate(final))
+ @test_util.run_deprecated_v1
def testDestroyNonexistentTemporaryVariable(self):
with test_util.use_gpu():
var = gen_state_ops.temporary_variable([1, 2], dtypes.float32)
@@ -180,6 +196,7 @@ class VariableOpTest(test.TestCase):
with self.assertRaises(errors.NotFoundError):
self.evaluate(final)
+ @test_util.run_deprecated_v1
def testDuplicateTemporaryVariable(self):
with test_util.use_gpu():
var1 = gen_state_ops.temporary_variable(
@@ -192,6 +209,7 @@ class VariableOpTest(test.TestCase):
with self.assertRaises(errors.AlreadyExistsError):
self.evaluate(final)
+ @test_util.run_deprecated_v1
def testDestroyTemporaryVariableTwice(self):
with test_util.use_gpu():
var = gen_state_ops.temporary_variable([1, 2], dtypes.float32)
@@ -201,6 +219,7 @@ class VariableOpTest(test.TestCase):
with self.assertRaises(errors.NotFoundError):
self.evaluate(final)
+ @test_util.run_deprecated_v1
def testTemporaryVariableNoLeak(self):
with test_util.use_gpu():
var = gen_state_ops.temporary_variable(
@@ -208,6 +227,7 @@ class VariableOpTest(test.TestCase):
final = array_ops.identity(var)
self.evaluate(final)
+ @test_util.run_deprecated_v1
def testTwoTemporaryVariablesNoLeaks(self):
with test_util.use_gpu():
var1 = gen_state_ops.temporary_variable(
@@ -217,6 +237,7 @@ class VariableOpTest(test.TestCase):
final = var1 + var2
self.evaluate(final)
+ @test_util.run_deprecated_v1
def testAssignDependencyAcrossDevices(self):
with test_util.use_gpu():
# The variable and an op to increment it are on the GPU.
@@ -232,6 +253,7 @@ class VariableOpTest(test.TestCase):
result = math_ops.multiply(var, var)
self.assertAllClose([4.0], self.evaluate(result))
+ @test_util.run_deprecated_v1
def testIsVariableInitialized(self):
for use_gpu in [True, False]:
with self.test_session(use_gpu=use_gpu):
diff --git a/tensorflow/python/kernel_tests/variable_scope_test.py b/tensorflow/python/kernel_tests/variable_scope_test.py
index 3720f736ac4..44d4bd5e30f 100644
--- a/tensorflow/python/kernel_tests/variable_scope_test.py
+++ b/tensorflow/python/kernel_tests/variable_scope_test.py
@@ -152,6 +152,7 @@ class VariableScopeTest(test.TestCase):
# TypeError: Fetch argument <tf.Variable 'string:0' shape=() dtype=string>
# has invalid type <class '...ResourceVariable'>, must be a string or Tensor.
# (Can not convert a ResourceVariable into a Tensor or Operation.)
+ @test_util.run_deprecated_v1
def testStringDefaultInitializer(self):
with self.cached_session():
v = variable_scope.get_variable("string", shape=[], dtype=dtypes.string)
@@ -310,6 +311,7 @@ class VariableScopeTest(test.TestCase):
# TODO(mihaimaruseac): Not converted to use wrap_function because of
# InvalidArgumentError: /job:moo/replica:0/task:0/device:CPU:0 unknown device.
+ @test_util.run_deprecated_v1
def testVarScopeCachingDevice(self):
with self.cached_session():
caching_device = "/job:moo"
@@ -424,6 +426,7 @@ class VariableScopeTest(test.TestCase):
# invalid type <class '...ops.resource_variable_ops.ResourceVariable'>, must
# be a string or Tensor. (Can not convert a ResourceVariable into a Tensor or
# Operation.)
+ @test_util.run_deprecated_v1
def testControlDeps(self):
with self.cached_session() as sess:
v0 = variable_scope.get_variable(
@@ -450,6 +453,7 @@ class VariableScopeTest(test.TestCase):
# TODO(mihaimaruseac): Not converted to use wrap_function because of
# AssertionError: True is not false (last assertFalse)
+ @test_util.run_deprecated_v1
def testEnableResourceVariables(self):
old = variable_scope._DEFAULT_USE_RESOURCE
try:
@@ -464,6 +468,7 @@ class VariableScopeTest(test.TestCase):
# TODO(mihaimaruseac): Not converted to use wrap_function because of
# TypeError: Fetch argument None has invalid type <type 'NoneType'>
+ @test_util.run_deprecated_v1
def testControlFlow(self):
with self.cached_session() as sess:
v0 = variable_scope.get_variable(
@@ -1148,6 +1153,7 @@ class VariableScopeTest(test.TestCase):
# TODO(mihaimaruseac): Not converted to use wrap_function because of
# obtaining different results in the eager case compared to the graph one
+ @test_util.run_deprecated_v1
def testGetCollection(self):
with self.cached_session():
_ = variable_scope.get_variable("testGetCollection_a", [])
@@ -1204,6 +1210,7 @@ class VariableScopeTest(test.TestCase):
# TODO(mihaimaruseac): Not converted to use wrap_function because of
# obtaining different results in the eager case compared to the graph one
+ @test_util.run_deprecated_v1
def testGetTrainableVariablesWithGetVariable(self):
with self.cached_session():
_ = variable_scope.get_variable("testGetTrainableVariables_a", [])
@@ -1242,6 +1249,7 @@ class VariableScopeTest(test.TestCase):
# TODO(mihaimaruseac): Not converted to use wrap_function because of
# obtaining different results in the eager case compared to the graph one
+ @test_util.run_deprecated_v1
def testGetTrainableVariablesWithVariable(self):
with self.cached_session():
_ = variable_scope.variable(1.0, name="testGetTrainableVariables_a")
@@ -1283,6 +1291,7 @@ class VariableScopeTest(test.TestCase):
# TODO(mihaimaruseac): Not converted to use wrap_function because of
# obtaining different results in the eager case compared to the graph one
+ @test_util.run_deprecated_v1
def testGetGlobalVariables(self):
with self.cached_session():
_ = variable_scope.get_variable("testGetGlobalVariables_a", [])
@@ -1295,6 +1304,7 @@ class VariableScopeTest(test.TestCase):
# TODO(mihaimaruseac): Not converted to use wrap_function because of
# obtaining different results in the eager case compared to the graph one
+ @test_util.run_deprecated_v1
def testGetLocalVariables(self):
with self.cached_session():
_ = variable_scope.get_variable(
@@ -1370,6 +1380,7 @@ class VariableScopeWithPartitioningTest(test.TestCase):
# TODO(mihaimaruseac): Not converted to use wrap_function because of
# obtaining different results in the eager case compared to the graph one
+ @test_util.run_deprecated_v1
def testResultNameMatchesRequested(self):
with variable_scope.variable_scope(
"scope0", partitioner=axis0_into2_partitioner):
@@ -1444,6 +1455,7 @@ class VariableScopeWithPartitioningTest(test.TestCase):
# TODO(mihaimaruseac): Not converted to use wrap_function because of
# obtaining different results in the eager case compared to the graph one
+ @test_util.run_deprecated_v1
def testScalarIgnoresPartitioner(self):
with variable_scope.variable_scope(
"scope0", partitioner=axis0_into2_partitioner):
@@ -1583,6 +1595,7 @@ class VariableScopeWithCustomGetterTest(test.TestCase):
# dtype=float32> cannot be interpreted as a Tensor. (Tensor
# Tensor("custom_getter/add:0", shape=(1, 2, 3), dtype=float32) is not an
# element of this graph.)
+ @test_util.run_deprecated_v1
def testGetterThatCreatesTwoVariablesAndSumsThem(self):
def custom_getter(getter, name, *args, **kwargs):
@@ -1610,6 +1623,7 @@ class VariableScopeWithCustomGetterTest(test.TestCase):
# dtype=float32> cannot be interpreted as a Tensor. (Tensor
# Tensor("sum_getter_2/add:0", shape=(1, 2, 3), dtype=float32) is not an
# element of this graph.)
+ @test_util.run_deprecated_v1
def testNestedCustomGetters(self):
def sum_getter(getter, name, *args, **kwargs):
diff --git a/tensorflow/python/kernel_tests/variables_test.py b/tensorflow/python/kernel_tests/variables_test.py
index 14ec46dcb22..08d885e8a87 100644
--- a/tensorflow/python/kernel_tests/variables_test.py
+++ b/tensorflow/python/kernel_tests/variables_test.py
@@ -28,6 +28,7 @@ from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors_impl
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import control_flow_ops
from tensorflow.python.ops import gen_state_ops
@@ -42,6 +43,7 @@ from tensorflow.python.util import compat
class VariablesTestCase(test.TestCase):
+ @test_util.run_deprecated_v1
def testInitialization(self):
with self.cached_session():
var0 = variables.VariableV1(0.0)
@@ -69,6 +71,7 @@ class VariablesTestCase(test.TestCase):
self.assertAllClose(0.0, self.evaluate(var0))
self.assertAllClose(1.1, self.evaluate(var1))
+ @test_util.run_deprecated_v1
def testInitializationOrder(self):
with self.cached_session():
rnd = variables.Variable(random_ops.random_uniform([3, 6]), name="rnd")
@@ -107,6 +110,7 @@ class VariablesTestCase(test.TestCase):
for _ in variables.Variable([0.0, 1.0]):
pass
+ @test_util.run_deprecated_v1
def testAssignments(self):
with self.cached_session():
var = variables.Variable(0.0)
@@ -125,6 +129,7 @@ class VariablesTestCase(test.TestCase):
self.assertAllClose(4.0, self.evaluate(four))
self.assertAllClose(4.0, self.evaluate(var))
+ @test_util.run_deprecated_v1
def testResourceAssignments(self):
with self.session(use_gpu=True):
var = resource_variable_ops.ResourceVariable(0.0)
@@ -181,12 +186,15 @@ class VariablesTestCase(test.TestCase):
self.evaluate(count_up_to)
self.assertEqual(3, self.evaluate(var))
+ @test_util.run_deprecated_v1
def testCountUpToInt32(self):
self._countUpToTest(dtypes.int32)
+ @test_util.run_deprecated_v1
def testCountUpToInt64(self):
self._countUpToTest(dtypes.int64)
+ @test_util.run_deprecated_v1
def testControlDepsNone(self):
with self.cached_session():
c = constant_op.constant(1.0)
@@ -200,6 +208,7 @@ class VariablesTestCase(test.TestCase):
self.assertEqual([], var_x.value().op.control_inputs)
self.assertEqual([], var_x._ref().op.control_inputs) # pylint: disable=protected-access
+ @test_util.run_deprecated_v1
def testControlFlow(self):
with self.cached_session() as sess:
v0 = variables.Variable(0, name="v0")
@@ -236,6 +245,7 @@ class VariablesTestCase(test.TestCase):
self.evaluate(v0.initializer)
self.evaluate(add)
+ @test_util.run_deprecated_v1
def testControlFlowInitialization(self):
"""Expects an error if an initializer is in a control-flow scope."""
def cond(i, _):
@@ -249,6 +259,7 @@ class VariablesTestCase(test.TestCase):
with self.assertRaisesRegexp(ValueError, "inside a control-flow"):
control_flow_ops.while_loop(cond, body, [0, 0])
+ @test_util.run_deprecated_v1
def testUseVariableAsTensor(self):
with self.cached_session():
var_x = variables.Variable(2.0)
@@ -258,6 +269,7 @@ class VariablesTestCase(test.TestCase):
self.assertAllClose(3.0, self.evaluate(var_y))
self.assertAllClose(5.0, math_ops.add(var_x, var_y).eval())
+ @test_util.run_deprecated_v1
def testZeroSizeVarSameAsConst(self):
with self.cached_session():
zero_size_var = variables.Variable(array_ops.zeros([0, 2]))
@@ -270,6 +282,7 @@ class VariablesTestCase(test.TestCase):
self.assertAllClose(const_mul.eval(), variable_output)
self.assertAllClose([[0., 0.], [0., 0.]], variable_output)
+ @test_util.run_deprecated_v1
def testCachingDevice(self):
with self.cached_session():
var = variables.Variable(2.0)
@@ -280,6 +293,7 @@ class VariablesTestCase(test.TestCase):
self.assertFalse(var_cached.device.startswith("/job:foo"))
self.assertTrue(var_cached.value().device.startswith("/job:foo"))
+ @test_util.run_deprecated_v1
def testCollections(self):
with self.cached_session():
var_x = variables.VariableV1(2.0)
@@ -295,6 +309,7 @@ class VariablesTestCase(test.TestCase):
variables.global_variables())
self.assertEqual([var_x, var_z, var_t], variables.trainable_variables())
+ @test_util.run_deprecated_v1
def testCollectionsWithScope(self):
with self.cached_session():
with ops.name_scope("scope_1"):
@@ -316,6 +331,7 @@ class VariablesTestCase(test.TestCase):
getattr(variables.Variable.__add__, attr),
getattr(ops.Tensor.__add__, attr))
+ @test_util.run_deprecated_v1
def testOperators(self):
with self.cached_session():
var_f = variables.Variable([2.0])
@@ -389,12 +405,14 @@ class VariablesTestCase(test.TestCase):
self.assertAllClose([[80.0]], self.evaluate(matmul))
self.assertAllClose([[20.0, 30.0], [40.0, 60.0]], self.evaluate(rmatmul))
+ @test_util.run_deprecated_v1
def testSession(self):
with self.cached_session() as sess:
var = variables.Variable([1, 12])
variables.global_variables_initializer().run()
self.assertAllClose([1, 12], self.evaluate(var))
+ @test_util.run_deprecated_v1
def testColocation(self):
with ops.device("/job:ps"):
var = variables.VariableV1(0, name="v")
@@ -403,6 +421,7 @@ class VariablesTestCase(test.TestCase):
self.assertDeviceEqual("/job:ps", assign_op.device)
self.assertEqual([b"loc:@v"], assign_op.op.colocation_groups())
+ @test_util.run_deprecated_v1
def testInitializerFunction(self):
value = [[-42], [133.7]]
shape = [2, 1]
@@ -440,6 +459,7 @@ class VariablesTestCase(test.TestCase):
lambda: constant_op.constant(1.),
constraint=constraint)
+ @test_util.run_deprecated_v1
def testNoRefDataRace(self):
with self.cached_session():
a = variables.Variable([1, 2, 3], dtype=dtypes.float32)
@@ -450,6 +470,7 @@ class VariablesTestCase(test.TestCase):
self.assertAllEqual(b.eval(), [3, 4, 5])
self.assertAllEqual(c.eval(), [5, 6, 7])
+ @test_util.run_deprecated_v1
def testInitializerFunctionDevicePlacement(self):
with self.cached_session():
initializer = lambda: constant_op.constant(42.0)
@@ -468,6 +489,7 @@ class VariablesTestCase(test.TestCase):
for i in v2.initializer.inputs:
self.assertEqual(expected_group_v2, i.op.colocation_groups())
+ @test_util.run_deprecated_v1
def testVariableDefInitializedInstances(self):
with ops.Graph().as_default(), self.cached_session() as sess:
v_def = variables.Variable(
@@ -511,6 +533,7 @@ class VariablesTestCase(test.TestCase):
variables.Variable(variable_def=trainable_variable.to_proto())
.trainable)
+ @test_util.run_deprecated_v1
def testLoad(self):
with self.cached_session():
var = variables.Variable(np.zeros((5, 5), np.float32))
@@ -519,6 +542,7 @@ class VariablesTestCase(test.TestCase):
self.assertAllClose(np.ones((5, 5), np.float32), self.evaluate(var))
+ @test_util.run_deprecated_v1
def testRepr(self):
var = variables.VariableV1(np.zeros((5, 5), np.float32), name="noop")
self.assertEqual(
@@ -552,6 +576,7 @@ class IsInitializedTest(test.TestCase):
variables.global_variables_initializer().run()
self.assertEqual(0, self.evaluate(uninited).size)
+ @test_util.run_deprecated_v1
def testVariableList(self):
with ops.Graph().as_default(), self.cached_session() as sess:
v = variables.VariableV1([1, 2], name="v")
@@ -589,6 +614,7 @@ class ObsoleteIsInitializedTest(test.TestCase):
with ops.Graph().as_default():
self.assertEqual(None, variables.assert_variables_initialized())
+ @test_util.run_deprecated_v1
def testVariables(self):
with ops.Graph().as_default(), self.cached_session() as sess:
v = variables.VariableV1([1, 2])
@@ -600,6 +626,7 @@ class ObsoleteIsInitializedTest(test.TestCase):
variables.global_variables_initializer().run()
self.evaluate(inited)
+ @test_util.run_deprecated_v1
def testVariableList(self):
with ops.Graph().as_default(), self.cached_session() as sess:
v = variables.VariableV1([1, 2])
diff --git a/tensorflow/python/kernel_tests/weights_broadcast_test.py b/tensorflow/python/kernel_tests/weights_broadcast_test.py
index c476004b893..677d8f2f22f 100644
--- a/tensorflow/python/kernel_tests/weights_broadcast_test.py
+++ b/tensorflow/python/kernel_tests/weights_broadcast_test.py
@@ -23,6 +23,7 @@ import numpy as np
from tensorflow.python.framework import dtypes as dtypes_lib
from tensorflow.python.framework import errors_impl
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import weights_broadcast_ops
from tensorflow.python.platform import test
@@ -51,40 +52,48 @@ class AssertBroadcastableTest(test.TestCase):
values_placeholder: values,
})
+ @test_util.run_deprecated_v1
def testScalar(self):
self._test_valid(weights=5, values=_test_values((3, 2, 4)))
+ @test_util.run_deprecated_v1
def test1x1x1(self):
self._test_valid(
weights=np.asarray((5,)).reshape((1, 1, 1)),
values=_test_values((3, 2, 4)))
+ @test_util.run_deprecated_v1
def test1x1xN(self):
self._test_valid(
weights=np.asarray((5, 7, 11, 3)).reshape((1, 1, 4)),
values=_test_values((3, 2, 4)))
+ @test_util.run_deprecated_v1
def test1xNx1(self):
self._test_valid(
weights=np.asarray((5, 11)).reshape((1, 2, 1)),
values=_test_values((3, 2, 4)))
+ @test_util.run_deprecated_v1
def test1xNxN(self):
self._test_valid(
weights=np.asarray((5, 7, 11, 3, 2, 13, 7, 5)).reshape((1, 2, 4)),
values=_test_values((3, 2, 4)))
+ @test_util.run_deprecated_v1
def testNx1x1(self):
self._test_valid(
weights=np.asarray((5, 7, 11)).reshape((3, 1, 1)),
values=_test_values((3, 2, 4)))
+ @test_util.run_deprecated_v1
def testNx1xN(self):
self._test_valid(
weights=np.asarray((
5, 7, 11, 3, 2, 12, 7, 5, 2, 17, 11, 3)).reshape((3, 1, 4)),
values=_test_values((3, 2, 4)))
+ @test_util.run_deprecated_v1
def testNxNxN(self):
self._test_valid(
weights=np.asarray((
@@ -107,29 +116,35 @@ class AssertBroadcastableTest(test.TestCase):
values_placeholder: values,
})
+ @test_util.run_deprecated_v1
def testInvalid1(self):
self._test_invalid(weights=np.asarray((5,)), values=_test_values((3, 2, 4)))
+ @test_util.run_deprecated_v1
def testInvalid1x1(self):
self._test_invalid(
weights=np.asarray((5,)).reshape((1, 1)),
values=_test_values((3, 2, 4)))
+ @test_util.run_deprecated_v1
def testInvalidPrefixMatch(self):
self._test_invalid(
weights=np.asarray((5, 7, 11, 3, 2, 12)).reshape((3, 2)),
values=_test_values((3, 2, 4)))
+ @test_util.run_deprecated_v1
def testInvalidSuffixMatch(self):
self._test_invalid(
weights=np.asarray((5, 7, 11, 3, 2, 12, 7, 5)).reshape((2, 4)),
values=_test_values((3, 2, 4)))
+ @test_util.run_deprecated_v1
def testInvalidOnesExtraDim(self):
self._test_invalid(
weights=np.asarray((5,)).reshape((1, 1, 1, 1)),
values=_test_values((3, 2, 4)))
+ @test_util.run_deprecated_v1
def testInvalidPrefixMatchExtraDim(self):
self._test_invalid(
weights=np.asarray((
@@ -137,6 +152,7 @@ class AssertBroadcastableTest(test.TestCase):
2, 17, 11, 3, 5, 7, 11, 3, 2, 12, 7, 5)).reshape((3, 2, 4, 1)),
values=_test_values((3, 2, 4)))
+ @test_util.run_deprecated_v1
def testInvalidSuffixMatchExtraDim(self):
self._test_invalid(
weights=np.asarray((
@@ -164,18 +180,21 @@ class BroadcastWeightsTest(test.TestCase):
values_placeholder: values,
}))
+ @test_util.run_deprecated_v1
def testScalar(self):
self._test_valid(
weights=5,
values=_test_values((3, 2, 4)),
expected=5 * np.ones((3, 2, 4)))
+ @test_util.run_deprecated_v1
def test1x1x1(self):
self._test_valid(
weights=np.asarray((5,)).reshape((1, 1, 1)),
values=_test_values((3, 2, 4)),
expected=5 * np.ones((3, 2, 4)))
+ @test_util.run_deprecated_v1
def test1x1xN(self):
weights = np.asarray((5, 7, 11, 3)).reshape((1, 1, 4))
self._test_valid(
@@ -183,6 +202,7 @@ class BroadcastWeightsTest(test.TestCase):
values=_test_values((3, 2, 4)),
expected=np.tile(weights, reps=(3, 2, 1)))
+ @test_util.run_deprecated_v1
def test1xNx1(self):
weights = np.asarray((5, 11)).reshape((1, 2, 1))
self._test_valid(
@@ -190,6 +210,7 @@ class BroadcastWeightsTest(test.TestCase):
values=_test_values((3, 2, 4)),
expected=np.tile(weights, reps=(3, 1, 4)))
+ @test_util.run_deprecated_v1
def test1xNxN(self):
weights = np.asarray((5, 7, 11, 3, 2, 13, 7, 5)).reshape((1, 2, 4))
self._test_valid(
@@ -197,6 +218,7 @@ class BroadcastWeightsTest(test.TestCase):
values=_test_values((3, 2, 4)),
expected=np.tile(weights, reps=(3, 1, 1)))
+ @test_util.run_deprecated_v1
def testNx1x1(self):
weights = np.asarray((5, 7, 11)).reshape((3, 1, 1))
self._test_valid(
@@ -204,6 +226,7 @@ class BroadcastWeightsTest(test.TestCase):
values=_test_values((3, 2, 4)),
expected=np.tile(weights, reps=(1, 2, 4)))
+ @test_util.run_deprecated_v1
def testNx1xN(self):
weights = np.asarray((
5, 7, 11, 3, 2, 12, 7, 5, 2, 17, 11, 3)).reshape((3, 1, 4))
@@ -212,6 +235,7 @@ class BroadcastWeightsTest(test.TestCase):
values=_test_values((3, 2, 4)),
expected=np.tile(weights, reps=(1, 2, 1)))
+ @test_util.run_deprecated_v1
def testNxNxN(self):
weights = np.asarray((
5, 7, 11, 3, 2, 12, 7, 5, 2, 17, 11, 3,
@@ -234,29 +258,35 @@ class BroadcastWeightsTest(test.TestCase):
values_placeholder: values,
})
+ @test_util.run_deprecated_v1
def testInvalid1(self):
self._test_invalid(weights=np.asarray((5,)), values=_test_values((3, 2, 4)))
+ @test_util.run_deprecated_v1
def testInvalid1x1(self):
self._test_invalid(
weights=np.asarray((5,)).reshape((1, 1)),
values=_test_values((3, 2, 4)))
+ @test_util.run_deprecated_v1
def testInvalidPrefixMatch(self):
self._test_invalid(
weights=np.asarray((5, 7, 11, 3, 2, 12)).reshape((3, 2)),
values=_test_values((3, 2, 4)))
+ @test_util.run_deprecated_v1
def testInvalidSuffixMatch(self):
self._test_invalid(
weights=np.asarray((5, 7, 11, 3, 2, 12, 7, 5)).reshape((2, 4)),
values=_test_values((3, 2, 4)))
+ @test_util.run_deprecated_v1
def testInvalidOnesExtraDim(self):
self._test_invalid(
weights=np.asarray((5,)).reshape((1, 1, 1, 1)),
values=_test_values((3, 2, 4)))
+ @test_util.run_deprecated_v1
def testInvalidPrefixMatchExtraDim(self):
self._test_invalid(
weights=np.asarray((
@@ -264,6 +294,7 @@ class BroadcastWeightsTest(test.TestCase):
2, 17, 11, 3, 5, 7, 11, 3, 2, 12, 7, 5)).reshape((3, 2, 4, 1)),
values=_test_values((3, 2, 4)))
+ @test_util.run_deprecated_v1
def testInvalidSuffixMatchExtraDim(self):
self._test_invalid(
weights=np.asarray((
diff --git a/tensorflow/python/kernel_tests/where_op_test.py b/tensorflow/python/kernel_tests/where_op_test.py
index 9e074b23043..56c13904113 100644
--- a/tensorflow/python/kernel_tests/where_op_test.py
+++ b/tensorflow/python/kernel_tests/where_op_test.py
@@ -27,6 +27,7 @@ from tensorflow.python.client import session
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import random_ops
from tensorflow.python.ops import resource_variable_ops
@@ -54,6 +55,7 @@ class WhereOpTest(test.TestCase):
with self.assertRaises(ValueError):
array_ops.where([False, True], None, [1, 2])
+ @test_util.run_deprecated_v1
def testBasicVec(self):
x = np.asarray([True, False])
truth = np.asarray([[0]], dtype=np.int64)
@@ -67,11 +69,13 @@ class WhereOpTest(test.TestCase):
truth = np.asarray([[2], [4]], dtype=np.int64)
self._testWhere(x, truth)
+ @test_util.run_deprecated_v1
def testRandomVec(self):
x = np.random.rand(1000000) > 0.5
truth = np.vstack([np.where(x)[0].astype(np.int64)]).T
self._testWhere(x, truth)
+ @test_util.run_deprecated_v1
def testBasicMat(self):
x = np.asarray([[True, False], [True, False]])
@@ -80,6 +84,7 @@ class WhereOpTest(test.TestCase):
self._testWhere(x, truth)
+ @test_util.run_deprecated_v1
def testBasic3Tensor(self):
x = np.asarray([[[True, False], [True, False]],
[[False, True], [False, True]],
@@ -99,36 +104,47 @@ class WhereOpTest(test.TestCase):
truth = np.vstack(truth).T # Convert to [num_true, indices].
self._testWhere(x, truth, expected_err_re)
+ @test_util.run_deprecated_v1
def testRandomBool(self):
self._testRandom(np.bool)
+ @test_util.run_deprecated_v1
def testRandomInt32(self):
self._testRandom(np.int32)
+ @test_util.run_deprecated_v1
def testRandomInt64(self):
self._testRandom(np.int64)
+ @test_util.run_deprecated_v1
def testRandomFloat(self):
self._testRandom(np.float32)
+ @test_util.run_deprecated_v1
def testRandomDouble(self):
self._testRandom(np.float64)
+ @test_util.run_deprecated_v1
def testRandomComplex64(self):
self._testRandom(np.complex64)
+ @test_util.run_deprecated_v1
def testRandomComplex128(self):
self._testRandom(np.complex128)
+ @test_util.run_deprecated_v1
def testRandomUint8(self):
self._testRandom(np.uint8)
+ @test_util.run_deprecated_v1
def testRandomInt8(self):
self._testRandom(np.int8)
+ @test_util.run_deprecated_v1
def testRandomInt16(self):
self._testRandom(np.int16)
+ @test_util.run_deprecated_v1
def testThreeArgument(self):
x = np.array([[-2, 3, -1], [1, -3, -3]])
np_val = np.where(x > 0, x * x, -x)
@@ -136,6 +152,7 @@ class WhereOpTest(test.TestCase):
tf_val = array_ops.where(constant_op.constant(x) > 0, x * x, -x).eval()
self.assertAllEqual(tf_val, np_val)
+ @test_util.run_deprecated_v1
def testBatchSelect(self):
x = np.array([[-2, 3, -1] * 64, [1, -3, -3] * 64] * 8192) # [16384, 192]
c_mat = np.array([[False] * 192, [True] * 192] * 8192) # [16384, 192]
diff --git a/tensorflow/python/kernel_tests/while_v2_test.py b/tensorflow/python/kernel_tests/while_v2_test.py
index e08699922af..09cbeb1a0d5 100644
--- a/tensorflow/python/kernel_tests/while_v2_test.py
+++ b/tensorflow/python/kernel_tests/while_v2_test.py
@@ -43,6 +43,7 @@ from tensorflow.python.platform import test
class WhileV2Test(test.TestCase, parameterized.TestCase):
+ @test_util.run_deprecated_v1
def testSingleLoopVar(self):
x = constant_op.constant(2.)
ret = while_loop_v2(
@@ -64,6 +65,7 @@ class WhileV2Test(test.TestCase, parameterized.TestCase):
self.assertEqual(16., eval_result[0])
self.assertSequenceEqual(sess.run(grad), [32.])
+ @test_util.run_deprecated_v1
def testMultipleLoopVarsBasic(self):
x = constant_op.constant(5.)
y = constant_op.constant(3.)
@@ -84,6 +86,7 @@ class WhileV2Test(test.TestCase, parameterized.TestCase):
self.assertSequenceEqual(self.evaluate(ret), [45., 3.])
self.assertSequenceEqual(self.evaluate(grad), [9.])
+ @test_util.run_deprecated_v1
def testMultipleLoopVars(self):
x = constant_op.constant(5.)
y = constant_op.constant(3.)
@@ -114,6 +117,7 @@ class WhileV2Test(test.TestCase, parameterized.TestCase):
self.assertSequenceEqual(self.evaluate(grady_1), [6.])
self.assertSequenceEqual(self.evaluate(grady_2), [61.])
+ @test_util.run_deprecated_v1
def testMultipleWhileLoops(self):
x = constant_op.constant(2.)
ret1 = while_loop_v2(
@@ -128,6 +132,7 @@ class WhileV2Test(test.TestCase, parameterized.TestCase):
self.assertSequenceEqual(self.evaluate(grad), [32.])
self.assertSequenceEqual(self.evaluate(grad_grad), [48.])
+ @test_util.run_deprecated_v1
def testDoubleDerivative(self):
x = constant_op.constant(2.)
ret = while_loop_v2(
@@ -140,6 +145,7 @@ class WhileV2Test(test.TestCase, parameterized.TestCase):
self.assertSequenceEqual(self.evaluate(grad), [32.])
self.assertSequenceEqual(self.evaluate(grad_grad), [48.])
+ @test_util.run_deprecated_v1
def testPruning(self):
x = constant_op.constant(1)
@@ -175,6 +181,7 @@ class WhileV2Test(test.TestCase, parameterized.TestCase):
g = GetOptimizedGraph()
self.assertEqual(len([n for n in g.node if n.op == "Enter"]), 2)
+ @test_util.run_deprecated_v1
def testCaptureExternalTensorInCond(self):
x = constant_op.constant(2.)
y = constant_op.constant(1.)
@@ -187,6 +194,7 @@ class WhileV2Test(test.TestCase, parameterized.TestCase):
self.assertEqual(self.evaluate(ret), 18.)
self.assertSequenceEqual(self.evaluate(grad), [9.])
+ @test_util.run_deprecated_v1
def testCaptureExternalTensorInBody(self):
x = constant_op.constant(2.)
y = constant_op.constant(3.)
@@ -197,6 +205,7 @@ class WhileV2Test(test.TestCase, parameterized.TestCase):
self.assertEqual(self.evaluate(ret), 18.)
self.assertSequenceEqual(self.evaluate(grad), [9.])
+ @test_util.run_deprecated_v1
def testLoopWithTensorListPushBack(self):
x = constant_op.constant(2.)
@@ -219,6 +228,7 @@ class WhileV2Test(test.TestCase, parameterized.TestCase):
self.assertEqual(sess.run(ret[0]), 16.)
self.assertSequenceEqual(self.evaluate(grad), [32.])
+ @test_util.run_deprecated_v1
def testDuplicateAccumulator(self):
x = constant_op.constant(2.)
@@ -259,6 +269,7 @@ class WhileV2Test(test.TestCase, parameterized.TestCase):
("PartiallyDefinedShape", [None, 2]),
("FullyDefinedShape", [1, 2]),
)
+ @test_util.run_deprecated_v1
def testAccumulatorElementShape(self, shape):
def MatchShape(actual_tensor_shape):
@@ -344,6 +355,7 @@ class WhileV2Test(test.TestCase, parameterized.TestCase):
while2_op.get_attr("body").name, r"foo_while_1_body_\d*")
@test_util.enable_control_flow_v2
+ @test_util.run_deprecated_v1
def testWhileAndTensorArray(self):
with self.cached_session() as sess:
param = constant_op.constant(2.0)
@@ -354,6 +366,7 @@ class WhileV2Test(test.TestCase, parameterized.TestCase):
r = gradients_impl.gradients(r, param)[0]
self.assertAllClose(21.0, self.evaluate(r))
+ @test_util.run_deprecated_v1
def testNestedWhile(self):
# Compute sum of geometric progression: n^0 + n^1 + ... + n^m
# We compute the pow using a while loop.
@@ -377,6 +390,7 @@ class WhileV2Test(test.TestCase, parameterized.TestCase):
self.assertEqual(self.evaluate(result), 364.)
self.assertSequenceEqual(self.evaluate(grad), [547.])
+ @test_util.run_deprecated_v1
def testIdentityNodeInBody(self):
def Body(v):
@@ -392,6 +406,7 @@ class WhileV2Test(test.TestCase, parameterized.TestCase):
self.assertEqual(self.evaluate(ret), 16.)
self.assertSequenceEqual(self.evaluate(grad), [32.])
+ @test_util.run_deprecated_v1
def testNestedWhileAndTensorArray(self):
n = constant_op.constant(3.0)
diff --git a/tensorflow/python/kernel_tests/xent_op_test.py b/tensorflow/python/kernel_tests/xent_op_test.py
index 77669f08cc1..f5d03c23701 100644
--- a/tensorflow/python/kernel_tests/xent_op_test.py
+++ b/tensorflow/python/kernel_tests/xent_op_test.py
@@ -27,6 +27,7 @@ from tensorflow.python.client import session
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gen_nn_ops
from tensorflow.python.ops import gradient_checker
@@ -88,6 +89,7 @@ class XentTest(test.TestCase):
self._testSingleClass(True)
self._testSingleClass(False)
+ @test_util.run_deprecated_v1
def testRankTooLarge(self):
for dtype in np.float16, np.float32:
np_features = np.array([[[1., 1., 1., 1.]], [[1., 2., 3.,
@@ -152,12 +154,14 @@ class XentTest(test.TestCase):
self.assertAllCloseAccordingToType(np_loss, tf_loss)
self.assertAllCloseAccordingToType(np_backprop, tf_backprop)
+ @test_util.run_deprecated_v1
def testShapeMismatch(self):
with self.cached_session():
with self.assertRaises(ValueError):
gen_nn_ops.softmax_cross_entropy_with_logits(
[[0., 1.], [2., 3.]], [[0., 1., 0.], [1., 0., 0.]])
+ @test_util.run_deprecated_v1
def testNotMatrix(self):
with self.cached_session():
with self.assertRaises(ValueError):
@@ -179,6 +183,7 @@ class XentTest(test.TestCase):
np.array([[1., 1., 1., 1.], [1., 2., 3., 4.]]).astype(np.float64),
np.array([[0., 0., 0., 1.], [0., .5, .5, 0.]]).astype(np.float64))
+ @test_util.run_deprecated_v1
def testGradient(self):
with self.cached_session() as sess:
l = constant_op.constant(
@@ -206,6 +211,7 @@ class XentTest(test.TestCase):
print("cross entropy gradient err = ", err)
self.assertLess(err, 5e-8)
+ @test_util.run_deprecated_v1
def testGradientLabelWithV2(self):
with self.cached_session():
l = constant_op.constant(
@@ -224,6 +230,7 @@ class XentTest(test.TestCase):
self.assertLess(err, 5e-8)
+ @test_util.run_deprecated_v1
def testSecondGradient(self):
with self.cached_session() as sess:
l = constant_op.constant(
diff --git a/tensorflow/python/kernel_tests/zero_division_test.py b/tensorflow/python/kernel_tests/zero_division_test.py
index 7c82f9320a1..3dd9ec4ba94 100644
--- a/tensorflow/python/kernel_tests/zero_division_test.py
+++ b/tensorflow/python/kernel_tests/zero_division_test.py
@@ -27,6 +27,7 @@ from tensorflow.python.platform import test
class ZeroDivisionTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testZeros(self):
with test_util.use_gpu():
for dtype in dtypes.uint8, dtypes.int16, dtypes.int32, dtypes.int64:
diff --git a/tensorflow/python/layers/base_test.py b/tensorflow/python/layers/base_test.py
index 45099677e0f..d0ec4f4425f 100644
--- a/tensorflow/python/layers/base_test.py
+++ b/tensorflow/python/layers/base_test.py
@@ -143,6 +143,7 @@ class BaseLayerTest(test.TestCase):
synchronization=variable_scope.VariableSynchronization.ON_READ,
trainable=True)
+ @test_util.run_deprecated_v1
def testReusePartitionedVaraiblesAndRegularizers(self):
regularizer = lambda x: math_ops.reduce_sum(x) * 1e-3
partitioner = partitioned_variables.fixed_size_partitioner(3)
@@ -445,6 +446,7 @@ class BaseLayerTest(test.TestCase):
self.assertTrue(isinstance(result, dict))
self.assertEqual(set(['label', 'logits']), set(result.keys()))
+ @test_util.run_deprecated_v1
def testActivityRegularizer(self):
regularizer = math_ops.reduce_sum
layer = base_layers.Layer(activity_regularizer=regularizer)
@@ -533,6 +535,7 @@ class BaseLayerTest(test.TestCase):
self.assertEqual(len(layer.trainable_variables), 1)
self.assertEqual(layer.variables[0].graph, outer_graph)
+ @test_util.run_deprecated_v1
def testGetUpdateFor(self):
class MyLayer(base_layers.Layer):
@@ -577,6 +580,7 @@ class BaseLayerTest(test.TestCase):
self.assertEqual(len(layer.get_updates_for([intermediate_inputs])), 1)
self.assertEqual(len(layer.get_updates_for([outputs])), 0)
+ @test_util.run_deprecated_v1
def testGetLossesFor(self):
class MyLayer(base_layers.Layer):
diff --git a/tensorflow/python/layers/convolutional_test.py b/tensorflow/python/layers/convolutional_test.py
index d3200fa5b57..a3e493edfea 100644
--- a/tensorflow/python/layers/convolutional_test.py
+++ b/tensorflow/python/layers/convolutional_test.py
@@ -22,6 +22,7 @@ import numpy as np
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.layers import convolutional as conv_layers
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import init_ops
@@ -59,6 +60,7 @@ class ConvTest(test.TestCase):
with self.assertRaisesRegexp(ValueError, 'kernel_size'):
conv_layers.conv2d(images, 32, None)
+ @test_util.run_deprecated_v1
def testCreateConv2D(self):
height, width = 7, 9
images = random_ops.random_uniform((5, height, width, 4))
@@ -87,6 +89,7 @@ class ConvTest(test.TestCase):
self.assertListEqual(layer.kernel.get_shape().as_list(), [3, 3, 4, 32])
self.assertListEqual(layer.bias.get_shape().as_list(), [32])
+ @test_util.run_deprecated_v1
def testCreateConv2DChannelsFirst(self):
height, width = 7, 9
images = random_ops.random_uniform((5, 4, height, width))
@@ -97,6 +100,7 @@ class ConvTest(test.TestCase):
self.assertListEqual(layer.kernel.get_shape().as_list(), [3, 3, 4, 32])
self.assertListEqual(layer.bias.get_shape().as_list(), [32])
+ @test_util.run_deprecated_v1
def testUnknownInputChannels(self):
images = array_ops.placeholder(dtypes.float32, (5, 7, 9, None))
layer = conv_layers.Conv2D(32, [3, 3], activation=nn_ops.relu)
@@ -140,6 +144,7 @@ class ConvTest(test.TestCase):
self.assertListEqual(output.get_shape().as_list(),
[5, height / 2, width, 32])
+ @test_util.run_deprecated_v1
def testCreateConv1D(self):
width = 7
data = random_ops.random_uniform((5, width, 4))
@@ -156,6 +161,7 @@ class ConvTest(test.TestCase):
output = conv_layers.conv1d(data, 32, 3, activation=nn_ops.relu)
self.assertListEqual(output.get_shape().as_list(), [5, width - 2, 32])
+ @test_util.run_deprecated_v1
def testCreateConv1DChannelsFirst(self):
width = 7
data = random_ops.random_uniform((5, 4, width))
@@ -165,6 +171,7 @@ class ConvTest(test.TestCase):
self.assertListEqual(layer.kernel.get_shape().as_list(), [3, 4, 32])
self.assertListEqual(layer.bias.get_shape().as_list(), [32])
+ @test_util.run_deprecated_v1
def testUnknownInputChannelsConv1D(self):
data = array_ops.placeholder(dtypes.float32, (5, 4, None))
layer = conv_layers.Conv1D(32, 3, activation=nn_ops.relu)
@@ -180,6 +187,7 @@ class ConvTest(test.TestCase):
'should be defined. Found `None`.'):
_ = layer.apply(data)
+ @test_util.run_deprecated_v1
def testCreateConv3D(self):
depth, height, width = 6, 7, 9
volumes = random_ops.random_uniform((5, depth, height, width, 4))
@@ -191,6 +199,7 @@ class ConvTest(test.TestCase):
self.assertListEqual(layer.kernel.get_shape().as_list(), [3, 3, 3, 4, 32])
self.assertListEqual(layer.bias.get_shape().as_list(), [32])
+ @test_util.run_deprecated_v1
def testUnknownInputChannelsConv3D(self):
volumes = array_ops.placeholder(dtypes.float32, (5, 6, 7, 9, None))
layer = conv_layers.Conv3D(32, [3, 3, 3], activation=nn_ops.relu)
@@ -199,6 +208,7 @@ class ConvTest(test.TestCase):
'should be defined. Found `None`.'):
_ = layer.apply(volumes)
+ @test_util.run_deprecated_v1
def testConv2DKernelRegularizer(self):
height, width = 7, 9
images = random_ops.random_uniform((5, height, width, 4))
@@ -210,6 +220,7 @@ class ConvTest(test.TestCase):
self.evaluate([v.initializer for v in layer.variables])
self.assertListEqual(self.evaluate(layer.losses), self.evaluate(loss_keys))
+ @test_util.run_deprecated_v1
def testConv2DBiasRegularizer(self):
height, width = 7, 9
images = random_ops.random_uniform((5, height, width, 4))
@@ -221,6 +232,7 @@ class ConvTest(test.TestCase):
self.evaluate([v.initializer for v in layer.variables])
self.assertListEqual(self.evaluate(layer.losses), self.evaluate(loss_keys))
+ @test_util.run_deprecated_v1
def testConv2DNoBias(self):
height, width = 7, 9
images = random_ops.random_uniform((5, height, width, 4))
@@ -247,6 +259,7 @@ class ConvTest(test.TestCase):
output = layer.apply(images)
self.assertListEqual(output.get_shape().as_list(), [5, height - 2, 3, 32])
+ @test_util.run_deprecated_v1
def testFunctionalConv2DReuse(self):
height, width = 7, 9
images = random_ops.random_uniform((5, height, width, 3), seed=1)
@@ -255,6 +268,7 @@ class ConvTest(test.TestCase):
conv_layers.conv2d(images, 32, [3, 3], name='conv1', reuse=True)
self.assertEqual(len(variables.trainable_variables()), 2)
+ @test_util.run_deprecated_v1
def testFunctionalConv2DReuseFromScope(self):
with variable_scope.variable_scope('scope'):
height, width = 7, 9
@@ -265,6 +279,7 @@ class ConvTest(test.TestCase):
conv_layers.conv2d(images, 32, [3, 3], name='conv1')
self.assertEqual(len(variables.trainable_variables()), 2)
+ @test_util.run_deprecated_v1
def testFunctionalConv2DInitializerFromScope(self):
with self.cached_session() as sess:
with variable_scope.variable_scope(
@@ -283,6 +298,7 @@ class ConvTest(test.TestCase):
# Check that the bias still got initialized to zeros.
self.assertAllClose(weights[1], np.zeros((32)))
+ @test_util.run_deprecated_v1
def testFunctionalConv2DNoReuse(self):
height, width = 7, 9
images = random_ops.random_uniform((5, height, width, 3), seed=1)
@@ -325,6 +341,7 @@ class ConvTest(test.TestCase):
self.assertEqual(conv3d.kernel_constraint, k_constraint)
self.assertEqual(conv3d.bias_constraint, b_constraint)
+ @test_util.run_deprecated_v1
def testConv3DChannelsFirst(self):
# Test case for GitHub issue 15655
images = array_ops.placeholder(
@@ -358,6 +375,7 @@ class SeparableConv1DTest(test.TestCase):
with self.assertRaisesRegexp(ValueError, 'kernel_size'):
conv_layers.separable_conv1d(data, 32, None)
+ @test_util.run_deprecated_v1
def testCreateSeparableConv1D(self):
length = 9
data = random_ops.random_uniform((5, length, 4))
@@ -379,6 +397,7 @@ class SeparableConv1DTest(test.TestCase):
self.assertEqual(layer.pointwise_kernel.get_shape().as_list(), [1, 8, 32])
self.assertEqual(layer.bias.get_shape().as_list(), [32])
+ @test_util.run_deprecated_v1
def testCreateSeparableConv1DChannelsFirst(self):
length = 9
data = random_ops.random_uniform((5, 4, length))
@@ -404,6 +423,7 @@ class SeparableConv1DTest(test.TestCase):
output = layer.apply(data)
self.assertEqual(output.get_shape().as_list(), [5, length // 2, 32])
+ @test_util.run_deprecated_v1
def testCreateSeparableConv1DWithStridesChannelsFirst(self):
data_format = 'channels_first'
length = 10
@@ -413,6 +433,7 @@ class SeparableConv1DTest(test.TestCase):
output = layer.apply(data)
self.assertEqual(output.get_shape().as_list(), [5, 32, length // 2])
+ @test_util.run_deprecated_v1
def testFunctionalConv1DReuse(self):
length = 10
data = random_ops.random_uniform((5, length, 3), seed=1)
@@ -421,6 +442,7 @@ class SeparableConv1DTest(test.TestCase):
conv_layers.separable_conv1d(data, 32, 3, name='sepconv1', reuse=True)
self.assertEqual(len(variables.trainable_variables()), 3)
+ @test_util.run_deprecated_v1
def testFunctionalConv1DReuseFromScope(self):
with variable_scope.variable_scope('scope'):
length = 10
@@ -431,6 +453,7 @@ class SeparableConv1DTest(test.TestCase):
conv_layers.separable_conv1d(data, 32, 3, name='sepconv1')
self.assertEqual(len(variables.trainable_variables()), 3)
+ @test_util.run_deprecated_v1
def testFunctionalConv1DNoReuse(self):
length = 10
data = random_ops.random_uniform((5, length, 3), seed=1)
@@ -439,6 +462,7 @@ class SeparableConv1DTest(test.TestCase):
conv_layers.separable_conv1d(data, 32, 3)
self.assertEqual(len(variables.trainable_variables()), 6)
+ @test_util.run_deprecated_v1
def testSeparableConv1DDepthwiseRegularizer(self):
length = 9
data = random_ops.random_uniform((5, length, 4))
@@ -450,6 +474,7 @@ class SeparableConv1DTest(test.TestCase):
self.evaluate([v.initializer for v in layer.variables])
self.assertListEqual(self.evaluate(layer.losses), self.evaluate(loss_keys))
+ @test_util.run_deprecated_v1
def testSeparableConv1DPointwiseRegularizer(self):
length = 9
data = random_ops.random_uniform((5, length, 4))
@@ -461,6 +486,7 @@ class SeparableConv1DTest(test.TestCase):
self.evaluate([v.initializer for v in layer.variables])
self.assertListEqual(self.evaluate(layer.losses), self.evaluate(loss_keys))
+ @test_util.run_deprecated_v1
def testSeparableConv1DBiasRegularizer(self):
length = 9
data = random_ops.random_uniform((5, length, 4))
@@ -472,6 +498,7 @@ class SeparableConv1DTest(test.TestCase):
self.evaluate([v.initializer for v in layer.variables])
self.assertListEqual(self.evaluate(layer.losses), self.evaluate(loss_keys))
+ @test_util.run_deprecated_v1
def testSeparableConv1DNoBias(self):
length = 9
data = random_ops.random_uniform((5, length, 4))
@@ -522,6 +549,7 @@ class SeparableConv2DTest(test.TestCase):
with self.assertRaisesRegexp(ValueError, 'kernel_size'):
conv_layers.separable_conv2d(images, 32, None)
+ @test_util.run_deprecated_v1
def testCreateSeparableConv2D(self):
height, width = 7, 9
images = random_ops.random_uniform((5, height, width, 4))
@@ -562,6 +590,7 @@ class SeparableConv2DTest(test.TestCase):
[1, 1, 4, 32])
self.assertListEqual(layer.bias.get_shape().as_list(), [32])
+ @test_util.run_deprecated_v1
def testCreateSeparableConv2DChannelsFirst(self):
height, width = 7, 9
images = random_ops.random_uniform((5, 4, height, width))
@@ -584,6 +613,7 @@ class SeparableConv2DTest(test.TestCase):
output = layer.apply(images)
self.assertListEqual(output.get_shape().as_list(), [5, height, width, 64])
+ @test_util.run_deprecated_v1
def testCreateSeparableConvWithStrides(self):
height, width = 6, 8
# Test strides tuple
@@ -607,6 +637,7 @@ class SeparableConv2DTest(test.TestCase):
self.assertListEqual(output.get_shape().as_list(),
[5, height / 2, width, 32])
+ @test_util.run_deprecated_v1
def testCreateSeparableConvWithStridesChannelsFirst(self):
data_format = 'channels_first'
height, width = 6, 8
@@ -632,6 +663,7 @@ class SeparableConv2DTest(test.TestCase):
self.assertListEqual(output.get_shape().as_list(),
[5, 32, height / 2, width])
+ @test_util.run_deprecated_v1
def testFunctionalConv2DReuse(self):
height, width = 7, 9
images = random_ops.random_uniform((5, height, width, 3), seed=1)
@@ -641,6 +673,7 @@ class SeparableConv2DTest(test.TestCase):
images, 32, [3, 3], name='sepconv1', reuse=True)
self.assertEqual(len(variables.trainable_variables()), 3)
+ @test_util.run_deprecated_v1
def testFunctionalConv2DReuseFromScope(self):
with variable_scope.variable_scope('scope'):
height, width = 7, 9
@@ -651,6 +684,7 @@ class SeparableConv2DTest(test.TestCase):
conv_layers.separable_conv2d(images, 32, [3, 3], name='sepconv1')
self.assertEqual(len(variables.trainable_variables()), 3)
+ @test_util.run_deprecated_v1
def testFunctionalConv2DInitializerFromScope(self):
with self.cached_session() as sess:
with variable_scope.variable_scope(
@@ -671,6 +705,7 @@ class SeparableConv2DTest(test.TestCase):
# Check that the bias still got initialized to zeros.
self.assertAllClose(weights[2], np.zeros((32)))
+ @test_util.run_deprecated_v1
def testFunctionalConv2DNoReuse(self):
height, width = 7, 9
images = random_ops.random_uniform((5, height, width, 3), seed=1)
@@ -679,6 +714,7 @@ class SeparableConv2DTest(test.TestCase):
conv_layers.separable_conv2d(images, 32, [3, 3])
self.assertEqual(len(variables.trainable_variables()), 6)
+ @test_util.run_deprecated_v1
def testSeparableConv2DDepthwiseRegularizer(self):
height, width = 7, 9
images = random_ops.random_uniform((5, height, width, 4))
@@ -690,6 +726,7 @@ class SeparableConv2DTest(test.TestCase):
self.evaluate([v.initializer for v in layer.variables])
self.assertListEqual(self.evaluate(layer.losses), self.evaluate(loss_keys))
+ @test_util.run_deprecated_v1
def testSeparableConv2DPointwiseRegularizer(self):
height, width = 7, 9
images = random_ops.random_uniform((5, height, width, 4))
@@ -701,6 +738,7 @@ class SeparableConv2DTest(test.TestCase):
self.evaluate([v.initializer for v in layer.variables])
self.assertListEqual(self.evaluate(layer.losses), self.evaluate(loss_keys))
+ @test_util.run_deprecated_v1
def testSeparableConv2DBiasRegularizer(self):
height, width = 7, 9
images = random_ops.random_uniform((5, height, width, 4))
@@ -712,6 +750,7 @@ class SeparableConv2DTest(test.TestCase):
self.evaluate([v.initializer for v in layer.variables])
self.assertListEqual(self.evaluate(layer.losses), self.evaluate(loss_keys))
+ @test_util.run_deprecated_v1
def testSeparableConv2DNoBias(self):
height, width = 7, 9
images = random_ops.random_uniform((5, height, width, 4))
@@ -768,6 +807,7 @@ class Conv2DTransposeTest(test.TestCase):
with self.assertRaisesRegexp(ValueError, 'kernel_size'):
conv_layers.conv2d_transpose(images, 32, None)
+ @test_util.run_deprecated_v1
def testCreateConv2DTranspose(self):
height, width = 7, 9
images = random_ops.random_uniform((5, height, width, 4))
@@ -839,6 +879,7 @@ class Conv2DTransposeTest(test.TestCase):
self.assertListEqual(output.get_shape().as_list(),
[5, height * 2, width, 32])
+ @test_util.run_deprecated_v1
def testConv2DTransposeKernelRegularizer(self):
height, width = 7, 9
images = random_ops.random_uniform((5, height, width, 4))
@@ -850,6 +891,7 @@ class Conv2DTransposeTest(test.TestCase):
self.evaluate([v.initializer for v in layer.variables])
self.assertListEqual(self.evaluate(layer.losses), self.evaluate(loss_keys))
+ @test_util.run_deprecated_v1
def testConv2DTransposeBiasRegularizer(self):
height, width = 7, 9
images = random_ops.random_uniform((5, height, width, 4))
@@ -861,6 +903,7 @@ class Conv2DTransposeTest(test.TestCase):
self.evaluate([v.initializer for v in layer.variables])
self.assertListEqual(self.evaluate(layer.losses), self.evaluate(loss_keys))
+ @test_util.run_deprecated_v1
def testConv2DTransposeNoBias(self):
height, width = 7, 9
images = random_ops.random_uniform((5, height, width, 4))
@@ -873,6 +916,7 @@ class Conv2DTransposeTest(test.TestCase):
self.assertListEqual(layer.kernel.get_shape().as_list(), [3, 3, 32, 4])
self.assertEqual(layer.bias, None)
+ @test_util.run_deprecated_v1
def testFunctionalConv2DTransposeReuse(self):
height, width = 7, 9
images = random_ops.random_uniform((5, height, width, 3), seed=1)
@@ -881,6 +925,7 @@ class Conv2DTransposeTest(test.TestCase):
conv_layers.conv2d_transpose(images, 32, [3, 3], name='deconv1', reuse=True)
self.assertEqual(len(variables.trainable_variables()), 2)
+ @test_util.run_deprecated_v1
def testFunctionalConv2DTransposeReuseFromScope(self):
with variable_scope.variable_scope('scope'):
height, width = 7, 9
@@ -891,6 +936,7 @@ class Conv2DTransposeTest(test.TestCase):
conv_layers.conv2d_transpose(images, 32, [3, 3], name='deconv1')
self.assertEqual(len(variables.trainable_variables()), 2)
+ @test_util.run_deprecated_v1
def testFunctionalConv2DTransposeInitializerFromScope(self):
with self.cached_session() as sess:
with variable_scope.variable_scope(
@@ -909,6 +955,7 @@ class Conv2DTransposeTest(test.TestCase):
# Check that the bias still got initialized to zeros.
self.assertAllClose(weights[1], np.zeros((32)))
+ @test_util.run_deprecated_v1
def testFunctionalConv2DTransposeNoReuse(self):
height, width = 7, 9
images = random_ops.random_uniform((5, height, width, 3), seed=1)
@@ -955,6 +1002,7 @@ class Conv3DTransposeTest(test.TestCase):
with self.assertRaisesRegexp(ValueError, 'kernel_size'):
conv_layers.conv3d_transpose(volumes, 4, None)
+ @test_util.run_deprecated_v1
def testCreateConv3DTranspose(self):
depth, height, width = 5, 7, 9
volumes = random_ops.random_uniform((5, depth, height, width, 32))
@@ -976,6 +1024,7 @@ class Conv3DTransposeTest(test.TestCase):
self.assertListEqual(layer.kernel.get_shape().as_list(), [3, 3, 3, 4, 32])
self.assertListEqual(layer.bias.get_shape().as_list(), [4])
+ @test_util.run_deprecated_v1
def testCreateConv3DTransposeChannelsFirst(self):
depth, height, width = 5, 7, 9
volumes = random_ops.random_uniform((5, 32, depth, height, width))
@@ -1019,6 +1068,7 @@ class Conv3DTransposeTest(test.TestCase):
self.assertListEqual(output.get_shape().as_list(),
[5, depth * 2, height, width, 4])
+ @test_util.run_deprecated_v1
def testConv3DTransposeKernelRegularizer(self):
depth, height, width = 5, 7, 9
volumes = random_ops.random_uniform((5, depth, height, width, 32))
@@ -1030,6 +1080,7 @@ class Conv3DTransposeTest(test.TestCase):
self.evaluate([v.initializer for v in layer.variables])
self.assertListEqual(self.evaluate(layer.losses), self.evaluate(loss_keys))
+ @test_util.run_deprecated_v1
def testConv3DTransposeBiasRegularizer(self):
depth, height, width = 5, 7, 9
volumes = random_ops.random_uniform((5, depth, height, width, 32))
@@ -1041,6 +1092,7 @@ class Conv3DTransposeTest(test.TestCase):
self.evaluate([v.initializer for v in layer.variables])
self.assertListEqual(self.evaluate(layer.losses), self.evaluate(loss_keys))
+ @test_util.run_deprecated_v1
def testConv3DTransposeNoBias(self):
depth, height, width = 5, 7, 9
volumes = random_ops.random_uniform((5, depth, height, width, 32))
@@ -1053,6 +1105,7 @@ class Conv3DTransposeTest(test.TestCase):
self.assertListEqual(layer.kernel.get_shape().as_list(), [3, 3, 3, 4, 32])
self.assertEqual(layer.bias, None)
+ @test_util.run_deprecated_v1
def testFunctionalConv3DTransposeReuse(self):
depth, height, width = 5, 7, 9
volumes = random_ops.random_uniform((5, depth, height, width, 32), seed=1)
@@ -1062,6 +1115,7 @@ class Conv3DTransposeTest(test.TestCase):
volumes, 4, [3, 3, 3], name='deconv1', reuse=True)
self.assertEqual(len(variables.trainable_variables()), 2)
+ @test_util.run_deprecated_v1
def testFunctionalConv3DTransposeReuseFromScope(self):
with variable_scope.variable_scope('scope'):
depth, height, width = 5, 7, 9
@@ -1072,6 +1126,7 @@ class Conv3DTransposeTest(test.TestCase):
conv_layers.conv3d_transpose(volumes, 4, [3, 3, 3], name='deconv1')
self.assertEqual(len(variables.trainable_variables()), 2)
+ @test_util.run_deprecated_v1
def testFunctionalConv3DTransposeInitializerFromScope(self):
with self.cached_session() as sess:
with variable_scope.variable_scope(
@@ -1091,6 +1146,7 @@ class Conv3DTransposeTest(test.TestCase):
# Check that the bias still got initialized to zeros.
self.assertAllClose(weights[1], np.zeros((4)))
+ @test_util.run_deprecated_v1
def testFunctionalConv3DTransposeNoReuse(self):
depth, height, width = 5, 7, 9
volumes = random_ops.random_uniform((5, depth, height, width, 32), seed=1)
diff --git a/tensorflow/python/layers/core_test.py b/tensorflow/python/layers/core_test.py
index a61639b2db8..cf6f0fbb700 100644
--- a/tensorflow/python/layers/core_test.py
+++ b/tensorflow/python/layers/core_test.py
@@ -59,6 +59,7 @@ class DenseTest(test.TestCase):
dense.apply(random_ops.random_uniform((5, 2)))
self.assertEqual(dense.name, 'dense_2')
+ @test_util.run_deprecated_v1
def testVariableInput(self):
with self.cached_session():
v = variable_scope.get_variable(
@@ -140,6 +141,7 @@ class DenseTest(test.TestCase):
outputs = dense.apply(inputs)
self.assertEqual(outputs.get_shape().as_list(), [1, 2, 4, 7])
+ @test_util.run_deprecated_v1
def testCallOnPlaceHolder(self):
inputs = array_ops.placeholder(dtype=dtypes.float32)
dense = core_layers.Dense(4, name='my_dense')
@@ -179,6 +181,7 @@ class DenseTest(test.TestCase):
if not context.executing_eagerly():
self.assertEqual(outputs.op.name, 'dense2/BiasAdd')
+ @test_util.run_deprecated_v1
def testActivityRegularizer(self):
regularizer = lambda x: math_ops.reduce_sum(x) * 1e-3
dense = core_layers.Dense(
@@ -189,6 +192,7 @@ class DenseTest(test.TestCase):
self.assertEqual(len(loss_keys), 1)
self.assertListEqual(dense.losses, loss_keys)
+ @test_util.run_deprecated_v1
def testKernelRegularizer(self):
regularizer = lambda x: math_ops.reduce_sum(x) * 1e-3
dense = core_layers.Dense(
@@ -200,6 +204,7 @@ class DenseTest(test.TestCase):
self.evaluate([v.initializer for v in dense.variables])
self.assertAllEqual(self.evaluate(dense.losses), self.evaluate(loss_keys))
+ @test_util.run_deprecated_v1
def testKernelRegularizerWithReuse(self):
regularizer = lambda x: math_ops.reduce_sum(x) * 1e-3
inputs = random_ops.random_uniform((5, 3), seed=1)
@@ -212,6 +217,7 @@ class DenseTest(test.TestCase):
self.assertEqual(
len(ops.get_collection(ops.GraphKeys.REGULARIZATION_LOSSES)), 1)
+ @test_util.run_deprecated_v1
def testBiasRegularizer(self):
regularizer = lambda x: math_ops.reduce_sum(x) * 1e-3
dense = core_layers.Dense(2, name='my_dense', bias_regularizer=regularizer)
@@ -222,6 +228,7 @@ class DenseTest(test.TestCase):
self.evaluate([v.initializer for v in dense.variables])
self.assertAllEqual(self.evaluate(dense.losses), self.evaluate(loss_keys))
+ @test_util.run_deprecated_v1
def testFunctionalDense(self):
with self.cached_session():
inputs = random_ops.random_uniform((5, 3), seed=1)
@@ -231,6 +238,7 @@ class DenseTest(test.TestCase):
len(ops.get_collection(ops.GraphKeys.TRAINABLE_VARIABLES)), 2)
self.assertEqual(outputs.op.name, 'my_dense/Relu')
+ @test_util.run_deprecated_v1
def testFunctionalDenseTwice(self):
inputs = random_ops.random_uniform((5, 3), seed=1)
core_layers.dense(inputs, 2)
@@ -262,6 +270,7 @@ class DenseTest(test.TestCase):
vars2 = variables.trainable_variables()
self.assertEqual(vars1, vars2)
+ @test_util.run_deprecated_v1
def testFunctionalDenseInitializerFromScope(self):
with variable_scope.variable_scope(
'scope',
@@ -307,6 +316,7 @@ class DenseTest(test.TestCase):
core_layers.dense(inputs, 2)
self.assertEqual(called[0], 2)
+ @test_util.run_deprecated_v1
def testFunctionalDenseInScope(self):
with self.cached_session():
with variable_scope.variable_scope('test'):
@@ -393,6 +403,7 @@ class DropoutTest(test.TestCase):
np_output = self.evaluate(dropped)
self.assertAllClose(np.ones((5, 3)), np_output)
+ @test_util.run_deprecated_v1
def testDynamicLearningPhase(self):
with self.cached_session() as sess:
dp = core_layers.Dropout(0.5, seed=1)
@@ -426,6 +437,7 @@ class DropoutTest(test.TestCase):
self.assertAlmostEqual(0., np_output.min())
self.assertAllClose(np_output[:, 0, :], np_output[:, 1, :])
+ @test_util.run_deprecated_v1
def testFunctionalDropout(self):
with self.cached_session():
inputs = array_ops.ones((5, 5))
@@ -437,6 +449,7 @@ class DropoutTest(test.TestCase):
np_output = self.evaluate(dropped)
self.assertAllClose(np.ones((5, 5)), np_output)
+ @test_util.run_deprecated_v1
def testDynamicRate(self):
with self.cached_session() as sess:
rate = array_ops.placeholder(dtype='float32', name='rate')
@@ -452,6 +465,7 @@ class DropoutTest(test.TestCase):
class FlattenTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testCreateFlatten(self):
with self.cached_session() as sess:
x = array_ops.placeholder(shape=(None, 2, 3), dtype='float32')
@@ -476,6 +490,7 @@ class FlattenTest(test.TestCase):
shape = core_layers.Flatten().compute_output_shape((None, 3, None))
self.assertEqual(shape.as_list(), [None, None])
+ @test_util.run_deprecated_v1
def testDataFormat5d(self):
np_input_channels_last = np.arange(
120, dtype='float32').reshape([1, 5, 4, 3, 2])
@@ -493,6 +508,7 @@ class FlattenTest(test.TestCase):
self.assertAllEqual(np_output_cl, np_output_cf)
+ @test_util.run_deprecated_v1
def testDataFormat4d(self):
np_input_channels_last = np.arange(
24, dtype='float32').reshape([1, 4, 3, 2])
@@ -510,16 +526,19 @@ class FlattenTest(test.TestCase):
self.assertAllEqual(np_output_cl, np_output_cf)
+ @test_util.run_deprecated_v1
def testFunctionalFlatten(self):
x = array_ops.placeholder(shape=(None, 2, 3), dtype='float32')
y = core_layers.flatten(x, name='flatten')
self.assertEqual(y.get_shape().as_list(), [None, 6])
+ @test_util.run_deprecated_v1
def testFlattenValueError(self):
x = array_ops.placeholder(shape=(None,), dtype='float32')
with self.assertRaises(ValueError):
core_layers.Flatten()(x)
+ @test_util.run_deprecated_v1
def testFlattenUnknownAxes(self):
with self.cached_session() as sess:
x = array_ops.placeholder(shape=(5, None, None), dtype='float32')
diff --git a/tensorflow/python/layers/normalization_test.py b/tensorflow/python/layers/normalization_test.py
index cc3badbde1d..07d8e40b759 100644
--- a/tensorflow/python/layers/normalization_test.py
+++ b/tensorflow/python/layers/normalization_test.py
@@ -24,6 +24,7 @@ import numpy as np
from tensorflow.core.protobuf import saver_pb2
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.layers import convolutional as conv_layers
from tensorflow.python.layers import normalization as normalization_layers
from tensorflow.python.ops import array_ops
@@ -143,6 +144,7 @@ class BNTest(test.TestCase):
return train_vars, loss_val
+ @test_util.run_deprecated_v1
def testHalfPrecision(self):
ref_vars, ref_loss = self._trainEvalSequence(
dtype=dtypes.float32,
@@ -228,33 +230,43 @@ class BNTest(test.TestCase):
ckpt_b_use_gpu, use_gpu_test_a, use_gpu_test_b,
freeze_mode)
+ @test_util.run_deprecated_v1
def testCheckpointFusedCPUAndFusedGPU(self):
self._testCheckpointCrossDevice(True, False, True, True)
+ @test_util.run_deprecated_v1
def testCheckpointFusedCPUAndFusedCPU(self):
self._testCheckpointCrossDevice(True, False, True, False)
+ @test_util.run_deprecated_v1
def testCheckpointFusedGPUAndFusedGPU(self):
self._testCheckpointCrossDevice(True, True, True, True)
+ @test_util.run_deprecated_v1
def testCheckpointNonFusedCPUAndNonFusedGPU(self):
self._testCheckpointCrossDevice(False, False, False, True)
+ @test_util.run_deprecated_v1
def testCheckpointNonFusedCPUAndNonFusedCPU(self):
self._testCheckpointCrossDevice(False, False, False, False)
+ @test_util.run_deprecated_v1
def testCheckpointNonFusedGPUAndNonFusedGPU(self):
self._testCheckpointCrossDevice(False, True, False, True)
+ @test_util.run_deprecated_v1
def testCheckpointNonFusedGPUAndFusedGPU(self):
self._testCheckpointCrossDevice(False, True, True, True)
+ @test_util.run_deprecated_v1
def testCheckpointNonFusedGPUAndFusedCPU(self):
self._testCheckpointCrossDevice(False, True, True, False)
+ @test_util.run_deprecated_v1
def testCheckpointNonFusedCPUAndFusedCPU(self):
self._testCheckpointCrossDevice(False, False, True, False)
+ @test_util.run_deprecated_v1
def testCreateBN(self):
# Call layer.
bn = normalization_layers.BatchNormalization(axis=1)
@@ -281,6 +293,7 @@ class BNTest(test.TestCase):
ops.get_collection(ops.GraphKeys.TRAINABLE_VARIABLES),
bn.trainable_variables)
+ @test_util.run_deprecated_v1
def testCreateFusedBNFloat16(self):
# Call layer.
bn = normalization_layers.BatchNormalization(axis=1, fused=True)
@@ -310,6 +323,7 @@ class BNTest(test.TestCase):
ops.get_collection(ops.GraphKeys.TRAINABLE_VARIABLES),
bn.trainable_variables)
+ @test_util.run_deprecated_v1
def test3DInputAxis1(self):
epsilon = 1e-3
bn = normalization_layers.BatchNormalization(
@@ -353,6 +367,7 @@ class BNTest(test.TestCase):
self.assertAlmostEqual(np.mean(normed_np_output), 0., places=1)
self.assertAlmostEqual(np.std(normed_np_output), 1., places=1)
+ @test_util.run_deprecated_v1
def test3DInputAxis2(self):
epsilon = 1e-3
bn = normalization_layers.BatchNormalization(
@@ -436,6 +451,7 @@ class BNTest(test.TestCase):
self.assertAlmostEqual(np.mean(normed_np_output), 0., places=1)
self.assertAlmostEqual(np.std(normed_np_output), 1., places=1)
+ @test_util.run_deprecated_v1
def test4DInputAxis2(self):
epsilon = 1e-3
bn = normalization_layers.BatchNormalization(
@@ -477,6 +493,7 @@ class BNTest(test.TestCase):
self.assertAlmostEqual(np.mean(normed_np_output), 0., places=1)
self.assertAlmostEqual(np.std(normed_np_output), 1., places=1)
+ @test_util.run_deprecated_v1
def test4DInputAxis3(self):
epsilon = 1e-3
bn = normalization_layers.BatchNormalization(
@@ -518,6 +535,7 @@ class BNTest(test.TestCase):
self.assertAlmostEqual(np.mean(normed_np_output), 0., places=1)
self.assertAlmostEqual(np.std(normed_np_output), 1., places=1)
+ @test_util.run_deprecated_v1
def test4DInputAxis3Fused(self):
epsilon = 1e-3
bn = normalization_layers.BatchNormalization(
@@ -601,6 +619,7 @@ class BNTest(test.TestCase):
self.assertAlmostEqual(np.mean(normed_np_output), 0., places=1)
self.assertAlmostEqual(np.std(normed_np_output), 1., places=1)
+ @test_util.run_deprecated_v1
def testNegativeAxis(self):
epsilon = 1e-3
bn = normalization_layers.BatchNormalization(
@@ -643,6 +662,7 @@ class BNTest(test.TestCase):
self.assertAlmostEqual(np.mean(normed_np_output), 0., places=1)
self.assertAlmostEqual(np.std(normed_np_output), 1., places=1)
+ @test_util.run_deprecated_v1
def testBooleanLearningPhase(self):
epsilon = 1e-3
bn = normalization_layers.BatchNormalization(
@@ -683,6 +703,7 @@ class BNTest(test.TestCase):
self.assertAlmostEqual(np.mean(normed_np_output), 0., places=1)
self.assertAlmostEqual(np.std(normed_np_output), 1., places=1)
+ @test_util.run_deprecated_v1
def testFunctionalNoReuse(self):
inputs = variables.Variable(
np.random.random((5, 4, 3, 6)), dtype=dtypes.float32)
@@ -735,6 +756,7 @@ class BNTest(test.TestCase):
self.assertAlmostEqual(np.mean(normed_np_output), 0., places=1)
self.assertAlmostEqual(np.std(normed_np_output), 1., places=1)
+ @test_util.run_deprecated_v1
def testFunctionalReuse(self):
inputs1 = variables.Variable(
np.random.random((5, 4, 3, 6)), dtype=dtypes.float32)
@@ -799,6 +821,7 @@ class BNTest(test.TestCase):
self.assertAlmostEqual(np.mean(normed_np_output), 0., places=2)
self.assertAlmostEqual(np.std(normed_np_output), 1., places=1)
+ @test_util.run_deprecated_v1
def testFunctionalReuseFromScope(self):
inputs = variables.Variable(
np.random.random((5, 4, 3, 6)), dtype=dtypes.float32)
@@ -813,6 +836,7 @@ class BNTest(test.TestCase):
inputs, axis=-1, momentum=0.9, epsilon=epsilon, training=training)
self.assertEqual(len(variables.global_variables()), 5)
+ @test_util.run_deprecated_v1
def testNoCenter(self):
bn = normalization_layers.BatchNormalization(axis=1, center=False)
inputs = random_ops.random_uniform((5, 4, 3), seed=1)
@@ -828,6 +852,7 @@ class BNTest(test.TestCase):
self.assertEqual(len(bn.trainable_variables), 1)
self.assertEqual(len(bn.non_trainable_variables), 2)
+ @test_util.run_deprecated_v1
def testNoScale(self):
bn = normalization_layers.BatchNormalization(axis=1, scale=False)
inputs = random_ops.random_uniform((5, 4, 3), seed=1)
@@ -843,6 +868,7 @@ class BNTest(test.TestCase):
self.assertEqual(len(bn.trainable_variables), 1)
self.assertEqual(len(bn.non_trainable_variables), 2)
+ @test_util.run_deprecated_v1
def testRegularizers(self):
reg = lambda x: 0.1 * math_ops.reduce_sum(x)
bn = normalization_layers.BatchNormalization(axis=1, beta_regularizer=reg)
@@ -868,6 +894,7 @@ class BNTest(test.TestCase):
self.assertEqual(bn.gamma_constraint, g_constraint)
self.assertEqual(bn.beta_constraint, b_constraint)
+ @test_util.run_deprecated_v1
def testRenorm(self):
shape = (4, 3)
xt = array_ops.placeholder(dtypes.float32, shape)
@@ -926,6 +953,7 @@ class BNTest(test.TestCase):
self.assertAllClose(y_train, yt_val_train, atol=1e-5)
self.assertAllClose(y_test, yt_val_test, atol=1e-5)
+ @test_util.run_deprecated_v1
def testAdjustment(self):
shape = (4, 3)
xt = array_ops.placeholder(dtypes.float32, shape)
@@ -970,6 +998,7 @@ class BNTest(test.TestCase):
self.assertAllClose(y_train, yt_val_train, atol=1e-5)
self.assertAllClose(y_test, yt_val_test, atol=1e-5)
+ @test_util.run_deprecated_v1
def testRenormWithAdjustment(self):
shape = (4, 3)
xt = array_ops.placeholder(dtypes.float32, shape)
@@ -1040,6 +1069,7 @@ class BNTest(test.TestCase):
normalization_layers.batch_normalization(
inp, virtual_batch_size=-1)
+ @test_util.run_deprecated_v1
def testGhostBNVirtualBatchFull(self):
shape = [6, 5, 4, 3]
inp = random_ops.random_uniform(shape, seed=1)
@@ -1065,6 +1095,7 @@ class BNTest(test.TestCase):
inp, virtual_batch_size=3)
self.assertListEqual(out.shape.as_list(), shape)
+ @test_util.run_deprecated_v1
def testGhostBNUnknownBatchSize(self):
np_shape = [10, 5, 4]
tf_shape = [None, 5, 4]
@@ -1080,6 +1111,7 @@ class BNTest(test.TestCase):
self.assertListEqual(list(y.shape), np_shape)
+ @test_util.run_deprecated_v1
def testGhostBN2Dims(self):
shape = [6, 2]
virtual_batch_size = 3
@@ -1133,6 +1165,7 @@ class BNTest(test.TestCase):
self.assertAllClose(y_train, y_val_train, atol=1e-5)
self.assertAllClose(y_test, y_val_test, atol=1e-5)
+ @test_util.run_deprecated_v1
def testGhostBN4DimsAxis3(self):
shape = [6, 10, 10, 3]
virtual_batch_size = 2
@@ -1186,6 +1219,7 @@ class BNTest(test.TestCase):
self.assertAllClose(y_train, y_val_train, atol=1e-2)
self.assertAllClose(y_test, y_val_test, atol=1e-2)
+ @test_util.run_deprecated_v1
def testGhostBN4DimsAxis1(self):
shape = [6, 3, 10, 10]
virtual_batch_size = 2
@@ -1256,6 +1290,7 @@ class BNTest(test.TestCase):
normalization_layers.batch_normalization(
inp, axis=[1, 2, 1]) # duplicate
+ @test_util.run_deprecated_v1
def test3DInputMultiAxis12(self):
epsilon = 1e-3
bn = normalization_layers.BatchNormalization(
@@ -1297,6 +1332,7 @@ class BNTest(test.TestCase):
self.assertAlmostEqual(np.mean(normed_np_output), 0., places=1)
self.assertAlmostEqual(np.std(normed_np_output), 1., places=1)
+ @test_util.run_deprecated_v1
def test5DInputMultiAxis123(self):
epsilon = 1e-3
bn = normalization_layers.BatchNormalization(
@@ -1338,6 +1374,7 @@ class BNTest(test.TestCase):
self.assertAlmostEqual(np.mean(normed_np_output), 0., places=1)
self.assertAlmostEqual(np.std(normed_np_output), 1., places=1)
+ @test_util.run_deprecated_v1
def testGhostBN5DimsMultiAxis14(self):
shape = [6, 3, 10, 10, 4]
virtual_batch_size = 3
diff --git a/tensorflow/python/layers/pooling_test.py b/tensorflow/python/layers/pooling_test.py
index 7533674e5a0..cf1fa1e6915 100644
--- a/tensorflow/python/layers/pooling_test.py
+++ b/tensorflow/python/layers/pooling_test.py
@@ -18,6 +18,7 @@ from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
+from tensorflow.python.framework import test_util
from tensorflow.python.layers import pooling as pooling_layers
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import random_ops
@@ -64,6 +65,7 @@ class PoolingTest(test.TestCase):
output = layer.apply(images)
self.assertListEqual(output.get_shape().as_list(), [5, 3, 4, 4])
+ @test_util.run_deprecated_v1
def testCreateMaxPooling2DChannelsFirst(self):
height, width = 7, 9
images = random_ops.random_uniform((5, 2, height, width))
@@ -73,6 +75,7 @@ class PoolingTest(test.TestCase):
output = layer.apply(images)
self.assertListEqual(output.get_shape().as_list(), [5, 2, 6, 8])
+ @test_util.run_deprecated_v1
def testCreateAveragePooling2DChannelsFirst(self):
height, width = 5, 6
images = random_ops.random_uniform((3, 4, height, width))
@@ -83,6 +86,7 @@ class PoolingTest(test.TestCase):
output = layer.apply(images)
self.assertListEqual(output.get_shape().as_list(), [3, 4, 4, 5])
+ @test_util.run_deprecated_v1
def testCreateAveragePooling2DChannelsFirstWithNoneBatch(self):
height, width = 5, 6
images = array_ops.placeholder(dtype='float32',
diff --git a/tensorflow/python/ops/bitwise_ops_test.py b/tensorflow/python/ops/bitwise_ops_test.py
index 739278273b9..d154b6759bf 100644
--- a/tensorflow/python/ops/bitwise_ops_test.py
+++ b/tensorflow/python/ops/bitwise_ops_test.py
@@ -34,6 +34,7 @@ class BitwiseOpTest(test_util.TensorFlowTestCase):
def __init__(self, method_name="runTest"):
super(BitwiseOpTest, self).__init__(method_name)
+ @test_util.run_deprecated_v1
def testBinaryOps(self):
dtype_list = [dtypes.int8, dtypes.int16, dtypes.int32, dtypes.int64,
dtypes.uint8, dtypes.uint16, dtypes.uint32, dtypes.uint64]
@@ -70,6 +71,7 @@ class BitwiseOpTest(test_util.TensorFlowTestCase):
gen_bitwise_ops.population_count(input_tensor))
self.assertAllEqual(truth, popcnt_result)
+ @test_util.run_deprecated_v1
def testInvertOp(self):
dtype_list = [dtypes.int8, dtypes.int16, dtypes.int32, dtypes.int64,
dtypes.uint8, dtypes.uint16, dtypes.uint32, dtypes.uint64]
@@ -94,6 +96,7 @@ class BitwiseOpTest(test_util.TensorFlowTestCase):
expected = [dtype.max - x for x in inputs]
self.assertAllEqual(inverted, expected)
+ @test_util.run_deprecated_v1
def testShiftsWithPositiveLHS(self):
dtype_list = [np.int8, np.int16, np.int32, np.int64,
np.uint8, np.uint16, np.uint32, np.uint64]
@@ -108,6 +111,7 @@ class BitwiseOpTest(test_util.TensorFlowTestCase):
self.assertAllEqual(left_shift_result, np.left_shift(lhs, rhs))
self.assertAllEqual(right_shift_result, np.right_shift(lhs, rhs))
+ @test_util.run_deprecated_v1
def testShiftsWithNegativeLHS(self):
dtype_list = [np.int8, np.int16, np.int32, np.int64]
@@ -121,6 +125,7 @@ class BitwiseOpTest(test_util.TensorFlowTestCase):
self.assertAllEqual(left_shift_result, np.left_shift(lhs, rhs))
self.assertAllEqual(right_shift_result, np.right_shift(lhs, rhs))
+ @test_util.run_deprecated_v1
def testImplementationDefinedShiftsDoNotCrash(self):
dtype_list = [np.int8, np.int16, np.int32, np.int64]
@@ -136,6 +141,7 @@ class BitwiseOpTest(test_util.TensorFlowTestCase):
bitwise_ops.right_shift(lhs, rhs)])
+ @test_util.run_deprecated_v1
def testShapeInference(self):
dtype_list = [dtypes.int8, dtypes.int16, dtypes.int32, dtypes.int64,
dtypes.uint8, dtypes.uint16]
diff --git a/tensorflow/python/ops/clip_ops_test.py b/tensorflow/python/ops/clip_ops_test.py
index e9f7941b426..a59a0c22d40 100644
--- a/tensorflow/python/ops/clip_ops_test.py
+++ b/tensorflow/python/ops/clip_ops_test.py
@@ -20,6 +20,7 @@ from __future__ import print_function
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import clip_ops
from tensorflow.python.ops import numerics
from tensorflow.python.platform import test
@@ -57,6 +58,7 @@ class ClipOpsTest(test.TestCase):
result, expected = self.evaluate([clipped, dense_clipped])
self.assertAllClose(result, expected)
+ @test_util.run_deprecated_v1
def testClipTensorByNorm(self):
# Simple example
self._testClipTensorByNorm([[-3.0, 0.0, 0.0], [4.0, 0.0, 0.0]], 4.0,
diff --git a/tensorflow/python/ops/collective_ops_test.py b/tensorflow/python/ops/collective_ops_test.py
index 9c772a93548..0fd9368d219 100644
--- a/tensorflow/python/ops/collective_ops_test.py
+++ b/tensorflow/python/ops/collective_ops_test.py
@@ -21,6 +21,7 @@ from __future__ import print_function
from tensorflow.core.protobuf import config_pb2
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import collective_ops
from tensorflow.python.platform import test
@@ -49,16 +50,19 @@ class CollectiveOpTest(test.TestCase):
self.assertAllClose(results[0], expected, rtol=1e-5, atol=1e-5)
self.assertAllClose(results[1], expected, rtol=1e-5, atol=1e-5)
+ @test_util.run_deprecated_v1
def testCollectiveReduce(self):
self._testCollectiveReduce([0.1, 1.1, 2.1, 3.1, 4.1, 5.1, 6.1, 7.1],
[0.3, 1.3, 2.3, 3.3, 4.3, 5.3, 6.3, 7.3],
[0.2, 1.2, 2.2, 3.2, 4.2, 5.2, 6.2, 7.2], True)
+ @test_util.run_deprecated_v1
def testCollectiveAutoGraphKey(self):
self._testCollectiveReduce([0.1, 1.1, 2.1, 3.1, 4.1, 5.1, 6.1, 7.1],
[0.3, 1.3, 2.3, 3.3, 4.3, 5.3, 6.3, 7.3],
[0.2, 1.2, 2.2, 3.2, 4.2, 5.2, 6.2, 7.2], False)
+ @test_util.run_deprecated_v1
def testCollectiveReduceScalar(self):
self._testCollectiveReduce(0.1, 0.3, 0.2, True)
@@ -81,6 +85,7 @@ class CollectiveOpTest(test.TestCase):
self.assertAllClose(results[0], t0, rtol=1e-5, atol=1e-5)
self.assertAllClose(results[1], t0, rtol=1e-5, atol=1e-5)
+ @test_util.run_deprecated_v1
def testCollectiveBroadcast(self):
self._testCollectiveBroadcast([0.1, 1.1, 2.1, 3.1, 4.1, 5.1, 6.1, 7.1])
diff --git a/tensorflow/python/ops/gradient_checker_test.py b/tensorflow/python/ops/gradient_checker_test.py
index 66c7b9a71b5..4d2b5efac7b 100644
--- a/tensorflow/python/ops/gradient_checker_test.py
+++ b/tensorflow/python/ops/gradient_checker_test.py
@@ -23,6 +23,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import math_ops
@@ -46,6 +47,7 @@ def _nan_grad(unused_op, grad):
class GradientCheckerTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testAddSimple(self):
np.random.seed(1) # Fix seed to avoid flakiness
with self.session(use_gpu=False):
@@ -60,6 +62,7 @@ class GradientCheckerTest(test.TestCase):
tf_logging.info("x1 error = %f", error)
assert error < 1e-4
+ @test_util.run_deprecated_v1
def testAddSimpleGPU(self):
np.random.seed(2) # Fix seed to avoid flakiness
with self.session(use_gpu=True):
@@ -74,6 +77,7 @@ class GradientCheckerTest(test.TestCase):
tf_logging.info("x1 error = %f", error)
assert error < 1e-4
+ @test_util.run_deprecated_v1
def testAddCustomized(self):
np.random.seed(3) # Fix seed to avoid flakiness
with self.cached_session():
@@ -92,6 +96,7 @@ class GradientCheckerTest(test.TestCase):
tf_logging.info("x2 error = %f", error)
assert error < 1e-10
+ @test_util.run_deprecated_v1
def testGather(self):
np.random.seed(4) # Fix seed to avoid flakiness
with self.cached_session():
@@ -109,6 +114,7 @@ class GradientCheckerTest(test.TestCase):
tf_logging.info("gather error = %f", error)
assert error < 1e-4
+ @test_util.run_deprecated_v1
def testNestedGather(self):
np.random.seed(5) # Fix seed to avoid flakiness
with self.cached_session():
@@ -130,6 +136,7 @@ class GradientCheckerTest(test.TestCase):
tf_logging.info("nested gather error = %f", error)
assert error < 1e-4
+ @test_util.run_deprecated_v1
def testComplexMul(self):
with self.cached_session():
size = ()
@@ -144,6 +151,7 @@ class GradientCheckerTest(test.TestCase):
self.assertLess(
gradient_checker.compute_gradient_error(x, size, y, size), 2e-4)
+ @test_util.run_deprecated_v1
def testComplexConj(self):
with self.cached_session():
size = ()
@@ -157,6 +165,7 @@ class GradientCheckerTest(test.TestCase):
self.assertLess(
gradient_checker.compute_gradient_error(x, size, y, size), 2e-5)
+ @test_util.run_deprecated_v1
def testEmptySucceeds(self):
with self.cached_session():
x = array_ops.placeholder(dtypes.float32)
@@ -279,18 +288,23 @@ class MiniMNISTTest(test.TestCase):
tf_logging.info("Mini MNIST: %s gradient error = %g", tag, err)
return err
+ @test_util.run_deprecated_v1
def testInputGradient(self):
self.assertLess(self._BuildAndTestMiniMNIST(0, "input"), 1e-8)
+ @test_util.run_deprecated_v1
def testHiddenWeightGradient(self):
self.assertLess(self._BuildAndTestMiniMNIST(1, "hidden_weight"), 1e-8)
+ @test_util.run_deprecated_v1
def testHiddenBiasGradient(self):
self.assertLess(self._BuildAndTestMiniMNIST(2, "hidden_bias"), 1e-8)
+ @test_util.run_deprecated_v1
def testSoftmaxWeightGradient(self):
self.assertLess(self._BuildAndTestMiniMNIST(3, "softmax_weight"), 1e-8)
+ @test_util.run_deprecated_v1
def testSoftmaxBiasGradient(self):
self.assertLess(self._BuildAndTestMiniMNIST(4, "softmax_bias"), 1e-8)
diff --git a/tensorflow/python/ops/histogram_ops_test.py b/tensorflow/python/ops/histogram_ops_test.py
index cd1abbfc132..b48ef67196b 100644
--- a/tensorflow/python/ops/histogram_ops_test.py
+++ b/tensorflow/python/ops/histogram_ops_test.py
@@ -21,6 +21,7 @@ from __future__ import print_function
import numpy as np
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.framework import constant_op
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import histogram_ops
@@ -84,6 +85,7 @@ class HistogramFixedWidthTest(test.TestCase):
def setUp(self):
self.rng = np.random.RandomState(0)
+ @test_util.run_deprecated_v1
def test_with_invalid_value_range(self):
values = [-1.0, 0.0, 1.5, 2.0, 5.0, 15]
with self.assertRaisesRegexp(
@@ -92,6 +94,7 @@ class HistogramFixedWidthTest(test.TestCase):
with self.assertRaisesRegexp(ValueError, "Dimension must be 2 but is 3"):
histogram_ops.histogram_fixed_width(values, [1.0, 2.0, 3.0])
+ @test_util.run_deprecated_v1
def test_with_invalid_nbins(self):
values = [-1.0, 0.0, 1.5, 2.0, 5.0, 15]
with self.assertRaisesRegexp(
@@ -146,6 +149,7 @@ class HistogramFixedWidthTest(test.TestCase):
self.assertEqual(dtypes.int32, hist.dtype)
self.assertAllClose(expected_bin_counts, self.evaluate(hist))
+ @test_util.run_deprecated_v1
def test_shape_inference(self):
value_range = [0.0, 5.0]
values = [[-1.0, 0.0, 1.5], [2.0, 5.0, 15]]
diff --git a/tensorflow/python/ops/image_grad_test.py b/tensorflow/python/ops/image_grad_test.py
index 0ea15b0d23f..c481266dd71 100644
--- a/tensorflow/python/ops/image_grad_test.py
+++ b/tensorflow/python/ops/image_grad_test.py
@@ -21,6 +21,7 @@ from __future__ import print_function
import numpy as np
from tensorflow.python.framework import constant_op
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import gradients_impl
from tensorflow.python.ops import image_ops
@@ -47,6 +48,7 @@ class ResizeNearestNeighborOpTest(test.TestCase):
resize_out = self.evaluate(resize_out)
self.assertEqual(out_shape, list(resize_out.shape))
+ @test_util.run_deprecated_v1
def testGradFromResizeToLargerInBothDims(self):
in_shape = [1, 2, 3, 1]
out_shape = [1, 4, 6, 1]
@@ -62,6 +64,7 @@ class ResizeNearestNeighborOpTest(test.TestCase):
input_tensor, in_shape, resize_out, out_shape, x_init_value=x)
self.assertLess(err, 1e-3)
+ @test_util.run_deprecated_v1
def testGradFromResizeToSmallerInBothDims(self):
in_shape = [1, 4, 6, 1]
out_shape = [1, 2, 3, 1]
@@ -77,6 +80,7 @@ class ResizeNearestNeighborOpTest(test.TestCase):
input_tensor, in_shape, resize_out, out_shape, x_init_value=x)
self.assertLess(err, 1e-3)
+ @test_util.run_deprecated_v1
def testCompareGpuVsCpu(self):
in_shape = [1, 4, 6, 3]
out_shape = [1, 8, 16, 3]
@@ -116,6 +120,7 @@ class ResizeBilinearOpTest(test.TestCase):
resize_out = self.evaluate(resize_out)
self.assertEqual(out_shape, list(resize_out.shape))
+ @test_util.run_deprecated_v1
def testGradFromResizeToLargerInBothDims(self):
in_shape = [1, 2, 3, 1]
out_shape = [1, 4, 6, 1]
@@ -129,6 +134,7 @@ class ResizeBilinearOpTest(test.TestCase):
input_tensor, in_shape, resize_out, out_shape, x_init_value=x)
self.assertLess(err, 1e-3)
+ @test_util.run_deprecated_v1
def testGradFromResizeToSmallerInBothDims(self):
in_shape = [1, 4, 6, 1]
out_shape = [1, 2, 3, 1]
@@ -142,6 +148,7 @@ class ResizeBilinearOpTest(test.TestCase):
input_tensor, in_shape, resize_out, out_shape, x_init_value=x)
self.assertLess(err, 1e-3)
+ @test_util.run_deprecated_v1
def testCompareGpuVsCpu(self):
in_shape = [2, 4, 6, 3]
out_shape = [2, 8, 16, 3]
@@ -160,6 +167,7 @@ class ResizeBilinearOpTest(test.TestCase):
self.assertAllClose(grad[False], grad[True], rtol=1e-4, atol=1e-4)
+ @test_util.run_deprecated_v1
def testTypes(self):
in_shape = [1, 4, 6, 1]
out_shape = [1, 2, 3, 1]
@@ -199,6 +207,7 @@ class ResizeBicubicOpTest(test.TestCase):
resize_out = self.evaluate(resize_out)
self.assertEqual(out_shape, list(resize_out.shape))
+ @test_util.run_deprecated_v1
def testGradFromResizeToLargerInBothDims(self):
in_shape = [1, 2, 3, 1]
out_shape = [1, 4, 6, 1]
@@ -214,6 +223,7 @@ class ResizeBicubicOpTest(test.TestCase):
input_tensor, in_shape, resize_out, out_shape, x_init_value=x)
self.assertLess(err, 1e-3)
+ @test_util.run_deprecated_v1
def testGradFromResizeToSmallerInBothDims(self):
in_shape = [1, 4, 6, 1]
out_shape = [1, 2, 3, 1]
@@ -229,6 +239,7 @@ class ResizeBicubicOpTest(test.TestCase):
input_tensor, in_shape, resize_out, out_shape, x_init_value=x)
self.assertLess(err, 1e-3)
+ @test_util.run_deprecated_v1
def testGradOnUnsupportedType(self):
in_shape = [1, 4, 6, 1]
out_shape = [1, 2, 3, 1]
@@ -306,6 +317,7 @@ class CropAndResizeOpTest(test.TestCase):
samples.append(sample)
return samples
+ @test_util.run_deprecated_v1
def testGradRandomBoxes(self):
"""Test that the gradient is correct for randomly generated boxes.
diff --git a/tensorflow/python/ops/image_ops_test.py b/tensorflow/python/ops/image_ops_test.py
index 71a574e0a02..e7249333bd3 100644
--- a/tensorflow/python/ops/image_ops_test.py
+++ b/tensorflow/python/ops/image_ops_test.py
@@ -211,6 +211,7 @@ class GrayscaleToRGBTest(test_util.TensorFlowTestCase):
y_tf = self.evaluate(y)
self.assertAllEqual(y_tf, y_np)
+ @test_util.run_deprecated_v1
def testShapeInference(self):
# Shape inference works and produces expected output where possible
rgb_shape = [7, None, 19, 3]
@@ -271,6 +272,7 @@ class AdjustGamma(test_util.TensorFlowTestCase):
else:
raise AssertionError("Exception not raised: %s" % err_msg)
+ @test_util.run_deprecated_v1
def test_adjust_gamma_less_zero_tensor(self):
"""White image should be returned for gamma equal to zero"""
with self.cached_session():
@@ -308,6 +310,7 @@ class AdjustGamma(test_util.TensorFlowTestCase):
self.assertAllClose(y_tf, y_np, 1e-6)
+ @test_util.run_deprecated_v1
def test_adjust_gamma_less_one(self):
"""Verifying the output with expected results for gamma
correction with gamma equal to half"""
@@ -329,6 +332,7 @@ class AdjustGamma(test_util.TensorFlowTestCase):
self.assertAllClose(y_tf, y_np, 1e-6)
+ @test_util.run_deprecated_v1
def test_adjust_gamma_greater_one(self):
"""Verifying the output with expected results for gamma
correction with gamma equal to two"""
@@ -938,6 +942,7 @@ class AdjustSaturationTest(test_util.TensorFlowTestCase):
y_v[i][2] = b
return y_v.reshape(x_np.shape)
+ @test_util.run_deprecated_v1
def testAdjustRandomSaturation(self):
x_shapes = [
[2, 2, 3],
@@ -996,6 +1001,7 @@ class FlipTransposeRotateTest(test_util.TensorFlowTestCase):
y_tf = self.evaluate(y)
self.assertAllEqual(y_tf, x_np)
+ @test_util.run_deprecated_v1
def testLeftRight(self):
x_np = np.array([[1, 2, 3], [1, 2, 3]], dtype=np.uint8).reshape([2, 3, 1])
y_np = np.array([[3, 2, 1], [3, 2, 1]], dtype=np.uint8).reshape([2, 3, 1])
@@ -1021,6 +1027,7 @@ class FlipTransposeRotateTest(test_util.TensorFlowTestCase):
y_tf = self.evaluate(y)
self.assertAllEqual(y_tf, y_np)
+ @test_util.run_deprecated_v1
def testRandomFlipLeftRight(self):
x_np = np.array([[1, 2, 3], [1, 2, 3]], dtype=np.uint8).reshape([2, 3, 1])
y_np = np.array([[3, 2, 1], [3, 2, 1]], dtype=np.uint8).reshape([2, 3, 1])
@@ -1049,6 +1056,7 @@ class FlipTransposeRotateTest(test_util.TensorFlowTestCase):
self.assertGreaterEqual(count_flipped, 20)
self.assertGreaterEqual(count_unflipped, 20)
+ @test_util.run_deprecated_v1
def testRandomFlipLeftRightWithBatch(self):
batch_size = 16
seed = 42
@@ -1113,6 +1121,7 @@ class FlipTransposeRotateTest(test_util.TensorFlowTestCase):
y_tf = self.evaluate(y)
self.assertAllEqual(y_tf, x_np)
+ @test_util.run_deprecated_v1
def testUpDown(self):
x_np = np.array([[1, 2, 3], [4, 5, 6]], dtype=np.uint8).reshape([2, 3, 1])
y_np = np.array([[4, 5, 6], [1, 2, 3]], dtype=np.uint8).reshape([2, 3, 1])
@@ -1138,6 +1147,7 @@ class FlipTransposeRotateTest(test_util.TensorFlowTestCase):
y_tf = self.evaluate(y)
self.assertAllEqual(y_tf, y_np)
+ @test_util.run_deprecated_v1
def testRandomFlipUpDown(self):
x_np = np.array([[1, 2, 3], [4, 5, 6]], dtype=np.uint8).reshape([2, 3, 1])
y_np = np.array([[4, 5, 6], [1, 2, 3]], dtype=np.uint8).reshape([2, 3, 1])
@@ -1166,6 +1176,7 @@ class FlipTransposeRotateTest(test_util.TensorFlowTestCase):
self.assertGreaterEqual(count_flipped, 20)
self.assertGreaterEqual(count_unflipped, 20)
+ @test_util.run_deprecated_v1
def testRandomFlipUpDownWithBatch(self):
batch_size = 16
seed = 42
@@ -1230,6 +1241,7 @@ class FlipTransposeRotateTest(test_util.TensorFlowTestCase):
y_tf = self.evaluate(y)
self.assertAllEqual(y_tf, x_np)
+ @test_util.run_deprecated_v1
def testTranspose(self):
x_np = np.array([[1, 2, 3], [4, 5, 6]], dtype=np.uint8).reshape([2, 3, 1])
y_np = np.array([[1, 4], [2, 5], [3, 6]], dtype=np.uint8).reshape([3, 2, 1])
@@ -1256,6 +1268,7 @@ class FlipTransposeRotateTest(test_util.TensorFlowTestCase):
y_tf = self.evaluate(y)
self.assertAllEqual(y_tf, y_np)
+ @test_util.run_deprecated_v1
def testPartialShapes(self):
p_unknown_rank = array_ops.placeholder(dtypes.uint8)
p_unknown_dims_3 = array_ops.placeholder(
@@ -1314,6 +1327,7 @@ class FlipTransposeRotateTest(test_util.TensorFlowTestCase):
rotated = image_ops.rot90(rotated)
self.assertAllEqual(image, self.evaluate(rotated))
+ @test_util.run_deprecated_v1
def testRot90NumpyEquivalence(self):
image = np.arange(24, dtype=np.uint8).reshape([2, 4, 3])
with self.test_session(use_gpu=True):
@@ -1323,6 +1337,7 @@ class FlipTransposeRotateTest(test_util.TensorFlowTestCase):
y_np = np.rot90(image, k=k)
self.assertAllEqual(y_np, y_tf.eval({k_placeholder: k}))
+ @test_util.run_deprecated_v1
def testRot90NumpyEquivalenceWithBatch(self):
image = np.arange(48, dtype=np.uint8).reshape([2, 2, 4, 3])
with self.test_session(use_gpu=True):
@@ -1411,6 +1426,7 @@ class AdjustContrastTest(test_util.TensorFlowTestCase):
y_tf = self._adjustContrastTf(x_np, contrast_factor)
self.assertAllClose(y_tf, y_np, rtol=1e-5, atol=1e-5)
+ @test_util.run_deprecated_v1
def testContrastFactorShape(self):
x_shape = [1, 2, 2, 3]
x_data = [0, 5, 13, 54, 135, 226, 37, 8, 234, 90, 255, 1]
@@ -1474,6 +1490,7 @@ class PerImageWhiteningTest(test_util.TensorFlowTestCase):
y /= stddev
return y
+ @test_util.run_deprecated_v1
def testBasic(self):
x_shape = [13, 9, 3]
x_np = np.arange(0, np.prod(x_shape), dtype=np.int32).reshape(x_shape)
@@ -1574,11 +1591,13 @@ class CropToBoundingBoxTest(test_util.TensorFlowTestCase):
y = image_ops.crop_to_bounding_box(image, 0, 0, height, width)
self.assertEqual(y.get_shape().as_list(), post_shape)
+ @test_util.run_deprecated_v1
def testNoOp(self):
x_shape = [10, 10, 10]
x = np.random.uniform(size=x_shape)
self._assertReturns(x, x_shape, 0, 0, x, x_shape)
+ @test_util.run_deprecated_v1
def testCrop(self):
x = [1, 2, 3, 4, 5, 6, 7, 8, 9]
x_shape = [3, 3, 1]
@@ -1603,6 +1622,7 @@ class CropToBoundingBoxTest(test_util.TensorFlowTestCase):
y = [1, 2, 4, 5, 7, 8]
self._assertReturns(x, x_shape, offset_height, offset_width, y, y_shape)
+ @test_util.run_deprecated_v1
def testShapeInference(self):
self._assertShapeInference([55, 66, 3], 55, 66, [55, 66, 3])
self._assertShapeInference([59, 69, 3], 55, 66, [55, 66, 3])
@@ -1616,6 +1636,7 @@ class CropToBoundingBoxTest(test_util.TensorFlowTestCase):
self._assertShapeInference([None, None, None], 55, 66, [55, 66, None])
self._assertShapeInference(None, 55, 66, [55, 66, None])
+ @test_util.run_deprecated_v1
def testNon3DInput(self):
# Input image is not 3D
x = [0] * 15
@@ -1627,6 +1648,7 @@ class CropToBoundingBoxTest(test_util.TensorFlowTestCase):
target_width,
"'image' must have either 3 or 4 dimensions.")
+ @test_util.run_deprecated_v1
def testZeroLengthInput(self):
# Input image has 0-length dimension(s).
# Each line is a test configuration:
@@ -1658,6 +1680,7 @@ class CropToBoundingBoxTest(test_util.TensorFlowTestCase):
"assertion failed:",
use_tensor_inputs_options=[True])
+ @test_util.run_deprecated_v1
def testBadParams(self):
x_shape = [4, 4, 1]
x = np.zeros(x_shape)
@@ -1675,6 +1698,7 @@ class CropToBoundingBoxTest(test_util.TensorFlowTestCase):
for params, err_msg in test_config:
self._assertRaises(x, x_shape, *params, err_msg=err_msg)
+ @test_util.run_deprecated_v1
def testNameScope(self):
image = array_ops.placeholder(dtypes.float32, shape=[55, 66, 3])
y = image_ops.crop_to_bounding_box(image, 0, 0, 55, 66)
@@ -1691,6 +1715,7 @@ class CentralCropTest(test_util.TensorFlowTestCase):
else:
self.assertEqual(y.get_shape().as_list(), post_shape)
+ @test_util.run_deprecated_v1
def testNoOp(self):
x_shapes = [[13, 9, 3], [5, 13, 9, 3]]
for x_shape in x_shapes:
@@ -1734,6 +1759,7 @@ class CentralCropTest(test_util.TensorFlowTestCase):
self.assertAllEqual(y_tf, y_np)
self.assertAllEqual(y_tf.shape, y_np.shape)
+ @test_util.run_deprecated_v1
def testCropping2(self):
# Test case for 10315
x_shapes = [[240, 320, 3], [5, 240, 320, 3]]
@@ -1750,6 +1776,7 @@ class CentralCropTest(test_util.TensorFlowTestCase):
self.assertAllEqual(y_tf, y_np)
self.assertAllEqual(y_tf.shape, y_np.shape)
+ @test_util.run_deprecated_v1
def testShapeInference(self):
# Test no-op fraction=1.0, with 3-D tensors.
self._assertShapeInference([50, 60, 3], 1.0, [50, 60, 3])
@@ -1810,6 +1837,7 @@ class CentralCropTest(test_util.TensorFlowTestCase):
with self.assertRaises(ValueError):
_ = image_ops.central_crop(x, 0.5)
+ @test_util.run_deprecated_v1
def testNameScope(self):
x_shape = [13, 9, 3]
x_np = np.ones(x_shape, dtype=np.float32)
@@ -1902,12 +1930,14 @@ class PadToBoundingBoxTest(test_util.TensorFlowTestCase):
with self.test_session(use_gpu=True):
self.assertAllClose(y, self.evaluate(y_tf))
+ @test_util.run_deprecated_v1
def testNoOp(self):
x_shape = [10, 10, 10]
x = np.random.uniform(size=x_shape)
offset_height, offset_width = [0, 0]
self._assertReturns(x, x_shape, offset_height, offset_width, x, x_shape)
+ @test_util.run_deprecated_v1
def testPadding(self):
x = [1, 2, 3, 4, 5, 6, 7, 8, 9]
x_shape = [3, 3, 1]
@@ -1932,6 +1962,7 @@ class PadToBoundingBoxTest(test_util.TensorFlowTestCase):
y_shape = [3, 4, 1]
self._assertReturns(x, x_shape, offset_height, offset_width, y, y_shape)
+ @test_util.run_deprecated_v1
def testShapeInference(self):
self._assertShapeInference([55, 66, 3], 55, 66, [55, 66, 3])
self._assertShapeInference([50, 60, 3], 55, 66, [55, 66, 3])
@@ -1945,6 +1976,7 @@ class PadToBoundingBoxTest(test_util.TensorFlowTestCase):
self._assertShapeInference([None, None, None], 55, 66, [55, 66, None])
self._assertShapeInference(None, 55, 66, [55, 66, None])
+ @test_util.run_deprecated_v1
def testNon3DInput(self):
# Input image is not 3D
x = [0] * 15
@@ -1956,6 +1988,7 @@ class PadToBoundingBoxTest(test_util.TensorFlowTestCase):
target_width,
"'image' must have either 3 or 4 dimensions.")
+ @test_util.run_deprecated_v1
def testZeroLengthInput(self):
# Input image has 0-length dimension(s).
# Each line is a test configuration:
@@ -1988,6 +2021,7 @@ class PadToBoundingBoxTest(test_util.TensorFlowTestCase):
"all dims of \\'image.shape\\' must be > 0",
use_tensor_inputs_options=[True])
+ @test_util.run_deprecated_v1
def testBadParams(self):
x_shape = [3, 3, 1]
x = np.zeros(x_shape)
@@ -2002,6 +2036,7 @@ class PadToBoundingBoxTest(test_util.TensorFlowTestCase):
for config_item in test_config:
self._assertRaises(x, x_shape, *config_item)
+ @test_util.run_deprecated_v1
def testNameScope(self):
image = array_ops.placeholder(dtypes.float32, shape=[55, 66, 3])
y = image_ops.pad_to_bounding_box(image, 0, 0, 55, 66)
@@ -2109,6 +2144,7 @@ class SelectDistortedCropBoxTest(test_util.TensorFlowTestCase):
# TODO(wicke, shlens, dga): Restore this test so that it is no longer flaky.
# self.assertGreaterEqual(min(fraction_object_covered), min_object_covered)
+ @test_util.run_deprecated_v1
def testWholeImageBoundingBox(self):
height = 40
width = 50
@@ -2123,6 +2159,7 @@ class SelectDistortedCropBoxTest(test_util.TensorFlowTestCase):
aspect_ratio_range=(0.75, 1.33),
area_range=(0.05, 1.0))
+ @test_util.run_deprecated_v1
def testWithBoundingBox(self):
height = 40
width = 50
@@ -2153,6 +2190,7 @@ class SelectDistortedCropBoxTest(test_util.TensorFlowTestCase):
aspect_ratio_range=(0.75, 1.33),
area_range=(0.05, 1.0))
+ @test_util.run_deprecated_v1
def testSampleDistortedBoundingBoxShape(self):
with self.test_session(use_gpu=True):
image_size = constant_op.constant(
@@ -2248,6 +2286,7 @@ class ResizeImagesTest(test_util.TensorFlowTestCase):
else:
return False
+ @test_util.run_deprecated_v1
def testNoOp(self):
img_shape = [1, 6, 4, 1]
single_shape = [6, 4, 1]
@@ -2282,6 +2321,7 @@ class ResizeImagesTest(test_util.TensorFlowTestCase):
newshape = self.evaluate(yshape)
self.assertAllEqual(single_shape, newshape)
+ @test_util.run_deprecated_v1
def testTensorArguments(self):
img_shape = [1, 6, 4, 1]
single_shape = [6, 4, 1]
@@ -2343,6 +2383,7 @@ class ResizeImagesTest(test_util.TensorFlowTestCase):
_ = image_ops.resize_images(image, [6, None],
image_ops.ResizeMethod.BILINEAR)
+ @test_util.run_deprecated_v1
def testReturnDtype(self):
target_shapes = [[6, 4], [3, 2], [
array_ops.placeholder(dtypes.int32),
@@ -2591,6 +2632,7 @@ class ResizeImagesTest(test_util.TensorFlowTestCase):
value[use_gpu] = self.evaluate(out_op)
self.assertAllClose(value[True], value[False], rtol=1e-5, atol=1e-5)
+ @test_util.run_deprecated_v1
def testShapeInference(self):
self._assertShapeInference([50, 60, 3], [55, 66], [55, 66, 3])
self._assertShapeInference([55, 66, 3], [55, 66], [55, 66, 3])
@@ -2611,6 +2653,7 @@ class ResizeImagesTest(test_util.TensorFlowTestCase):
self._assertShapeInference([59, 60, None], [55, 66], [55, 66, None])
self._assertShapeInference([None, None, None], [55, 66], [55, 66, None])
+ @test_util.run_deprecated_v1
def testNameScope(self):
img_shape = [1, 3, 2, 1]
with self.test_session(use_gpu=True):
@@ -2661,6 +2704,7 @@ class ResizeImagesTest(test_util.TensorFlowTestCase):
preserve_aspect_ratio, use_tensor_inputs)
self.assertShapeEqual(y, ops.convert_to_tensor(y_tf))
+ @test_util.run_deprecated_v1
def testPreserveAspectRatioMultipleImages(self):
x_shape = [10, 100, 100, 10]
x = np.random.uniform(size=x_shape)
@@ -2668,36 +2712,42 @@ class ResizeImagesTest(test_util.TensorFlowTestCase):
self._assertResizeCheckShape(x, x_shape, [250, 250], [10, 250, 250, 10],
preserve_aspect_ratio=False)
+ @test_util.run_deprecated_v1
def testPreserveAspectRatioNoOp(self):
x_shape = [10, 10, 10]
x = np.random.uniform(size=x_shape)
self._assertResizeEqual(x, x_shape, x, x_shape)
+ @test_util.run_deprecated_v1
def testPreserveAspectRatioSmaller(self):
x_shape = [100, 100, 10]
x = np.random.uniform(size=x_shape)
self._assertResizeCheckShape(x, x_shape, [75, 50], [50, 50, 10])
+ @test_util.run_deprecated_v1
def testPreserveAspectRatioSmallerMultipleImages(self):
x_shape = [10, 100, 100, 10]
x = np.random.uniform(size=x_shape)
self._assertResizeCheckShape(x, x_shape, [75, 50], [10, 50, 50, 10])
+ @test_util.run_deprecated_v1
def testPreserveAspectRatioLarger(self):
x_shape = [100, 100, 10]
x = np.random.uniform(size=x_shape)
self._assertResizeCheckShape(x, x_shape, [150, 200], [150, 150, 10])
+ @test_util.run_deprecated_v1
def testPreserveAspectRatioSameRatio(self):
x_shape = [1920, 1080, 3]
x = np.random.uniform(size=x_shape)
self._assertResizeCheckShape(x, x_shape, [3840, 2160], [3840, 2160, 3])
+ @test_util.run_deprecated_v1
def testPreserveAspectRatioSquare(self):
x_shape = [299, 299, 3]
x = np.random.uniform(size=x_shape)
@@ -2767,12 +2817,14 @@ class ResizeImageWithPadTest(test_util.TensorFlowTestCase):
y = image_ops.resize_image_with_pad(image, height, width)
self.assertEqual(y.get_shape().as_list(), post_shape)
+ @test_util.run_deprecated_v1
def testNoOp(self):
x_shape = [10, 10, 10]
x = np.random.uniform(size=x_shape)
self._assertReturns(x, x_shape, x, x_shape)
+ @test_util.run_deprecated_v1
def testPad(self):
# Reduce vertical dimension
x = [1, 2, 3, 4, 5, 6, 7, 8]
@@ -2863,12 +2915,14 @@ class ResizeImageWithCropOrPadTest(test_util.TensorFlowTestCase):
y = image_ops.resize_image_with_crop_or_pad(image, height, width)
self.assertEqual(y.get_shape().as_list(), post_shape)
+ @test_util.run_deprecated_v1
def testNoOp(self):
x_shape = [10, 10, 10]
x = np.random.uniform(size=x_shape)
self._assertReturns(x, x_shape, x, x_shape)
+ @test_util.run_deprecated_v1
def testPad(self):
# Pad even along col.
x = [1, 2, 3, 4, 5, 6, 7, 8]
@@ -2906,6 +2960,7 @@ class ResizeImageWithCropOrPadTest(test_util.TensorFlowTestCase):
self._assertReturns(x, x_shape, y, y_shape)
+ @test_util.run_deprecated_v1
def testCrop(self):
# Crop even along col.
x = [1, 2, 3, 4, 5, 6, 7, 8]
@@ -2943,6 +2998,7 @@ class ResizeImageWithCropOrPadTest(test_util.TensorFlowTestCase):
self._assertReturns(x, x_shape, y, y_shape)
+ @test_util.run_deprecated_v1
def testCropAndPad(self):
# Pad along row but crop along col.
x = [1, 2, 3, 4, 5, 6, 7, 8]
@@ -2962,6 +3018,7 @@ class ResizeImageWithCropOrPadTest(test_util.TensorFlowTestCase):
self._assertReturns(x, x_shape, y, y_shape)
+ @test_util.run_deprecated_v1
def testShapeInference(self):
self._assertShapeInference([50, 60, 3], 55, 66, [55, 66, 3])
self._assertShapeInference([55, 66, 3], 55, 66, [55, 66, 3])
@@ -2983,6 +3040,7 @@ class ResizeImageWithCropOrPadTest(test_util.TensorFlowTestCase):
self._assertShapeInference([None, None, None], 55, 66, [55, 66, None])
self._assertShapeInference(None, 55, 66, [55, 66, None])
+ @test_util.run_deprecated_v1
def testNon3DInput(self):
# Input image is not 3D
x = [0] * 15
@@ -2996,6 +3054,7 @@ class ResizeImageWithCropOrPadTest(test_util.TensorFlowTestCase):
self._assertRaises(x, x_shape, target_height, target_width,
"'image' must have either 3 or 4 dimensions.")
+ @test_util.run_deprecated_v1
def testZeroLengthInput(self):
# Input image has 0-length dimension(s).
target_height, target_width = [1, 1]
@@ -3021,6 +3080,7 @@ class ResizeImageWithCropOrPadTest(test_util.TensorFlowTestCase):
"all dims of \\'image.shape\\' must be > 0",
use_tensor_inputs_options=[True])
+ @test_util.run_deprecated_v1
def testBadParams(self):
x_shape = [4, 4, 1]
x = np.zeros(x_shape)
@@ -3035,6 +3095,7 @@ class ResizeImageWithCropOrPadTest(test_util.TensorFlowTestCase):
self._assertRaises(x, x_shape, target_height, target_width,
"target_width must be > 0")
+ @test_util.run_deprecated_v1
def testNameScope(self):
image = array_ops.placeholder(dtypes.float32, shape=[50, 60, 3])
y = image_ops.resize_image_with_crop_or_pad(image, 55, 66)
@@ -3118,6 +3179,7 @@ class JpegTest(test_util.TensorFlowTestCase):
image1_crop, image2 = self.evaluate([image1_crop, image2])
self.assertAllEqual(image1_crop, image2)
+ @test_util.run_deprecated_v1
def testCropAndDecodeJpegWithInvalidCropWindow(self):
with self.cached_session() as sess:
# Encode it, then decode it, then encode it
@@ -3194,6 +3256,7 @@ class JpegTest(test_util.TensorFlowTestCase):
# The images should be the same.
self.assertAllClose(image1, image2)
+ @test_util.run_deprecated_v1
def testShape(self):
with self.test_session(use_gpu=True) as sess:
jpeg = constant_op.constant("nonsense")
@@ -3202,6 +3265,7 @@ class JpegTest(test_util.TensorFlowTestCase):
self.assertEqual(image.get_shape().as_list(),
[None, None, channels or None])
+ @test_util.run_deprecated_v1
def testExtractJpegShape(self):
# Read a real jpeg and verify shape.
path = ("tensorflow/core/lib/jpeg/testdata/"
@@ -3212,6 +3276,7 @@ class JpegTest(test_util.TensorFlowTestCase):
[image_shape] = sess.run([image_ops.extract_jpeg_shape(jpeg)])
self.assertEqual(image_shape.tolist(), [256, 128, 3])
+ @test_util.run_deprecated_v1
def testExtractJpegShapeforCmyk(self):
# Read a cmyk jpeg image, and verify its shape.
path = ("tensorflow/core/lib/jpeg/testdata/"
@@ -3293,6 +3358,7 @@ class PngTest(test_util.TensorFlowTestCase):
self.assertEqual(2, image0.shape[-1])
self.assertAllEqual(image0, image1)
+ @test_util.run_deprecated_v1
def testShape(self):
with self.test_session(use_gpu=True):
png = constant_op.constant("nonsense")
@@ -3337,6 +3403,7 @@ class GifTest(test_util.TensorFlowTestCase):
self._testValid("scan.gif")
self._testValid("optimized.gif")
+ @test_util.run_deprecated_v1
def testShape(self):
with self.test_session(use_gpu=True) as sess:
gif = constant_op.constant("nonsense")
@@ -3363,6 +3430,7 @@ class ConvertImageTest(test_util.TensorFlowTestCase):
self.assertTrue(y_saturate.dtype == output_dtype)
self.assertAllClose(y_saturate.eval(), y_np, atol=1e-5)
+ @test_util.run_deprecated_v1
def testNoConvert(self):
# Make sure converting to the same data type creates only an identity op
with self.test_session(use_gpu=True):
@@ -3372,6 +3440,7 @@ class ConvertImageTest(test_util.TensorFlowTestCase):
self.assertEquals(y.op.type, "Identity")
self.assertEquals(y.op.inputs[0], image)
+ @test_util.run_deprecated_v1
def testConvertBetweenInteger(self):
# Make sure converting to between integer types scales appropriately
with self.test_session(use_gpu=True):
@@ -3380,6 +3449,7 @@ class ConvertImageTest(test_util.TensorFlowTestCase):
self._convert([0, 2**32], dtypes.int64, dtypes.int32, [0, 1])
self._convert([0, 1], dtypes.int32, dtypes.int64, [0, 2**32])
+ @test_util.run_deprecated_v1
def testConvertBetweenFloat(self):
# Make sure converting to between float types does nothing interesting
with self.test_session(use_gpu=True):
@@ -3388,6 +3458,7 @@ class ConvertImageTest(test_util.TensorFlowTestCase):
self._convert([-1.0, 0, 1.0, 200000], dtypes.float64, dtypes.float32,
[-1.0, 0, 1.0, 200000])
+ @test_util.run_deprecated_v1
def testConvertBetweenIntegerAndFloat(self):
# Make sure converting from and to a float type scales appropriately
with self.test_session(use_gpu=True):
@@ -3396,6 +3467,7 @@ class ConvertImageTest(test_util.TensorFlowTestCase):
self._convert([0, 1.1 / 255.0, 1], dtypes.float32, dtypes.uint8,
[0, 1, 255])
+ @test_util.run_deprecated_v1
def testConvertBetweenInt16AndInt8(self):
with self.test_session(use_gpu=True):
# uint8, uint16
@@ -3587,6 +3659,7 @@ class TotalVariationTest(test_util.TensorFlowTestCase):
class FormatTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testFormats(self):
prefix = "tensorflow/core/lib"
paths = ("png/testdata/lena_gray.png", "jpeg/testdata/jpeg_merge_test1.jpg",
@@ -3619,6 +3692,7 @@ class FormatTest(test_util.TensorFlowTestCase):
class NonMaxSuppressionTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testSelectFromThreeClusters(self):
boxes_np = [[0, 0, 1, 1], [0, 0.1, 1, 1.1], [0, -0.1, 1, 0.9],
[0, 10, 1, 11], [0, 10.1, 1, 11.1], [0, 100, 1, 101]]
@@ -3634,6 +3708,7 @@ class NonMaxSuppressionTest(test_util.TensorFlowTestCase):
boxes, scores, max_output_size, iou_threshold).eval()
self.assertAllClose(selected_indices, [3, 0, 5])
+ @test_util.run_deprecated_v1
def testInvalidShape(self):
# The boxes should be 2D of shape [num_boxes, 4].
with self.assertRaisesRegexp(ValueError,
@@ -3676,6 +3751,7 @@ class NonMaxSuppressionTest(test_util.TensorFlowTestCase):
scores = constant_op.constant([0.9])
image_ops.non_max_suppression(boxes, scores, 3, [[0.5]])
+ @test_util.run_deprecated_v1
def testDataTypes(self):
# Test case for GitHub issue 20199.
boxes_np = [[0, 0, 1, 1], [0, 0.1, 1, 1.1], [0, -0.1, 1, 0.9],
@@ -3720,6 +3796,7 @@ class NonMaxSuppressionTest(test_util.TensorFlowTestCase):
class NonMaxSuppressionPaddedTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testSelectFromThreeClusters(self):
boxes_np = [[0, 0, 1, 1], [0, 0.1, 1, 1.1], [0, -0.1, 1, 0.9],
[0, 10, 1, 11], [0, 10.1, 1, 11.1], [0, 100, 1, 101]]
@@ -3752,6 +3829,7 @@ class NonMaxSuppressionPaddedTest(test_util.TensorFlowTestCase):
self.assertAllClose(selected_indices.eval(), [3, 0, 5])
self.assertEqual(num_valid.eval(), 3)
+ @test_util.run_deprecated_v1
def testSelectFromContinuousOverLap(self):
boxes_np = [[0, 0, 1, 1], [0, 0.2, 1, 1.2], [0, 0.4, 1, 1.4],
[0, 0.6, 1, 1.6], [0, 0.8, 1, 1.8], [0, 2, 1, 2]]
@@ -3779,6 +3857,7 @@ class NonMaxSuppressionPaddedTest(test_util.TensorFlowTestCase):
class NonMaxSuppressionWithOverlapsTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testSelectOneFromThree(self):
overlaps_np = [
[1.0, 0.7, 0.2],
@@ -3804,6 +3883,7 @@ class NonMaxSuppressionWithOverlapsTest(test_util.TensorFlowTestCase):
class VerifyCompatibleImageShapesTest(test_util.TensorFlowTestCase):
"""Tests utility function used by ssim() and psnr()."""
+ @test_util.run_deprecated_v1
def testWrongDims(self):
img = array_ops.placeholder(dtype=dtypes.float32)
img_np = np.array((2, 2))
@@ -3813,6 +3893,7 @@ class VerifyCompatibleImageShapesTest(test_util.TensorFlowTestCase):
with self.assertRaises(errors.InvalidArgumentError):
sess.run(checks, {img: img_np})
+ @test_util.run_deprecated_v1
def testShapeMismatch(self):
img1 = array_ops.placeholder(dtype=dtypes.float32)
img2 = array_ops.placeholder(dtype=dtypes.float32)
@@ -3853,6 +3934,7 @@ class PSNRTest(test_util.TensorFlowTestCase):
"""Returns an image or image batch with given shape."""
return np.random.rand(*shape).astype(np.float32) * max_val
+ @test_util.run_deprecated_v1
def testPSNRSingleImage(self):
image1 = self._RandomImage((8, 8, 1), 1)
image2 = self._RandomImage((8, 8, 1), 1)
@@ -3866,6 +3948,7 @@ class PSNRTest(test_util.TensorFlowTestCase):
tf_psnr = image_ops.psnr(tf_image1, tf_image2, 1.0, "psnr").eval()
self.assertAllClose(psnr, tf_psnr, atol=0.001)
+ @test_util.run_deprecated_v1
def testPSNRMultiImage(self):
image1 = self._RandomImage((10, 8, 8, 1), 1)
image2 = self._RandomImage((10, 8, 8, 1), 1)
@@ -3879,6 +3962,7 @@ class PSNRTest(test_util.TensorFlowTestCase):
tf_psnr = image_ops.psnr(tf_image1, tf_image2, 1, "psnr").eval()
self.assertAllClose(psnr, tf_psnr, atol=0.001)
+ @test_util.run_deprecated_v1
def testGoldenPSNR(self):
q20, q72, q95 = self._LoadTestImages()
@@ -3903,6 +3987,7 @@ class PSNRTest(test_util.TensorFlowTestCase):
self.assertAllClose(psnr2, tf_psnr2, atol=0.001)
self.assertAllClose(psnr3, tf_psnr3, atol=0.001)
+ @test_util.run_deprecated_v1
def testInfinity(self):
q20, _, _ = self._LoadTestImages()
psnr = self._PSNR_NumPy(q20, q20, 1)
@@ -3911,6 +3996,7 @@ class PSNRTest(test_util.TensorFlowTestCase):
tf_psnr = image_ops.psnr(tf_q20, tf_q20, 1, "psnr").eval()
self.assertAllClose(psnr, tf_psnr, atol=0.001)
+ @test_util.run_deprecated_v1
def testInt(self):
img1 = self._RandomImage((10, 8, 8, 1), 255)
img2 = self._RandomImage((10, 8, 8, 1), 255)
@@ -3952,6 +4038,7 @@ class SSIMTest(test_util.TensorFlowTestCase):
"""Returns an image or image batch with given shape."""
return np.random.rand(*shape).astype(np.float32) * max_val
+ @test_util.run_deprecated_v1
def testAgainstMatlab(self):
"""Tests against values produced by Matlab."""
img = self._LoadTestImages()
@@ -3989,6 +4076,7 @@ class SSIMTest(test_util.TensorFlowTestCase):
with self.test_session(use_gpu=True):
self.assertAllClose(expected, self.evaluate(ssim), atol=1e-4)
+ @test_util.run_deprecated_v1
def testNegative(self):
"""Tests against negative SSIM index."""
step = np.expand_dims(np.arange(0, 256, 16, dtype=np.uint8), axis=0)
@@ -4003,6 +4091,7 @@ class SSIMTest(test_util.TensorFlowTestCase):
with self.test_session(use_gpu=True):
self.assertLess(ssim.eval(), 0)
+ @test_util.run_deprecated_v1
def testInt(self):
img1 = self._RandomImage((1, 16, 16, 3), 255)
img2 = self._RandomImage((1, 16, 16, 3), 255)
@@ -4044,6 +4133,7 @@ class MultiscaleSSIMTest(test_util.TensorFlowTestCase):
"""Returns an image or image batch with given shape."""
return np.random.rand(*shape).astype(np.float32) * max_val
+ @test_util.run_deprecated_v1
def testAgainstMatlab(self):
"""Tests against MS-SSIM computed with Matlab implementation.
@@ -4060,6 +4150,7 @@ class MultiscaleSSIMTest(test_util.TensorFlowTestCase):
self.assertAllClose(expected, np.squeeze(scores), atol=1e-4)
+ @test_util.run_deprecated_v1
def testUnweightedIsDifferentiable(self):
img = self._LoadTestImages()
ph = [array_ops.placeholder(dtype=dtypes.float32) for _ in range(2)]
@@ -4121,6 +4212,7 @@ class MultiscaleSSIMTest(test_util.TensorFlowTestCase):
self.assertTrue(np.all(msssim >= 0.0))
self.assertTrue(np.all(msssim <= 1.0))
+ @test_util.run_deprecated_v1
def testInt(self):
img1 = self._RandomImage((1, 180, 240, 3), 255)
img2 = self._RandomImage((1, 180, 240, 3), 255)
diff --git a/tensorflow/python/ops/losses/util_test.py b/tensorflow/python/ops/losses/util_test.py
index df2e60e2e45..22a8eaae266 100644
--- a/tensorflow/python/ops/losses/util_test.py
+++ b/tensorflow/python/ops/losses/util_test.py
@@ -20,12 +20,14 @@ from __future__ import print_function
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops.losses import util
from tensorflow.python.platform import test
class LossesUtilTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testGetRegularizationLoss(self):
# Empty regularization collection should evaluate to 0.0.
with self.cached_session():
diff --git a/tensorflow/python/ops/math_grad_test.py b/tensorflow/python/ops/math_grad_test.py
index d1fe834fc78..88aa48271f3 100644
--- a/tensorflow/python/ops/math_grad_test.py
+++ b/tensorflow/python/ops/math_grad_test.py
@@ -23,6 +23,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import gradients
@@ -52,6 +53,7 @@ class SquaredDifferenceOpTest(test.TestCase):
self.assertLess(left_err, 1e-10)
self.assertLess(right_err, 1e-10)
+ @test_util.run_deprecated_v1
def testGrad(self):
self._testGrad([1, 2, 3, 2], [3, 2])
self._testGrad([2, 4], [3, 2, 4])
@@ -83,6 +85,7 @@ class AbsOpTest(test.TestCase):
value, shape, output, output.get_shape().as_list())
self.assertLess(error, max_error)
+ @test_util.run_deprecated_v1
def testComplexAbs(self):
# Bias random test values away from zero to avoid numeric instabilities.
self._testGrad(
@@ -99,6 +102,7 @@ class AbsOpTest(test.TestCase):
class MinOrMaxGradientTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testMinGradient(self):
inputs = constant_op.constant([1.0], dtype=dtypes.float32)
outputs = math_ops.reduce_min(array_ops.concat([inputs, inputs], 0))
@@ -106,6 +110,7 @@ class MinOrMaxGradientTest(test.TestCase):
error = gradient_checker.compute_gradient_error(inputs, [1], outputs, [])
self.assertLess(error, 1e-4)
+ @test_util.run_deprecated_v1
def testMaxGradient(self):
inputs = constant_op.constant([1.0], dtype=dtypes.float32)
outputs = math_ops.reduce_max(array_ops.concat([inputs, inputs], 0))
@@ -116,6 +121,7 @@ class MinOrMaxGradientTest(test.TestCase):
class MaximumOrMinimumGradientTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testMaximumGradient(self):
inputs = constant_op.constant([1.0, 2.0, 3.0, 4.0], dtype=dtypes.float32)
outputs = math_ops.maximum(inputs, 3.0)
@@ -123,6 +129,7 @@ class MaximumOrMinimumGradientTest(test.TestCase):
error = gradient_checker.compute_gradient_error(inputs, [4], outputs, [4])
self.assertLess(error, 1e-4)
+ @test_util.run_deprecated_v1
def testMinimumGradient(self):
inputs = constant_op.constant([1.0, 2.0, 3.0, 4.0], dtype=dtypes.float32)
outputs = math_ops.minimum(inputs, 2.0)
@@ -133,6 +140,7 @@ class MaximumOrMinimumGradientTest(test.TestCase):
class ProdGradientTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testProdGradient(self):
inputs = constant_op.constant([[1., 2.], [3., 4.]],
dtype=dtypes.float32)
@@ -143,6 +151,7 @@ class ProdGradientTest(test.TestCase):
outputs, outputs.get_shape().as_list())
self.assertLess(error, 1e-4)
+ @test_util.run_deprecated_v1
def testProdGradientForNegativeAxis(self):
inputs = constant_op.constant([[1., 2.], [3., 4.]],
dtype=dtypes.float32)
@@ -153,6 +162,7 @@ class ProdGradientTest(test.TestCase):
outputs, outputs.get_shape().as_list())
self.assertLess(error, 1e-4)
+ @test_util.run_deprecated_v1
def testProdGradientComplex(self):
for dtype in dtypes.complex64, dtypes.complex128:
inputs = constant_op.constant([[1 + 3j, 2 - 1j], [3j, 4]],
@@ -164,6 +174,7 @@ class ProdGradientTest(test.TestCase):
outputs, outputs.get_shape().as_list())
self.assertLess(error, 1e-4)
+ @test_util.run_deprecated_v1
def testProdGradientForNegativeAxisComplex(self):
for dtype in dtypes.complex64, dtypes.complex128:
inputs = constant_op.constant([[1 + 3j, 2 - 1j], [3j, 4]],
@@ -178,6 +189,7 @@ class ProdGradientTest(test.TestCase):
class SegmentMinOrMaxGradientTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testSegmentMinGradient(self):
data = constant_op.constant([1.0, 2.0, 3.0], dtype=dtypes.float32)
segment_ids = constant_op.constant([0, 0, 1], dtype=dtypes.int64)
@@ -187,6 +199,7 @@ class SegmentMinOrMaxGradientTest(test.TestCase):
[2])
self.assertLess(error, 1e-4)
+ @test_util.run_deprecated_v1
def testSegmentMaxGradient(self):
data = constant_op.constant([1.0, 2.0, 3.0], dtype=dtypes.float32)
segment_ids = constant_op.constant([0, 0, 1], dtype=dtypes.int64)
@@ -196,6 +209,7 @@ class SegmentMinOrMaxGradientTest(test.TestCase):
[2])
self.assertLess(error, 1e-4)
+ @test_util.run_deprecated_v1
def testSegmentMinGradientWithTies(self):
inputs = constant_op.constant([1.0], dtype=dtypes.float32)
data = array_ops.concat([inputs, inputs], 0)
@@ -206,6 +220,7 @@ class SegmentMinOrMaxGradientTest(test.TestCase):
[1])
self.assertLess(error, 1e-4)
+ @test_util.run_deprecated_v1
def testSegmentMaxGradientWithTies(self):
inputs = constant_op.constant([1.0], dtype=dtypes.float32)
data = array_ops.concat([inputs, inputs], 0)
@@ -219,6 +234,7 @@ class SegmentMinOrMaxGradientTest(test.TestCase):
class FloorModGradientTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testFloorModGradient(self):
# Making sure the input is not near the discontinuity point where
# x/y == floor(x/y)
@@ -233,6 +249,7 @@ class FloorModGradientTest(test.TestCase):
class DivNoNanGradientTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testBasicGradient(self):
inputs = constant_op.constant(np.arange(-3, 3),
dtype=dtypes.float32)
@@ -244,6 +261,7 @@ class DivNoNanGradientTest(test.TestCase):
outputs.get_shape().as_list())
self.assertLess(error, 1e-4)
+ @test_util.run_deprecated_v1
def testGradientWithDenominatorIsZero(self):
x = constant_op.constant(np.arange(-3, 3),
dtype=dtypes.float32)
@@ -263,6 +281,7 @@ class XlogyTest(test.TestCase):
xlogy_ygrad = self.evaluate(gradients.gradients(math_ops.xlogy(x, y), y)[0])
return xlogy_xgrad, xlogy_ygrad
+ @test_util.run_deprecated_v1
def testNonZeroValuesGrad(self):
for dtype in [dtypes.float16, dtypes.float32, dtypes.float64]:
x = constant_op.constant(0.1, dtype=dtype)
@@ -273,6 +292,7 @@ class XlogyTest(test.TestCase):
self.assertAllClose(xlogy_expected_xgrad, xlogy_xgrad)
self.assertAllClose(xlogy_expected_ygrad, xlogy_ygrad)
+ @test_util.run_deprecated_v1
def testZeroXGrad(self):
for dtype in [dtypes.float16, dtypes.float32, dtypes.float64]:
x = constant_op.constant(0., dtype=dtype)
@@ -282,6 +302,7 @@ class XlogyTest(test.TestCase):
self.assertAllClose(zero, xlogy_xgrad)
self.assertAllClose(zero, xlogy_ygrad)
+ @test_util.run_deprecated_v1
def testZeroYGrad(self):
for dtype in [dtypes.float16, dtypes.float32, dtypes.float64]:
x = constant_op.constant(0.1, dtype=dtype)
@@ -290,6 +311,7 @@ class XlogyTest(test.TestCase):
self.assertAllClose(-np.inf, xlogy_xgrad)
self.assertAllClose(np.inf, xlogy_ygrad)
+ @test_util.run_deprecated_v1
def testZeroXYGrad(self):
for dtype in [dtypes.float16, dtypes.float32, dtypes.float64]:
x = constant_op.constant(0., dtype=dtype)
@@ -307,6 +329,7 @@ class XdivyTest(test.TestCase):
xdivy_ygrad = self.evaluate(gradients.gradients(math_ops.xdivy(x, y), y)[0])
return xdivy_xgrad, xdivy_ygrad
+ @test_util.run_deprecated_v1
def testNonZeroValuesGrad(self):
for dtype in [dtypes.float16, dtypes.float32, dtypes.float64]:
x = constant_op.constant(0.1, dtype=dtype)
@@ -317,6 +340,7 @@ class XdivyTest(test.TestCase):
self.assertAllClose(xdivy_expected_xgrad, xdivy_xgrad)
self.assertAllClose(xdivy_expected_ygrad, xdivy_ygrad)
+ @test_util.run_deprecated_v1
def testZeroXGrad(self):
for dtype in [dtypes.float16, dtypes.float32, dtypes.float64]:
x = constant_op.constant(0., dtype=dtype)
@@ -326,6 +350,7 @@ class XdivyTest(test.TestCase):
self.assertAllClose(zero, xdivy_xgrad)
self.assertAllClose(zero, xdivy_ygrad)
+ @test_util.run_deprecated_v1
def testZeroYGrad(self):
for dtype in [dtypes.float16, dtypes.float32, dtypes.float64]:
x = constant_op.constant(0.1, dtype=dtype)
@@ -334,6 +359,7 @@ class XdivyTest(test.TestCase):
self.assertAllClose(np.inf, xdivy_xgrad)
self.assertAllClose(-np.inf, xdivy_ygrad)
+ @test_util.run_deprecated_v1
def testZeroXYGrad(self):
for dtype in [dtypes.float16, dtypes.float32, dtypes.float64]:
x = constant_op.constant(0., dtype=dtype)
diff --git a/tensorflow/python/ops/math_ops_test.py b/tensorflow/python/ops/math_ops_test.py
index cd45b6f1364..add1621a56b 100644
--- a/tensorflow/python/ops/math_ops_test.py
+++ b/tensorflow/python/ops/math_ops_test.py
@@ -92,6 +92,7 @@ class ReduceTest(test_util.TensorFlowTestCase):
class LogSumExpTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testReduceLogSumExp(self):
for dtype in [np.float16, np.float32, np.double]:
x_np = np.random.rand(5, 5).astype(dtype)
@@ -120,6 +121,7 @@ class LogSumExpTest(test_util.TensorFlowTestCase):
y_tf_np = self.evaluate(y_tf)
self.assertAllClose(y_tf_np, y_np)
+ @test_util.run_deprecated_v1
def testKeepDims(self):
for dtype in [np.float16, np.float32, np.double]:
x_np = np.random.rand(5, 5).astype(dtype)
@@ -129,6 +131,7 @@ class LogSumExpTest(test_util.TensorFlowTestCase):
y_np = log(np.sum(exp(x_np), keepdims=True))
self.assertAllClose(y_tf_np, y_np)
+ @test_util.run_deprecated_v1
def testOverflow(self):
x = [1000, 1001, 1002, 1003]
for dtype in [np.float16, np.float32, np.double]:
@@ -146,6 +149,7 @@ class LogSumExpTest(test_util.TensorFlowTestCase):
y_np = log(np.sum(exp(x_np - max_np))) + max_np
self.assertAllClose(y_tf_np, y_np)
+ @test_util.run_deprecated_v1
def testUnderflow(self):
x = [-1000, -1001, -1002, -1003]
for dtype in [np.float16, np.float32, np.double]:
@@ -163,6 +167,7 @@ class LogSumExpTest(test_util.TensorFlowTestCase):
y_np = log(np.sum(exp(x_np - max_np))) + max_np
self.assertAllClose(y_tf_np, y_np)
+ @test_util.run_deprecated_v1
def testInfinity(self):
with self.session(use_gpu=True):
res = math_ops.reduce_logsumexp(-np.inf).eval()
@@ -186,6 +191,7 @@ class RoundTest(test_util.TensorFlowTestCase):
class ModTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testFloat(self):
x = [0.5, 0.7, 0.3]
for dtype in [np.float32, np.double]:
@@ -256,6 +262,7 @@ class ApproximateEqualTest(test_util.TensorFlowTestCase):
z_tf = self.evaluate(math_ops.approximate_equal(x, y, tolerance=0.0001))
self.assertAllEqual(z, z_tf)
+ @test_util.run_deprecated_v1
def testApproximateEqualShape(self):
for dtype in [np.float32, np.double]:
x = np.array([1, 2], dtype=dtype)
@@ -309,6 +316,7 @@ class ScalarMulTest(test_util.TensorFlowTestCase):
class AccumulateNTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testFloat(self):
np.random.seed(12345)
x = [np.random.random((1, 2, 3, 4, 5)) - 0.5 for _ in range(5)]
@@ -317,6 +325,7 @@ class AccumulateNTest(test_util.TensorFlowTestCase):
self.assertAllClose(sum(x), math_ops.accumulate_n(tf_x).eval())
self.assertAllClose(x[0] * 5, math_ops.accumulate_n([tf_x[0]] * 5).eval())
+ @test_util.run_deprecated_v1
def testInt(self):
np.random.seed(54321)
x = [np.random.randint(-128, 128, (5, 4, 3, 2, 1)) for _ in range(6)]
@@ -328,6 +337,7 @@ class AccumulateNTest(test_util.TensorFlowTestCase):
class AddNTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testPartials(self):
"""Test that previously revealed a bug in buffer forwarding for AddN."""
partials = []
@@ -341,6 +351,7 @@ class AddNTest(test_util.TensorFlowTestCase):
with self.session(use_gpu=True):
self.assertAllEqual(res.eval(), 100)
+ @test_util.run_deprecated_v1
def testFloat(self):
np.random.seed(12345)
for num_inputs in range(1, 10):
@@ -351,6 +362,7 @@ class AddNTest(test_util.TensorFlowTestCase):
self.assertAllClose(x[0] * num_inputs,
math_ops.add_n([tf_x[0]] * num_inputs).eval())
+ @test_util.run_deprecated_v1
def testInt(self):
np.random.seed(54321)
for num_inputs in range(1, 10):
@@ -364,6 +376,7 @@ class AddNTest(test_util.TensorFlowTestCase):
self.assertAllEqual(x[0] * num_inputs,
math_ops.add_n([tf_x[0]] * num_inputs).eval())
+ @test_util.run_deprecated_v1
def testGrad(self):
np.random.seed(42)
for num_inputs in range(1, 10):
@@ -392,6 +405,7 @@ class DivAndModTest(test_util.TensorFlowTestCase):
divs = np.arange(-3, 0, .25).reshape(1, 12)
return nums, divs
+ @test_util.run_deprecated_v1
def testFloorModInt(self):
nums, divs = self.intTestData()
with self.cached_session():
@@ -401,6 +415,7 @@ class DivAndModTest(test_util.TensorFlowTestCase):
np_result = nums % divs
self.assertAllEqual(tf_result, np_result)
+ @test_util.run_deprecated_v1
def testFloorModFloat(self):
nums, divs = self.floatTestData()
with self.cached_session():
@@ -412,6 +427,7 @@ class DivAndModTest(test_util.TensorFlowTestCase):
# % array_ops.constant(divs)).eval()
# self.assertAllEqual(tf2_result, tf_result)
+ @test_util.run_deprecated_v1
def testTruncateModInt(self):
nums, divs = self.intTestData()
with self.cached_session():
@@ -419,6 +435,7 @@ class DivAndModTest(test_util.TensorFlowTestCase):
np_result = np.fmod(nums, divs)
self.assertAllEqual(tf_result, np_result)
+ @test_util.run_deprecated_v1
def testTruncateModFloat(self):
nums, divs = self.floatTestData()
with self.cached_session():
@@ -426,6 +443,7 @@ class DivAndModTest(test_util.TensorFlowTestCase):
np_result = np.fmod(nums, divs)
self.assertAllEqual(tf_result, np_result)
+ @test_util.run_deprecated_v1
def testDivideInt(self):
nums, divs = self.intTestData()
with self.cached_session():
@@ -437,12 +455,14 @@ class DivAndModTest(test_util.TensorFlowTestCase):
# // array_ops.constant(divs)).eval()
# self.assertAllEqual(tf2_result, tf_result)
+ @test_util.run_deprecated_v1
def testDivideName(self):
with self.cached_session():
op = math_ops.divide(
array_ops.constant(3), array_ops.constant(4), name="my_cool_divide")
self.assertEqual(op.name, "my_cool_divide:0")
+ @test_util.run_deprecated_v1
def testRealDiv(self):
nums, divs = self.floatTestData()
with self.cached_session():
@@ -450,12 +470,14 @@ class DivAndModTest(test_util.TensorFlowTestCase):
np_result = np.divide(nums, divs)
self.assertAllEqual(tf_result, np_result)
+ @test_util.run_deprecated_v1
def testComplexDiv(self):
foo = array_ops.constant([1. + 3.j])
with self.cached_session():
_ = math_ops.divide(foo, 1.).eval()
_ = math_ops.div(foo, 2.).eval()
+ @test_util.run_deprecated_v1
def testFloorDivGrad(self):
with self.cached_session():
a = variables.Variable(2.)
@@ -471,6 +493,7 @@ class DivAndModTest(test_util.TensorFlowTestCase):
[None if x is None else self.evaluate(x) for x in c_grad],
[None, None])
+ @test_util.run_deprecated_v1
def testConsistent(self):
nums, divs = self.intTestData()
with self.cached_session():
@@ -497,6 +520,7 @@ class DivAndModTest(test_util.TensorFlowTestCase):
class DivNoNanTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testBasic(self):
for dtype in [np.float32, np.float64]:
nums = np.arange(-10, 10, .25, dtype=dtype).reshape(80, 1)
diff --git a/tensorflow/python/ops/nn_batchnorm_test.py b/tensorflow/python/ops/nn_batchnorm_test.py
index 31b2790f2b8..e978f1d3260 100644
--- a/tensorflow/python/ops/nn_batchnorm_test.py
+++ b/tensorflow/python/ops/nn_batchnorm_test.py
@@ -71,6 +71,7 @@ class BatchNormalizationTest(test.TestCase):
gamma if scale_after_normalization else
None, epsilon)
+ @test_util.run_deprecated_v1
def testBatchNorm(self):
x_shape = [3, 5, 4, 2]
param_shape = [2]
@@ -169,16 +170,20 @@ class BatchNormalizationTest(test.TestCase):
shift_after_normalization, v,
err_tolerance)
+ @test_util.run_deprecated_v1
def testBatchNormInputGradient(self):
self._testBatchNormGradientInAllNeedConfigs(0, "x")
+ @test_util.run_deprecated_v1
def testBatchNormMeanGradient(self):
self._testBatchNormGradientInAllNeedConfigs(1, "mean")
+ @test_util.run_deprecated_v1
def testBatchNormVarianceGradient(self):
self._testBatchNormGradientInAllNeedConfigs(
2, "variance", err_tolerance=1e-03)
+ @test_util.run_deprecated_v1
def testBatchNormBetaGradient(self):
# Since beta does not exist when scale_after_normalization=False, we only
# test for scale_after_normalization=True.
@@ -187,6 +192,7 @@ class BatchNormalizationTest(test.TestCase):
self._testBatchNormGradient(3, "beta", scale_after_normalization, True,
v)
+ @test_util.run_deprecated_v1
def testBatchNormGammaGradient(self):
# If scale_after_normalization is False, backprop for gamma in v1
# will be 0. In version 2 of the API, if scale_after_normalization is False,
@@ -199,6 +205,7 @@ class BatchNormalizationTest(test.TestCase):
self._testBatchNormGradient(4, "gamma", True, shift_after_normalization,
2)
+ @test_util.run_deprecated_v1
def testBatchNormGradImpl(self):
x_shape = [7, 5, 4, 6]
param_shape = [6]
@@ -245,6 +252,7 @@ class BatchNormalizationTest(test.TestCase):
self.assertAllClose(
all_grads[i + len(to_check)], all_grads[i], atol=0.000001)
+ @test_util.run_deprecated_v1
def testBatchNormKeepDims(self):
"""Test for tf.nn.moments(..., keep_dims=True / False).
@@ -391,6 +399,7 @@ class SufficientStatisticsTest(test.TestCase):
if shift:
self.assertAllClose(np_s, tf_s, atol=0.000001)
+ @test_util.run_deprecated_v1
def testSuffStats(self):
for has_shape in [True, False]:
for keep_dims in [True, False]:
@@ -511,6 +520,7 @@ class MomentsTest(test.TestCase):
self.assertAllCloseAccordingToType(expected_mean, self.evaluate(mean))
self.assertAllCloseAccordingToType(expected_variance, self.evaluate(var))
+ @test_util.run_deprecated_v1
def testBasic(self):
for keep_dims in [False, True]:
for dtype in [dtypes.float32, dtypes.float16]:
@@ -519,6 +529,7 @@ class MomentsTest(test.TestCase):
self.RunMomentTestWithDynamicShape(
shape=[2, 3, 5, 4], axes=[0], keep_dims=keep_dims, dtype=dtype)
+ @test_util.run_deprecated_v1
def testGlobalNormalization(self):
for keep_dims in [False, True]:
for dtype in [dtypes.float32, dtypes.float16]:
@@ -533,6 +544,7 @@ class MomentsTest(test.TestCase):
keep_dims=keep_dims,
dtype=dtype)
+ @test_util.run_deprecated_v1
def testAxes(self):
for keep_dims in [False, True]:
for dtype in [dtypes.float32, dtypes.float16]:
@@ -573,9 +585,11 @@ class MomentsTest(test.TestCase):
print("Moments %s gradient err vs input %d = %g" % (from_y, i, err))
self.assertLess(err, 1e-11)
+ @test_util.run_deprecated_v1
def testMeanGlobalGradient(self):
self._testGlobalGradient(from_y="mean")
+ @test_util.run_deprecated_v1
def testVarGlobalGradient(self):
self._testGlobalGradient(from_y="var")
diff --git a/tensorflow/python/ops/nn_grad_test.py b/tensorflow/python/ops/nn_grad_test.py
index 8065df4b165..95e05a977b8 100644
--- a/tensorflow/python/ops/nn_grad_test.py
+++ b/tensorflow/python/ops/nn_grad_test.py
@@ -22,6 +22,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import gradients_impl
from tensorflow.python.ops import nn_grad # pylint: disable=unused-import
@@ -31,6 +32,7 @@ from tensorflow.python.platform import test
class Relu6OpTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testRelu6GradGrad(self):
inputs = constant_op.constant(
[[-2, -1, 1, 3], [5, 7, 8, 9]], dtype=dtypes.float32)
diff --git a/tensorflow/python/ops/nn_test.py b/tensorflow/python/ops/nn_test.py
index f7c8a7a70ac..a7ed834c723 100644
--- a/tensorflow/python/ops/nn_test.py
+++ b/tensorflow/python/ops/nn_test.py
@@ -49,6 +49,7 @@ class ZeroFractionTest(test_lib.TestCase):
nonzeros = np.count_nonzero(x.flatten())
return 1.0 - nonzeros / total_elements
+ @test_util.run_deprecated_v1
def testZeroFraction(self):
x_shape = [5, 17]
x_np = np.random.randint(0, 2, size=x_shape).astype(np.float32)
@@ -62,21 +63,25 @@ class ZeroFractionTest(test_lib.TestCase):
eps = 1e-8
self.assertAllClose(y_tf_np, y_np, eps)
+ @test_util.run_deprecated_v1
def testZeroFractionEmpty(self):
x = np.zeros(0)
y = self.evaluate(nn_impl.zero_fraction(x))
self.assertTrue(np.isnan(y))
+ @test_util.run_deprecated_v1
def testZeroFraction2_27Zeros(self):
sparsity = nn_impl.zero_fraction(
array_ops.zeros([int(2**27 * 1.01)], dtype=dtypes.int8))
self.assertAllClose(1.0, self.evaluate(sparsity))
+ @test_util.run_deprecated_v1
def testZeroFraction2_27Ones(self):
sparsity = nn_impl.zero_fraction(
array_ops.ones([int(2**27 * 1.01)], dtype=dtypes.int8))
self.assertAllClose(0.0, self.evaluate(sparsity))
+ @test_util.run_deprecated_v1
def testUnknownSize(self):
value = array_ops.placeholder(dtype=dtypes.float32)
sparsity = nn_impl.zero_fraction(value)
@@ -122,6 +127,7 @@ class SoftmaxTest(test_lib.TestCase, parameterized.TestCase):
self.assertAllClose(y_pos_axis_tf, z_gt_axis_tf, eps)
@parameterized.parameters(((5, 10),), ((2, 3, 4),))
+ @test_util.run_deprecated_v1
def testGradient(self, x_shape):
x_np = np.random.randn(*x_shape).astype(np.float64)
with self.cached_session():
@@ -157,6 +163,7 @@ class LogPoissonLossTest(test_lib.TestCase):
self.assertAllClose(y_tf_np, y_np, eps)
self.assertAllClose(y_tf_np_stirling, y_np_stirling, eps)
+ @test_util.run_deprecated_v1
def testGradient(self):
x_shape = [5, 10]
x_np = np.random.randn(*x_shape).astype(np.float64)
@@ -207,6 +214,7 @@ class LogSoftmaxTest(test_lib.TestCase, parameterized.TestCase):
self.assertAllClose(y_pos_axis_tf, z_gt_axis_tf, eps)
@parameterized.parameters(((5, 10),), ((2, 3, 4),))
+ @test_util.run_deprecated_v1
def testGradient(self, x_shape):
x_np = np.random.randn(*x_shape).astype(np.float64)
with self.cached_session():
@@ -229,6 +237,7 @@ class L2LossTest(test_lib.TestCase):
value = self.evaluate(l2loss)
self.assertAllClose(7.0, value)
+ @test_util.run_deprecated_v1
def testGradient(self):
x_shape = [20, 7, 3]
np.random.seed(1) # Make it reproducible.
@@ -276,6 +285,7 @@ class L2NormalizeTest(test_lib.TestCase):
y_tf = nn_impl.l2_normalize_v2(x_tf, dim)
self.assertAllClose(y_np, self.evaluate(y_tf))
+ @test_util.run_deprecated_v1
def testL2NormalizeGradient(self):
x_shape = [20, 7, 3]
np.random.seed(1)
@@ -361,6 +371,7 @@ class DropoutTest(test_lib.TestCase):
sorted_value = np.unique(np.sort(value[i, :]))
self.assertEqual(sorted_value.size, 1)
+ @test_util.run_deprecated_v1
def testDropoutPlaceholderKeepProb(self):
# Runs dropout with 0-1 tensor 10 times, sum the number of ones and validate
# that it is producing approximately the right number of ones over a large
@@ -389,6 +400,7 @@ class DropoutTest(test_lib.TestCase):
print(rel_error)
self.assertTrue(rel_error < 0.15)
+ @test_util.run_deprecated_v1
def testShapedDropoutUnknownShape(self):
x_dim = 40
y_dim = 30
@@ -422,6 +434,7 @@ class DropoutTest(test_lib.TestCase):
print(rel_error)
self.assertTrue(rel_error < 0.15)
+ @test_util.run_deprecated_v1
def testInvalidKeepProb(self):
x_dim = 40
y_dim = 30
@@ -437,6 +450,7 @@ class DropoutTest(test_lib.TestCase):
with self.assertRaises(ValueError):
nn_ops.dropout(t, array_ops.placeholder(dtypes.float32, shape=[2]))
+ @test_util.run_deprecated_v1
def testShapedDropoutShapeError(self):
# Runs shaped dropout and verifies an error is thrown on misshapen noise.
x_dim = 40
@@ -457,6 +471,7 @@ class DropoutTest(test_lib.TestCase):
_ = nn_ops.dropout(t, keep_prob, noise_shape=[x_dim, 1])
_ = nn_ops.dropout(t, keep_prob, noise_shape=[1, 1])
+ @test_util.run_deprecated_v1
def testNoDropoutFast(self):
x = array_ops.zeros((5,))
for p in 1, constant_op.constant(1.0):
@@ -938,6 +953,7 @@ class ReluTest(test_lib.TestCase):
z = self.evaluate(nn_ops.relu(constant_op.constant(x)))
self.assertAllEqual(y, z)
+ @test_util.run_deprecated_v1
def testNaNs(self):
# Test that relu(nan) = nan for various sizes.
for i in range(18):
@@ -966,6 +982,7 @@ class LeakyReluTest(test_lib.TestCase):
self.assertLessEqual(outputs.max(), 1.0)
self.assertAllClose(inputs, outputs)
+ @test_util.run_deprecated_v1
def testValues(self):
for dtype in [np.int32, np.int64, np.float16, np.float32, np.float64]:
np_values = np.array([-2, -1, 0, 1, 2], dtype=dtype)
@@ -977,6 +994,7 @@ class LeakyReluTest(test_lib.TestCase):
self.assertAllClose(
outputs, [-0.4, -0.2, 0.0, 1.0, 2.0], rtol=tol, atol=tol)
+ @test_util.run_deprecated_v1
def testName(self):
np_values = np.array([-2, -1, 0, 1, 2], dtype=np.float64)
outputs_with_name_set = nn_ops.leaky_relu(
@@ -990,6 +1008,7 @@ class LeakyReluTest(test_lib.TestCase):
class SwishTest(test_lib.TestCase):
+ @test_util.run_deprecated_v1
def testValues(self):
np_values = np.array(
[np.linspace(-10.0, 0.0, 100),
@@ -1004,6 +1023,7 @@ class SwishTest(test_lib.TestCase):
self.assertAllClose(actual_outputs, expected_outputs)
+ @test_util.run_deprecated_v1
def testGradients(self):
shape = [5, 3, 4]
sigma = 5
diff --git a/tensorflow/python/ops/nn_xent_test.py b/tensorflow/python/ops/nn_xent_test.py
index 7bf18c47fee..3e5c198fc6a 100644
--- a/tensorflow/python/ops/nn_xent_test.py
+++ b/tensorflow/python/ops/nn_xent_test.py
@@ -24,6 +24,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import gradient_checker
from tensorflow.python.ops import gradients_impl
from tensorflow.python.ops import nn_impl
@@ -53,6 +54,7 @@ class SigmoidCrossEntropyWithLogitsTest(test.TestCase):
losses = np.array(self._SigmoidCrossEntropyWithLogits(x, y)).reshape(*sizes)
return logits, targets, losses
+ @test_util.run_deprecated_v1
def testConstructionNamed(self):
with self.cached_session():
logits, targets, _ = self._Inputs()
@@ -82,6 +84,7 @@ class SigmoidCrossEntropyWithLogitsTest(test.TestCase):
tf_loss = self.evaluate(loss)
self.assertAllClose(np_loss, tf_loss, atol=0.001)
+ @test_util.run_deprecated_v1
def testGradient(self):
sizes = [4, 2]
with self.cached_session():
@@ -92,6 +95,7 @@ class SigmoidCrossEntropyWithLogitsTest(test.TestCase):
print("logistic loss gradient err = ", err)
self.assertLess(err, 1e-7)
+ @test_util.run_deprecated_v1
def testGradientAtZero(self):
with self.cached_session():
logits = constant_op.constant([0.0, 0.0], dtype=dtypes.float64)
@@ -129,6 +133,7 @@ class WeightedCrossEntropyTest(test.TestCase):
losses = np.array(self._WeightedCrossEntropy(x, y, q)).reshape(*sizes)
return logits, targets, q, losses
+ @test_util.run_deprecated_v1
def testConstructionNamed(self):
with self.cached_session():
logits, targets, pos_weight, _ = self._Inputs()
@@ -157,6 +162,7 @@ class WeightedCrossEntropyTest(test.TestCase):
tf_loss = self.evaluate(loss)
self.assertAllClose(np_loss, tf_loss, atol=0.001)
+ @test_util.run_deprecated_v1
def testGradient(self):
sizes = [4, 2]
with self.cached_session():
diff --git a/tensorflow/python/ops/ragged/convert_to_tensor_or_ragged_tensor_op_test.py b/tensorflow/python/ops/ragged/convert_to_tensor_or_ragged_tensor_op_test.py
index 243fa34c4b8..ef3464f2437 100644
--- a/tensorflow/python/ops/ragged/convert_to_tensor_or_ragged_tensor_op_test.py
+++ b/tensorflow/python/ops/ragged/convert_to_tensor_or_ragged_tensor_op_test.py
@@ -90,6 +90,7 @@ class RaggedConvertToTensorOrRaggedTensorTest(test_util.TensorFlowTestCase,
preferred_dtype=dtypes.string,
expected_dtype=dtypes.int32),
])
+ @test_util.run_deprecated_v1
def testConvertRaggedTensorValue(self,
value,
dtype=None,
@@ -145,6 +146,7 @@ class RaggedConvertToTensorOrRaggedTensorTest(test_util.TensorFlowTestCase,
message=('Tensor conversion requested dtype string for '
'Tensor with dtype int32')),
])
+ @test_util.run_deprecated_v1
def testConvertTensorError(self,
pylist,
message,
diff --git a/tensorflow/python/ops/ragged/ragged_batch_gather_op_test.py b/tensorflow/python/ops/ragged/ragged_batch_gather_op_test.py
index 79a2ecd87ae..d9d840500cb 100644
--- a/tensorflow/python/ops/ragged/ragged_batch_gather_op_test.py
+++ b/tensorflow/python/ops/ragged/ragged_batch_gather_op_test.py
@@ -135,6 +135,7 @@ class RaggedBatchGatherOpTest(test_util.TensorFlowTestCase,
expected=ragged.constant_value(
[[[[b'c', b'a'], [b'd', b'd']], [[b'f', b'e']]]], ragged_rank=2)),
])
+ @test_util.run_deprecated_v1
def testRaggedBatchGather(self, descr, params, indices, expected):
result = ragged.batch_gather(params, indices)
self.assertEqual(
@@ -144,6 +145,7 @@ class RaggedBatchGatherOpTest(test_util.TensorFlowTestCase,
expected = expected.tolist()
self.assertEqual(result.eval().tolist(), expected)
+ @test_util.run_deprecated_v1
def testRaggedBatchGatherUnknownRankError(self):
params = [['a', 'b'], ['c', 'd']]
indices = array_ops.placeholder(dtypes.int32, shape=None)
@@ -186,6 +188,7 @@ class RaggedBatchGatherOpTest(test_util.TensorFlowTestCase,
indices=[[[0]]],
message='batch shape from indices does not match params shape'),
])
+ @test_util.run_deprecated_v1
def testRaggedBatchGatherStaticError(self,
params,
indices,
diff --git a/tensorflow/python/ops/ragged/ragged_boolean_mask_op_test.py b/tensorflow/python/ops/ragged/ragged_boolean_mask_op_test.py
index b3279c1e840..d939d9d6341 100644
--- a/tensorflow/python/ops/ragged/ragged_boolean_mask_op_test.py
+++ b/tensorflow/python/ops/ragged/ragged_boolean_mask_op_test.py
@@ -298,6 +298,7 @@ class RaggedBooleanMaskOpTest(test_util.TensorFlowTestCase,
keepdims=True,
expected=ragged.constant_value([[[1], [4, 6]], [[7, 9], []]])),
]) # pyformat: disable
+ @test_util.run_deprecated_v1
def testBooleanMask(self, descr, data, mask, keepdims, expected):
actual = ragged.boolean_mask(data, mask, keepdims=keepdims)
self.assertEqual(
@@ -307,6 +308,7 @@ class RaggedBooleanMaskOpTest(test_util.TensorFlowTestCase,
expected = expected.tolist()
self.assertEqual(actual.eval().tolist(), expected)
+ @test_util.run_deprecated_v1
def testErrors(self):
self.assertRaisesRegexp(ValueError,
r'mask\.shape\.ndims must be kown statically',
diff --git a/tensorflow/python/ops/ragged/ragged_concat_op_test.py b/tensorflow/python/ops/ragged/ragged_concat_op_test.py
index bddc5d8580f..3699f90f46b 100644
--- a/tensorflow/python/ops/ragged/ragged_concat_op_test.py
+++ b/tensorflow/python/ops/ragged/ragged_concat_op_test.py
@@ -221,6 +221,7 @@ class RaggedConcatOpTest(test_util.TensorFlowTestCase, parameterized.TestCase):
axis=0,
expected=[[b'a00', b'a01'], [], [b'a20', b'a21']]),
) # pyformat: disable
+ @test_util.run_deprecated_v1
def testRaggedConcat(self,
descr,
rt_inputs,
@@ -266,6 +267,7 @@ class RaggedConcatOpTest(test_util.TensorFlowTestCase, parameterized.TestCase):
error=ValueError,
message='Dimension 0 in both shapes must be equal'),
)
+ @test_util.run_deprecated_v1
def testStaticError(self, rt_inputs, axis, error, message, ragged_ranks=None):
rt_inputs = self._rt_inputs_to_tensors(rt_inputs, ragged_ranks)
self.assertRaisesRegexp(error, message, ragged.concat, rt_inputs, axis)
@@ -278,6 +280,7 @@ class RaggedConcatOpTest(test_util.TensorFlowTestCase, parameterized.TestCase):
error=errors.InvalidArgumentError,
message='Input tensors have incompatible shapes'),
])
+ @test_util.run_deprecated_v1
def testRuntimeError(self, rt_inputs, axis, error, message,
ragged_ranks=None):
rt_inputs = [
@@ -287,6 +290,7 @@ class RaggedConcatOpTest(test_util.TensorFlowTestCase, parameterized.TestCase):
with self.test_session():
self.assertRaisesRegexp(error, message, concatenated.eval)
+ @test_util.run_deprecated_v1
def testNegativeAxisWithUnknownRankError(self):
rt_inputs = [
array_ops.placeholder(dtypes.int64),
@@ -296,6 +300,7 @@ class RaggedConcatOpTest(test_util.TensorFlowTestCase, parameterized.TestCase):
ValueError, r'axis may only be negative if ndims is statically known.',
ragged.concat, rt_inputs, -1)
+ @test_util.run_deprecated_v1
def testSingleTensorInput(self):
"""Tests ragged_concat with a single tensor input.
diff --git a/tensorflow/python/ops/ragged/ragged_const_op_test.py b/tensorflow/python/ops/ragged/ragged_const_op_test.py
index 9c3b2ac88af..2505b23912a 100644
--- a/tensorflow/python/ops/ragged/ragged_const_op_test.py
+++ b/tensorflow/python/ops/ragged/ragged_const_op_test.py
@@ -133,6 +133,7 @@ class RaggedConstOpTest(test_util.TensorFlowTestCase, parameterized.TestCase):
dict(pylist=[[b'a', b'b'], [b'c'], [b'd', b'e', b'f']],
dtype=dtypes.string),
)
+ @test_util.run_deprecated_v1
def testRaggedConst(self,
pylist,
dtype=None,
@@ -258,6 +259,7 @@ class RaggedConstOpTest(test_util.TensorFlowTestCase, parameterized.TestCase):
exception=ValueError,
message='inner values have inconsistent shape'),
)
+ @test_util.run_deprecated_v1
def testRaggedConstError(self,
pylist,
dtype=None,
diff --git a/tensorflow/python/ops/ragged/ragged_elementwise_ops_test.py b/tensorflow/python/ops/ragged/ragged_elementwise_ops_test.py
index 26e6b8b6d44..305a96df9cc 100644
--- a/tensorflow/python/ops/ragged/ragged_elementwise_ops_test.py
+++ b/tensorflow/python/ops/ragged/ragged_elementwise_ops_test.py
@@ -394,6 +394,7 @@ class RaggedElementwiseOpsTest(test_util.TensorFlowTestCase,
result_flat_values = array_ops.reshape(result, [-1])
self.assertAllEqual(expected_flat_values, result_flat_values)
+ @test_util.run_deprecated_v1
def testUnknownRankError(self):
x = ragged.constant([[1, 2], [3]])
y = ragged.from_row_splits(
diff --git a/tensorflow/python/ops/ragged/ragged_expand_dims_op_test.py b/tensorflow/python/ops/ragged/ragged_expand_dims_op_test.py
index 0c4fd458c23..3ff66973b6f 100644
--- a/tensorflow/python/ops/ragged/ragged_expand_dims_op_test.py
+++ b/tensorflow/python/ops/ragged/ragged_expand_dims_op_test.py
@@ -105,6 +105,7 @@ class RaggedExpandDimsOpTest(test_util.TensorFlowTestCase,
expected=EXAMPLE4D_EXPAND_AXIS[4],
expected_shape=[3, None, None, 2, 1]),
]) # pyformat: disable
+ @test_util.run_deprecated_v1
def testRaggedExpandDims(self,
rt_input,
axis,
diff --git a/tensorflow/python/ops/ragged/ragged_from_sparse_op_test.py b/tensorflow/python/ops/ragged/ragged_from_sparse_op_test.py
index 77418ff20db..3c0db9e8fb6 100644
--- a/tensorflow/python/ops/ragged/ragged_from_sparse_op_test.py
+++ b/tensorflow/python/ops/ragged/ragged_from_sparse_op_test.py
@@ -29,6 +29,7 @@ from tensorflow.python.platform import googletest
class RaggedTensorToSparseOpTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testDocStringExample(self):
st = sparse_tensor.SparseTensor(
indices=[[0, 0], [0, 1], [0, 2], [1, 0], [3, 0]],
@@ -39,6 +40,7 @@ class RaggedTensorToSparseOpTest(test_util.TensorFlowTestCase):
with self.test_session():
self.assertEqual(rt.eval().tolist(), [[1, 2, 3], [4], [], [5]])
+ @test_util.run_deprecated_v1
def testEmpty(self):
st = sparse_tensor.SparseTensor(
indices=array_ops.zeros([0, 2], dtype=dtypes.int64),
@@ -49,6 +51,7 @@ class RaggedTensorToSparseOpTest(test_util.TensorFlowTestCase):
with self.test_session():
self.assertEqual(rt.eval().tolist(), [[], [], [], []])
+ @test_util.run_deprecated_v1
def testBadSparseTensorRank(self):
st1 = sparse_tensor.SparseTensor(indices=[[0]], values=[0], dense_shape=[3])
st2 = sparse_tensor.SparseTensor(
@@ -64,6 +67,7 @@ class RaggedTensorToSparseOpTest(test_util.TensorFlowTestCase):
self.assertRaisesRegexp(ValueError, r'rank\(st_input\) must be 2',
ragged.from_sparse, st3)
+ @test_util.run_deprecated_v1
def testGoodPartialSparseTensorRank(self):
st1 = sparse_tensor.SparseTensor(
indices=[[0, 0]],
@@ -78,6 +82,7 @@ class RaggedTensorToSparseOpTest(test_util.TensorFlowTestCase):
ragged.from_sparse(st1)
ragged.from_sparse(st2)
+ @test_util.run_deprecated_v1
def testNonRaggedSparseTensor(self):
# "index_suffix" means the value of the innermost dimension of the index
# (i.e., indices[i][-1]).
diff --git a/tensorflow/python/ops/ragged/ragged_from_tensor_op_test.py b/tensorflow/python/ops/ragged/ragged_from_tensor_op_test.py
index 7c59cd0b77b..1d8a00cc18d 100644
--- a/tensorflow/python/ops/ragged/ragged_from_tensor_op_test.py
+++ b/tensorflow/python/ops/ragged/ragged_from_tensor_op_test.py
@@ -31,6 +31,7 @@ from tensorflow.python.platform import googletest
class RaggedFromTensorOpTest(test_util.TensorFlowTestCase,
parameterized.TestCase):
+ @test_util.run_deprecated_v1
def testDocStringExamples(self):
# The examples from ragged.from_tensor.__doc__.
dt = constant_op.constant([[5, 7, 0], [0, 3, 0], [6, 0, 0]])
@@ -262,6 +263,7 @@ class RaggedFromTensorOpTest(test_util.TensorFlowTestCase,
[[[5, 6], [7]], [[0, 8], []]]]
},
) # pyformat: disable
+ @test_util.run_deprecated_v1
def testRaggedFromTensor(self,
tensor,
expected,
@@ -278,6 +280,7 @@ class RaggedFromTensorOpTest(test_util.TensorFlowTestCase,
with self.test_session():
self.assertEqual(rt.eval().tolist(), expected)
+ @test_util.run_deprecated_v1
def testHighDimensions(self):
# Use distinct prime numbers for all dimension shapes in this test, so
# we can see any errors that are caused by mixing up dimension sizes.
@@ -395,6 +398,7 @@ class RaggedFromTensorOpTest(test_util.TensorFlowTestCase,
'expected': [[], []]
},
)
+ @test_util.run_deprecated_v1
def testEmpty(self, dt_shape, expected, lengths=None, padding=None):
dt = array_ops.zeros(dt_shape)
rt = ragged.from_tensor(dt, lengths, padding)
@@ -447,6 +451,7 @@ class RaggedFromTensorOpTest(test_util.TensorFlowTestCase,
'error': (ValueError, r'ragged_rank must be greater than 0; got -1')
},
)
+ @test_util.run_deprecated_v1
def testErrors(self,
tensor,
lengths=None,
diff --git a/tensorflow/python/ops/ragged/ragged_gather_nd_op_test.py b/tensorflow/python/ops/ragged/ragged_gather_nd_op_test.py
index c52db9e2a16..62c6819374a 100644
--- a/tensorflow/python/ops/ragged/ragged_gather_nd_op_test.py
+++ b/tensorflow/python/ops/ragged/ragged_gather_nd_op_test.py
@@ -183,6 +183,7 @@ class RaggedGatherNdOpTest(test_util.TensorFlowTestCase,
indices=[[0, 0, 1], [0, 0, 0], [0, 1, 0]],
expected=[[b'c', b'd'], [b'a', b'b'], [b'e', b'f']]),
]) # pyformat: disable
+ @test_util.run_deprecated_v1
def testRaggedGatherNd(self, descr, params, indices, expected):
result = ragged.gather_nd(params, indices)
self.assertEqual(
@@ -192,6 +193,7 @@ class RaggedGatherNdOpTest(test_util.TensorFlowTestCase,
expected = expected.tolist()
self.assertEqual(self.evaluate(result).tolist(), expected)
+ @test_util.run_deprecated_v1
def testRaggedGatherNdUnknownRankError(self):
params = ragged.constant([['a', 'b'], ['c', 'd']])
indices1 = array_ops.placeholder(dtypes.int32, shape=None)
@@ -219,6 +221,7 @@ class RaggedGatherNdOpTest(test_util.TensorFlowTestCase,
indices=ragged.constant([[0]]),
message='The innermost dimension of indices may not be ragged'),
])
+ @test_util.run_deprecated_v1
def testRaggedGatherNdStaticError(self,
params,
indices,
diff --git a/tensorflow/python/ops/ragged/ragged_gather_op_test.py b/tensorflow/python/ops/ragged/ragged_gather_op_test.py
index bb52d05c32e..76c90cdfeeb 100644
--- a/tensorflow/python/ops/ragged/ragged_gather_op_test.py
+++ b/tensorflow/python/ops/ragged/ragged_gather_op_test.py
@@ -30,6 +30,7 @@ from tensorflow.python.platform import googletest
class RaggedTensorOpsTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testDocStringExamples(self):
params = constant_op.constant(['a', 'b', 'c', 'd', 'e'])
indices = constant_op.constant([3, 1, 2, 1, 0])
@@ -46,6 +47,7 @@ class RaggedTensorOpsTest(test_util.TensorFlowTestCase):
ragged.gather(ragged_params, ragged_indices).eval().tolist(),
[[[b'e'], [b'd'], []], [[b'd']], [], [[b'a', b'b', b'c']]])
+ @test_util.run_deprecated_v1
def testTensorParamsAndTensorIndices(self):
params = ['a', 'b', 'c', 'd', 'e']
indices = [2, 0, 2, 1]
@@ -55,6 +57,7 @@ class RaggedTensorOpsTest(test_util.TensorFlowTestCase):
[b'c', b'a', b'c', b'b'])
self.assertEqual(type(ragged.gather(params, indices)), ops.Tensor)
+ @test_util.run_deprecated_v1
def testRaggedParamsAndTensorIndices(self):
params = ragged.constant([['a', 'b'], ['c', 'd', 'e'], ['f'], [], ['g']])
indices = [2, 0, 2, 1]
@@ -63,6 +66,7 @@ class RaggedTensorOpsTest(test_util.TensorFlowTestCase):
ragged.gather(params, indices).eval().tolist(),
[[b'f'], [b'a', b'b'], [b'f'], [b'c', b'd', b'e']])
+ @test_util.run_deprecated_v1
def testTensorParamsAndRaggedIndices(self):
params = ['a', 'b', 'c', 'd', 'e']
indices = ragged.constant([[2, 1], [1, 2, 0], [3]])
@@ -71,6 +75,7 @@ class RaggedTensorOpsTest(test_util.TensorFlowTestCase):
ragged.gather(params, indices).eval().tolist(),
[[b'c', b'b'], [b'b', b'c', b'a'], [b'd']])
+ @test_util.run_deprecated_v1
def testRaggedParamsAndRaggedIndices(self):
params = ragged.constant([['a', 'b'], ['c', 'd', 'e'], ['f'], [], ['g']])
indices = ragged.constant([[2, 1], [1, 2, 0], [3]])
@@ -82,6 +87,7 @@ class RaggedTensorOpsTest(test_util.TensorFlowTestCase):
[[]]] # [p[3] ]]
) # pyformat: disable
+ @test_util.run_deprecated_v1
def testRaggedParamsAndScalarIndices(self):
params = ragged.constant([['a', 'b'], ['c', 'd', 'e'], ['f'], [], ['g']])
indices = 1
@@ -89,6 +95,7 @@ class RaggedTensorOpsTest(test_util.TensorFlowTestCase):
self.assertEqual(
ragged.gather(params, indices).eval().tolist(), [b'c', b'd', b'e'])
+ @test_util.run_deprecated_v1
def test3DRaggedParamsAnd2DTensorIndices(self):
params = ragged.constant([[['a', 'b'], []], [['c', 'd'], ['e'], ['f']],
[['g']]])
@@ -101,6 +108,7 @@ class RaggedTensorOpsTest(test_util.TensorFlowTestCase):
[[[b'g']], [[b'g']]]] # [p2, p2]]
) # pyformat: disable
+ @test_util.run_deprecated_v1
def testTensorParamsAnd4DRaggedIndices(self):
indices = ragged.constant(
[[[[3, 4], [0, 6]], []], [[[2, 1], [1, 0]], [[2, 5]], [[2, 3]]],
@@ -115,6 +123,7 @@ class RaggedTensorOpsTest(test_util.TensorFlowTestCase):
[[[b'c', b'b'], [b'b', b'a']], [[b'c', b'f']], [[b'c', b'd']]],
[[[b'b', b'a']]]]) # pyformat: disable
+ @test_util.run_deprecated_v1
def testOutOfBoundsError(self):
tensor_params = ['a', 'b', 'c']
tensor_indices = [0, 1, 2]
@@ -131,6 +140,7 @@ class RaggedTensorOpsTest(test_util.TensorFlowTestCase):
r'indices\[1\] = 3 is not in \[0, 2\)',
ragged.gather(ragged_params, ragged_indices).eval)
+ @test_util.run_deprecated_v1
def testUnknownIndicesRankError(self):
params = ragged.constant([], ragged_rank=1)
indices = constant_op.constant([0], dtype=dtypes.int64)
diff --git a/tensorflow/python/ops/ragged/ragged_map_fn_op_test.py b/tensorflow/python/ops/ragged/ragged_map_fn_op_test.py
index dac86310b9f..7a8603c949a 100644
--- a/tensorflow/python/ops/ragged/ragged_map_fn_op_test.py
+++ b/tensorflow/python/ops/ragged/ragged_map_fn_op_test.py
@@ -140,6 +140,7 @@ class RaggedMapOpTest(test_util.TensorFlowTestCase, parameterized.TestCase):
),
])
+ @test_util.run_deprecated_v1
def testRaggedMap(
self,
fn,
@@ -164,6 +165,7 @@ class RaggedMapOpTest(test_util.TensorFlowTestCase, parameterized.TestCase):
output_values = self.evaluate(output)
self.assertAllEqual(expected_output, output_values.tolist())
+ @test_util.run_deprecated_v1
def testRaggedMapOnStructure(self):
batman = ragged.constant([[1, 2, 3], [4], [5, 6, 7]])
# [[10, 20, 30], [40], [50, 60, 70]]
@@ -184,6 +186,7 @@ class RaggedMapOpTest(test_util.TensorFlowTestCase, parameterized.TestCase):
self.assertAllEqual(output.eval().tolist(), [66, 44, 198])
# Test mapping over a dict of RTs can produce a dict of RTs.
+ @test_util.run_deprecated_v1
def testRaggedMapOnStructure_RaggedOutputs(self):
batman = ragged.constant([[1, 2, 3], [4], [5, 6, 7]])
# [[10, 20, 30], [40], [50, 60, 70]]
@@ -215,6 +218,7 @@ class RaggedMapOpTest(test_util.TensorFlowTestCase, parameterized.TestCase):
self.assertAllEqual(output['robin'].eval().tolist(),
[[11, 21, 31], [41], [51, 61, 71]])
+ @test_util.run_deprecated_v1
def testZip(self):
x = ragged.constant([[10, 20], [30, 40], [50, 60], [70], [80, 90, 100]],
dtypes.int64)
@@ -237,6 +241,7 @@ class RaggedMapOpTest(test_util.TensorFlowTestCase, parameterized.TestCase):
result, [[[0, 10], [0, 20]], [[1, 30], [1, 40]], [[2, 50], [2, 60]],
[[3, 70]], [[4, 80], [4, 90], [4, 100]]])
+ @test_util.run_deprecated_v1
def testBatchGather(self):
tokens = ragged.constant([['hello', '.', 'there'], ['merhaba'],
['bonjour', '.', 'ca va', '?']])
diff --git a/tensorflow/python/ops/ragged/ragged_map_inner_values_op_test.py b/tensorflow/python/ops/ragged/ragged_map_inner_values_op_test.py
index 798d7c3ce81..b5802cb82d9 100644
--- a/tensorflow/python/ops/ragged/ragged_map_inner_values_op_test.py
+++ b/tensorflow/python/ops/ragged/ragged_map_inner_values_op_test.py
@@ -43,6 +43,7 @@ class RaggedMapInnerValuesOpTest(test_util.TensorFlowTestCase,
with self.test_session():
self.assertEqual(result.eval().tolist(), expected)
+ @test_util.run_deprecated_v1
def testDocStringExamples(self):
"""Test the examples in apply_op_to_ragged_values.__doc__."""
rt = ragged.constant([[1, 2, 3], [], [4, 5], [6]])
@@ -54,6 +55,7 @@ class RaggedMapInnerValuesOpTest(test_util.TensorFlowTestCase,
self.assertEqual(v2.eval().tolist(), [[1, 4, 9], [], [16, 25], [36]])
self.assertEqual(v3.eval().tolist(), [[6, 7, 8], [], [9, 10], [11]])
+ @test_util.run_deprecated_v1
def testOpWithSingleRaggedTensorArg(self):
tensor = ragged.constant([[1, 2, 3], [], [4, 5]])
self.assertRaggedMapInnerValuesReturns(
@@ -61,17 +63,20 @@ class RaggedMapInnerValuesOpTest(test_util.TensorFlowTestCase,
args=(tensor,),
expected=[[0, 0, 0], [], [0, 0]])
+ @test_util.run_deprecated_v1
def testOpWithTwoRaggedTensorArgs(self):
x = ragged.constant([[3, 1, 4], [], [1, 5]])
y = ragged.constant([[1, 2, 3], [], [4, 5]])
self.assertRaggedMapInnerValuesReturns(
op=math_ops.multiply, args=(x, y), expected=[[3, 2, 12], [], [4, 25]])
+ @test_util.run_deprecated_v1
def testOpWithRaggedTensorAndScalarArgs(self):
y = ragged.constant([[1, 2, 3], [], [4, 5]])
self.assertRaggedMapInnerValuesReturns(
op=math_ops.multiply, args=(5, y), expected=[[5, 10, 15], [], [20, 25]])
+ @test_util.run_deprecated_v1
def testOpWithThreeRaggedTensorArgs(self):
condition = ragged.constant(
[[True, True, False], [], [True, False]]) # pyformat: disable
@@ -82,6 +87,7 @@ class RaggedMapInnerValuesOpTest(test_util.TensorFlowTestCase,
args=(condition, x, y),
expected=[[b'a', b'b', b'C'], [], [b'd', b'E']])
+ @test_util.run_deprecated_v1
def testOpWithRaggedTensorListArg(self):
x = ragged.constant([[1, 2, 3], [], [4, 5]])
y = ragged.constant([[10, 20, 30], [], [40, 50]])
@@ -90,6 +96,7 @@ class RaggedMapInnerValuesOpTest(test_util.TensorFlowTestCase,
args=([x, y, x],),
expected=[[12, 24, 36], [], [48, 60]])
+ @test_util.run_deprecated_v1
def testOpWithKeywordArgs(self):
x = ragged.constant([[3, 1, 4], [], [1, 5]])
y = ragged.constant([[1, 2, 3], [], [4, 5]])
@@ -98,6 +105,7 @@ class RaggedMapInnerValuesOpTest(test_util.TensorFlowTestCase,
kwargs=dict(x=x, y=y),
expected=[[3, 2, 12], [], [4, 25]])
+ @test_util.run_deprecated_v1
def testOpWithMixedPositionalAndKeywordArgs(self):
x = ragged.constant([[3, 1, 4], [], [1, 5]])
y = ragged.constant([[1, 2, 3], [], [4, 5]])
@@ -107,6 +115,7 @@ class RaggedMapInnerValuesOpTest(test_util.TensorFlowTestCase,
kwargs=dict(y=y),
expected=[[3, 2, 12], [], [4, 25]])
+ @test_util.run_deprecated_v1
def testNonElementWiseOp(self):
x = ragged.constant(
[[[3, 1, 4], [1, 5, 9], [2, 6, 5]], [], [[3, 5, 8], [9, 7, 9]]],
@@ -119,6 +128,7 @@ class RaggedMapInnerValuesOpTest(test_util.TensorFlowTestCase,
},
expected=[[8, 15, 13], [], [16, 25]])
+ @test_util.run_deprecated_v1
def testOpWithRaggedRankGreaterThanOne(self):
# ragged_rank=0
x0 = [3, 1, 4, 1, 5, 9, 2, 6, 5]
@@ -163,6 +173,7 @@ class RaggedMapInnerValuesOpTest(test_util.TensorFlowTestCase,
[[[54, 14], [48, 45]]] # row 3
]) # pyformat: disable
+ @test_util.run_deprecated_v1
def testOpWithRaggedRankThree(self):
x = ragged.constant([[[3, 1, 4]], [], [[], [1, 5]]])
y = ragged.constant([[[1, 2, 3]], [], [[], [4, 5]]])
@@ -171,6 +182,7 @@ class RaggedMapInnerValuesOpTest(test_util.TensorFlowTestCase,
args=(x, y),
expected=[[[3, 2, 12]], [], [[], [4, 25]]])
+ @test_util.run_deprecated_v1
def testOpWithInnerValuesOnly(self):
x = constant_op.constant([[1, 2], [3, 4], [5, 6]])
y = constant_op.constant(2)
@@ -191,6 +203,7 @@ class RaggedMapInnerValuesOpTest(test_util.TensorFlowTestCase,
r'Inputs must have identical ragged splits.*',
ragged.map_inner_values, math_ops.add, x, y)
+ @test_util.run_deprecated_v1
def testRaggedTensorSplitsMismatchErrorAtRuntime(self):
splits1 = array_ops.placeholder_with_default(
constant_op.constant([0, 3, 3, 5], dtypes.int64), None)
diff --git a/tensorflow/python/ops/ragged/ragged_operators_test.py b/tensorflow/python/ops/ragged/ragged_operators_test.py
index a99d788ef79..7fe8159d822 100644
--- a/tensorflow/python/ops/ragged/ragged_operators_test.py
+++ b/tensorflow/python/ops/ragged/ragged_operators_test.py
@@ -27,6 +27,7 @@ class RaggedElementwiseOpsTest(test_util.TensorFlowTestCase):
# @TODO(edloper): Test right-handed versions of operators once we add
# broadcasting support for elementwise ops.
+ @test_util.run_deprecated_v1
def testOrderingOperators(self):
x = ragged.constant([[1, 5], [3]])
y = ragged.constant([[4, 5], [1]])
@@ -40,6 +41,7 @@ class RaggedElementwiseOpsTest(test_util.TensorFlowTestCase):
if a != b:
print('%30s %s' % (b, a))
+ @test_util.run_deprecated_v1
def testArithmeticOperators(self):
x = ragged.constant([[1.0, -2.0], [8.0]])
y = ragged.constant([[4.0, 4.0], [2.0]])
@@ -75,6 +77,7 @@ class RaggedElementwiseOpsTest(test_util.TensorFlowTestCase):
self.assertEqual((2.0 % y).eval().tolist(), [[2.0, 2.0], [0.0]])
self.assertEqual((x % 2.0).eval().tolist(), [[1.0, 0.0], [0.0]])
+ @test_util.run_deprecated_v1
def testLogicalOperators(self):
a = ragged.constant([[True, True], [False]])
b = ragged.constant([[True, False], [False]])
diff --git a/tensorflow/python/ops/ragged/ragged_range_op_test.py b/tensorflow/python/ops/ragged/ragged_range_op_test.py
index 3c6a6fb75c8..644423ecb7f 100644
--- a/tensorflow/python/ops/ragged/ragged_range_op_test.py
+++ b/tensorflow/python/ops/ragged/ragged_range_op_test.py
@@ -26,6 +26,7 @@ from tensorflow.python.platform import googletest
class RaggedRangeOpTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testDocStringExamples(self):
"""Examples from ragged_range.__doc__."""
with self.test_session():
@@ -38,6 +39,7 @@ class RaggedRangeOpTest(test_util.TensorFlowTestCase):
rt3 = ragged.range([0, 5, 8], [3, 3, 12], 2).eval().tolist()
self.assertEqual(rt3, [[0, 2], [], [8, 10]])
+ @test_util.run_deprecated_v1
def testBasicRanges(self):
with self.test_session():
# Specify limits only.
@@ -56,6 +58,7 @@ class RaggedRangeOpTest(test_util.TensorFlowTestCase):
[list(range(0, 4, 2)), list(range(3, 4, 3)),
list(range(5, 15, 4))])
+ @test_util.run_deprecated_v1
def testFloatRanges(self):
with self.test_session():
expected = [[0.0, 0.4, 0.8, 1.2, 1.6, 2.0, 2.4, 2.8, 3.2, 3.6], [3.0],
@@ -64,6 +67,7 @@ class RaggedRangeOpTest(test_util.TensorFlowTestCase):
[0.4, 1.5, 2.2]).eval().tolist()
self.assertEqual(expected, [[round(v, 5) for v in row] for row in actual])
+ @test_util.run_deprecated_v1
def testNegativeDeltas(self):
with self.test_session():
self.assertEqual(
@@ -77,6 +81,7 @@ class RaggedRangeOpTest(test_util.TensorFlowTestCase):
[list(range(0, 0, -1)), list(range(-3, 0, 1)),
list(range(5, 0, -2))])
+ @test_util.run_deprecated_v1
def testBroadcast(self):
with self.test_session():
# Specify starts and limits, broadcast deltas.
@@ -89,6 +94,7 @@ class RaggedRangeOpTest(test_util.TensorFlowTestCase):
self.assertEqual(
ragged.range(0, 5, 1).eval().tolist(), [list(range(0, 5, 1))])
+ @test_util.run_deprecated_v1
def testEmptyRanges(self):
rt1 = ragged.range([0, 5, 3], [0, 3, 5])
rt2 = ragged.range([0, 5, 5], [0, 3, 5], -1)
@@ -96,6 +102,7 @@ class RaggedRangeOpTest(test_util.TensorFlowTestCase):
self.assertEqual(rt1.eval().tolist(), [[], [], [3, 4]])
self.assertEqual(rt2.eval().tolist(), [[], [5, 4], []])
+ @test_util.run_deprecated_v1
def testShapeFnErrors(self):
with self.test_session():
self.assertRaisesRegexp(ValueError, r'Shape must be at most rank 1.*',
@@ -107,12 +114,14 @@ class RaggedRangeOpTest(test_util.TensorFlowTestCase):
self.assertRaisesRegexp(ValueError, r'Dimensions must be equal.*',
ragged.range, [0], [1, 2])
+ @test_util.run_deprecated_v1
def testKernelErrors(self):
with self.test_session():
self.assertRaisesRegexp(errors.InvalidArgumentError,
r'Requires delta != 0',
ragged.range(0, 0, 0).eval)
+ @test_util.run_deprecated_v1
def testShape(self):
self.assertEqual(ragged.range(0, 0, 0).shape.as_list(), [1, None])
self.assertEqual(ragged.range([1, 2, 3]).shape.as_list(), [3, None])
diff --git a/tensorflow/python/ops/ragged/ragged_reduce_op_test.py b/tensorflow/python/ops/ragged/ragged_reduce_op_test.py
index 93176c738df..9f51d59ba3c 100644
--- a/tensorflow/python/ops/ragged/ragged_reduce_op_test.py
+++ b/tensorflow/python/ops/ragged/ragged_reduce_op_test.py
@@ -300,6 +300,7 @@ class RaggedReduceOpsTest(test_util.TensorFlowTestCase, parameterized.TestCase):
axis=2,
expected=[[mean(1, 2), mean(3, 4, 5)], [mean(6, 7), 8], [9]]),
)
+ @test_util.run_deprecated_v1
def testReduce(self, ragged_reduce_op, rt_input, axis, expected):
rt_input = ragged.constant(rt_input)
reduced = ragged_reduce_op(rt_input, axis)
@@ -311,6 +312,7 @@ class RaggedReduceOpsTest(test_util.TensorFlowTestCase, parameterized.TestCase):
self.assertTrue(
((actual == expected) | (np.isnan(actual) & np.isnan(expected))).all())
+ @test_util.run_deprecated_v1
def testMeanNan(self):
rt_as_list = [[0, 1, 2, 3], [4], [], [5, 6], [7], [8, 9]]
expected = (
@@ -321,6 +323,7 @@ class RaggedReduceOpsTest(test_util.TensorFlowTestCase, parameterized.TestCase):
with self.test_session():
self.assertEqualWithNan(reduced.eval(), expected)
+ @test_util.run_deprecated_v1
def testMeanWithTensorInputs(self):
tensor = [[1.0, 2.0, 3.0], [10.0, 20.0, 30.0]]
expected = [2.0, 20.0]
@@ -328,6 +331,7 @@ class RaggedReduceOpsTest(test_util.TensorFlowTestCase, parameterized.TestCase):
with self.test_session():
self.assertAllEqual(reduced.eval(), expected)
+ @test_util.run_deprecated_v1
def testErrors(self):
rt_input = ragged.constant([[1, 2, 3], [4, 5]])
axis = array_ops.placeholder_with_default(constant_op.constant([0]), None)
diff --git a/tensorflow/python/ops/ragged/ragged_row_lengths_op_test.py b/tensorflow/python/ops/ragged/ragged_row_lengths_op_test.py
index 4d5a0a5d11c..4a705be4848 100644
--- a/tensorflow/python/ops/ragged/ragged_row_lengths_op_test.py
+++ b/tensorflow/python/ops/ragged/ragged_row_lengths_op_test.py
@@ -143,6 +143,7 @@ class RaggedRowLengthsOp(test_util.TensorFlowTestCase, parameterized.TestCase):
expected=[[2, 3, 0], [4, 1]],
expected_ragged_rank=1),
]) # pyformat: disable
+ @test_util.run_deprecated_v1
def testRowLengths(self,
rt_input,
expected,
diff --git a/tensorflow/python/ops/ragged/ragged_row_splits_to_segment_ids_op_test.py b/tensorflow/python/ops/ragged/ragged_row_splits_to_segment_ids_op_test.py
index f246bf35524..7f5f4e91bde 100644
--- a/tensorflow/python/ops/ragged/ragged_row_splits_to_segment_ids_op_test.py
+++ b/tensorflow/python/ops/ragged/ragged_row_splits_to_segment_ids_op_test.py
@@ -26,6 +26,7 @@ from tensorflow.python.platform import googletest
class RaggedSplitsToSegmentIdsOpTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testDocStringExample(self):
splits = [0, 3, 3, 5, 6, 9]
expected = [0, 0, 0, 2, 2, 3, 4, 4, 4]
@@ -33,12 +34,14 @@ class RaggedSplitsToSegmentIdsOpTest(test_util.TensorFlowTestCase):
with self.test_session():
self.assertEqual(segment_ids.eval().tolist(), expected)
+ @test_util.run_deprecated_v1
def testEmptySplits(self):
# Note: the splits for an empty ragged tensor contains a single zero.
segment_ids = ragged.row_splits_to_segment_ids([0])
with self.test_session():
self.assertEqual(segment_ids.eval().tolist(), [])
+ @test_util.run_deprecated_v1
def testErrors(self):
self.assertRaisesRegexp(ValueError, r'Invalid row_splits: \[\]',
ragged.row_splits_to_segment_ids, [])
diff --git a/tensorflow/python/ops/ragged/ragged_segment_ids_to_row_splits_op_test.py b/tensorflow/python/ops/ragged/ragged_segment_ids_to_row_splits_op_test.py
index fa7adf66b0b..7e52f2d844b 100644
--- a/tensorflow/python/ops/ragged/ragged_segment_ids_to_row_splits_op_test.py
+++ b/tensorflow/python/ops/ragged/ragged_segment_ids_to_row_splits_op_test.py
@@ -26,6 +26,7 @@ from tensorflow.python.platform import googletest
class RaggedSplitsToSegmentIdsOpTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testDocStringExample(self):
segment_ids = [0, 0, 0, 2, 2, 3, 4, 4, 4]
expected = [0, 3, 3, 5, 6, 9]
@@ -33,6 +34,7 @@ class RaggedSplitsToSegmentIdsOpTest(test_util.TensorFlowTestCase):
with self.test_session():
self.assertEqual(splits.eval().tolist(), expected)
+ @test_util.run_deprecated_v1
def testEmptySegmentIds(self):
# Note: the splits for an empty ragged tensor contains a single zero.
segment_ids = ragged.segment_ids_to_row_splits([])
@@ -49,6 +51,7 @@ class RaggedSplitsToSegmentIdsOpTest(test_util.TensorFlowTestCase):
self.assertRaisesRegexp(ValueError, r'Shape \(1, 1\) must have rank 1',
ragged.segment_ids_to_row_splits, [[0]])
+ @test_util.run_deprecated_v1
def testNumSegments(self):
segment_ids = [0, 0, 0, 2, 2, 3, 4, 4, 4]
num_segments = 7
@@ -57,6 +60,7 @@ class RaggedSplitsToSegmentIdsOpTest(test_util.TensorFlowTestCase):
with self.test_session():
self.assertEqual(splits.eval().tolist(), expected)
+ @test_util.run_deprecated_v1
def testUnsortedSegmentIds(self):
# Segment ids are not required to be sorted.
segment_ids = [0, 4, 3, 2, 4, 4, 2, 0, 0]
diff --git a/tensorflow/python/ops/ragged/ragged_segment_op_test.py b/tensorflow/python/ops/ragged/ragged_segment_op_test.py
index 40a101b4dad..9e4877ae3e6 100644
--- a/tensorflow/python/ops/ragged/ragged_segment_op_test.py
+++ b/tensorflow/python/ops/ragged/ragged_segment_op_test.py
@@ -110,6 +110,7 @@ class RaggedSegmentOpsTest(test_util.TensorFlowTestCase,
(ragged.segment_mean, mean, [5, 4, 3, 2, 1, 0]),
(ragged.segment_mean, mean, [0, 0, 0, 10, 10, 10]),
)
+ @test_util.run_deprecated_v1
def testRaggedSegment_Int(self, segment_op, combiner, segment_ids):
rt_as_list = [[0, 1, 2, 3], [4], [], [5, 6], [7], [8, 9]]
rt = ragged.constant(rt_as_list)
@@ -146,6 +147,7 @@ class RaggedSegmentOpsTest(test_util.TensorFlowTestCase,
(ragged.segment_sqrt_n, sqrt_n, [5, 4, 3, 2, 1, 0]),
(ragged.segment_sqrt_n, sqrt_n, [0, 0, 0, 10, 10, 10]),
)
+ @test_util.run_deprecated_v1
def testRaggedSegment_Float(self, segment_op, combiner, segment_ids):
rt_as_list = [[0., 1., 2., 3.], [4.], [], [5., 6.], [7.], [8., 9.]]
rt = ragged.constant(rt_as_list)
@@ -157,6 +159,7 @@ class RaggedSegmentOpsTest(test_util.TensorFlowTestCase,
self.assertNestedListAmostEqual(
self.evaluate(segmented).tolist(), expected, places=5)
+ @test_util.run_deprecated_v1
def testRaggedRankTwo(self):
rt = ragged.constant([
[[111, 112, 113, 114], [121],], # row 0
@@ -179,6 +182,7 @@ class RaggedSegmentOpsTest(test_util.TensorFlowTestCase,
[]] # pyformat: disable
self.assertEqual(self.evaluate(segmented2).tolist(), expected2)
+ @test_util.run_deprecated_v1
def testRaggedSegmentIds(self):
rt = ragged.constant([
[[111, 112, 113, 114], [121],], # row 0
@@ -201,6 +205,7 @@ class RaggedSegmentOpsTest(test_util.TensorFlowTestCase,
'but segment_ids is ragged and data is not.', ragged.segment_sum, dt,
segment_ids, 3)
+ @test_util.run_deprecated_v1
def testShapeMismatchError2(self):
rt = ragged.constant([
[[111, 112, 113, 114], [121]], # row 0
diff --git a/tensorflow/python/ops/ragged/ragged_stack_op_test.py b/tensorflow/python/ops/ragged/ragged_stack_op_test.py
index d474a749f04..43434716942 100644
--- a/tensorflow/python/ops/ragged/ragged_stack_op_test.py
+++ b/tensorflow/python/ops/ragged/ragged_stack_op_test.py
@@ -265,6 +265,7 @@ class RaggedStackOpTest(test_util.TensorFlowTestCase, parameterized.TestCase):
axis=0,
expected=[[[b'a00', b'a01'], [], [b'a20', b'a21']]]),
) # pyformat: disable
+ @test_util.run_deprecated_v1
def testRaggedStack(self,
descr,
rt_inputs,
@@ -313,6 +314,7 @@ class RaggedStackOpTest(test_util.TensorFlowTestCase, parameterized.TestCase):
def testError(self, rt_inputs, axis, error, message):
self.assertRaisesRegexp(error, message, ragged.stack, rt_inputs, axis)
+ @test_util.run_deprecated_v1
def testSingleTensorInput(self):
"""Tests ragged_stack with a single tensor input.
diff --git a/tensorflow/python/ops/ragged/ragged_tensor_test.py b/tensorflow/python/ops/ragged/ragged_tensor_test.py
index fa681c07bb7..608fbd6e5b7 100644
--- a/tensorflow/python/ops/ragged/ragged_tensor_test.py
+++ b/tensorflow/python/ops/ragged/ragged_tensor_test.py
@@ -114,6 +114,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
# RaggedTensor class docstring examples
#=============================================================================
+ @test_util.run_deprecated_v1
def testClassDocStringExamples(self):
# From section: "Component Tensors"
rt = ragged.from_row_splits(
@@ -199,6 +200,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
# RaggedTensor Constructor (private)
#=============================================================================
+ @test_util.run_deprecated_v1
def testRaggedTensorConstruction(self):
values = constant_op.constant(['a', 'b', 'c', 'd', 'e', 'f', 'g'])
row_splits = constant_op.constant([0, 2, 2, 5, 6, 7], dtypes.int64)
@@ -243,6 +245,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
# RaggedTensor Factory Ops
#=============================================================================
+ @test_util.run_deprecated_v1
def testFromValueRowIdsWithDerivedNRows(self):
# nrows is known at graph creation time.
values = constant_op.constant(['a', 'b', 'c', 'd', 'e', 'f', 'g'])
@@ -265,6 +268,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
self.evaluate(rt).tolist(),
[[b'a', b'b'], [], [b'c', b'd', b'e'], [b'f'], [b'g']])
+ @test_util.run_deprecated_v1
def testFromValueRowIdsWithDerivedNRowsDynamic(self):
# nrows is not known at graph creation time.
values = constant_op.constant(['a', 'b', 'c', 'd', 'e', 'f', 'g'])
@@ -288,6 +292,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
self.evaluate(rt).tolist(),
[[b'a', b'b'], [], [b'c', b'd', b'e'], [b'f'], [b'g']])
+ @test_util.run_deprecated_v1
def testFromValueRowIdsWithExplicitNRows(self):
values = constant_op.constant(['a', 'b', 'c', 'd', 'e', 'f', 'g'])
value_rowids = constant_op.constant([0, 0, 2, 2, 2, 3, 4], dtypes.int64)
@@ -309,6 +314,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
self.evaluate(rt).tolist(),
[[b'a', b'b'], [], [b'c', b'd', b'e'], [b'f'], [b'g'], [], []])
+ @test_util.run_deprecated_v1
def testFromValueRowIdsWithExplicitNRowsEqualToDefault(self):
values = constant_op.constant(['a', 'b', 'c', 'd', 'e', 'f', 'g'])
value_rowids = constant_op.constant([0, 0, 2, 2, 2, 3, 4], dtypes.int64)
@@ -332,6 +338,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
self.evaluate(rt).tolist(),
[[b'a', b'b'], [], [b'c', b'd', b'e'], [b'f'], [b'g']])
+ @test_util.run_deprecated_v1
def testFromValueRowIdsWithEmptyValues(self):
rt = ragged.from_value_rowids([], [])
rt_nrows = ragged.nrows(rt)
@@ -343,6 +350,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
self.assertEqual(self.evaluate(rt_nrows).tolist(), 0)
self.assertEqual(self.evaluate(rt).tolist(), [])
+ @test_util.run_deprecated_v1
def testFromRowSplits(self):
values = constant_op.constant(['a', 'b', 'c', 'd', 'e', 'f', 'g'])
row_splits = constant_op.constant([0, 2, 2, 5, 6, 7], dtypes.int64)
@@ -368,6 +376,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
with self.assertRaisesRegexp(ValueError, err_msg):
ragged.from_row_splits([], [])
+ @test_util.run_deprecated_v1
def testFromRowStarts(self):
values = constant_op.constant(['a', 'b', 'c', 'd', 'e', 'f', 'g'])
row_starts = constant_op.constant([0, 2, 2, 5, 6], dtypes.int64)
@@ -388,6 +397,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
self.evaluate(rt).tolist(),
[[b'a', b'b'], [], [b'c', b'd', b'e'], [b'f'], [b'g']])
+ @test_util.run_deprecated_v1
def testFromRowLimits(self):
values = constant_op.constant(['a', 'b', 'c', 'd', 'e', 'f', 'g'])
row_limits = constant_op.constant([2, 2, 5, 6, 7], dtypes.int64)
@@ -408,6 +418,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
self.evaluate(rt).tolist(),
[[b'a', b'b'], [], [b'c', b'd', b'e'], [b'f'], [b'g']])
+ @test_util.run_deprecated_v1
def testFromRowLengths(self):
values = constant_op.constant(['a', 'b', 'c', 'd', 'e', 'f', 'g'])
row_lengths = constant_op.constant([2, 0, 3, 1, 1], dtypes.int64)
@@ -429,6 +440,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
self.evaluate(rt).tolist(),
[[b'a', b'b'], [], [b'c', b'd', b'e'], [b'f'], [b'g']])
+ @test_util.run_deprecated_v1
def testFromNestedValueRowIdsWithDerivedNRows(self):
values = constant_op.constant(['a', 'b', 'c', 'd', 'e', 'f', 'g'])
nested_value_rowids = [
@@ -453,6 +465,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
self.evaluate(rt).tolist(),
[[[b'a', b'b'], []], [[b'c', b'd', b'e']], [], [[b'f'], [b'g']]])
+ @test_util.run_deprecated_v1
def testFromNestedValueRowIdsWithExplicitNRows(self):
values = constant_op.constant(['a', 'b', 'c', 'd', 'e', 'f', 'g'])
nested_value_rowids = [
@@ -509,6 +522,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
ragged.from_nested_value_rowids([1, 2, 3], [[0, 1, 2], [0, 1, 2]],
constant_op.constant([3, 3]))
+ @test_util.run_deprecated_v1
def testFromNestedRowSplits(self):
inner_values = constant_op.constant(['a', 'b', 'c', 'd', 'e', 'f', 'g'])
nested_row_splits = [
@@ -576,6 +590,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
value_rowids=value_rowids,
nrows=array_ops.expand_dims(nrows, 0))
+ @test_util.run_deprecated_v1
def testGraphMismatch(self):
with ops.Graph().as_default():
values = constant_op.constant([1, 2, 3])
@@ -588,6 +603,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
# Ragged Value & Row-Partitioning Tensor Accessors
#=============================================================================
+ @test_util.run_deprecated_v1
def testRaggedTensorAccessors_2d(self):
values = constant_op.constant(['a', 'b', 'c', 'd', 'e', 'f', 'g'])
row_splits = constant_op.constant([0, 2, 2, 5, 6, 7], dtypes.int64)
@@ -622,6 +638,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
[self.evaluate(s).tolist() for s in rt.nested_row_splits],
[[0, 2, 2, 5, 6, 7]])
+ @test_util.run_deprecated_v1
def testRaggedTensorAccessors_3d_with_ragged_rank_1(self):
values = [[0, 1], [2, 3], [4, 5], [6, 7], [8, 9], [10, 11], [12, 13]]
row_splits = constant_op.constant([0, 2, 2, 5, 6, 7], dtypes.int64)
@@ -657,6 +674,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
[self.evaluate(s).tolist() for s in rt.nested_row_splits],
[[0, 2, 2, 5, 6, 7]])
+ @test_util.run_deprecated_v1
def testRaggedTensorAccessors_3d_with_ragged_rank_2(self):
values = constant_op.constant(['a', 'b', 'c', 'd', 'e', 'f', 'g'])
nested_row_splits = [
@@ -709,6 +727,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
# RaggedTensor.shape
#=============================================================================
+ @test_util.run_deprecated_v1
def testShape(self):
"""Tests for RaggedTensor.shape."""
rt1 = ragged.from_row_splits(b'a b c d e f g'.split(), [0, 2, 5, 6, 6, 7])
@@ -842,6 +861,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
(SLICE_BUILDER[:, -2:], [row[-2:] for row in EXAMPLE_RAGGED_TENSOR_2D]),
# TODO(edloper): Add tests for strided slices, once support is added.
)
+ @test_util.run_deprecated_v1
def testRaggedTensorGetItemWithRaggedRank1(self, slice_spec, expected):
"""Test that rt.__getitem__(slice_spec) == expected."""
# Ragged tensor
@@ -883,6 +903,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
(SLICE_BUILDER[..., 0, 0, 0], IndexError,
'Too many indices for RaggedTensor'),
)
+ @test_util.run_deprecated_v1
def testRaggedTensorGetItemErrorsWithRaggedRank1(self, slice_spec, expected,
message):
"""Test that rt.__getitem__(slice_spec) == expected."""
@@ -961,6 +982,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
# TODO(edloper): Add tests slicing inner ragged dimensions, one support
# is added.
)
+ @test_util.run_deprecated_v1
def testRaggedTensorGetItemWithRaggedRank2(self, slice_spec, expected):
"""Test that rt.__getitem__(slice_spec) == expected."""
rt = ragged.from_nested_row_splits(
@@ -982,6 +1004,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
(SLICE_BUILDER[5], ValueError, '.*out of bounds.*'),
(SLICE_BUILDER[0, 5], ValueError, '.*out of bounds.*'),
)
+ @test_util.run_deprecated_v1
def testRaggedTensorGetItemErrorsWithRaggedRank2(self, slice_spec, expected,
message):
"""Test that rt.__getitem__(slice_spec) == expected."""
@@ -996,6 +1019,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
(SLICE_BUILDER[2:], []),
(SLICE_BUILDER[:-3], []),
)
+ @test_util.run_deprecated_v1
def testRaggedTensorGetItemWithEmptyTensor(self, slice_spec, expected):
"""Test that rt.__getitem__(slice_spec) == expected."""
rt = ragged.from_row_splits([], [0])
@@ -1005,6 +1029,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
(SLICE_BUILDER[0], ValueError, '.*out of bounds.*'),
(SLICE_BUILDER[-1], ValueError, '.*out of bounds.*'),
)
+ @test_util.run_deprecated_v1
def testRaggedTensorGetItemErrorsWithEmptyTensor(self, slice_spec, expected,
message):
"""Test that rt.__getitem__(slice_spec) == expected."""
@@ -1020,6 +1045,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
(SLICE_BUILDER[0, 1], EXAMPLE_RAGGED_TENSOR_2D[0][1]),
(SLICE_BUILDER[-3, 0], EXAMPLE_RAGGED_TENSOR_2D[-3][0]),
)
+ @test_util.run_deprecated_v1
def testRaggedTensorGetItemWithPlaceholderShapes(self, slice_spec, expected):
"""Test that rt.__getitem__(slice_spec) == expected."""
# Intentionally use an unknown shape for `splits`, to force the code path
@@ -1034,6 +1060,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
@parameterized.parameters(
(SLICE_BUILDER[..., 2], ValueError,
'Ellipsis not supported for unknown shape RaggedTensors'),)
+ @test_util.run_deprecated_v1
def testRaggedTensorGetItemErrorsWithPlaceholderShapes(
self, slice_spec, expected, message):
"""Test that rt.__getitem__(slice_spec) == expected."""
@@ -1042,6 +1069,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
rt = ragged.from_row_splits(values, [0, 1])
self._TestGetItemException(rt, slice_spec, expected, message)
+ @test_util.run_deprecated_v1
def testGetItemNewAxis(self):
# rt: [[[['a', 'b'], ['c', 'd']], [], [['e', 'f']]], []]
splits1 = [0, 3, 3]
@@ -1089,6 +1117,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
#=============================================================================
# RaggedTensor.__str__
#=============================================================================
+ @test_util.run_deprecated_v1
def testRaggedTensorStr(self):
rt1 = ragged.from_row_splits(b'a b c d e f g'.split(), [0, 2, 5, 6, 6, 7])
expected1 = ('RaggedTensor(values=Tensor("RaggedFromRowSplits/values:0", '
@@ -1126,6 +1155,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
# RaggedTensor.with_values() and RaggedTensor.with_inner_values().
#=============================================================================
+ @test_util.run_deprecated_v1
def testWithValues(self):
rt1 = ragged.constant([[1, 2], [3, 4, 5], [6], [], [7]])
rt2 = ragged.constant([[[1, 2], [3, 4, 5]], [[6]], [], [[], [7]]])
@@ -1147,6 +1177,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
#=============================================================================
# Session.run
#=============================================================================
+ @test_util.run_deprecated_v1
def testSessionRun(self):
rt1 = ragged.constant([[1, 2, 3], [4]])
rt2 = ragged.constant([[[], [1, 2]], [[3]]])
@@ -1156,6 +1187,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
self.assertEqual(result['rt1'].tolist(), [[1, 2, 3], [4]])
self.assertEqual(result['rt2'].tolist(), [[[], [1, 2]], [[3]]])
+ @test_util.run_deprecated_v1
def testSessionRunFeed(self):
rt1 = ragged.from_row_splits(
array_ops.placeholder(dtypes.int32),
@@ -1176,6 +1208,7 @@ class RaggedTensorTest(test_util.TensorFlowTestCase, parameterized.TestCase):
self.assertEqual(result['rt1'].tolist(), [[1, 2, 3], [4]])
self.assertEqual(result['rt2'].tolist(), [[[], [1, 2]], [[3]]])
+ @test_util.run_deprecated_v1
def testSessionPartialRunFeed(self):
# Placeholder inputs.
a = ragged.from_row_splits(
diff --git a/tensorflow/python/ops/ragged/ragged_tile_op_test.py b/tensorflow/python/ops/ragged/ragged_tile_op_test.py
index 672d2121147..f335b15dd15 100644
--- a/tensorflow/python/ops/ragged/ragged_tile_op_test.py
+++ b/tensorflow/python/ops/ragged/ragged_tile_op_test.py
@@ -181,6 +181,7 @@ class RaggedTileOpTest(test_util.TensorFlowTestCase, parameterized.TestCase):
[[[5], [6]]]]),
]) # pyformat: disable
+ @test_util.run_deprecated_v1
def testRaggedTile(self,
descr,
rt_input,
@@ -209,6 +210,7 @@ class RaggedTileOpTest(test_util.TensorFlowTestCase, parameterized.TestCase):
with self.test_session():
self.assertEqual(tiled.eval().tolist(), expected)
+ @test_util.run_deprecated_v1
def testRaggedTileWithTensorInput(self):
# When the input is a `Tensor`, ragged_tile just delegates to tf.tile.
dt = constant_op.constant([[1, 2], [3, 4]])
diff --git a/tensorflow/python/ops/ragged/ragged_to_sparse_op_test.py b/tensorflow/python/ops/ragged/ragged_to_sparse_op_test.py
index cb8e82c00d1..69b31ad0e97 100644
--- a/tensorflow/python/ops/ragged/ragged_to_sparse_op_test.py
+++ b/tensorflow/python/ops/ragged/ragged_to_sparse_op_test.py
@@ -30,6 +30,7 @@ from tensorflow.python.platform import googletest
class RaggedTensorToSparseOpTest(test_util.TensorFlowTestCase):
+ @test_util.run_deprecated_v1
def testDocStringExample(self):
rt = ragged.constant([[1, 2, 3], [4], [], [5, 6]])
st = ragged.to_sparse(rt)
@@ -40,6 +41,7 @@ class RaggedTensorToSparseOpTest(test_util.TensorFlowTestCase):
with self.test_session():
self.assertEqual(' '.join(repr(st.eval()).split()), expected)
+ @test_util.run_deprecated_v1
def test2DRaggedTensorWithOneRaggedDimension(self):
rt = ragged.constant([['a', 'b'], ['c', 'd', 'e'], ['f'], [], ['g']])
with self.test_session():
@@ -49,6 +51,7 @@ class RaggedTensorToSparseOpTest(test_util.TensorFlowTestCase):
self.assertAllEqual(st.values, b'a b c d e f g'.split())
self.assertAllEqual(st.dense_shape, [5, 3])
+ @test_util.run_deprecated_v1
def test3DRaggedTensorWithOneRaggedDimension(self):
rt = ragged.constant([[[1, 2], [3, 4]], [[5, 6], [7, 8], [9, 10]],
[[11, 12]], [], [[13, 14]]],
@@ -63,6 +66,7 @@ class RaggedTensorToSparseOpTest(test_util.TensorFlowTestCase):
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14])
self.assertAllEqual(st.dense_shape, [5, 3, 2])
+ @test_util.run_deprecated_v1
def test4DRaggedTensorWithOneRaggedDimension(self):
rt = ragged.constant(
[[[[1, 2], [3, 4]], [[5, 6], [7, 8]]], [], [[[9, 10], [11, 12]]]],
@@ -88,6 +92,7 @@ class RaggedTensorToSparseOpTest(test_util.TensorFlowTestCase):
])
self.assertAllEqual(st.dense_shape, [3, 2, 2, 2])
+ @test_util.run_deprecated_v1
def test4DRaggedTensorWithTwoRaggedDimensions(self):
rt = ragged.constant([[[[1, 2], [3, 4]], [[5, 6], [7, 8], [9, 10]]],
[[[11, 12]], [], [[13, 14]]], []],
@@ -135,6 +140,7 @@ class RaggedTensorToSparseOpTest(test_util.TensorFlowTestCase):
self.assertEqual(st.values.shape.as_list(), [7])
self.assertEqual(st.dense_shape.shape.as_list(), [3])
+ @test_util.run_deprecated_v1
def testKernelErrors(self):
# An empty vector, defined using a placeholder to ensure that we can't
# determine that it's invalid at graph-construction time.
@@ -173,6 +179,7 @@ class RaggedTensorToSparseOpTest(test_util.TensorFlowTestCase):
self.assertRaisesRegexp(errors.InvalidArgumentError, empty_splits_error,
ragged.to_sparse(bad_rt5).eval)
+ @test_util.run_deprecated_v1
def testGradient(self):
# rt1.shape == rt2.shape == [2, (D2), (D3), 2].
rt1 = ragged.constant([[[[1.0, 2.0], [3.0, 4.0]], [[5.0, 6.0]]]],
diff --git a/tensorflow/python/ops/ragged/ragged_to_tensor_op_test.py b/tensorflow/python/ops/ragged/ragged_to_tensor_op_test.py
index 688676e46c6..77499b9cb3c 100644
--- a/tensorflow/python/ops/ragged/ragged_to_tensor_op_test.py
+++ b/tensorflow/python/ops/ragged/ragged_to_tensor_op_test.py
@@ -30,6 +30,7 @@ from tensorflow.python.platform import googletest
class RaggedTensorToTensorOpTest(test_util.TensorFlowTestCase,
parameterized.TestCase):
+ @test_util.run_deprecated_v1
def testDocStringExamples(self):
"""Example from ragged_to_tensor.__doc__."""
rt = ragged.constant([[9, 8, 7], [], [6, 5], [4]])
@@ -97,6 +98,7 @@ class RaggedTensorToTensorOpTest(test_util.TensorFlowTestCase,
'expected': [[[[1], [2]], [[9], [9]], [[3], [9]]]],
},
)
+ @test_util.run_deprecated_v1
def testRaggedTensorToTensor(self,
rt_input,
expected,
@@ -132,6 +134,7 @@ class RaggedTensorToTensorOpTest(test_util.TensorFlowTestCase,
'error': (TypeError, "Expected int32, got 'a' of type 'str' instead"),
},
)
+ @test_util.run_deprecated_v1
def testError(self, rt_input, default, error, ragged_rank=None):
rt = ragged.constant(rt_input, ragged_rank=ragged_rank)
with self.assertRaisesRegexp(error[0], error[1]):
diff --git a/tensorflow/python/ops/ragged/ragged_where_op_test.py b/tensorflow/python/ops/ragged/ragged_where_op_test.py
index 03672e4521b..de83a549771 100644
--- a/tensorflow/python/ops/ragged/ragged_where_op_test.py
+++ b/tensorflow/python/ops/ragged/ragged_where_op_test.py
@@ -165,6 +165,7 @@ class RaggedWhereOpTest(test_util.TensorFlowTestCase, parameterized.TestCase):
y=ragged.constant_value([[[['a']]], [[['b']]]]),
expected=ragged.constant_value([[[[], [b'A']]], [[[b'b']]]])),
]) # pyformat: disable
+ @test_util.run_deprecated_v1
def testRaggedWhere(self, condition, expected, x=None, y=None):
result = ragged.where(condition, x, y)
self.assertEqual(
diff --git a/tensorflow/python/ops/sort_ops_test.py b/tensorflow/python/ops/sort_ops_test.py
index 8a92f492664..17ce604cbf1 100644
--- a/tensorflow/python/ops/sort_ops_test.py
+++ b/tensorflow/python/ops/sort_ops_test.py
@@ -25,6 +25,7 @@ from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors
from tensorflow.python.framework import ops
from tensorflow.python.framework import tensor_util
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import random_ops
from tensorflow.python.ops import sort_ops
@@ -33,9 +34,11 @@ from tensorflow.python.platform import test
class SortTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testRandom_lowDimensionality(self):
self._testRandom_lowDimensionality(negative_axis=False)
+ @test_util.run_deprecated_v1
def testRandom_lowDimensionality_negative(self):
self._testRandom_lowDimensionality(negative_axis=True)
@@ -53,6 +56,7 @@ class SortTest(test.TestCase):
np.sort(arr, axis=sort_axis),
sort_ops.sort(constant_op.constant(arr), axis=sort_axis).eval())
+ @test_util.run_deprecated_v1
def testRandom_highDimensionality(self):
np.random.seed(100)
for _ in range(20):
@@ -65,6 +69,7 @@ class SortTest(test.TestCase):
np.sort(arr, axis=sort_axis),
sort_ops.sort(constant_op.constant(arr), axis=sort_axis).eval())
+ @test_util.run_deprecated_v1
def testScalar(self):
# Create an empty scalar where the static shape is unknown.
zeros_length_1 = array_ops.zeros(
@@ -77,11 +82,13 @@ class SortTest(test.TestCase):
with self.assertRaises(errors.InvalidArgumentError):
sort.eval()
+ @test_util.run_deprecated_v1
def testNegativeOutOfBounds_staticShape(self):
arr = constant_op.constant([3, 4, 5])
with self.assertRaises(ValueError):
sort_ops.sort(arr, axis=-4)
+ @test_util.run_deprecated_v1
def testDescending(self):
arr = np.random.random((10, 5, 5))
with self.cached_session():
@@ -90,6 +97,7 @@ class SortTest(test.TestCase):
sort_ops.sort(
constant_op.constant(arr), axis=0, direction='DESCENDING').eval())
+ @test_util.run_deprecated_v1
def testSort_staticallyKnownRank_constantTransposition(self):
# The transposition array should be a constant if the rank of "values" is
# statically known.
@@ -107,6 +115,7 @@ class SortTest(test.TestCase):
tensor_util.constant_value(transposition),
[0, 4, 2, 3, 1])
+ @test_util.run_deprecated_v1
def testArgsort_1d(self):
arr = np.random.random(42)
with self.cached_session():
@@ -114,6 +123,7 @@ class SortTest(test.TestCase):
np.sort(arr),
array_ops.gather(arr, sort_ops.argsort(arr)).eval())
+ @test_util.run_deprecated_v1
def testArgsort(self):
arr = np.random.random((5, 6, 7, 8))
for axis in range(4):
diff --git a/tensorflow/python/ops/special_math_ops_test.py b/tensorflow/python/ops/special_math_ops_test.py
index 7438cdb3f11..94aaebed951 100644
--- a/tensorflow/python/ops/special_math_ops_test.py
+++ b/tensorflow/python/ops/special_math_ops_test.py
@@ -46,6 +46,7 @@ class LBetaTest(test.TestCase):
0.5, self.evaluate(math_ops.exp(special_math_ops.lbeta(x_one_half))))
self.assertEqual([], special_math_ops.lbeta(x_one).get_shape())
+ @test_util.run_deprecated_v1
def test_one_dimensional_arg_dynamic(self):
# Should evaluate to 1 and 1/2.
x_one = [1, 1.]
@@ -57,6 +58,7 @@ class LBetaTest(test.TestCase):
self.assertAllClose(0.5,
beta_ph.eval(feed_dict={ph: x_one_half}))
+ @test_util.run_deprecated_v1
def test_four_dimensional_arg_with_partial_shape_dynamic(self):
x_ = np.ones((3, 2, 3, 4))
# Gamma(1) = 0! = 1
@@ -81,6 +83,7 @@ class LBetaTest(test.TestCase):
self.evaluate(math_ops.exp(special_math_ops.lbeta(x_one_half))))
self.assertEqual((2,), special_math_ops.lbeta(x_one_half).get_shape())
+ @test_util.run_deprecated_v1
def test_two_dimensional_arg_dynamic(self):
# Should evaluate to 1/2.
x_one_half = [[2, 1.], [2, 1.]]
@@ -288,6 +291,7 @@ class EinsumTest(test.TestCase):
for case in self.long_cases:
self.run_test(case)
+ @test_util.run_deprecated_v1
def test_invalid(self):
for axes in self.invalid_cases:
inputs = [
@@ -297,6 +301,7 @@ class EinsumTest(test.TestCase):
with self.assertRaises(ValueError):
_ = special_math_ops.einsum(axes, *inputs)
+ @test_util.run_deprecated_v1
def test_invalid_keyword_arguments(self):
m0 = array_ops.placeholder(dtypes.int32, shape=(1, None))
m1 = array_ops.placeholder(dtypes.int32, shape=(None, 1))
@@ -311,11 +316,13 @@ class EinsumTest(test.TestCase):
invalid1='value1',
invalid2='value2')
+ @test_util.run_deprecated_v1
def test_repeated_axis_single_input(self):
x = array_ops.placeholder(dtypes.float32, shape=[2, 2])
with self.assertRaises(ValueError):
_ = special_math_ops.einsum('ii->', x)
+ @test_util.run_deprecated_v1
def test_dim_mismatch(self):
for axes, input_shapes in self.dim_mismatch_cases:
inputs = [
diff --git a/tensorflow/python/profiler/internal/run_metadata_test.py b/tensorflow/python/profiler/internal/run_metadata_test.py
index 216cc3dd54b..a8859f845b3 100644
--- a/tensorflow/python/profiler/internal/run_metadata_test.py
+++ b/tensorflow/python/profiler/internal/run_metadata_test.py
@@ -26,6 +26,7 @@ from tensorflow.core.protobuf import config_pb2
from tensorflow.core.protobuf import rewriter_config_pb2
from tensorflow.python.client import session
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import random_ops
from tensorflow.python.ops import variables
@@ -154,6 +155,7 @@ class RunMetadataTest(test.TestCase):
# deallocates the memory after matmul started.
self.assertGreater(random_allocs[1].alloc_micros, mm.all_start_micros)
+ @test_util.run_deprecated_v1
def testCPU(self):
ops.reset_default_graph()
with ops.device('/cpu:0'):
@@ -167,6 +169,7 @@ class RunMetadataTest(test.TestCase):
ret = _extract_node(run_meta, 'MatMul:MatMul')
self.assertEqual(len(ret), 0)
+ @test_util.run_deprecated_v1
def testLoopCPU(self):
ops.reset_default_graph()
with ops.device('/cpu:0'):
diff --git a/tensorflow/python/profiler/pprof_profiler_test.py b/tensorflow/python/profiler/pprof_profiler_test.py
index 11a3487360c..120a0d0eaa6 100644
--- a/tensorflow/python/profiler/pprof_profiler_test.py
+++ b/tensorflow/python/profiler/pprof_profiler_test.py
@@ -24,6 +24,7 @@ from proto import profile_pb2
from tensorflow.core.framework import step_stats_pb2
from tensorflow.core.protobuf import config_pb2
from tensorflow.python.framework import constant_op
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import control_flow_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.platform import test
@@ -135,6 +136,7 @@ comment: 9
profile.ParseFromString(profile_contents)
self.assertEquals(expected_proto, str(profile))
+ @test_util.run_deprecated_v1
def testProfileWithWhileLoop(self):
options = config_pb2.RunOptions()
options.trace_level = config_pb2.RunOptions.FULL_TRACE
diff --git a/tensorflow/python/profiler/profile_context_test.py b/tensorflow/python/profiler/profile_context_test.py
index 680cd71d1fc..885f08ca4b9 100644
--- a/tensorflow/python/profiler/profile_context_test.py
+++ b/tensorflow/python/profiler/profile_context_test.py
@@ -21,6 +21,7 @@ import os
from tensorflow.python.client import session
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import variables
from tensorflow.python.platform import gfile
from tensorflow.python.platform import test
@@ -35,6 +36,7 @@ builder = option_builder.ProfileOptionBuilder
class ProfilerContextTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testBasics(self):
ops.reset_default_graph()
outfile = os.path.join(test.get_temp_dir(), "dump")
@@ -69,6 +71,7 @@ class ProfilerContextTest(test.TestCase):
with gfile.Open(outfile, "r") as f:
self.assertEqual(profile_str, f.read())
+ @test_util.run_deprecated_v1
def testAutoTracingInDeubMode(self):
ops.reset_default_graph()
x = lib.BuildFullModel()
@@ -90,6 +93,7 @@ class ProfilerContextTest(test.TestCase):
for f in gfile.ListDirectory(test.get_temp_dir()):
self.assertFalse("run_meta" in f)
+ @test_util.run_deprecated_v1
def testDisabled(self):
ops.reset_default_graph()
x = lib.BuildFullModel()
diff --git a/tensorflow/python/profiler/profiler_test.py b/tensorflow/python/profiler/profiler_test.py
index eacb7d21e6a..e4f7361e5d7 100644
--- a/tensorflow/python/profiler/profiler_test.py
+++ b/tensorflow/python/profiler/profiler_test.py
@@ -21,6 +21,7 @@ import os
from tensorflow.core.protobuf import config_pb2
from tensorflow.python.client import session
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import variables
from tensorflow.python.platform import gfile
from tensorflow.python.platform import test
@@ -35,6 +36,7 @@ builder = option_builder.ProfileOptionBuilder
class ProfilerTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testProfileBasic(self):
ops.reset_default_graph()
outfile = os.path.join(test.get_temp_dir(), 'dump')
@@ -171,6 +173,7 @@ class ProfilerTest(test.TestCase):
checker = advice_pb.checkers['ExpensiveOperationChecker']
self.assertGreater(len(checker.reports), 0)
+ @test_util.run_deprecated_v1
def testMultipleProfilePerStep(self):
ops.reset_default_graph()
opts = (builder(builder.trainable_variables_parameter())
diff --git a/tensorflow/python/saved_model/loader_test.py b/tensorflow/python/saved_model/loader_test.py
index 3378bf08cd9..3b7f0b250e7 100644
--- a/tensorflow/python/saved_model/loader_test.py
+++ b/tensorflow/python/saved_model/loader_test.py
@@ -26,6 +26,7 @@ from absl.testing import parameterized
from tensorflow.python.client import session
from tensorflow.python.framework import errors
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import control_flow_ops
from tensorflow.python.ops import state_ops
from tensorflow.python.ops import variables
@@ -93,6 +94,7 @@ class SavedModelLoaderTest(test.TestCase, parameterized.TestCase):
super(SavedModelLoaderTest, self).tearDown()
shutil.rmtree(test.get_temp_dir(), ignore_errors=True)
+ @test_util.run_deprecated_v1
def test_load_function(self, builder_cls):
self.export_simple_graph(builder_cls)
loader = loader_impl.SavedModelLoader(SIMPLE_ADD_SAVED_MODEL)
@@ -108,6 +110,7 @@ class SavedModelLoaderTest(test.TestCase, parameterized.TestCase):
self.assertEqual(5, sess.graph.get_tensor_by_name("x:0").eval())
self.assertEqual(7, sess.graph.get_tensor_by_name("y:0").eval())
+ @test_util.run_deprecated_v1
def test_load_graph(self, builder_cls):
self.export_simple_graph(builder_cls)
loader = loader_impl.SavedModelLoader(SIMPLE_ADD_SAVED_MODEL)
@@ -127,6 +130,7 @@ class SavedModelLoaderTest(test.TestCase, parameterized.TestCase):
with self.assertRaises(errors.FailedPreconditionError):
self.evaluate(y)
+ @test_util.run_deprecated_v1
def test_load_with_import_scope(self, builder_cls):
self.export_graph_with_main_op(builder_cls)
loader = loader_impl.SavedModelLoader(SAVED_MODEL_WITH_MAIN_OP)
@@ -157,6 +161,7 @@ class SavedModelLoaderTest(test.TestCase, parameterized.TestCase):
self.assertEqual(5, sess.graph.get_tensor_by_name("baa/x:0").eval())
self.assertEqual(7, sess.graph.get_tensor_by_name("baa/y:0").eval())
+ @test_util.run_deprecated_v1
def test_restore_variables(self, builder_cls):
self.export_graph_with_main_op(builder_cls)
loader = loader_impl.SavedModelLoader(SAVED_MODEL_WITH_MAIN_OP)
@@ -174,6 +179,7 @@ class SavedModelLoaderTest(test.TestCase, parameterized.TestCase):
loader.restore_variables(sess, tf_saver.Saver())
self.assertEqual(55, self.evaluate(z))
+ @test_util.run_deprecated_v1
def test_run_init_op(self, builder_cls):
self.export_graph_with_main_op(builder_cls)
loader = loader_impl.SavedModelLoader(SAVED_MODEL_WITH_MAIN_OP)
@@ -206,6 +212,7 @@ class SavedModelLoaderTest(test.TestCase, parameterized.TestCase):
with self.assertRaises(RuntimeError):
loader.get_meta_graph_def_from_tags(["not_a_graph"])
+ @test_util.run_deprecated_v1
def test_load_saved_model_with_no_variables(self, builder_cls):
"""Test that SavedModel runs saver when there appear to be no variables.
diff --git a/tensorflow/python/saved_model/save_test.py b/tensorflow/python/saved_model/save_test.py
index 8fb28039a44..ef0a92fddd9 100644
--- a/tensorflow/python/saved_model/save_test.py
+++ b/tensorflow/python/saved_model/save_test.py
@@ -282,6 +282,7 @@ class SaveTest(test.TestCase):
{"out": model(array_ops.ones([1, 4]))},
self._import_and_infer(save_dir, {"x": [[1., 1., 1., 1.]]}))
+ @test_util.run_deprecated_v1
def test_export_functional_keras_model_after_fit(self):
x = input_layer.Input((1,))
y = core.Dense(1, name="y")(x)
diff --git a/tensorflow/python/saved_model/saved_model_test.py b/tensorflow/python/saved_model/saved_model_test.py
index efcd21cce3a..0f18fb1a016 100644
--- a/tensorflow/python/saved_model/saved_model_test.py
+++ b/tensorflow/python/saved_model/saved_model_test.py
@@ -199,6 +199,7 @@ class SavedModelTest(SavedModelTestBase):
constants.SAVED_MODEL_FILENAME_PBTXT):
loader.load(sess, ["foo"], export_dir)
+ @test_util.run_deprecated_v1
def testVerifySessionGraphUsage(self):
export_dir = self._get_export_dir("test_verify_session_graph_usage")
builder = saved_model_builder._SavedModelBuilder(export_dir)
@@ -219,6 +220,7 @@ class SavedModelTest(SavedModelTestBase):
self.assertEqual(
42, ops.get_collection(ops.GraphKeys.GLOBAL_VARIABLES)[0].eval())
+ @test_util.run_deprecated_v1
def testSequence(self):
export_dir = self._get_export_dir("test_sequence")
builder = saved_model_builder._SavedModelBuilder(export_dir)
@@ -236,6 +238,7 @@ class SavedModelTest(SavedModelTestBase):
self.assertRaises(AssertionError, builder.add_meta_graph_and_variables,
sess, ["baz"])
+ @test_util.run_deprecated_v1
def testTags(self):
export_dir = self._get_export_dir("test_tags")
builder = saved_model_builder._SavedModelBuilder(export_dir)
@@ -325,6 +328,7 @@ class SavedModelTest(SavedModelTestBase):
self.assertRaises(RuntimeError, loader.load, sess, ["foo", "baz"],
export_dir)
+ @test_util.run_deprecated_v1
def testVariables(self):
export_dir = self._get_export_dir("test_variables")
builder = saved_model_builder._SavedModelBuilder(export_dir)
@@ -377,6 +381,7 @@ class SavedModelTest(SavedModelTestBase):
self.assertRaises(errors.NotFoundError, loader.load, sess, ["baz"],
export_dir)
+ @test_util.run_deprecated_v1
def testGraphWithoutVariables(self):
export_dir = self._get_export_dir("test_graph_has_variables")
builder = saved_model_builder._SavedModelBuilder(export_dir)
@@ -412,6 +417,7 @@ class SavedModelTest(SavedModelTestBase):
c = a * b
self.assertEqual(30.0, self.evaluate(c))
+ @test_util.run_deprecated_v1
def testNoOverwrite(self):
export_dir = self._get_export_dir("test_no_overwrite")
builder = saved_model_builder._SavedModelBuilder(export_dir)
@@ -436,6 +442,7 @@ class SavedModelTest(SavedModelTestBase):
self.assertRaises(AssertionError, saved_model_builder._SavedModelBuilder,
export_dir)
+ @test_util.run_deprecated_v1
def testSaveAsText(self):
export_dir = self._get_export_dir("test_astext")
builder = saved_model_builder._SavedModelBuilder(export_dir)
@@ -467,6 +474,7 @@ class SavedModelTest(SavedModelTestBase):
self.assertEqual(
42, ops.get_collection(ops.GraphKeys.GLOBAL_VARIABLES)[0].eval())
+ @test_util.run_deprecated_v1
def testCollections(self):
export_dir = self._get_export_dir("test_collections")
builder = saved_model_builder._SavedModelBuilder(export_dir)
@@ -517,6 +525,7 @@ class SavedModelTest(SavedModelTestBase):
self.assertEqual(len(ops.get_collection("foo_vars")), 0)
+ @test_util.run_deprecated_v1
def testSignatureDefs(self):
export_dir = self._get_export_dir("test_signature_defs")
builder = saved_model_builder._SavedModelBuilder(export_dir)
@@ -604,6 +613,7 @@ class SavedModelTest(SavedModelTestBase):
self._validate_sig_def_keys(builder, valid_tensor_info,
constants.TRAIN_OP_SIGNATURE_KEY)
+ @test_util.run_deprecated_v1
def testSignatureDefValidationSucceedsWithName(self):
tensor_with_name = meta_graph_pb2.TensorInfo()
tensor_with_name.name = "foo"
@@ -617,6 +627,7 @@ class SavedModelTest(SavedModelTestBase):
builder = saved_model_builder._SavedModelBuilder(export_dir)
self._validate_outputs_tensor_info_accept(builder, tensor_with_name)
+ @test_util.run_deprecated_v1
def testSignatureDefValidationSucceedsWithCoo(self):
tensor_with_coo = meta_graph_pb2.TensorInfo()
# TODO(soergel) test validation of each of the fields of coo_sparse
@@ -631,6 +642,7 @@ class SavedModelTest(SavedModelTestBase):
builder = saved_model_builder._SavedModelBuilder(export_dir)
self._validate_outputs_tensor_info_accept(builder, tensor_with_coo)
+ @test_util.run_deprecated_v1
def testAssets(self):
export_dir = self._get_export_dir("test_assets")
builder = saved_model_builder._SavedModelBuilder(export_dir)
@@ -662,6 +674,7 @@ class SavedModelTest(SavedModelTestBase):
compat.as_bytes("ignored.txt"))
self.assertFalse(file_io.file_exists(ignored_asset_path))
+ @test_util.run_deprecated_v1
def testAssetsNameCollisionDiffFile(self):
export_dir = self._get_export_dir("test_assets_name_collision_diff_file")
builder = saved_model_builder._SavedModelBuilder(export_dir)
@@ -693,6 +706,7 @@ class SavedModelTest(SavedModelTestBase):
"asset_file_tensor_1:0",
asset_id=1)
+ @test_util.run_deprecated_v1
def testAssetsNameCollisionSameFilepath(self):
export_dir = self._get_export_dir("test_assets_name_collision_same_path")
builder = saved_model_builder._SavedModelBuilder(export_dir)
@@ -730,6 +744,7 @@ class SavedModelTest(SavedModelTestBase):
compat.as_bytes("hello42.txt_1"))
self.assertFalse(file_io.file_exists(ignored_asset_path))
+ @test_util.run_deprecated_v1
def testAssetsNameCollisionSameFile(self):
export_dir = self._get_export_dir("test_assets_name_collision_same_file")
builder = saved_model_builder._SavedModelBuilder(export_dir)
@@ -767,6 +782,7 @@ class SavedModelTest(SavedModelTestBase):
compat.as_bytes("hello42.txt_1"))
self.assertFalse(file_io.file_exists(ignored_asset_path))
+ @test_util.run_deprecated_v1
def testAssetsNameCollisionManyFiles(self):
export_dir = self._get_export_dir("test_assets_name_collision_many_files")
builder = saved_model_builder._SavedModelBuilder(export_dir)
@@ -838,6 +854,7 @@ class SavedModelTest(SavedModelTestBase):
# the main_op, following a restore.
self.assertEqual(3, ops.get_collection("v")[2].eval())
+ @test_util.run_deprecated_v1
def testTrainOp(self):
export_dir = self._get_export_dir("test_train_op")
builder = saved_model_builder._SavedModelBuilder(export_dir)
@@ -865,6 +882,7 @@ class SavedModelTest(SavedModelTestBase):
self.assertIsInstance(
loader_impl.get_train_op(meta_graph_def), ops.Tensor)
+ @test_util.run_deprecated_v1
def testTrainOpGroup(self):
export_dir = self._get_export_dir("test_train_op_group")
builder = saved_model_builder._SavedModelBuilder(export_dir)
@@ -892,6 +910,7 @@ class SavedModelTest(SavedModelTestBase):
self.assertIsInstance(
loader_impl.get_train_op(meta_graph_def), ops.Operation)
+ @test_util.run_deprecated_v1
def testTrainOpAfterVariables(self):
export_dir = self._get_export_dir("test_train_op_after_variables")
builder = saved_model_builder._SavedModelBuilder(export_dir)
@@ -922,6 +941,7 @@ class SavedModelTest(SavedModelTestBase):
loader.load(sess, ["pre_foo"], export_dir)
self.assertFalse(ops.get_collection(constants.TRAIN_OP_KEY))
+ @test_util.run_deprecated_v1
def testMultipleAssets(self):
export_dir = self._get_export_dir("test_multiple_assets")
builder = saved_model_builder._SavedModelBuilder(export_dir)
@@ -962,6 +982,7 @@ class SavedModelTest(SavedModelTestBase):
self._validate_assets(export_dir, bar_graph.asset_file_def, "bar.txt",
"content_bar", "asset_file_tensor:0")
+ @test_util.run_deprecated_v1
def testDuplicateAssets(self):
export_dir = self._get_export_dir("test_duplicate_assets")
builder = saved_model_builder._SavedModelBuilder(export_dir)
@@ -1008,6 +1029,7 @@ class SavedModelTest(SavedModelTestBase):
self._validate_assets(export_dir, bar_graph.asset_file_def, "foo.txt",
"content_foo", "asset_file_tensor:0")
+ @test_util.run_deprecated_v1
def testOp(self):
export_dir = self._get_export_dir("test_op")
builder = saved_model_builder._SavedModelBuilder(export_dir)
@@ -1080,6 +1102,7 @@ class SavedModelTest(SavedModelTestBase):
self.assertEqual(b"k1", v1.keys().eval())
self.assertEqual(3.0, v1.values().eval())
+ @test_util.run_deprecated_v1
def testCustomSaver(self):
export_dir = self._get_export_dir("test_custom_saver")
builder = saved_model_builder._SavedModelBuilder(export_dir)
@@ -1102,6 +1125,7 @@ class SavedModelTest(SavedModelTestBase):
self.assertEqual(
saved_graph.saver_def.restore_op_name, "my_saver/restore_all")
+ @test_util.run_deprecated_v1
def testNoCustomSaver(self):
export_dir = self._get_export_dir("test_no_custom_saver")
builder = saved_model_builder._SavedModelBuilder(export_dir)
@@ -1124,6 +1148,7 @@ class SavedModelTest(SavedModelTestBase):
self.assertEqual(
saved_graph.saver_def.restore_op_name, "save/restore_all")
+ @test_util.run_deprecated_v1
def testMultipleCustomSavers(self):
export_dir = self._get_export_dir("test_multiple_custom_savers")
builder = saved_model_builder._SavedModelBuilder(export_dir)
@@ -1154,6 +1179,7 @@ class SavedModelTest(SavedModelTestBase):
_validate_custom_saver("tag_1", "save_1/restore_all")
_validate_custom_saver("tag_2", "save_2/restore_all")
+ @test_util.run_deprecated_v1
def testImportScope(self):
export_dir = self._get_export_dir("test_scoped_assets")
builder = saved_model_builder._SavedModelBuilder(export_dir)
@@ -1205,6 +1231,7 @@ class SavedModelTest(SavedModelTestBase):
ops.get_default_graph().get_tensor_by_name(
"scope_name/constant_tensor_name:0").eval())
+ @test_util.run_deprecated_v1
def testClearDevices(self):
export_dir = self._get_export_dir("test_clear_devices")
builder = saved_model_builder._SavedModelBuilder(export_dir)
@@ -1323,6 +1350,7 @@ class SavedModelV1Test(SavedModelTestBase):
self.assertEqual(expected_asset_file_name, asset.filename)
self.assertEqual(expected_asset_tensor_name, asset.tensor_info.name)
+ @test_util.run_deprecated_v1
def testWritingAssetsToCollection(self):
export_dir = self._get_export_dir("test_writing_assets_to_collection")
builder = saved_model_builder.SavedModelBuilder(export_dir)
@@ -1355,12 +1383,14 @@ class SavedModelV1Test(SavedModelTestBase):
compat.as_bytes("ignored.txt"))
self.assertFalse(file_io.file_exists(ignored_asset_path))
+ @test_util.run_deprecated_v1
def testLegacyInitOpWithNonEmptyCollection(self):
export_dir = self._get_export_dir(
"test_legacy_init_op_with_non_empty_collection")
self._testInitOpsWithNonEmptyCollection(export_dir,
constants.LEGACY_INIT_OP_KEY)
+ @test_util.run_deprecated_v1
def testMainOpWithNonEmptyCollection(self):
export_dir = self._get_export_dir("test_main_op_with_non_empty_collection")
self._testInitOpsWithNonEmptyCollection(export_dir, constants.MAIN_OP_KEY)
@@ -1464,6 +1494,7 @@ class SavedModelV1Test(SavedModelTestBase):
self.assertIn("T", node_def.attr)
self.assertIn("Tout", node_def.attr)
+ @test_util.run_deprecated_v1
def testLegacyInitOp(self):
export_dir = self._get_export_dir("test_legacy_init_op")
builder = saved_model_builder.SavedModelBuilder(export_dir)
diff --git a/tensorflow/python/saved_model/signature_def_utils_test.py b/tensorflow/python/saved_model/signature_def_utils_test.py
index cc0fd8ce056..53c452359f1 100644
--- a/tensorflow/python/saved_model/signature_def_utils_test.py
+++ b/tensorflow/python/saved_model/signature_def_utils_test.py
@@ -22,6 +22,7 @@ from tensorflow.core.framework import types_pb2
from tensorflow.core.protobuf import meta_graph_pb2
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.platform import test
@@ -59,6 +60,7 @@ def _make_signature(inputs, outputs, name=None):
class SignatureDefUtilsTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testBuildSignatureDef(self):
x = array_ops.placeholder(dtypes.float32, 1, name="x")
x_tensor_info = utils.build_tensor_info(x)
@@ -89,6 +91,7 @@ class SignatureDefUtilsTest(test.TestCase):
self.assertEqual(types_pb2.DT_FLOAT, y_tensor_info_actual.dtype)
self.assertEqual(0, len(y_tensor_info_actual.tensor_shape.dim))
+ @test_util.run_deprecated_v1
def testRegressionSignatureDef(self):
input1 = constant_op.constant("a", name="input-1")
output1 = constant_op.constant(2.2, name="output-1")
@@ -114,6 +117,7 @@ class SignatureDefUtilsTest(test.TestCase):
self.assertEqual(types_pb2.DT_FLOAT, y_tensor_info_actual.dtype)
self.assertEqual(0, len(y_tensor_info_actual.tensor_shape.dim))
+ @test_util.run_deprecated_v1
def testClassificationSignatureDef(self):
input1 = constant_op.constant("a", name="input-1")
output1 = constant_op.constant("b", name="output-1")
@@ -145,6 +149,7 @@ class SignatureDefUtilsTest(test.TestCase):
self.assertEqual(types_pb2.DT_FLOAT, scores_tensor_info_actual.dtype)
self.assertEqual(0, len(scores_tensor_info_actual.tensor_shape.dim))
+ @test_util.run_deprecated_v1
def testPredictionSignatureDef(self):
input1 = constant_op.constant("a", name="input-1")
input2 = constant_op.constant("b", name="input-2")
@@ -181,11 +186,13 @@ class SignatureDefUtilsTest(test.TestCase):
self.assertEqual(types_pb2.DT_STRING, output2_tensor_info_actual.dtype)
self.assertEqual(0, len(output2_tensor_info_actual.tensor_shape.dim))
+ @test_util.run_deprecated_v1
def testTrainSignatureDef(self):
self._testSupervisedSignatureDef(
signature_def_utils_impl.supervised_train_signature_def,
signature_constants.SUPERVISED_TRAIN_METHOD_NAME)
+ @test_util.run_deprecated_v1
def testEvalSignatureDef(self):
self._testSupervisedSignatureDef(
signature_def_utils_impl.supervised_eval_signature_def,
@@ -239,11 +246,13 @@ class SignatureDefUtilsTest(test.TestCase):
self.assertEqual(
types_pb2.DT_FLOAT, signature_def.outputs["metrics/value"].dtype)
+ @test_util.run_deprecated_v1
def testTrainSignatureDefMissingInputs(self):
self._testSupervisedSignatureDefMissingInputs(
signature_def_utils_impl.supervised_train_signature_def,
signature_constants.SUPERVISED_TRAIN_METHOD_NAME)
+ @test_util.run_deprecated_v1
def testEvalSignatureDefMissingInputs(self):
self._testSupervisedSignatureDefMissingInputs(
signature_def_utils_impl.supervised_eval_signature_def,
diff --git a/tensorflow/python/saved_model/simple_save_test.py b/tensorflow/python/saved_model/simple_save_test.py
index 0d0665072ac..21c2e9df2fa 100644
--- a/tensorflow/python/saved_model/simple_save_test.py
+++ b/tensorflow/python/saved_model/simple_save_test.py
@@ -21,6 +21,7 @@ from __future__ import print_function
import os
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import variables
from tensorflow.python.platform import test
from tensorflow.python.saved_model import loader
@@ -53,6 +54,7 @@ class SimpleSaveTest(test.TestCase):
self.assertEqual(actual_tensor_info.tensor_shape.dim[i].size,
expected_tensor.shape[i])
+ @test_util.run_deprecated_v1
def testSimpleSave(self):
"""Test simple_save that uses the default parameters."""
export_dir = os.path.join(test.get_temp_dir(),
diff --git a/tensorflow/python/summary/summary_test.py b/tensorflow/python/summary/summary_test.py
index cacc28cc596..64f0f315c58 100644
--- a/tensorflow/python/summary/summary_test.py
+++ b/tensorflow/python/summary/summary_test.py
@@ -30,6 +30,7 @@ from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import meta_graph
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import variables
from tensorflow.python.platform import test
@@ -38,6 +39,7 @@ from tensorflow.python.summary import summary as summary_lib
class SummaryTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testScalarSummary(self):
with self.cached_session() as s:
i = constant_op.constant(3)
@@ -51,6 +53,7 @@ class SummaryTest(test.TestCase):
self.assertEqual(values[0].tag, 'outer/inner')
self.assertEqual(values[0].simple_value, 3.0)
+ @test_util.run_deprecated_v1
def testScalarSummaryWithFamily(self):
with self.cached_session() as s:
i = constant_op.constant(7)
@@ -74,6 +77,7 @@ class SummaryTest(test.TestCase):
self.assertEqual(values[0].tag, 'family/outer/family/inner_1')
self.assertEqual(values[0].simple_value, 7.0)
+ @test_util.run_deprecated_v1
def testSummarizingVariable(self):
with self.cached_session() as s:
c = constant_op.constant(42.0)
@@ -89,6 +93,7 @@ class SummaryTest(test.TestCase):
self.assertEqual(value.tag, 'summary')
self.assertEqual(value.simple_value, 42.0)
+ @test_util.run_deprecated_v1
def testImageSummary(self):
with self.cached_session() as s:
i = array_ops.ones((5, 4, 4, 3))
@@ -103,6 +108,7 @@ class SummaryTest(test.TestCase):
expected = sorted('outer/inner/image/{}'.format(i) for i in xrange(3))
self.assertEqual(tags, expected)
+ @test_util.run_deprecated_v1
def testImageSummaryWithFamily(self):
with self.cached_session() as s:
i = array_ops.ones((5, 2, 3, 1))
@@ -119,6 +125,7 @@ class SummaryTest(test.TestCase):
for i in xrange(3))
self.assertEqual(tags, expected)
+ @test_util.run_deprecated_v1
def testHistogramSummary(self):
with self.cached_session() as s:
i = array_ops.ones((5, 4, 4, 3))
@@ -130,6 +137,7 @@ class SummaryTest(test.TestCase):
self.assertEqual(len(summary.value), 1)
self.assertEqual(summary.value[0].tag, 'outer/inner')
+ @test_util.run_deprecated_v1
def testHistogramSummaryWithFamily(self):
with self.cached_session() as s:
i = array_ops.ones((5, 4, 4, 3))
@@ -148,6 +156,7 @@ class SummaryTest(test.TestCase):
const = constant_op.constant(10, dtype=dtype)
summary_lib.histogram('h', const)
+ @test_util.run_deprecated_v1
def testAudioSummary(self):
with self.cached_session() as s:
i = array_ops.ones((5, 3, 4))
@@ -162,6 +171,7 @@ class SummaryTest(test.TestCase):
expected = sorted('outer/inner/audio/{}'.format(i) for i in xrange(3))
self.assertEqual(tags, expected)
+ @test_util.run_deprecated_v1
def testAudioSummaryWithFamily(self):
with self.cached_session() as s:
i = array_ops.ones((5, 3, 4))
@@ -178,6 +188,7 @@ class SummaryTest(test.TestCase):
for i in xrange(3))
self.assertEqual(tags, expected)
+ @test_util.run_deprecated_v1
def testTextSummary(self):
with self.cached_session():
with self.assertRaises(ValueError):
@@ -193,6 +204,7 @@ class SummaryTest(test.TestCase):
summ = summary_lib.text('foo', array_ops.constant('one'))
self.assertEqual(summ.op.type, 'TensorSummaryV2')
+ @test_util.run_deprecated_v1
def testSummaryNameConversion(self):
c = constant_op.constant(3)
s = summary_lib.scalar('name with spaces', c)
@@ -204,6 +216,7 @@ class SummaryTest(test.TestCase):
s3 = summary_lib.scalar('/name/with/leading/slash', c)
self.assertEqual(s3.op.name, 'name/with/leading/slash')
+ @test_util.run_deprecated_v1
def testSummaryWithFamilyMetaGraphExport(self):
with ops.name_scope('outer'):
i = constant_op.constant(11)
diff --git a/tensorflow/python/summary/writer/writer_test.py b/tensorflow/python/summary/writer/writer_test.py
index 20b62e5016a..d702ddc0a27 100644
--- a/tensorflow/python/summary/writer/writer_test.py
+++ b/tensorflow/python/summary/writer/writer_test.py
@@ -35,6 +35,7 @@ from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import meta_graph
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import summary_ops_v2
from tensorflow.python.platform import gfile
from tensorflow.python.platform import test
@@ -100,6 +101,7 @@ class FileWriterTestCase(test.TestCase):
# We should be done.
self.assertRaises(StopIteration, lambda: next(rr))
+ @test_util.run_deprecated_v1
def testAddingSummaryGraphAndRunMetadata(self):
test_dir = self._CleanTestDir("basics")
sw = self._FileWriter(test_dir)
@@ -173,6 +175,7 @@ class FileWriterTestCase(test.TestCase):
# We should be done.
self.assertRaises(StopIteration, lambda: next(rr))
+ @test_util.run_deprecated_v1
def testGraphAsNamed(self):
test_dir = self._CleanTestDir("basics_named_graph")
with ops.Graph().as_default() as g:
@@ -181,6 +184,7 @@ class FileWriterTestCase(test.TestCase):
sw.close()
self._assertEventsWithGraph(test_dir, g, True)
+ @test_util.run_deprecated_v1
def testGraphAsPositional(self):
test_dir = self._CleanTestDir("basics_positional_graph")
with ops.Graph().as_default() as g:
@@ -189,6 +193,7 @@ class FileWriterTestCase(test.TestCase):
sw.close()
self._assertEventsWithGraph(test_dir, g, True)
+ @test_util.run_deprecated_v1
def testGraphDefAsNamed(self):
test_dir = self._CleanTestDir("basics_named_graph_def")
with ops.Graph().as_default() as g:
@@ -198,6 +203,7 @@ class FileWriterTestCase(test.TestCase):
sw.close()
self._assertEventsWithGraph(test_dir, g, False)
+ @test_util.run_deprecated_v1
def testGraphDefAsPositional(self):
test_dir = self._CleanTestDir("basics_positional_graph_def")
with ops.Graph().as_default() as g:
@@ -207,6 +213,7 @@ class FileWriterTestCase(test.TestCase):
sw.close()
self._assertEventsWithGraph(test_dir, g, False)
+ @test_util.run_deprecated_v1
def testGraphAndGraphDef(self):
with self.assertRaises(ValueError):
test_dir = self._CleanTestDir("basics_graph_and_graph_def")
@@ -216,12 +223,14 @@ class FileWriterTestCase(test.TestCase):
sw = self._FileWriter(test_dir, graph=g, graph_def=gd)
sw.close()
+ @test_util.run_deprecated_v1
def testNeitherGraphNorGraphDef(self):
with self.assertRaises(TypeError):
test_dir = self._CleanTestDir("basics_string_instead_of_graph")
sw = self._FileWriter(test_dir, "string instead of graph object")
sw.close()
+ @test_util.run_deprecated_v1
def testCloseAndReopen(self):
test_dir = self._CleanTestDir("close_and_reopen")
sw = self._FileWriter(test_dir)
@@ -265,6 +274,7 @@ class FileWriterTestCase(test.TestCase):
# We should be done.
self.assertRaises(StopIteration, lambda: next(rr))
+ @test_util.run_deprecated_v1
def testNonBlockingClose(self):
test_dir = self._CleanTestDir("non_blocking_close")
sw = self._FileWriter(test_dir)
@@ -274,6 +284,7 @@ class FileWriterTestCase(test.TestCase):
sw.close()
self._assertRecent(time_before_close)
+ @test_util.run_deprecated_v1
def testUseAfterClose(self):
test_dir = self._CleanTestDir("use_after_close")
sw = self._FileWriter(test_dir)
@@ -289,6 +300,7 @@ class FileWriterTestCase(test.TestCase):
for w in triggered:
self.assertEqual(w.category, UserWarning)
+ @test_util.run_deprecated_v1
def testWithStatement(self):
test_dir = self._CleanTestDir("with_statement")
with self._FileWriter(test_dir) as sw:
@@ -299,6 +311,7 @@ class FileWriterTestCase(test.TestCase):
# Checks that values returned from session Run() calls are added correctly to
# summaries. These are numpy types so we need to check they fit in the
# protocol buffers correctly.
+ @test_util.run_deprecated_v1
def testAddingSummariesFromSessionRunCalls(self):
test_dir = self._CleanTestDir("global_step")
sw = self._FileWriter(test_dir)
@@ -345,6 +358,7 @@ class FileWriterTestCase(test.TestCase):
# We should be done.
self.assertRaises(StopIteration, lambda: next(rr))
+ @test_util.run_deprecated_v1
def testPluginMetadataStrippedFromSubsequentEvents(self):
test_dir = self._CleanTestDir("basics")
sw = self._FileWriter(test_dir)
@@ -404,6 +418,7 @@ class FileWriterTestCase(test.TestCase):
# We should be done.
self.assertRaises(StopIteration, lambda: next(rr))
+ @test_util.run_deprecated_v1
def testFileWriterWithSuffix(self):
test_dir = self._CleanTestDir("test_suffix")
sw = self._FileWriter(test_dir, filename_suffix="_test_suffix")
diff --git a/tensorflow/python/tools/freeze_graph_test.py b/tensorflow/python/tools/freeze_graph_test.py
index 5dc14a6961e..efdf7dd2cf1 100644
--- a/tensorflow/python/tools/freeze_graph_test.py
+++ b/tensorflow/python/tools/freeze_graph_test.py
@@ -161,9 +161,11 @@ class FreezeGraphTest(test_util.TensorFlowTestCase):
},)
builder.save(as_text=True)
+ @test_util.run_deprecated_v1
def testFreezeGraphV1(self):
self._testFreezeGraph(saver_pb2.SaverDef.V1)
+ @test_util.run_deprecated_v1
def testFreezeGraphV2(self):
self._testFreezeGraph(saver_pb2.SaverDef.V2)
diff --git a/tensorflow/python/tools/optimize_for_inference_test.py b/tensorflow/python/tools/optimize_for_inference_test.py
index 10bfb0dc706..310776ff1b0 100644
--- a/tensorflow/python/tools/optimize_for_inference_test.py
+++ b/tensorflow/python/tools/optimize_for_inference_test.py
@@ -128,6 +128,7 @@ class OptimizeForInferenceTest(test.TestCase):
graph_def, [], [add_name], dtypes.float32.as_datatype_enum)
self.assertProtoEquals(expected_output, output)
+ @test_util.run_deprecated_v1
def testFoldBatchNorms(self):
with self.cached_session() as sess:
inputs = [1, 4, 2, 5, 3, 6, -1, -4, -2, -5, -3, -6]
@@ -171,6 +172,7 @@ class OptimizeForInferenceTest(test.TestCase):
for node in optimized_graph_def.node:
self.assertNotEqual("BatchNormWithGlobalNormalization", node.op)
+ @test_util.run_deprecated_v1
def testFoldFusedBatchNorms(self):
for data_format, use_gpu in [("NHWC", False), ("NCHW", True)]:
with self.cached_session(use_gpu=use_gpu) as sess:
@@ -222,6 +224,7 @@ class OptimizeForInferenceTest(test.TestCase):
for node in optimized_graph_def.node:
self.assertNotEqual("FusedBatchNorm", node.op)
+ @test_util.run_deprecated_v1
def testFuseResizePadAndConv(self):
with self.cached_session() as sess:
inputs = [1, 4, 2, 5, 3, 6, -1, -4, -2, -5, -3, -6]
@@ -253,6 +256,7 @@ class OptimizeForInferenceTest(test.TestCase):
self.assertNotEqual("MirrorPad", node.op)
self.assertNotEqual("ResizeBilinear", node.op)
+ @test_util.run_deprecated_v1
def testFuseResizeAndConv(self):
with self.cached_session() as sess:
inputs = [1, 4, 2, 5, 3, 6, -1, -4, -2, -5, -3, -6]
@@ -282,6 +286,7 @@ class OptimizeForInferenceTest(test.TestCase):
self.assertNotEqual("MirrorPad", node.op)
+ @test_util.run_deprecated_v1
def testFusePadAndConv(self):
with self.cached_session() as sess:
inputs = [1, 4, 2, 5, 3, 6, -1, -4, -2, -5, -3, -6]
diff --git a/tensorflow/python/training/adadelta_test.py b/tensorflow/python/training/adadelta_test.py
index 7cbaf1039f9..0e5af5a9222 100644
--- a/tensorflow/python/training/adadelta_test.py
+++ b/tensorflow/python/training/adadelta_test.py
@@ -166,6 +166,7 @@ class AdadeltaOptimizerTest(test.TestCase):
with context.eager_mode():
self.doTestBasic(use_resource=True, use_callable_params=True)
+ @test_util.run_deprecated_v1
def testMinimizeSparseResourceVariable(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
diff --git a/tensorflow/python/training/adagrad_da_test.py b/tensorflow/python/training/adagrad_da_test.py
index c7c47206a9c..aacfe6faf4e 100644
--- a/tensorflow/python/training/adagrad_da_test.py
+++ b/tensorflow/python/training/adagrad_da_test.py
@@ -22,6 +22,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import embedding_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import resource_variable_ops
@@ -73,12 +74,15 @@ class AdagradDAOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(
np.array([-0.094821, -0.189358]), v1_val)
+ @test_util.run_deprecated_v1
def testAdagradDAWithoutRegularizationBasic1(self):
self.doTestAdagradDAwithoutRegularizationBasic1()
+ @test_util.run_deprecated_v1
def testResourceAdagradDAWithoutRegularizationBasic1(self):
self.doTestAdagradDAwithoutRegularizationBasic1(use_resource=True)
+ @test_util.run_deprecated_v1
def testMinimizeSparseResourceVariable(self):
for dtype in [dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -100,6 +104,7 @@ class AdagradDAOptimizerTest(test.TestCase):
self.evaluate(var0),
rtol=0.01)
+ @test_util.run_deprecated_v1
def testAdagradDAwithoutRegularizationBasic2(self):
for dtype in [dtypes.float64, dtypes.float32]:
with self.cached_session() as sess:
@@ -132,6 +137,7 @@ class AdagradDAOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(
np.array([-0.094821, -0.189358]), v1_val)
+ @test_util.run_deprecated_v1
def testAdagradDAWithL1(self):
for dtype in [dtypes.float64, dtypes.float32]:
with self.cached_session() as sess:
@@ -164,6 +170,7 @@ class AdagradDAOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(
np.array([-0.085339, -0.17989]), v1_val)
+ @test_util.run_deprecated_v1
def testAdagradDAWithL1_L2(self):
for dtype in [dtypes.float64, dtypes.float32]:
with self.cached_session() as sess:
diff --git a/tensorflow/python/training/adagrad_test.py b/tensorflow/python/training/adagrad_test.py
index 962e65c41f5..da26fcdb7f6 100644
--- a/tensorflow/python/training/adagrad_test.py
+++ b/tensorflow/python/training/adagrad_test.py
@@ -96,6 +96,7 @@ class AdagradOptimizerTest(test.TestCase):
def testBasicLocked(self):
self.doTestBasic(use_locking=True)
+ @test_util.run_deprecated_v1
def testMinimizeSparseResourceVariable(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -116,6 +117,7 @@ class AdagradOptimizerTest(test.TestCase):
self.evaluate(var0),
atol=0.01)
+ @test_util.run_deprecated_v1
def testTensorLearningRate(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -142,6 +144,7 @@ class AdagradOptimizerTest(test.TestCase):
np.array([2.715679168701172, 3.715679168701172]),
self.evaluate(var1))
+ @test_util.run_deprecated_v1
def testSparseBasic(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -173,6 +176,7 @@ class AdagradOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(
np.array([[3.0], [3.715679168701172]]), self.evaluate(var1))
+ @test_util.run_deprecated_v1
def testSparseRepeatedIndices(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -203,6 +207,7 @@ class AdagradOptimizerTest(test.TestCase):
self.assertAllClose(aggregated_update_var.eval(),
self.evaluate(repeated_index_update_var))
+ @test_util.run_deprecated_v1
def testSparseRepeatedIndicesResourceVariable(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -227,6 +232,7 @@ class AdagradOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(
self.evaluate(var_repeated), self.evaluate(var_aggregated))
+ @test_util.run_deprecated_v1
def testSparseStability(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -263,6 +269,7 @@ class AdagradOptimizerTest(test.TestCase):
-0.01029443
]]), self.evaluate(var0))
+ @test_util.run_deprecated_v1
def testSharing(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -299,6 +306,7 @@ class AdagradOptimizerTest(test.TestCase):
np.array([2.715679168701172, 3.715679168701172]),
self.evaluate(var1))
+ @test_util.run_deprecated_v1
def testDynamicShapeVariable_Ok(self):
with self.cached_session():
v = variable_scope.get_variable("v", initializer=constant_op.constant(1.),
@@ -307,6 +315,7 @@ class AdagradOptimizerTest(test.TestCase):
# Creating optimizer should cause no exception.
adagrad.AdagradOptimizer(3.0, initial_accumulator_value=0.1)
+ @test_util.run_deprecated_v1
def testDynamicShapeVariableWithCallableInit(self):
var0 = variable_scope.get_variable("var0",
initializer=constant_op.constant(1.),
diff --git a/tensorflow/python/training/adam_test.py b/tensorflow/python/training/adam_test.py
index 87dad0a8a65..b0bae275773 100644
--- a/tensorflow/python/training/adam_test.py
+++ b/tensorflow/python/training/adam_test.py
@@ -102,12 +102,15 @@ class AdamOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(var0_np, self.evaluate(var0))
self.assertAllCloseAccordingToType(var1_np, self.evaluate(var1))
+ @test_util.run_deprecated_v1
def testSparse(self):
self.doTestSparse(use_resource=False)
+ @test_util.run_deprecated_v1
def testResourceSparse(self):
self.doTestSparse(use_resource=True)
+ @test_util.run_deprecated_v1
def testSparseDevicePlacement(self):
for index_dtype in [dtypes.int32, dtypes.int64]:
with self.cached_session(force_gpu=test.is_gpu_available()):
@@ -121,6 +124,7 @@ class AdamOptimizerTest(test.TestCase):
variables.global_variables_initializer().run()
minimize_op.run()
+ @test_util.run_deprecated_v1
def testSparseRepeatedIndices(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -236,6 +240,7 @@ class AdamOptimizerTest(test.TestCase):
with context.eager_mode():
self.doTestBasic(use_resource=True, use_callable_params=True)
+ @test_util.run_deprecated_v1
def testTensorLearningRate(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -274,6 +279,7 @@ class AdamOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(var0_np, self.evaluate(var0))
self.assertAllCloseAccordingToType(var1_np, self.evaluate(var1))
+ @test_util.run_deprecated_v1
def testSharing(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
diff --git a/tensorflow/python/training/basic_loops_test.py b/tensorflow/python/training/basic_loops_test.py
index 5f5718e64a6..511a8334d56 100644
--- a/tensorflow/python/training/basic_loops_test.py
+++ b/tensorflow/python/training/basic_loops_test.py
@@ -23,6 +23,7 @@ import shutil
from tensorflow.python.framework import errors_impl
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.platform import test
from tensorflow.python.training import basic_loops
from tensorflow.python.training import supervisor
@@ -37,6 +38,7 @@ def _test_dir(test_name):
class BasicTrainLoopTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testBasicTrainLoop(self):
logdir = _test_dir("basic_train_loop")
sv = supervisor.Supervisor(logdir=logdir)
@@ -55,6 +57,7 @@ class BasicTrainLoopTest(test.TestCase):
sv, train_fn, args=(sv, "y"), kwargs={"a": "A"})
self.assertEqual(3, num_calls[0])
+ @test_util.run_deprecated_v1
def testBasicTrainLoopExceptionAborts(self):
logdir = _test_dir("basic_train_loop_exception_aborts")
sv = supervisor.Supervisor(logdir=logdir)
@@ -71,6 +74,7 @@ class BasicTrainLoopTest(test.TestCase):
with self.assertRaisesRegexp(RuntimeError, "Failed"):
basic_loops.basic_train_loop(sv, train_fn)
+ @test_util.run_deprecated_v1
def testBasicTrainLoopRetryOnAborted(self):
logdir = _test_dir("basic_train_loop_exception_aborts")
sv = supervisor.Supervisor(logdir=logdir)
diff --git a/tensorflow/python/training/basic_session_run_hooks_test.py b/tensorflow/python/training/basic_session_run_hooks_test.py
index 03810b57e37..8e54a14f47c 100644
--- a/tensorflow/python/training/basic_session_run_hooks_test.py
+++ b/tensorflow/python/training/basic_session_run_hooks_test.py
@@ -34,6 +34,7 @@ from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors
from tensorflow.python.framework import meta_graph
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import control_flow_ops
from tensorflow.python.ops import state_ops
@@ -91,10 +92,12 @@ class MockCheckpointSaverListener(
class SecondOrStepTimerTest(test.TestCase):
+ @test_util.run_deprecated_v1
def test_raise_in_both_secs_and_steps(self):
with self.assertRaises(ValueError):
basic_session_run_hooks.SecondOrStepTimer(every_secs=2.0, every_steps=10)
+ @test_util.run_deprecated_v1
def test_raise_in_none_secs_and_steps(self):
with self.assertRaises(ValueError):
basic_session_run_hooks.SecondOrStepTimer()
@@ -413,11 +416,13 @@ class CheckpointSaverHookTest(test.TestCase):
basic_session_run_hooks.CheckpointSaverHook(
self.model_dir, saver=self.scaffold.saver, scaffold=self.scaffold)
+ @test_util.run_deprecated_v1
def test_raise_in_both_secs_and_steps(self):
with self.assertRaises(ValueError):
basic_session_run_hooks.CheckpointSaverHook(
self.model_dir, save_secs=10, save_steps=20)
+ @test_util.run_deprecated_v1
def test_raise_in_none_secs_and_steps(self):
with self.assertRaises(ValueError):
basic_session_run_hooks.CheckpointSaverHook(self.model_dir)
@@ -1143,11 +1148,13 @@ class SummarySaverHookTest(test.TestCase):
basic_session_run_hooks.SummarySaverHook(
scaffold=monitored_session.Scaffold(), summary_op=self.summary_op)
+ @test_util.run_deprecated_v1
def test_raise_in_both_secs_and_steps(self):
with self.assertRaises(ValueError):
basic_session_run_hooks.SummarySaverHook(
save_secs=10, save_steps=20, summary_writer=self.summary_writer)
+ @test_util.run_deprecated_v1
def test_raise_in_none_secs_and_steps(self):
with self.assertRaises(ValueError):
basic_session_run_hooks.SummarySaverHook(
@@ -1478,10 +1485,12 @@ class ProfilerHookTest(test.TestCase):
def _count_timeline_files(self):
return len(gfile.Glob(self.filepattern))
+ @test_util.run_deprecated_v1
def test_raise_in_both_secs_and_steps(self):
with self.assertRaises(ValueError):
basic_session_run_hooks.ProfilerHook(save_secs=10, save_steps=20)
+ @test_util.run_deprecated_v1
def test_raise_in_none_secs_and_steps(self):
with self.assertRaises(ValueError):
basic_session_run_hooks.ProfilerHook(save_secs=None, save_steps=None)
diff --git a/tensorflow/python/training/checkpoint_management_test.py b/tensorflow/python/training/checkpoint_management_test.py
index b61ed17531a..8606ec4a206 100644
--- a/tensorflow/python/training/checkpoint_management_test.py
+++ b/tensorflow/python/training/checkpoint_management_test.py
@@ -62,6 +62,7 @@ class LatestCheckpointWithRelativePaths(test.TestCase):
finally:
shutil.rmtree(tempdir)
+ @test_util.run_deprecated_v1
def testNameCollision(self):
# Make sure we have a clean directory to work in.
with self.tempDir() as tempdir:
@@ -99,6 +100,7 @@ class LatestCheckpointWithRelativePaths(test.TestCase):
self.assertIsNotNone(
checkpoint_management.latest_checkpoint(traindir))
+ @test_util.run_deprecated_v1
def testRelativePath(self):
# Make sure we have a clean directory to work in.
with self.tempDir() as tempdir:
@@ -270,6 +272,7 @@ class SaverUtilsTest(test.TestCase):
def tearDown(self):
gfile.DeleteRecursively(self._base_dir)
+ @test_util.run_deprecated_v1
def testCheckpointExists(self):
for sharded in (False, True):
for version in (saver_pb2.SaverDef.V2, saver_pb2.SaverDef.V1):
@@ -288,6 +291,7 @@ class SaverUtilsTest(test.TestCase):
ckpt_prefix = checkpoint_management.latest_checkpoint(self._base_dir)
self.assertTrue(checkpoint_management.checkpoint_exists(ckpt_prefix))
+ @test_util.run_deprecated_v1
def testGetCheckpointMtimes(self):
prefixes = []
for version in (saver_pb2.SaverDef.V2, saver_pb2.SaverDef.V1):
@@ -302,6 +306,7 @@ class SaverUtilsTest(test.TestCase):
self.assertEqual(2, len(mtimes))
self.assertTrue(mtimes[1] >= mtimes[0])
+ @test_util.run_deprecated_v1
def testRemoveCheckpoint(self):
for sharded in (False, True):
for version in (saver_pb2.SaverDef.V2, saver_pb2.SaverDef.V1):
diff --git a/tensorflow/python/training/device_setter_test.py b/tensorflow/python/training/device_setter_test.py
index 85b75502ab0..3cff87b326f 100644
--- a/tensorflow/python/training/device_setter_test.py
+++ b/tensorflow/python/training/device_setter_test.py
@@ -19,6 +19,7 @@ from __future__ import division
from __future__ import print_function
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import resource_variable_ops
from tensorflow.python.ops import variables
from tensorflow.python.platform import test
@@ -33,6 +34,7 @@ class DeviceSetterTest(test.TestCase):
"worker": ["worker0:2222", "worker1:2222", "worker2:2222"]
})
+ @test_util.run_deprecated_v1
def testCPUOverride(self):
with ops.device(
device_setter.replica_device_setter(cluster=self._cluster_spec)):
@@ -47,12 +49,14 @@ class DeviceSetterTest(test.TestCase):
self.assertDeviceEqual("/job:ps/task:1", w.initializer.device)
self.assertDeviceEqual("/job:worker/cpu:0", a.device)
+ @test_util.run_deprecated_v1
def testResource(self):
with ops.device(
device_setter.replica_device_setter(cluster=self._cluster_spec)):
v = resource_variable_ops.ResourceVariable([1, 2])
self.assertDeviceEqual("/job:ps/task:0", v.device)
+ @test_util.run_deprecated_v1
def testPS2TasksWithClusterSpecClass(self):
with ops.device(
device_setter.replica_device_setter(cluster=self._cluster_spec)):
@@ -65,6 +69,7 @@ class DeviceSetterTest(test.TestCase):
self.assertDeviceEqual("/job:ps/task:1", w.initializer.device)
self.assertDeviceEqual("/job:worker", a.device)
+ @test_util.run_deprecated_v1
def testPS2TasksPinVariableToJob(self):
with ops.device(
device_setter.replica_device_setter(cluster=self._cluster_spec)):
@@ -82,6 +87,7 @@ class DeviceSetterTest(test.TestCase):
self.assertDeviceEqual("/job:ps/task:1", x.initializer.device)
self.assertDeviceEqual("/job:worker", a.device)
+ @test_util.run_deprecated_v1
def testPS2TasksUseCpuForPS(self):
with ops.device(
device_setter.replica_device_setter(ps_tasks=1, ps_device="/cpu:0")):
@@ -95,6 +101,7 @@ class DeviceSetterTest(test.TestCase):
self.assertDeviceEqual("/job:moon/cpu:0", w.initializer.device)
self.assertDeviceEqual("/job:worker", a.device)
+ @test_util.run_deprecated_v1
def testPS2TasksNoMerging(self):
with ops.device(
device_setter.replica_device_setter(
@@ -109,6 +116,7 @@ class DeviceSetterTest(test.TestCase):
self.assertDeviceEqual("/job:ps", w.initializer.device)
self.assertDeviceEqual("/job:worker", a.device)
+ @test_util.run_deprecated_v1
def testPS2TasksWithClusterSpecDict(self):
with ops.device(
device_setter.replica_device_setter(cluster=self._cluster_spec.as_dict(
@@ -122,6 +130,7 @@ class DeviceSetterTest(test.TestCase):
self.assertDeviceEqual("/job:ps/task:1", w.initializer.device)
self.assertDeviceEqual("/job:worker", a.device)
+ @test_util.run_deprecated_v1
def testPS2TasksWithClusterDef(self):
with ops.device(
device_setter.replica_device_setter(
@@ -135,6 +144,7 @@ class DeviceSetterTest(test.TestCase):
self.assertDeviceEqual("/job:ps/task:1", w.initializer.device)
self.assertDeviceEqual("/job:worker", a.device)
+ @test_util.run_deprecated_v1
def testPS2TasksWithDevice(self):
cluster_spec = server_lib.ClusterSpec({
"sun": ["sun0:2222", "sun1:2222", "sun2:2222"],
@@ -155,6 +165,7 @@ class DeviceSetterTest(test.TestCase):
self.assertDeviceEqual("/job:moon/task:1", w.initializer.device)
self.assertDeviceEqual("/job:sun", a.device)
+ @test_util.run_deprecated_v1
def testPS2TasksWithCPUConstraint(self):
cluster_spec = server_lib.ClusterSpec({
"sun": ["sun0:2222", "sun1:2222", "sun2:2222"],
diff --git a/tensorflow/python/training/ftrl_test.py b/tensorflow/python/training/ftrl_test.py
index 70b5db31f80..39b299c64a3 100644
--- a/tensorflow/python/training/ftrl_test.py
+++ b/tensorflow/python/training/ftrl_test.py
@@ -23,6 +23,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import embedding_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import resource_variable_ops
@@ -68,12 +69,15 @@ class FtrlOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(
np.array([-0.28432083, -0.56694895]), v1_val)
+ @test_util.run_deprecated_v1
def testFtrlWithoutRegularization(self):
self.doTestFtrlwithoutRegularization(use_resource=False)
+ @test_util.run_deprecated_v1
def testResourceFtrlWithoutRegularization(self):
self.doTestFtrlwithoutRegularization(use_resource=True)
+ @test_util.run_deprecated_v1
def testFtrlwithoutRegularization2(self):
for dtype in [dtypes.half, dtypes.float32]:
with self.cached_session() as sess:
@@ -103,6 +107,7 @@ class FtrlOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(
np.array([-0.28232238, -0.56096673]), v1_val)
+ @test_util.run_deprecated_v1
def testMinimizeSparseResourceVariable(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -121,6 +126,7 @@ class FtrlOptimizerTest(test.TestCase):
self.evaluate(var0),
atol=0.01)
+ @test_util.run_deprecated_v1
def testFtrlWithL1(self):
for dtype in [dtypes.half, dtypes.float32]:
with self.cached_session() as sess:
@@ -150,6 +156,7 @@ class FtrlOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(
np.array([-0.93460727, -1.86147261]), v1_val)
+ @test_util.run_deprecated_v1
def testFtrlWithL1_L2(self):
for dtype in [dtypes.half, dtypes.float32]:
with self.cached_session() as sess:
@@ -180,6 +187,7 @@ class FtrlOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(
np.array([-0.02406147, -0.04830509]), v1_val)
+ @test_util.run_deprecated_v1
def testFtrlWithL1_L2_L2Shrinkage(self):
"""Test the new FTRL op with support for l2 shrinkage.
@@ -217,6 +225,7 @@ class FtrlOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(
np.array([-0.14378493, -0.13229476]), v1_val)
+ @test_util.run_deprecated_v1
def testFtrlWithL1_L2_L2ShrinkageSparse(self):
"""Tests the new FTRL op with support for l2 shrinkage on sparse grads."""
for dtype in [dtypes.half, dtypes.float32]:
@@ -251,6 +260,7 @@ class FtrlOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType([[-0.22578995], [2.]], v0_val)
self.assertAllCloseAccordingToType([[4.], [-0.13229476]], v1_val)
+ @test_util.run_deprecated_v1
def testFtrlWithL2ShrinkageDoesNotChangeLrSchedule(self):
"""Verifies that l2 shrinkage in FTRL does not change lr schedule."""
for dtype in [dtypes.half, dtypes.float32]:
@@ -335,6 +345,7 @@ class FtrlOptimizerTest(test.TestCase):
# with Adagrad.
# So, basing on these two properties, we test if our implementation of
# FTRL-Proximal performs same updates as Adagrad or GradientDescent.
+ @test_util.run_deprecated_v1
def testEquivAdagradwithoutRegularization(self):
for dtype in [dtypes.half, dtypes.float32]:
with self.cached_session():
@@ -355,6 +366,7 @@ class FtrlOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(val0, val2)
self.assertAllCloseAccordingToType(val1, val3)
+ @test_util.run_deprecated_v1
def testEquivSparseAdagradwithoutRegularization(self):
for dtype in [dtypes.half, dtypes.float32]:
with self.cached_session():
@@ -378,6 +390,7 @@ class FtrlOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(val0, val2)
self.assertAllCloseAccordingToType(val1, val3)
+ @test_util.run_deprecated_v1
def testEquivSparseGradientDescentwithoutRegularization(self):
for dtype in [dtypes.half, dtypes.float32]:
with self.cached_session():
@@ -401,6 +414,7 @@ class FtrlOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(val0, val2)
self.assertAllCloseAccordingToType(val1, val3)
+ @test_util.run_deprecated_v1
def testEquivGradientDescentwithoutRegularization(self):
for dtype in [dtypes.half, dtypes.float32]:
with self.cached_session():
diff --git a/tensorflow/python/training/gradient_descent_test.py b/tensorflow/python/training/gradient_descent_test.py
index 2028e7b4b09..5a6c5cfa747 100644
--- a/tensorflow/python/training/gradient_descent_test.py
+++ b/tensorflow/python/training/gradient_descent_test.py
@@ -24,6 +24,7 @@ from tensorflow.python.eager import function
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import embedding_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import resource_variable_ops
@@ -35,6 +36,7 @@ from tensorflow.python.training import gradient_descent
class GradientDescentOptimizerTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testBasic(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -58,6 +60,7 @@ class GradientDescentOptimizerTest(test.TestCase):
self.evaluate(var1))
self.assertEqual(0, len(optimizer.variables()))
+ @test_util.run_deprecated_v1
def testBasicResourceVariable(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -83,6 +86,7 @@ class GradientDescentOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType([3.0 - 3.0 * 0.01, 4.0 - 3.0 * 0.01],
self.evaluate(var1))
+ @test_util.run_deprecated_v1
def testBasicCallableParams(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -109,6 +113,7 @@ class GradientDescentOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType([3.0 - 3.0 * 0.01, 4.0 - 3.0 * 0.01],
self.evaluate(var1))
+ @test_util.run_deprecated_v1
def testMinimizeResourceVariable(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -135,6 +140,7 @@ class GradientDescentOptimizerTest(test.TestCase):
[[1.0 - np_grad * 4.0, 2.0 - np_grad * 5.0]], self.evaluate(var0))
self.assertAllCloseAccordingToType([3.0 - np_grad], self.evaluate(var1))
+ @test_util.run_deprecated_v1
def testMinimizeSparseResourceVariable(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -162,6 +168,7 @@ class GradientDescentOptimizerTest(test.TestCase):
[[1.0 - np_grad * 4.0, 2.0 - np_grad * 5.0]], self.evaluate(var0))
self.assertAllCloseAccordingToType([3.0 - np_grad], self.evaluate(var1))
+ @test_util.run_deprecated_v1
def testTensorLearningRate(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -184,6 +191,7 @@ class GradientDescentOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType([3.0 - 3.0 * 0.01, 4.0 - 3.0 * 0.01],
self.evaluate(var1))
+ @test_util.run_deprecated_v1
def testGradWrtRef(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -195,6 +203,7 @@ class GradientDescentOptimizerTest(test.TestCase):
for grad, _ in grads_and_vars:
self.assertAllCloseAccordingToType([1.0], self.evaluate(grad))
+ @test_util.run_deprecated_v1
def testWithGlobalStep(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -218,6 +227,7 @@ class GradientDescentOptimizerTest(test.TestCase):
self.evaluate(var1))
self.assertAllCloseAccordingToType(1, self.evaluate(global_step))
+ @test_util.run_deprecated_v1
def testSparseBasic(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
diff --git a/tensorflow/python/training/input_test.py b/tensorflow/python/training/input_test.py
index 327f0871383..a3d268a0174 100644
--- a/tensorflow/python/training/input_test.py
+++ b/tensorflow/python/training/input_test.py
@@ -28,6 +28,7 @@ from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors_impl
from tensorflow.python.framework import sparse_tensor
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import variables
@@ -41,6 +42,7 @@ from tensorflow.python.util import compat
class MatchFilenamesOnceTest(test_lib.TestCase):
+ @test_util.run_deprecated_v1
def test(self):
temp_dir = self.get_temp_dir()
filenames = [os.path.join(temp_dir, n) for n in os.listdir(temp_dir)]
@@ -68,6 +70,7 @@ class MatchFilenamesOnceTest(test_lib.TestCase):
class LimitEpochsTest(test_lib.TestCase):
+ @test_util.run_deprecated_v1
def testNoLimit(self):
with self.cached_session():
seven = constant_op.constant(7)
@@ -76,6 +79,7 @@ class LimitEpochsTest(test_lib.TestCase):
for _ in range(100):
self.assertEqual(7, self.evaluate(seven_forever))
+ @test_util.run_deprecated_v1
def testLimit(self):
with self.cached_session():
love_me = constant_op.constant("Love Me")
@@ -90,6 +94,7 @@ class LimitEpochsTest(test_lib.TestCase):
class InputProducerTest(test_lib.TestCase):
+ @test_util.run_deprecated_v1
def testNoShuffle(self):
with self.cached_session():
input_tensor = [[1, 2, 3, 4],
@@ -114,6 +119,7 @@ class InputProducerTest(test_lib.TestCase):
for thread in threads:
thread.join()
+ @test_util.run_deprecated_v1
def testNoShapeInference(self):
with self.cached_session():
# Disable shape inference for the input.
@@ -139,6 +145,7 @@ class InputProducerTest(test_lib.TestCase):
for thread in threads:
thread.join()
+ @test_util.run_deprecated_v1
def testShapeError(self):
input_tensor = array_ops.placeholder(dtypes.float32, None)
with self.assertRaisesRegexp(ValueError, "fully defined shape"):
@@ -147,6 +154,7 @@ class InputProducerTest(test_lib.TestCase):
class StringInputProducerTest(test_lib.TestCase):
+ @test_util.run_deprecated_v1
def testNoShuffle(self):
with self.cached_session():
strings = [b"to", b"be", b"or", b"not", b"to", b"be"]
@@ -169,6 +177,7 @@ class StringInputProducerTest(test_lib.TestCase):
for thread in threads:
thread.join()
+ @test_util.run_deprecated_v1
def testShuffle(self):
with self.cached_session():
strings = [b"a", b"b", b"c"]
@@ -214,6 +223,7 @@ class StringInputProducerTest(test_lib.TestCase):
with self.assertRaises(ValueError):
_ = inp.string_input_producer([])
+ @test_util.run_deprecated_v1
def testNullString(self):
# Runtime check for empty string list. This is slightly oblique:
# The queue runner should die with an assertion error on the null
@@ -233,6 +243,7 @@ class StringInputProducerTest(test_lib.TestCase):
for thread in threads:
thread.join()
+ @test_util.run_deprecated_v1
def testSharedName(self):
with self.cached_session():
strings = [b"to", b"be", b"or", b"not", b"to", b"be"]
@@ -241,6 +252,7 @@ class StringInputProducerTest(test_lib.TestCase):
self.assertProtoEquals("s: 'SHARED_NAME_XYZ'",
queue.queue_ref.op.node_def.attr["shared_name"])
+ @test_util.run_deprecated_v1
def testConstructionRace(self):
with self.cached_session() as sess:
strings = [b"to", b"be", b"or", b"not", b"to", b"be"]
@@ -263,6 +275,7 @@ class StringInputProducerTest(test_lib.TestCase):
class RangeInputProducerTest(test_lib.TestCase):
+ @test_util.run_deprecated_v1
def testNoShuffle(self):
with self.cached_session():
num_epochs = 3
@@ -285,6 +298,7 @@ class RangeInputProducerTest(test_lib.TestCase):
for thread in threads:
thread.join()
+ @test_util.run_deprecated_v1
def testShuffle(self):
with self.cached_session():
num_epochs = 200
@@ -324,6 +338,7 @@ class RangeInputProducerTest(test_lib.TestCase):
for thread in threads:
thread.join()
+ @test_util.run_deprecated_v1
def testSharedName(self):
with self.cached_session():
range_size = 5
@@ -335,6 +350,7 @@ class RangeInputProducerTest(test_lib.TestCase):
class SliceInputProducerTest(test_lib.TestCase):
+ @test_util.run_deprecated_v1
def testNoShuffle(self):
with self.cached_session() as sess:
num_epochs = 3
@@ -359,6 +375,7 @@ class SliceInputProducerTest(test_lib.TestCase):
for thread in threads:
thread.join()
+ @test_util.run_deprecated_v1
def testShuffle(self):
with self.cached_session() as sess:
num_epochs = 1200
@@ -403,6 +420,7 @@ class SliceInputProducerTest(test_lib.TestCase):
for thread in threads:
thread.join()
+ @test_util.run_deprecated_v1
def testSharedName(self):
with self.cached_session():
source_strings = ["A", "B", "D", "G"]
@@ -495,12 +513,15 @@ class BatchTest(test_lib.TestCase):
for thread in threads:
thread.join()
+ @test_util.run_deprecated_v1
def testOneThread(self):
self._testOneThreadHelper(use_dict=False)
+ @test_util.run_deprecated_v1
def testOneThreadDict(self):
self._testOneThreadHelper(use_dict=True)
+ @test_util.run_deprecated_v1
def testUint32DataTypes(self):
values = constant_op.constant([0, 1, 2, 3, 4, 5], dtype=dtypes.uint32)
batched = inp.batch([values], batch_size=2)
@@ -512,6 +533,7 @@ class BatchTest(test_lib.TestCase):
for thread in threads:
thread.join()
+ @test_util.run_deprecated_v1
def testUint64DataTypes(self):
values = constant_op.constant([0, 1, 2, 3, 4, 5], dtype=dtypes.uint64)
batched = inp.batch([values], batch_size=2)
@@ -523,6 +545,7 @@ class BatchTest(test_lib.TestCase):
for thread in threads:
thread.join()
+ @test_util.run_deprecated_v1
def testOneThreadDynamicPad(self):
with self.cached_session() as sess:
batch_size = 10
@@ -553,6 +576,7 @@ class BatchTest(test_lib.TestCase):
for thread in threads:
thread.join()
+ @test_util.run_deprecated_v1
def testOneThreadEnqueueMany(self):
with self.cached_session() as sess:
batch_size = 10
@@ -588,6 +612,7 @@ class BatchTest(test_lib.TestCase):
for thread in threads:
thread.join()
+ @test_util.run_deprecated_v1
def testManyThreads(self):
with self.cached_session() as sess:
batch_size = 10
@@ -628,6 +653,7 @@ class BatchTest(test_lib.TestCase):
for thread in threads:
thread.join()
+ @test_util.run_deprecated_v1
def testOneThreadSmallerBatch(self):
with self.cached_session() as sess:
batch_size = 10
@@ -685,6 +711,7 @@ class BatchTest(test_lib.TestCase):
for thread in threads:
thread.join()
+ @test_util.run_deprecated_v1
def testManyThreadsSmallerBatch(self):
with self.cached_session() as sess:
batch_size = 10
@@ -740,6 +767,7 @@ class BatchTest(test_lib.TestCase):
for thread in threads:
thread.join()
+ @test_util.run_deprecated_v1
def testSharedName(self):
with self.cached_session():
batch_size = 10
@@ -757,12 +785,14 @@ class BatchTest(test_lib.TestCase):
"s: 'SHARED_NAME_XYZ'",
batched[0].op.inputs[0].op.node_def.attr["shared_name"])
+ @test_util.run_deprecated_v1
def testCannotInferRankError(self):
with self.cached_session():
x = array_ops.placeholder(dtype=dtypes.int64)
with self.assertRaisesRegexp(ValueError, "Cannot infer Tensor's rank"):
inp.batch([x], batch_size=2)
+ @test_util.run_deprecated_v1
def testBatchedSparseTensorInferredShape(self):
sparse = sparse_tensor.SparseTensor(
indices=[[0]], values=[1.0], dense_shape=[1])
@@ -770,6 +800,7 @@ class BatchTest(test_lib.TestCase):
batched = inp.batch([sparse], batch_size=2)
self.assertAllEqual((2,), batched.dense_shape.get_shape().as_list())
+ @test_util.run_deprecated_v1
def testBatchedSparseTensorInferredShapeEnqueueMany(self):
sparse = sparse_tensor.SparseTensor(
indices=[[0]], values=[1.0], dense_shape=[1])
@@ -777,6 +808,7 @@ class BatchTest(test_lib.TestCase):
batched = inp.batch([sparse], batch_size=2, enqueue_many=True)
self.assertAllEqual((1,), batched.dense_shape.get_shape().as_list())
+ @test_util.run_deprecated_v1
def testBatchedSparseTensorInferredShapeUnknownRank(self):
sparse = sparse_tensor.SparseTensor(
indices=array_ops.placeholder(dtypes.int64),
@@ -786,6 +818,7 @@ class BatchTest(test_lib.TestCase):
batched = inp.batch([sparse], batch_size=2)
self.assertIs(None, batched.dense_shape.get_shape().num_elements())
+ @test_util.run_deprecated_v1
def testBatchedSparseTensorInferredShapeUnknownRankEnqueueMany(self):
sparse = sparse_tensor.SparseTensor(
indices=array_ops.placeholder(dtypes.int64),
@@ -795,6 +828,7 @@ class BatchTest(test_lib.TestCase):
batched = inp.batch([sparse], batch_size=2, enqueue_many=True)
self.assertIs(None, batched.dense_shape.get_shape().num_elements())
+ @test_util.run_deprecated_v1
def testSingleElementDict(self):
x = inp.batch({"c": [12, 12]}, batch_size=8)
self.assertAllEqual((8, 2), x["c"].get_shape().as_list())
@@ -838,24 +872,31 @@ class BatchTest(test_lib.TestCase):
for thread in threads:
thread.join()
+ @test_util.run_deprecated_v1
def testSingleThreadKeepInput(self):
self._testKeepInputHelper(1, False)
+ @test_util.run_deprecated_v1
def testSingleThreadKeepInputEnqueueMany(self):
self._testKeepInputHelper(1, True)
+ @test_util.run_deprecated_v1
def testMultipleThreadKeepInput(self):
self._testKeepInputHelper(5, False)
+ @test_util.run_deprecated_v1
def testMultipleThreadKeepInputEnqueueMany(self):
self._testKeepInputHelper(5, True)
+ @test_util.run_deprecated_v1
def testMaybeEnqueuePerExample(self):
self._testKeepInputHelper(1, True, keep_input_vector=True)
+ @test_util.run_deprecated_v1
def testMultipleThreadMaybeEnqueuePerExample(self):
self._testKeepInputHelper(5, True, keep_input_vector=True)
+ @test_util.run_deprecated_v1
def testInvalidKeepInputVector(self):
# Can't have vector `keep_input` with `enqueue_many=False`.
with self.assertRaisesRegexp(ValueError, "`keep_input` cannot be a vector"):
@@ -877,6 +918,7 @@ class BatchTest(test_lib.TestCase):
batch_size=1,
enqueue_many=True)
+ @test_util.run_deprecated_v1
def testMaybeBatchedSparseTensorInferredShape(self):
sparse = sparse_tensor.SparseTensor(
indices=[[0]], values=[1.0], dense_shape=[1])
@@ -884,6 +926,7 @@ class BatchTest(test_lib.TestCase):
batched = inp.maybe_batch([sparse], keep_input=True, batch_size=2)
self.assertAllEqual((2,), batched.dense_shape.get_shape().as_list())
+ @test_util.run_deprecated_v1
def testMaybeBatchedSparseTensorInferredShapeEnqueueMany(self):
sparse = sparse_tensor.SparseTensor(
indices=[[0]], values=[1.0], dense_shape=[1])
@@ -892,6 +935,7 @@ class BatchTest(test_lib.TestCase):
[sparse], keep_input=True, batch_size=2, enqueue_many=True)
self.assertAllEqual((1,), batched.dense_shape.get_shape().as_list())
+ @test_util.run_deprecated_v1
def testMaybeBatchedSparseTensorInferredShapeEnqueueManyPerExample(self):
sparse = sparse_tensor.SparseTensor(
indices=[[0], [0]], values=[1.0, 2.0], dense_shape=[2])
@@ -900,6 +944,7 @@ class BatchTest(test_lib.TestCase):
[sparse], keep_input=[True, False], batch_size=2, enqueue_many=True)
self.assertAllEqual((1,), batched.dense_shape.get_shape().as_list())
+ @test_util.run_deprecated_v1
def testMaybeBatchedSparseTensorInferredShapeUnknownRank(self):
sparse = sparse_tensor.SparseTensor(
indices=array_ops.placeholder(dtypes.int64),
@@ -909,6 +954,7 @@ class BatchTest(test_lib.TestCase):
batched = inp.maybe_batch([sparse], keep_input=True, batch_size=2)
self.assertIs(None, batched.dense_shape.get_shape().num_elements())
+ @test_util.run_deprecated_v1
def testMaybeBatchedSparseTensorInferredShapeUnknownRankEnqueueMany(self):
sparse = sparse_tensor.SparseTensor(
indices=array_ops.placeholder(dtypes.int64),
@@ -919,6 +965,7 @@ class BatchTest(test_lib.TestCase):
[sparse], keep_input=True, batch_size=2, enqueue_many=True)
self.assertIs(None, batched.dense_shape.get_shape().num_elements())
+ @test_util.run_deprecated_v1
def testMaybeBatchedSparseTensorInferredShapeUnknownRankPerExample(self):
sparse = sparse_tensor.SparseTensor(
indices=array_ops.placeholder(dtypes.int64),
@@ -929,6 +976,7 @@ class BatchTest(test_lib.TestCase):
[sparse], keep_input=[True, False], batch_size=2, enqueue_many=True)
self.assertIs(None, batched.dense_shape.get_shape().num_elements())
+ @test_util.run_deprecated_v1
def testMaybeBatchCorrectValues(self):
sparse_t = sparse_tensor.SparseTensor(
indices=[[0, 1], [0, 2], [1, 0], [1, 3]],
@@ -1055,12 +1103,15 @@ class BatchJoinTest(test_lib.TestCase):
for thread in threads:
thread.join()
+ @test_util.run_deprecated_v1
def testTwoThreads(self):
self._testTwoThreadsHelper(use_dict=False)
+ @test_util.run_deprecated_v1
def testTwoThreadsDict(self):
self._testTwoThreadsHelper(use_dict=True)
+ @test_util.run_deprecated_v1
def testMismatchedDictKeys(self):
with self.assertRaisesRegexp(ValueError, "must have the same keys"):
inp.batch_join(
@@ -1075,6 +1126,7 @@ class BatchJoinTest(test_lib.TestCase):
}],
batch_size=8)
+ @test_util.run_deprecated_v1
def testTwoThreadsDynamicPad(self):
with self.cached_session() as sess:
# Two threads, the first generates (0..69, ["a"] * 1..70).
@@ -1152,6 +1204,7 @@ class BatchJoinTest(test_lib.TestCase):
for thread in threads:
thread.join()
+ @test_util.run_deprecated_v1
def testTwoThreadsSmallerBatch(self):
with self.cached_session() as sess:
extra_elements = 2
@@ -1253,6 +1306,7 @@ class BatchJoinTest(test_lib.TestCase):
for thread in threads:
thread.join()
+ @test_util.run_deprecated_v1
def testTwoThreadsDynamicPadSmallerBatch(self):
with self.cached_session() as sess:
extra_elements = 2
@@ -1351,6 +1405,7 @@ class BatchJoinTest(test_lib.TestCase):
for thread in threads:
thread.join()
+ @test_util.run_deprecated_v1
def testSharedName(self):
with self.cached_session():
batch_size = 10
@@ -1373,12 +1428,14 @@ class BatchJoinTest(test_lib.TestCase):
"s: 'SHARED_NAME_XYZ'",
batched[0].op.inputs[0].op.node_def.attr["shared_name"])
+ @test_util.run_deprecated_v1
def testCannotInferRankError(self):
with self.cached_session():
x = array_ops.placeholder(dtype=dtypes.int64)
with self.assertRaisesRegexp(ValueError, "Cannot infer Tensor's rank"):
inp.batch_join([[x]], batch_size=2)
+ @test_util.run_deprecated_v1
def testSingleElementDict(self):
x = inp.batch_join([{"c": [12, 12]}], batch_size=8)
self.assertAllEqual((8, 2), x["c"].get_shape().as_list())
@@ -1425,24 +1482,31 @@ class BatchJoinTest(test_lib.TestCase):
for thread in threads:
thread.join()
+ @test_util.run_deprecated_v1
def testSingleThreadKeepInput(self):
self._testKeepInputHelper(1, False)
+ @test_util.run_deprecated_v1
def testSingleThreadKeepInputEnqueueMany(self):
self._testKeepInputHelper(1, True)
+ @test_util.run_deprecated_v1
def testMultipleThreadKeepInput(self):
self._testKeepInputHelper(5, False)
+ @test_util.run_deprecated_v1
def testMultipleThreadKeepInputEnqueueMany(self):
self._testKeepInputHelper(5, True)
+ @test_util.run_deprecated_v1
def testSingleThreadKeepInputPerExample(self):
self._testKeepInputHelper(1, True, keep_input_vector=True)
+ @test_util.run_deprecated_v1
def testMultipleThreadKeepInputPerExample(self):
self._testKeepInputHelper(5, True, keep_input_vector=True)
+ @test_util.run_deprecated_v1
def testInvalidKeepInputVector(self):
# Can't have vector `keep_input` with `enqueue_many=False`.
with self.assertRaisesRegexp(ValueError, "`keep_input` cannot be a vector"):
@@ -1464,6 +1528,7 @@ class BatchJoinTest(test_lib.TestCase):
batch_size=1,
enqueue_many=True)
+ @test_util.run_deprecated_v1
def testMaybeBatchedSparseTensorInferredShape(self):
sparse = sparse_tensor.SparseTensor(
indices=[[0]], values=[1.0], dense_shape=[1])
@@ -1471,6 +1536,7 @@ class BatchJoinTest(test_lib.TestCase):
batched = inp.maybe_batch_join([[sparse]], keep_input=True, batch_size=2)
self.assertAllEqual((2,), batched.dense_shape.get_shape().as_list())
+ @test_util.run_deprecated_v1
def testMaybeBatchedSparseTensorInferredShapeEnqueueMany(self):
sparse = sparse_tensor.SparseTensor(
indices=[[0]], values=[1.0], dense_shape=[1])
@@ -1479,6 +1545,7 @@ class BatchJoinTest(test_lib.TestCase):
[[sparse]], keep_input=True, batch_size=2, enqueue_many=True)
self.assertAllEqual((1,), batched.dense_shape.get_shape().as_list())
+ @test_util.run_deprecated_v1
def testMaybeBatchedSparseTensorInferredShapeEnqueueManyPerExample(self):
sparse = sparse_tensor.SparseTensor(
indices=[[0], [0]], values=[1.0, 2.0], dense_shape=[2])
@@ -1487,6 +1554,7 @@ class BatchJoinTest(test_lib.TestCase):
[[sparse]], keep_input=[True, False], batch_size=2, enqueue_many=True)
self.assertAllEqual((1,), batched.dense_shape.get_shape().as_list())
+ @test_util.run_deprecated_v1
def testMaybeBatchedSparseTensorInferredShapeUnknownRank(self):
sparse = sparse_tensor.SparseTensor(
indices=array_ops.placeholder(dtypes.int64),
@@ -1496,6 +1564,7 @@ class BatchJoinTest(test_lib.TestCase):
batched = inp.maybe_batch_join([[sparse]], keep_input=True, batch_size=2)
self.assertIs(None, batched.dense_shape.get_shape().num_elements())
+ @test_util.run_deprecated_v1
def testMaybeBatchedSparseTensorInferredShapeUnknownRankEnqueueMany(self):
sparse = sparse_tensor.SparseTensor(
indices=array_ops.placeholder(dtypes.int64),
@@ -1506,6 +1575,7 @@ class BatchJoinTest(test_lib.TestCase):
[[sparse]], keep_input=True, batch_size=2, enqueue_many=True)
self.assertIs(None, batched.dense_shape.get_shape().num_elements())
+ @test_util.run_deprecated_v1
def testMaybeBatchedSparseTensorInferredShapeUnknownRankPerExample(self):
sparse = sparse_tensor.SparseTensor(
indices=array_ops.placeholder(dtypes.int64),
@@ -1516,6 +1586,7 @@ class BatchJoinTest(test_lib.TestCase):
[[sparse]], keep_input=[True, False], batch_size=2, enqueue_many=True)
self.assertIs(None, batched.dense_shape.get_shape().num_elements())
+ @test_util.run_deprecated_v1
def testMaybeBatchCorrectValues(self):
sparse = sparse_tensor.SparseTensor(
indices=[[0, 1], [0, 2], [1, 0], [1, 3]],
@@ -1601,12 +1672,15 @@ class ShuffleBatchTest(test_lib.TestCase):
for thread in threads:
thread.join()
+ @test_util.run_deprecated_v1
def testOneThread(self):
self._testOneThreadHelper(use_dict=False)
+ @test_util.run_deprecated_v1
def testOneThreadDict(self):
self._testOneThreadHelper(use_dict=True)
+ @test_util.run_deprecated_v1
def testOneThreadSmallerBatch(self):
with self.cached_session() as sess:
batch_size = 10
@@ -1663,6 +1737,7 @@ class ShuffleBatchTest(test_lib.TestCase):
for thread in threads:
thread.join()
+ @test_util.run_deprecated_v1
def testManyThreads(self):
with self.cached_session() as sess:
batch_size = 10
@@ -1710,6 +1785,7 @@ class ShuffleBatchTest(test_lib.TestCase):
for thread in threads:
thread.join()
+ @test_util.run_deprecated_v1
def testManyThreadsSmallerBatch(self):
with self.cached_session() as sess:
batch_size = 10
@@ -1768,6 +1844,7 @@ class ShuffleBatchTest(test_lib.TestCase):
for thread in threads:
thread.join()
+ @test_util.run_deprecated_v1
def testSharedName(self):
with self.cached_session():
batch_size = 10
@@ -1828,24 +1905,31 @@ class ShuffleBatchTest(test_lib.TestCase):
for thread in threads:
thread.join()
+ @test_util.run_deprecated_v1
def testSingleThreadKeepInput(self):
self._testKeepInputHelper(1, False)
+ @test_util.run_deprecated_v1
def testSingleThreadKeepInputEnqueueMany(self):
self._testKeepInputHelper(1, True)
+ @test_util.run_deprecated_v1
def testMultipleThreadKeepInput(self):
self._testKeepInputHelper(5, False)
+ @test_util.run_deprecated_v1
def testMultipleThreadKeepInputEnqueueMany(self):
self._testKeepInputHelper(5, True)
+ @test_util.run_deprecated_v1
def testSingleThreadKeepInputPerExample(self):
self._testKeepInputHelper(1, True, keep_input_vector=True)
+ @test_util.run_deprecated_v1
def testMultipleThreadKeepInputPerExample(self):
self._testKeepInputHelper(5, True, keep_input_vector=True)
+ @test_util.run_deprecated_v1
def testInvalidKeepInputVector(self):
# Can't have vector `keep_input` with `enqueue_many=False`.
with self.assertRaisesRegexp(ValueError, "`keep_input` cannot be a vector"):
@@ -1864,6 +1948,7 @@ class ShuffleBatchTest(test_lib.TestCase):
keep_input=array_ops.placeholder(dtypes.bool),
enqueue_many=True)
+ @test_util.run_deprecated_v1
def testMaybeBatchedSparseTensorInferredShape(self):
sparse = sparse_tensor.SparseTensor(
indices=[[0]], values=[1.0], dense_shape=[1])
@@ -1871,6 +1956,7 @@ class ShuffleBatchTest(test_lib.TestCase):
batched = inp.maybe_shuffle_batch([sparse], 2, 10, 1, True)
self.assertAllEqual((2,), batched.dense_shape.get_shape().as_list())
+ @test_util.run_deprecated_v1
def testMaybeBatchedSparseTensorInferredShapeEnqueueMany(self):
sparse = sparse_tensor.SparseTensor(
indices=[[0]], values=[1.0], dense_shape=[1])
@@ -1879,6 +1965,7 @@ class ShuffleBatchTest(test_lib.TestCase):
[sparse], 2, 10, 1, True, enqueue_many=True)
self.assertAllEqual((1,), batched.dense_shape.get_shape().as_list())
+ @test_util.run_deprecated_v1
def testMaybeBatchedSparseTensorInferredShapeEnqueueManyPerExample(self):
sparse = sparse_tensor.SparseTensor(
indices=[[0], [0]], values=[1.0, 2.0], dense_shape=[2])
@@ -1887,6 +1974,7 @@ class ShuffleBatchTest(test_lib.TestCase):
[sparse], 2, 10, 1, [True, False], enqueue_many=True)
self.assertAllEqual((1,), batched.dense_shape.get_shape().as_list())
+ @test_util.run_deprecated_v1
def testMaybeBatchedSparseTensorInferredShapeUnknownRank(self):
sparse = sparse_tensor.SparseTensor(
indices=array_ops.placeholder(dtypes.int64),
@@ -1896,6 +1984,7 @@ class ShuffleBatchTest(test_lib.TestCase):
batched = inp.maybe_shuffle_batch([sparse], 2, 10, 1, True)
self.assertIs(None, batched.dense_shape.get_shape().num_elements())
+ @test_util.run_deprecated_v1
def testMaybeBatchedSparseTensorInferredShapeUnknownRankEnqueueMany(self):
sparse = sparse_tensor.SparseTensor(
indices=array_ops.placeholder(dtypes.int64),
@@ -1906,6 +1995,7 @@ class ShuffleBatchTest(test_lib.TestCase):
[sparse], 2, 10, 1, True, enqueue_many=True)
self.assertIs(None, batched.dense_shape.get_shape().num_elements())
+ @test_util.run_deprecated_v1
def testMaybeBatchedSparseTensorInferredShapeUnknownRankPerExample(self):
sparse = sparse_tensor.SparseTensor(
indices=array_ops.placeholder(dtypes.int64),
@@ -2024,12 +2114,15 @@ class ShuffleBatchJoinTest(test_lib.TestCase):
for thread in threads:
thread.join()
+ @test_util.run_deprecated_v1
def testTwoThreads(self):
self._testTwoThreadsHelper(use_dict=False)
+ @test_util.run_deprecated_v1
def testTwoThreadsDict(self):
self._testTwoThreadsHelper(use_dict=True)
+ @test_util.run_deprecated_v1
def testTwoThreadsSmallerBatch(self):
with self.cached_session() as sess:
# Two threads, the first generates (0..26, "a").
@@ -2133,6 +2226,7 @@ class ShuffleBatchJoinTest(test_lib.TestCase):
for thread in threads:
thread.join()
+ @test_util.run_deprecated_v1
def testMismatchedDictKeys(self):
with self.assertRaisesRegexp(ValueError, "must have the same keys"):
inp.shuffle_batch_join(
@@ -2150,6 +2244,7 @@ class ShuffleBatchJoinTest(test_lib.TestCase):
min_after_dequeue=16,
seed=223607)
+ @test_util.run_deprecated_v1
def testSharedName(self):
with self.cached_session():
batch_size = 10
@@ -2214,24 +2309,31 @@ class ShuffleBatchJoinTest(test_lib.TestCase):
for thread in threads:
thread.join()
+ @test_util.run_deprecated_v1
def testSingleThreadKeepInput(self):
self._testKeepInputHelper(1, False)
+ @test_util.run_deprecated_v1
def testSingleThreadKeepInputEnqueueMany(self):
self._testKeepInputHelper(1, True)
+ @test_util.run_deprecated_v1
def testMultipleThreadKeepInput(self):
self._testKeepInputHelper(5, False)
+ @test_util.run_deprecated_v1
def testMultipleThreadKeepInputEnqueueMany(self):
self._testKeepInputHelper(5, True)
+ @test_util.run_deprecated_v1
def testSingleThreadKeepInputPerExample(self):
self._testKeepInputHelper(1, True, keep_input_vector=True)
+ @test_util.run_deprecated_v1
def testMultipleThreadKeepInputPerExample(self):
self._testKeepInputHelper(5, True, keep_input_vector=True)
+ @test_util.run_deprecated_v1
def testInvalidKeepInputVector(self):
# Can't have vector `keep_input` with `enqueue_many=False`.
with self.assertRaisesRegexp(ValueError, "`keep_input` cannot be a vector"):
@@ -2253,6 +2355,7 @@ class ShuffleBatchJoinTest(test_lib.TestCase):
keep_input=array_ops.placeholder(dtypes.bool),
enqueue_many=True)
+ @test_util.run_deprecated_v1
def testMaybeBatchedSparseTensorInferredShape(self):
sparse = sparse_tensor.SparseTensor(
indices=[[0]], values=[1.0], dense_shape=[1])
@@ -2260,6 +2363,7 @@ class ShuffleBatchJoinTest(test_lib.TestCase):
batched = inp.maybe_shuffle_batch_join([[sparse]], 2, 10, 1, True)
self.assertAllEqual((2,), batched.dense_shape.get_shape().as_list())
+ @test_util.run_deprecated_v1
def testMaybeBatchedSparseTensorInferredShapeEnqueueMany(self):
sparse = sparse_tensor.SparseTensor(
indices=[[0]], values=[1.0], dense_shape=[1])
@@ -2268,6 +2372,7 @@ class ShuffleBatchJoinTest(test_lib.TestCase):
[[sparse]], 2, 10, 1, True, enqueue_many=True)
self.assertAllEqual((1,), batched.dense_shape.get_shape().as_list())
+ @test_util.run_deprecated_v1
def testMaybeBatchedSparseTensorInferredShapeEnqueueManyPerExample(self):
sparse = sparse_tensor.SparseTensor(
indices=[[0], [0]], values=[1.0, 2.0], dense_shape=[2])
@@ -2276,6 +2381,7 @@ class ShuffleBatchJoinTest(test_lib.TestCase):
[[sparse]], 2, 10, 1, [True, False], enqueue_many=True)
self.assertAllEqual((1,), batched.dense_shape.get_shape().as_list())
+ @test_util.run_deprecated_v1
def testMaybeBatchedSparseTensorInferredShapeUnknownRank(self):
sparse = sparse_tensor.SparseTensor(
indices=array_ops.placeholder(dtypes.int64),
@@ -2285,6 +2391,7 @@ class ShuffleBatchJoinTest(test_lib.TestCase):
batched = inp.maybe_shuffle_batch_join([[sparse]], 2, 10, 1, True)
self.assertIs(None, batched.dense_shape.get_shape().num_elements())
+ @test_util.run_deprecated_v1
def testMaybeBatchedSparseTensorInferredShapeUnknownRankEnqueueMany(self):
sparse = sparse_tensor.SparseTensor(
indices=array_ops.placeholder(dtypes.int64),
@@ -2295,6 +2402,7 @@ class ShuffleBatchJoinTest(test_lib.TestCase):
[[sparse]], 2, 10, 1, True, enqueue_many=True)
self.assertIs(None, batched.dense_shape.get_shape().num_elements())
+ @test_util.run_deprecated_v1
def testMaybeBatchedSparseTensorInferredShapeUnknownRankPerExample(self):
sparse = sparse_tensor.SparseTensor(
indices=array_ops.placeholder(dtypes.int64),
diff --git a/tensorflow/python/training/learning_rate_decay_test.py b/tensorflow/python/training/learning_rate_decay_test.py
index 9c31c0924f5..9de5bc8168f 100644
--- a/tensorflow/python/training/learning_rate_decay_test.py
+++ b/tensorflow/python/training/learning_rate_decay_test.py
@@ -61,6 +61,7 @@ class LRDecayTest(test_util.TensorFlowTestCase):
self.evaluate(step.assign(100))
self.assertAllClose(self.evaluate(decayed_lr), expected, 1e-6)
+ @test_util.run_deprecated_v1
def testVariables(self):
step = variables.VariableV1(1)
assign_1 = step.assign(1)
@@ -100,6 +101,7 @@ class LRDecayTest(test_util.TensorFlowTestCase):
self.assertAllClose(self.evaluate(decayed_lr), 0.001, 1e-6)
@test_util.run_in_graph_and_eager_modes
+ @test_util.run_deprecated_v1
def testPiecewiseConstantEdgeCases(self):
x_int = resource_variable_ops.ResourceVariable(
0, dtype=variables.dtypes.int32)
diff --git a/tensorflow/python/training/learning_rate_decay_v2_test.py b/tensorflow/python/training/learning_rate_decay_v2_test.py
index 354ddb25be5..cb96773e299 100644
--- a/tensorflow/python/training/learning_rate_decay_v2_test.py
+++ b/tensorflow/python/training/learning_rate_decay_v2_test.py
@@ -61,6 +61,7 @@ class LRDecayTestV2(test_util.TensorFlowTestCase):
self.evaluate(step.assign(100))
self.assertAllClose(self.evaluate(decayed_lr()), expected, 1e-6)
+ @test_util.run_deprecated_v1
def testVariables(self):
step = variables.Variable(1)
assign_1 = step.assign(1)
diff --git a/tensorflow/python/training/momentum_test.py b/tensorflow/python/training/momentum_test.py
index b6cac6addfb..ba155fa6c64 100644
--- a/tensorflow/python/training/momentum_test.py
+++ b/tensorflow/python/training/momentum_test.py
@@ -160,6 +160,7 @@ class MomentumOptimizerTest(test.TestCase):
self.assertStartsWith(optimizer_variables[1].name, "var3")
self.assertEquals(2, len(optimizer_variables))
+ @test_util.run_deprecated_v1
def testNesterovMomentum(self):
for dtype in [dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -186,6 +187,7 @@ class MomentumOptimizerTest(test.TestCase):
self.assertAllClose(var0_np, self.evaluate(var0))
self.assertAllClose(var1_np, self.evaluate(var1))
+ @test_util.run_deprecated_v1
def testSparseNesterovMomentum(self):
for dtype in [dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -280,6 +282,7 @@ class MomentumOptimizerTest(test.TestCase):
self.evaluate(sgd_op)
self.assertAllCloseAccordingToType([[1, 1], [0, 0]], self.evaluate(var0))
+ @test_util.run_deprecated_v1
def testTensorLearningRateAndMomentum(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -440,6 +443,7 @@ class MomentumOptimizerTest(test.TestCase):
# pylint: enable=line-too-long
return db_grad, db_out
+ @test_util.run_deprecated_v1
def testLikeDistBeliefMom01(self):
with self.cached_session():
db_grad, db_out = self._dbParamsMom01()
@@ -453,6 +457,7 @@ class MomentumOptimizerTest(test.TestCase):
mom_update.run(feed_dict={grads0: db_grad[i]})
self.assertAllClose(np.array(db_out[i]), self.evaluate(var0))
+ @test_util.run_deprecated_v1
def testSparse(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -534,6 +539,7 @@ class MomentumOptimizerTest(test.TestCase):
]),
self.evaluate(var1)[2])
+ @test_util.run_deprecated_v1
def testSharing(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
diff --git a/tensorflow/python/training/monitored_session_test.py b/tensorflow/python/training/monitored_session_test.py
index 2ceb387ec34..9dbcfa52b7c 100644
--- a/tensorflow/python/training/monitored_session_test.py
+++ b/tensorflow/python/training/monitored_session_test.py
@@ -37,6 +37,7 @@ from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors_impl
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import control_flow_ops
from tensorflow.python.ops import resource_variable_ops
@@ -504,6 +505,7 @@ class StopAtNSession(monitored_session._WrappedSession):
class WrappedSessionTest(test.TestCase):
"""_WrappedSession tests."""
+ @test_util.run_deprecated_v1
def test_properties(self):
with self.cached_session() as sess:
constant_op.constant(0.0)
@@ -511,6 +513,7 @@ class WrappedSessionTest(test.TestCase):
self.assertEquals(sess.graph, wrapped_sess.graph)
self.assertEquals(sess.sess_str, wrapped_sess.sess_str)
+ @test_util.run_deprecated_v1
def test_should_stop_on_close(self):
with self.cached_session() as sess:
wrapped_sess = monitored_session._WrappedSession(sess)
@@ -518,6 +521,7 @@ class WrappedSessionTest(test.TestCase):
wrapped_sess.close()
self.assertTrue(wrapped_sess.should_stop())
+ @test_util.run_deprecated_v1
def test_should_stop_uses_check_stop(self):
with self.cached_session() as sess:
wrapped_sess = StopAtNSession(sess, 3)
@@ -526,6 +530,7 @@ class WrappedSessionTest(test.TestCase):
self.assertFalse(wrapped_sess.should_stop())
self.assertTrue(wrapped_sess.should_stop())
+ @test_util.run_deprecated_v1
def test_should_stop_delegates_to_wrapped_session(self):
with self.cached_session() as sess:
wrapped_sess0 = StopAtNSession(sess, 4)
@@ -544,6 +549,7 @@ class WrappedSessionTest(test.TestCase):
wrapped_sess.close()
self.assertTrue(wrapped_sess.should_stop())
+ @test_util.run_deprecated_v1
def test_run(self):
with self.cached_session() as sess:
c = constant_op.constant(0)
@@ -561,6 +567,7 @@ def busy_wait_for_coord_stop(coord):
class CoordinatedSessionTest(test.TestCase):
"""_CoordinatedSession tests."""
+ @test_util.run_deprecated_v1
def test_properties(self):
with self.cached_session() as sess:
constant_op.constant(0.0)
@@ -569,6 +576,7 @@ class CoordinatedSessionTest(test.TestCase):
self.assertEquals(sess.graph, coord_sess.graph)
self.assertEquals(sess.sess_str, coord_sess.sess_str)
+ @test_util.run_deprecated_v1
def test_run(self):
with self.cached_session() as sess:
c = constant_op.constant(0)
@@ -577,6 +585,7 @@ class CoordinatedSessionTest(test.TestCase):
coord_sess = monitored_session._CoordinatedSession(sess, coord)
self.assertEqual(42, coord_sess.run(v, feed_dict={c: 42}))
+ @test_util.run_deprecated_v1
def test_should_stop_on_close(self):
with self.cached_session() as sess:
coord = coordinator.Coordinator()
@@ -585,6 +594,7 @@ class CoordinatedSessionTest(test.TestCase):
coord_sess.close()
self.assertTrue(coord_sess.should_stop())
+ @test_util.run_deprecated_v1
def test_should_stop_on_coord_stop(self):
with self.cached_session() as sess:
coord = coordinator.Coordinator()
@@ -593,6 +603,7 @@ class CoordinatedSessionTest(test.TestCase):
coord.request_stop()
self.assertTrue(coord_sess.should_stop())
+ @test_util.run_deprecated_v1
def test_dont_request_stop_on_exception_in_main_thread(self):
with self.cached_session() as sess:
c = constant_op.constant(0)
@@ -607,6 +618,7 @@ class CoordinatedSessionTest(test.TestCase):
self.assertFalse(coord.should_stop())
self.assertFalse(coord_sess.should_stop())
+ @test_util.run_deprecated_v1
def test_stop_threads_on_close_after_exception(self):
with self.cached_session() as sess:
c = constant_op.constant(0)
@@ -654,6 +666,7 @@ class CoordinatedSessionTest(test.TestCase):
self.assertTrue(coord.should_stop())
self.assertTrue(coord_sess.should_stop())
+ @test_util.run_deprecated_v1
def test_propagates_exception_trace(self):
assertion = control_flow_ops.Assert(False, ['This should fail.'])
with self.cached_session() as sess:
@@ -801,6 +814,7 @@ class RecoverableSessionTest(test.TestCase):
def create_session(self):
return self._sess
+ @test_util.run_deprecated_v1
def test_properties(self):
with self.cached_session() as sess:
constant_op.constant(0.0)
@@ -809,6 +823,7 @@ class RecoverableSessionTest(test.TestCase):
self.assertEquals(sess.graph, recoverable_sess.graph)
self.assertEquals(sess.sess_str, recoverable_sess.sess_str)
+ @test_util.run_deprecated_v1
def test_run(self):
with self.cached_session() as sess:
c = constant_op.constant(0)
@@ -817,6 +832,7 @@ class RecoverableSessionTest(test.TestCase):
self._SessionReturner(sess))
self.assertEqual(51, recoverable_sess.run(v, feed_dict={c: 51}))
+ @test_util.run_deprecated_v1
def test_recovery(self):
with self.cached_session() as sess:
@@ -863,6 +879,7 @@ class RecoverableSessionTest(test.TestCase):
with self.assertRaisesRegexp(IndexError, 'pop from empty list'):
recoverable_sess.run(v, feed_dict={c: -12})
+ @test_util.run_deprecated_v1
def test_recovery_from_coordinator_exception(self):
with self.cached_session() as test_session:
session_creator = CountingSessionCreator(test_session)
@@ -888,6 +905,7 @@ class RecoverableSessionTest(test.TestCase):
self.assertFalse(session.should_stop())
self.assertEqual(2, session_creator.number_of_sessions_created)
+ @test_util.run_deprecated_v1
def test_recovery_from_non_preemption_in_coordinator(self):
with self.cached_session() as test_session:
session_creator = CountingSessionCreator(test_session)
@@ -917,6 +935,7 @@ class RecoverableSessionTest(test.TestCase):
with self.assertRaises(errors_impl.UnknownError):
session.close()
+ @test_util.run_deprecated_v1
def test_recovery_from_session_getting_stuck(self):
with self.cached_session() as test_session:
session_creator = CountingSessionCreator(test_session)
@@ -941,6 +960,7 @@ class RecoverableSessionTest(test.TestCase):
self.assertFalse(session.should_stop())
self.assertEqual(2, session_creator.number_of_sessions_created)
+ @test_util.run_deprecated_v1
def test_step_fn_recovery_from_coordinator_exception_when_run_hooks(self):
with self.cached_session() as test_session:
session_creator = CountingSessionCreator(test_session)
@@ -971,6 +991,7 @@ class RecoverableSessionTest(test.TestCase):
self.assertFalse(session.should_stop())
self.assertEqual(2, session_creator.number_of_sessions_created)
+ @test_util.run_deprecated_v1
def test_recovery_from_non_preemption_in_coordinator_when_run_hooks(self):
with self.cached_session() as test_session:
session_creator = CountingSessionCreator(test_session)
@@ -1005,6 +1026,7 @@ class RecoverableSessionTest(test.TestCase):
with self.assertRaises(errors_impl.UnknownError):
session.close()
+ @test_util.run_deprecated_v1
def test_recovery_from_session_getting_stuck_when_run_hooks(self):
with self.cached_session() as test_session:
session_creator = CountingSessionCreator(test_session)
@@ -1049,6 +1071,7 @@ class RecoverableSessionTest(test.TestCase):
# exception.
return session
+ @test_util.run_deprecated_v1
def test_step_fn_recovery_from_coordinator_exception_with_raw_session(self):
with self.cached_session() as test_session:
session_creator = CountingSessionCreator(test_session)
@@ -1081,6 +1104,7 @@ class RecoverableSessionTest(test.TestCase):
self.assertFalse(session.should_stop())
self.assertEqual(2, session_creator.number_of_sessions_created)
+ @test_util.run_deprecated_v1
def test_recovery_from_non_preemption_in_coordinator_with_raw_session(self):
with self.cached_session() as test_session:
session_creator = CountingSessionCreator(test_session)
@@ -1118,6 +1142,7 @@ class RecoverableSessionTest(test.TestCase):
with self.assertRaises(errors_impl.UnknownError):
session.close()
+ @test_util.run_deprecated_v1
def test_recovery_from_session_getting_stuck_with_raw_session(self):
with self.cached_session() as test_session:
session_creator = CountingSessionCreator(test_session)
@@ -1443,6 +1468,7 @@ class MonitoredSessionTest(test.TestCase):
# This set of tests, verifies the supervised session behavior when exceptions
# are raised next to the innermost session run() call.
+ @test_util.run_deprecated_v1
def test_recovery(self):
logdir = _test_dir(self.get_temp_dir(), 'test_recovery')
with ops.Graph().as_default():
@@ -1795,6 +1821,7 @@ class MonitoredSessionTest(test.TestCase):
isinstance(hook.run_metadata_list[0], config_pb2.RunMetadata))
self.assertGreater(len(hook.run_metadata_list[0].partition_graphs), 0)
+ @test_util.run_deprecated_v1
def test_with_statement_and_close(self):
# Test case for https://github.com/tensorflow/tensorflow/issues/12224
# where close() inside the with should have a better error message.
diff --git a/tensorflow/python/training/moving_averages_test.py b/tensorflow/python/training/moving_averages_test.py
index 6ce5de6663d..b15f7377f07 100644
--- a/tensorflow/python/training/moving_averages_test.py
+++ b/tensorflow/python/training/moving_averages_test.py
@@ -35,6 +35,7 @@ from tensorflow.python.training import saver as saver_lib
class MovingAveragesTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testAssignMovingAverageWithoutZeroDebias(self):
with self.cached_session():
var = variables.Variable([10.0, 11.0])
@@ -49,6 +50,7 @@ class MovingAveragesTest(test.TestCase):
[10.0 * 0.25 + 1.0 * (1.0 - 0.25), 11.0 * 0.25 + 2.0 * (1.0 - 0.25)],
self.evaluate(var))
+ @test_util.run_deprecated_v1
def testAssignMovingAverage(self):
with self.cached_session():
var = variables.Variable([0.0, 0.0])
@@ -62,6 +64,7 @@ class MovingAveragesTest(test.TestCase):
[1.0 * (1.0 - 0.25) / (1 - 0.25), 2.0 * (1.0 - 0.25) / (1 - 0.25)],
self.evaluate(var))
+ @test_util.run_deprecated_v1
def testAssignMovingAverageNewNamingMultipleCalls(self):
with variable_scope.variable_scope("scope1") as vs1:
with variable_scope.variable_scope("scope2"):
@@ -76,6 +79,7 @@ class MovingAveragesTest(test.TestCase):
actual_names = [v.name for v in vs1.global_variables()]
self.assertSetEqual(set(expected_names), set(actual_names))
+ @test_util.run_deprecated_v1
def testAssignMovingAverageNewNamingMultipleCallsWithReuse(self):
with variable_scope.variable_scope("scope1") as vs1:
var = variable_scope.get_variable("Var", shape=[])
@@ -86,6 +90,7 @@ class MovingAveragesTest(test.TestCase):
moving_averages.assign_moving_average(var, 0.0, 0.99)
moving_averages.assign_moving_average(var, 0.0, 0.99)
+ @test_util.run_deprecated_v1
def testWeightedMovingAverage(self):
with self.cached_session() as sess:
decay = 0.5
@@ -111,6 +116,7 @@ class MovingAveragesTest(test.TestCase):
denominator_2 = denominator_1 * decay + weight_2 * (1.0 - decay)
self.assertAllClose(numerator_2 / denominator_2, wma_array)
+ @test_util.run_deprecated_v1
def testWeightedMovingAverageBfloat16(self):
bfloat16 = pywrap_tensorflow.TF_bfloat16_type()
with self.cached_session() as sess:
@@ -213,32 +219,38 @@ class ExponentialMovingAverageTest(test.TestCase):
(10.0 + 30.0) * (1 - dk)) / _Scale(dk, 2), dim)
self.assertAllClose(expected, self.evaluate(avg2))
+ @test_util.run_deprecated_v1
def testAverageVariablesNoNumUpdates_Scalar(self):
with self.cached_session():
ema = moving_averages.ExponentialMovingAverage(0.25)
self._CheckDecay(ema, actual_decay=0.25, dim=1)
+ @test_util.run_deprecated_v1
def testAverageVariablesNoNumUpdates_Scalar_Debias(self):
with self.cached_session():
ema = moving_averages.ExponentialMovingAverage(0.25, zero_debias=True)
self._CheckDecay(ema, actual_decay=0.25, dim=1)
+ @test_util.run_deprecated_v1
def testAverageVariablesNoNumUpdates_Vector(self):
with self.cached_session():
ema = moving_averages.ExponentialMovingAverage(0.25)
self._CheckDecay(ema, actual_decay=0.25, dim=5)
+ @test_util.run_deprecated_v1
def testAverageVariablesNoNumUpdates_Vector_Debias(self):
with self.cached_session():
ema = moving_averages.ExponentialMovingAverage(0.25, zero_debias=True)
self._CheckDecay(ema, actual_decay=0.25, dim=5)
+ @test_util.run_deprecated_v1
def testAverageVariablesNumUpdates_Scalar(self):
with self.cached_session():
# With num_updates 1, the decay applied is 0.1818
ema = moving_averages.ExponentialMovingAverage(0.25, num_updates=1)
self._CheckDecay(ema, actual_decay=0.181818, dim=1)
+ @test_util.run_deprecated_v1
def testAverageVariablesNumUpdates_Scalar_Debias(self):
with self.cached_session():
# With num_updates 1, the decay applied is 0.1818
@@ -246,12 +258,14 @@ class ExponentialMovingAverageTest(test.TestCase):
0.25, num_updates=1, zero_debias=True)
self._CheckDecay(ema, actual_decay=0.181818, dim=1)
+ @test_util.run_deprecated_v1
def testAverageVariablesNumUpdates_Vector(self):
with self.cached_session():
# With num_updates 1, the decay applied is 0.1818
ema = moving_averages.ExponentialMovingAverage(0.25, num_updates=1)
self._CheckDecay(ema, actual_decay=0.181818, dim=5)
+ @test_util.run_deprecated_v1
def testAverageVariablesNumUpdates_Vector_Debias(self):
with self.cached_session():
# With num_updates 1, the decay applied is 0.1818
@@ -259,6 +273,7 @@ class ExponentialMovingAverageTest(test.TestCase):
0.25, num_updates=1, zero_debias=True)
self._CheckDecay(ema, actual_decay=0.181818, dim=5)
+ @test_util.run_deprecated_v1
def testAverageVariablesWithControlDeps(self):
with self.cached_session() as sess:
v0 = variables.Variable(0, name="v0")
@@ -284,6 +299,7 @@ class ExponentialMovingAverageTest(test.TestCase):
self.assertEqual([17.5], self.evaluate(v1_avg))
@test_util.run_in_graph_and_eager_modes
+ @test_util.run_deprecated_v1
def testBasicEager(self):
v0 = variables.Variable(1.0)
v1 = variables.Variable(2.0)
@@ -339,9 +355,11 @@ class ExponentialMovingAverageTest(test.TestCase):
self.assertEqual(ema.average(v1).op.name, ema.average_name(v1))
self.assertEqual(ema.average(tensor2).op.name, ema.average_name(tensor2))
+ @test_util.run_deprecated_v1
def testAverageVariablesNames(self):
self.averageVariablesNamesHelper(zero_debias=True)
+ @test_util.run_deprecated_v1
def testAverageVariablesNamesNoDebias(self):
self.averageVariablesNamesHelper(zero_debias=False)
@@ -387,12 +405,15 @@ class ExponentialMovingAverageTest(test.TestCase):
self.assertEqual(
ema.average(tensor2).op.name, ema.average_name(tensor2))
+ @test_util.run_deprecated_v1
def testAverageVariablesNamesRespectScope(self):
self.averageVariablesNamesRespectScopeHelper(zero_debias=True)
+ @test_util.run_deprecated_v1
def testAverageVariablesNamesRespectScopeNoDebias(self):
self.averageVariablesNamesRespectScopeHelper(zero_debias=False)
+ @test_util.run_deprecated_v1
def testSubsetAverageVariablesNames(self):
with self.cached_session():
v0 = variables.Variable(10.0, name="v0")
@@ -421,6 +442,7 @@ class ExponentialMovingAverageTest(test.TestCase):
self.assertEqual(ema.average(v1).op.name, ema.average_name(v1))
self.assertEqual(ema.average(tensor2).op.name, ema.average_name(tensor2))
+ @test_util.run_deprecated_v1
def testAverageVariablesDeviceAssignment(self):
with ops.device("/job:dev_v0"):
v0 = variables.Variable(10.0, name="v0")
@@ -451,6 +473,7 @@ class ExponentialMovingAverageTest(test.TestCase):
_ = saver_lib.import_meta_graph(meta_graph)
return graph_copy
+ @test_util.run_deprecated_v1
def testImportedGraphVariablesToRestore(self):
g = ops.Graph()
with g.as_default():
diff --git a/tensorflow/python/training/optimizer_test.py b/tensorflow/python/training/optimizer_test.py
index 5ed0a302859..e175b5a7998 100644
--- a/tensorflow/python/training/optimizer_test.py
+++ b/tensorflow/python/training/optimizer_test.py
@@ -62,6 +62,7 @@ class OptimizerTest(test.TestCase):
self.assertAllClose([-14., -13.], self.evaluate(var0))
self.assertAllClose([-6., -5.], self.evaluate(var1))
+ @test_util.run_deprecated_v1
def testAggregationMethod(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -87,6 +88,7 @@ class OptimizerTest(test.TestCase):
self.assertAllClose([-14., -13.], self.evaluate(var0))
self.assertAllClose([-6., -5.], self.evaluate(var1))
+ @test_util.run_deprecated_v1
def testPrecomputedGradient(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -230,6 +232,7 @@ class OptimizerTest(test.TestCase):
with self.assertRaises(NotImplementedError):
sgd_op.apply_gradients(grads_and_vars)
+ @test_util.run_deprecated_v1
def testTrainOp(self):
with self.cached_session():
var0 = variables.Variable([1.0, 2.0])
@@ -241,6 +244,7 @@ class OptimizerTest(test.TestCase):
opt_op = sgd_op.minimize(cost, global_step, [var0, var1])
self.assertTrue(opt_op in ops.get_collection(ops.GraphKeys.TRAIN_OP))
+ @test_util.run_deprecated_v1
def testConstraint(self):
constraint_01 = lambda x: clip_ops.clip_by_value(x, -0.1, 0.)
constraint_0 = lambda x: clip_ops.clip_by_value(x, 0., 1.)
diff --git a/tensorflow/python/training/proximal_adagrad_test.py b/tensorflow/python/training/proximal_adagrad_test.py
index 9d46a6682d9..ce214ac418a 100644
--- a/tensorflow/python/training/proximal_adagrad_test.py
+++ b/tensorflow/python/training/proximal_adagrad_test.py
@@ -23,6 +23,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import embedding_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import resource_variable_ops
@@ -64,12 +65,15 @@ class ProximalAdagradOptimizerTest(test.TestCase):
self.assertStartsWith(opt_vars[1].name, var1._shared_name)
self.assertEqual(2, len(opt_vars))
+ @test_util.run_deprecated_v1
def testProximalAdagradwithoutRegularization(self):
self.doTestProximalAdagradwithoutRegularization(use_resource=False)
+ @test_util.run_deprecated_v1
def testResourceProximalAdagradwithoutRegularization(self):
self.doTestProximalAdagradwithoutRegularization(use_resource=True)
+ @test_util.run_deprecated_v1
def testProximalAdagradwithoutRegularization2(self):
with self.cached_session() as sess:
var0 = variables.Variable([1.0, 2.0])
@@ -96,6 +100,7 @@ class ProximalAdagradOptimizerTest(test.TestCase):
self.assertAllClose(np.array([-1.60261, -2.296985]), v0_val)
self.assertAllClose(np.array([3.715679, 2.433051]), v1_val)
+ @test_util.run_deprecated_v1
def testMinimizeSparseResourceVariable(self):
for dtype in [dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -114,6 +119,7 @@ class ProximalAdagradOptimizerTest(test.TestCase):
self.evaluate(var0),
atol=0.01)
+ @test_util.run_deprecated_v1
def testProximalAdagradWithL1(self):
with self.cached_session() as sess:
var0 = variables.Variable([1.0, 2.0])
@@ -140,6 +146,7 @@ class ProximalAdagradOptimizerTest(test.TestCase):
self.assertAllClose(np.array([-6.663634, -9.190331]), v0_val)
self.assertAllClose(np.array([2.959304, 1.029232]), v1_val)
+ @test_util.run_deprecated_v1
def testProximalAdagradWithL1_L2(self):
with self.cached_session() as sess:
var0 = variables.Variable([1.0, 2.0])
@@ -206,6 +213,7 @@ class ProximalAdagradOptimizerTest(test.TestCase):
v0_val, v1_val = self.evaluate([var0, var1])
return v0_val, v1_val
+ @test_util.run_deprecated_v1
def testEquivAdagradwithoutRegularization(self):
with self.cached_session():
val0, val1 = self.applyOptimizer(
@@ -223,6 +231,7 @@ class ProximalAdagradOptimizerTest(test.TestCase):
self.assertAllClose(val0, val2)
self.assertAllClose(val1, val3)
+ @test_util.run_deprecated_v1
def testEquivSparseAdagradwithoutRegularization(self):
with self.cached_session():
val0, val1 = self.applyOptimizer(
diff --git a/tensorflow/python/training/proximal_gradient_descent_test.py b/tensorflow/python/training/proximal_gradient_descent_test.py
index 8797b308ebd..25b206605dc 100644
--- a/tensorflow/python/training/proximal_gradient_descent_test.py
+++ b/tensorflow/python/training/proximal_gradient_descent_test.py
@@ -23,6 +23,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import embedding_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import resource_variable_ops
@@ -62,12 +63,15 @@ class ProximalGradientDescentOptimizerTest(test.TestCase):
self.assertAllClose(np.array([-0.9, -1.8]), v0_val)
self.assertAllClose(np.array([-0.09, -0.18]), v1_val)
+ @test_util.run_deprecated_v1
def testProximalGradientDescentwithoutRegularization(self):
self.doTestProximalGradientDescentwithoutRegularization(use_resource=False)
+ @test_util.run_deprecated_v1
def testResourceProximalGradientDescentwithoutRegularization(self):
self.doTestProximalGradientDescentwithoutRegularization(use_resource=True)
+ @test_util.run_deprecated_v1
def testProximalGradientDescentwithoutRegularization2(self):
with self.cached_session() as sess:
var0 = variables.Variable([1.0, 2.0])
@@ -92,6 +96,7 @@ class ProximalGradientDescentOptimizerTest(test.TestCase):
self.assertAllClose(np.array([0.1, 0.2]), v0_val)
self.assertAllClose(np.array([3.91, 2.82]), v1_val)
+ @test_util.run_deprecated_v1
def testMinimizeSparseResourceVariable(self):
for dtype in [dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -111,6 +116,7 @@ class ProximalGradientDescentOptimizerTest(test.TestCase):
self.evaluate(var0),
atol=0.01)
+ @test_util.run_deprecated_v1
def testProximalGradientDescentWithL1_L2(self):
with self.cached_session() as sess:
var0 = variables.Variable([1.0, 2.0])
@@ -174,6 +180,7 @@ class ProximalGradientDescentOptimizerTest(test.TestCase):
v0_val, v1_val = self.evaluate([var0, var1])
return v0_val, v1_val
+ @test_util.run_deprecated_v1
def testEquivSparseGradientDescentwithoutRegularization(self):
with self.cached_session():
val0, val1 = self.applyOptimizer(
@@ -190,6 +197,7 @@ class ProximalGradientDescentOptimizerTest(test.TestCase):
self.assertAllClose(val0, val2)
self.assertAllClose(val1, val3)
+ @test_util.run_deprecated_v1
def testEquivGradientDescentwithoutRegularization(self):
with self.cached_session():
val0, val1 = self.applyOptimizer(
diff --git a/tensorflow/python/training/quantize_training_test.py b/tensorflow/python/training/quantize_training_test.py
index 07fd488563e..62e783f2000 100644
--- a/tensorflow/python/training/quantize_training_test.py
+++ b/tensorflow/python/training/quantize_training_test.py
@@ -25,6 +25,7 @@ from tensorflow.python.client import session
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import importer
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import variables
from tensorflow.python.platform import test
@@ -52,6 +53,7 @@ class PywrapQuantizeTrainingTest(test.TestCase):
# Test that save/restoring works for EMA variables generated in the
# quantized training rewrite.
+ @test_util.run_deprecated_v1
def testQuantizedSaveRestore(self):
save_path = os.path.join(self.get_temp_dir(), 'quantized_save_restore')
diff --git a/tensorflow/python/training/queue_runner_test.py b/tensorflow/python/training/queue_runner_test.py
index 65c2c13d8bb..4113cecf55d 100644
--- a/tensorflow/python/training/queue_runner_test.py
+++ b/tensorflow/python/training/queue_runner_test.py
@@ -26,6 +26,7 @@ from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors_impl
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import control_flow_ops
from tensorflow.python.ops import data_flow_ops
from tensorflow.python.ops import variables
@@ -40,6 +41,7 @@ _MockOp = collections.namedtuple("MockOp", ["name"])
class QueueRunnerTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testBasic(self):
with self.cached_session() as sess:
# CountUpTo will raise OUT_OF_RANGE when it reaches the count.
@@ -60,6 +62,7 @@ class QueueRunnerTest(test.TestCase):
# The variable should be 3.
self.assertEqual(3, self.evaluate(var))
+ @test_util.run_deprecated_v1
def testTwoOps(self):
with self.cached_session() as sess:
# CountUpTo will raise OUT_OF_RANGE when it reaches the count.
@@ -83,6 +86,7 @@ class QueueRunnerTest(test.TestCase):
self.assertEqual(3, self.evaluate(var0))
self.assertEqual(30, self.evaluate(var1))
+ @test_util.run_deprecated_v1
def testExceptionsCaptured(self):
with self.cached_session() as sess:
queue = data_flow_ops.FIFOQueue(10, dtypes.float32)
@@ -99,6 +103,7 @@ class QueueRunnerTest(test.TestCase):
self.assertTrue("Operation not in the graph" in str(exceptions[0]))
self.assertTrue("Operation not in the graph" in str(exceptions[1]))
+ @test_util.run_deprecated_v1
def testRealDequeueEnqueue(self):
with self.cached_session() as sess:
q0 = data_flow_ops.FIFOQueue(3, dtypes.float32)
@@ -127,6 +132,7 @@ class QueueRunnerTest(test.TestCase):
with self.assertRaisesRegexp(errors_impl.OutOfRangeError, "is closed"):
self.evaluate(dequeue1)
+ @test_util.run_deprecated_v1
def testRespectCoordShouldStop(self):
with self.cached_session() as sess:
# CountUpTo will raise OUT_OF_RANGE when it reaches the count.
@@ -151,6 +157,7 @@ class QueueRunnerTest(test.TestCase):
# The variable should be 0.
self.assertEqual(0, self.evaluate(var))
+ @test_util.run_deprecated_v1
def testRequestStopOnException(self):
with self.cached_session() as sess:
queue = data_flow_ops.FIFOQueue(10, dtypes.float32)
@@ -163,6 +170,7 @@ class QueueRunnerTest(test.TestCase):
with self.assertRaisesRegexp(ValueError, "Operation not in the graph"):
coord.join()
+ @test_util.run_deprecated_v1
def testGracePeriod(self):
with self.cached_session() as sess:
# The enqueue will quickly block.
@@ -180,6 +188,7 @@ class QueueRunnerTest(test.TestCase):
# the queue to be closed and the enqueue to terminate.
coord.join(stop_grace_period_secs=1.0)
+ @test_util.run_deprecated_v1
def testMultipleSessions(self):
with self.cached_session() as sess:
with session.Session() as other_sess:
@@ -195,6 +204,7 @@ class QueueRunnerTest(test.TestCase):
other_threads = qr.create_threads(other_sess, coord=coord)
self.assertEqual(len(threads), len(other_threads))
+ @test_util.run_deprecated_v1
def testIgnoreMultiStarts(self):
with self.cached_session() as sess:
# CountUpTo will raise OUT_OF_RANGE when it reaches the count.
@@ -211,6 +221,7 @@ class QueueRunnerTest(test.TestCase):
new_threads = qr.create_threads(sess, coord=coord)
self.assertEqual([], new_threads)
+ @test_util.run_deprecated_v1
def testThreads(self):
with self.cached_session() as sess:
# CountUpTo will raise OUT_OF_RANGE when it reaches the count.
@@ -238,6 +249,7 @@ class QueueRunnerTest(test.TestCase):
self.assertEqual(1, len(exceptions))
self.assertTrue("Operation not in the graph" in str(exceptions[0]))
+ @test_util.run_deprecated_v1
def testName(self):
with ops.name_scope("scope"):
queue = data_flow_ops.FIFOQueue(10, dtypes.float32, name="queue")
@@ -247,6 +259,7 @@ class QueueRunnerTest(test.TestCase):
self.assertEqual(
1, len(ops.get_collection(ops.GraphKeys.QUEUE_RUNNERS, "scope")))
+ @test_util.run_deprecated_v1
def testStartQueueRunners(self):
# CountUpTo will raise OUT_OF_RANGE when it reaches the count.
zero64 = constant_op.constant(0, dtype=dtypes.int64)
@@ -265,6 +278,7 @@ class QueueRunnerTest(test.TestCase):
# The variable should be 3.
self.assertEqual(3, self.evaluate(var))
+ @test_util.run_deprecated_v1
def testStartQueueRunnersRaisesIfNotASession(self):
zero64 = constant_op.constant(0, dtype=dtypes.int64)
var = variables.VariableV1(zero64)
@@ -278,6 +292,7 @@ class QueueRunnerTest(test.TestCase):
with self.assertRaisesRegexp(TypeError, "tf.Session"):
queue_runner_impl.start_queue_runners("NotASession")
+ @test_util.run_deprecated_v1
def testStartQueueRunnersIgnoresMonitoredSession(self):
zero64 = constant_op.constant(0, dtype=dtypes.int64)
var = variables.VariableV1(zero64)
@@ -292,6 +307,7 @@ class QueueRunnerTest(test.TestCase):
monitored_session.MonitoredSession())
self.assertFalse(threads)
+ @test_util.run_deprecated_v1
def testStartQueueRunnersNonDefaultGraph(self):
# CountUpTo will raise OUT_OF_RANGE when it reaches the count.
graph = ops.Graph()
diff --git a/tensorflow/python/training/rmsprop_test.py b/tensorflow/python/training/rmsprop_test.py
index a9b8954e39d..8f029d5310e 100644
--- a/tensorflow/python/training/rmsprop_test.py
+++ b/tensorflow/python/training/rmsprop_test.py
@@ -89,6 +89,7 @@ class RMSPropOptimizerTest(test.TestCase):
var_t[gindex] = var[gindex] - mom_t[gindex]
return var_t, mg_t, rms_t, mom_t
+ @test_util.run_deprecated_v1
def testDense(self):
# TODO(yori): Use ParameterizedTest when available
for (dtype, learning_rate, decay, momentum,
@@ -164,6 +165,7 @@ class RMSPropOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(var0_np, self.evaluate(var0))
self.assertAllCloseAccordingToType(var1_np, self.evaluate(var1))
+ @test_util.run_deprecated_v1
def testMinimizeSparseResourceVariable(self):
for dtype in [dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -187,6 +189,7 @@ class RMSPropOptimizerTest(test.TestCase):
self.evaluate(var0),
atol=0.01)
+ @test_util.run_deprecated_v1
def testMinimizeSparseResourceVariableCentered(self):
for dtype in [dtypes.float32, dtypes.float64]:
with self.cached_session():
@@ -210,6 +213,7 @@ class RMSPropOptimizerTest(test.TestCase):
self.evaluate(var0),
atol=0.01)
+ @test_util.run_deprecated_v1
def testSparse(self):
# TODO(yori): Use ParameterizedTest when available
for (dtype, learning_rate, decay,
@@ -286,6 +290,7 @@ class RMSPropOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType(var0_np, self.evaluate(var0))
self.assertAllCloseAccordingToType(var1_np, self.evaluate(var1))
+ @test_util.run_deprecated_v1
def testWithoutMomentum(self):
for dtype in [dtypes.half, dtypes.float32]:
with test_util.use_gpu():
@@ -354,6 +359,7 @@ class RMSPropOptimizerTest(test.TestCase):
(0.01 * 2.0 / math.sqrt(0.90001 * 0.9 + 1e-5 + 1.0))
]), self.evaluate(var1))
+ @test_util.run_deprecated_v1
def testWithMomentum(self):
for dtype in [dtypes.half, dtypes.float32]:
with test_util.use_gpu():
diff --git a/tensorflow/python/training/saver_test.py b/tensorflow/python/training/saver_test.py
index 6b2177b0bb7..40b7c0d5a7f 100644
--- a/tensorflow/python/training/saver_test.py
+++ b/tensorflow/python/training/saver_test.py
@@ -170,6 +170,7 @@ class SaverTest(test.TestCase):
def testResourceBasic(self):
self.basicSaveRestore(resource_variable_ops.ResourceVariable)
+ @test_util.run_deprecated_v1
def testResourceColocation(self):
partitioner = partitioned_variables.fixed_size_partitioner(num_shards=2)
with ops_lib.device("/job:ps/device:GPU:0"):
@@ -300,6 +301,7 @@ class SaverTest(test.TestCase):
not op.name.startswith("saver2/save/"))]
self.assertEqual(ops_in_saver2_scope_but_not_save_scope, [])
+ @test_util.run_deprecated_v1
def testSaveCopyRestoreWithSaveRelativePaths(self):
"""Save, copy checkpoint dir and restore from copied dir.
@@ -369,6 +371,7 @@ class SaverTest(test.TestCase):
self.assertEqual(b"k1", v2.keys().eval())
self.assertEqual(30.0, v2.values().eval())
+ @test_util.run_deprecated_v1
def testFilenameTensor(self):
v0 = variables.VariableV1(0, name="v0")
filename = b"somerandomfilename"
@@ -387,6 +390,7 @@ class SaverTest(test.TestCase):
ValueError, "The passed save_path is not a valid checkpoint:"):
save.restore(sess, "invalid path")
+ @test_util.run_deprecated_v1
def testInt64(self):
save_path = os.path.join(self.get_temp_dir(), "int64")
@@ -462,6 +466,7 @@ class SaverTest(test.TestCase):
# Verify non-duplicate names work.
saver_module.Saver({"v0": v0, "v2": v2.saveable})
+ @test_util.run_deprecated_v1
def testBasicsWithListOfVariables(self):
save_path = os.path.join(self.get_temp_dir(), "basics_with_list")
@@ -557,6 +562,7 @@ class SaverTest(test.TestCase):
# The cached readers should know to re-read the file.
self._SaveAndLoad("var1", 1.1, 2.2, save_path)
+ @test_util.run_deprecated_v1
def testAllowEmpty(self):
save_path = os.path.join(self.get_temp_dir(), "allow_empty")
with self.cached_session() as sess:
@@ -661,6 +667,7 @@ class SaverTest(test.TestCase):
self.assertAllClose(1.0, one.eval())
self.assertAllClose([2.0, 2.0, 2.0], twos.eval())
+ @test_util.run_deprecated_v1
def testReshape(self):
save_path = os.path.join(self.get_temp_dir(), "variables_reshape")
with session.Session("", graph=ops_lib.Graph()) as sess:
@@ -719,6 +726,7 @@ class SaverTest(test.TestCase):
def testSaveWithGlobalStepWithPadding(self):
self.testSaveWithGlobalStep(pad_step_number=True)
+ @test_util.run_deprecated_v1
def testSaveToNonexistingPath(self):
file_io.write_string_to_file(
os.path.join(self.get_temp_dir(), "actually_a_file"), "")
@@ -761,6 +769,7 @@ class SaverTest(test.TestCase):
error_msg_template = "Parent directory of {} doesn't exist, can't save."
self.assertEqual(error_msg_template.format(save_path), str(exc))
+ @test_util.run_deprecated_v1
def testSaveToURI(self):
# ParseURI functions don't work on Windows yet.
# TODO(jhseu): Remove this check when it works.
@@ -982,6 +991,7 @@ class SaveRestoreShardedTest(test.TestCase):
checkpoint_management.latest_checkpoint(self.get_temp_dir()),
os.path.join(self.get_temp_dir(), "sharded_basics"))
+ @test_util.run_deprecated_v1
def testSaverDef(self):
with self.cached_session():
v0 = variables.VariableV1(123, name="v0")
@@ -1087,9 +1097,11 @@ class SaveRestoreShardedTest(test.TestCase):
num_shards=3))
self.assertAllEqual(saved_full, restored_full)
+ @test_util.run_deprecated_v1
def testPartitionedVariable(self):
self._testPartitionedVariables(use_resource=False)
+ @test_util.run_deprecated_v1
def testPartitionedResourceVariable(self):
self._testPartitionedVariables(use_resource=True)
@@ -1184,6 +1196,7 @@ class MaxToKeepTest(test.TestCase):
# Deleted by the first helper.
self.assertFalse(checkpoint_management.checkpoint_exists(s3))
+ @test_util.run_deprecated_v1
def testNonSharded(self):
save_dir = self._get_test_dir("max_to_keep_non_sharded")
@@ -1421,6 +1434,7 @@ class MaxToKeepTest(test.TestCase):
self.assertTrue(
gfile.Exists(checkpoint_management.meta_graph_filename(s3)))
+ @test_util.run_deprecated_v1
def testNoMaxToKeep(self):
save_dir = self._get_test_dir("no_max_to_keep")
save_dir2 = self._get_test_dir("max_to_keep_0")
@@ -1449,6 +1463,7 @@ class MaxToKeepTest(test.TestCase):
self.assertEqual([], save2.last_checkpoints)
self.assertTrue(checkpoint_management.checkpoint_exists(s2))
+ @test_util.run_deprecated_v1
def testNoMetaGraph(self):
save_dir = self._get_test_dir("no_meta_graph")
@@ -1472,6 +1487,7 @@ class KeepCheckpointEveryNHoursTest(test.TestCase):
@test_util.run_in_graph_and_eager_modes
@test.mock.patch.object(saver_module, "time")
+ @test_util.run_deprecated_v1
def testNonSharded(self, mock_time):
save_dir = self._get_test_dir("keep_checkpoint_every_n_hours")
@@ -1591,6 +1607,7 @@ class SaveRestoreWithVariableNameMap(test.TestCase):
self.assertEqual(20.0, self.evaluate(v1))
@test_util.run_in_graph_and_eager_modes
+ @test_util.run_deprecated_v1
def testNonReshapeResourceVariable(self):
self._testNonReshape(resource_variable_ops.ResourceVariable)
@@ -1605,6 +1622,7 @@ class MetaGraphTest(test.TestCase):
gfile.MakeDirs(test_dir)
return test_dir
+ @test_util.run_deprecated_v1
def testAddCollectionDef(self):
test_dir = self._get_test_dir("good_collection")
filename = os.path.join(test_dir, "metafile")
@@ -1754,11 +1772,13 @@ class MetaGraphTest(test.TestCase):
v1 = sess.graph.get_tensor_by_name("v1:0")
self.assertEqual(11.0, v1.eval())
+ @test_util.run_deprecated_v1
def testMultiSaverCollection(self):
test_dir = self._get_test_dir("saver_collection")
self._testMultiSaverCollectionSave(test_dir)
self._testMultiSaverCollectionRestore(test_dir)
+ @test_util.run_deprecated_v1
def testClearExtraneousSavers(self):
test_dir = self._get_test_dir("clear_extraneous_savers")
filename = os.path.join(test_dir, "metafile")
@@ -1813,6 +1833,7 @@ class MetaGraphTest(test.TestCase):
self.assertEqual(33, len(meta_graph_def0.graph_def.node))
self.assertEqual(21, len(meta_graph_def1.graph_def.node))
+ @test_util.run_deprecated_v1
def testBinaryAndTextFormat(self):
test_dir = self._get_test_dir("binary_and_text")
filename = os.path.join(test_dir, "metafile")
@@ -1845,6 +1866,7 @@ class MetaGraphTest(test.TestCase):
lambda e: "does not exist"):
saver_module.import_meta_graph(filename)
+ @test_util.run_deprecated_v1
def testSliceVariable(self):
test_dir = self._get_test_dir("slice_saver")
filename = os.path.join(test_dir, "metafile")
@@ -1985,6 +2007,7 @@ class MetaGraphTest(test.TestCase):
train_op = ops_lib.get_collection("train_op")[0]
self.evaluate(train_op)
+ @test_util.run_deprecated_v1
def testGraphExtension(self):
test_dir = self._get_test_dir("graph_extension")
self._testGraphExtensionSave(test_dir)
@@ -2070,6 +2093,7 @@ class MetaGraphTest(test.TestCase):
return i + 1, x + r
self._testWhileLoopAndGradientSerDes(body)
+ @test_util.run_deprecated_v1
def testNestedControlFlowSerDes(self):
# Test while loop in a cond in a while loop.
# pylint: disable=g-long-lambda
@@ -2098,6 +2122,7 @@ class MetaGraphTest(test.TestCase):
lambda: math_ops.multiply(x, -1.0))))
# pylint: enable=g-long-lambda
+ @test_util.run_deprecated_v1
def testStrippedOpListDef(self):
with self.cached_session():
# Creates a graph.
@@ -2135,6 +2160,7 @@ class MetaGraphTest(test.TestCase):
self.assertEqual(o.summary, "")
self.assertEqual(o.description, "")
+ @test_util.run_deprecated_v1
def testStripDefaultValuedAttrs(self):
"""Verifies that default valued attrs are stripped, unless disabled."""
@@ -2171,6 +2197,7 @@ class MetaGraphTest(test.TestCase):
self.assertIn("T", node_def.attr)
self.assertIn("Tout", node_def.attr)
+ @test_util.run_deprecated_v1
def testImportIntoNamescope(self):
# Test that we can import a meta graph into a namescope.
test_dir = self._get_test_dir("import_into_namescope")
@@ -2241,6 +2268,7 @@ class MetaGraphTest(test.TestCase):
filename + ".meta", graph=graph_2, import_scope="my_scope")
self.assertIsInstance(new_saver_3, saver_module.Saver)
+ @test_util.run_deprecated_v1
def testImportIntoImplicitNamescope(self):
# Test that we can import a meta graph into an implicit namescope.
test_dir = self._get_test_dir("import_into_namescope")
@@ -2363,6 +2391,7 @@ class CheckpointReaderTest(test.TestCase):
_WRITE_VERSION = saver_pb2.SaverDef.V1
+ @test_util.run_deprecated_v1
def testDebugString(self):
# Builds a graph.
v0 = variables.VariableV1(
@@ -2594,6 +2623,7 @@ class ScopedGraphTest(test.TestCase):
# Verifies that we can save the subgraph under "hidden1" and restore it
# into "new_hidden1" in the new graph.
+ @test_util.run_deprecated_v1
def testScopedSaveAndRestore(self):
test_dir = self._get_test_dir("scoped_export_import")
ckpt_filename = "ckpt"
@@ -2603,6 +2633,7 @@ class ScopedGraphTest(test.TestCase):
# Verifies that we can copy the subgraph under "hidden1" and copy it
# to different name scope in the same graph or different graph.
+ @test_util.run_deprecated_v1
def testCopyScopedGraph(self):
test_dir = self._get_test_dir("scoped_copy")
saver0_ckpt = os.path.join(test_dir, "saver0.ckpt")
@@ -2659,6 +2690,7 @@ class ScopedGraphTest(test.TestCase):
saver3.restore(sess, saver0_ckpt)
self.assertAllClose(expected, sess.run("new_hidden1/relu:0"))
+ @test_util.run_deprecated_v1
def testExportGraphDefWithScope(self):
test_dir = self._get_test_dir("export_graph_def")
saver0_ckpt = os.path.join(test_dir, "saver0.ckpt")
@@ -2695,6 +2727,7 @@ class ScopedGraphTest(test.TestCase):
saver3.restore(sess, saver0_ckpt)
self.assertAllClose(expected, sess.run("new_hidden1/relu:0"))
+ @test_util.run_deprecated_v1
def testSerializeSaverWithScope(self):
test_dir = self._get_test_dir("export_graph_def")
saver1_ckpt = os.path.join(test_dir, "saver1.ckpt")
@@ -2955,6 +2988,7 @@ class CheckpointableCompatibilityTests(test.TestCase):
# exception" block in Python 3.
self.assertNotIn("NewCheckpointReader", cs.exception.message)
+ @test_util.run_deprecated_v1
def testGraphChangedForRestoreErrorRaised(self):
checkpoint_directory = self.get_temp_dir()
checkpoint_prefix = os.path.join(checkpoint_directory, "ckpt")
@@ -2976,6 +3010,7 @@ class CheckpointableCompatibilityTests(test.TestCase):
"a mismatch between the current graph and the graph"):
a_saver.restore(sess=sess, save_path=save_path)
+ @test_util.run_deprecated_v1
def testLoadFromObjectBasedGraph(self):
checkpoint_directory = self.get_temp_dir()
checkpoint_prefix = os.path.join(checkpoint_directory, "ckpt")
diff --git a/tensorflow/python/training/server_lib_multiple_containers_test.py b/tensorflow/python/training/server_lib_multiple_containers_test.py
index f599e9b55b9..fb6118942bd 100644
--- a/tensorflow/python/training/server_lib_multiple_containers_test.py
+++ b/tensorflow/python/training/server_lib_multiple_containers_test.py
@@ -21,6 +21,7 @@ from __future__ import print_function
from tensorflow.python.client import session
from tensorflow.python.framework import errors_impl
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import variables
from tensorflow.python.platform import test
from tensorflow.python.training import server_lib
@@ -33,6 +34,7 @@ class MultipleContainersTest(test.TestCase):
# TODO(b/34465411): Starting multiple servers with different configurations
# in the same test is flaky. Move this test case back into
# "server_lib_test.py" when this is no longer the case.
+ @test_util.run_deprecated_v1
def testMultipleContainers(self):
with ops.container("test0"):
v0 = variables.Variable(1.0, name="v0")
diff --git a/tensorflow/python/training/server_lib_same_variables_clear_container_test.py b/tensorflow/python/training/server_lib_same_variables_clear_container_test.py
index 3a5eb712c6f..e0ab21bbd97 100644
--- a/tensorflow/python/training/server_lib_same_variables_clear_container_test.py
+++ b/tensorflow/python/training/server_lib_same_variables_clear_container_test.py
@@ -20,6 +20,7 @@ from __future__ import print_function
from tensorflow.python.client import session
from tensorflow.python.framework import errors_impl
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import variables
from tensorflow.python.platform import test
from tensorflow.python.training import server_lib
@@ -32,6 +33,7 @@ class SameVariablesClearContainerTest(test.TestCase):
# TODO(b/34465411): Starting multiple servers with different configurations
# in the same test is flaky. Move this test case back into
# "server_lib_test.py" when this is no longer the case.
+ @test_util.run_deprecated_v1
def testSameVariablesClearContainer(self):
# Starts two servers with different names so they map to different
# resource "containers".
diff --git a/tensorflow/python/training/server_lib_same_variables_clear_test.py b/tensorflow/python/training/server_lib_same_variables_clear_test.py
index 4682f1ab84d..7b147af6c55 100644
--- a/tensorflow/python/training/server_lib_same_variables_clear_test.py
+++ b/tensorflow/python/training/server_lib_same_variables_clear_test.py
@@ -20,6 +20,7 @@ from __future__ import print_function
from tensorflow.python.client import session
from tensorflow.python.framework import errors_impl
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import variables
from tensorflow.python.platform import test
@@ -32,6 +33,7 @@ class SameVariablesClearTest(test.TestCase):
# TODO(b/34465411): Starting multiple servers with different configurations
# in the same test is flaky. Move this test case back into
# "server_lib_test.py" when this is no longer the case.
+ @test_util.run_deprecated_v1
def testSameVariablesClear(self):
server = server_lib.Server.create_local_server()
diff --git a/tensorflow/python/training/server_lib_same_variables_no_clear_test.py b/tensorflow/python/training/server_lib_same_variables_no_clear_test.py
index 5aa7f45c2b3..1b2d588f444 100644
--- a/tensorflow/python/training/server_lib_same_variables_no_clear_test.py
+++ b/tensorflow/python/training/server_lib_same_variables_no_clear_test.py
@@ -20,6 +20,7 @@ from __future__ import print_function
from tensorflow.python.client import session
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import variables
from tensorflow.python.platform import test
@@ -33,6 +34,7 @@ class SameVariablesNoClearTest(test.TestCase):
# TODO(b/34465411): Starting multiple servers with different configurations
# in the same test is flaky. Move this test case back into
# "server_lib_test.py" when this is no longer the case.
+ @test_util.run_deprecated_v1
def testSameVariablesNoClear(self):
server = server_lib.Server.create_local_server()
diff --git a/tensorflow/python/training/server_lib_sparse_job_test.py b/tensorflow/python/training/server_lib_sparse_job_test.py
index 8c2745b51aa..93b06e62160 100644
--- a/tensorflow/python/training/server_lib_sparse_job_test.py
+++ b/tensorflow/python/training/server_lib_sparse_job_test.py
@@ -21,6 +21,7 @@ from __future__ import print_function
from tensorflow.python.client import session
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.platform import test
from tensorflow.python.training import server_lib
@@ -30,6 +31,7 @@ class SparseJobTest(test.TestCase):
# TODO(b/34465411): Starting multiple servers with different configurations
# in the same test is flaky. Move this test case back into
# "server_lib_test.py" when this is no longer the case.
+ @test_util.run_deprecated_v1
def testSparseJob(self):
server = server_lib.Server({"local": {37: "localhost:0"}})
with ops.device("/job:local/task:37"):
diff --git a/tensorflow/python/training/session_manager_test.py b/tensorflow/python/training/session_manager_test.py
index 2b5c3b01def..4294ffa8512 100644
--- a/tensorflow/python/training/session_manager_test.py
+++ b/tensorflow/python/training/session_manager_test.py
@@ -25,6 +25,7 @@ from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors
from tensorflow.python.framework import errors_impl
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import control_flow_ops
from tensorflow.python.ops import variables
@@ -68,6 +69,7 @@ class SessionManagerTest(test.TestCase):
"", init_fn=lambda sess: sess.run(v.initializer))
self.assertAllClose([125], sess.run(v))
+ @test_util.run_deprecated_v1
def testPrepareSessionFails(self):
checkpoint_dir = os.path.join(self.get_temp_dir(), "prepare_session")
checkpoint_dir2 = os.path.join(self.get_temp_dir(), "prepare_session2")
@@ -152,6 +154,7 @@ class SessionManagerTest(test.TestCase):
sess.graph.get_tensor_by_name("v:0")).eval(session=sess))
self.assertEquals(1, sess.run(v))
+ @test_util.run_deprecated_v1
def testRecoverSession(self):
# Create a checkpoint.
checkpoint_dir = os.path.join(self.get_temp_dir(), "recover_session")
@@ -206,6 +209,7 @@ class SessionManagerTest(test.TestCase):
variables.global_variables()),
local_init_op=None)
+ @test_util.run_deprecated_v1
def testRecoverSessionWithReadyForLocalInitOp(self):
# Create a checkpoint.
checkpoint_dir = os.path.join(self.get_temp_dir(),
@@ -259,6 +263,7 @@ class SessionManagerTest(test.TestCase):
self.assertEquals(1, sess.run(v))
self.assertEquals(1, sess.run(w))
+ @test_util.run_deprecated_v1
def testRecoverSessionWithReadyForLocalInitOpFailsToReadyLocal(self):
# We use ready_for_local_init_op=tf.report_uninitialized_variables(),
# which causes recover_session to not run local_init_op, and to return
@@ -315,6 +320,7 @@ class SessionManagerTest(test.TestCase):
sess.graph.get_tensor_by_name("w:0")).eval(session=sess))
self.assertEquals(1, sess.run(v))
+ @test_util.run_deprecated_v1
def testRecoverSessionNoChkptStillRunsLocalInitOp(self):
# This test checks for backwards compatibility.
# In particular, we continue to ensure that recover_session will execute
@@ -343,6 +349,7 @@ class SessionManagerTest(test.TestCase):
sess.graph.get_tensor_by_name("w:0")).eval(session=sess))
self.assertEquals(1, sess.run(w))
+ @test_util.run_deprecated_v1
def testRecoverSessionFailsStillRunsLocalInitOp(self):
# Create a checkpoint.
checkpoint_dir = os.path.join(
@@ -386,6 +393,7 @@ class SessionManagerTest(test.TestCase):
sess.graph.get_tensor_by_name("w:0")).eval(session=sess))
self.assertEquals(1, sess.run(w))
+ @test_util.run_deprecated_v1
def testWaitForSessionLocalInit(self):
server = server_lib.Server.create_local_server()
with ops.Graph().as_default() as graph:
@@ -437,6 +445,7 @@ class SessionManagerTest(test.TestCase):
# because of overly restrictive ready_for_local_init_op
sm.wait_for_session("", max_wait_secs=3)
+ @test_util.run_deprecated_v1
def testWaitForSessionInsufficientReadyForLocalInitCheck(self):
with ops.Graph().as_default() as graph:
v = variables.VariableV1(1, name="v")
@@ -454,6 +463,7 @@ class SessionManagerTest(test.TestCase):
"Session was not ready after waiting.*"):
sm.wait_for_session("", max_wait_secs=3)
+ @test_util.run_deprecated_v1
def testPrepareSessionWithReadyForLocalInitOp(self):
with ops.Graph().as_default():
v = variables.VariableV1(1, name="v")
@@ -493,6 +503,7 @@ class SessionManagerTest(test.TestCase):
self.assertEquals(1, sess.run(w))
self.assertEquals(3, sess.run(x))
+ @test_util.run_deprecated_v1
def testPrepareSessionWithPartialInitOp(self):
with ops.Graph().as_default():
v = variables.VariableV1(1, name="v")
@@ -559,6 +570,7 @@ class SessionManagerTest(test.TestCase):
self.assertEquals(1, sess.run(w_res))
self.assertEquals(3, sess.run(x_res))
+ @test_util.run_deprecated_v1
def testPrepareSessionWithCyclicInitializer(self):
# Regression test. Previously Variable._build_initializer_expr would enter
# into an infinite recursion when the variable's initial_value involved
@@ -632,6 +644,7 @@ class SessionManagerTest(test.TestCase):
"Init operations did not make model ready for local_init"):
sm2.prepare_session("", init_op=None)
+ @test_util.run_deprecated_v1
def testPrepareSessionWithInsufficientReadyForLocalInitCheck(self):
with ops.Graph().as_default():
v = variables.VariableV1(1, name="v")
@@ -684,6 +697,7 @@ class ObsoleteSessionManagerTest(test.TestCase):
"", init_fn=lambda sess: sess.run(v.initializer))
self.assertAllClose([125], sess.run(v))
+ @test_util.run_deprecated_v1
def testPrepareSessionFails(self):
checkpoint_dir = os.path.join(self.get_temp_dir(), "prepare_session")
checkpoint_dir2 = os.path.join(self.get_temp_dir(), "prepare_session2")
@@ -745,6 +759,7 @@ class ObsoleteSessionManagerTest(test.TestCase):
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("v:0")).eval(session=sess))
+ @test_util.run_deprecated_v1
def testRecoverSession(self):
# Create a checkpoint.
checkpoint_dir = os.path.join(self.get_temp_dir(), "recover_session")
diff --git a/tensorflow/python/training/slot_creator_test.py b/tensorflow/python/training/slot_creator_test.py
index 382c15bb55c..1f26aaa434e 100644
--- a/tensorflow/python/training/slot_creator_test.py
+++ b/tensorflow/python/training/slot_creator_test.py
@@ -21,6 +21,7 @@ from __future__ import print_function
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import random_ops
from tensorflow.python.ops import variable_scope
@@ -31,6 +32,7 @@ from tensorflow.python.training import slot_creator
class SlotCreatorTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testCreateSlotFromVariable(self):
with self.cached_session():
v = variables.Variable([1.0, 2.5], name="var")
@@ -43,6 +45,7 @@ class SlotCreatorTest(test.TestCase):
self.assertEqual(dtypes.float32, slot.dtype.base_dtype)
self.assertAllEqual([1.0, 2.5], self.evaluate(slot))
+ @test_util.run_deprecated_v1
def testCreateSlotFromTensor(self):
with self.cached_session():
v = constant_op.constant([1.0, 2.5], name="const")
@@ -55,6 +58,7 @@ class SlotCreatorTest(test.TestCase):
self.assertEqual(dtypes.float32, slot.dtype.base_dtype)
self.assertAllEqual([2.0, 5.0], self.evaluate(slot))
+ @test_util.run_deprecated_v1
def testCreateZerosSlotFromVariable(self):
with self.cached_session():
v = variables.Variable([1.0, 2.5], name="var")
@@ -69,6 +73,7 @@ class SlotCreatorTest(test.TestCase):
self.assertEqual(dtypes.float64, slot.dtype.base_dtype)
self.assertAllEqual([0.0, 0.0], self.evaluate(slot))
+ @test_util.run_deprecated_v1
def testCreateZerosSlotFromDynamicShapedVariable(self):
with self.cached_session():
dyn_shape = constant_op.constant([2], dtype=dtypes.int32)
@@ -90,6 +95,7 @@ class SlotCreatorTest(test.TestCase):
self.assertEqual(dtypes.float64, slot.dtype.base_dtype)
self.assertAllEqual([0.0, 0.0], self.evaluate(slot))
+ @test_util.run_deprecated_v1
def testCreateZerosSlotFromTensor(self):
with self.cached_session():
v = constant_op.constant([1.0, 2.5], name="const")
@@ -103,6 +109,7 @@ class SlotCreatorTest(test.TestCase):
self.assertEqual(dtypes.float32, slot.dtype.base_dtype)
self.assertAllEqual([0.0, 0.0], self.evaluate(slot))
+ @test_util.run_deprecated_v1
def testCreateZerosSlotFromDynamicShapedTensor(self):
with self.cached_session():
v = random_ops.random_uniform([2], dtype=dtypes.float64)
@@ -118,6 +125,7 @@ class SlotCreatorTest(test.TestCase):
self.assertEqual(dtypes.float64, slot.dtype.base_dtype)
self.assertAllEqual([0.0, 0.0], self.evaluate(slot))
+ @test_util.run_deprecated_v1
def testCreateSlotFromVariableRespectsScope(self):
# See discussion on #2740.
with self.cached_session():
diff --git a/tensorflow/python/training/supervisor_test.py b/tensorflow/python/training/supervisor_test.py
index 9dc88d78ccc..f6505acc9ac 100644
--- a/tensorflow/python/training/supervisor_test.py
+++ b/tensorflow/python/training/supervisor_test.py
@@ -35,6 +35,7 @@ from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors_impl
from tensorflow.python.framework import meta_graph
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import io_ops
from tensorflow.python.ops import parsing_ops
@@ -420,6 +421,7 @@ class SupervisorTest(test.TestCase):
with self.assertRaisesRegexp(RuntimeError, "requires a summary writer"):
sv.summary_computed(sess, sess.run(summ))
+ @test_util.run_deprecated_v1
def testLogdirButExplicitlyNoSummaryWriter(self):
logdir = self._test_dir("explicit_no_summary_writer")
with ops.Graph().as_default():
@@ -505,6 +507,7 @@ class SupervisorTest(test.TestCase):
sv = supervisor.Supervisor(logdir="", session_manager=sm)
sv.prepare_or_wait_for_session("")
+ @test_util.run_deprecated_v1
def testInitOp(self):
logdir = self._test_dir("default_init_op")
with ops.Graph().as_default():
@@ -514,6 +517,7 @@ class SupervisorTest(test.TestCase):
self.assertAllClose([1.0, 2.0, 3.0], sess.run(v))
sv.stop()
+ @test_util.run_deprecated_v1
def testInitFn(self):
logdir = self._test_dir("default_init_op")
with ops.Graph().as_default():
@@ -527,6 +531,7 @@ class SupervisorTest(test.TestCase):
self.assertAllClose([1.0, 2.0, 3.0], sess.run(v))
sv.stop()
+ @test_util.run_deprecated_v1
def testInitOpWithFeedDict(self):
logdir = self._test_dir("feed_dict_init_op")
with ops.Graph().as_default():
@@ -540,6 +545,7 @@ class SupervisorTest(test.TestCase):
self.assertAllClose([1.0, 2.0, 3.0], sess.run(v))
sv.stop()
+ @test_util.run_deprecated_v1
def testReadyForLocalInitOp(self):
server = server_lib.Server.create_local_server()
logdir = self._test_dir("default_ready_for_local_init_op")
@@ -582,6 +588,7 @@ class SupervisorTest(test.TestCase):
sv0.stop()
sv1.stop()
+ @test_util.run_deprecated_v1
def testReadyForLocalInitOpRestoreFromCheckpoint(self):
server = server_lib.Server.create_local_server()
logdir = self._test_dir("ready_for_local_init_op_restore")
@@ -713,6 +720,7 @@ class SupervisorTest(test.TestCase):
"Variables not initialized: w"):
sv.prepare_or_wait_for_session(server.target)
+ @test_util.run_deprecated_v1
def testSetupFail(self):
logdir = self._test_dir("setup_fail")
with ops.Graph().as_default():
@@ -723,6 +731,7 @@ class SupervisorTest(test.TestCase):
variables.VariableV1([1.0, 2.0, 3.0], name="v")
supervisor.Supervisor(logdir=logdir, is_chief=False)
+ @test_util.run_deprecated_v1
def testDefaultGlobalStep(self):
logdir = self._test_dir("default_global_step")
with ops.Graph().as_default():
@@ -732,6 +741,7 @@ class SupervisorTest(test.TestCase):
self.assertEquals(287, sess.run(sv.global_step))
sv.stop()
+ @test_util.run_deprecated_v1
def testRestoreFromMetaGraph(self):
logdir = self._test_dir("restore_from_meta_graph")
with ops.Graph().as_default():
@@ -753,6 +763,7 @@ class SupervisorTest(test.TestCase):
# This test is based on the fact that the standard services start
# right away and get to run once before sv.stop() returns.
# We still sleep a bit to make the test robust.
+ @test_util.run_deprecated_v1
def testStandardServicesWithoutGlobalStep(self):
logdir = self._test_dir("standard_services_without_global_step")
# Create a checkpoint.
@@ -803,6 +814,7 @@ class SupervisorTest(test.TestCase):
# Same as testStandardServicesNoGlobalStep but with a global step.
# We should get a summary about the step time.
+ @test_util.run_deprecated_v1
def testStandardServicesWithGlobalStep(self):
logdir = self._test_dir("standard_services_with_global_step")
# Create a checkpoint.
diff --git a/tensorflow/python/training/training_ops_test.py b/tensorflow/python/training/training_ops_test.py
index 929dd74ac64..51f49ca0818 100644
--- a/tensorflow/python/training/training_ops_test.py
+++ b/tensorflow/python/training/training_ops_test.py
@@ -24,6 +24,7 @@ import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
from tensorflow.python.framework.test_util import TensorFlowTestCase
# Import resource_variable_ops for the variables-to-tensor implicit conversion.
from tensorflow.python.ops import resource_variable_ops # pylint: disable=unused-import
@@ -59,6 +60,7 @@ class TrainingOpsTest(TensorFlowTestCase):
self.assertShapeEqual(out, apply_sgd)
self.assertAllCloseAccordingToType(x - alpha * delta, out)
+ @test_util.run_deprecated_v1
def testApplyGradientDescent(self):
for (dtype, use_gpu) in itertools.product(
[np.float16, np.float32, np.float64], [False, True]):
@@ -127,6 +129,7 @@ class TrainingOpsTest(TensorFlowTestCase):
self.assertAllClose(linear_update, self.evaluate(linear))
self.assertAllClose(expected_out, out)
+ @test_util.run_deprecated_v1
def testApplyAdagrad(self):
for (dtype, use_gpu) in itertools.product(
[np.float16, np.float32, np.float64], [False, True]):
@@ -136,6 +139,7 @@ class TrainingOpsTest(TensorFlowTestCase):
grad = np.arange(100).astype(dtype)
self._testTypesForAdagrad(x, y, lr, grad, use_gpu)
+ @test_util.run_deprecated_v1
def testApplyFtrl(self):
for dtype in [np.float16, np.float32, np.float64]:
x = np.arange(100).astype(dtype)
@@ -207,6 +211,7 @@ class TrainingOpsTest(TensorFlowTestCase):
self.assertAllCloseAccordingToType(y[index] + grad[i] * grad[i],
self.evaluate(accum)[index])
+ @test_util.run_deprecated_v1
def testSparseApplyAdagrad(self):
for (dtype, index_type) in itertools.product(
[np.float16, np.float32, np.float64], [np.int32, np.int64]):
@@ -220,6 +225,7 @@ class TrainingOpsTest(TensorFlowTestCase):
indices = np.array([0, 2]).astype(index_type)
self._testTypesForSparseAdagrad(x, y, lr, grad, indices)
+ @test_util.run_deprecated_v1
def testSparseApplyAdagradDim1(self):
for (dtype, index_type) in itertools.product(
[np.float16, np.float32, np.float64], [np.int32, np.int64]):
@@ -233,6 +239,7 @@ class TrainingOpsTest(TensorFlowTestCase):
indices = np.array([0, 2]).astype(index_type)
self._testTypesForSparseAdagrad(x, y, lr, grad, indices)
+ @test_util.run_deprecated_v1
def testSparseApplyFtrlDim1(self):
for (dtype, index_type) in itertools.product(
[np.float16, np.float32, np.float64], [np.int32, np.int64]):
@@ -248,6 +255,7 @@ class TrainingOpsTest(TensorFlowTestCase):
indices = np.array([0, 2]).astype(index_type)
self._testTypesForSparseFtrl(x, y, z, lr, grad, indices)
+ @test_util.run_deprecated_v1
def testApplyAdam(self):
for dtype, use_gpu in itertools.product(
[np.float16, np.float32, np.float64], [False, True]):
diff --git a/tensorflow/python/training/training_util_test.py b/tensorflow/python/training/training_util_test.py
index ba64e785ac6..3317008fce0 100644
--- a/tensorflow/python/training/training_util_test.py
+++ b/tensorflow/python/training/training_util_test.py
@@ -20,6 +20,7 @@ from __future__ import print_function
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
from tensorflow.python.ops import variables
from tensorflow.python.platform import test
from tensorflow.python.training import monitored_session
@@ -46,6 +47,7 @@ class GlobalStepTest(test.TestCase):
self.assertRaisesRegexp(TypeError, 'does not have integer type',
training_util.get_global_step, g)
+ @test_util.run_deprecated_v1
def test_invalid_shape(self):
with ops.Graph().as_default() as g:
self.assertIsNone(training_util.get_global_step())
@@ -70,6 +72,7 @@ class GlobalStepTest(test.TestCase):
training_util.create_global_step, g)
self._assert_global_step(training_util.create_global_step(ops.Graph()))
+ @test_util.run_deprecated_v1
def test_get_global_step(self):
with ops.Graph().as_default() as g:
self.assertIsNone(training_util.get_global_step())
diff --git a/tensorflow/python/util/deprecation_test.py b/tensorflow/python/util/deprecation_test.py
index 34cbca52a1b..035c416d793 100644
--- a/tensorflow/python/util/deprecation_test.py
+++ b/tensorflow/python/util/deprecation_test.py
@@ -19,6 +19,7 @@ from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
+from tensorflow.python.framework import test_util
from tensorflow.python.platform import test
from tensorflow.python.platform import tf_logging as logging
from tensorflow.python.util import deprecation
@@ -174,6 +175,7 @@ class DeprecationTest(test.TestCase):
set(args[1:]))
@test.mock.patch.object(logging, "warning", autospec=True)
+ @test_util.run_deprecated_v1
def test_static_fn_with_doc(self, mock_warning):
date = "2016-07-04"
instructions = "This is how you update..."
@@ -214,6 +216,7 @@ class DeprecationTest(test.TestCase):
self._assert_subset(set(["after " + date, instructions]), set(args[1:]))
@test.mock.patch.object(logging, "warning", autospec=True)
+ @test_util.run_deprecated_v1
def test_static_fn_with_one_line_doc(self, mock_warning):
date = "2016-07-04"
instructions = "This is how you update..."
@@ -239,6 +242,7 @@ class DeprecationTest(test.TestCase):
self._assert_subset(set(["after " + date, instructions]), set(args[1:]))
@test.mock.patch.object(logging, "warning", autospec=True)
+ @test_util.run_deprecated_v1
def test_static_fn_no_doc(self, mock_warning):
date = "2016-07-04"
instructions = "This is how you update..."
@@ -488,6 +492,7 @@ class DeprecatedArgsTest(test.TestCase):
deprecation.deprecated_args(date, instructions, "missing")(_fn)
@test.mock.patch.object(logging, "warning", autospec=True)
+ @test_util.run_deprecated_v1
def test_static_fn_with_doc(self, mock_warning):
date = "2016-07-04"
instructions = "This is how you update..."
@@ -535,6 +540,7 @@ class DeprecatedArgsTest(test.TestCase):
self._assert_subset(set(["after " + date, instructions]), set(args[1:]))
@test.mock.patch.object(logging, "warning", autospec=True)
+ @test_util.run_deprecated_v1
def test_static_fn_with_one_line_doc(self, mock_warning):
date = "2016-07-04"
instructions = "This is how you update..."
@@ -565,6 +571,7 @@ class DeprecatedArgsTest(test.TestCase):
self._assert_subset(set(["after " + date, instructions]), set(args[1:]))
@test.mock.patch.object(logging, "warning", autospec=True)
+ @test_util.run_deprecated_v1
def test_static_fn_no_doc(self, mock_warning):
date = "2016-07-04"
instructions = "This is how you update..."
@@ -595,6 +602,7 @@ class DeprecatedArgsTest(test.TestCase):
self._assert_subset(set(["after " + date, instructions]), set(args[1:]))
@test.mock.patch.object(logging, "warning", autospec=True)
+ @test_util.run_deprecated_v1
def test_varargs(self, mock_warning):
date = "2016-07-04"
instructions = "This is how you update..."
@@ -615,6 +623,7 @@ class DeprecatedArgsTest(test.TestCase):
self._assert_subset(set(["after " + date, instructions]), set(args[1:]))
@test.mock.patch.object(logging, "warning", autospec=True)
+ @test_util.run_deprecated_v1
def test_kwargs(self, mock_warning):
date = "2016-07-04"
instructions = "This is how you update..."
@@ -635,6 +644,7 @@ class DeprecatedArgsTest(test.TestCase):
self._assert_subset(set(["after " + date, instructions]), set(args[1:]))
@test.mock.patch.object(logging, "warning", autospec=True)
+ @test_util.run_deprecated_v1
def test_positional_and_named(self, mock_warning):
date = "2016-07-04"
instructions = "This is how you update..."
@@ -660,6 +670,7 @@ class DeprecatedArgsTest(test.TestCase):
set(args2[1:]))
@test.mock.patch.object(logging, "warning", autospec=True)
+ @test_util.run_deprecated_v1
def test_positional_and_named_with_ok_vals(self, mock_warning):
date = "2016-07-04"
instructions = "This is how you update..."
@@ -692,6 +703,7 @@ class DeprecatedArgsTest(test.TestCase):
self.assertEqual(0, mock_warning.call_count)
@test.mock.patch.object(logging, "warning", autospec=True)
+ @test_util.run_deprecated_v1
def test_deprecated_args_once(self, mock_warning):
date = "2016-07-04"
instructions = "This is how you update..."
@@ -708,6 +720,7 @@ class DeprecatedArgsTest(test.TestCase):
self.assertEqual(1, mock_warning.call_count)
@test.mock.patch.object(logging, "warning", autospec=True)
+ @test_util.run_deprecated_v1
def test_deprecated_multiple_args_once_each(self, mock_warning):
date = "2016-07-04"
instructions = "This is how you update..."
@@ -752,6 +765,7 @@ class DeprecatedArgValuesTest(test.TestCase):
deprecation.deprecated_arg_values(date, instructions)
@test.mock.patch.object(logging, "warning", autospec=True)
+ @test_util.run_deprecated_v1
def test_static_fn_with_doc(self, mock_warning):
date = "2016-07-04"
instructions = "This is how you update..."
@@ -804,6 +818,7 @@ class DeprecatedArgValuesTest(test.TestCase):
self.assertEqual(2, mock_warning.call_count)
@test.mock.patch.object(logging, "warning", autospec=True)
+ @test_util.run_deprecated_v1
def test_static_fn_with_one_line_doc(self, mock_warning):
date = "2016-07-04"
instructions = "This is how you update..."
@@ -839,6 +854,7 @@ class DeprecatedArgValuesTest(test.TestCase):
self.assertEqual(2, mock_warning.call_count)
@test.mock.patch.object(logging, "warning", autospec=True)
+ @test_util.run_deprecated_v1
def test_static_fn_no_doc(self, mock_warning):
date = "2016-07-04"
instructions = "This is how you update..."
diff --git a/tensorflow/python/util/nest_test.py b/tensorflow/python/util/nest_test.py
index 997a3c5c36f..d0d0c5f7935 100644
--- a/tensorflow/python/util/nest_test.py
+++ b/tensorflow/python/util/nest_test.py
@@ -482,6 +482,7 @@ class NestTest(parameterized.TestCase, test.TestCase):
self.assertEqual(nt.a[1][::-1], rev_nt.a[1])
self.assertEqual(nt.b[::-1], rev_nt.b)
+ @test_util.run_deprecated_v1
def testMapStructureOverPlaceholders(self):
inp_a = (array_ops.placeholder(dtypes.float32, shape=[3, 4]),
array_ops.placeholder(dtypes.float32, shape=[3, 7]))
diff --git a/tensorflow/python/util/tf_should_use_test.py b/tensorflow/python/util/tf_should_use_test.py
index cde67c4e4f5..65d848cf2a5 100644
--- a/tensorflow/python/util/tf_should_use_test.py
+++ b/tensorflow/python/util/tf_should_use_test.py
@@ -24,6 +24,7 @@ import gc
import sys
from tensorflow.python.framework import constant_op
+from tensorflow.python.framework import test_util
from tensorflow.python.platform import test
from tensorflow.python.platform import tf_logging
from tensorflow.python.util import tf_should_use
@@ -39,6 +40,7 @@ def reroute_error():
class TfShouldUseTest(test.TestCase):
+ @test_util.run_deprecated_v1
def testAddShouldUseWarningWhenNotUsed(self):
c = constant_op.constant(0, name='blah0')
def in_this_function():
@@ -52,6 +54,7 @@ class TfShouldUseTest(test.TestCase):
self.assertIn('in_this_function', msg)
self.assertFalse(gc.garbage)
+ @test_util.run_deprecated_v1
def testAddShouldUseFatalWhenNotUsed(self):
c = constant_op.constant(0, name='blah0')
def in_this_function():
@@ -74,6 +77,7 @@ class TfShouldUseTest(test.TestCase):
error.assert_not_called()
fatal.assert_not_called()
+ @test_util.run_deprecated_v1
def testAddShouldUseWarningWhenUsedWithAdd(self):
def add(h):
_ = h + 1
@@ -81,6 +85,7 @@ class TfShouldUseTest(test.TestCase):
gc.collect()
self.assertFalse(gc.garbage)
+ @test_util.run_deprecated_v1
def testAddShouldUseWarningWhenUsedWithGetName(self):
def get_name(h):
_ = h.name
@@ -88,6 +93,7 @@ class TfShouldUseTest(test.TestCase):
gc.collect()
self.assertFalse(gc.garbage)
+ @test_util.run_deprecated_v1
def testShouldUseResult(self):
@tf_should_use.should_use_result
def return_const(value):
@@ -101,6 +107,7 @@ class TfShouldUseTest(test.TestCase):
gc.collect()
self.assertFalse(gc.garbage)
+ @test_util.run_deprecated_v1
def testShouldUseResultWhenNotReallyUsed(self):
@tf_should_use.should_use_result
def return_const(value):
diff --git a/tensorflow/tools/api/tests/api_compatibility_test.py b/tensorflow/tools/api/tests/api_compatibility_test.py
index cba6246feff..e7f23a11740 100644
--- a/tensorflow/tools/api/tests/api_compatibility_test.py
+++ b/tensorflow/tools/api/tests/api_compatibility_test.py
@@ -39,6 +39,7 @@ from google.protobuf import message
from google.protobuf import text_format
from tensorflow.python.lib.io import file_io
+from tensorflow.python.framework import test_util
from tensorflow.python.platform import resource_loader
from tensorflow.python.platform import test
from tensorflow.python.platform import tf_logging as logging
@@ -310,6 +311,7 @@ class ApiCompatibilityTest(test.TestCase):
update_goldens=FLAGS.update_goldens,
api_version=api_version)
+ @test_util.run_deprecated_v1
def testAPIBackwardsCompatibility(self):
api_version = 1
golden_file_pattern = os.path.join(
@@ -328,6 +330,7 @@ class ApiCompatibilityTest(test.TestCase):
'tensorflow.python.util.lazy_loader.LazyLoader'
in str(type(tf.contrib)))
+ @test_util.run_deprecated_v1
def testAPIBackwardsCompatibilityV1(self):
api_version = 1
golden_file_pattern = os.path.join(