From 1fdd7c7408aa1cb37729e76a6e9fbfe8daa0b1f5 Mon Sep 17 00:00:00 2001 From: Gaurav Jain Date: Sun, 18 Nov 2018 20:00:30 -0800 Subject: [PATCH] Replace a few calls of Session `run` with `evaluate` In order to support tests running in eager mode we need to avoid unnecessary use of Sessions in tests. This moves to remove some of the uses of the `run` function in favor of `evaluate`. PiperOrigin-RevId: 222013881 --- .../compiler/tests/categorical_op_test.py | 10 +- tensorflow/compiler/tests/concat_ops_test.py | 8 +- tensorflow/compiler/tests/eager_test.py | 2 +- tensorflow/compiler/tests/function_test.py | 6 +- tensorflow/compiler/tests/lstm_test.py | 4 +- tensorflow/compiler/tests/placeholder_test.py | 2 +- tensorflow/compiler/tests/random_ops_test.py | 14 +- .../compiler/tests/tensor_array_ops_test.py | 2 +- .../compiler/tests/variable_ops_test.py | 30 +- .../autograph/integration_tests/keras_test.py | 2 +- .../integration_tests/list_literals_test.py | 2 +- .../speech_commands/input_data_test.py | 2 +- .../speech_commands/label_wav_test.py | 2 +- .../speech_commands/wav_to_features_test.py | 2 +- .../autograph/converters/call_trees_test.py | 2 +- .../python/autograph/converters/lists_test.py | 6 +- .../converters/side_effect_guards_test.py | 20 +- .../autograph/converters/slices_test.py | 2 +- tensorflow/python/autograph/impl/api_test.py | 46 +- .../autograph/lang/special_functions_test.py | 12 +- .../autograph/operators/control_flow_test.py | 14 +- .../operators/data_structures_test.py | 16 +- .../autograph/operators/logical_test.py | 14 +- .../autograph/operators/py_builtins_test.py | 28 +- .../python/autograph/operators/slices_test.py | 8 +- .../python/autograph/utils/misc_test.py | 4 +- .../python/autograph/utils/py_func_test.py | 18 +- .../autograph/utils/tensor_list_test.py | 4 +- .../client/session_clusterspec_prop_test.py | 6 +- tensorflow/python/client/timeline_test.py | 4 +- tensorflow/python/client/virtual_gpu_test.py | 2 +- .../kernel_tests/batch_dataset_op_test.py | 54 +-- .../bucket_by_sequence_length_test.py | 2 +- .../kernel_tests/copy_to_device_test.py | 84 ++-- .../experimental/kernel_tests/counter_test.py | 12 +- .../dense_to_sparse_batch_test.py | 8 +- .../directed_interleave_dataset_test.py | 6 +- .../kernel_tests/enumerate_dataset_test.py | 6 +- .../function_buffering_resource_test.py | 70 +-- .../kernel_tests/group_by_reducer_test.py | 6 +- .../kernel_tests/group_by_window_test.py | 52 +-- .../kernel_tests/ignore_errors_test.py | 16 +- .../kernel_tests/indexed_dataset_ops_test.py | 6 +- .../make_batched_features_dataset_test.py | 4 +- .../kernel_tests/make_csv_dataset_test.py | 2 +- .../make_tf_record_dataset_test.py | 6 +- .../kernel_tests/map_and_batch_test.py | 38 +- .../kernel_tests/map_defun_op_test.py | 2 +- .../kernel_tests/override_threadpool_test.py | 2 +- .../kernel_tests/parallel_interleave_test.py | 6 +- .../kernel_tests/prefetch_to_device_test.py | 26 +- .../experimental/kernel_tests/scan_test.py | 6 +- .../range_dataset_serialization_test.py | 26 +- .../serialization_integration_test.py | 4 +- .../kernel_tests/shuffle_and_repeat_test.py | 2 +- .../experimental/kernel_tests/sleep_test.py | 4 +- .../kernel_tests/sql_dataset_test.py | 97 ++-- .../kernel_tests/stats_dataset_ops_test.py | 58 +-- .../experimental/kernel_tests/unbatch_test.py | 12 +- .../experimental/kernel_tests/unique_test.py | 4 +- .../kernel_tests/batch_dataset_op_test.py | 26 +- .../kernel_tests/cache_dataset_op_test.py | 18 +- .../concatenate_dataset_op_test.py | 8 +- .../dataset_constructor_op_test.py | 44 +- .../dataset_from_generator_op_test.py | 78 ++-- .../kernel_tests/filter_dataset_op_test.py | 26 +- .../kernel_tests/flat_map_dataset_op_test.py | 20 +- .../interleave_dataset_op_test.py | 8 +- .../kernel_tests/iterator_ops_cluster_test.py | 12 +- .../data/kernel_tests/iterator_ops_test.py | 44 +- .../list_files_dataset_op_test.py | 2 +- .../data/kernel_tests/map_dataset_op_test.py | 126 +++--- .../multi_device_iterator_test.py | 68 +-- .../data/kernel_tests/optional_ops_test.py | 4 +- .../kernel_tests/prefetch_dataset_op_test.py | 2 +- .../kernel_tests/range_dataset_op_test.py | 116 ++--- .../kernel_tests/reader_dataset_ops_test.py | 112 ++--- .../kernel_tests/reduce_dataset_op_test.py | 11 +- .../kernel_tests/sequence_dataset_op_test.py | 20 +- .../kernel_tests/shuffle_dataset_op_test.py | 12 +- .../kernel_tests/window_dataset_op_test.py | 24 +- .../data/kernel_tests/zip_dataset_op_test.py | 6 +- tensorflow/python/data/util/convert_test.py | 8 +- .../python/debug/cli/analyzer_cli_test.py | 2 +- .../lib/debug_graph_reconstruction_test.py | 14 +- .../debug/lib/dist_session_debug_grpc_test.py | 8 +- .../debug/lib/session_debug_multi_gpu_test.py | 2 +- .../python/debug/lib/source_utils_test.py | 4 +- .../distribute/distribute_coordinator_test.py | 6 +- .../python/distribute/input_ops_test.py | 7 +- tensorflow/python/eager/def_function_test.py | 8 +- .../python/eager/function_gradients_test.py | 2 +- tensorflow/python/eager/function_test.py | 4 +- .../feature_column/feature_column_test.py | 8 +- .../feature_column/feature_column_v2_test.py | 11 +- tensorflow/python/framework/function_test.py | 50 +-- .../python/framework/graph_util_test.py | 10 +- tensorflow/python/framework/importer_test.py | 12 +- .../python/framework/meta_graph_test.py | 12 +- tensorflow/python/framework/ops_test.py | 6 +- .../python/framework/smart_cond_test.py | 8 +- .../python/framework/sparse_tensor_test.py | 2 +- .../python/framework/tensor_util_test.py | 2 +- .../python/grappler/constant_folding_test.py | 2 +- .../python/grappler/layout_optimizer_test.py | 48 +- .../python/grappler/memory_optimizer_test.py | 12 +- tensorflow/python/keras/backend_test.py | 2 +- .../python/keras/layers/recurrent_test.py | 4 +- .../python/kernel_tests/accumulate_n_test.py | 2 +- .../python/kernel_tests/array_ops_test.py | 14 +- .../python/kernel_tests/basic_gpu_test.py | 8 +- .../boosted_trees/quantile_ops_test.py | 4 +- .../boosted_trees/stats_ops_test.py | 30 +- .../python/kernel_tests/bucketize_op_test.py | 6 +- .../candidate_sampler_ops_test.py | 2 +- .../python/kernel_tests/cast_op_test.py | 2 +- .../python/kernel_tests/concat_op_test.py | 6 +- .../conditional_accumulator_test.py | 8 +- .../kernel_tests/control_flow_ops_py_test.py | 48 +- .../python/kernel_tests/conv_ops_3d_test.py | 10 +- .../python/kernel_tests/conv_ops_test.py | 12 +- .../python/kernel_tests/cwise_ops_test.py | 4 +- .../kernel_tests/decode_jpeg_op_test.py | 2 +- .../dense_update_ops_no_tsan_test.py | 8 +- .../kernel_tests/depthwise_conv_op_test.py | 6 +- .../distributions/categorical_test.py | 4 +- .../kernel_tests/dynamic_partition_op_test.py | 28 +- .../python/kernel_tests/fifo_queue_test.py | 84 ++-- .../kernel_tests/functional_ops_test.py | 46 +- .../kernel_tests/gradient_correctness_test.py | 8 +- .../python/kernel_tests/init_ops_test.py | 8 +- .../python/kernel_tests/lookup_ops_test.py | 2 +- tensorflow/python/kernel_tests/losses_test.py | 4 +- .../python/kernel_tests/map_stage_op_test.py | 22 +- .../kernel_tests/matrix_inverse_op_test.py | 2 +- .../kernel_tests/matrix_solve_op_test.py | 2 +- .../matrix_square_root_op_test.py | 2 +- .../python/kernel_tests/metrics_test.py | 419 +++++++++--------- .../neon_depthwise_conv_op_test.py | 6 +- .../python/kernel_tests/norm_op_test.py | 2 +- .../kernel_tests/nth_element_op_test.py | 2 +- .../kernel_tests/padding_fifo_queue_test.py | 88 ++-- .../parse_single_example_op_test.py | 2 +- .../python/kernel_tests/parsing_ops_test.py | 4 +- .../kernel_tests/pooling_ops_3d_test.py | 2 +- .../kernel_tests/priority_queue_test.py | 20 +- .../python/kernel_tests/py_func_test.py | 14 +- tensorflow/python/kernel_tests/qr_op_test.py | 2 +- .../random/multinomial_op_big_test.py | 6 +- .../random/multinomial_op_test.py | 12 +- .../kernel_tests/random/random_gamma_test.py | 2 +- .../kernel_tests/random/random_ops_test.py | 12 +- .../random/random_poisson_test.py | 2 +- .../random/random_shuffle_queue_test.py | 66 +-- .../python/kernel_tests/reader_ops_test.py | 2 +- .../python/kernel_tests/record_input_test.py | 16 +- .../python/kernel_tests/reduction_ops_test.py | 18 +- .../resource_variable_ops_test.py | 2 +- .../kernel_tests/scatter_nd_ops_test.py | 14 +- .../kernel_tests/self_adjoint_eig_op_test.py | 2 +- .../python/kernel_tests/session_ops_test.py | 22 +- tensorflow/python/kernel_tests/sets_test.py | 2 +- .../python/kernel_tests/shape_ops_test.py | 4 +- .../signal/reconstruction_ops_test.py | 8 +- .../python/kernel_tests/sparse_add_op_test.py | 8 +- .../kernel_tests/sparse_concat_op_test.py | 14 +- .../sparse_conditional_accumulator_test.py | 24 +- .../kernel_tests/sparse_cross_op_test.py | 34 +- .../python/kernel_tests/sparse_ops_test.py | 34 +- .../kernel_tests/sparse_reorder_op_test.py | 4 +- .../kernel_tests/sparse_reshape_op_test.py | 4 +- .../sparse_serialization_ops_test.py | 2 +- .../sparse_tensors_map_ops_test.py | 11 +- .../python/kernel_tests/stage_op_test.py | 18 +- .../kernel_tests/string_length_op_test.py | 2 +- .../kernel_tests/string_split_op_test.py | 28 +- .../kernel_tests/string_strip_op_test.py | 6 +- .../kernel_tests/summary_v1_audio_op_test.py | 2 +- .../kernel_tests/summary_v1_image_op_test.py | 4 +- .../kernel_tests/summary_v1_ops_test.py | 6 +- .../kernel_tests/summary_v1_tensor_op_test.py | 12 +- tensorflow/python/kernel_tests/svd_op_test.py | 4 +- .../python/kernel_tests/template_test.py | 8 +- .../kernel_tests/tensor_array_ops_test.py | 6 +- .../kernel_tests/unicode_transcode_op_test.py | 46 +- .../kernel_tests/variable_scope_test.py | 16 +- .../python/kernel_tests/variables_test.py | 36 +- .../python/kernel_tests/while_v2_test.py | 56 +-- .../python/kernel_tests/xent_op_test.py | 4 +- .../python/layers/convolutional_test.py | 16 +- tensorflow/python/layers/core_test.py | 2 +- .../python/layers/normalization_test.py | 74 ++-- .../python/ops/control_flow_ops_test.py | 12 +- tensorflow/python/ops/gradients_test.py | 28 +- tensorflow/python/ops/image_grad_test.py | 8 +- tensorflow/python/ops/image_ops_test.py | 30 +- tensorflow/python/ops/init_ops_test.py | 4 +- tensorflow/python/ops/math_ops_test.py | 4 +- .../python/ops/nn_fused_batchnorm_test.py | 2 +- tensorflow/python/ops/nn_test.py | 28 +- .../python/ops/parallel_for/gradients_test.py | 2 +- .../python/ops/quantized_conv_ops_test.py | 2 +- tensorflow/python/ops/quantized_ops_test.py | 4 +- .../ops/ragged/ragged_gather_nd_op_test.py | 2 +- .../python/profiler/model_analyzer_test.py | 30 +- .../python/profiler/profile_context_test.py | 8 +- tensorflow/python/saved_model/loader_test.py | 4 +- .../python/saved_model/saved_model_test.py | 42 +- .../python/saved_model/simple_save_test.py | 2 +- tensorflow/python/tools/strip_unused_test.py | 4 +- .../training/basic_session_run_hooks_test.py | 32 +- .../python/training/checkpoint_ops_test.py | 2 +- tensorflow/python/training/input_test.py | 54 +-- .../python/training/monitored_session_test.py | 16 +- .../python/training/moving_averages_test.py | 12 +- tensorflow/python/training/saver_test.py | 62 +-- .../training/server_lib_sparse_job_test.py | 2 +- tensorflow/python/training/supervisor_test.py | 10 +- .../training/warm_starting_util_test.py | 76 ++-- 219 files changed, 2039 insertions(+), 2015 deletions(-) diff --git a/tensorflow/compiler/tests/categorical_op_test.py b/tensorflow/compiler/tests/categorical_op_test.py index a57d1dc81ea..532e2b57484 100644 --- a/tensorflow/compiler/tests/categorical_op_test.py +++ b/tensorflow/compiler/tests/categorical_op_test.py @@ -60,7 +60,7 @@ class CategoricalTest(xla_test.XLATestCase): random_seed.set_random_seed(1618) op = random_ops.multinomial(logits, num_samples, output_dtype=dtypes.int32) - d = sess.run(op) + d = self.evaluate(op) batch_size, num_classes = logits.shape freqs_mat = [] @@ -85,9 +85,9 @@ class CategoricalTest(xla_test.XLATestCase): # The random-number generator, if working correctly, should produce the # same output multiple times with low probability. - y = sess.run(x) - z = sess.run(x) - w = sess.run(x) + y = self.evaluate(x) + z = self.evaluate(x) + w = self.evaluate(x) # We use exact equality here. If the random-number generator is producing # deterministic output, all three outputs will be bitwise identical. @@ -112,7 +112,7 @@ class CategoricalTest(xla_test.XLATestCase): x = random_ops.multinomial( array_ops.ones(shape=[1, 20], dtype=dtype), 1000, output_dtype=output_dtype) - y = sess.run(x) + y = self.evaluate(x) self.assertTrue((y >= 0).sum() == 1000) self.assertTrue((y < 20).sum() == 1000) diff --git a/tensorflow/compiler/tests/concat_ops_test.py b/tensorflow/compiler/tests/concat_ops_test.py index 30fbe6f701f..deb9ac186e6 100644 --- a/tensorflow/compiler/tests/concat_ops_test.py +++ b/tensorflow/compiler/tests/concat_ops_test.py @@ -337,7 +337,7 @@ class ConcatOffsetTest(xla_test.XLATestCase): s1 = constant_op.constant([2, 7, 5], dtypes.int32) s2 = constant_op.constant([2, 20, 5], dtypes.int32) off = gen_array_ops.concat_offset(cdim, [s0, s1, s2]) - ans = sess.run(off) + ans = self.evaluate(off) self.assertAllEqual(ans, [[0, 0, 0], [0, 3, 0], [0, 10, 0]]) @@ -350,7 +350,7 @@ class PackTest(xla_test.XLATestCase): s1 = constant_op.constant([2, 7, 5], dtypes.int32) s2 = constant_op.constant([2, 20, 5], dtypes.int32) packed = array_ops.stack([s0, s1, s2]) - ans = sess.run(packed) + ans = self.evaluate(packed) self.assertAllEqual(ans, [[2, 3, 5], [2, 7, 5], [2, 20, 5]]) def testScalars(self): @@ -360,7 +360,7 @@ class PackTest(xla_test.XLATestCase): s1 = constant_op.constant(3, dtypes.int32) s2 = constant_op.constant(5, dtypes.int32) packed = array_ops.stack([s0, s1, s2]) - ans = sess.run(packed) + ans = self.evaluate(packed) self.assertAllEqual(ans, [2, 3, 5]) def testEmpty(self): @@ -370,7 +370,7 @@ class PackTest(xla_test.XLATestCase): s1 = constant_op.constant([[]], dtypes.int32) s2 = constant_op.constant([[]], dtypes.int32) packed = array_ops.stack([s0, s1, s2]) - ans = sess.run(packed) + ans = self.evaluate(packed) self.assertAllEqual(ans, [[[]], [[]], [[]]]) diff --git a/tensorflow/compiler/tests/eager_test.py b/tensorflow/compiler/tests/eager_test.py index 63cee550fde..76706ad40a0 100644 --- a/tensorflow/compiler/tests/eager_test.py +++ b/tensorflow/compiler/tests/eager_test.py @@ -106,7 +106,7 @@ class EagerTest(xla_test.XLATestCase): three = constant_op.constant(3) five = constant_op.constant(5) product = three * five - self.assertAllEqual(15, sess.run(product)) + self.assertAllEqual(15, self.evaluate(product)) def testDegenerateSlices(self): with self.test_scope(): diff --git a/tensorflow/compiler/tests/function_test.py b/tensorflow/compiler/tests/function_test.py index b1891b918c6..dd9b7f30efe 100644 --- a/tensorflow/compiler/tests/function_test.py +++ b/tensorflow/compiler/tests/function_test.py @@ -50,7 +50,7 @@ class FunctionTest(xla_test.XLATestCase): b = constant_op.constant(bval, name="b") with self.test_scope(): call_f = Foo(a, b) - result = sess.run(call_f) + result = self.evaluate(call_f) self.assertAllClose(result, expected, rtol=1e-3) def testNestedFunctions(self): @@ -76,7 +76,7 @@ class FunctionTest(xla_test.XLATestCase): b = constant_op.constant(bval, name="b") with self.test_scope(): call_g = Foo(a, b) - result = sess.run(call_g) + result = self.evaluate(call_g) self.assertAllClose(result, expected, rtol=1e-3) def testFunctionMultipleRetvals(self): @@ -100,7 +100,7 @@ class FunctionTest(xla_test.XLATestCase): b = constant_op.constant(bval, name="b") with self.test_scope(): call_f = Foo(a, b) - result = sess.run(call_f) + result = self.evaluate(call_f) self.assertAllClose(result, expected, rtol=1e-3) def testCompileTimeConstantsInDefun(self): diff --git a/tensorflow/compiler/tests/lstm_test.py b/tensorflow/compiler/tests/lstm_test.py index 265c0b6d141..fd02a50aff9 100644 --- a/tensorflow/compiler/tests/lstm_test.py +++ b/tensorflow/compiler/tests/lstm_test.py @@ -88,7 +88,7 @@ class LSTMTest(test.TestCase): (basename, m_prev_scalar, c_prev_scalar, pad_scalar)) # Initialize variables and run the unrolled LSTM step. - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) return sess.run([m, c]) def testLSTMCell(self): @@ -173,7 +173,7 @@ class LSTMTest(test.TestCase): (basename, m_init_scalar, c_init_scalar, pad_scalar)) # Initialize variables and run the unrolled LSTM layer. - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) return sess.run(out_seq) def testLSTMLayer(self): diff --git a/tensorflow/compiler/tests/placeholder_test.py b/tensorflow/compiler/tests/placeholder_test.py index 77bb839409f..9671ae0ae97 100644 --- a/tensorflow/compiler/tests/placeholder_test.py +++ b/tensorflow/compiler/tests/placeholder_test.py @@ -33,7 +33,7 @@ class PlaceholderTest(xla_test.XLATestCase): ph = array_ops.placeholder_with_default(v, shape=[]) out = ph * 2 sess.run(variables.variables_initializer([v])) - self.assertEqual(8.0, sess.run(out)) + self.assertEqual(8.0, self.evaluate(out)) def test_placeholder_with_default_fed(self): with self.cached_session() as sess, self.test_scope(): diff --git a/tensorflow/compiler/tests/random_ops_test.py b/tensorflow/compiler/tests/random_ops_test.py index 36ef6ed5fee..1e913909452 100644 --- a/tensorflow/compiler/tests/random_ops_test.py +++ b/tensorflow/compiler/tests/random_ops_test.py @@ -46,9 +46,9 @@ class RandomOpsTest(xla_test.XLATestCase): # The random-number generator, if working correctly, should produce the # same output multiple times with low probability. - y = sess.run(x) - z = sess.run(x) - w = sess.run(x) + y = self.evaluate(x) + z = self.evaluate(x) + w = self.evaluate(x) # We use exact equality here. If the random-number generator is producing # deterministic output, all three outputs will be bitwise identical. @@ -83,7 +83,7 @@ class RandomOpsTest(xla_test.XLATestCase): with self.test_scope(): x = random_ops.random_uniform( shape=[1000], dtype=dtype, minval=-2, maxval=33) - y = sess.run(x) + y = self.evaluate(x) self.assertTrue((y >= -2).sum() == 1000) self.assertTrue((y < 33).sum() == 1000) @@ -102,7 +102,7 @@ class RandomOpsTest(xla_test.XLATestCase): with self.cached_session() as sess: with self.test_scope(): x = random_ops.truncated_normal(shape=[count], dtype=dtype) - y = sess.run(x) + y = self.evaluate(x) def normal_cdf(x): return .5 * math.erfc(-x / math.sqrt(2)) @@ -148,7 +148,7 @@ class RandomOpsTest(xla_test.XLATestCase): with self.test_scope(): x = math_ops.range(1 << 16) shuffle = random_ops.random_shuffle(x) - result = sess.run(shuffle) + result = self.evaluate(shuffle) expected = range(1 << 16) # Compare sets to avoid randomness behavior changes but make sure still # have all the values. @@ -159,7 +159,7 @@ class RandomOpsTest(xla_test.XLATestCase): with self.test_scope(): x = array_ops.diag(math_ops.range(20)) shuffle = random_ops.random_shuffle(x) - result = sess.run(shuffle) + result = self.evaluate(shuffle) expected = np.diag(range(20)).flatten() # Compare sets to avoid randomness behavior changes but make sure still # have all the values. diff --git a/tensorflow/compiler/tests/tensor_array_ops_test.py b/tensorflow/compiler/tests/tensor_array_ops_test.py index c8208adb587..d7e26d79c4c 100644 --- a/tensorflow/compiler/tests/tensor_array_ops_test.py +++ b/tensorflow/compiler/tests/tensor_array_ops_test.py @@ -505,7 +505,7 @@ class TensorArrayTest(xla_test.XLATestCase): [-0.5, 1.5], # read(0) gradient [20.0, 30.0, 40.0, 50.0], # concat gradient ]) - grad_vals = sess.run(grad_r) # 2 + 2 entries + grad_vals = self.evaluate(grad_r) # 2 + 2 entries self.assertAllClose([2.0 - 0.5 + 20.0, 3.0 + 1.5 + 30.0], grad_vals[0]) self.assertAllEqual([4.0 + 40.0, 5.0 + 50.0], grad_vals[1]) diff --git a/tensorflow/compiler/tests/variable_ops_test.py b/tensorflow/compiler/tests/variable_ops_test.py index 77cdeac8168..e776c8a951c 100644 --- a/tensorflow/compiler/tests/variable_ops_test.py +++ b/tensorflow/compiler/tests/variable_ops_test.py @@ -229,7 +229,7 @@ class VariableOpsTest(xla_test.XLATestCase): resource_variable_ops.resource_scatter_add( handle, [0], constant_op.constant([[2]], dtype=dtypes.int32))) read = resource_variable_ops.read_variable_op(handle, dtype=dtypes.int32) - self.assertAllEqual(sess.run(read), [[3], [7]]) + self.assertAllEqual(self.evaluate(read), [[3], [7]]) def testScatterSub(self): with self.test_session() as sess, self.test_scope(): @@ -242,7 +242,7 @@ class VariableOpsTest(xla_test.XLATestCase): resource_variable_ops.resource_scatter_sub( handle, [1], constant_op.constant([[2]], dtype=dtypes.int32))) read = resource_variable_ops.read_variable_op(handle, dtype=dtypes.int32) - self.assertAllEqual(sess.run(read), [[4], [-1]]) + self.assertAllEqual(self.evaluate(read), [[4], [-1]]) def testScatterMul(self): with self.test_session() as sess, self.test_scope(): @@ -255,7 +255,7 @@ class VariableOpsTest(xla_test.XLATestCase): resource_variable_ops.resource_scatter_mul( handle, [0], constant_op.constant([[5]], dtype=dtypes.int32))) read = resource_variable_ops.read_variable_op(handle, dtype=dtypes.int32) - self.assertEqual(sess.run(read), [[5]]) + self.assertEqual(self.evaluate(read), [[5]]) def testScatterDiv(self): with self.test_session() as sess, self.test_scope(): @@ -268,7 +268,7 @@ class VariableOpsTest(xla_test.XLATestCase): resource_variable_ops.resource_scatter_div( handle, [0], constant_op.constant([[3]], dtype=dtypes.int32))) read = resource_variable_ops.read_variable_op(handle, dtype=dtypes.int32) - self.assertAllEqual(sess.run(read), [[2]]) + self.assertAllEqual(self.evaluate(read), [[2]]) def testScatterMin(self): with self.test_session() as sess, self.test_scope(): @@ -281,7 +281,7 @@ class VariableOpsTest(xla_test.XLATestCase): resource_variable_ops.resource_scatter_min( handle, [0], constant_op.constant([[3]], dtype=dtypes.int32))) read = resource_variable_ops.read_variable_op(handle, dtype=dtypes.int32) - self.assertEqual(sess.run(read), [[3]]) + self.assertEqual(self.evaluate(read), [[3]]) def testScatterMax(self): with self.test_session() as sess, self.test_scope(): @@ -294,7 +294,7 @@ class VariableOpsTest(xla_test.XLATestCase): resource_variable_ops.resource_scatter_max( handle, [0], constant_op.constant([[3]], dtype=dtypes.int32))) read = resource_variable_ops.read_variable_op(handle, dtype=dtypes.int32) - self.assertEqual(sess.run(read), [[6]]) + self.assertEqual(self.evaluate(read), [[6]]) def testScatterUpdate(self): with self.test_session() as sess, self.test_scope(): @@ -307,7 +307,7 @@ class VariableOpsTest(xla_test.XLATestCase): resource_variable_ops.resource_scatter_update( handle, [0], constant_op.constant([[3]], dtype=dtypes.int32))) read = resource_variable_ops.read_variable_op(handle, dtype=dtypes.int32) - self.assertEqual(sess.run(read), [[3]]) + self.assertEqual(self.evaluate(read), [[3]]) def testScatterAddScalar(self): with self.test_session() as sess, self.test_scope(): @@ -320,7 +320,7 @@ class VariableOpsTest(xla_test.XLATestCase): resource_variable_ops.resource_scatter_add( handle, [0], constant_op.constant(2, dtype=dtypes.int32))) read = resource_variable_ops.read_variable_op(handle, dtype=dtypes.int32) - self.assertEqual(sess.run(read), [[3]]) + self.assertEqual(self.evaluate(read), [[3]]) def testScatterSubScalar(self): with self.test_session() as sess, self.test_scope(): @@ -333,7 +333,7 @@ class VariableOpsTest(xla_test.XLATestCase): resource_variable_ops.resource_scatter_sub( handle, [0], constant_op.constant(2, dtype=dtypes.int32))) read = resource_variable_ops.read_variable_op(handle, dtype=dtypes.int32) - self.assertEqual(sess.run(read), [[-1]]) + self.assertEqual(self.evaluate(read), [[-1]]) def testScatterMulScalar(self): with self.test_session() as sess, self.test_scope(): @@ -346,7 +346,7 @@ class VariableOpsTest(xla_test.XLATestCase): resource_variable_ops.resource_scatter_mul( handle, [0], constant_op.constant(5, dtype=dtypes.int32))) read = resource_variable_ops.read_variable_op(handle, dtype=dtypes.int32) - self.assertEqual(sess.run(read), [[5]]) + self.assertEqual(self.evaluate(read), [[5]]) def testScatterDivScalar(self): with self.test_session() as sess, self.test_scope(): @@ -359,7 +359,7 @@ class VariableOpsTest(xla_test.XLATestCase): resource_variable_ops.resource_scatter_div( handle, [0], constant_op.constant(3, dtype=dtypes.int32))) read = resource_variable_ops.read_variable_op(handle, dtype=dtypes.int32) - self.assertEqual(sess.run(read), [[2]]) + self.assertEqual(self.evaluate(read), [[2]]) def testScatterMinScalar(self): with self.test_session() as sess, self.test_scope(): @@ -372,7 +372,7 @@ class VariableOpsTest(xla_test.XLATestCase): resource_variable_ops.resource_scatter_min( handle, [0], constant_op.constant(3, dtype=dtypes.int32))) read = resource_variable_ops.read_variable_op(handle, dtype=dtypes.int32) - self.assertEqual(sess.run(read), [[3]]) + self.assertEqual(self.evaluate(read), [[3]]) def testScatterMaxScalar(self): with self.test_session() as sess, self.test_scope(): @@ -385,7 +385,7 @@ class VariableOpsTest(xla_test.XLATestCase): resource_variable_ops.resource_scatter_max( handle, [0], constant_op.constant(3, dtype=dtypes.int32))) read = resource_variable_ops.read_variable_op(handle, dtype=dtypes.int32) - self.assertEqual(sess.run(read), [[6]]) + self.assertEqual(self.evaluate(read), [[6]]) def testScatterNdAddOps(self): with self.test_session() as sess, self.test_scope(): @@ -400,7 +400,7 @@ class VariableOpsTest(xla_test.XLATestCase): sess.run(gen_state_ops.resource_scatter_nd_add(handle, indices, updates)) read = resource_variable_ops.read_variable_op( handle, dtype=dtypes.float32) - self.assertAllClose(expected, sess.run(read)) + self.assertAllClose(expected, self.evaluate(read)) def testScatterNdUpdateAddOps(self): with self.test_session() as sess, self.test_scope(): @@ -416,7 +416,7 @@ class VariableOpsTest(xla_test.XLATestCase): gen_state_ops.resource_scatter_nd_update(handle, indices, updates)) read = resource_variable_ops.read_variable_op( handle, dtype=dtypes.float32) - self.assertAllClose(expected, sess.run(read)) + self.assertAllClose(expected, self.evaluate(read)) class StridedSliceAssignChecker(object): diff --git a/tensorflow/examples/autograph/integration_tests/keras_test.py b/tensorflow/examples/autograph/integration_tests/keras_test.py index dca7c07b470..9828ac34dc9 100644 --- a/tensorflow/examples/autograph/integration_tests/keras_test.py +++ b/tensorflow/examples/autograph/integration_tests/keras_test.py @@ -96,7 +96,7 @@ class KerasTest(tf.test.TestCase): sess.run(init) sample_input = tf.random_uniform((1, 10, 10, 1)) output = model(sample_input) # pylint: disable=not-callable - self.assertEqual(sess.run(output).shape, (1, 3)) + self.assertEqual(self.evaluate(output).shape, (1, 3)) if __name__ == '__main__': diff --git a/tensorflow/examples/autograph/integration_tests/list_literals_test.py b/tensorflow/examples/autograph/integration_tests/list_literals_test.py index 917f5ff9d84..e85d4abcfc9 100644 --- a/tensorflow/examples/autograph/integration_tests/list_literals_test.py +++ b/tensorflow/examples/autograph/integration_tests/list_literals_test.py @@ -34,7 +34,7 @@ class ListLiteralsTest(tf.test.TestCase): result = converted() with self.cached_session() as sess: - self.assertAllEqual(sess.run(result), [1, 2, 3]) + self.assertAllEqual(self.evaluate(result), [1, 2, 3]) if __name__ == '__main__': diff --git a/tensorflow/examples/speech_commands/input_data_test.py b/tensorflow/examples/speech_commands/input_data_test.py index b766ba6de0d..33b58b9d09b 100644 --- a/tensorflow/examples/speech_commands/input_data_test.py +++ b/tensorflow/examples/speech_commands/input_data_test.py @@ -35,7 +35,7 @@ class InputDataTest(test.TestCase): with self.cached_session() as sess: sample_data = tf.zeros([32000, 2]) wav_encoder = contrib_audio.encode_wav(sample_data, 16000) - wav_data = sess.run(wav_encoder) + wav_data = self.evaluate(wav_encoder) return wav_data def _saveTestWavFile(self, filename, wav_data): diff --git a/tensorflow/examples/speech_commands/label_wav_test.py b/tensorflow/examples/speech_commands/label_wav_test.py index f0af2a47987..77a88f98e16 100644 --- a/tensorflow/examples/speech_commands/label_wav_test.py +++ b/tensorflow/examples/speech_commands/label_wav_test.py @@ -33,7 +33,7 @@ class LabelWavTest(test.TestCase): with self.cached_session() as sess: sample_data = tf.zeros([1000, 2]) wav_encoder = contrib_audio.encode_wav(sample_data, 16000) - wav_data = sess.run(wav_encoder) + wav_data = self.evaluate(wav_encoder) return wav_data def _saveTestWavFile(self, filename, wav_data): diff --git a/tensorflow/examples/speech_commands/wav_to_features_test.py b/tensorflow/examples/speech_commands/wav_to_features_test.py index 87f29876939..cb8ea912fa2 100644 --- a/tensorflow/examples/speech_commands/wav_to_features_test.py +++ b/tensorflow/examples/speech_commands/wav_to_features_test.py @@ -33,7 +33,7 @@ class WavToFeaturesTest(test.TestCase): with self.cached_session() as sess: sample_data = tf.zeros([32000, 2]) wav_encoder = contrib_audio.encode_wav(sample_data, 16000) - wav_data = sess.run(wav_encoder) + wav_data = self.evaluate(wav_encoder) return wav_data def _saveTestWavFile(self, filename, wav_data): diff --git a/tensorflow/python/autograph/converters/call_trees_test.py b/tensorflow/python/autograph/converters/call_trees_test.py index 916c736fb4b..892f90e350c 100644 --- a/tensorflow/python/autograph/converters/call_trees_test.py +++ b/tensorflow/python/autograph/converters/call_trees_test.py @@ -113,7 +113,7 @@ class CallTreesTest(converter_testing.TestCase): with self.compiled(node, ns) as result: with self.cached_session() as sess: result_tensor = result.test_fn(constant_op.constant(1)) - self.assertEquals(sess.run(result_tensor), 3) + self.assertEquals(self.evaluate(result_tensor), 3) def test_call_to_decorated_function(self): diff --git a/tensorflow/python/autograph/converters/lists_test.py b/tensorflow/python/autograph/converters/lists_test.py index f6da845fcc3..8c8135acefb 100644 --- a/tensorflow/python/autograph/converters/lists_test.py +++ b/tensorflow/python/autograph/converters/lists_test.py @@ -68,7 +68,7 @@ class ListTest(converter_testing.TestCase): with self.cached_session() as sess: tl = result.test_fn() r = list_ops.tensor_list_stack(tl, dtypes.int32) - self.assertAllEqual(sess.run(r), [1, 2, 3]) + self.assertAllEqual(self.evaluate(r), [1, 2, 3]) def test_list_pop(self): @@ -91,8 +91,8 @@ class ListTest(converter_testing.TestCase): with self.cached_session() as sess: ts, tl = result.test_fn() r = list_ops.tensor_list_stack(tl, dtypes.int32) - self.assertAllEqual(sess.run(r), [1, 2]) - self.assertAllEqual(sess.run(ts), 3) + self.assertAllEqual(self.evaluate(r), [1, 2]) + self.assertAllEqual(self.evaluate(ts), 3) def test_double_list_pop(self): diff --git a/tensorflow/python/autograph/converters/side_effect_guards_test.py b/tensorflow/python/autograph/converters/side_effect_guards_test.py index cef3199169c..e72b5eac324 100644 --- a/tensorflow/python/autograph/converters/side_effect_guards_test.py +++ b/tensorflow/python/autograph/converters/side_effect_guards_test.py @@ -48,12 +48,12 @@ class SideEffectGuardsTest(converter_testing.TestCase): with self.compiled(node, {}, state_ops.assign) as result: with self.cached_session() as sess: v = variable_scope.get_variable('test', initializer=2) - sess.run(v.initializer) + self.evaluate(v.initializer) sess.run(result.test_fn(v)) # TODO(mdan): Add support for this use case. # Right now the variable `a` is not conditioned on the `assign` because # there's no way to add control dependencies to a variable object. - self.assertEqual(2, sess.run(v)) + self.assertEqual(2, self.evaluate(v)) def test_side_effect_on_used_variable(self): @@ -69,11 +69,11 @@ class SideEffectGuardsTest(converter_testing.TestCase): with self.compiled(node, {}, state_ops.assign) as result: with self.cached_session() as sess: v = variable_scope.get_variable('test', initializer=2) - sess.run(v.initializer) + self.evaluate(v.initializer) sess.run(result.test_fn(v)) # TODO(mdan): Ensure the result of test_fn(v) is also deterministic. # Right now it's 3 or 4 based on whether the read is synchronized. - self.assertEqual(3, sess.run(v)) + self.assertEqual(3, self.evaluate(v)) def test_side_effect_on_tensor(self): @@ -109,10 +109,10 @@ class SideEffectGuardsTest(converter_testing.TestCase): with self.compiled(node, {}, state_ops.assign_add) as result: with self.cached_session() as sess: v = variable_scope.get_variable('test', initializer=2) - sess.run(v.initializer) + self.evaluate(v.initializer) sess.run(result.test_fn(v)) # TODO(mdan): Ensure the result of test_fn(v) is also deterministic. - self.assertEqual(4, sess.run(v)) + self.assertEqual(4, self.evaluate(v)) def test_multiline_nested_block(self): @@ -130,10 +130,10 @@ class SideEffectGuardsTest(converter_testing.TestCase): with self.compiled(node, {}, state_ops.assign, ops.name_scope) as result: with self.cached_session() as sess: v = variable_scope.get_variable('test', initializer=2) - sess.run(v.initializer) + self.evaluate(v.initializer) sess.run(result.test_fn(v)) # TODO(mdan): Ensure the result of test_fn(v) is also deterministic. - self.assertEqual(3, sess.run(v)) + self.assertEqual(3, self.evaluate(v)) def test_multiline_block_unsafe(self): @@ -153,10 +153,10 @@ class SideEffectGuardsTest(converter_testing.TestCase): state_ops.assign_add) as result: with self.cached_session() as sess: v = variable_scope.get_variable('test', initializer=2) - sess.run(v.initializer) + self.evaluate(v.initializer) sess.run(result.test_fn(v)) # TODO(mdan): Ensure the result of test_fn(v) is also deterministic. - self.assertEqual(4, sess.run(v)) + self.assertEqual(4, self.evaluate(v)) if __name__ == '__main__': diff --git a/tensorflow/python/autograph/converters/slices_test.py b/tensorflow/python/autograph/converters/slices_test.py index e190a7cfe84..bd049afdfce 100644 --- a/tensorflow/python/autograph/converters/slices_test.py +++ b/tensorflow/python/autograph/converters/slices_test.py @@ -49,7 +49,7 @@ class SliceTest(converter_testing.TestCase): tl = list_ops.tensor_list_from_tensor( [1, 2], element_shape=constant_op.constant([], dtype=dtypes.int32)) y = result.test_fn(tl) - self.assertEqual(2, sess.run(y)) + self.assertEqual(2, self.evaluate(y)) def test_index_access_multiple_definitions(self): diff --git a/tensorflow/python/autograph/impl/api_test.py b/tensorflow/python/autograph/impl/api_test.py index ef577568c4e..44cb99d657f 100644 --- a/tensorflow/python/autograph/impl/api_test.py +++ b/tensorflow/python/autograph/impl/api_test.py @@ -63,7 +63,7 @@ class ApiTest(test.TestCase): x = tc.test_method( constant_op.constant([2, 4]), constant_op.constant(1), constant_op.constant(-2)) - self.assertListEqual([0, 1], sess.run(x).tolist()) + self.assertListEqual([0, 1], self.evaluate(x).tolist()) def test_decorator_does_not_recurse(self): @@ -83,7 +83,7 @@ class ApiTest(test.TestCase): x = tc.test_method( constant_op.constant([2, 4]), constant_op.constant(1), constant_op.constant(-2)) - self.assertListEqual([0, 1], sess.run(x).tolist()) + self.assertListEqual([0, 1], self.evaluate(x).tolist()) def test_decorator_calls_unconverted_graph(self): @@ -104,7 +104,7 @@ class ApiTest(test.TestCase): x = tc.test_method( constant_op.constant([2, 4]), constant_op.constant(1), constant_op.constant(-2)) - self.assertListEqual([0, 1], sess.run(x).tolist()) + self.assertListEqual([0, 1], self.evaluate(x).tolist()) def test_decorator_calls_unconverted_py_func(self): @@ -130,7 +130,7 @@ class ApiTest(test.TestCase): x = tc.test_method( constant_op.constant([2, 4]), constant_op.constant(1), constant_op.constant(-2)) - self.assertListEqual([0, 1], sess.run(x).tolist()) + self.assertListEqual([0, 1], self.evaluate(x).tolist()) def test_decorator_calls_decorated(self): @@ -153,7 +153,7 @@ class ApiTest(test.TestCase): x = tc.test_method( constant_op.constant([2, 4]), constant_op.constant(1), constant_op.constant(-2)) - self.assertListEqual([0, 1], sess.run(x).tolist()) + self.assertListEqual([0, 1], self.evaluate(x).tolist()) def test_decorator_preserves_argspec(self): @@ -192,7 +192,7 @@ class ApiTest(test.TestCase): x = tc.test_method( constant_op.constant([2, 4]), constant_op.constant(1), constant_op.constant(-2)) - self.assertListEqual([0, 1], sess.run(x).tolist()) + self.assertListEqual([0, 1], self.evaluate(x).tolist()) def test_converted_call_builtin(self): x = api.converted_call(range, None, converter.ConversionOptions(), 3) @@ -208,7 +208,7 @@ class ApiTest(test.TestCase): with self.cached_session() as sess: x = api.converted_call(test_fn, None, converter.ConversionOptions(), constant_op.constant(-1)) - self.assertEqual(1, sess.run(x)) + self.assertEqual(1, self.evaluate(x)) def test_converted_call_method_explicit_owner(self): # TODO(mdan): Implement. @@ -234,7 +234,7 @@ class ApiTest(test.TestCase): tc = TestClass(constant_op.constant(-1)) x = api.converted_call(tc.test_method, None, converter.ConversionOptions(), tc) - self.assertEqual(1, sess.run(x)) + self.assertEqual(1, self.evaluate(x)) def test_converted_call_method_by_class(self): @@ -252,7 +252,7 @@ class ApiTest(test.TestCase): tc = TestClass(constant_op.constant(-1)) x = api.converted_call(TestClass.test_method, None, converter.ConversionOptions(), tc) - self.assertEqual(1, sess.run(x)) + self.assertEqual(1, self.evaluate(x)) def test_converted_call_callable_object(self): @@ -269,7 +269,7 @@ class ApiTest(test.TestCase): with self.cached_session() as sess: tc = TestClass(constant_op.constant(-1)) x = api.converted_call(tc, None, converter.ConversionOptions()) - self.assertEqual(1, sess.run(x)) + self.assertEqual(1, self.evaluate(x)) def test_converted_call_constructor(self): @@ -288,7 +288,7 @@ class ApiTest(test.TestCase): constant_op.constant(-1)) # tc is now a converted object. x = tc.test_method() - self.assertEqual(1, sess.run(x)) + self.assertEqual(1, self.evaluate(x)) def test_converted_call_already_converted(self): @@ -298,12 +298,12 @@ class ApiTest(test.TestCase): with self.cached_session() as sess: x = api.converted_call(f, None, converter.ConversionOptions(), constant_op.constant(0)) - self.assertTrue(sess.run(x)) + self.assertTrue(self.evaluate(x)) converted_f = api.to_graph(f) x = api.converted_call(converted_f, None, converter.ConversionOptions(), constant_op.constant(0)) - self.assertTrue(sess.run(x)) + self.assertTrue(self.evaluate(x)) def test_converted_call_no_user_code(self): @@ -334,8 +334,8 @@ class ApiTest(test.TestCase): constant_op.constant([[0.0]]), training=True) with self.cached_session() as sess: - sess.run(variables.global_variables_initializer()) - self.assertAllEqual([[0.0, 0.0]], sess.run(x)) + self.evaluate(variables.global_variables_initializer()) + self.assertAllEqual([[0.0, 0.0]], self.evaluate(x)) def test_converted_call_whitelisted_method_extra_self(self): @@ -349,8 +349,8 @@ class ApiTest(test.TestCase): model, constant_op.constant([[0.0]]), training=True) with self.cached_session() as sess: - sess.run(variables.global_variables_initializer()) - self.assertAllEqual([[0.0, 0.0]], sess.run(x)) + self.evaluate(variables.global_variables_initializer()) + self.assertAllEqual([[0.0, 0.0]], self.evaluate(x)) def test_converted_call_whitelisted_method_via_owner(self): @@ -364,8 +364,8 @@ class ApiTest(test.TestCase): constant_op.constant([[0.0]]), training=True) with self.cached_session() as sess: - sess.run(variables.global_variables_initializer()) - self.assertAllEqual([[0.0, 0.0]], sess.run(x)) + self.evaluate(variables.global_variables_initializer()) + self.assertAllEqual([[0.0, 0.0]], self.evaluate(x)) def test_converted_call_lambda(self): @@ -376,8 +376,8 @@ class ApiTest(test.TestCase): x = api.converted_call(l, None, opts, constant_op.constant(0)) with self.cached_session() as sess: - sess.run(variables.global_variables_initializer()) - self.assertAllEqual(True, sess.run(x)) + self.evaluate(variables.global_variables_initializer()) + self.assertAllEqual(True, self.evaluate(x)) def test_to_graph_basic(self): @@ -390,7 +390,7 @@ class ApiTest(test.TestCase): with self.cached_session() as sess: x = compiled_fn(constant_op.constant([4, 8]), 4) - self.assertListEqual([1, 2], sess.run(x).tolist()) + self.assertListEqual([1, 2], self.evaluate(x).tolist()) def test_to_graph_with_defaults(self): @@ -405,7 +405,7 @@ class ApiTest(test.TestCase): with self.cached_session() as sess: x = compiled_fn(constant_op.constant([4, 8])) - self.assertListEqual([1, 2], sess.run(x).tolist()) + self.assertListEqual([1, 2], self.evaluate(x).tolist()) def test_to_code_basic(self): diff --git a/tensorflow/python/autograph/lang/special_functions_test.py b/tensorflow/python/autograph/lang/special_functions_test.py index 123ee65b326..8d40f4036c5 100644 --- a/tensorflow/python/autograph/lang/special_functions_test.py +++ b/tensorflow/python/autograph/lang/special_functions_test.py @@ -36,7 +36,7 @@ class SpecialFunctionsTest(test.TestCase): python_one = special_functions.match_staging_level(1, 1) with self.cached_session() as sess: self.assertTrue(tensor_util.is_tensor(tensor_one)) - self.assertAllEqual(sess.run(tensor_one), 1) + self.assertAllEqual(self.evaluate(tensor_one), 1) self.assertEqual(python_one, 1) def test_tensor_list_empty_list(self): @@ -45,21 +45,21 @@ class SpecialFunctionsTest(test.TestCase): element_shape=()) sl = list_ops.tensor_list_stack(l, element_dtype=dtypes.int32) with self.cached_session() as sess: - self.assertAllEqual(sess.run(sl), []) + self.assertAllEqual(self.evaluate(sl), []) l = special_functions.tensor_list((), element_dtype=dtypes.int32, element_shape=()) sl = list_ops.tensor_list_stack(l, element_dtype=dtypes.int32) with self.cached_session() as sess: - self.assertAllEqual(sess.run(sl), []) + self.assertAllEqual(self.evaluate(sl), []) def test_tensor_list_tensor(self): l = special_functions.tensor_list( constant_op.constant([], dtype=dtypes.int32)) sl = list_ops.tensor_list_stack(l, element_dtype=dtypes.int32) with self.cached_session() as sess: - self.assertAllEqual(sess.run(sl), []) + self.assertAllEqual(self.evaluate(sl), []) def test_tensor_list_unsupported_initializer(self): with self.assertRaisesRegexp(ValueError, 'unknown type'): @@ -76,7 +76,7 @@ class SpecialFunctionsTest(test.TestCase): l = special_functions.tensor_list(elements) sl = list_ops.tensor_list_stack(l, element_dtype=dtypes.int32) with self.cached_session() as sess: - self.assertAllEqual(sess.run(sl), [[1, 2], [3, 4]]) + self.assertAllEqual(self.evaluate(sl), [[1, 2], [3, 4]]) def test_tensor_list_array_from_elements(self): elements = [constant_op.constant([1, 2]), constant_op.constant([3, 4])] @@ -84,7 +84,7 @@ class SpecialFunctionsTest(test.TestCase): l = special_functions.tensor_list(elements, use_tensor_array=True) sl = l.stack() with self.cached_session() as sess: - self.assertAllEqual(sess.run(sl), [[1, 2], [3, 4]]) + self.assertAllEqual(self.evaluate(sl), [[1, 2], [3, 4]]) def test_stack(self): self.assertEqual(special_functions.stack(1, strict=False), 1) diff --git a/tensorflow/python/autograph/operators/control_flow_test.py b/tensorflow/python/autograph/operators/control_flow_test.py index 2dea18dc5fa..05b5660941d 100644 --- a/tensorflow/python/autograph/operators/control_flow_test.py +++ b/tensorflow/python/autograph/operators/control_flow_test.py @@ -35,7 +35,7 @@ class ForLoopTest(test.TestCase): body=lambda i, s: (s + i,), init_state=(0,)) with self.cached_session() as sess: - self.assertEqual((10,), sess.run(s)) + self.assertEqual((10,), self.evaluate(s)) def test_python(self): s = control_flow.for_stmt( @@ -53,7 +53,7 @@ class ForLoopTest(test.TestCase): body=lambda i, s: (s + i,), init_state=(0,)) with self.cached_session() as sess: - self.assertEqual((10,), sess.run(s)) + self.assertEqual((10,), self.evaluate(s)) class WhileLoopTest(test.TestCase): @@ -66,7 +66,7 @@ class WhileLoopTest(test.TestCase): init_state=(0, 0), extra_deps=(n,)) with self.cached_session() as sess: - self.assertEqual((5, 10), sess.run(results)) + self.assertEqual((5, 10), self.evaluate(results)) def test_python(self): n = 5 @@ -90,9 +90,9 @@ class IfStmtTest(test.TestCase): def test_tensor(self): with self.cached_session() as sess: t = self.single_return_if_stmt(constant_op.constant(True)) - self.assertEqual(1, sess.run(t)) + self.assertEqual(1, self.evaluate(t)) t = self.single_return_if_stmt(constant_op.constant(False)) - self.assertEqual(-1, sess.run(t)) + self.assertEqual(-1, self.evaluate(t)) def test_python(self): self.assertEqual(1, self.single_return_if_stmt(True)) @@ -101,9 +101,9 @@ class IfStmtTest(test.TestCase): def test_tensor_multiple_returns(self): with self.cached_session() as sess: t = self.multi_return_if_stmt(constant_op.constant(True)) - self.assertAllEqual([1, 2], sess.run(t)) + self.assertAllEqual([1, 2], self.evaluate(t)) t = self.multi_return_if_stmt(constant_op.constant(False)) - self.assertAllEqual([-1, -2], sess.run(t)) + self.assertAllEqual([-1, -2], self.evaluate(t)) def test_python_multiple_returns(self): self.assertEqual((1, 2), self.multi_return_if_stmt(True)) diff --git a/tensorflow/python/autograph/operators/data_structures_test.py b/tensorflow/python/autograph/operators/data_structures_test.py index 72476ccb6bf..dc50edb4c98 100644 --- a/tensorflow/python/autograph/operators/data_structures_test.py +++ b/tensorflow/python/autograph/operators/data_structures_test.py @@ -43,7 +43,7 @@ class ListTest(test.TestCase): l = data_structures.tf_tensor_list_new([3, 4, 5]) t = list_ops.tensor_list_stack(l, element_dtype=dtypes.int32) with self.cached_session() as sess: - self.assertAllEqual(sess.run(t), [3, 4, 5]) + self.assertAllEqual(self.evaluate(t), [3, 4, 5]) def test_tf_tensor_list_new_empty(self): l = data_structures.tf_tensor_list_new([], @@ -51,13 +51,13 @@ class ListTest(test.TestCase): element_shape=()) t = list_ops.tensor_list_stack(l, element_dtype=dtypes.int32) with self.cached_session() as sess: - self.assertAllEqual(sess.run(t), []) + self.assertAllEqual(self.evaluate(t), []) def test_tf_tensor_list_new_from_tensor(self): l = data_structures.tf_tensor_list_new(constant_op.constant([3, 4, 5])) t = list_ops.tensor_list_stack(l, element_dtype=dtypes.int32) with self.cached_session() as sess: - self.assertAllEqual(sess.run(t), [3, 4, 5]) + self.assertAllEqual(self.evaluate(t), [3, 4, 5]) def test_tf_tensor_list_new_illegal_input(self): with self.assertRaises(ValueError): @@ -77,7 +77,7 @@ class ListTest(test.TestCase): l = data_structures.tf_tensor_array_new([3, 4, 5]) t = l.stack() with self.cached_session() as sess: - self.assertAllEqual(sess.run(t), [3, 4, 5]) + self.assertAllEqual(self.evaluate(t), [3, 4, 5]) def test_tf_tensor_array_new_illegal_input(self): with self.assertRaises(ValueError): @@ -102,7 +102,7 @@ class ListTest(test.TestCase): t = list_ops.tensor_list_stack(l, element_dtype=x.dtype) with self.cached_session() as sess: - self.assertAllEqual(sess.run(t), [[1, 2, 3]]) + self.assertAllEqual(self.evaluate(t), [[1, 2, 3]]) def test_append_tensorarray(self): l = tensor_array_ops.TensorArray(dtypes.int32, size=0, dynamic_size=True) @@ -131,10 +131,10 @@ class ListTest(test.TestCase): with self.cached_session() as sess: l, x = data_structures.list_pop(l, None, opts) - self.assertAllEqual(sess.run(x), [3, 4]) + self.assertAllEqual(self.evaluate(x), [3, 4]) t = list_ops.tensor_list_stack(l, element_dtype=initial_list.dtype) - self.assertAllEqual(sess.run(t), [[1, 2]]) + self.assertAllEqual(self.evaluate(t), [[1, 2]]) def test_pop_python(self): l = [1, 2, 3] @@ -152,7 +152,7 @@ class ListTest(test.TestCase): with self.cached_session() as sess: t = data_structures.list_stack(l, opts) - self.assertAllEqual(sess.run(t), sess.run(initial_list)) + self.assertAllEqual(sess.run(t), self.evaluate(initial_list)) def test_stack_tensor_list_empty(self): l = list_ops.empty_tensor_list( diff --git a/tensorflow/python/autograph/operators/logical_test.py b/tensorflow/python/autograph/operators/logical_test.py index d6649f7b2bf..ebf6458f01e 100644 --- a/tensorflow/python/autograph/operators/logical_test.py +++ b/tensorflow/python/autograph/operators/logical_test.py @@ -45,11 +45,11 @@ class LogicalOperatorsTest(test.TestCase): def test_and_tf(self): with self.cached_session() as sess: t = logical.and_(self._tf_true, self._tf_true) - self.assertEqual(sess.run(t), True) + self.assertEqual(self.evaluate(t), True) t = logical.and_(self._tf_true, lambda: True) - self.assertEqual(sess.run(t), True) + self.assertEqual(self.evaluate(t), True) t = logical.and_(self._tf_false, lambda: True) - self.assertEqual(sess.run(t), False) + self.assertEqual(self.evaluate(t), False) # TODO(mdan): Add a test for ops with side effects. def test_or_python(self): @@ -63,11 +63,11 @@ class LogicalOperatorsTest(test.TestCase): def test_or_tf(self): with self.cached_session() as sess: t = logical.or_(self._tf_false, self._tf_true) - self.assertEqual(sess.run(t), True) + self.assertEqual(self.evaluate(t), True) t = logical.or_(self._tf_false, lambda: True) - self.assertEqual(sess.run(t), True) + self.assertEqual(self.evaluate(t), True) t = logical.or_(self._tf_true, lambda: True) - self.assertEqual(sess.run(t), True) + self.assertEqual(self.evaluate(t), True) # TODO(mdan): Add a test for ops with side effects. def test_not_python(self): @@ -78,7 +78,7 @@ class LogicalOperatorsTest(test.TestCase): def test_not_tf(self): with self.cached_session() as sess: t = logical.not_(self._tf_false()) - self.assertEqual(sess.run(t), True) + self.assertEqual(self.evaluate(t), True) if __name__ == '__main__': diff --git a/tensorflow/python/autograph/operators/py_builtins_test.py b/tensorflow/python/autograph/operators/py_builtins_test.py index 443e30a475d..4d9eec77c38 100644 --- a/tensorflow/python/autograph/operators/py_builtins_test.py +++ b/tensorflow/python/autograph/operators/py_builtins_test.py @@ -38,29 +38,29 @@ class PyBuiltinsTest(test.TestCase): self.assertEqual(py_builtins.abs_(-1), 1) with self.cached_session() as sess: t = py_builtins.abs_(constant_op.constant(-1)) - self.assertEqual(sess.run(t), 1) + self.assertEqual(self.evaluate(t), 1) t = py_builtins.abs_(constant_op.constant([-1, 2, -3])) - self.assertAllEqual(sess.run(t), [1, 2, 3]) + self.assertAllEqual(self.evaluate(t), [1, 2, 3]) def test_float(self): self.assertEqual(py_builtins.float_(10), 10.0) self.assertEqual(py_builtins.float_('10.0'), 10.0) with self.cached_session() as sess: t = py_builtins.float_(constant_op.constant(1, dtype=dtypes.int64)) - self.assertEqual(sess.run(t), 1.0) + self.assertEqual(self.evaluate(t), 1.0) st = py_builtins.float_(constant_op.constant('1.0')) - self.assertEqual(sess.run(st), 1.0) + self.assertEqual(self.evaluate(st), 1.0) def test_int(self): self.assertEqual(py_builtins.int_(10.0), 10) self.assertEqual(py_builtins.int_('11', 2), 3) with self.cached_session() as sess: t = py_builtins.int_(constant_op.constant(1, dtype=dtypes.float64)) - self.assertEqual(sess.run(t), 1) + self.assertEqual(self.evaluate(t), 1) st = py_builtins.int_(constant_op.constant('1')) - self.assertEqual(sess.run(st), 1) + self.assertEqual(self.evaluate(st), 1) st = py_builtins.int_(constant_op.constant('1'), 10) - self.assertEqual(sess.run(st), 1) + self.assertEqual(self.evaluate(st), 1) def test_int_unsupported_base(self): t = constant_op.constant(1, dtype=dtypes.float64) @@ -73,9 +73,9 @@ class PyBuiltinsTest(test.TestCase): t = py_builtins.len_(constant_op.constant([[1], [2], [3]])) self.assertEqual(t, 3) ta = py_builtins.len_(tensor_array_ops.TensorArray(dtypes.int32, size=5)) - self.assertEqual(sess.run(ta), 5) + self.assertEqual(self.evaluate(ta), 5) tl = py_builtins.len_(data_structures.tf_tensor_list_new([3, 4, 5])) - self.assertEqual(sess.run(tl), 3) + self.assertEqual(self.evaluate(tl), 3) def test_len_scalar(self): with self.assertRaises(ValueError): @@ -120,18 +120,18 @@ class PyBuiltinsTest(test.TestCase): def test_range_tensor(self): with self.cached_session() as sess: r = py_builtins.range_(constant_op.constant(3)) - self.assertAllEqual(sess.run(r), [0, 1, 2]) + self.assertAllEqual(self.evaluate(r), [0, 1, 2]) r = py_builtins.range_(1, constant_op.constant(3)) - self.assertAllEqual(sess.run(r), [1, 2]) + self.assertAllEqual(self.evaluate(r), [1, 2]) r = py_builtins.range_(2, 0, constant_op.constant(-1)) - self.assertAllEqual(sess.run(r), [2, 1]) + self.assertAllEqual(self.evaluate(r), [2, 1]) def test_range_tensor_empty_range(self): with self.session() as sess: r = py_builtins.range_(constant_op.constant(-3)) - self.assertAllEqual(sess.run(r), []) + self.assertAllEqual(self.evaluate(r), []) r = py_builtins.range_(5, constant_op.constant(2)) - self.assertAllEqual(sess.run(r), []) + self.assertAllEqual(self.evaluate(r), []) if __name__ == '__main__': diff --git a/tensorflow/python/autograph/operators/slices_test.py b/tensorflow/python/autograph/operators/slices_test.py index 9e4865b3c66..d444054fd77 100644 --- a/tensorflow/python/autograph/operators/slices_test.py +++ b/tensorflow/python/autograph/operators/slices_test.py @@ -34,7 +34,7 @@ class SlicesTest(test.TestCase): with self.cached_session() as sess: t = list_ops.tensor_list_stack(l, element_dtype=initial_list.dtype) - self.assertAllEqual(sess.run(t), [[5, 6], [3, 4]]) + self.assertAllEqual(self.evaluate(t), [[5, 6], [3, 4]]) def test_get_item_tensor_list(self): initial_list = constant_op.constant([[1, 2], [3, 4]]) @@ -44,7 +44,7 @@ class SlicesTest(test.TestCase): l, 1, slices.GetItemOpts(element_dtype=initial_list.dtype)) with self.cached_session() as sess: - self.assertAllEqual(sess.run(t), [3, 4]) + self.assertAllEqual(self.evaluate(t), [3, 4]) def test_get_item_tensor_string(self): initial_str = constant_op.constant('abcd') @@ -52,14 +52,14 @@ class SlicesTest(test.TestCase): slices.GetItemOpts(element_dtype=initial_str.dtype)) with self.cached_session() as sess: - self.assertEqual(sess.run(t), b'b') + self.assertEqual(self.evaluate(t), b'b') initial_list_str = constant_op.constant(['abcd', 'bcde']) t = slices.get_item(initial_list_str, 1, slices.GetItemOpts(element_dtype=initial_str.dtype)) with self.cached_session() as sess: - self.assertEqual(sess.run(t), b'bcde') + self.assertEqual(self.evaluate(t), b'bcde') if __name__ == '__main__': diff --git a/tensorflow/python/autograph/utils/misc_test.py b/tensorflow/python/autograph/utils/misc_test.py index 8d2b0d6e138..c813e0f5c96 100644 --- a/tensorflow/python/autograph/utils/misc_test.py +++ b/tensorflow/python/autograph/utils/misc_test.py @@ -32,7 +32,7 @@ class MiscTest(test.TestCase): new_a = alias_tensors(a) self.assertFalse(new_a is a) with self.cached_session() as sess: - self.assertEqual(1, sess.run(new_a)) + self.assertEqual(1, self.evaluate(new_a)) def test_alias_tensors(self): a = constant(1) @@ -47,7 +47,7 @@ class MiscTest(test.TestCase): self.assertTrue(new_s is s) self.assertTrue(new_l is l) with self.cached_session() as sess: - self.assertEqual(1, sess.run(new_a)) + self.assertEqual(1, self.evaluate(new_a)) if __name__ == '__main__': diff --git a/tensorflow/python/autograph/utils/py_func_test.py b/tensorflow/python/autograph/utils/py_func_test.py index 1c220d94922..28cefd8c3ed 100644 --- a/tensorflow/python/autograph/utils/py_func_test.py +++ b/tensorflow/python/autograph/utils/py_func_test.py @@ -34,13 +34,13 @@ class PyFuncTest(test.TestCase): with self.cached_session() as sess: result = py_func.wrap_py_func(test_fn, dtypes.int64, (1, constant_op.constant(1), 1)) - self.assertEqual(3, sess.run(result)) + self.assertEqual(3, self.evaluate(result)) result = py_func.wrap_py_func(test_fn, dtypes.int64, (1, 1, 1)) - self.assertEqual(3, sess.run(result)) + self.assertEqual(3, self.evaluate(result)) result = py_func.wrap_py_func( test_fn, dtypes.int64, (constant_op.constant(1), 1, constant_op.constant(1))) - self.assertEqual(3, sess.run(result)) + self.assertEqual(3, self.evaluate(result)) def test_wrap_py_func_complex_args(self): @@ -54,10 +54,10 @@ class PyFuncTest(test.TestCase): with self.cached_session() as sess: result = py_func.wrap_py_func(test_fn, dtypes.int64, (7, TestClass())) - self.assertEqual(35, sess.run(result)) + self.assertEqual(35, self.evaluate(result)) result = py_func.wrap_py_func(test_fn, dtypes.int64, (constant_op.constant(7), TestClass())) - self.assertEqual(35, sess.run(result)) + self.assertEqual(35, self.evaluate(result)) def test_wrap_py_func_kwargs(self): @@ -74,13 +74,13 @@ class PyFuncTest(test.TestCase): 'c': 11, 'd': TestClass(13) }) - self.assertEqual(178, sess.run(result)) + self.assertEqual(178, self.evaluate(result)) result = py_func.wrap_py_func(test_fn, dtypes.int64, (constant_op.constant(7), TestClass(5)), { 'c': constant_op.constant(11), 'd': TestClass(13) }) - self.assertEqual(178, sess.run(result)) + self.assertEqual(178, self.evaluate(result)) def test_wrap_py_func_dummy_return(self): @@ -91,11 +91,11 @@ class PyFuncTest(test.TestCase): with self.cached_session() as sess: result = py_func.wrap_py_func(test_fn, None, (5,), use_dummy_return=True) - self.assertEqual(1, sess.run(result)) + self.assertEqual(1, self.evaluate(result)) self.assertEqual([1], side_counter) result = py_func.wrap_py_func( test_fn, None, (constant_op.constant(5),), use_dummy_return=True) - self.assertEqual(1, sess.run(result)) + self.assertEqual(1, self.evaluate(result)) self.assertEqual([2], side_counter) diff --git a/tensorflow/python/autograph/utils/tensor_list_test.py b/tensorflow/python/autograph/utils/tensor_list_test.py index 697c166eb12..a5bbd97cf92 100644 --- a/tensorflow/python/autograph/utils/tensor_list_test.py +++ b/tensorflow/python/autograph/utils/tensor_list_test.py @@ -43,13 +43,13 @@ class TensorListTest(test.TestCase): l = tl.dynamic_list_append(l, 1) s = list_ops.tensor_list_stack(l, element_dtype=dtypes.int32) with self.cached_session() as sess: - self.assertAllEqual(sess.run(s), [1]) + self.assertAllEqual(self.evaluate(s), [1]) l = tensor_array_ops.TensorArray(dtypes.int32, size=0, dynamic_size=True) l = tl.dynamic_list_append(l, 1) s = l.stack() with self.cached_session() as sess: - self.assertAllEqual(sess.run(s), [1]) + self.assertAllEqual(self.evaluate(s), [1]) l = tl.TensorList(self._shape(()), dtypes.int32) l = tl.dynamic_list_append(l, 1) diff --git a/tensorflow/python/client/session_clusterspec_prop_test.py b/tensorflow/python/client/session_clusterspec_prop_test.py index df020f88a88..224f880ed15 100644 --- a/tensorflow/python/client/session_clusterspec_prop_test.py +++ b/tensorflow/python/client/session_clusterspec_prop_test.py @@ -62,7 +62,7 @@ class SessionClusterSpecPropagationTest(test_util.TensorFlowTestCase): const = constant_op.constant(17) sess = session.Session(server1.target, config=config) - output = sess.run(const) + output = self.evaluate(const) self.assertEqual(17, output) def testClusterSpecPropagationWorker2Placement(self): @@ -106,7 +106,7 @@ class SessionClusterSpecPropagationTest(test_util.TensorFlowTestCase): with ops.Graph().as_default() as g, ops.device('/job:worker/task:0'): const = constant_op.constant(17) sess = session.Session(server1.target, config=config, graph=g) - output = sess.run(const) + output = self.evaluate(const) self.assertEqual(17, output) def testCanonicalDeviceNames(self): @@ -208,7 +208,7 @@ class SessionClusterSpecPropagationTest(test_util.TensorFlowTestCase): with ops.device('/job:worker/task:0/cpu:0'): sum3 = sum1 + sum2 sess = session.Session(server1.target, config=config, graph=g) - output = sess.run(sum3) + output = self.evaluate(sum3) self.assertEqual(40, output) def testLegacyDeviceNames(self): diff --git a/tensorflow/python/client/timeline_test.py b/tensorflow/python/client/timeline_test.py index dfd01476430..f9bd50957a7 100644 --- a/tensorflow/python/client/timeline_test.py +++ b/tensorflow/python/client/timeline_test.py @@ -147,7 +147,7 @@ class TimelineTest(test.TestCase): num2 = variables.Variable(2.0, name='num2') with ops.device('/cpu:2'): result = num1 + num2 + num1 * num2 - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) sess.run(result, options=run_options, run_metadata=run_metadata) self.assertTrue(run_metadata.HasField('step_stats')) @@ -176,7 +176,7 @@ class TimelineTest(test.TestCase): num2 = variables.Variable(2.0, name='num2') with ops.device('/cpu:2'): result = num1 + num2 + num1 * num2 - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) sess.run(result, options=run_options, run_metadata=run_metadata) self.assertTrue(run_metadata.HasField('step_stats')) step_stats = run_metadata.step_stats diff --git a/tensorflow/python/client/virtual_gpu_test.py b/tensorflow/python/client/virtual_gpu_test.py index 5892e0fc845..e82ee0666c3 100644 --- a/tensorflow/python/client/virtual_gpu_test.py +++ b/tensorflow/python/client/virtual_gpu_test.py @@ -216,7 +216,7 @@ class VirtualGpuTest(test_util.TensorFlowTestCase): for d in self._util.devices: with ops.device(d): var = variables.Variable(random_ops.random_uniform(mat_shape)) - sess.run(var.initializer) + self.evaluate(var.initializer) data.append(var) s = data[0] for i in range(1, len(data)): diff --git a/tensorflow/python/data/experimental/kernel_tests/batch_dataset_op_test.py b/tensorflow/python/data/experimental/kernel_tests/batch_dataset_op_test.py index e896752a269..dbb780c47d9 100644 --- a/tensorflow/python/data/experimental/kernel_tests/batch_dataset_op_test.py +++ b/tensorflow/python/data/experimental/kernel_tests/batch_dataset_op_test.py @@ -53,10 +53,10 @@ class BatchDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for start in range(0, len(components), 4): - results = sess.run(get_next) + results = self.evaluate(get_next) self.assertAllEqual([[i, j] for i, c in enumerate(components[start:start + 4]) for j in range(c)], results.indices) @@ -81,10 +81,10 @@ class BatchDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for start in range(0, len(components), 4): - results = sess.run(get_next) + results = self.evaluate(get_next) self.assertAllEqual([[i, j, z] for i, c in enumerate(components[start:start + 4]) for j in range(c) @@ -141,7 +141,7 @@ class BatchDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): with self.cached_session() as sess: sess.run(iterator.initializer, feed_dict={placeholder: [0, 1, 2, 3]}) for i in range(4): - self.assertEqual(i, sess.run(next_elem)) + self.assertEqual(i, self.evaluate(next_elem)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_elem) @@ -159,7 +159,7 @@ class BatchDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): with self.cached_session() as sess: for i in range(10): - self.assertEqual((i,) * 3, sess.run(op)) + self.assertEqual((i,) * 3, self.evaluate(op)) with self.assertRaises(errors.OutOfRangeError): sess.run(op) @@ -179,7 +179,7 @@ class BatchDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): with self.cached_session() as sess: for i in range(10): - self.assertEqual((i, compat.as_bytes(str(i)), i), sess.run(op)) + self.assertEqual((i, compat.as_bytes(str(i)), i), self.evaluate(op)) with self.assertRaises(errors.OutOfRangeError): sess.run(op) @@ -198,7 +198,7 @@ class BatchDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): with self.cached_session() as sess: for i in range(10): - st_row = sess.run(next_element) + st_row = self.evaluate(next_element) self.assertEqual([i], st_row.indices) self.assertEqual([i], st_row.values) self.assertEqual([10], st_row.dense_shape) @@ -219,7 +219,7 @@ class BatchDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): with self.cached_session() as sess: for i in range(10): - dense_elem, st_row = sess.run(next_element) + dense_elem, st_row = self.evaluate(next_element) self.assertEqual(i, dense_elem) self.assertEqual([i], st_row.indices) self.assertEqual([i], st_row.values) @@ -241,7 +241,7 @@ class BatchDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): with self.cached_session() as sess: for i in range(10): - self.assertEqual(((i,),) * 3, sess.run(op)) + self.assertEqual(((i,),) * 3, self.evaluate(op)) with self.assertRaises(errors.OutOfRangeError): sess.run(op) @@ -354,7 +354,7 @@ class BatchDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): sess.run(init_op, feed_dict={count: 28, batch_size: 14}) num_batches = (28 * 7) // 14 for i in range(num_batches): - result = sess.run(get_next) + result = self.evaluate(get_next) for component, result_component in zip(components, result): for j in range(14): self.assertAllEqual(component[(i * 14 + j) % 7]**2, @@ -369,12 +369,12 @@ class BatchDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): # We expect (num_batches - 1) full-sized batches. num_batches = int(math.ceil((14 * 7) / 8)) for i in range(num_batches - 1): - result = sess.run(get_next) + result = self.evaluate(get_next) for component, result_component in zip(components, result): for j in range(8): self.assertAllEqual(component[(i * 8 + j) % 7]**2, result_component[j]) - result = sess.run(get_next) + result = self.evaluate(get_next) for component, result_component in zip(components, result): for j in range((14 * 7) % 8): self.assertAllEqual(component[((num_batches - 1) * 8 + j) % 7]**2, @@ -408,10 +408,10 @@ class BatchDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): self.assertEqual([None, 1], iterator.output_shapes.as_list()) next_element = iterator.get_next() with self.cached_session() as sess: - self.assertAllEqual([[0], [1], [4], [9]], sess.run(next_element)) - self.assertAllEqual([[16], [25], [36], [49]], sess.run(next_element)) + self.assertAllEqual([[0], [1], [4], [9]], self.evaluate(next_element)) + self.assertAllEqual([[16], [25], [36], [49]], self.evaluate(next_element)) if not drop_remainder: - self.assertAllEqual([[64], [81]], sess.run(next_element)) + self.assertAllEqual([[64], [81]], self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -423,9 +423,9 @@ class BatchDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): self.assertEqual([None, 1], iterator.output_shapes.as_list()) next_element = iterator.get_next() with self.cached_session() as sess: - self.assertAllEqual([[0], [1], [4], [9]], sess.run(next_element)) - self.assertAllEqual([[16], [25], [36], [49]], sess.run(next_element)) - self.assertAllEqual([[64], [81]], sess.run(next_element)) + self.assertAllEqual([[0], [1], [4], [9]], self.evaluate(next_element)) + self.assertAllEqual([[16], [25], [36], [49]], self.evaluate(next_element)) + self.assertAllEqual([[64], [81]], self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -439,7 +439,7 @@ class BatchDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): elements.append(iterator.get_next()) with self.cached_session() as sess: for i in range(5): - got = sess.run(elements) + got = self.evaluate(elements) got.sort(key=lambda x: x[0]) expected = [] for j in range(100): @@ -459,7 +459,7 @@ class BatchDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): elements.append(iterator.get_next()) with self.cached_session() as sess: for i in range(4): - got = sess.run(elements) + got = self.evaluate(elements) got.sort(key=lambda x: x[0]) expected = [] for j in range(100): @@ -480,9 +480,9 @@ class BatchDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for i in range(2): - actual = sess.run(get_next) + actual = self.evaluate(get_next) expected = sparse_tensor.SparseTensorValue( indices=[[0, 0], [1, 0], [2, 0], [3, 0], [4, 0]], values=[i * 5, i * 5 + 1, i * 5 + 2, i * 5 + 3, i * 5 + 4], @@ -524,7 +524,7 @@ class BatchDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): init_op = iterator.initializer get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) with self.assertRaisesRegexp(errors.InvalidArgumentError, "number of elements does not match"): sess.run(get_next) @@ -576,7 +576,8 @@ class BatchDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): with self.cached_session() as sess: for i in range(threshold // 10): - self.assertAllEqual([i * 10 + j for j in range(10)], sess.run(get_next)) + self.assertAllEqual([i * 10 + j for j in range(10)], + self.evaluate(get_next)) if threshold % 10 != 0: self.assertAllEqual( [threshold // 10 * 10 + j for j in range(threshold % 10)], @@ -609,7 +610,8 @@ class BatchDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): with self.cached_session() as sess: for _ in range(10): - self.assertAllEqual([element for _ in range(10)], sess.run(get_next)) + self.assertAllEqual([element for _ in range(10)], + self.evaluate(get_next)) class UnbatchDatasetBenchmark(test.Benchmark): diff --git a/tensorflow/python/data/experimental/kernel_tests/bucket_by_sequence_length_test.py b/tensorflow/python/data/experimental/kernel_tests/bucket_by_sequence_length_test.py index 3903ec49b98..4263a90f4cc 100644 --- a/tensorflow/python/data/experimental/kernel_tests/bucket_by_sequence_length_test.py +++ b/tensorflow/python/data/experimental/kernel_tests/bucket_by_sequence_length_test.py @@ -300,7 +300,7 @@ class BucketBySequenceLengthTest(test_base.DatasetTestBase): with self.cached_session() as sess: with self.assertRaises(errors.OutOfRangeError): while True: - output = sess.run(batch) + output = self.evaluate(batch) sprs_tensor = (tuple([tuple(idx) for idx in output.indices]), tuple(output.values)) all_sparse_tensors.add(sprs_tensor) 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 cea8bd6f0b7..6d063ac9c8f 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 @@ -57,7 +57,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase): worker_config = config_pb2.ConfigProto(device_count={"CPU": 2}) with self.test_session(config=worker_config) as sess: for i in range(10): - self.assertEqual(i, sess.run(next_element)) + self.assertEqual(i, self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -82,7 +82,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase): worker_config = config_pb2.ConfigProto(device_count={"CPU": 2}) with self.test_session(config=worker_config) as sess: - self.assertAllEqual([0, 1, 2, 3], sess.run(next_element)) + self.assertAllEqual([0, 1, 2, 3], self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -108,7 +108,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase): worker_config = config_pb2.ConfigProto(device_count={"CPU": 2}) with self.test_session(config=worker_config) as sess: for i in range(10): - self.assertEqual(i, sess.run(next_element)) + self.assertEqual(i, self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -134,7 +134,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase): worker_config = config_pb2.ConfigProto(device_count={"CPU": 2}) with self.test_session(config=worker_config) as sess: for i in range(10): - self.assertEqual(i, sess.run(next_element)) + self.assertEqual(i, self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -160,7 +160,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase): worker_config = config_pb2.ConfigProto(device_count={"CPU": 2}) with self.test_session(config=worker_config) as sess: for i in range(10): - self.assertEqual({"a": i}, sess.run(next_element)) + self.assertEqual({"a": i}, self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -186,7 +186,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase): worker_config = config_pb2.ConfigProto(device_count={"CPU": 2}) with self.test_session(config=worker_config) as sess: for i in range(10): - self.assertEqual({"a": i}, sess.run(next_element)) + self.assertEqual({"a": i}, self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -217,7 +217,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase): worker_config = config_pb2.ConfigProto(device_count={"CPU": 2}) with self.test_session(config=worker_config) as sess: for i in range(10): - actual = sess.run(next_element) + actual = self.evaluate(next_element) self.assertAllEqual([i], actual.values) self.assertAllEqual([[0, 0]], actual.indices) self.assertAllEqual([2, 2], actual.dense_shape) @@ -251,7 +251,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase): worker_config = config_pb2.ConfigProto(device_count={"CPU": 2}) with self.test_session(config=worker_config) as sess: for i in range(10): - actual = sess.run(next_element) + actual = self.evaluate(next_element) self.assertAllEqual([i], actual.values) self.assertAllEqual([[0, 0]], actual.indices) self.assertAllEqual([2, 2], actual.dense_shape) @@ -271,9 +271,9 @@ class CopyToDeviceTest(test_base.DatasetTestBase): next_element = iterator.get_next() with self.cached_session() as sess: - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) for i in range(10): - self.assertEqual(i, sess.run(next_element)) + self.assertEqual(i, self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -290,9 +290,9 @@ class CopyToDeviceTest(test_base.DatasetTestBase): next_element = iterator.get_next() with self.cached_session() as sess: - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) for i in range(10): - self.assertEqual(i, sess.run(next_element)) + self.assertEqual(i, self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -323,9 +323,9 @@ class CopyToDeviceTest(test_base.DatasetTestBase): next_element = iterator.get_next() with self.cached_session() as sess: - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) for i in range(10): - x, y, z = sess.run(next_element) + x, y, z = self.evaluate(next_element) self.assertEqual(i**2, x) self.assertEqual(float(i**2), y) self.assertEqual(util_compat.as_bytes(str(i)), z) @@ -345,8 +345,8 @@ class CopyToDeviceTest(test_base.DatasetTestBase): next_element = iterator.get_next() with self.cached_session() as sess: - sess.run(iterator.initializer) - self.assertAllEqual([0, 1, 2, 3], sess.run(next_element)) + self.evaluate(iterator.initializer) + self.assertAllEqual([0, 1, 2, 3], self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -363,8 +363,8 @@ class CopyToDeviceTest(test_base.DatasetTestBase): next_element = iterator.get_next() with self.cached_session() as sess: - sess.run(iterator.initializer) - self.assertAllEqual([0, 1, 2, 3], sess.run(next_element)) + self.evaluate(iterator.initializer) + self.assertAllEqual([0, 1, 2, 3], self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -381,8 +381,8 @@ class CopyToDeviceTest(test_base.DatasetTestBase): next_element = iterator.get_next() with self.cached_session() as sess: - sess.run(iterator.initializer) - self.assertAllEqual([b"a", b"b", b"c"], sess.run(next_element)) + self.evaluate(iterator.initializer) + self.assertAllEqual([b"a", b"b", b"c"], self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -399,8 +399,8 @@ class CopyToDeviceTest(test_base.DatasetTestBase): next_element = iterator.get_next() with self.cached_session() as sess: - sess.run(iterator.initializer) - self.assertAllEqual([b"a", b"b", b"c"], sess.run(next_element)) + self.evaluate(iterator.initializer) + self.assertAllEqual([b"a", b"b", b"c"], self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -420,9 +420,9 @@ class CopyToDeviceTest(test_base.DatasetTestBase): next_element = iterator.get_next() with self.cached_session() as sess: - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) for i in range(10): - self.assertEqual(i, sess.run(next_element)) + self.assertEqual(i, self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -447,12 +447,12 @@ class CopyToDeviceTest(test_base.DatasetTestBase): worker_config = config_pb2.ConfigProto(device_count={"CPU": 2}) with self.test_session(config=worker_config) as sess: - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) for i in range(5): - self.assertEqual(i, sess.run(next_element)) - sess.run(iterator.initializer) + self.assertEqual(i, self.evaluate(next_element)) + self.evaluate(iterator.initializer) for i in range(10): - self.assertEqual(i, sess.run(next_element)) + self.assertEqual(i, self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -477,12 +477,12 @@ class CopyToDeviceTest(test_base.DatasetTestBase): worker_config = config_pb2.ConfigProto(device_count={"CPU": 2}) with self.test_session(config=worker_config) as sess: - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) for i in range(5): - self.assertEqual(i, sess.run(next_element)) - sess.run(iterator.initializer) + self.assertEqual(i, self.evaluate(next_element)) + self.evaluate(iterator.initializer) for i in range(10): - self.assertEqual(i, sess.run(next_element)) + self.assertEqual(i, self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -499,12 +499,12 @@ class CopyToDeviceTest(test_base.DatasetTestBase): next_element = iterator.get_next() with self.cached_session() as sess: - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) for i in range(5): - self.assertEqual(i, sess.run(next_element)) - sess.run(iterator.initializer) + self.assertEqual(i, self.evaluate(next_element)) + self.evaluate(iterator.initializer) for i in range(10): - self.assertEqual(i, sess.run(next_element)) + self.assertEqual(i, self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -521,12 +521,12 @@ class CopyToDeviceTest(test_base.DatasetTestBase): next_element = iterator.get_next() with self.cached_session() as sess: - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) for i in range(5): - self.assertEqual(i, sess.run(next_element)) - sess.run(iterator.initializer) + self.assertEqual(i, self.evaluate(next_element)) + self.evaluate(iterator.initializer) for i in range(10): - self.assertEqual(i, sess.run(next_element)) + self.assertEqual(i, self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -553,7 +553,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase): # For each element of the dataset, assert that the optional evaluates to # the expected value. - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) for i in range(3): elem_has_value, elem_value = sess.run([elem_has_value_t, elem_value_t]) self.assertTrue(elem_has_value) @@ -562,7 +562,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase): # After exhausting the iterator, `next_elem.has_value()` will evaluate to # false, and attempting to get the value will fail. for _ in range(2): - self.assertFalse(sess.run(elem_has_value_t)) + self.assertFalse(self.evaluate(elem_has_value_t)) with self.assertRaises(errors.InvalidArgumentError): sess.run(elem_value_t) diff --git a/tensorflow/python/data/experimental/kernel_tests/counter_test.py b/tensorflow/python/data/experimental/kernel_tests/counter_test.py index 4e114ac4791..d1dd07a8794 100644 --- a/tensorflow/python/data/experimental/kernel_tests/counter_test.py +++ b/tensorflow/python/data/experimental/kernel_tests/counter_test.py @@ -38,13 +38,13 @@ class CounterTest(test_base.DatasetTestBase): negative_get_next = negative_iterator.get_next() with self.cached_session() as sess: - self.assertEqual(3, sess.run(get_next)) - self.assertEqual(3 + 4, sess.run(get_next)) - self.assertEqual(3 + 2 * 4, sess.run(get_next)) + self.assertEqual(3, self.evaluate(get_next)) + self.assertEqual(3 + 4, self.evaluate(get_next)) + self.assertEqual(3 + 2 * 4, self.evaluate(get_next)) - self.assertEqual(0, sess.run(negative_get_next)) - self.assertEqual(-1, sess.run(negative_get_next)) - self.assertEqual(-2, sess.run(negative_get_next)) + self.assertEqual(0, self.evaluate(negative_get_next)) + self.assertEqual(-1, self.evaluate(negative_get_next)) + self.assertEqual(-2, self.evaluate(negative_get_next)) if __name__ == "__main__": 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 73be6cbcca8..9fe2ee43ed9 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 @@ -41,10 +41,10 @@ class DenseToSparseBatchTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for start in range(0, len(components), 4): - results = sess.run(get_next) + results = self.evaluate(get_next) self.assertAllEqual([[i, j] for i, c in enumerate(components[start:start + 4]) for j in range(c)], results.indices) @@ -69,10 +69,10 @@ class DenseToSparseBatchTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for start in range(0, len(components), 4): - results = sess.run(get_next) + results = self.evaluate(get_next) self.assertAllEqual([[i, j, z] for i, c in enumerate(components[start:start + 4]) for j in range(c) 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 796a692c56f..234fd86bdde 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 @@ -40,10 +40,10 @@ class DirectedInterleaveDatasetTest(test_base.DatasetTestBase): next_element = iterator.get_next() with self.cached_session() as sess: - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) for _ in range(100): for i in range(10): - self.assertEqual(i, sess.run(next_element)) + self.assertEqual(i, self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -107,7 +107,7 @@ class DirectedInterleaveDatasetTest(test_base.DatasetTestBase): with self.cached_session() as sess: for i in choice_array: - self.assertEqual(words[i], sess.run(next_element)) + self.assertEqual(words[i], self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) 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 e54235d9f80..78805bb801e 100644 --- a/tensorflow/python/data/experimental/kernel_tests/enumerate_dataset_test.py +++ b/tensorflow/python/data/experimental/kernel_tests/enumerate_dataset_test.py @@ -44,9 +44,9 @@ class EnumerateDatasetTest(test_base.DatasetTestBase): [t.shape for t in get_next[1]]) with self.cached_session() as sess: - sess.run(init_op) - self.assertEqual((20, (b"a", 1, 37.0)), sess.run(get_next)) - self.assertEqual((21, (b"b", 2, 38.0)), sess.run(get_next)) + self.evaluate(init_op) + self.assertEqual((20, (b"a", 1, 37.0)), self.evaluate(get_next)) + self.assertEqual((21, (b"b", 2, 38.0)), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) 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 d38452e265a..860442571eb 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 @@ -94,18 +94,18 @@ class FunctionBufferingResourceTest(test_base.DatasetTestBase): device0, device1) with self.test_session(config=worker_config) as sess: - elem = sess.run(prefetch_op) + elem = self.evaluate(prefetch_op) self.assertEqual(elem, [1.0]) - elem = sess.run(prefetch_op) + elem = self.evaluate(prefetch_op) self.assertEqual(elem, [2.0]) - elem = sess.run(prefetch_op) + elem = self.evaluate(prefetch_op) self.assertEqual(elem, [3.0]) - elem = sess.run(prefetch_op) + elem = self.evaluate(prefetch_op) self.assertEqual(elem, [4.0]) self._event.wait() - elem = sess.run(prefetch_op) + elem = self.evaluate(prefetch_op) self.assertEqual(elem, [5.0]) - sess.run(destroy_op) + self.evaluate(destroy_op) def testSameDeviceCPU(self): self._prefetch_fn_helper_one_shot("same_device_cpu", @@ -135,35 +135,35 @@ class FunctionBufferingResourceTest(test_base.DatasetTestBase): ds, ds_iterator, "reinit", device0, device1) with self.test_session(config=worker_config) as sess: - sess.run(ds_iterator.initializer) - elem = sess.run(prefetch_op) + self.evaluate(ds_iterator.initializer) + elem = self.evaluate(prefetch_op) self.assertEqual(elem, [1.0]) - elem = sess.run(prefetch_op) + elem = self.evaluate(prefetch_op) self.assertEqual(elem, [2.0]) - elem = sess.run(prefetch_op) + elem = self.evaluate(prefetch_op) self.assertEqual(elem, [3.0]) - elem = sess.run(prefetch_op) + elem = self.evaluate(prefetch_op) self.assertEqual(elem, [4.0]) self._event.wait() - elem = sess.run(prefetch_op) + elem = self.evaluate(prefetch_op) self.assertEqual(elem, [5.0]) # Lets reset the function buffering resource and reinitialize the # iterator. Should be able to go through this again. self._event.clear() - sess.run(reset_op) - sess.run(ds_iterator.initializer) - elem = sess.run(prefetch_op) + self.evaluate(reset_op) + self.evaluate(ds_iterator.initializer) + elem = self.evaluate(prefetch_op) self.assertEqual(elem, [1.0]) - elem = sess.run(prefetch_op) + elem = self.evaluate(prefetch_op) self.assertEqual(elem, [2.0]) - elem = sess.run(prefetch_op) + elem = self.evaluate(prefetch_op) self.assertEqual(elem, [3.0]) - elem = sess.run(prefetch_op) + elem = self.evaluate(prefetch_op) self.assertEqual(elem, [4.0]) self._event.wait() - elem = sess.run(prefetch_op) + elem = self.evaluate(prefetch_op) self.assertEqual(elem, [5.0]) - sess.run(destroy_op) + self.evaluate(destroy_op) def testReinitializationOutOfRange(self): worker_config = config_pb2.ConfigProto(device_count={"CPU": 2}) @@ -175,30 +175,30 @@ class FunctionBufferingResourceTest(test_base.DatasetTestBase): ds, ds_iterator, "reinit", device0, device1) with self.test_session(config=worker_config) as sess: - sess.run(ds_iterator.initializer) + self.evaluate(ds_iterator.initializer) for i in range(1, 10): - elem = sess.run(prefetch_op) + elem = self.evaluate(prefetch_op) self.assertEqual(elem, [float(i)]) # Try fetching after its over twice to test out end of sequence. with self.assertRaises(errors.OutOfRangeError): - sess.run(prefetch_op) + self.evaluate(prefetch_op) with self.assertRaises(errors.OutOfRangeError): - sess.run(prefetch_op) + self.evaluate(prefetch_op) # Now reset everything and try it out again. self._event.clear() - sess.run(reset_op) - sess.run(ds_iterator.initializer) + self.evaluate(reset_op) + self.evaluate(ds_iterator.initializer) for i in range(1, 10): - elem = sess.run(prefetch_op) + elem = self.evaluate(prefetch_op) self.assertEqual(elem, [float(i)]) # Try fetching after its over twice to test out end of sequence. with self.assertRaises(errors.OutOfRangeError): - sess.run(prefetch_op) + self.evaluate(prefetch_op) with self.assertRaises(errors.OutOfRangeError): - sess.run(prefetch_op) + self.evaluate(prefetch_op) - sess.run(destroy_op) + self.evaluate(destroy_op) def testStringsGPU(self): if not test_util.is_gpu_available(): @@ -235,13 +235,13 @@ class FunctionBufferingResourceTest(test_base.DatasetTestBase): buffer_resource_handle, ignore_lookup_error=True) with self.cached_session() as sess: - self.assertEqual([b"a"], sess.run(prefetch_op)) - self.assertEqual([b"b"], sess.run(prefetch_op)) - self.assertEqual([b"c"], sess.run(prefetch_op)) + self.assertEqual([b"a"], self.evaluate(prefetch_op)) + self.assertEqual([b"b"], self.evaluate(prefetch_op)) + self.assertEqual([b"c"], self.evaluate(prefetch_op)) with self.assertRaises(errors.OutOfRangeError): - sess.run(prefetch_op) + self.evaluate(prefetch_op) - sess.run(destroy_op) + self.evaluate(destroy_op) if __name__ == "__main__": 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 90303285931..15396f329d0 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 @@ -39,7 +39,7 @@ class GroupByReducerTest(test_base.DatasetTestBase): get_next = dataset.make_one_shot_iterator().get_next() with self.cached_session() as sess: for expected in values: - got = sess.run(get_next) + got = self.evaluate(get_next) self.assertEqual(got, expected) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -127,7 +127,7 @@ class GroupByReducerTest(test_base.DatasetTestBase): iterator = dataset.make_one_shot_iterator() get_next = iterator.get_next() with self.cached_session() as sess: - x, y = sess.run(get_next) + x, y = self.evaluate(get_next) self.assertAllEqual([0] * (2**i), x) self.assertAllEqual(np.array(1, ndmin=i), y) with self.assertRaises(errors.OutOfRangeError): @@ -190,7 +190,7 @@ class GroupByReducerTest(test_base.DatasetTestBase): grouping.group_by_reducer(lambda x, y: np.int64(0), reducer)) get_next = dataset.make_one_shot_iterator().get_next() with self.cached_session() as sess: - x, y = sess.run(get_next) + x, y = self.evaluate(get_next) self.assertAllEqual(x, np.asarray([x for x in range(10)])) self.assertEqual(y, 45) 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 557d56e8b9a..cfc357ba13a 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 @@ -68,9 +68,9 @@ class GroupByWindowTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) - which_bucket, bucketed_values = sess.run(get_next) + which_bucket, bucketed_values = self.evaluate(get_next) self.assertEqual(0, which_bucket) @@ -103,11 +103,11 @@ class GroupByWindowTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) # Get two minibatches (one containing even values, one containing odds) - which_bucket_even, bucketed_values_even = sess.run(get_next) - which_bucket_odd, bucketed_values_odd = sess.run(get_next) + which_bucket_even, bucketed_values_even = self.evaluate(get_next) + which_bucket_odd, bucketed_values_odd = self.evaluate(get_next) # Count number of bucket_tensors. self.assertEqual(3, len(bucketed_values_even)) @@ -174,11 +174,11 @@ class GroupByWindowTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) # Get two minibatches ([0, 2, ...] and [64, 66, ...]) - which_bucket0, bucketed_values_even0 = sess.run(get_next) - which_bucket1, bucketed_values_even1 = sess.run(get_next) + which_bucket0, bucketed_values_even0 = self.evaluate(get_next) + which_bucket1, bucketed_values_even1 = self.evaluate(get_next) # Ensure that bucket 1 was completely filtered out self.assertAllEqual(0, which_bucket0) @@ -207,11 +207,11 @@ class GroupByWindowTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) with self.assertRaises(errors.OutOfRangeError): batches = 0 while True: - result = sess.run(get_next) + result = self.evaluate(get_next) is_even = all(x % 2 == 0 for x in result) is_odd = all(x % 2 == 1 for x in result) self.assertTrue(is_even or is_odd) @@ -232,11 +232,11 @@ class GroupByWindowTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) counts = [] with self.assertRaises(errors.OutOfRangeError): while True: - result = sess.run(get_next) + result = self.evaluate(get_next) self.assertTrue( all(x % 2 == 0 for x in result) or all(x % 2 == 1) @@ -259,16 +259,16 @@ class GroupByWindowTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) # The input is infinite, so this test demonstrates that: # 1. We produce output without having to consume the entire input, # 2. Different buckets can produce output at different rates, and # 3. For deterministic input, the output is deterministic. for _ in range(3): - self.assertAllEqual([0, 0, 0, 0], sess.run(get_next)) - self.assertAllEqual([1, 1, 1, 1], sess.run(get_next)) - self.assertAllEqual([2, 2, 2, 2], sess.run(get_next)) - self.assertAllEqual([0, 0, 0, 0], sess.run(get_next)) + self.assertAllEqual([0, 0, 0, 0], self.evaluate(get_next)) + self.assertAllEqual([1, 1, 1, 1], self.evaluate(get_next)) + self.assertAllEqual([2, 2, 2, 2], self.evaluate(get_next)) + self.assertAllEqual([0, 0, 0, 0], self.evaluate(get_next)) def testSmallGroups(self): components = np.array([0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0], dtype=np.int64) @@ -280,13 +280,13 @@ class GroupByWindowTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) - self.assertAllEqual([0, 0, 0, 0], sess.run(get_next)) - self.assertAllEqual([1, 1, 1, 1], sess.run(get_next)) + self.evaluate(init_op) + self.assertAllEqual([0, 0, 0, 0], self.evaluate(get_next)) + self.assertAllEqual([1, 1, 1, 1], self.evaluate(get_next)) # The small outputs at the end are deterministically produced in key # order. - self.assertAllEqual([0, 0, 0], sess.run(get_next)) - self.assertAllEqual([1], sess.run(get_next)) + self.assertAllEqual([0, 0, 0], self.evaluate(get_next)) + self.assertAllEqual([1], self.evaluate(get_next)) def testEmpty(self): iterator = ( @@ -297,7 +297,7 @@ class GroupByWindowTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) with self.assertRaisesRegexp( errors.InvalidArgumentError, "Window size must be greater than zero, but got 0."): @@ -323,7 +323,7 @@ class GroupByWindowTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) with self.assertRaises(errors.InvalidArgumentError): sess.run(get_next) @@ -351,11 +351,11 @@ class GroupByWindowTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) counts = [] with self.assertRaises(errors.OutOfRangeError): while True: - tight_result, multiple_of_10_result = sess.run(get_next) + tight_result, multiple_of_10_result = self.evaluate(get_next) self.assertEqual(0, multiple_of_10_result.shape[1] % 10) self.assertAllEqual(tight_result, multiple_of_10_result[:, :tight_result.shape[1]]) 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 c0ec1486ab8..cb0fc139145 100644 --- a/tensorflow/python/data/experimental/kernel_tests/ignore_errors_test.py +++ b/tensorflow/python/data/experimental/kernel_tests/ignore_errors_test.py @@ -47,9 +47,9 @@ class IgnoreErrorsTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for x in [1., 2., 3., 5.]: - self.assertEqual(x, sess.run(get_next)) + self.assertEqual(x, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -65,9 +65,9 @@ class IgnoreErrorsTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for x in [1., 2., 3., 5.]: - self.assertEqual(x, sess.run(get_next)) + self.assertEqual(x, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -93,9 +93,9 @@ class IgnoreErrorsTest(test_base.DatasetTestBase): with self.cached_session() as sess: # All of the files are present. - sess.run(init_op) + self.evaluate(init_op) for filename in filenames: - self.assertEqual(compat.as_bytes(filename), sess.run(get_next)) + self.assertEqual(compat.as_bytes(filename), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -104,9 +104,9 @@ class IgnoreErrorsTest(test_base.DatasetTestBase): # Attempting to read filenames[0] will fail, but ignore_errors() # will catch the error. - sess.run(init_op) + self.evaluate(init_op) for filename in filenames[1:]: - self.assertEqual(compat.as_bytes(filename), sess.run(get_next)) + self.assertEqual(compat.as_bytes(filename), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) 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 c93a8353ce0..c4076daef2a 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 @@ -53,7 +53,7 @@ class IndexedDatasetOpsTest(test_base.DatasetTestBase): ds = indexed_dataset_ops.IdentityIndexedDataset(16) materialized = ds.materialize() with self.cached_session() as sess: - sess.run(materialized.initializer) + self.evaluate(materialized.initializer) placeholder = array_ops.placeholder(dtypes.uint64, shape=[]) for i in range(16): output = sess.run( @@ -68,9 +68,9 @@ class IndexedDatasetOpsTest(test_base.DatasetTestBase): itr = ds.make_initializable_iterator() n = itr.get_next() with self.cached_session() as sess: - sess.run(itr.initializer) + self.evaluate(itr.initializer) for i in range(16): - output = sess.run(n) + output = self.evaluate(n) self.assertEqual(i, output) with self.assertRaises(errors.OutOfRangeError): sess.run(n) 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 91ae8cb1bd2..c6cefa7034e 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 @@ -112,10 +112,10 @@ class MakeBatchedFeaturesDatasetTest( next_element = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for file_batch, _, _, _, record_batch, _ in self._next_expected_batch( range(self._num_files), 2, 10): - actual_batch = sess.run(next_element) + actual_batch = self.evaluate(next_element) self.assertAllEqual(file_batch, actual_batch["file"]) self.assertAllEqual(record_batch, actual_batch["record"]) with self.assertRaises(errors.OutOfRangeError): 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 e4bf0891842..5486369462d 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 @@ -90,7 +90,7 @@ class MakeCsvDatasetTest(test_base.DatasetTestBase): batch_size, num_epochs, ): - actual_features = sess.run(nxt) + actual_features = self.evaluate(nxt) if label_name is not None: expected_labels = expected_features.pop(label_name) diff --git a/tensorflow/python/data/experimental/kernel_tests/make_tf_record_dataset_test.py b/tensorflow/python/data/experimental/kernel_tests/make_tf_record_dataset_test.py index 657cf3c00ee..404edf2fdab 100644 --- a/tensorflow/python/data/experimental/kernel_tests/make_tf_record_dataset_test.py +++ b/tensorflow/python/data/experimental/kernel_tests/make_tf_record_dataset_test.py @@ -105,7 +105,7 @@ class MakeTFRecordDatasetTest( for expected_batch in self._next_expected_batch( file_indices, batch_size, num_epochs, interleave_cycle_length, drop_final_batch, use_parser_fn): - actual_batch = sess.run(outputs) + actual_batch = self.evaluate(outputs) self.assertAllEqual(expected_batch, actual_batch) def _read_test(self, batch_size, num_epochs, file_index=None, @@ -188,7 +188,7 @@ class MakeTFRecordDatasetTest( iterator = dataset.make_initializable_iterator() next_element = iterator.get_next() - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) first_batches = [] try: while True: @@ -196,7 +196,7 @@ class MakeTFRecordDatasetTest( except errors.OutOfRangeError: pass - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) second_batches = [] try: while True: 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 5ead6d1c754..b4bc4a617fe 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 @@ -89,7 +89,7 @@ class MapAndBatchTest(test_base.DatasetTestBase, parameterized.TestCase): sess.run(init_op, feed_dict={count: 28, batch_size: 14}) num_batches = (28 * 7) // 14 for i in range(num_batches): - result = sess.run(get_next) + result = self.evaluate(get_next) for component, result_component in zip(components, result): for j in range(14): self.assertAllEqual(component[(i * 14 + j) % 7]**2, @@ -104,12 +104,12 @@ class MapAndBatchTest(test_base.DatasetTestBase, parameterized.TestCase): # We expect (num_batches - 1) full-sized batches. num_batches = int(math.ceil((14 * 7) / 8)) for i in range(num_batches - 1): - result = sess.run(get_next) + result = self.evaluate(get_next) for component, result_component in zip(components, result): for j in range(8): self.assertAllEqual(component[(i * 8 + j) % 7]**2, result_component[j]) - result = sess.run(get_next) + result = self.evaluate(get_next) for component, result_component in zip(components, result): for j in range((14 * 7) % 8): self.assertAllEqual(component[((num_batches - 1) * 8 + j) % 7]**2, @@ -152,10 +152,10 @@ class MapAndBatchTest(test_base.DatasetTestBase, parameterized.TestCase): self.assertEqual([None, 1], iterator.output_shapes.as_list()) next_element = iterator.get_next() with self.cached_session() as sess: - self.assertAllEqual([[0], [1], [4], [9]], sess.run(next_element)) - self.assertAllEqual([[16], [25], [36], [49]], sess.run(next_element)) + self.assertAllEqual([[0], [1], [4], [9]], self.evaluate(next_element)) + self.assertAllEqual([[16], [25], [36], [49]], self.evaluate(next_element)) if not drop_remainder: - self.assertAllEqual([[64], [81]], sess.run(next_element)) + self.assertAllEqual([[64], [81]], self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -177,9 +177,9 @@ class MapAndBatchTest(test_base.DatasetTestBase, parameterized.TestCase): self.assertEqual([None, 1], iterator.output_shapes.as_list()) next_element = iterator.get_next() with self.cached_session() as sess: - self.assertAllEqual([[0], [1], [4], [9]], sess.run(next_element)) - self.assertAllEqual([[16], [25], [36], [49]], sess.run(next_element)) - self.assertAllEqual([[64], [81]], sess.run(next_element)) + self.assertAllEqual([[0], [1], [4], [9]], self.evaluate(next_element)) + self.assertAllEqual([[16], [25], [36], [49]], self.evaluate(next_element)) + self.assertAllEqual([[64], [81]], self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -201,7 +201,7 @@ class MapAndBatchTest(test_base.DatasetTestBase, parameterized.TestCase): elements.append(iterator.get_next()) with self.cached_session() as sess: for i in range(5): - got = sess.run(elements) + got = self.evaluate(elements) got.sort(key=lambda x: x[0]) expected = [] for j in range(100): @@ -230,7 +230,7 @@ class MapAndBatchTest(test_base.DatasetTestBase, parameterized.TestCase): elements.append(iterator.get_next()) with self.cached_session() as sess: for i in range(4): - got = sess.run(elements) + got = self.evaluate(elements) got.sort(key=lambda x: x[0]) expected = [] for j in range(100): @@ -261,9 +261,9 @@ class MapAndBatchTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for i in range(2): - actual = sess.run(get_next) + actual = self.evaluate(get_next) expected = sparse_tensor.SparseTensorValue( indices=[[0, 0], [1, 0], [2, 0], [3, 0], [4, 0]], values=[i * 5, i * 5 + 1, i * 5 + 2, i * 5 + 3, i * 5 + 4], @@ -321,7 +321,7 @@ class MapAndBatchTest(test_base.DatasetTestBase, parameterized.TestCase): init_op = iterator.initializer get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) with self.assertRaisesRegexp(errors.InvalidArgumentError, "number of elements does not match"): sess.run(get_next) @@ -393,7 +393,8 @@ class MapAndBatchTest(test_base.DatasetTestBase, parameterized.TestCase): with self.cached_session() as sess: for i in range(threshold // 10): - self.assertAllEqual([i * 10 + j for j in range(10)], sess.run(get_next)) + self.assertAllEqual([i * 10 + j for j in range(10)], + self.evaluate(get_next)) if threshold % 10 != 0: self.assertAllEqual( [threshold // 10 * 10 + j for j in range(threshold % 10)], @@ -442,7 +443,8 @@ class MapAndBatchTest(test_base.DatasetTestBase, parameterized.TestCase): with self.cached_session() as sess: for _ in range(10): - self.assertAllEqual([element for _ in range(10)], sess.run(get_next)) + self.assertAllEqual([element for _ in range(10)], + self.evaluate(get_next)) @parameterized.named_parameters( ("Identity", None, lambda x: x, None), @@ -462,7 +464,7 @@ class MapAndBatchTest(test_base.DatasetTestBase, parameterized.TestCase): else: expected = map_fn( sess.run(self.structuredElement(structure, shape=[10]))) - self.assertAllEqual(expected, sess.run(get_next)) + self.assertAllEqual(expected, self.evaluate(get_next)) def testShortCircuitCapturedInput(self): captured_t = array_ops.placeholder(dtypes.int64, shape=[]) @@ -473,7 +475,7 @@ class MapAndBatchTest(test_base.DatasetTestBase, parameterized.TestCase): with self.cached_session() as sess: sess.run(iterator.initializer, feed_dict={captured_t: 42}) - self.assertAllEqual([42] * 10, sess.run(get_next)) + self.assertAllEqual([42] * 10, self.evaluate(get_next)) @parameterized.named_parameters( ("Normal", False), diff --git a/tensorflow/python/data/experimental/kernel_tests/map_defun_op_test.py b/tensorflow/python/data/experimental/kernel_tests/map_defun_op_test.py index 11694540fae..3cf3b89c3f2 100644 --- a/tensorflow/python/data/experimental/kernel_tests/map_defun_op_test.py +++ b/tensorflow/python/data/experimental/kernel_tests/map_defun_op_test.py @@ -218,7 +218,7 @@ class MapDefunTest(test_base.DatasetTestBase): def _assert_op_cancelled(self, sess, map_defun_op): with self.assertRaisesRegexp(errors.CancelledError, "was cancelled"): - sess.run(map_defun_op) + self.evaluate(map_defun_op) def testMapDefunWithParentCancellation(self): # Checks that a cancellation of the parent graph is threaded through to 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 5e419a9b2f9..ca8bc5ff97a 100644 --- a/tensorflow/python/data/experimental/kernel_tests/override_threadpool_test.py +++ b/tensorflow/python/data/experimental/kernel_tests/override_threadpool_test.py @@ -72,7 +72,7 @@ class OverrideThreadpoolTest(test_base.DatasetTestBase, next_element = iterator.get_next() with self.cached_session() as sess: - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) thread_ids = [] try: while True: diff --git a/tensorflow/python/data/experimental/kernel_tests/parallel_interleave_test.py b/tensorflow/python/data/experimental/kernel_tests/parallel_interleave_test.py index 90ac250df70..91908f5582f 100644 --- a/tensorflow/python/data/experimental/kernel_tests/parallel_interleave_test.py +++ b/tensorflow/python/data/experimental/kernel_tests/parallel_interleave_test.py @@ -637,11 +637,11 @@ class ParallelInterleaveTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for i in range(10): for j in range(2): expected = [i, 0] if j % 2 == 0 else [0, -i] - self.assertAllEqual(expected, sess.run(get_next)) + self.assertAllEqual(expected, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -796,7 +796,7 @@ class ParallelInterleaveTest(test_base.DatasetTestBase): with self.cached_session() as sess: for _ in range(2): elements = [] - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) try: while True: elements.extend(sess.run(next_element)) 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 f73725366c4..60c3741d32d 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 @@ -57,7 +57,7 @@ class PrefetchToDeviceTest(test_base.DatasetTestBase): worker_config = config_pb2.ConfigProto(device_count={"CPU": 2}) with self.test_session(config=worker_config) as sess: for i in range(10): - self.assertEqual(i, sess.run(next_element)) + self.assertEqual(i, self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -87,7 +87,7 @@ class PrefetchToDeviceTest(test_base.DatasetTestBase): with self.cached_session() as sess: for i in range(10): - self.assertEqual(i, sess.run(next_element)) + self.assertEqual(i, self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -117,7 +117,7 @@ class PrefetchToDeviceTest(test_base.DatasetTestBase): worker_config = config_pb2.ConfigProto(device_count={"CPU": 2}) with self.test_session(config=worker_config) as sess: for i in range(10): - self.assertEqual({"a": i}, sess.run(next_element)) + self.assertEqual({"a": i}, self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -150,7 +150,7 @@ class PrefetchToDeviceTest(test_base.DatasetTestBase): worker_config = config_pb2.ConfigProto(device_count={"CPU": 2}) with self.test_session(config=worker_config) as sess: for i in range(10): - actual = sess.run(next_element) + actual = self.evaluate(next_element) self.assertAllEqual([i], actual.values) self.assertAllEqual([[0, 0]], actual.indices) self.assertAllEqual([2, 2], actual.dense_shape) @@ -170,7 +170,7 @@ class PrefetchToDeviceTest(test_base.DatasetTestBase): with self.cached_session() as sess: for i in range(10): - self.assertEqual(i, sess.run(next_element)) + self.assertEqual(i, self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -199,12 +199,12 @@ class PrefetchToDeviceTest(test_base.DatasetTestBase): worker_config = config_pb2.ConfigProto(device_count={"CPU": 2}) with self.test_session(config=worker_config) as sess: - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) for i in range(5): - self.assertEqual(i, sess.run(next_element)) - sess.run(iterator.initializer) + self.assertEqual(i, self.evaluate(next_element)) + self.evaluate(iterator.initializer) for i in range(10): - self.assertEqual(i, sess.run(next_element)) + self.assertEqual(i, self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -220,12 +220,12 @@ class PrefetchToDeviceTest(test_base.DatasetTestBase): next_element = iterator.get_next() with self.cached_session() as sess: - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) for i in range(5): - self.assertEqual(i, sess.run(next_element)) - sess.run(iterator.initializer) + self.assertEqual(i, self.evaluate(next_element)) + self.evaluate(iterator.initializer) for i in range(10): - self.assertEqual(i, sess.run(next_element)) + self.assertEqual(i, self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) diff --git a/tensorflow/python/data/experimental/kernel_tests/scan_test.py b/tensorflow/python/data/experimental/kernel_tests/scan_test.py index 0730455431f..0e9bb462f30 100644 --- a/tensorflow/python/data/experimental/kernel_tests/scan_test.py +++ b/tensorflow/python/data/experimental/kernel_tests/scan_test.py @@ -60,7 +60,7 @@ class ScanTest(test_base.DatasetTestBase): feed_dict={start: start_val, step: step_val, take: take_val}) for expected, _ in zip( itertools.count(start_val, step_val), range(take_val)): - self.assertEqual(expected, sess.run(next_element)) + self.assertEqual(expected, self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -110,7 +110,7 @@ class ScanTest(test_base.DatasetTestBase): feed_dict={start: start_val, step: step_val, take: take_val}) for expected, _ in zip( itertools.count(start_val, step_val), range(take_val)): - self.assertEqual(expected, sess.run(next_element).values[0]) + self.assertEqual(expected, self.evaluate(next_element).values[0]) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -136,7 +136,7 @@ class ScanTest(test_base.DatasetTestBase): with self.cached_session() as sess: for i in range(5): - (longer_vector_val, larger_rank_val), _ = sess.run(next_element) + (longer_vector_val, larger_rank_val), _ = self.evaluate(next_element) self.assertAllEqual([0] * (2**i), longer_vector_val) self.assertAllEqual(np.array(1, ndmin=i), larger_rank_val) with self.assertRaises(errors.OutOfRangeError): diff --git a/tensorflow/python/data/experimental/kernel_tests/serialization/range_dataset_serialization_test.py b/tensorflow/python/data/experimental/kernel_tests/serialization/range_dataset_serialization_test.py index ef99d01c73c..704a40721f8 100644 --- a/tensorflow/python/data/experimental/kernel_tests/serialization/range_dataset_serialization_test.py +++ b/tensorflow/python/data/experimental/kernel_tests/serialization/range_dataset_serialization_test.py @@ -71,19 +71,19 @@ class RangeDatasetSerializationTest( with ops.Graph().as_default() as g: init_op, get_next, save_op, _ = _build_graph(start, stop) with self.session(graph=g) as sess: - sess.run(variables.global_variables_initializer()) - sess.run(init_op) + self.evaluate(variables.global_variables_initializer()) + self.evaluate(init_op) for i in range(start, break_point): - self.assertEqual(i, sess.run(get_next)) - sess.run(save_op) + self.assertEqual(i, self.evaluate(get_next)) + self.evaluate(save_op) with ops.Graph().as_default() as g: init_op, get_next, _, restore_op = _build_graph(start, stop) with self.session(graph=g) as sess: - sess.run(init_op) - sess.run(restore_op) + self.evaluate(init_op) + self.evaluate(restore_op) for i in range(break_point, stop): - self.assertEqual(i, sess.run(get_next)) + self.assertEqual(i, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -91,14 +91,14 @@ class RangeDatasetSerializationTest( with ops.Graph().as_default() as g: init_op, get_next, save_op, restore_op = _build_graph(start, stop) with self.session(graph=g) as sess: - sess.run(variables.global_variables_initializer()) - sess.run(init_op) + self.evaluate(variables.global_variables_initializer()) + self.evaluate(init_op) for i in range(start, break_point): - self.assertEqual(i, sess.run(get_next)) - sess.run(save_op) - sess.run(restore_op) + self.assertEqual(i, self.evaluate(get_next)) + self.evaluate(save_op) + self.evaluate(restore_op) for i in range(break_point, stop): - self.assertEqual(i, sess.run(get_next)) + self.assertEqual(i, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) diff --git a/tensorflow/python/data/experimental/kernel_tests/serialization/serialization_integration_test.py b/tensorflow/python/data/experimental/kernel_tests/serialization/serialization_integration_test.py index 88d5c896c9f..496fd459477 100644 --- a/tensorflow/python/data/experimental/kernel_tests/serialization/serialization_integration_test.py +++ b/tensorflow/python/data/experimental/kernel_tests/serialization/serialization_integration_test.py @@ -62,7 +62,7 @@ class SerializationIntegrationTest(test.TestCase): with self.session(graph=g) as sess: sess.run(init_ops) for _ in range(break_point): - output = sess.run(get_next_ops) + output = self.evaluate(get_next_ops) for i in range(num_pipelines): all_outputs[i].append(output[i]) saver.save(sess, self._ckpt_path()) @@ -73,7 +73,7 @@ class SerializationIntegrationTest(test.TestCase): with self.session(graph=g) as sess: saver.restore(sess, self._ckpt_path()) for _ in range(num_outputs - break_point): - output = sess.run(get_next_ops) + output = self.evaluate(get_next_ops) for i in range(num_pipelines): all_outputs[i].append(output[i]) 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 c208963a861..5f7d9051eca 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 @@ -108,7 +108,7 @@ class ShuffleAndRepeatTest(test_base.DatasetTestBase): shuffle_ops.shuffle_and_repeat(buffer_size=21)) get_next_op = ds.make_one_shot_iterator().get_next() with self.session(graph=g) as sess: - sess.run(get_next_op) + self.evaluate(get_next_op) if __name__ == "__main__": diff --git a/tensorflow/python/data/experimental/kernel_tests/sleep_test.py b/tensorflow/python/data/experimental/kernel_tests/sleep_test.py index bf53acc82a8..f7d42bc5b34 100644 --- a/tensorflow/python/data/experimental/kernel_tests/sleep_test.py +++ b/tensorflow/python/data/experimental/kernel_tests/sleep_test.py @@ -38,10 +38,10 @@ class SleepTest(test_base.DatasetTestBase): next_element = iterator.get_next() with self.cached_session() as sess: - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) start_time = time.time() for i in range(10): - self.assertEqual(i, sess.run(next_element)) + self.assertEqual(i, self.evaluate(next_element)) end_time = time.time() self.assertGreater(end_time - start_time, (10 * sleep_microseconds) / 1e6) with self.assertRaises(errors.OutOfRangeError): diff --git a/tensorflow/python/data/experimental/kernel_tests/sql_dataset_test.py b/tensorflow/python/data/experimental/kernel_tests/sql_dataset_test.py index a2c11696387..e11bad7969c 100644 --- a/tensorflow/python/data/experimental/kernel_tests/sql_dataset_test.py +++ b/tensorflow/python/data/experimental/kernel_tests/sql_dataset_test.py @@ -39,8 +39,9 @@ class SqlDatasetTest(sql_dataset_test_base.SqlDatasetTestBase): "ORDER BY first_name DESC" }) for _ in range(2): # Dataset is repeated. See setUp. - self.assertEqual((b"John", b"Doe", b"Hi!"), sess.run(get_next)) - self.assertEqual((b"Jane", b"Moe", b"Hi again!"), sess.run(get_next)) + self.assertEqual((b"John", b"Doe", b"Hi!"), self.evaluate(get_next)) + self.assertEqual((b"Jane", b"Moe", b"Hi again!"), + self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -58,7 +59,8 @@ class SqlDatasetTest(sql_dataset_test_base.SqlDatasetTestBase): "ON students.first_name = people.first_name " "AND students.last_name = people.last_name" }) - self.assertEqual((b"John", b"California", b"Hi!"), sess.run(get_next)) + self.assertEqual((b"John", b"California", b"Hi!"), + self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -75,8 +77,9 @@ class SqlDatasetTest(sql_dataset_test_base.SqlDatasetTestBase): "SELECT first_name, last_name, favorite_nonsense_word " "FROM students ORDER BY first_name DESC" }) - self.assertEqual((b"John", b"Doe", b"n\0nsense"), sess.run(get_next)) - self.assertEqual((b"Jane", b"Moe", b"nonsense\0"), sess.run(get_next)) + self.assertEqual((b"John", b"Doe", b"n\0nsense"), self.evaluate(get_next)) + self.assertEqual((b"Jane", b"Moe", b"nonsense\0"), + self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -93,8 +96,8 @@ class SqlDatasetTest(sql_dataset_test_base.SqlDatasetTestBase): self.query: "SELECT first_name, last_name, motto FROM students " "ORDER BY first_name DESC" }) - self.assertEqual((b"John", b"Doe", b"Hi!"), sess.run(get_next)) - self.assertEqual((b"Jane", b"Moe", b"Hi again!"), sess.run(get_next)) + self.assertEqual((b"John", b"Doe", b"Hi!"), self.evaluate(get_next)) + self.assertEqual((b"Jane", b"Moe", b"Hi again!"), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) sess.run( @@ -103,7 +106,8 @@ class SqlDatasetTest(sql_dataset_test_base.SqlDatasetTestBase): self.query: "SELECT first_name, last_name, state FROM people " "ORDER BY first_name DESC" }) - self.assertEqual((b"John", b"Doe", b"California"), sess.run(get_next)) + self.assertEqual((b"John", b"Doe", b"California"), + self.evaluate(get_next)) self.assertEqual((b"Benjamin", b"Franklin", b"Pennsylvania"), sess.run(get_next)) with self.assertRaises(errors.OutOfRangeError): @@ -212,8 +216,8 @@ class SqlDatasetTest(sql_dataset_test_base.SqlDatasetTestBase): self.query: "SELECT first_name, desk_number FROM students " "ORDER BY first_name DESC" }) - self.assertEqual((b"John", 9), sess.run(get_next)) - self.assertEqual((b"Jane", 127), sess.run(get_next)) + self.assertEqual((b"John", 9), self.evaluate(get_next)) + self.assertEqual((b"Jane", 127), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -230,7 +234,7 @@ class SqlDatasetTest(sql_dataset_test_base.SqlDatasetTestBase): "FROM students " "WHERE first_name = 'John' ORDER BY first_name DESC" }) - self.assertEqual((b"John", 0, -2), sess.run(get_next)) + self.assertEqual((b"John", 0, -2), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -246,9 +250,9 @@ class SqlDatasetTest(sql_dataset_test_base.SqlDatasetTestBase): "SELECT desk_number, favorite_negative_number FROM students " "ORDER BY first_name DESC" }) - self.assertEqual((9, -2), sess.run(get_next)) + self.assertEqual((9, -2), self.evaluate(get_next)) # Max and min values of int8 - self.assertEqual((127, -128), sess.run(get_next)) + self.assertEqual((127, -128), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -263,8 +267,8 @@ class SqlDatasetTest(sql_dataset_test_base.SqlDatasetTestBase): self.query: "SELECT first_name, desk_number FROM students " "ORDER BY first_name DESC" }) - self.assertEqual((b"John", 9), sess.run(get_next)) - self.assertEqual((b"Jane", 127), sess.run(get_next)) + self.assertEqual((b"John", 9), self.evaluate(get_next)) + self.assertEqual((b"Jane", 127), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -281,7 +285,7 @@ class SqlDatasetTest(sql_dataset_test_base.SqlDatasetTestBase): "FROM students " "WHERE first_name = 'John' ORDER BY first_name DESC" }) - self.assertEqual((b"John", 0, -2), sess.run(get_next)) + self.assertEqual((b"John", 0, -2), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -297,9 +301,9 @@ class SqlDatasetTest(sql_dataset_test_base.SqlDatasetTestBase): "FROM students ORDER BY first_name DESC" }) # Max value of int16 - self.assertEqual((b"John", 32767), sess.run(get_next)) + self.assertEqual((b"John", 32767), self.evaluate(get_next)) # Min value of int16 - self.assertEqual((b"Jane", -32768), sess.run(get_next)) + self.assertEqual((b"Jane", -32768), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -314,8 +318,8 @@ class SqlDatasetTest(sql_dataset_test_base.SqlDatasetTestBase): self.query: "SELECT first_name, desk_number FROM students " "ORDER BY first_name DESC" }) - self.assertEqual((b"John", 9), sess.run(get_next)) - self.assertEqual((b"Jane", 127), sess.run(get_next)) + self.assertEqual((b"John", 9), self.evaluate(get_next)) + self.assertEqual((b"Jane", 127), self.evaluate(get_next)) # Test that `SqlDataset` can read a negative or 0-valued integer from a # SQLite database table and place it in an `int32` tensor. @@ -328,8 +332,8 @@ class SqlDatasetTest(sql_dataset_test_base.SqlDatasetTestBase): self.query: "SELECT first_name, income FROM students " "ORDER BY first_name DESC" }) - self.assertEqual((b"John", 0), sess.run(get_next)) - self.assertEqual((b"Jane", -20000), sess.run(get_next)) + self.assertEqual((b"John", 0), self.evaluate(get_next)) + self.assertEqual((b"Jane", -20000), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -345,9 +349,9 @@ class SqlDatasetTest(sql_dataset_test_base.SqlDatasetTestBase): "ORDER BY first_name DESC" }) # Max value of int32 - self.assertEqual((b"John", 2147483647), sess.run(get_next)) + self.assertEqual((b"John", 2147483647), self.evaluate(get_next)) # Min value of int32 - self.assertEqual((b"Jane", -2147483648), sess.run(get_next)) + self.assertEqual((b"Jane", -2147483648), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -362,8 +366,8 @@ class SqlDatasetTest(sql_dataset_test_base.SqlDatasetTestBase): self.query: "SELECT first_name, school_id FROM students " "ORDER BY first_name DESC" }) - self.assertEqual((b"John", 123), sess.run(get_next)) - self.assertEqual((b"Jane", 1000), sess.run(get_next)) + self.assertEqual((b"John", 123), self.evaluate(get_next)) + self.assertEqual((b"Jane", 1000), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -378,8 +382,8 @@ class SqlDatasetTest(sql_dataset_test_base.SqlDatasetTestBase): self.query: "SELECT first_name, desk_number FROM students " "ORDER BY first_name DESC" }) - self.assertEqual((b"John", 9), sess.run(get_next)) - self.assertEqual((b"Jane", 127), sess.run(get_next)) + self.assertEqual((b"John", 9), self.evaluate(get_next)) + self.assertEqual((b"Jane", 127), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -394,8 +398,8 @@ class SqlDatasetTest(sql_dataset_test_base.SqlDatasetTestBase): self.query: "SELECT first_name, income FROM students " "ORDER BY first_name DESC" }) - self.assertEqual((b"John", 0), sess.run(get_next)) - self.assertEqual((b"Jane", -20000), sess.run(get_next)) + self.assertEqual((b"John", 0), self.evaluate(get_next)) + self.assertEqual((b"Jane", -20000), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -412,9 +416,9 @@ class SqlDatasetTest(sql_dataset_test_base.SqlDatasetTestBase): "ORDER BY first_name DESC" }) # Max value of int64 - self.assertEqual((b"John", 9223372036854775807), sess.run(get_next)) + self.assertEqual((b"John", 9223372036854775807), self.evaluate(get_next)) # Min value of int64 - self.assertEqual((b"Jane", -9223372036854775808), sess.run(get_next)) + self.assertEqual((b"Jane", -9223372036854775808), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -429,8 +433,8 @@ class SqlDatasetTest(sql_dataset_test_base.SqlDatasetTestBase): self.query: "SELECT first_name, desk_number FROM students " "ORDER BY first_name DESC" }) - self.assertEqual((b"John", 9), sess.run(get_next)) - self.assertEqual((b"Jane", 127), sess.run(get_next)) + self.assertEqual((b"John", 9), self.evaluate(get_next)) + self.assertEqual((b"Jane", 127), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -446,9 +450,9 @@ class SqlDatasetTest(sql_dataset_test_base.SqlDatasetTestBase): "ORDER BY first_name DESC" }) # Min value of uint8 - self.assertEqual((b"John", 0), sess.run(get_next)) + self.assertEqual((b"John", 0), self.evaluate(get_next)) # Max value of uint8 - self.assertEqual((b"Jane", 255), sess.run(get_next)) + self.assertEqual((b"Jane", 255), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -463,8 +467,8 @@ class SqlDatasetTest(sql_dataset_test_base.SqlDatasetTestBase): self.query: "SELECT first_name, desk_number FROM students " "ORDER BY first_name DESC" }) - self.assertEqual((b"John", 9), sess.run(get_next)) - self.assertEqual((b"Jane", 127), sess.run(get_next)) + self.assertEqual((b"John", 9), self.evaluate(get_next)) + self.assertEqual((b"Jane", 127), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -480,9 +484,9 @@ class SqlDatasetTest(sql_dataset_test_base.SqlDatasetTestBase): "ORDER BY first_name DESC" }) # Min value of uint16 - self.assertEqual((b"John", 0), sess.run(get_next)) + self.assertEqual((b"John", 0), self.evaluate(get_next)) # Max value of uint16 - self.assertEqual((b"Jane", 65535), sess.run(get_next)) + self.assertEqual((b"Jane", 65535), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -499,8 +503,8 @@ class SqlDatasetTest(sql_dataset_test_base.SqlDatasetTestBase): "SELECT first_name, registration_complete FROM students " "ORDER BY first_name DESC" }) - self.assertEqual((b"John", True), sess.run(get_next)) - self.assertEqual((b"Jane", False), sess.run(get_next)) + self.assertEqual((b"John", True), self.evaluate(get_next)) + self.assertEqual((b"Jane", False), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -515,8 +519,8 @@ class SqlDatasetTest(sql_dataset_test_base.SqlDatasetTestBase): self.query: "SELECT first_name, favorite_medium_sized_number " "FROM students ORDER BY first_name DESC" }) - self.assertEqual((b"John", True), sess.run(get_next)) - self.assertEqual((b"Jane", True), sess.run(get_next)) + self.assertEqual((b"John", True), self.evaluate(get_next)) + self.assertEqual((b"Jane", True), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -533,8 +537,9 @@ class SqlDatasetTest(sql_dataset_test_base.SqlDatasetTestBase): "SELECT first_name, last_name, victories FROM townspeople " "ORDER BY first_name" }) - self.assertEqual((b"George", b"Washington", 20.0), sess.run(get_next)) - self.assertEqual((b"John", b"Adams", -19.95), sess.run(get_next)) + self.assertEqual((b"George", b"Washington", 20.0), + self.evaluate(get_next)) + self.assertEqual((b"John", b"Adams", -19.95), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) 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 83028937d36..958c3f0038a 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 @@ -74,18 +74,18 @@ class StatsDatasetTest(stats_dataset_test_base.StatsDatasetTestBase): summary_t = aggregator.get_summary() with self.cached_session() as sess: - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) expected_sum = 0.0 for i in range(100): self.assertAllEqual( np.array([i] * i, dtype=np.int64), sess.run(next_element)) - summary_str = sess.run(summary_t) + summary_str = self.evaluate(summary_t) self._assertSummaryHasCount(summary_str, "bytes_produced", float(i + 1)) expected_sum += i * 8.0 self._assertSummaryHasSum(summary_str, "bytes_produced", expected_sum) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) - summary_str = sess.run(summary_t) + summary_str = self.evaluate(summary_t) self._assertSummaryHasCount(summary_str, "bytes_produced", 100.0) self._assertSummaryHasSum(summary_str, "bytes_produced", expected_sum) @@ -99,14 +99,15 @@ class StatsDatasetTest(stats_dataset_test_base.StatsDatasetTestBase): summary_t = aggregator.get_summary() with self.cached_session() as sess: - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) for i in range(100): - self.assertEqual(i, sess.run(next_element)) + self.assertEqual(i, self.evaluate(next_element)) self._assertSummaryHasCount( sess.run(summary_t), "record_latency", float(i + 1)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) - self._assertSummaryHasCount(sess.run(summary_t), "record_latency", 100.0) + self._assertSummaryHasCount( + self.evaluate(summary_t), "record_latency", 100.0) def testPrefetchBufferUtilization(self, dataset_transformation): aggregator = stats_aggregator.StatsAggregator() @@ -118,11 +119,11 @@ class StatsDatasetTest(stats_dataset_test_base.StatsDatasetTestBase): summary_t = aggregator.get_summary() with self.cached_session() as sess: - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) for i in range(100): self.assertAllEqual( np.array([i] * i, dtype=np.int64), sess.run(next_element)) - summary_str = sess.run(summary_t) + summary_str = self.evaluate(summary_t) self._assertSummaryHasCount(summary_str, "Prefetch::buffer_utilization", float(i + 1)) self._assertSummaryContains(summary_str, "Prefetch::buffer_capacity") @@ -131,7 +132,7 @@ class StatsDatasetTest(stats_dataset_test_base.StatsDatasetTestBase): 0, 1) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) - summary_str = sess.run(summary_t) + summary_str = self.evaluate(summary_t) self._assertSummaryHasCount(summary_str, "Prefetch::buffer_utilization", 100) @@ -145,11 +146,11 @@ class StatsDatasetTest(stats_dataset_test_base.StatsDatasetTestBase): summary_t = aggregator.get_summary() with self.cached_session() as sess: - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) for i in range(10): self.assertAllEqual( np.array([i] * i, dtype=np.int64), sess.run(next_element)) - summary_str = sess.run(summary_t) + summary_str = self.evaluate(summary_t) self._assertSummaryHasScalarValue(summary_str, "Prefetch::buffer_capacity", 0) self._assertSummaryHasScalarValue(summary_str, "Prefetch::buffer_size", @@ -167,9 +168,9 @@ class StatsDatasetTest(stats_dataset_test_base.StatsDatasetTestBase): summary_t = aggregator.get_summary() with self.test_session() as sess: - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) for i in range(34): - self.assertEqual(i * 3, sess.run(next_element)) + self.assertEqual(i * 3, self.evaluate(next_element)) if i is not 0: self._assertSummaryHasScalarValue( sess.run(summary_t), "Filter::dropped_elements", float(i * 2)) @@ -261,9 +262,9 @@ class StatsDatasetTest(stats_dataset_test_base.StatsDatasetTestBase): with self.cached_session() as sess: for j in range(5): - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) for i in range(100): - self.assertEqual(i, sess.run(next_element)) + self.assertEqual(i, self.evaluate(next_element)) self._assertSummaryHasCount( sess.run(summary_t), "record_latency", float((j * 100) + i + 1)) with self.assertRaises(errors.OutOfRangeError): @@ -278,9 +279,9 @@ class StatsDatasetTest(stats_dataset_test_base.StatsDatasetTestBase): next_element = iterator.get_next() with self.cached_session() as sess: - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) for i in range(100): - self.assertEqual(i, sess.run(next_element)) + self.assertEqual(i, self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -295,16 +296,17 @@ class StatsDatasetTest(stats_dataset_test_base.StatsDatasetTestBase): summary_t = aggregator.get_summary() with self.cached_session() as sess: - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) for i in range(100): - self.assertEqual(i, sess.run(next_element)) + self.assertEqual(i, self.evaluate(next_element)) self._assertSummaryHasCount( sess.run(summary_t), "record_latency", float(i + 1)) self._assertSummaryHasCount( sess.run(summary_t), "record_latency_2", float(i + 1)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) - self._assertSummaryHasCount(sess.run(summary_t), "record_latency", 100.0) + self._assertSummaryHasCount( + self.evaluate(summary_t), "record_latency", 100.0) self._assertSummaryHasCount( sess.run(summary_t), "record_latency_2", 100.0) @@ -319,14 +321,15 @@ class StatsDatasetTest(stats_dataset_test_base.StatsDatasetTestBase): summary_t = aggregator.get_summary() with self.cached_session() as sess: - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) for i in range(100): - self.assertEqual(i, sess.run(next_element)) + self.assertEqual(i, self.evaluate(next_element)) self._assertSummaryHasCount( sess.run(summary_t), "record_latency", float(2 * (i + 1))) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) - self._assertSummaryHasCount(sess.run(summary_t), "record_latency", 200.0) + self._assertSummaryHasCount( + self.evaluate(summary_t), "record_latency", 200.0) def testMultipleIteratorsSameAggregator(self, dataset_transformation): aggregator = stats_aggregator.StatsAggregator() @@ -341,12 +344,13 @@ class StatsDatasetTest(stats_dataset_test_base.StatsDatasetTestBase): with self.cached_session() as sess: sess.run([iterator_0.initializer, iterator_1.initializer]) for i in range(100): - self.assertEqual(i * 2, sess.run(next_element)) + self.assertEqual(i * 2, self.evaluate(next_element)) self._assertSummaryHasCount( sess.run(summary_t), "record_latency", float(2 * (i + 1))) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) - self._assertSummaryHasCount(sess.run(summary_t), "record_latency", 200.0) + self._assertSummaryHasCount( + self.evaluate(summary_t), "record_latency", 200.0) def testMultipleDatasetWithPrefixes(self, dataset_transformation): aggregator = stats_aggregator.StatsAggregator() @@ -364,7 +368,7 @@ class StatsDatasetTest(stats_dataset_test_base.StatsDatasetTestBase): with self.test_session() as sess: sess.run([iterator_0.initializer, iterator_1.initializer]) for i in range(100): - self.assertEqual(i * 2, sess.run(next_element)) + self.assertEqual(i * 2, self.evaluate(next_element)) self._assertSummaryHasCount( sess.run(summary_t), "dataset1_record_latency", float(i + 1)) self._assertSummaryHasCount( @@ -421,7 +425,7 @@ class FeatureStatsDatasetTest( summary_t = aggregator.get_summary() with self.test_session() as sess: - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) for _ in range(num_output): sess.run(next_element) diff --git a/tensorflow/python/data/experimental/kernel_tests/unbatch_test.py b/tensorflow/python/data/experimental/kernel_tests/unbatch_test.py index 0278a208cbb..755294ac451 100644 --- a/tensorflow/python/data/experimental/kernel_tests/unbatch_test.py +++ b/tensorflow/python/data/experimental/kernel_tests/unbatch_test.py @@ -50,7 +50,7 @@ class UnbatchTest(test_base.DatasetTestBase, parameterized.TestCase): with self.cached_session() as sess: sess.run(iterator.initializer, feed_dict={placeholder: [0, 1, 2, 3]}) for i in range(4): - self.assertEqual(i, sess.run(next_elem)) + self.assertEqual(i, self.evaluate(next_elem)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_elem) @@ -68,7 +68,7 @@ class UnbatchTest(test_base.DatasetTestBase, parameterized.TestCase): with self.cached_session() as sess: for i in range(10): - self.assertEqual((i,) * 3, sess.run(op)) + self.assertEqual((i,) * 3, self.evaluate(op)) with self.assertRaises(errors.OutOfRangeError): sess.run(op) @@ -88,7 +88,7 @@ class UnbatchTest(test_base.DatasetTestBase, parameterized.TestCase): with self.cached_session() as sess: for i in range(10): - self.assertEqual((i, compat.as_bytes(str(i)), i), sess.run(op)) + self.assertEqual((i, compat.as_bytes(str(i)), i), self.evaluate(op)) with self.assertRaises(errors.OutOfRangeError): sess.run(op) @@ -107,7 +107,7 @@ class UnbatchTest(test_base.DatasetTestBase, parameterized.TestCase): with self.cached_session() as sess: for i in range(10): - st_row = sess.run(next_element) + st_row = self.evaluate(next_element) self.assertEqual([i], st_row.indices) self.assertEqual([i], st_row.values) self.assertEqual([10], st_row.dense_shape) @@ -128,7 +128,7 @@ class UnbatchTest(test_base.DatasetTestBase, parameterized.TestCase): with self.cached_session() as sess: for i in range(10): - dense_elem, st_row = sess.run(next_element) + dense_elem, st_row = self.evaluate(next_element) self.assertEqual(i, dense_elem) self.assertEqual([i], st_row.indices) self.assertEqual([i], st_row.values) @@ -150,7 +150,7 @@ class UnbatchTest(test_base.DatasetTestBase, parameterized.TestCase): with self.cached_session() as sess: for i in range(10): - self.assertEqual(((i,),) * 3, sess.run(op)) + self.assertEqual(((i,),) * 3, self.evaluate(op)) with self.assertRaises(errors.OutOfRangeError): sess.run(op) diff --git a/tensorflow/python/data/experimental/kernel_tests/unique_test.py b/tensorflow/python/data/experimental/kernel_tests/unique_test.py index 847cff26b0d..4b14a7e9635 100644 --- a/tensorflow/python/data/experimental/kernel_tests/unique_test.py +++ b/tensorflow/python/data/experimental/kernel_tests/unique_test.py @@ -49,11 +49,11 @@ class UniqueTest(test_base.DatasetTestBase): with self.cached_session() as sess: for test_case, expected in test_cases: current_test_case = test_case - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) for element in expected: if dtype == dtypes.string: element = compat.as_bytes(element) - self.assertAllEqual(element, sess.run(next_element)) + self.assertAllEqual(element, self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) diff --git a/tensorflow/python/data/kernel_tests/batch_dataset_op_test.py b/tensorflow/python/data/kernel_tests/batch_dataset_op_test.py index e8decb9ad0e..10a0427c7f7 100644 --- a/tensorflow/python/data/kernel_tests/batch_dataset_op_test.py +++ b/tensorflow/python/data/kernel_tests/batch_dataset_op_test.py @@ -93,13 +93,13 @@ class BatchDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): }) num_full_batches = (count * 7) // batch_size for i in range(num_full_batches): - result = sess.run(get_next) + result = self.evaluate(get_next) for component, result_component in zip(components, result): for j in range(batch_size): self.assertAllEqual(component[(i * batch_size + j) % 7]**2, result_component[j]) if not drop_remainder and (count * 7) % batch_size > 0: - result = sess.run(get_next) + result = self.evaluate(get_next) for component, result_component in zip(components, result): for j in range((count * 7) % batch_size): self.assertAllEqual( @@ -128,9 +128,9 @@ class BatchDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for i in range(2): - actual = sess.run(get_next) + actual = self.evaluate(get_next) expected = sparse_tensor.SparseTensorValue( indices=[[0, 0], [1, 0], [2, 0], [3, 0], [4, 0]], values=[i * 5, i * 5 + 1, i * 5 + 2, i * 5 + 3, i * 5 + 4], @@ -155,9 +155,9 @@ class BatchDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for i in range(2): - actual = sess.run(get_next) + actual = self.evaluate(get_next) expected_indices = [] expected_values = [] for j in range(5): @@ -185,8 +185,8 @@ class BatchDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) - actual = sess.run(get_next) + self.evaluate(init_op) + actual = self.evaluate(get_next) expected = sparse_tensor.SparseTensorValue( indices=[[0, 0, 0], [0, 1, 0], [0, 2, 0], [0, 3, 0], [0, 4, 0], [1, 0, 0], [1, 1, 0], [1, 2, 0], [1, 3, 0], [1, 4, 0]], @@ -211,7 +211,7 @@ class BatchDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): next_element = iterator.get_next() with self.cached_session() as sess: - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) with self.assertRaisesRegexp( errors.InvalidArgumentError, r'Cannot batch tensors with different shapes in component 0. ' @@ -271,7 +271,7 @@ class PaddedBatchDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): num_full_batches = len(seq_lens) // batch_size for i in range(num_full_batches): - result = sess.run(get_next) + result = self.evaluate(get_next) padded_len = padded_shapes[0] if padded_len is None or padded_len == -1: padded_len = np.max(result) if result.size > 0 else 0 @@ -283,7 +283,7 @@ class PaddedBatchDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): [0] * (padded_len - seq_len)) if not drop_remainder and len(seq_lens) % batch_size > 0: - result = sess.run(get_next) + result = self.evaluate(get_next) padded_len = np.max(result) if result.size > 0 else 0 self.assertEqual((len(seq_lens) % batch_size, padded_len), result.shape) @@ -315,7 +315,7 @@ class PaddedBatchDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - result = sess.run(get_next) + result = self.evaluate(get_next) self.assertAllEqual([[], [], [], []], result) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -347,7 +347,7 @@ class PaddedBatchDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): seq_lens: random_seq_lens }) for i in range(8): - result = sess.run(get_next) + result = self.evaluate(get_next) padded_len = np.max(result[0]) self.assertEqual((4, padded_len), result[0].shape) self.assertEqual((4, padded_len), result[1].shape) diff --git a/tensorflow/python/data/kernel_tests/cache_dataset_op_test.py b/tensorflow/python/data/kernel_tests/cache_dataset_op_test.py index 63625fac03b..1f351279c69 100644 --- a/tensorflow/python/data/kernel_tests/cache_dataset_op_test.py +++ b/tensorflow/python/data/kernel_tests/cache_dataset_op_test.py @@ -71,7 +71,7 @@ class FileCacheDatasetTest(test_base.DatasetTestBase): with self.cached_session() as sess: # First run without caching to collect the "ground truth". - sess.run(init_fifo_op) + self.evaluate(init_fifo_op) elements = [] for _ in range(20): elements.append(sess.run(get_next)) @@ -220,14 +220,14 @@ class MemoryCacheDatasetTest(test_base.DatasetTestBase): with self.cached_session() as sess: - sess.run(repeat_count.initializer) - sess.run(cached_iterator.initializer) - sess.run(uncached_iterator.initializer) + self.evaluate(repeat_count.initializer) + self.evaluate(cached_iterator.initializer) + self.evaluate(uncached_iterator.initializer) for i in range(3): for _ in range(10): - self.assertEqual(sess.run(cached_next), i) - self.assertEqual(sess.run(uncached_next), i) + self.assertEqual(self.evaluate(cached_next), i) + self.assertEqual(self.evaluate(uncached_next), i) sess.run(repeat_count.assign(0)) @@ -238,7 +238,7 @@ class MemoryCacheDatasetTest(test_base.DatasetTestBase): # The cached iterator replays from cache. for i in range(3): for _ in range(10): - self.assertEqual(sess.run(cached_next), i) + self.assertEqual(self.evaluate(cached_next), i) # The cached iterator should now be empty. with self.assertRaises(errors.OutOfRangeError): @@ -280,7 +280,7 @@ class MemoryCacheDatasetTest(test_base.DatasetTestBase): i2 = d2.make_initializable_iterator() with self.cached_session() as sess: - sess.run(i1.initializer) + self.evaluate(i1.initializer) self.assertEqual(1, sess.run(i1.get_next())) self.assertEqual(2, sess.run(i1.get_next())) @@ -307,7 +307,7 @@ class MemoryCacheDatasetTest(test_base.DatasetTestBase): with self.cached_session() as sess: for i, expected in enumerate(expected_values): - self.assertEqual(expected, sess.run(n), + self.assertEqual(expected, self.evaluate(n), "Unexpected value at index %s" % i) with self.assertRaises(errors.OutOfRangeError): diff --git a/tensorflow/python/data/kernel_tests/concatenate_dataset_op_test.py b/tensorflow/python/data/kernel_tests/concatenate_dataset_op_test.py index 83af31f380e..a0ef69f0823 100644 --- a/tensorflow/python/data/kernel_tests/concatenate_dataset_op_test.py +++ b/tensorflow/python/data/kernel_tests/concatenate_dataset_op_test.py @@ -51,9 +51,9 @@ class ConcatenateDatasetTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for i in range(9): - result = sess.run(get_next) + result = self.evaluate(get_next) if i < 4: for component, result_component in zip(input_components, result): self.assertAllEqual(component[i], result_component) @@ -85,9 +85,9 @@ class ConcatenateDatasetTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for i in range(9): - result = sess.run(get_next) + result = self.evaluate(get_next) if i < 4: for component, result_component in zip(input_components, result): self.assertAllEqual(component[i], result_component) diff --git a/tensorflow/python/data/kernel_tests/dataset_constructor_op_test.py b/tensorflow/python/data/kernel_tests/dataset_constructor_op_test.py index bc6b36285aa..f7b500881c7 100644 --- a/tensorflow/python/data/kernel_tests/dataset_constructor_op_test.py +++ b/tensorflow/python/data/kernel_tests/dataset_constructor_op_test.py @@ -52,8 +52,8 @@ class DatasetConstructorTest(test_base.DatasetTestBase): [t.shape for t in get_next]) with self.cached_session() as sess: - sess.run(init_op) - results = sess.run(get_next) + self.evaluate(init_op) + results = self.evaluate(get_next) for component, result_component in zip(components, results): self.assertAllEqual(component, result_component) with self.assertRaises(errors.OutOfRangeError): @@ -81,8 +81,8 @@ class DatasetConstructorTest(test_base.DatasetTestBase): [shape for shape in iterator.output_shapes]) with self.cached_session() as sess: - sess.run(init_op) - results = sess.run(get_next) + self.evaluate(init_op) + results = self.evaluate(get_next) for component, result_component in zip(components, results): self.assertSparseValuesEqual(component, result_component) with self.assertRaises(errors.OutOfRangeError): @@ -112,8 +112,8 @@ class DatasetConstructorTest(test_base.DatasetTestBase): ], [shape for shape in iterator.output_shapes]) with self.cached_session() as sess: - sess.run(init_op) - results = sess.run(get_next) + self.evaluate(init_op) + results = self.evaluate(get_next) for component, result_component in zip(components, results): if sparse_tensor.is_sparse(component): self.assertSparseValuesEqual(component, result_component) @@ -139,9 +139,9 @@ class DatasetConstructorTest(test_base.DatasetTestBase): [t.shape for t in get_next]) with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for i in range(4): - results = sess.run(get_next) + results = self.evaluate(get_next) for component, result_component in zip(components, results): self.assertAllEqual(component[i], result_component) with self.assertRaises(errors.OutOfRangeError): @@ -169,7 +169,7 @@ class DatasetConstructorTest(test_base.DatasetTestBase): [shape for shape in iterator.output_shapes]) with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) expected = [ (sparse_tensor.SparseTensorValue( indices=np.array([[0]]), @@ -197,7 +197,7 @@ class DatasetConstructorTest(test_base.DatasetTestBase): dense_shape=np.array([3]))), ] for i in range(3): - results = sess.run(get_next) + results = self.evaluate(get_next) for component, result_component in zip(expected[i], results): self.assertSparseValuesEqual(component, result_component) with self.assertRaises(errors.OutOfRangeError): @@ -229,7 +229,7 @@ class DatasetConstructorTest(test_base.DatasetTestBase): ], [shape for shape in iterator.output_shapes]) with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) expected = [ (sparse_tensor.SparseTensorValue( indices=np.array([[0]]), @@ -257,7 +257,7 @@ class DatasetConstructorTest(test_base.DatasetTestBase): dense_shape=np.array([3]))), ] for i in range(3): - results = sess.run(get_next) + results = self.evaluate(get_next) for component, result_component in zip( (list(zip(*components[:3]))[i] + expected[i]), results): if sparse_tensor.is_sparse(component): @@ -280,9 +280,9 @@ class DatasetConstructorTest(test_base.DatasetTestBase): self.assertEqual((1,), iterator.output_shapes["bar"]) with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for i in range(3): - results = sess.run(get_next) + results = self.evaluate(get_next) self.assertEqual(components["foo"][i], results["foo"]) self.assertEqual(components["bar"][i], results["bar"]) with self.assertRaises(errors.OutOfRangeError): @@ -308,7 +308,7 @@ class DatasetConstructorTest(test_base.DatasetTestBase): dense_shape) sess.run(init_op, feed_dict={st: sparse_feed}) for i, s in enumerate(slices): - results = sess.run(get_next) + results = self.evaluate(get_next) self.assertAllEqual(s, results.values) expected_indices = np.array( [[j] for j in range(len(slices[i]))]).reshape([-1, 1]) @@ -474,15 +474,15 @@ class DatasetConstructorTest(test_base.DatasetTestBase): with ops.device("/cpu:0"): var_0 = resource_variable_ops.ResourceVariable(initial_value=0) dataset = dataset.map(lambda x: x + var_0.read_value()) - sess.run(var_0.initializer) + self.evaluate(var_0.initializer) with ops.device("/cpu:1"): var_1 = resource_variable_ops.ResourceVariable(initial_value=0) dataset = dataset.map(lambda x: x + var_1.read_value()) - sess.run(var_1.initializer) + self.evaluate(var_1.initializer) iterator = dataset.make_initializable_iterator() - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) with self.assertRaisesRegexp( errors.FailedPreconditionError, @@ -506,7 +506,7 @@ class DatasetConstructorBenchmark(test.Benchmark): next_element = iterator.get_next() with session.Session() as sess: - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) # Run one whole epoch to burn in the computation. for _ in range(input_size // batch_size): sess.run(next_element) @@ -543,7 +543,7 @@ class DatasetConstructorBenchmark(test.Benchmark): next_element = iterator.get_next() with session.Session() as sess: - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) get_next_element = sess.make_callable(next_element) # Run one whole epoch to burn in the computation. for _ in range(input_size // batch_size): @@ -582,7 +582,7 @@ class DatasetConstructorBenchmark(test.Benchmark): next_element = iterator.get_next() with session.Session() as sess: - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) get_next_element = sess.make_callable(next_element) # Run one whole epoch to burn in the computation. for _ in range(input_size // batch_size): @@ -620,7 +620,7 @@ class DatasetConstructorBenchmark(test.Benchmark): next_element = iterator.get_next() with session.Session() as sess: - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) get_next_element = sess.make_callable(next_element) # Run one whole epoch to burn in the computation. for _ in range(input_size // batch_size): diff --git a/tensorflow/python/data/kernel_tests/dataset_from_generator_op_test.py b/tensorflow/python/data/kernel_tests/dataset_from_generator_op_test.py index cb8cb9a77df..7087b4dd57f 100644 --- a/tensorflow/python/data/kernel_tests/dataset_from_generator_op_test.py +++ b/tensorflow/python/data/kernel_tests/dataset_from_generator_op_test.py @@ -47,10 +47,10 @@ class DatasetConstructorTest(test_base.DatasetTestBase): with self.cached_session() as sess: for _ in range(2): # Run twice to test reinitialization. - sess.run(init_op) + self.evaluate(init_op) for _ in range(num_repeats): for elem in elem_sequence: - self.assertAllEqual(elem, sess.run(get_next)) + self.assertAllEqual(elem, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -65,7 +65,7 @@ class DatasetConstructorTest(test_base.DatasetTestBase): with self.cached_session() as sess: for _ in range(num_repeats): for elem in elem_sequence: - self.assertAllEqual(elem, sess.run(get_next)) + self.assertAllEqual(elem, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -133,10 +133,10 @@ class DatasetConstructorTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for _ in range(num_inner_repeats * num_outer_repeats): for elem in input_list: - val0, val1 = sess.run(get_next) + val0, val1 = self.evaluate(get_next) self.assertAllEqual(elem[0], val0) self.assertAllEqual(elem[1], val1) with self.assertRaises(errors.OutOfRangeError): @@ -192,10 +192,10 @@ class DatasetConstructorTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for elem in [0, 1]: for _ in range(num_parallel_iterators): - self.assertAllEqual(elem, sess.run(get_next)) + self.assertAllEqual(elem, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -215,9 +215,9 @@ class DatasetConstructorTest(test_base.DatasetTestBase): self.assertEqual(dtype, get_next.dtype) with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for expected in [[1], [2], [3]]: - next_val = sess.run(get_next) + next_val = self.evaluate(get_next) self.assertEqual(dtype.as_numpy_dtype, next_val.dtype) self.assertAllEqual(expected, next_val) with self.assertRaises(errors.OutOfRangeError): @@ -236,9 +236,9 @@ class DatasetConstructorTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for expected in [b"foo", b"bar", b"baz"]: - next_val = sess.run(get_next) + next_val = self.evaluate(get_next) self.assertAllEqual(expected, next_val) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -257,12 +257,12 @@ class DatasetConstructorTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) - self.assertAllEqual([1, 2, 3], sess.run(get_next)) - self.assertAllEqual([4, 5, 6], sess.run(get_next)) + self.evaluate(init_op) + self.assertAllEqual([1, 2, 3], self.evaluate(get_next)) + self.assertAllEqual([4, 5, 6], self.evaluate(get_next)) with self.assertRaisesOpError("The expected type was int64"): sess.run(get_next) - self.assertAllEqual([7, 8, 9], sess.run(get_next)) + self.assertAllEqual([7, 8, 9], self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -280,12 +280,12 @@ class DatasetConstructorTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) - self.assertAllEqual([1, 2, 3], sess.run(get_next)) - self.assertAllEqual([4, 5, 6], sess.run(get_next)) + self.evaluate(init_op) + self.assertAllEqual([1, 2, 3], self.evaluate(get_next)) + self.assertAllEqual([4, 5, 6], self.evaluate(get_next)) with self.assertRaisesOpError(r"element of shape \(3,\) was expected"): sess.run(get_next) - self.assertAllEqual([11, 12, 13], sess.run(get_next)) + self.assertAllEqual([11, 12, 13], self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -304,16 +304,16 @@ class DatasetConstructorTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) - self.assertEqual((1, 2), sess.run(get_next)) - self.assertEqual((3, 4), sess.run(get_next)) + self.evaluate(init_op) + self.assertEqual((1, 2), self.evaluate(get_next)) + self.assertEqual((3, 4), self.evaluate(get_next)) with self.assertRaisesOpError( r"The expected structure was \(tf\.int64, tf\.int64\)"): sess.run(get_next) with self.assertRaisesOpError( r"The expected structure was \(tf\.int64, tf\.int64\)"): sess.run(get_next) - self.assertEqual((9, 10), sess.run(get_next)) + self.assertEqual((9, 10), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -329,9 +329,9 @@ class DatasetConstructorTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) - self.assertAllEqual(1, sess.run(get_next)) - self.assertAllEqual([2, 3], sess.run(get_next)) + self.evaluate(init_op) + self.assertAllEqual(1, self.evaluate(get_next)) + self.assertAllEqual([2, 3], self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -349,9 +349,9 @@ class DatasetConstructorTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) - self.assertAllEqual(0, sess.run(get_next)) - self.assertAllEqual(1, sess.run(get_next)) + self.evaluate(init_op) + self.assertAllEqual(0, self.evaluate(get_next)) + self.assertAllEqual(1, self.evaluate(get_next)) def testFromGeneratorDestructorCalled(self): # Use an `Event` to signal that the generator has been deleted. @@ -378,9 +378,9 @@ class DatasetConstructorTest(test_base.DatasetTestBase): get_next = iterator.get_next() with session.Session() as sess: - sess.run(init_op) - self.assertAllEqual(42, sess.run(get_next)) - self.assertAllEqual(42, sess.run(get_next)) + self.evaluate(init_op) + self.assertAllEqual(42, self.evaluate(get_next)) + self.assertAllEqual(42, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) # Test that `GeneratorWrapper` object is destroyed when the @@ -407,10 +407,10 @@ class DatasetConstructorTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) expected = [1, 2, 2, 3, 3, 3, 4, 4, 4, 4] for x in expected: - self.assertEqual(x, sess.run(get_next)) + self.assertEqual(x, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -436,13 +436,13 @@ class DatasetConstructorTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) expected = [(0, b"Hi!"), (0, b"Hi!"), (1, b"Hi!"), (0, b"Hi!"), (1, b"Hi!"), (2, b"Hi!"), (0, b"Hi!"), (1, b"Hi!"), (2, b"Hi!"), (3, b"Hi!")] for x in expected: - self.assertEqual(x, sess.run(get_next)) + self.assertEqual(x, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -470,9 +470,9 @@ class DatasetConstructorTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) - self.assertAllEqual(37, sess.run(get_next)) - self.assertAllEqual(37, sess.run(get_next)) + self.evaluate(init_op) + self.assertAllEqual(37, self.evaluate(get_next)) + self.assertAllEqual(37, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) self.assertTrue(event.is_set()) diff --git a/tensorflow/python/data/kernel_tests/filter_dataset_op_test.py b/tensorflow/python/data/kernel_tests/filter_dataset_op_test.py index a0c6b37a6dc..5ddb22285f9 100644 --- a/tensorflow/python/data/kernel_tests/filter_dataset_op_test.py +++ b/tensorflow/python/data/kernel_tests/filter_dataset_op_test.py @@ -67,7 +67,7 @@ class FilterDatasetTest(test_base.DatasetTestBase): sess.run(init_op, feed_dict={count: count_val, modulus: modulus_val}) for _ in range(count_val): for i in [x for x in range(7) if x**2 % modulus_val == 0]: - result = sess.run(get_next) + result = self.evaluate(get_next) for component, result_component in zip(components, result): self.assertAllEqual(component[i]**2, result_component) with self.assertRaises(errors.OutOfRangeError): @@ -86,9 +86,9 @@ class FilterDatasetTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - self.assertEqual(0, sess.run(get_next)) - self.assertEqual(1, sess.run(get_next)) - self.assertEqual(3, sess.run(get_next)) + self.assertEqual(0, self.evaluate(get_next)) + self.assertEqual(1, self.evaluate(get_next)) + self.assertEqual(3, self.evaluate(get_next)) def testFilterDict(self): iterator = (dataset_ops.Dataset.range(10) @@ -100,10 +100,10 @@ class FilterDatasetTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for i in range(10): if (i ** 2) % 2 == 0: - self.assertEqual(i * 2 + i ** 2, sess.run(get_next)) + self.assertEqual(i * 2 + i**2, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -125,8 +125,8 @@ class FilterDatasetTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) - self.assertAllEqual(input_data[0], sess.run(get_next)) + self.evaluate(init_op) + self.assertAllEqual(input_data[0], self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -148,9 +148,9 @@ class FilterDatasetTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for i in range(5): - actual = sess.run(get_next) + actual = self.evaluate(get_next) self.assertTrue(isinstance(actual, sparse_tensor.SparseTensorValue)) self.assertSparseValuesEqual(actual, _map_fn(i * 2)[0]) with self.assertRaises(errors.OutOfRangeError): @@ -166,9 +166,9 @@ class FilterDatasetTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for i in range(10): - self.assertEqual((i, True), sess.run(get_next)) + self.assertEqual((i, True), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -178,7 +178,7 @@ class FilterDatasetTest(test_base.DatasetTestBase): iterators = [dataset.make_one_shot_iterator() for _ in range(10)] next_elements = [iterator.get_next() for iterator in iterators] with self.cached_session() as sess: - self.assertEqual([0 for _ in range(10)], sess.run(next_elements)) + self.assertEqual([0 for _ in range(10)], self.evaluate(next_elements)) class FilterDatasetBenchmark(test.Benchmark): diff --git a/tensorflow/python/data/kernel_tests/flat_map_dataset_op_test.py b/tensorflow/python/data/kernel_tests/flat_map_dataset_op_test.py index 68038f9cfc0..02979fc2c40 100644 --- a/tensorflow/python/data/kernel_tests/flat_map_dataset_op_test.py +++ b/tensorflow/python/data/kernel_tests/flat_map_dataset_op_test.py @@ -45,10 +45,10 @@ class FlatMapDatasetTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for i in repeats: for _ in range(i): - self.assertEqual(i, sess.run(get_next)) + self.assertEqual(i, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -64,11 +64,11 @@ class FlatMapDatasetTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for row in repeats: for i in row: for _ in range(i): - self.assertEqual(i, sess.run(get_next)) + self.assertEqual(i, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -94,12 +94,12 @@ class FlatMapDatasetTest(test_base.DatasetTestBase): with session.Session(server.target) as sess2: for _ in range(3): sess = random.choice([sess1, sess2]) - sess.run(init_op) + self.evaluate(init_op) for row in repeats: for i in row: for _ in range(i): sess = random.choice([sess1, sess2]) - self.assertEqual(i, sess.run(get_next)) + self.assertEqual(i, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess = random.choice([sess1, sess2]) @@ -115,10 +115,10 @@ class FlatMapDatasetTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for i in range(10): for _ in range(i ** 2): - self.assertEqual(i * 2, sess.run(get_next)) + self.assertEqual(i * 2, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) # pylint: enable=g-long-lambda @@ -139,11 +139,11 @@ class FlatMapDatasetTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for i in range(10): for j in range(2): expected = [i, 0] if j % 2 == 0 else [0, -i] - self.assertAllEqual(expected, sess.run(get_next)) + self.assertAllEqual(expected, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) diff --git a/tensorflow/python/data/kernel_tests/interleave_dataset_op_test.py b/tensorflow/python/data/kernel_tests/interleave_dataset_op_test.py index b911c249ced..56434d6e4c4 100644 --- a/tensorflow/python/data/kernel_tests/interleave_dataset_op_test.py +++ b/tensorflow/python/data/kernel_tests/interleave_dataset_op_test.py @@ -196,7 +196,7 @@ class InterleaveDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): with self.cached_session() as sess: for expected_element in _interleave( _repeat(input_values, count), cycle_length, block_length): - self.assertEqual(expected_element, sess.run(get_next)) + self.assertEqual(expected_element, self.evaluate(get_next)) for _ in range(2): with self.assertRaises(errors.OutOfRangeError): @@ -231,7 +231,7 @@ class InterleaveDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): with self.assertRaises(errors.InvalidArgumentError): sess.run(get_next) else: - self.assertEqual(value, sess.run(get_next)) + self.assertEqual(value, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -254,7 +254,7 @@ class InterleaveDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): for i in range(10): for j in range(2): expected = [i, 0] if j % 2 == 0 else [0, -i] - self.assertAllEqual(expected, sess.run(get_next)) + self.assertAllEqual(expected, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -308,7 +308,7 @@ class InterleaveDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): for element in elements: coordination_events[element].set() - self.assertEqual(element * element, sess.run(get_next)) + self.assertEqual(element * element, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) diff --git a/tensorflow/python/data/kernel_tests/iterator_ops_cluster_test.py b/tensorflow/python/data/kernel_tests/iterator_ops_cluster_test.py index bf5fd781d65..cb38728f238 100644 --- a/tensorflow/python/data/kernel_tests/iterator_ops_cluster_test.py +++ b/tensorflow/python/data/kernel_tests/iterator_ops_cluster_test.py @@ -57,7 +57,7 @@ class IteratorClusterTest(test.TestCase): with session.Session(worker[0].target) as sess: with self.assertRaises(errors.InvalidArgumentError): - sess.run(get_next_op) + self.evaluate(get_next_op) def _testRemoteIteratorHelper(self, device0, device1, target): with ops.device(device1): @@ -134,12 +134,12 @@ class IteratorClusterTest(test.TestCase): get_next = iterator.get_next() with session.Session(worker[0].target) as sess: - sess.run(table.initializer) - sess.run(init_op) - self.assertAllEqual([0, 0, -1, 1, 2], sess.run(get_next)) + self.evaluate(table.initializer) + self.evaluate(init_op) + self.assertAllEqual([0, 0, -1, 1, 2], self.evaluate(get_next)) with session.Session(worker[0].target) as sess: - self.assertAllEqual([2, 0], sess.run(get_next)) + self.assertAllEqual([2, 0], self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -166,7 +166,7 @@ class IteratorClusterTest(test.TestCase): get_next = iterator.get_next() with session.Session(worker[0].target) as sess: - sess.run(init_op) + self.evaluate(init_op) for _ in range(3): sess.run(get_next) diff --git a/tensorflow/python/data/kernel_tests/iterator_ops_test.py b/tensorflow/python/data/kernel_tests/iterator_ops_test.py index 490ca813dce..405d94d9564 100644 --- a/tensorflow/python/data/kernel_tests/iterator_ops_test.py +++ b/tensorflow/python/data/kernel_tests/iterator_ops_test.py @@ -97,7 +97,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase): with self.cached_session() as sess: for _ in range(14): for i in range(7): - result = sess.run(get_next) + result = self.evaluate(get_next) for component, result_component in zip(components, result): self.assertAllEqual(component[i]**2, result_component) with self.assertRaises(errors.OutOfRangeError): @@ -123,7 +123,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase): with self.cached_session() as sess: for _ in range(14): for i in range(7): - result = sess.run(get_next) + result = self.evaluate(get_next) for component, result_component in zip(components, result): self.assertAllEqual(component[i]**2, result_component) with self.assertRaises(errors.OutOfRangeError): @@ -159,7 +159,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase): for _ in range(14): for i in range(7): - result = sess.run(get_next) + result = self.evaluate(get_next) for component, result_component in zip(components, result): self.assertAllEqual(component[i]**2, result_component) with self.assertRaises(errors.OutOfRangeError): @@ -175,7 +175,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase): config = config_pb2.ConfigProto( inter_op_parallelism_threads=1, use_per_session_threads=True) with session.Session(config=config) as sess: - self.assertAllEqual([1, 4, 9], sess.run(next_element)) + self.assertAllEqual([1, 4, 9], self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -254,15 +254,15 @@ class IteratorTest(test.TestCase, parameterized.TestCase): get_next = iterator.get_next() with session.Session(server.target) as sess: - sess.run(init_op) - results = sess.run(get_next) + self.evaluate(init_op) + results = self.evaluate(get_next) for component, result_component in zip(components, results): self.assertAllEqual(component, result_component) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) # Re-initialize the iterator in the first session. - sess.run(init_op) + self.evaluate(init_op) with ops.Graph().as_default(): # Re-define the iterator manually, without defining any of the @@ -277,7 +277,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase): with session.Session(server.target) as sess: # Use the iterator without re-initializing in the second session. - results = sess.run(get_next) + results = self.evaluate(get_next) for component, result_component in zip(components, results): self.assertAllEqual(component, result_component) with self.assertRaises(errors.OutOfRangeError): @@ -317,20 +317,20 @@ class IteratorTest(test.TestCase, parameterized.TestCase): sess.run(get_next) # Initialize with one dataset. - sess.run(dataset_3_init_op) - self.assertAllEqual([1, 2, 3], sess.run(get_next)) + self.evaluate(dataset_3_init_op) + self.assertAllEqual([1, 2, 3], self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) # Initialize with a different dataset. - sess.run(dataset_4_init_op) - self.assertAllEqual([4, 5, 6, 7], sess.run(get_next)) + self.evaluate(dataset_4_init_op) + self.assertAllEqual([4, 5, 6, 7], self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) # Reinitialize with the first dataset. - sess.run(dataset_3_init_op) - self.assertAllEqual([1, 2, 3], sess.run(get_next)) + self.evaluate(dataset_3_init_op) + self.assertAllEqual([1, 2, 3], self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -348,7 +348,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase): g, output_types=dtypes.int64) sess.run(iterator.make_initializer(dataset_1)) for expected in range(10): - self.assertEqual(expected, sess.run(next_element)) + self.assertEqual(expected, self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -356,7 +356,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase): g, output_types=dtypes.int64) sess.run(iterator.make_initializer(dataset_2)) for expected in range(10): - self.assertEqual(expected, sess.run(next_element)) + self.assertEqual(expected, self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -679,10 +679,10 @@ class IteratorTest(test.TestCase, parameterized.TestCase): n = itr.get_next() with session.Session(s3.target, config=config) as sess: - sess.run(itr.initializer) + self.evaluate(itr.initializer) expected_values = worker_devices for expected in expected_values: - self.assertEqual((compat.as_bytes(expected),), sess.run(n)) + self.assertEqual((compat.as_bytes(expected),), self.evaluate(n)) with self.assertRaises(errors.OutOfRangeError): sess.run(n) @@ -786,8 +786,8 @@ class IteratorTest(test.TestCase, parameterized.TestCase): with ops.Graph().as_default() as g: init_op, _, save_op, _ = _build_range_dataset_graph() with self.session(graph=g) as sess: - sess.run(init_op) - sess.run(save_op) + self.evaluate(init_op) + self.evaluate(save_op) # Attempt to restore the saved iterator into an IteratorResource of # incompatible type. An iterator of RangeDataset has output type int64, @@ -798,7 +798,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase): _, _, _, restore_op = _build_reader_dataset_graph() with self.session(graph=g) as sess: with self.assertRaises(errors.InvalidArgumentError): - sess.run(restore_op) + self.evaluate(restore_op) def testRepeatedGetNextWarning(self): iterator = dataset_ops.Dataset.range(10).make_one_shot_iterator() @@ -949,7 +949,7 @@ class IteratorCheckpointingTest(test.TestCase): checkpoint.restore(checkpoint_management.latest_checkpoint( checkpoint_directory)).initialize_or_restore(sess) for j in range(2): - self.assertEqual(i * 2 + j, sess.run(get_next)) + self.assertEqual(i * 2 + j, self.evaluate(get_next)) checkpoint.save(file_prefix=checkpoint_prefix) diff --git a/tensorflow/python/data/kernel_tests/list_files_dataset_op_test.py b/tensorflow/python/data/kernel_tests/list_files_dataset_op_test.py index b58c1444dae..ac6fbabcd59 100644 --- a/tensorflow/python/data/kernel_tests/list_files_dataset_op_test.py +++ b/tensorflow/python/data/kernel_tests/list_files_dataset_op_test.py @@ -102,7 +102,7 @@ class ListFilesDatasetOpTest(test_base.DatasetTestBase): all_produced_filenames = [] for _ in range(3): produced_filenames = [] - sess.run(itr.initializer) + self.evaluate(itr.initializer) try: while True: produced_filenames.append(sess.run(next_element)) diff --git a/tensorflow/python/data/kernel_tests/map_dataset_op_test.py b/tensorflow/python/data/kernel_tests/map_dataset_op_test.py index 187b9da14ce..8f7a19d7e1b 100644 --- a/tensorflow/python/data/kernel_tests/map_dataset_op_test.py +++ b/tensorflow/python/data/kernel_tests/map_dataset_op_test.py @@ -114,7 +114,7 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): sess.run(init_op, feed_dict={count: 14}) for _ in range(14): for i in range(7): - result = sess.run(get_next) + result = self.evaluate(get_next) for component, result_component in zip(components, result): self.assertAllEqual(component[i]**2, result_component) with self.assertRaises(errors.OutOfRangeError): @@ -185,7 +185,7 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): output_buffer_size: output_buffer_size_val}) for _ in range(14): for i in range(7): - result = sess.run(get_next) + result = self.evaluate(get_next) for component, result_component in zip(components, result): self.assertAllEqual(component[i]**2, result_component) with self.assertRaises(errors.OutOfRangeError): @@ -242,7 +242,7 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for _ in range(3): sess.run(get_next) @@ -257,7 +257,7 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for _ in range(3): sess.run(get_next) @@ -272,7 +272,7 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for _ in range(3): sess.run(get_next) # The 4th element is NaN, so `array_ops.check_numerics()` should fail. @@ -293,7 +293,7 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for _ in range(3): sess.run(get_next) # The 4th element is NaN, so `array_ops.check_numerics()` should fail. @@ -325,10 +325,10 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): with ops.Graph().as_default() as g: captured_init_op, init_op, get_next = _build_graph() with self.session(graph=g) as sess: - sess.run(captured_init_op) - sess.run(init_op) + self.evaluate(captured_init_op) + self.evaluate(init_op) for i in range(10): - self.assertEqual(i * i, sess.run(get_next)) + self.assertEqual(i * i, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -353,8 +353,8 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(table.initializer) - sess.run(init_op) + self.evaluate(table.initializer) + self.evaluate(init_op) sess.run(get_next) sess.run(get_next) with self.assertRaises(errors.OutOfRangeError): @@ -371,11 +371,11 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(enqueue_op) - sess.run(close_op) - sess.run(init_op) + self.evaluate(enqueue_op) + self.evaluate(close_op) + self.evaluate(init_op) for element in elements: - self.assertEqual(element, sess.run(get_next)) + self.assertEqual(element, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -396,9 +396,9 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(enqueue_op) - sess.run(close_op) - sess.run(init_op) + self.evaluate(enqueue_op) + self.evaluate(close_op) + self.evaluate(init_op) for i in range(100): self.assertEqual(sorted([elements[i * 2], elements[i * 2 + 1]]), sorted(sess.run(get_next))) @@ -415,15 +415,15 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(counter_var.initializer) - sess.run(init_op) + self.evaluate(counter_var.initializer) + self.evaluate(init_op) for i in range(10): - self.assertEqual(i, sess.run(counter_var)) - self.assertEqual(i + 1, sess.run(get_next)) - self.assertEqual(10, sess.run(counter_var)) + self.assertEqual(i, self.evaluate(counter_var)) + self.assertEqual(i + 1, self.evaluate(get_next)) + self.assertEqual(10, self.evaluate(counter_var)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) - self.assertEqual(10, sess.run(counter_var)) + self.assertEqual(10, self.evaluate(counter_var)) def testCaptureUninitializedVariableError(self): counter_var = variable_scope.get_variable( @@ -435,7 +435,7 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) with self.assertRaises(errors.NotFoundError): sess.run(get_next) @@ -447,14 +447,14 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) random_values = [] with self.assertRaises(errors.OutOfRangeError): while True: random_values.extend(sess.run(get_next)) self.assertEqual(10, len(random_values)) self.assertGreater(np.abs(np.diff(random_values)).max(), 1e-6) - sess.run(init_op) + self.evaluate(init_op) random_values_2 = [] with self.assertRaises(errors.OutOfRangeError): while True: @@ -473,8 +473,8 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) - random_values = sess.run(get_next) + self.evaluate(init_op) + random_values = self.evaluate(get_next) # Assert that one of the next 99 batches yielded by the iterator is # different from the first. @@ -500,15 +500,15 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(counter_var.initializer) - sess.run(init_op) + self.evaluate(counter_var.initializer) + self.evaluate(init_op) for i in range(10): - self.assertEqual(i, sess.run(counter_var)) - self.assertEqual(i, sess.run(get_next)) - self.assertEqual(10, sess.run(counter_var)) + self.assertEqual(i, self.evaluate(counter_var)) + self.assertEqual(i, self.evaluate(get_next)) + self.assertEqual(10, self.evaluate(counter_var)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) - self.assertEqual(10, sess.run(counter_var)) + self.assertEqual(10, self.evaluate(counter_var)) def testMapDict(self): iterator = (dataset_ops.Dataset.range(10) @@ -519,9 +519,9 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for i in range(10): - self.assertEqual(i * 2 + i ** 2, sess.run(get_next)) + self.assertEqual(i * 2 + i**2, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -569,8 +569,8 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) - self.assertAllEqual(row ** 2, sess.run(get_next)) + self.evaluate(init_op) + self.assertAllEqual(row**2, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -611,7 +611,7 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): row = np.arange(6) for num in [2, 3, 4]: init_op, get_next = build_dataset(row, num) - sess.run(init_op) + self.evaluate(init_op) for i in range(6): self.assertEqual( (i // 2 if i % 2 else i * 2) if (num == 2 or num == 3) else i * 2, @@ -652,7 +652,7 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): row = np.arange(6) for num in [2, 3, 4]: init_op, get_next = build_dataset(row, num) - sess.run(init_op) + self.evaluate(init_op) self.assertAllEqual( [x // 2 if (num == 2 or num == 3) else x * 2 for x in row], sess.run(get_next)) @@ -697,7 +697,7 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) self.assertAllEqual([(x // 2 if x % 2 else x * 2) if (num == 2 or num == 3) else x * 2 for x in row], sess.run(get_next)) @@ -735,7 +735,7 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): for buffer_size in [1, 10, 100, 1000]: sess.run(init_op, feed_dict={buffer_size_placeholder: buffer_size}) for i in range(100): - self.assertEqual(i * i, sess.run(get_next)) + self.assertEqual(i * i, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -753,10 +753,10 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): sess.run(init_op, feed_dict={buffer_size_placeholder: buffer_size}) for i in range(event_will_be_set_after_consuming): self.assertFalse(ev.is_set()) - self.assertEqual(i * i, sess.run(get_next)) + self.assertEqual(i * i, self.evaluate(get_next)) ev.wait() for i in range(event_will_be_set_after_consuming, 100): - self.assertEqual(i * i, sess.run(get_next)) + self.assertEqual(i * i, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -768,9 +768,9 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for i in range(10): - self.assertEqual((i, 37.0), sess.run(get_next)) + self.assertEqual((i, 37.0), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -789,9 +789,9 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for i in range(10): - self.assertEqual((i, 37.0), sess.run(get_next)) + self.assertEqual((i, 37.0), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -810,9 +810,9 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for i in range(10): - actual = sess.run(get_next) + actual = self.evaluate(get_next) self.assertIsInstance(actual, sparse_tensor.SparseTensorValue) self.assertSparseValuesEqual(actual, _sparse(i)) with self.assertRaises(errors.OutOfRangeError): @@ -837,9 +837,9 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for i in range(10): - actual = sess.run(get_next) + actual = self.evaluate(get_next) self.assertIsInstance(actual, sparse_tensor.SparseTensorValue) self.assertSparseValuesEqual(actual, _check(_sparse(i)).eval()) with self.assertRaises(errors.OutOfRangeError): @@ -861,9 +861,9 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for i in range(100): - self.assertEqual(i, sess.run(get_next)) + self.assertEqual(i, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -875,9 +875,9 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for i in range(10): - self.assertEqual((i, b"hello", 10), sess.run(get_next)) + self.assertEqual((i, b"hello", 10), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -945,7 +945,7 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): with self.cached_session() as sess: with self.assertRaisesRegexp(errors.InvalidArgumentError, "BrokenConst"): - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) # pylint: disable=g-long-lambda @parameterized.named_parameters( @@ -972,7 +972,7 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - tids = sess.run(get_next) + tids = self.evaluate(get_next) self.assertTrue(all(tids[0] == tid for tid in tids)) # pylint: enable=g-long-lambda @@ -996,7 +996,7 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): expected = map_fn(*sess.run(self.structuredElement(structure))) else: expected = map_fn(sess.run(self.structuredElement(structure))) - self.assertEqual(expected, sess.run(get_next)) + self.assertEqual(expected, self.evaluate(get_next)) @parameterized.named_parameters( ("Sequential", None), @@ -1011,7 +1011,7 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): with self.cached_session() as sess: sess.run(iterator.initializer, feed_dict={captured_t: 42}) - self.assertEqual(42, sess.run(get_next)) + self.assertEqual(42, self.evaluate(get_next)) @parameterized.named_parameters( ("1", 1, 1), @@ -1030,7 +1030,7 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): with self.cached_session(config=config) as sess: for i in range(num_elements): coordination_events[i].set() - self.assertEqual(i * i, sess.run(get_next)) + self.assertEqual(i * i, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -1052,7 +1052,7 @@ class MapDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): for element in elements: coordination_events[element].set() - self.assertEqual(element * element, sess.run(get_next)) + self.assertEqual(element * element, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) diff --git a/tensorflow/python/data/kernel_tests/multi_device_iterator_test.py b/tensorflow/python/data/kernel_tests/multi_device_iterator_test.py index 42ee1e21864..ea6828e575b 100644 --- a/tensorflow/python/data/kernel_tests/multi_device_iterator_test.py +++ b/tensorflow/python/data/kernel_tests/multi_device_iterator_test.py @@ -40,7 +40,7 @@ class MultiDeviceIteratorTest(test_base.DatasetTestBase): config = config_pb2.ConfigProto(device_count={"CPU": 3}) with self.test_session(config=config) as sess: - sess.run(multi_device_iterator.initializer) + self.evaluate(multi_device_iterator.initializer) def testBasic(self): dataset = dataset_ops.Dataset.range(10) @@ -50,10 +50,10 @@ class MultiDeviceIteratorTest(test_base.DatasetTestBase): config = config_pb2.ConfigProto(device_count={"CPU": 3}) with self.test_session(config=config) as sess: - sess.run(multi_device_iterator.initializer) + self.evaluate(multi_device_iterator.initializer) for i in range(0, 10, 2): - self.assertEqual(i, sess.run(elem_on_1)) - self.assertEqual(i + 1, sess.run(elem_on_2)) + self.assertEqual(i, self.evaluate(elem_on_1)) + self.assertEqual(i + 1, self.evaluate(elem_on_2)) with self.assertRaises(errors.OutOfRangeError): sess.run(elem_on_1) sess.run(elem_on_2) @@ -67,10 +67,10 @@ class MultiDeviceIteratorTest(test_base.DatasetTestBase): config = config_pb2.ConfigProto(device_count={"CPU": 2}) with self.test_session(config=config) as sess: - sess.run(multi_device_iterator.initializer) + self.evaluate(multi_device_iterator.initializer) for i in range(0, 10, 2): - self.assertEqual(i, sess.run(elem_on_1)) - self.assertEqual(i + 1, sess.run(elem_on_2)) + self.assertEqual(i, self.evaluate(elem_on_1)) + self.assertEqual(i + 1, self.evaluate(elem_on_2)) with self.assertRaises(errors.OutOfRangeError): sess.run(elem_on_1) sess.run(elem_on_2) @@ -85,12 +85,12 @@ class MultiDeviceIteratorTest(test_base.DatasetTestBase): config = config_pb2.ConfigProto(device_count={"CPU": 3}) with self.test_session(config=config) as sess: - sess.run(multi_device_iterator.initializer) + self.evaluate(multi_device_iterator.initializer) for i in range(0, 20, 4): - self.assertEqual(i, sess.run(elem_on_1)) - self.assertEqual(i + 1, sess.run(elem_on_2)) - self.assertEqual(i + 2, sess.run(elem_on_3)) - self.assertEqual(i + 3, sess.run(elem_on_4)) + self.assertEqual(i, self.evaluate(elem_on_1)) + self.assertEqual(i + 1, self.evaluate(elem_on_2)) + self.assertEqual(i + 2, self.evaluate(elem_on_3)) + self.assertEqual(i + 3, self.evaluate(elem_on_4)) with self.assertRaises(errors.OutOfRangeError): sess.run(elem_on_1) sess.run(elem_on_2) @@ -105,11 +105,11 @@ class MultiDeviceIteratorTest(test_base.DatasetTestBase): config = config_pb2.ConfigProto(device_count={"CPU": 3}) with self.test_session(config=config) as sess: - sess.run(multi_device_iterator.initializer) + self.evaluate(multi_device_iterator.initializer) for i in range(0, 8, 2): - self.assertEqual(i, sess.run(elem_on_1)) - self.assertEqual(i + 1, sess.run(elem_on_2)) - self.assertEqual(8, sess.run(elem_on_1)) + self.assertEqual(i, self.evaluate(elem_on_1)) + self.assertEqual(i + 1, self.evaluate(elem_on_2)) + self.assertEqual(8, self.evaluate(elem_on_1)) with self.assertRaises(errors.OutOfRangeError): sess.run(elem_on_1) sess.run(elem_on_2) @@ -126,7 +126,7 @@ class MultiDeviceIteratorTest(test_base.DatasetTestBase): config = config_pb2.ConfigProto(device_count={"CPU": 3}) with self.test_session(config=config) as sess: - sess.run(multi_device_iterator.initializer) + self.evaluate(multi_device_iterator.initializer) for i in range(0, 8, 2): elem_on_1_has_value, elem_on_1_value = sess.run( [elem_on_1_has_value_t, elem_on_1_t]) @@ -140,8 +140,8 @@ class MultiDeviceIteratorTest(test_base.DatasetTestBase): [elem_on_1_has_value_t, elem_on_1_t]) self.assertTrue(elem_on_1_has_value) self.assertEqual(8, elem_on_1_value) - self.assertFalse(sess.run(elem_on_1_has_value_t)) - self.assertFalse(sess.run(elem_on_2_has_value_t)) + self.assertFalse(self.evaluate(elem_on_1_has_value_t)) + self.assertFalse(self.evaluate(elem_on_2_has_value_t)) with self.assertRaises(errors.InvalidArgumentError): sess.run(elem_on_1_t) with self.assertRaises(errors.InvalidArgumentError): @@ -155,11 +155,11 @@ class MultiDeviceIteratorTest(test_base.DatasetTestBase): config = config_pb2.ConfigProto(device_count={"CPU": 3}) with self.test_session(config=config) as sess: - sess.run(multi_device_iterator.initializer) + self.evaluate(multi_device_iterator.initializer) for i in range(0, 10, 2): - self.assertEqual(i, sess.run(elem_on_1)) + self.assertEqual(i, self.evaluate(elem_on_1)) for i in range(0, 10, 2): - self.assertEqual(i + 1, sess.run(elem_on_2)) + self.assertEqual(i + 1, self.evaluate(elem_on_2)) with self.assertRaises(errors.OutOfRangeError): sess.run(elem_on_1) sess.run(elem_on_2) @@ -192,10 +192,10 @@ class MultiDeviceIteratorTest(test_base.DatasetTestBase): config = config_pb2.ConfigProto(device_count={"CPU": 2, "GPU": 1}) with self.test_session(config=config) as sess: - sess.run(multi_device_iterator.initializer) + self.evaluate(multi_device_iterator.initializer) for i in range(0, 10, 2): - self.assertEqual(i, sess.run(elem_on_1)) - self.assertEqual(i + 1, sess.run(elem_on_2)) + self.assertEqual(i, self.evaluate(elem_on_1)) + self.assertEqual(i + 1, self.evaluate(elem_on_2)) with self.assertRaises(errors.OutOfRangeError): sess.run(elem_on_1) sess.run(elem_on_2) @@ -211,11 +211,11 @@ class MultiDeviceIteratorTest(test_base.DatasetTestBase): config = config_pb2.ConfigProto(device_count={"CPU": 2, "GPU": 1}) with self.test_session(config=config) as sess: - sess.run(multi_device_iterator.initializer) + self.evaluate(multi_device_iterator.initializer) for i in range(0, 10, 2): - self.assertEqual(i, sess.run(elem_on_1)) + self.assertEqual(i, self.evaluate(elem_on_1)) for i in range(0, 10, 2): - self.assertEqual(i + 1, sess.run(elem_on_2)) + self.assertEqual(i + 1, self.evaluate(elem_on_2)) with self.assertRaises(errors.OutOfRangeError): sess.run(elem_on_1) sess.run(elem_on_2) @@ -235,7 +235,7 @@ class MultiDeviceIteratorTest(test_base.DatasetTestBase): config = config_pb2.ConfigProto(device_count={"CPU": 2, "GPU": 1}) with self.test_session(config=config) as sess: - sess.run(multi_device_iterator.initializer) + self.evaluate(multi_device_iterator.initializer) for i in range(0, 8, 2): elem_on_1_has_value, elem_on_1_value = sess.run( [elem_on_1_has_value_t, elem_on_1_t]) @@ -249,8 +249,8 @@ class MultiDeviceIteratorTest(test_base.DatasetTestBase): [elem_on_1_has_value_t, elem_on_1_t]) self.assertTrue(elem_on_1_has_value) self.assertEqual(8, elem_on_1_value) - self.assertFalse(sess.run(elem_on_1_has_value_t)) - self.assertFalse(sess.run(elem_on_2_has_value_t)) + self.assertFalse(self.evaluate(elem_on_1_has_value_t)) + self.assertFalse(self.evaluate(elem_on_2_has_value_t)) with self.assertRaises(errors.InvalidArgumentError): sess.run(elem_on_1_t) with self.assertRaises(errors.InvalidArgumentError): @@ -272,10 +272,10 @@ class MultiDeviceIteratorTest(test_base.DatasetTestBase): config = config_pb2.ConfigProto(device_count={"CPU": 3}) with self.test_session(config=config) as sess: - sess.run(multi_device_iterator.initializer) + self.evaluate(multi_device_iterator.initializer) for i in range(0, 10, 2): - self.assertEqual(i, sess.run(elem_on_1)) - self.assertEqual(i + 1, sess.run(elem_on_2)) + self.assertEqual(i, self.evaluate(elem_on_1)) + self.assertEqual(i + 1, self.evaluate(elem_on_2)) with self.assertRaises(errors.OutOfRangeError): sess.run(elem_on_1) sess.run(elem_on_2) diff --git a/tensorflow/python/data/kernel_tests/optional_ops_test.py b/tensorflow/python/data/kernel_tests/optional_ops_test.py index 604e3ad88ec..0981ff9651a 100644 --- a/tensorflow/python/data/kernel_tests/optional_ops_test.py +++ b/tensorflow/python/data/kernel_tests/optional_ops_test.py @@ -227,7 +227,7 @@ class OptionalTest(test_base.DatasetTestBase, parameterized.TestCase): # For each element of the dataset, assert that the optional evaluates to # the expected value. - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) for _ in range(3): elem_has_value, elem_value = sess.run([elem_has_value_t, elem_value_t]) self.assertTrue(elem_has_value) @@ -236,7 +236,7 @@ class OptionalTest(test_base.DatasetTestBase, parameterized.TestCase): # After exhausting the iterator, `next_elem.has_value()` will evaluate to # false, and attempting to get the value will fail. for _ in range(2): - self.assertFalse(sess.run(elem_has_value_t)) + self.assertFalse(self.evaluate(elem_has_value_t)) with self.assertRaises(errors.InvalidArgumentError): sess.run(elem_value_t) diff --git a/tensorflow/python/data/kernel_tests/prefetch_dataset_op_test.py b/tensorflow/python/data/kernel_tests/prefetch_dataset_op_test.py index 76e2697b29d..af326ec210f 100644 --- a/tensorflow/python/data/kernel_tests/prefetch_dataset_op_test.py +++ b/tensorflow/python/data/kernel_tests/prefetch_dataset_op_test.py @@ -40,7 +40,7 @@ class PrefetchDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): with self.cached_session() as sess: sess.run(init_op, feed_dict={buffer_size_t: buffer_size}) for m in range(10): - self.assertEqual(m, sess.run(get_next)) + self.assertEqual(m, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) diff --git a/tensorflow/python/data/kernel_tests/range_dataset_op_test.py b/tensorflow/python/data/kernel_tests/range_dataset_op_test.py index 9fc79707d05..fcb025c8b88 100644 --- a/tensorflow/python/data/kernel_tests/range_dataset_op_test.py +++ b/tensorflow/python/data/kernel_tests/range_dataset_op_test.py @@ -124,19 +124,19 @@ class ExperimentalCheckpointDatasetTest(test_base.DatasetTestBase): with ops.Graph().as_default() as g: init_op, get_next, save_op, _ = _build_graph(start, stop) with self.session(graph=g) as sess: - sess.run(variables.global_variables_initializer()) - sess.run(init_op) + self.evaluate(variables.global_variables_initializer()) + self.evaluate(init_op) for i in range(start, break_point): - self.assertEqual(i, sess.run(get_next)) - sess.run(save_op) + self.assertEqual(i, self.evaluate(get_next)) + self.evaluate(save_op) with ops.Graph().as_default() as g: init_op, get_next, _, restore_op = _build_graph(start, stop) with self.session(graph=g) as sess: - sess.run(init_op) - sess.run(restore_op) + self.evaluate(init_op) + self.evaluate(restore_op) for i in range(break_point, stop): - self.assertEqual(i, sess.run(get_next)) + self.assertEqual(i, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -144,14 +144,14 @@ class ExperimentalCheckpointDatasetTest(test_base.DatasetTestBase): with ops.Graph().as_default() as g: init_op, get_next, save_op, restore_op = _build_graph(start, stop) with self.session(graph=g) as sess: - sess.run(variables.global_variables_initializer()) - sess.run(init_op) + self.evaluate(variables.global_variables_initializer()) + self.evaluate(init_op) for i in range(start, break_point): - self.assertEqual(i, sess.run(get_next)) - sess.run(save_op) - sess.run(restore_op) + self.assertEqual(i, self.evaluate(get_next)) + self.evaluate(save_op) + self.evaluate(restore_op) for i in range(break_point, stop): - self.assertEqual(i, sess.run(get_next)) + self.assertEqual(i, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -175,14 +175,14 @@ class ExperimentalCheckpointDatasetTest(test_base.DatasetTestBase): with ops.Graph().as_default() as g: init_op, get_next, save_op, _ = _build_graph(start, stop, num_epochs) with self.session(graph=g) as sess: - sess.run(variables.global_variables_initializer()) - sess.run(init_op) + self.evaluate(variables.global_variables_initializer()) + self.evaluate(init_op) for _ in range(break_epoch): for i in range(start, stop): - self.assertEqual(i, sess.run(get_next)) + self.assertEqual(i, self.evaluate(get_next)) for i in range(start, break_point): - self.assertEqual(i, sess.run(get_next)) - sess.run(save_op) + self.assertEqual(i, self.evaluate(get_next)) + self.evaluate(save_op) with ops.Graph().as_default() as g: # Create an empty IteratorResource and restore the Iterator into it. @@ -193,12 +193,12 @@ class ExperimentalCheckpointDatasetTest(test_base.DatasetTestBase): restore_op = self._restore_op(iterator._iterator_resource) get_next = iterator.get_next() with self.session(graph=g) as sess: - sess.run(restore_op) + self.evaluate(restore_op) for i in range(break_point, stop): - self.assertEqual(i, sess.run(get_next)) + self.assertEqual(i, self.evaluate(get_next)) for _ in range(break_epoch + 1, num_epochs): for i in range(start, stop): - self.assertEqual(i, sess.run(get_next)) + self.assertEqual(i, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -221,20 +221,20 @@ class ExperimentalCheckpointDatasetTest(test_base.DatasetTestBase): with ops.Graph().as_default() as g: init_op, get_next, save_op, _ = _build_graph(start, stop) with self.session(graph=g) as sess: - sess.run(variables.global_variables_initializer()) - sess.run(init_op) + self.evaluate(variables.global_variables_initializer()) + self.evaluate(init_op) for i in range(start, break_point): - self.assertEqual(i, sess.run(get_next)) - sess.run(save_op) + self.assertEqual(i, self.evaluate(get_next)) + self.evaluate(save_op) with ops.Graph().as_default() as g: # Intentionally build a graph with a different value for stop to make sure # the original dataset graph is actually getting loaded. init_op, get_next, _, restore_op = _build_graph(start, stop_1) with self.session(graph=g) as sess: - sess.run(restore_op) + self.evaluate(restore_op) for i in range(break_point, stop): - self.assertEqual(i, sess.run(get_next)) + self.assertEqual(i, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -259,19 +259,19 @@ class ExperimentalCheckpointDatasetTest(test_base.DatasetTestBase): with ops.Graph().as_default() as g: init_op, get_next, save_op, _ = _build_graph(start, stop) with self.session(graph=g) as sess: - sess.run(variables.global_variables_initializer()) - sess.run(init_op) + self.evaluate(variables.global_variables_initializer()) + self.evaluate(init_op) for i in range(start, break_point): - self.assertEqual(i, sess.run(get_next)) - sess.run(save_op) + self.assertEqual(i, self.evaluate(get_next)) + self.evaluate(save_op) with ops.Graph().as_default() as g: init_op, get_next, _, restore_op = _build_graph(start, stop) with self.session(graph=g) as sess: - sess.run(init_op) - sess.run(restore_op) + self.evaluate(init_op) + self.evaluate(restore_op) for i in range(break_point, stop): - self.assertEqual(i, sess.run(get_next)) + self.assertEqual(i, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -294,27 +294,27 @@ class ExperimentalCheckpointDatasetTest(test_base.DatasetTestBase): with ops.Graph().as_default() as g: init_op, get_next, save_op, _ = _build_graph(start, stop) with self.session(graph=g) as sess: - sess.run(variables.global_variables_initializer()) - sess.run(init_op) + self.evaluate(variables.global_variables_initializer()) + self.evaluate(init_op) for i in range(start, break_point1): - self.assertEqual(i, sess.run(get_next)) - sess.run(save_op) + self.assertEqual(i, self.evaluate(get_next)) + self.evaluate(save_op) with ops.Graph().as_default() as g: init_op, get_next, save_op, restore_op = _build_graph(start, stop) with self.session(graph=g) as sess: - sess.run(restore_op) + self.evaluate(restore_op) for i in range(break_point1, break_point2): - self.assertEqual(i, sess.run(get_next)) - sess.run(save_op) + self.assertEqual(i, self.evaluate(get_next)) + self.evaluate(save_op) break_point2 = 7 with ops.Graph().as_default() as g: init_op, get_next, save_op, restore_op = _build_graph(start, stop) with self.session(graph=g) as sess: - sess.run(restore_op) + self.evaluate(restore_op) for i in range(break_point2, stop): - self.assertEqual(i, sess.run(get_next)) + self.assertEqual(i, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -338,28 +338,28 @@ class ExperimentalCheckpointDatasetTest(test_base.DatasetTestBase): init_op, get_next, save_op, restore_op = _build_graph( start, stop, num_epochs) with self.session(graph=g) as sess: - sess.run(variables.global_variables_initializer()) - sess.run(init_op) + self.evaluate(variables.global_variables_initializer()) + self.evaluate(init_op) # Note: There is no checkpoint saved currently so a NotFoundError is # raised. with self.assertRaises(errors.NotFoundError): - sess.run(restore_op) + self.evaluate(restore_op) for _ in range(break_epoch - 1): for i in range(start, stop): - self.assertEqual(i, sess.run(get_next)) + self.assertEqual(i, self.evaluate(get_next)) for i in range(start, break_range): - self.assertEqual(i, sess.run(get_next)) - sess.run(save_op) + self.assertEqual(i, self.evaluate(get_next)) + self.evaluate(save_op) with ops.Graph().as_default() as g: init_op, get_next, _, restore_op = _build_graph(start, stop, num_epochs) with self.session(graph=g) as sess: - sess.run(restore_op) + self.evaluate(restore_op) for i in range(break_range, stop): - self.assertEqual(i, sess.run(get_next)) + self.assertEqual(i, self.evaluate(get_next)) for _ in range(break_epoch, num_epochs): for i in range(start, stop): - self.assertEqual(i, sess.run(get_next)) + self.assertEqual(i, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -381,23 +381,23 @@ class ExperimentalCheckpointDatasetTest(test_base.DatasetTestBase): init_op, get_next, save_op, restore_op = _build_graph( start, stop, num_epochs) with self.session(graph=g) as sess: - sess.run(variables.global_variables_initializer()) - sess.run(init_op) + self.evaluate(variables.global_variables_initializer()) + self.evaluate(init_op) # Note: There is no checkpoint saved currently so a NotFoundError is # raised. with self.assertRaises(errors.NotFoundError): - sess.run(restore_op) + self.evaluate(restore_op) for _ in range(num_epochs): for i in range(start, stop): - self.assertEqual(i, sess.run(get_next)) + self.assertEqual(i, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) - sess.run(save_op) + self.evaluate(save_op) with ops.Graph().as_default() as g: init_op, get_next, _, restore_op = _build_graph(start, stop, num_epochs) with self.session(graph=g) as sess: - sess.run(restore_op) + self.evaluate(restore_op) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) diff --git a/tensorflow/python/data/kernel_tests/reader_dataset_ops_test.py b/tensorflow/python/data/kernel_tests/reader_dataset_ops_test.py index 4fef4f30bf9..e26381e902b 100644 --- a/tensorflow/python/data/kernel_tests/reader_dataset_ops_test.py +++ b/tensorflow/python/data/kernel_tests/reader_dataset_ops_test.py @@ -107,7 +107,7 @@ class TextLineDatasetTest(test_base.DatasetTestBase): init_op, feed_dict={filenames: [test_filenames[0]], num_epochs: 1}) for i in range(5): - self.assertEqual(self._lineText(0, i), sess.run(get_next)) + self.assertEqual(self._lineText(0, i), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -116,7 +116,7 @@ class TextLineDatasetTest(test_base.DatasetTestBase): init_op, feed_dict={filenames: [test_filenames[1]], num_epochs: 1}) for i in range(5): - self.assertEqual(self._lineText(1, i), sess.run(get_next)) + self.assertEqual(self._lineText(1, i), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -124,7 +124,7 @@ class TextLineDatasetTest(test_base.DatasetTestBase): sess.run(init_op, feed_dict={filenames: test_filenames, num_epochs: 1}) for j in range(2): for i in range(5): - self.assertEqual(self._lineText(j, i), sess.run(get_next)) + self.assertEqual(self._lineText(j, i), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -133,7 +133,7 @@ class TextLineDatasetTest(test_base.DatasetTestBase): for _ in range(10): for j in range(2): for i in range(5): - self.assertEqual(self._lineText(j, i), sess.run(get_next)) + self.assertEqual(self._lineText(j, i), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -267,7 +267,7 @@ class FixedLengthRecordReaderTest(test_base.DatasetTestBase): init_op, feed_dict={filenames: [test_filenames[0]], num_epochs: 1}) for i in range(self._num_records): - self.assertEqual(self._record(0, i), sess.run(get_next)) + self.assertEqual(self._record(0, i), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -276,7 +276,7 @@ class FixedLengthRecordReaderTest(test_base.DatasetTestBase): init_op, feed_dict={filenames: [test_filenames[1]], num_epochs: 1}) for i in range(self._num_records): - self.assertEqual(self._record(1, i), sess.run(get_next)) + self.assertEqual(self._record(1, i), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -284,7 +284,7 @@ class FixedLengthRecordReaderTest(test_base.DatasetTestBase): sess.run(init_op, feed_dict={filenames: test_filenames, num_epochs: 1}) for j in range(self._num_files): for i in range(self._num_records): - self.assertEqual(self._record(j, i), sess.run(get_next)) + self.assertEqual(self._record(j, i), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -293,7 +293,7 @@ class FixedLengthRecordReaderTest(test_base.DatasetTestBase): for _ in range(10): for j in range(self._num_files): for i in range(self._num_records): - self.assertEqual(self._record(j, i), sess.run(get_next)) + self.assertEqual(self._record(j, i), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -405,19 +405,19 @@ class FixedLengthRecordReaderTest(test_base.DatasetTestBase): init_op, get_next_op, save_op, restore_op = self._build_iterator_graph( num_epochs=num_epochs) with self.session(graph=g) as sess: - sess.run(init_op) + self.evaluate(init_op) # Note: There is no checkpoint saved currently so a NotFoundError is # raised. with self.assertRaises(errors.NotFoundError): - sess.run(restore_op) + self.evaluate(restore_op) for epoch in range(num_epochs): for f in range(self._num_files): for r in range(self._num_records): if (epoch == epoch_break and f == file_break and r == record_break): - sess.run(save_op) + self.evaluate(save_op) break - self.assertEqual(self._record(f, r), sess.run(get_next_op)) + self.assertEqual(self._record(f, r), self.evaluate(get_next_op)) else: continue break @@ -426,13 +426,13 @@ class FixedLengthRecordReaderTest(test_base.DatasetTestBase): break else: with self.assertRaises(errors.OutOfRangeError): - sess.run(get_next_op) + self.evaluate(get_next_op) with ops.Graph().as_default() as g: init_op, get_next_op, save_op, restore_op = self._build_iterator_graph( num_epochs=num_epochs) with self.session(graph=g) as sess: - sess.run(restore_op) + self.evaluate(restore_op) for epoch in range(num_epochs): for f in range(self._num_files): for r in range(self._num_records): @@ -441,9 +441,9 @@ class FixedLengthRecordReaderTest(test_base.DatasetTestBase): (epoch == epoch_break and f == file_break and r < record_break)): continue - self.assertEqual(self._record(f, r), sess.run(get_next_op)) + self.assertEqual(self._record(f, r), self.evaluate(get_next_op)) with self.assertRaises(errors.OutOfRangeError): - sess.run(get_next_op) + self.evaluate(get_next_op) def testInitThenRestore(self): # Note: Calling init_op before restore_op is redundant. This test just makes @@ -458,19 +458,19 @@ class FixedLengthRecordReaderTest(test_base.DatasetTestBase): init_op, get_next_op, save_op, restore_op = self._build_iterator_graph( num_epochs=num_epochs) with self.session(graph=g) as sess: - sess.run(init_op) + self.evaluate(init_op) # Note: There is no checkpoint saved currently so a NotFoundError is # raised. with self.assertRaises(errors.NotFoundError): - sess.run(restore_op) + self.evaluate(restore_op) for epoch in range(num_epochs): for f in range(self._num_files): for r in range(self._num_records): if (epoch == epoch_break and f == file_break and r == record_break): - sess.run(save_op) + self.evaluate(save_op) break - self.assertEqual(self._record(f, r), sess.run(get_next_op)) + self.assertEqual(self._record(f, r), self.evaluate(get_next_op)) else: continue break @@ -479,14 +479,14 @@ class FixedLengthRecordReaderTest(test_base.DatasetTestBase): break else: with self.assertRaises(errors.OutOfRangeError): - sess.run(get_next_op) + self.evaluate(get_next_op) with ops.Graph().as_default() as g: init_op, get_next_op, save_op, restore_op = self._build_iterator_graph( num_epochs=num_epochs) with self.session(graph=g) as sess: - sess.run(init_op) - sess.run(restore_op) + self.evaluate(init_op) + self.evaluate(restore_op) for epoch in range(num_epochs): for f in range(self._num_files): for r in range(self._num_records): @@ -495,9 +495,9 @@ class FixedLengthRecordReaderTest(test_base.DatasetTestBase): (epoch == epoch_break and f == file_break and r < record_break)): continue - self.assertEqual(self._record(f, r), sess.run(get_next_op)) + self.assertEqual(self._record(f, r), self.evaluate(get_next_op)) with self.assertRaises(errors.OutOfRangeError): - sess.run(get_next_op) + self.evaluate(get_next_op) def testRestoreInModifiedGraph(self): num_epochs = 10 @@ -510,19 +510,19 @@ class FixedLengthRecordReaderTest(test_base.DatasetTestBase): init_op, get_next_op, save_op, restore_op = self._build_iterator_graph( num_epochs=num_epochs) with self.session(graph=g) as sess: - sess.run(init_op) + self.evaluate(init_op) # Note: There is no checkpoint saved currently so a NotFoundError is # raised. with self.assertRaises(errors.NotFoundError): - sess.run(restore_op) + self.evaluate(restore_op) for epoch in range(num_epochs): for f in range(self._num_files): for r in range(self._num_records): if (epoch == epoch_break and f == file_break and r == record_break): - sess.run(save_op) + self.evaluate(save_op) break - self.assertEqual(self._record(f, r), sess.run(get_next_op)) + self.assertEqual(self._record(f, r), self.evaluate(get_next_op)) else: continue break @@ -531,13 +531,13 @@ class FixedLengthRecordReaderTest(test_base.DatasetTestBase): break else: with self.assertRaises(errors.OutOfRangeError): - sess.run(get_next_op) + self.evaluate(get_next_op) with ops.Graph().as_default() as g: init_op, get_next_op, save_op, restore_op = self._build_iterator_graph( num_epochs=num_epochs_1) with self.session(graph=g) as sess: - sess.run(restore_op) + self.evaluate(restore_op) for epoch in range(num_epochs): for f in range(self._num_files): for r in range(self._num_records): @@ -546,9 +546,9 @@ class FixedLengthRecordReaderTest(test_base.DatasetTestBase): (epoch == epoch_break and f == file_break and r < record_break)): continue - self.assertEqual(self._record(f, r), sess.run(get_next_op)) + self.assertEqual(self._record(f, r), self.evaluate(get_next_op)) with self.assertRaises(errors.OutOfRangeError): - sess.run(get_next_op) + self.evaluate(get_next_op) def testRestoreWithoutBuildingDatasetGraph(self): num_epochs = 10 @@ -560,19 +560,19 @@ class FixedLengthRecordReaderTest(test_base.DatasetTestBase): init_op, get_next_op, save_op, restore_op = self._build_iterator_graph( num_epochs=num_epochs) with self.session(graph=g) as sess: - sess.run(init_op) + self.evaluate(init_op) # Note: There is no checkpoint saved currently so a NotFoundError is # raised. with self.assertRaises(errors.NotFoundError): - sess.run(restore_op) + self.evaluate(restore_op) for epoch in range(num_epochs): for f in range(self._num_files): for r in range(self._num_records): if (epoch == epoch_break and f == file_break and r == record_break): - sess.run(save_op) + self.evaluate(save_op) break - self.assertEqual(self._record(f, r), sess.run(get_next_op)) + self.assertEqual(self._record(f, r), self.evaluate(get_next_op)) else: continue break @@ -581,12 +581,12 @@ class FixedLengthRecordReaderTest(test_base.DatasetTestBase): break else: with self.assertRaises(errors.OutOfRangeError): - sess.run(get_next_op) + self.evaluate(get_next_op) with ops.Graph().as_default() as g: restore_op, get_next_op = self._restore_iterator() with self.session(graph=g) as sess: - sess.run(restore_op) + self.evaluate(restore_op) for epoch in range(num_epochs): for f in range(self._num_files): for r in range(self._num_records): @@ -595,9 +595,9 @@ class FixedLengthRecordReaderTest(test_base.DatasetTestBase): (epoch == epoch_break and f == file_break and r < record_break)): continue - self.assertEqual(self._record(f, r), sess.run(get_next_op)) + self.assertEqual(self._record(f, r), self.evaluate(get_next_op)) with self.assertRaises(errors.OutOfRangeError): - sess.run(get_next_op) + self.evaluate(get_next_op) def testRestoreUnusedIterator(self): num_epochs = 10 @@ -605,22 +605,22 @@ class FixedLengthRecordReaderTest(test_base.DatasetTestBase): init_op, get_next_op, save_op, restore_op = self._build_iterator_graph( num_epochs=num_epochs) with self.session(graph=g) as sess: - sess.run(init_op) + self.evaluate(init_op) # Note: There is no checkpoint saved currently so a NotFoundError is # raised. with self.assertRaises(errors.NotFoundError): - sess.run(restore_op) + self.evaluate(restore_op) # Save unused iterator. - sess.run(save_op) + self.evaluate(save_op) with ops.Graph().as_default() as g: init_op, get_next_op, save_op, restore_op = self._build_iterator_graph( num_epochs=num_epochs) with self.session(graph=g) as sess: - sess.run(restore_op) + self.evaluate(restore_op) for _ in range(num_epochs * self._num_files * self._num_records): - sess.run(get_next_op) + self.evaluate(get_next_op) with self.assertRaises(errors.OutOfRangeError): - sess.run(get_next_op) + self.evaluate(get_next_op) def testRestoreExhaustedIterator(self): num_epochs = 10 @@ -629,26 +629,26 @@ class FixedLengthRecordReaderTest(test_base.DatasetTestBase): init_op, get_next_op, save_op, restore_op = self._build_iterator_graph( num_epochs=num_epochs) with self.session(graph=g) as sess: - sess.run(init_op) + self.evaluate(init_op) # Note: There is no checkpoint saved currently so a NotFoundError is # raised. with self.assertRaises(errors.NotFoundError): - sess.run(restore_op) + self.evaluate(restore_op) for _ in range(num_epochs): for f in range(self._num_files): for r in range(self._num_records): - self.assertEqual(self._record(f, r), sess.run(get_next_op)) + self.assertEqual(self._record(f, r), self.evaluate(get_next_op)) with self.assertRaises(errors.OutOfRangeError): - sess.run(get_next_op) - sess.run(save_op) + self.evaluate(get_next_op) + self.evaluate(save_op) with ops.Graph().as_default() as g: init_op, get_next_op, save_op, restore_op = self._build_iterator_graph( num_epochs=num_epochs) with self.session(graph=g) as sess: - sess.run(restore_op) + self.evaluate(restore_op) with self.assertRaises(errors.OutOfRangeError): - sess.run(get_next_op) + self.evaluate(get_next_op) class TFRecordDatasetTest(test_base.DatasetTestBase): @@ -807,7 +807,7 @@ class TFRecordDatasetTest(test_base.DatasetTestBase): with self.cached_session() as sess: for j in range(self._num_files): for i in range(self._num_records): - self.assertAllEqual(self._record(j, i), sess.run(next_element)) + self.assertAllEqual(self._record(j, i), self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -819,7 +819,7 @@ class TFRecordDatasetTest(test_base.DatasetTestBase): with self.cached_session() as sess: for j in range(self._num_files): for i in range(self._num_records): - self.assertAllEqual(self._record(j, i), sess.run(next_element)) + self.assertAllEqual(self._record(j, i), self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) diff --git a/tensorflow/python/data/kernel_tests/reduce_dataset_op_test.py b/tensorflow/python/data/kernel_tests/reduce_dataset_op_test.py index 11e07300b97..d7f3988b1af 100644 --- a/tensorflow/python/data/kernel_tests/reduce_dataset_op_test.py +++ b/tensorflow/python/data/kernel_tests/reduce_dataset_op_test.py @@ -36,7 +36,7 @@ class ReduceDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): ds = dataset_ops.Dataset.range(1, i + 1) result = ds.reduce(np.int64(0), lambda x, y: x + y) with self.cached_session() as sess: - self.assertEqual(((i + 1) * i) // 2, sess.run(result)) + self.assertEqual(((i + 1) * i) // 2, self.evaluate(result)) def testSumTuple(self): @@ -49,7 +49,7 @@ class ReduceDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): ds = dataset_ops.Dataset.zip((ds, ds)) result = ds.reduce(np.int64(0), reduce_fn) with self.cached_session() as sess: - self.assertEqual(((i + 1) * i), sess.run(result)) + self.assertEqual(((i + 1) * i), self.evaluate(result)) def testSumAndCount(self): @@ -61,7 +61,7 @@ class ReduceDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): ds = dataset_ops.Dataset.range(1, i + 1) result = ds.reduce((np.int64(0), np.int64(0)), reduce_fn) with self.cached_session() as sess: - s, c = sess.run(result) + s, c = self.evaluate(result) self.assertEqual(((i + 1) * i) // 2, s) self.assertEqual(i, c) @@ -93,7 +93,8 @@ class ReduceDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): ds = dataset_ops.Dataset.from_tensors(make_sparse_fn(i+1)) result = ds.reduce(make_sparse_fn(0), reduce_fn) with self.cached_session() as sess: - self.assertSparseValuesEqual(make_sparse_fn(i+1), sess.run(result)) + self.assertSparseValuesEqual( + make_sparse_fn(i + 1), self.evaluate(result)) def testNested(self): @@ -116,7 +117,7 @@ class ReduceDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): ds = dataset_ops.Dataset.range(1, i + 1).map(map_fn) result = ds.reduce(map_fn(0), reduce_fn) with self.cached_session() as sess: - result = sess.run(result) + result = self.evaluate(result) self.assertEqual(((i + 1) * i) // 2, result["dense"]) self.assertSparseValuesEqual(make_sparse_fn(i), result["sparse"]) diff --git a/tensorflow/python/data/kernel_tests/sequence_dataset_op_test.py b/tensorflow/python/data/kernel_tests/sequence_dataset_op_test.py index e86356dee7c..946aa01f735 100644 --- a/tensorflow/python/data/kernel_tests/sequence_dataset_op_test.py +++ b/tensorflow/python/data/kernel_tests/sequence_dataset_op_test.py @@ -49,7 +49,7 @@ class SequenceDatasetTest(test_base.DatasetTestBase): # Test a finite repetition. sess.run(init_op, feed_dict={count_placeholder: 3}) for _ in range(3): - results = sess.run(get_next) + results = self.evaluate(get_next) for component, result_component in zip(components, results): self.assertAllEqual(component, result_component) @@ -59,7 +59,7 @@ class SequenceDatasetTest(test_base.DatasetTestBase): # Test a different finite repetition. sess.run(init_op, feed_dict={count_placeholder: 7}) for _ in range(7): - results = sess.run(get_next) + results = self.evaluate(get_next) for component, result_component in zip(components, results): self.assertAllEqual(component, result_component) with self.assertRaises(errors.OutOfRangeError): @@ -75,7 +75,7 @@ class SequenceDatasetTest(test_base.DatasetTestBase): # actually is infinite. sess.run(init_op, feed_dict={count_placeholder: -1}) for _ in range(17): - results = sess.run(get_next) + results = self.evaluate(get_next) for component, result_component in zip(components, results): self.assertAllEqual(component, result_component) @@ -95,7 +95,7 @@ class SequenceDatasetTest(test_base.DatasetTestBase): # Take fewer than input size sess.run(init_op, feed_dict={count_placeholder: 4}) for i in range(4): - results = sess.run(get_next) + results = self.evaluate(get_next) self.assertAllEqual(results, components[0][i:i+1]) with self.assertRaises(errors.OutOfRangeError): @@ -104,7 +104,7 @@ class SequenceDatasetTest(test_base.DatasetTestBase): # Take more than input size sess.run(init_op, feed_dict={count_placeholder: 25}) for i in range(10): - results = sess.run(get_next) + results = self.evaluate(get_next) self.assertAllEqual(results, components[0][i:i+1]) with self.assertRaises(errors.OutOfRangeError): @@ -113,7 +113,7 @@ class SequenceDatasetTest(test_base.DatasetTestBase): # Take all of input sess.run(init_op, feed_dict={count_placeholder: -1}) for i in range(10): - results = sess.run(get_next) + results = self.evaluate(get_next) self.assertAllEqual(results, components[0][i:i+1]) with self.assertRaises(errors.OutOfRangeError): @@ -142,7 +142,7 @@ class SequenceDatasetTest(test_base.DatasetTestBase): # the first 4 elements and then read the rest. sess.run(init_op, feed_dict={count_placeholder: 4}) for i in range(4, 10): - results = sess.run(get_next) + results = self.evaluate(get_next) self.assertAllEqual(results, components[0][i:i+1]) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -165,7 +165,7 @@ class SequenceDatasetTest(test_base.DatasetTestBase): # Skip nothing sess.run(init_op, feed_dict={count_placeholder: 0}) for i in range(0, 10): - results = sess.run(get_next) + results = self.evaluate(get_next) self.assertAllEqual(results, components[0][i:i+1]) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -187,7 +187,7 @@ class SequenceDatasetTest(test_base.DatasetTestBase): with self.cached_session() as sess: sess.run(init_op, feed_dict={inner_count: 7, outer_count: 14}) for _ in range(7 * 14): - results = sess.run(get_next) + results = self.evaluate(get_next) for component, result_component in zip(components, results): self.assertAllEqual(component, result_component) with self.assertRaises(errors.OutOfRangeError): @@ -201,7 +201,7 @@ class SequenceDatasetTest(test_base.DatasetTestBase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) diff --git a/tensorflow/python/data/kernel_tests/shuffle_dataset_op_test.py b/tensorflow/python/data/kernel_tests/shuffle_dataset_op_test.py index cad28f860e9..990f4f212b8 100644 --- a/tensorflow/python/data/kernel_tests/shuffle_dataset_op_test.py +++ b/tensorflow/python/data/kernel_tests/shuffle_dataset_op_test.py @@ -66,7 +66,7 @@ class ShuffleDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): with self.cached_session() as sess: # First run without shuffling to collect the "ground truth". - sess.run(init_fifo_op) + self.evaluate(init_fifo_op) unshuffled_elements = [] for _ in range(20): unshuffled_elements.append(sess.run(get_next)) @@ -159,7 +159,7 @@ class ShuffleDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): with self.cached_session() as sess: sess.run(iterator.initializer, feed_dict={seed_placeholder: 0}) for elem in elems: - self.assertEqual(elem, sess.run(get_next)) + self.assertEqual(elem, self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) @@ -188,9 +188,9 @@ class ShuffleDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): next_element = iterator.get_next() with self.cached_session() as sess: - initial_permutation = sess.run(next_element) - self.assertAllEqual(initial_permutation, sess.run(next_element)) - self.assertAllEqual(initial_permutation, sess.run(next_element)) + initial_permutation = self.evaluate(next_element) + self.assertAllEqual(initial_permutation, self.evaluate(next_element)) + self.assertAllEqual(initial_permutation, self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -261,7 +261,7 @@ class ShuffleDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): with self.session(graph=g) as sess: for iterator in iterators: if initializable: - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) next_element = iterator.get_next() run_results = [] for _ in range(300): diff --git a/tensorflow/python/data/kernel_tests/window_dataset_op_test.py b/tensorflow/python/data/kernel_tests/window_dataset_op_test.py index 9d067810944..35adcddfe70 100644 --- a/tensorflow/python/data/kernel_tests/window_dataset_op_test.py +++ b/tensorflow/python/data/kernel_tests/window_dataset_op_test.py @@ -102,7 +102,7 @@ class WindowDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): num_full_batches = max( 0, (count * 7 - ((size - 1) * stride + 1)) // shift + 1) for i in range(num_full_batches): - result = sess.run(get_next) + result = self.evaluate(get_next) for component, result_component in zip(components, result): for j in range(size): self.assertAllEqual(component[(i * shift + j * stride) % 7]**2, @@ -111,7 +111,7 @@ class WindowDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): num_partial_batches = (count * 7) // shift + ( (count * 7) % shift > 0) - num_full_batches for i in range(num_partial_batches): - result = sess.run(get_next) + result = self.evaluate(get_next) for component, result_component in zip(components, result): remaining = (count * 7) - ((num_full_batches + i) * shift) num_elements = remaining // stride + ((remaining % stride) > 0) @@ -164,10 +164,10 @@ class WindowDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) num_batches = (10 - 5) // 3 + 1 for i in range(num_batches): - actual = sess.run(get_next) + actual = self.evaluate(get_next) expected = sparse_tensor.SparseTensorValue( indices=[[0, 0], [1, 0], [2, 0], [3, 0], [4, 0]], values=[i * 3, i * 3 + 1, i * 3 + 2, i * 3 + 3, i * 3 + 4], @@ -193,10 +193,10 @@ class WindowDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) num_batches = (10 - 5) // 3 + 1 for i in range(num_batches): - actual = sess.run(get_next) + actual = self.evaluate(get_next) expected_indices = [] expected_values = [] for j in range(5): @@ -227,9 +227,9 @@ class WindowDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = iterator.get_next() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) # Slide: 1st batch. - actual = sess.run(get_next) + actual = self.evaluate(get_next) expected = sparse_tensor.SparseTensorValue( indices=[[0, 0, 0], [0, 1, 0], [0, 2, 0], [0, 3, 0], [1, 0, 0], [1, 1, 0], [1, 2, 0], [1, 3, 0], [2, 0, 0], [2, 1, 0], @@ -239,7 +239,7 @@ class WindowDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): self.assertTrue(sparse_tensor.is_sparse(actual)) self.assertSparseValuesEqual(actual, expected) # Slide: 2nd batch. - actual = sess.run(get_next) + actual = self.evaluate(get_next) expected = sparse_tensor.SparseTensorValue( indices=[[0, 0, 0], [0, 1, 0], [0, 2, 0], [0, 3, 0], [1, 0, 0], [1, 1, 0], [1, 2, 0], [1, 3, 0], [2, 0, 0], [2, 1, 0], @@ -265,7 +265,7 @@ class WindowDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): next_element = iterator.get_next() with self.cached_session() as sess: - sess.run(iterator.initializer) + self.evaluate(iterator.initializer) with self.assertRaisesRegexp( errors.InvalidArgumentError, r"Cannot batch tensors with different shapes in component 0. " @@ -281,8 +281,8 @@ class WindowDatasetTest(test_base.DatasetTestBase, parameterized.TestCase): get_next = dataset.make_one_shot_iterator().get_next() with self.cached_session() as sess: - self.assertAllEqual(np.float32([1., 2.]), sess.run(get_next)) - self.assertAllEqual(np.float32([2., 3.]), sess.run(get_next)) + self.assertAllEqual(np.float32([1., 2.]), self.evaluate(get_next)) + self.assertAllEqual(np.float32([2., 3.]), self.evaluate(get_next)) with self.assertRaises(errors.OutOfRangeError): sess.run(get_next) diff --git a/tensorflow/python/data/kernel_tests/zip_dataset_op_test.py b/tensorflow/python/data/kernel_tests/zip_dataset_op_test.py index 9d76387a343..b60ec4ecce5 100644 --- a/tensorflow/python/data/kernel_tests/zip_dataset_op_test.py +++ b/tensorflow/python/data/kernel_tests/zip_dataset_op_test.py @@ -55,7 +55,7 @@ class ZipDatasetTest(test_base.DatasetTestBase): sess.run(init_op, feed_dict={ph: value for ph, value in zip( component_placeholders, equal_length_components)}) for i in range(4): - results = sess.run(get_next) + results = self.evaluate(get_next) for component, result_component in zip( equal_length_components, results): self.assertAllEqual(component[i], result_component) @@ -66,7 +66,7 @@ class ZipDatasetTest(test_base.DatasetTestBase): sess.run(init_op, feed_dict={ph: value for ph, value in zip( component_placeholders, variable_length_components)}) for i in range(2): - results = sess.run(get_next) + results = self.evaluate(get_next) for component, result_component in zip( variable_length_components, results): self.assertAllEqual(component[i], result_component) @@ -103,7 +103,7 @@ class ZipDatasetTest(test_base.DatasetTestBase): sess.run(init_op, feed_dict={ph: value for ph, value in zip( component_placeholders, equal_length_components)}) for i in range(4): - result1, (result2, result3) = sess.run(get_next) + result1, (result2, result3) = self.evaluate(get_next) self.assertAllEqual(equal_length_components[0][i], result1) self.assertAllEqual(equal_length_components[1][i], result2) self.assertAllEqual(equal_length_components[2][i], result3) diff --git a/tensorflow/python/data/util/convert_test.py b/tensorflow/python/data/util/convert_test.py index 89c3afb2969..4a5b7303811 100644 --- a/tensorflow/python/data/util/convert_test.py +++ b/tensorflow/python/data/util/convert_test.py @@ -31,24 +31,24 @@ class ConvertTest(test.TestCase): def testInteger(self): resp = convert.optional_param_to_tensor("foo", 3) with self.cached_session() as sess: - self.assertEqual(3, sess.run(resp)) + self.assertEqual(3, self.evaluate(resp)) def testIntegerDefault(self): resp = convert.optional_param_to_tensor("foo", None) with self.cached_session() as sess: - self.assertEqual(0, sess.run(resp)) + self.assertEqual(0, self.evaluate(resp)) def testStringDefault(self): resp = convert.optional_param_to_tensor("bar", None, "default", dtypes.string) with self.cached_session() as sess: - self.assertEqual(compat.as_bytes("default"), sess.run(resp)) + self.assertEqual(compat.as_bytes("default"), self.evaluate(resp)) def testString(self): resp = convert.optional_param_to_tensor("bar", "value", "default", dtypes.string) with self.cached_session() as sess: - self.assertEqual(compat.as_bytes("value"), sess.run(resp)) + self.assertEqual(compat.as_bytes("value"), self.evaluate(resp)) def testPartialShapeToTensorKnownDimension(self): with self.cached_session() as sess: diff --git a/tensorflow/python/debug/cli/analyzer_cli_test.py b/tensorflow/python/debug/cli/analyzer_cli_test.py index f197a9e4dce..5aa7d1bb4c3 100644 --- a/tensorflow/python/debug/cli/analyzer_cli_test.py +++ b/tensorflow/python/debug/cli/analyzer_cli_test.py @@ -1583,7 +1583,7 @@ class AnalyzerCLISimpleMulAddTest(test_util.TensorFlowTestCase): x = variables.VariableV1([1, 3, 3, 7], name="x") _, idx = array_ops.unique(x, name="x_unique") idx_times_two = math_ops.multiply(idx, 2, name="idx_times_two") - sess.run(x.initializer) + self.evaluate(x.initializer) run_options = config_pb2.RunOptions(output_partition_graphs=True) debug_utils.watch_graph( diff --git a/tensorflow/python/debug/lib/debug_graph_reconstruction_test.py b/tensorflow/python/debug/lib/debug_graph_reconstruction_test.py index 1f67f8a0d4e..34030c0adca 100644 --- a/tensorflow/python/debug/lib/debug_graph_reconstruction_test.py +++ b/tensorflow/python/debug/lib/debug_graph_reconstruction_test.py @@ -126,8 +126,8 @@ class ReconstructNonDebugGraphTest(test_util.TensorFlowTestCase): u = variables.Variable([12.0], name="u") v = variables.Variable([30.0], name="v") w = math_ops.add(u, v, name="w") - sess.run(u.initializer) - sess.run(v.initializer) + self.evaluate(u.initializer) + self.evaluate(v.initializer) self._compareOriginalAndReconstructedGraphDefs( sess, w, expected_output=[42.0]) @@ -139,7 +139,7 @@ class ReconstructNonDebugGraphTest(test_util.TensorFlowTestCase): b = math_ops.add(a, a, name="b") with ops.control_dependencies([a, b]): c = math_ops.multiply(b, b, name="c") - sess.run(a.initializer) + self.evaluate(a.initializer) self._compareOriginalAndReconstructedGraphDefs( sess, c, expected_output=400.0) @@ -150,8 +150,8 @@ class ReconstructNonDebugGraphTest(test_util.TensorFlowTestCase): y = variables.Variable(20.0, name="y") cond = control_flow_ops.cond( x > y, lambda: math_ops.add(x, 1), lambda: math_ops.add(y, 1)) - sess.run(x.initializer) - sess.run(y.initializer) + self.evaluate(x.initializer) + self.evaluate(y.initializer) self._compareOriginalAndReconstructedGraphDefs( sess, cond, expected_output=21.0) @@ -173,8 +173,8 @@ class ReconstructNonDebugGraphTest(test_util.TensorFlowTestCase): toy_loss = x * (u - v) train_op = gradient_descent.GradientDescentOptimizer( learning_rate=0.1).minimize(toy_loss, name="train_op") - sess.run(u.initializer) - sess.run(v.initializer) + self.evaluate(u.initializer) + self.evaluate(v.initializer) self._compareOriginalAndReconstructedGraphDefs(sess, train_op) diff --git a/tensorflow/python/debug/lib/dist_session_debug_grpc_test.py b/tensorflow/python/debug/lib/dist_session_debug_grpc_test.py index 74498c8ea3d..b78c3d16d48 100644 --- a/tensorflow/python/debug/lib/dist_session_debug_grpc_test.py +++ b/tensorflow/python/debug/lib/dist_session_debug_grpc_test.py @@ -131,8 +131,8 @@ class DistributedSessionDebugTest(test_util.TensorFlowTestCase): with session.Session( config=self.session_config, graph=graph, target=self.server_target) as sess: - sess.run(self.a.initializer) - sess.run(self.b.initializer) + self.evaluate(self.a.initializer) + self.evaluate(self.b.initializer) run_options = config_pb2.RunOptions() debug_utils.watch_graph( @@ -198,8 +198,8 @@ class DistributedSessionDebugTest(test_util.TensorFlowTestCase): with session.Session( config=self.session_config, graph=graph, target=self.server_target) as sess: - sess.run(self.a.initializer) - sess.run(self.b.initializer) + self.evaluate(self.a.initializer) + self.evaluate(self.b.initializer) def watch_fn(feeds, fetch_keys): del feeds, fetch_keys diff --git a/tensorflow/python/debug/lib/session_debug_multi_gpu_test.py b/tensorflow/python/debug/lib/session_debug_multi_gpu_test.py index b0dc25851ca..8eef45392f2 100644 --- a/tensorflow/python/debug/lib/session_debug_multi_gpu_test.py +++ b/tensorflow/python/debug/lib/session_debug_multi_gpu_test.py @@ -67,7 +67,7 @@ class SessionDebugMultiGPUTest(test_util.TensorFlowTestCase): u1 = math_ops.multiply(v, v, name="u1") w = math_ops.subtract(u1, u0, name="w") - sess.run(v.initializer) + self.evaluate(v.initializer) run_options = config_pb2.RunOptions(output_partition_graphs=True) debug_utils.watch_graph(run_options, sess.graph, diff --git a/tensorflow/python/debug/lib/source_utils_test.py b/tensorflow/python/debug/lib/source_utils_test.py index 4a8d4eaa99f..a16d68329a3 100644 --- a/tensorflow/python/debug/lib/source_utils_test.py +++ b/tensorflow/python/debug/lib/source_utils_test.py @@ -109,8 +109,8 @@ class SourceHelperTest(test_util.TensorFlowTestCase): self.w = math_ops.matmul(self.u, self.v, name="w") self.w_line_number = line_number_above() - sess.run(self.u.initializer) - sess.run(self.v.initializer) + self.evaluate(self.u.initializer) + self.evaluate(self.v.initializer) run_options = config_pb2.RunOptions(output_partition_graphs=True) debug_utils.watch_graph( diff --git a/tensorflow/python/distribute/distribute_coordinator_test.py b/tensorflow/python/distribute/distribute_coordinator_test.py index 5d336648ce9..bf81ac04551 100644 --- a/tensorflow/python/distribute/distribute_coordinator_test.py +++ b/tensorflow/python/distribute/distribute_coordinator_test.py @@ -235,7 +235,7 @@ class DistributeCoordinatorTestBase(test.TestCase): result = math_ops.add_n(xs) variables.global_variables_initializer().run() - result_value = sess.run(result) + result_value = self.evaluate(result) self.assertEqual(result_value, expected) if result_value == expected: self._result_correct += 1 @@ -294,7 +294,7 @@ class DistributeCoordinatorTestBase(test.TestCase): if len(uninit_vars) == 0: break - sess.run(train_op) + self.evaluate(train_op) # Synchronize workers after one step to make sure they all have finished # training. @@ -327,7 +327,7 @@ class DistributeCoordinatorTestBase(test.TestCase): # The monitored session will run init or ready ops. with monitored_session.MonitoredSession() as sess: - sess.run(train_op) + self.evaluate(train_op) # Synchronize workers after one step to make sure they all have finished # training. diff --git a/tensorflow/python/distribute/input_ops_test.py b/tensorflow/python/distribute/input_ops_test.py index cbb93e89952..54f7c5d0121 100644 --- a/tensorflow/python/distribute/input_ops_test.py +++ b/tensorflow/python/distribute/input_ops_test.py @@ -92,7 +92,7 @@ class AutoShardDatasetTest(test.TestCase): with self.cached_session() as sess: for f in range(self._shard_index, self._num_files, self._num_shards): for r in range(self._num_records): - self.assertAllEqual(record_fn(r, f), sess.run(next_element)) + self.assertAllEqual(record_fn(r, f), self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) @@ -205,10 +205,11 @@ class AutoShardDatasetTest(test.TestCase): with self.cached_session() as sess: for f in range(self._shard_index, self._num_files, self._num_shards): for r in range(self._num_records): - self.assertAllEqual(self._record(r, f), sess.run(next_element)) + self.assertAllEqual(self._record(r, f), self.evaluate(next_element)) for f in range(self._shard_index, self._num_files, self._num_shards): for r in range(self._num_records): - self.assertAllEqual(self._text_line(r, f), sess.run(next_element)) + self.assertAllEqual( + self._text_line(r, f), self.evaluate(next_element)) with self.assertRaises(errors.OutOfRangeError): sess.run(next_element) diff --git a/tensorflow/python/eager/def_function_test.py b/tensorflow/python/eager/def_function_test.py index f0f71a219e6..54991344b75 100644 --- a/tensorflow/python/eager/def_function_test.py +++ b/tensorflow/python/eager/def_function_test.py @@ -149,9 +149,9 @@ class DefFunctionTest(test.TestCase): result = fn(3.0) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) self.assertAllEqual(sess.run(state[0]), 2.0) - self.assertAllEqual(sess.run(result), 6.0) + self.assertAllEqual(self.evaluate(result), 6.0) def testLegacyGraphModeVariablesNonTrivialInitializer(self): with ops.Graph().as_default(), self.test_session() as sess: @@ -168,9 +168,9 @@ class DefFunctionTest(test.TestCase): result = fn(3.0) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) self.assertAllEqual(sess.run(state[0]), 6.0) - self.assertAllEqual(sess.run(result), 18.0) + self.assertAllEqual(self.evaluate(result), 18.0) def testLegacyGraphModeInputDependentInitializerFails(self): with ops.Graph().as_default(): diff --git a/tensorflow/python/eager/function_gradients_test.py b/tensorflow/python/eager/function_gradients_test.py index d4f8aaa7e33..1ba596573f9 100644 --- a/tensorflow/python/eager/function_gradients_test.py +++ b/tensorflow/python/eager/function_gradients_test.py @@ -78,7 +78,7 @@ class FunctionGradientsTest(test.TestCase, parameterized.TestCase): c = constant_op.constant([[2.]]) f_c = f(c) g, = gradients_impl.gradients(f_c, c) - self.assertAllEqual(sess.run(g).values, [[1.0]]) + self.assertAllEqual(self.evaluate(g).values, [[1.0]]) def testNoSymGradNestedDefun(self): diff --git a/tensorflow/python/eager/function_test.py b/tensorflow/python/eager/function_test.py index 98040dc68c4..fe5f0ef57f2 100644 --- a/tensorflow/python/eager/function_test.py +++ b/tensorflow/python/eager/function_test.py @@ -564,7 +564,7 @@ class FunctionTest(test.TestCase, parameterized.TestCase): variables.global_variables_initializer().run() call = def_function.function(o.call) op = call() - self.assertAllEqual(sess.run(op), 2.0) + self.assertAllEqual(self.evaluate(op), 2.0) def testGraphModeManyFunctions(self): with ops.Graph().as_default(), self.cached_session(): @@ -1733,7 +1733,7 @@ class FunctionTest(test.TestCase, parameterized.TestCase): function.register(cpu_boost, x) y = gpu_boost(x) - y_value = sess.run(y) + y_value = self.evaluate(y) if test.is_gpu_available(): self.assertEqual(y_value, 5.0) diff --git a/tensorflow/python/feature_column/feature_column_test.py b/tensorflow/python/feature_column/feature_column_test.py index 73df7d9eb8d..e069b96bb92 100644 --- a/tensorflow/python/feature_column/feature_column_test.py +++ b/tensorflow/python/feature_column/feature_column_test.py @@ -1026,7 +1026,7 @@ class CrossedColumnTest(test.TestCase): outputs = _transform_features(features, [price_cross_wire]) output = outputs[price_cross_wire] with self.cached_session() as sess: - output_val = sess.run(output) + output_val = self.evaluate(output) self.assertAllEqual( [[0, 0], [0, 1], [1, 0], [1, 1], [1, 2], [1, 3]], output_val.indices) for val in output_val.values: @@ -1880,7 +1880,8 @@ class LinearModelTest(test.TestCase): sess.run(body_style_var.assign([[-10.], [-100.], [-1000.]])) sess.run(bias.assign([5.])) - self.assertAllClose([[10 - 1000 + 5.], [1000 - 10 + 5.]], sess.run(net)) + self.assertAllClose([[10 - 1000 + 5.], [1000 - 10 + 5.]], + self.evaluate(net)) def test_with_1d_unknown_shape_sparse_tensor(self): price = fc.numeric_column('price') @@ -2514,7 +2515,8 @@ class _LinearModelTest(test.TestCase): sess.run(body_style_var.assign([[-10.], [-100.], [-1000.]])) sess.run(bias.assign([5.])) - self.assertAllClose([[10 - 1000 + 5.], [1000 - 10 + 5.]], sess.run(net)) + self.assertAllClose([[10 - 1000 + 5.], [1000 - 10 + 5.]], + self.evaluate(net)) def test_with_1d_unknown_shape_sparse_tensor(self): price = fc.numeric_column('price') diff --git a/tensorflow/python/feature_column/feature_column_v2_test.py b/tensorflow/python/feature_column/feature_column_v2_test.py index 78321ee0969..251ede925c6 100644 --- a/tensorflow/python/feature_column/feature_column_v2_test.py +++ b/tensorflow/python/feature_column/feature_column_v2_test.py @@ -1190,7 +1190,7 @@ class CrossedColumnTest(test.TestCase): outputs = fc._transform_features(features, [price_cross_wire], None) output = outputs[price_cross_wire] with self.cached_session() as sess: - output_val = sess.run(output) + output_val = self.evaluate(output) self.assertAllEqual( [[0, 0], [0, 1], [1, 0], [1, 1], [1, 2], [1, 3]], output_val.indices) for val in output_val.values: @@ -2091,7 +2091,8 @@ class LinearModelTest(test.TestCase): sess.run(body_style_var.assign([[-10.], [-100.], [-1000.]])) sess.run(bias.assign([5.])) - self.assertAllClose([[10 - 1000 + 5.], [100 - 10 + 5.]], sess.run(net)) + self.assertAllClose([[10 - 1000 + 5.], [100 - 10 + 5.]], + self.evaluate(net)) coord.request_stop() coord.join(threads) @@ -2127,7 +2128,8 @@ class LinearModelTest(test.TestCase): sess.run(body_style_var.assign([[-10.], [-100.], [-1000.]])) sess.run(bias.assign([5.])) - self.assertAllClose([[10 - 1000 + 5.], [1000 - 10 + 5.]], sess.run(net)) + self.assertAllClose([[10 - 1000 + 5.], [1000 - 10 + 5.]], + self.evaluate(net)) def test_with_1d_unknown_shape_sparse_tensor(self): price = fc.numeric_column_v2('price') @@ -2849,7 +2851,8 @@ class OldLinearModelTest(test.TestCase): sess.run(body_style_var.assign([[-10.], [-100.], [-1000.]])) sess.run(bias.assign([5.])) - self.assertAllClose([[10 - 1000 + 5.], [1000 - 10 + 5.]], sess.run(net)) + self.assertAllClose([[10 - 1000 + 5.], [1000 - 10 + 5.]], + self.evaluate(net)) def test_with_1d_unknown_shape_sparse_tensor(self): price = fc.numeric_column_v2('price') diff --git a/tensorflow/python/framework/function_test.py b/tensorflow/python/framework/function_test.py index 971219d5b05..90deb9765f2 100644 --- a/tensorflow/python/framework/function_test.py +++ b/tensorflow/python/framework/function_test.py @@ -102,7 +102,7 @@ class FunctionTest(test.TestCase): call = MyIdentityFunc([18.0]) self.assertEqual("MyIdentity", call.op.name) with session.Session() as sess: - self.assertAllEqual([18.0], sess.run(call)) + self.assertAllEqual([18.0], self.evaluate(call)) def testIdentityImplicitDeref(self): @@ -116,8 +116,8 @@ class FunctionTest(test.TestCase): self.assertEqual("MyIdentity", call.op.name) for cfg in _OptimizerOptions(): with session.Session(config=cfg) as sess: - sess.run(var.initializer) - self.assertAllEqual([18.0], sess.run(call)) + self.evaluate(var.initializer) + self.assertAllEqual([18.0], self.evaluate(call)) def testIdentityOutputName(self): @@ -130,7 +130,7 @@ class FunctionTest(test.TestCase): call = MyIdentityFunc([18.0]) self.assertEqual("MyIdentity", call.op.name) with session.Session() as sess: - self.assertAllEqual([18.0], sess.run(call)) + self.assertAllEqual([18.0], self.evaluate(call)) def testTooManyOutputNames(self): @@ -158,7 +158,7 @@ class FunctionTest(test.TestCase): call = APlus2B([1.0], [2.0]) self.assertEqual("APlus2B", call.op.name) with session.Session() as sess: - self.assertAllEqual([5.0], sess.run(call)) + self.assertAllEqual([5.0], self.evaluate(call)) def testFunctionWithNoOutput(self): @@ -187,7 +187,7 @@ class FunctionTest(test.TestCase): call = APlus2B([1.0], [2.0]) self.assertEqual("APlus2B", call.op.name) with session.Session() as sess: - self.assertAllEqual([5.0], sess.run(call)) + self.assertAllEqual([5.0], self.evaluate(call)) def testDefineFunctionDuplicateOutputs(self): @@ -224,8 +224,8 @@ class FunctionTest(test.TestCase): call_g = XSquarePlusOneGrad([2.0], [0.1]) with session.Session() as sess: - self.assertAllClose([5.0], sess.run(call_f)) - self.assertAllClose([0.4], sess.run(call_g)) + self.assertAllClose([5.0], self.evaluate(call_f)) + self.assertAllClose([0.4], self.evaluate(call_g)) def testTanhSymGrad(self): @@ -387,7 +387,7 @@ class FunctionTest(test.TestCase): call = AConstant() self.assertEqual("AConstant", call.op.name) with session.Session() as sess: - self.assertAllEqual([42], sess.run(call)) + self.assertAllEqual([42], self.evaluate(call)) def testDefineFunctionNames(self): @@ -468,7 +468,7 @@ class FunctionTest(test.TestCase): loop = control_flow_ops.while_loop(lambda x: x < 1e5, Body, [1.0]) - ans = sess.run(loop) + ans = self.evaluate(loop) self.assertAllClose(ans, 131072.) def testControlFlowStrictness(self): @@ -650,8 +650,8 @@ class FunctionTest(test.TestCase): # pylint: enable=unexpected-keyword-arg self.assertEqual("next", call2.op.name) with session.Session() as sess: - self.assertAllEqual([1], sess.run(call1)) - self.assertAllEqual([0], sess.run(call2)) + self.assertAllEqual([1], self.evaluate(call1)) + self.assertAllEqual([0], self.evaluate(call2)) def testNestedFunction(self): @@ -794,7 +794,7 @@ class FunctionTest(test.TestCase): y = Foo() with self.session(graph=g) as sess: - self.assertEqual(sess.run(y), 10) + self.assertEqual(self.evaluate(y), 10) def testCaptureInCond(self): g = ops.Graph() @@ -809,8 +809,8 @@ class FunctionTest(test.TestCase): z = Foo(False) with self.session(graph=g) as sess: - self.assertEqual(sess.run(y), 1) - self.assertEqual(sess.run(z), 2) + self.assertEqual(self.evaluate(y), 1) + self.assertEqual(self.evaluate(z), 2) def testStableName(self): @@ -900,7 +900,7 @@ class FunctionTest(test.TestCase): self.assertEqual(global_vars[0].name, "linear/w:0") with session.Session() as sess: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) output_val = sess.run( output_op, feed_dict={input_op: np.random.rand(32, 100)}) self.assertEqual(output_val.shape, (32, 100)) @@ -928,7 +928,7 @@ class FunctionTest(test.TestCase): self.assertEqual(global_vars[0].name, "vs1/var:0") with session.Session() as sess: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) out1, out2 = sess.run( [out1_op, out2_op], feed_dict={input_op: np.linspace(1, 10, 10)}) self.assertAllEqual(out1, np.linspace(2, 11, 10)) @@ -991,8 +991,8 @@ class FunctionTest(test.TestCase): result_2 = Bar(constant_op.constant(100, dtype=dtypes.int64)) with session.Session() as sess: - self.assertEqual(4.0, sess.run(result_1)) - self.assertEqual(100, sess.run(result_2)) + self.assertEqual(4.0, self.evaluate(result_1)) + self.assertEqual(100, self.evaluate(result_2)) self.assertEqual((4.0, 100), sess.run((result_1, result_2))) def testStatefulFunction(self): @@ -1052,8 +1052,8 @@ class FunctionTest(test.TestCase): for config in _OptimizerOptions(): config.device_count["CPU"] = 2 with session.Session(config=config) as sess: - self.assertEqual(42.0, sess.run(f_0)) - self.assertEqual(44.0, sess.run(f_1)) + self.assertEqual(42.0, self.evaluate(f_0)) + self.assertEqual(44.0, self.evaluate(f_1)) self.assertEqual((42.0, 44.0), sess.run((f_0, f_1))) def testGuaranteedConstsAreCaptured(self): @@ -1076,7 +1076,7 @@ class FunctionTest(test.TestCase): return output with self.session(use_gpu=False) as sess: - sess.run(var.initializer) + self.evaluate(var.initializer) _ = sess.run(CapturesGuaranteedConst(), {also_not_const: 1.0}) def testSameFunctionDifferentGrads(self): @@ -1651,8 +1651,8 @@ class ModuleFunctionTest(test.TestCase): y = LinearWithCApi(a, b, c) z = Linear2WithCApi(a, b, c, d, e) with session.Session() as sess: - self.assertAllEqual([[1]], sess.run(y)) - self.assertAllEqual([[5]], sess.run(z)) + self.assertAllEqual([[1]], self.evaluate(y)) + self.assertAllEqual([[5]], self.evaluate(z)) class VariableHoistingTest(test.TestCase): @@ -1704,7 +1704,7 @@ class VariableHoistingTest(test.TestCase): self.assertEqual("Foo/b", b.op.name) with self.session(graph=g) as sess: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) w, b, x, y0, loss, dw, db = sess.run([w, b, x, y0, loss, dw, db]) self.assertAllEqual(w.shape, (64, 64)) diff --git a/tensorflow/python/framework/graph_util_test.py b/tensorflow/python/framework/graph_util_test.py index 563a177dd06..7a9f2e8d860 100644 --- a/tensorflow/python/framework/graph_util_test.py +++ b/tensorflow/python/framework/graph_util_test.py @@ -211,7 +211,7 @@ class DeviceFunctionsTest(test.TestCase): with session.Session() as sess: init = variables.variables_initializer([variable_node]) sess.run(init) - output = sess.run(output_node) + output = self.evaluate(output_node) self.assertNear(4.0, output, 0.00001) variable_graph_def = sess.graph.as_graph_def() @@ -242,8 +242,8 @@ class DeviceFunctionsTest(test.TestCase): output_node = math_ops_lib.multiply( variable_node, 2.0, name="output_node") with session.Session() as sess: - sess.run(variable_node.initializer) - output = sess.run(output_node) + self.evaluate(variable_node.initializer) + output = self.evaluate(output_node) self.assertNear(2.0, output, 0.00001) variable_graph_def = sess.graph.as_graph_def() # First get the constant_graph_def when variable_names_whitelist is @@ -256,7 +256,7 @@ class DeviceFunctionsTest(test.TestCase): # Then initialize the unused variable, and get another # constant_graph_def when variable_names_whitelist is not set. - sess.run(another_variable.initializer) + self.evaluate(another_variable.initializer) constant_graph_def_without_variable_whitelist = ( graph_util.convert_variables_to_constants( sess, variable_graph_def, ["output_node"])) @@ -295,7 +295,7 @@ class DeviceFunctionsTest(test.TestCase): ["Variable", "VariableV2", "VarHandleOp", "ReadVariableOp"]) with session.Session() as sess: output_node = sess.graph.get_tensor_by_name("output_node:0") - output = sess.run(output_node) + output = self.evaluate(output_node) self.assertNear(2.0, output, 0.00001) def create_node_def(self, op, name, inputs): diff --git a/tensorflow/python/framework/importer_test.py b/tensorflow/python/framework/importer_test.py index fc7367649e1..a57f0b36540 100644 --- a/tensorflow/python/framework/importer_test.py +++ b/tensorflow/python/framework/importer_test.py @@ -398,10 +398,10 @@ class ImportGraphDefTest(test.TestCase): # TODO(b/76173421): make this work (currently DCHECKS) # with self.cached_session() as sess: # sess.run(imported_init) - # self.assertEqual(sess.run(imported_var), 1.0) - # self.assertEqual(sess.run(imported_assign), 2.0) - # self.assertEqual(list(sess.run(imported_shape)), []) - # self.assertEqual(list(sess.run(new_var_shape)), []) + # self.assertEqual(self.evaluate(imported_var), 1.0) + # self.assertEqual(self.evaluate(imported_assign), 2.0) + # self.assertEqual(list(self.evaluate(imported_shape)), []) + # self.assertEqual(list(self.evaluate(new_var_shape)), []) def testWhileLoop(self): # Produce GraphDef containing while loop. @@ -418,7 +418,7 @@ class ImportGraphDefTest(test.TestCase): return_elements=[r.name]) self.assertEqual(imported_r.name, "import/" + r.name) with self.cached_session() as sess: - self.assertEqual(sess.run(imported_r), 10) + self.assertEqual(self.evaluate(imported_r), 10) def testImportWhileLoopInCond(self): # Produce GraphDef containing while loop. @@ -458,7 +458,7 @@ class ImportGraphDefTest(test.TestCase): lambda i: i < 2, ImportFn, [0], shape_invariants=[tensor_shape.TensorShape(None)]) with self.cached_session() as sess: - self.assertEqual(sess.run(out), 10) + self.assertEqual(self.evaluate(out), 10) def testTypeMismatchInGraphDef(self): # TODO(skyewm): improve error message diff --git a/tensorflow/python/framework/meta_graph_test.py b/tensorflow/python/framework/meta_graph_test.py index fc98b91a016..3605ed7fa2a 100644 --- a/tensorflow/python/framework/meta_graph_test.py +++ b/tensorflow/python/framework/meta_graph_test.py @@ -492,8 +492,8 @@ class ScopedMetaGraphTest(test.TestCase): init_op = variables.global_variables_initializer() grad = gradients_impl.gradients([output], [var]) with session.Session() as sess: - sess.run(init_op) - expected_grad_value = sess.run(grad) + self.evaluate(init_op) + expected_grad_value = self.evaluate(grad) # Restore the MetaGraphDef into a new Graph with an import scope. with ops.Graph().as_default(): @@ -518,8 +518,8 @@ class ScopedMetaGraphTest(test.TestCase): init_op = variables.global_variables_initializer() with session.Session() as sess: - sess.run(init_op) - actual_grad_value = sess.run(grad) + self.evaluate(init_op) + actual_grad_value = self.evaluate(grad) self.assertEqual(expected_grad_value, actual_grad_value) def testImportWhileLoopInWhileLoop(self): @@ -544,7 +544,7 @@ class ScopedMetaGraphTest(test.TestCase): _, x = control_flow_ops.while_loop(lambda i, x: i < 2, body, [0, 0.0], name="") with session.Session() as sess: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) sess.run(x) def testScopedImportUnderNameScope(self): @@ -869,7 +869,7 @@ class MetaGraphWithVariableScopeTest(test.TestCase): initializer = variables.local_variables_initializer() sess.run(initializer) - sess.run(update_op) + self.evaluate(update_op) meta_graph.export_scoped_meta_graph( filename=meta_graph_filename, graph=graph) diff --git a/tensorflow/python/framework/ops_test.py b/tensorflow/python/framework/ops_test.py index 3957d1de53d..b9c690849d3 100644 --- a/tensorflow/python/framework/ops_test.py +++ b/tensorflow/python/framework/ops_test.py @@ -517,21 +517,21 @@ class OperationTest(test_util.TensorFlowTestCase): self.assertEquals(x.consumers(), []) self.assertEquals(y.consumers(), [z.op, z.op]) with session.Session(graph=g) as sess: - self.assertEquals(sess.run(z), 4) + self.assertEquals(self.evaluate(z), 4) z.op._update_input(0, x) # pylint: disable=protected-access self.assertEquals(list(z.op.inputs), [x, y]) self.assertEquals(x.consumers(), [z.op]) self.assertEquals(y.consumers(), [z.op]) with session.Session(graph=g) as sess: - self.assertEquals(sess.run(z), 3) + self.assertEquals(self.evaluate(z), 3) z.op._update_input(1, y) # pylint: disable=protected-access self.assertEquals(list(z.op.inputs), [x, y]) self.assertEquals(x.consumers(), [z.op]) self.assertEquals(y.consumers(), [z.op]) with session.Session(graph=g) as sess: - self.assertEquals(sess.run(z), 3) + self.assertEquals(self.evaluate(z), 3) def testUpdateInputGraphError(self): g_0 = ops.Graph() diff --git a/tensorflow/python/framework/smart_cond_test.py b/tensorflow/python/framework/smart_cond_test.py index b8a9672b06d..174ada9fe11 100644 --- a/tensorflow/python/framework/smart_cond_test.py +++ b/tensorflow/python/framework/smart_cond_test.py @@ -109,8 +109,8 @@ class SmartCaseTest(test_util.TensorFlowTestCase): exclusive=True) with session.Session() as sess: # No feed_dict necessary - self.assertEqual(sess.run(y), 1) - self.assertEqual(sess.run(z), 1) + self.assertEqual(self.evaluate(y), 1) + self.assertEqual(self.evaluate(z), 1) def testFalse(self): conditions = [(False, raise_exception)] @@ -121,8 +121,8 @@ class SmartCaseTest(test_util.TensorFlowTestCase): default=lambda: constant_op.constant(1), exclusive=True) with session.Session() as sess: - self.assertEqual(sess.run(y), 1) - self.assertEqual(sess.run(z), 1) + self.assertEqual(self.evaluate(y), 1) + self.assertEqual(self.evaluate(z), 1) def testMix(self): x = array_ops.placeholder(dtype=dtypes.int32, shape=[]) diff --git a/tensorflow/python/framework/sparse_tensor_test.py b/tensorflow/python/framework/sparse_tensor_test.py index 2f7591abbd0..9ee1bd75a53 100644 --- a/tensorflow/python/framework/sparse_tensor_test.py +++ b/tensorflow/python/framework/sparse_tensor_test.py @@ -50,7 +50,7 @@ class SparseTensorTest(test_util.TensorFlowTestCase): self.assertAllEqual(indices, value.indices) self.assertAllEqual(values, value.values) self.assertAllEqual(shape, value.dense_shape) - sess_run_value = sess.run(sp) + sess_run_value = self.evaluate(sp) self.assertAllEqual(sess_run_value.indices, value.indices) self.assertAllEqual(sess_run_value.values, value.values) self.assertAllEqual(sess_run_value.dense_shape, value.dense_shape) diff --git a/tensorflow/python/framework/tensor_util_test.py b/tensorflow/python/framework/tensor_util_test.py index bdf759f2204..87d65c8c466 100644 --- a/tensorflow/python/framework/tensor_util_test.py +++ b/tensorflow/python/framework/tensor_util_test.py @@ -771,7 +771,7 @@ class TensorUtilTest(test.TestCase): with self.cached_session() as sess: ma = MockArray(np.array([10, 20, 30])) t = ops.convert_to_tensor(ma) - a = sess.run(t) + a = self.evaluate(t) self.assertEquals(np.int64, a.dtype) self.assertAllClose(np.array([10, 20, 30], dtype=np.int64), a) diff --git a/tensorflow/python/grappler/constant_folding_test.py b/tensorflow/python/grappler/constant_folding_test.py index ab1d0ed25b9..30c1e146814 100644 --- a/tensorflow/python/grappler/constant_folding_test.py +++ b/tensorflow/python/grappler/constant_folding_test.py @@ -61,7 +61,7 @@ class ConstantFoldingTest(test.TestCase): back_prop=False, parallel_iterations=1) with session.Session() as sess: - y_v = sess.run(y) + y_v = self.evaluate(y) self.assertAllEqual(np.zeros([10, 20, 30]), y_v) diff --git a/tensorflow/python/grappler/layout_optimizer_test.py b/tensorflow/python/grappler/layout_optimizer_test.py index 7b68d5e80da..55ccfbb93c3 100644 --- a/tensorflow/python/grappler/layout_optimizer_test.py +++ b/tensorflow/python/grappler/layout_optimizer_test.py @@ -241,7 +241,7 @@ class LayoutOptimizerTest(test.TestCase): if restore: saver.restore(sess, checkpoint_path) else: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) np.random.seed(0) for _ in range(2): @@ -262,7 +262,7 @@ class LayoutOptimizerTest(test.TestCase): output = _two_layer_model(x) with session.Session(config=_get_config(False)) as sess: - output_val_ref = sess.run(output) + output_val_ref = self.evaluate(output) with session.Session(config=_get_config()) as sess: metadata = config_pb2.RunMetadata() @@ -365,7 +365,7 @@ class LayoutOptimizerTest(test.TestCase): output = array_ops.identity(pad) with session.Session(config=_get_config(False)) as sess: - output_val_ref = sess.run(output) + output_val_ref = self.evaluate(output) with session.Session(config=_get_config()) as sess: metadata = config_pb2.RunMetadata() @@ -396,7 +396,7 @@ class LayoutOptimizerTest(test.TestCase): output = array_ops.identity(reduce_sum) with session.Session(config=_get_config(False)) as sess: - output_val_ref = sess.run(output) + output_val_ref = self.evaluate(output) with session.Session(config=_get_config()) as sess: metadata = config_pb2.RunMetadata() @@ -425,7 +425,7 @@ class LayoutOptimizerTest(test.TestCase): output = array_ops.identity(cast) with session.Session(config=_get_config(False)) as sess: - output_val_ref = sess.run(output) + output_val_ref = self.evaluate(output) with session.Session(config=_get_config()) as sess: metadata = config_pb2.RunMetadata() @@ -456,7 +456,7 @@ class LayoutOptimizerTest(test.TestCase): output = array_ops.identity(squeeze) with session.Session(config=_get_config(False)) as sess: - output_val_ref = sess.run(output) + output_val_ref = self.evaluate(output) with session.Session(config=_get_config()) as sess: metadata = config_pb2.RunMetadata() @@ -486,7 +486,7 @@ class LayoutOptimizerTest(test.TestCase): output = array_ops.identity(squeeze) with session.Session(config=_get_config(False)) as sess: - output_val_ref = sess.run(output) + output_val_ref = self.evaluate(output) with session.Session(config=_get_config()) as sess: metadata = config_pb2.RunMetadata() @@ -516,7 +516,7 @@ class LayoutOptimizerTest(test.TestCase): output = array_ops.identity(squeeze) with session.Session(config=_get_config(False)) as sess: - output_val_ref = sess.run(output) + output_val_ref = self.evaluate(output) with session.Session(config=_get_config()) as sess: metadata = config_pb2.RunMetadata() @@ -545,7 +545,7 @@ class LayoutOptimizerTest(test.TestCase): output = array_ops.identity(reduce_sum) with session.Session(config=_get_config(False)) as sess: - output_val_ref = sess.run(output) + output_val_ref = self.evaluate(output) with session.Session(config=_get_config()) as sess: metadata = config_pb2.RunMetadata() @@ -574,7 +574,7 @@ class LayoutOptimizerTest(test.TestCase): output = array_ops.identity(reduce_sum) with session.Session(config=_get_config(False)) as sess: - output_val_ref = sess.run(output) + output_val_ref = self.evaluate(output) with session.Session(config=_get_config()) as sess: metadata = config_pb2.RunMetadata() @@ -603,7 +603,7 @@ class LayoutOptimizerTest(test.TestCase): output = array_ops.identity(reduce_sum) with session.Session(config=_get_config(False)) as sess: - output_val_ref = sess.run(output) + output_val_ref = self.evaluate(output) with session.Session(config=_get_config()) as sess: metadata = config_pb2.RunMetadata() @@ -632,7 +632,7 @@ class LayoutOptimizerTest(test.TestCase): output = array_ops.identity(reduce_sum) with session.Session(config=_get_config(False)) as sess: - output_val_ref = sess.run(output) + output_val_ref = self.evaluate(output) with session.Session(config=_get_config()) as sess: metadata = config_pb2.RunMetadata() @@ -662,7 +662,7 @@ class LayoutOptimizerTest(test.TestCase): output = array_ops.identity(reduce_sum) with session.Session(config=_get_config(False)) as sess: - output_val_ref = sess.run(output) + output_val_ref = self.evaluate(output) with session.Session(config=_get_config()) as sess: metadata = config_pb2.RunMetadata() @@ -691,7 +691,7 @@ class LayoutOptimizerTest(test.TestCase): output = array_ops.identity(reduce_sum) with session.Session(config=_get_config(False)) as sess: - output_val_ref = sess.run(output) + output_val_ref = self.evaluate(output) with session.Session(config=_get_config()) as sess: metadata = config_pb2.RunMetadata() @@ -724,7 +724,7 @@ class LayoutOptimizerTest(test.TestCase): output = array_ops.identity(concat) with session.Session(config=_get_config(False)) as sess: - output_val_ref = sess.run(output) + output_val_ref = self.evaluate(output) with session.Session(config=_get_config()) as sess: metadata = config_pb2.RunMetadata() @@ -835,7 +835,7 @@ class LayoutOptimizerTest(test.TestCase): output = array_ops.identity(reverse) with session.Session(config=_get_config(False)) as sess: - output_val_ref = sess.run(output) + output_val_ref = self.evaluate(output) with session.Session(config=_get_config()) as sess: metadata = config_pb2.RunMetadata() @@ -905,7 +905,7 @@ class LayoutOptimizerTest(test.TestCase): output = array_ops.identity(select) with session.Session(config=_get_config(False)) as sess: - output_val_ref = sess.run(output) + output_val_ref = self.evaluate(output) with session.Session(config=_get_config()) as sess: metadata = config_pb2.RunMetadata() @@ -966,7 +966,7 @@ class LayoutOptimizerTest(test.TestCase): output = array_ops.identity(select) with session.Session(config=_get_config(False)) as sess: - output_val_ref = sess.run(output) + output_val_ref = self.evaluate(output) with session.Session(config=_get_config()) as sess: metadata = config_pb2.RunMetadata() @@ -1179,7 +1179,7 @@ class LayoutOptimizerTest(test.TestCase): output = array_ops.identity(s) with session.Session(config=_get_config(False)) as sess: - output_val_ref = sess.run(output) + output_val_ref = self.evaluate(output) with session.Session(config=_get_config()) as sess: metadata = config_pb2.RunMetadata() @@ -1214,7 +1214,7 @@ class LayoutOptimizerTest(test.TestCase): output = array_ops.identity(s) with session.Session(config=_get_config(False)) as sess: - output_val_ref = sess.run(output) + output_val_ref = self.evaluate(output) with session.Session(config=_get_config()) as sess: metadata = config_pb2.RunMetadata() @@ -1347,7 +1347,7 @@ class LayoutOptimizerTest(test.TestCase): output = _loop() with session.Session(config=_get_config(False)) as sess: - output_val_ref = sess.run(output) + output_val_ref = self.evaluate(output) with session.Session(config=_get_config()) as sess: metadata = config_pb2.RunMetadata() @@ -1374,7 +1374,7 @@ class LayoutOptimizerTest(test.TestCase): output = _loop_with_branch() with session.Session(config=_get_config(False)) as sess: - output_val_ref = sess.run(output) + output_val_ref = self.evaluate(output) with session.Session(config=_get_config()) as sess: metadata = config_pb2.RunMetadata() @@ -1398,7 +1398,7 @@ class LayoutOptimizerTest(test.TestCase): output = _loop_with_vec_and_4d() with session.Session(config=_get_config(False)) as sess: - output_val_ref = sess.run(output) + output_val_ref = self.evaluate(output) with session.Session(config=_get_config()) as sess: metadata = config_pb2.RunMetadata() @@ -1422,7 +1422,7 @@ class LayoutOptimizerTest(test.TestCase): output = _model_with_second_port() with session.Session(config=_get_config(False)) as sess: - output_val_ref = sess.run(output) + output_val_ref = self.evaluate(output) with session.Session(config=_get_config()) as sess: metadata = config_pb2.RunMetadata() diff --git a/tensorflow/python/grappler/memory_optimizer_test.py b/tensorflow/python/grappler/memory_optimizer_test.py index 98cbb1a4b62..d233629cbbd 100644 --- a/tensorflow/python/grappler/memory_optimizer_test.py +++ b/tensorflow/python/grappler/memory_optimizer_test.py @@ -231,10 +231,10 @@ class MemoryOptimizerRecomputeTest(test.TestCase): train_op = graph.get_operation_by_name(train_op_name) loss_op = graph.get_tensor_by_name(loss_op_name) with session.Session(config=config, graph=graph) as sess: - sess.run(init_op) - sess.run(train_op) - sess.run(train_op) - return sess.run(loss_op) + self.evaluate(init_op) + self.evaluate(train_op) + self.evaluate(train_op) + return self.evaluate(loss_op) def testRecomputationRewritingNoErrors(self): """Tests that graph output is not significantly different with rewriting.""" @@ -295,8 +295,8 @@ class MemoryOptimizerRecomputeTest(test.TestCase): rewrite_options=manual_memory_config) session_config = config_pb2.ConfigProto(graph_options=graph_options) with session.Session(config=session_config) as sess: - sess.run(init_op) - sess.run(train_op) + self.evaluate(init_op) + self.evaluate(train_op) def testHintDoesRewrite(self): graph = self._annotated_graph()[0] diff --git a/tensorflow/python/keras/backend_test.py b/tensorflow/python/keras/backend_test.py index d8aa3e9b529..0ab651b59e1 100644 --- a/tensorflow/python/keras/backend_test.py +++ b/tensorflow/python/keras/backend_test.py @@ -136,7 +136,7 @@ class BackendUtilsTest(test.TestCase): x = keras.Input((3,)) y = keras.layers.BatchNormalization()(x) if not context.executing_eagerly(): - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) sess.run(y, feed_dict={x: np.random.random((2, 3))}) def test_learning_phase_scope(self): diff --git a/tensorflow/python/keras/layers/recurrent_test.py b/tensorflow/python/keras/layers/recurrent_test.py index 7172571f7cc..b1449069e32 100644 --- a/tensorflow/python/keras/layers/recurrent_test.py +++ b/tensorflow/python/keras/layers/recurrent_test.py @@ -1013,8 +1013,8 @@ class RNNTest(test.TestCase): inputs, _ = cell(inputs, initial_state) output = inputs if not context.executing_eagerly(): - sess.run(variables_lib.global_variables_initializer()) - output = sess.run(output) + self.evaluate(variables_lib.global_variables_initializer()) + output = self.evaluate(output) return output random_seed.set_random_seed(12345) diff --git a/tensorflow/python/kernel_tests/accumulate_n_test.py b/tensorflow/python/kernel_tests/accumulate_n_test.py index ae24cf8f14a..c7f11f854d1 100644 --- a/tensorflow/python/kernel_tests/accumulate_n_test.py +++ b/tensorflow/python/kernel_tests/accumulate_n_test.py @@ -65,7 +65,7 @@ class AccumulateNV2Test(test_util.TensorFlowTestCase): for _ in range(0, num_inputs) ] accum_n = math_ops.accumulate_n(input_vars) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) accum_n_grad = gradients.gradients(accum_n, input_vars) self.assertAllEqual( np.repeat(1.0, num_inputs), # d/dx (x + y + ...) = 1 diff --git a/tensorflow/python/kernel_tests/array_ops_test.py b/tensorflow/python/kernel_tests/array_ops_test.py index da29a070cd1..b9d9d54c982 100644 --- a/tensorflow/python/kernel_tests/array_ops_test.py +++ b/tensorflow/python/kernel_tests/array_ops_test.py @@ -832,7 +832,7 @@ class StridedSliceGradTest(test_util.TensorFlowTestCase): index = constant_op.constant(1, dtype=dtypes.int64) b = 2. * a[index] grad, = gradients_impl.gradients(b, a) - self.assertAllEqual(sess.run(grad), [0., 2., 0.]) + self.assertAllEqual(self.evaluate(grad), [0., 2., 0.]) class StridedSliceGradTypeTest(test_util.TensorFlowTestCase): @@ -845,7 +845,7 @@ class StridedSliceGradTypeTest(test_util.TensorFlowTestCase): math_ops.cast(math_ops.range(1, 5, 1), dtypes.float32), shape=(4, 1, 1))) varshape = variables.Variable([6, 4, 4], dtype=dtypes.int32) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) begin = constant_op.constant([0, 0, 0]) end = constant_op.constant([4, 1, 1]) strides = constant_op.constant([1, 1, 1]) @@ -858,7 +858,7 @@ class StridedSliceGradTypeTest(test_util.TensorFlowTestCase): math_ops.cast(math_ops.range(1, 5, 1), dtypes.float32), shape=(4, 1, 1)) original_shape = constant_op.constant([6, 4, 4], dtype=dtypes.int64) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) begin = constant_op.constant([0, 0, 0], dtype=dtypes.int64) end = constant_op.constant([4, 1, 1], dtype=dtypes.int64) strides = constant_op.constant([1, 1, 1], dtype=dtypes.int64) @@ -872,7 +872,7 @@ class StridedSliceGradTypeTest(test_util.TensorFlowTestCase): math_ops.cast(math_ops.range(1, 5, 1), dtypes.float32), shape=(4, 1, 1)) original_shape = constant_op.constant([6, 4, 4], dtype=dtypes.int64) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) begin = constant_op.constant([0, 0, 0], dtype=dtypes.int32) end = constant_op.constant([4, 1, 1], dtype=dtypes.int64) strides = constant_op.constant([1, 1, 1], dtype=dtypes.int64) @@ -1041,7 +1041,7 @@ class SliceAssignTest(test_util.TensorFlowTestCase): too_large_val = constant_op.constant([3, 4], dtype=dtypes.int64) v = resource_variable_ops.ResourceVariable(init_val) with self.cached_session() as sess: - sess.run(v.initializer) + self.evaluate(v.initializer) with self.assertRaises(ValueError): sess.run(v[:].assign(too_large_val)) with self.assertRaises(ValueError): @@ -1268,7 +1268,7 @@ class GuaranteeConstOpTest(test_util.TensorFlowTestCase): initializer=init_ops.constant_initializer(10.0), use_resource=use_resource) guarantee_a = array_ops.guarantee_const(a) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) self.assertEqual(10.0, guarantee_a.eval()) def testResourceRejection(self): @@ -1278,7 +1278,7 @@ class GuaranteeConstOpTest(test_util.TensorFlowTestCase): initializer=init_ops.constant_initializer(10.0), use_resource=True) guarantee_a = array_ops.guarantee_const(a.handle) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) with self.assertRaisesWithPredicateMatch(errors.InvalidArgumentError, "cannot be a resource variable"): guarantee_a.eval() diff --git a/tensorflow/python/kernel_tests/basic_gpu_test.py b/tensorflow/python/kernel_tests/basic_gpu_test.py index ac5cbc810a9..cd330481214 100644 --- a/tensorflow/python/kernel_tests/basic_gpu_test.py +++ b/tensorflow/python/kernel_tests/basic_gpu_test.py @@ -44,13 +44,13 @@ class GPUBinaryOpsTest(test.TestCase): inx = ops.convert_to_tensor(x) iny = ops.convert_to_tensor(y) out = tf_func(inx, iny) - tf_gpu = sess.run(out) + tf_gpu = self.evaluate(out) with self.cached_session(use_gpu=False) as sess: inx = ops.convert_to_tensor(x) iny = ops.convert_to_tensor(y) out = tf_func(inx, iny) - tf_cpu = sess.run(out) + tf_cpu = self.evaluate(out) self.assertAllClose(tf_cpu, tf_gpu) @@ -96,7 +96,7 @@ class MathBuiltinUnaryTest(test.TestCase): with self.cached_session(use_gpu=use_gpu) as sess: inx = ops.convert_to_tensor(x) ofunc = tf_func(inx) - tf_out = sess.run(ofunc) + tf_out = self.evaluate(ofunc) self.assertAllClose(np_out, tf_out) def _inv(self, x): @@ -148,7 +148,7 @@ class MathBuiltinUnaryTest(test.TestCase): iny = ops.convert_to_tensor(y + 0.1) ofunc = inx / iny out_func2 = math_ops.floor(ofunc) - tf_out = sess.run(out_func2) + tf_out = self.evaluate(out_func2) self.assertAllClose(np_out, tf_out) 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 12afb6a2ad8..adfb0949717 100644 --- a/tensorflow/python/kernel_tests/boosted_trees/quantile_ops_test.py +++ b/tensorflow/python/kernel_tests/boosted_trees/quantile_ops_test.py @@ -98,8 +98,8 @@ class QuantileOpsTest(test_util.TensorFlowTestCase): quantile_accumulator_handle, num_features=2) quantiles = boosted_trees_ops.boosted_trees_bucketize( [self._feature_0, self._feature_1], buckets) - sess.run(summary_op) - sess.run(flush_op) + self.evaluate(summary_op) + self.evaluate(flush_op) self.assertAllClose(self._feature_0_boundaries, buckets[0].eval()) self.assertAllClose(self._feature_1_boundaries, buckets[1].eval()) 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 cc3984015da..e4c5431c26c 100644 --- a/tensorflow/python/kernel_tests/boosted_trees/stats_ops_test.py +++ b/tensorflow/python/kernel_tests/boosted_trees/stats_ops_test.py @@ -65,10 +65,10 @@ class StatsOpsTest(test_util.TensorFlowTestCase): min_node_weight=0, max_splits=max_splits) - self.assertAllEqual([[1, 2], [1, 2]], sess.run(node_ids_list)) + self.assertAllEqual([[1, 2], [1, 2]], self.evaluate(node_ids_list)) self.assertAllClose([[0.004775, 0.41184], [0.02823, 0.41184]], sess.run(gains_list)) - self.assertAllEqual([[1, 1], [1, 1]], sess.run(thresholds_list)) + self.assertAllEqual([[1, 1], [1, 1]], self.evaluate(thresholds_list)) # The left node contrib will be later added to the previous node value to # make the left node value, and the same for right node contrib. self.assertAllClose([[[-.416667], [.568966]], [[-.6], [-.75]]], @@ -113,10 +113,10 @@ class StatsOpsTest(test_util.TensorFlowTestCase): min_node_weight=0, max_splits=max_splits) - self.assertAllEqual([[1, 2], [1, 2]], sess.run(node_ids_list)) + self.assertAllEqual([[1, 2], [1, 2]], self.evaluate(node_ids_list)) self.assertAllClose([[0., 0.33931375], [0.01879096, 0.33931375]], sess.run(gains_list)) - self.assertAllEqual([[0, 1], [1, 1]], sess.run(thresholds_list)) + self.assertAllEqual([[0, 1], [1, 1]], self.evaluate(thresholds_list)) # The left node contrib will be later added to the previous node value to # make the left node value, and the same for right node contrib. self.assertAllClose([[[0.], [.485294]], [[-.5], [-.6]]], @@ -162,9 +162,9 @@ class StatsOpsTest(test_util.TensorFlowTestCase): min_node_weight=0, max_splits=max_splits) - self.assertAllEqual([[0, 1], [1, 1]], sess.run(thresholds_list)) + self.assertAllEqual([[0, 1], [1, 1]], self.evaluate(thresholds_list)) - self.assertAllEqual([[1, 2], [1, 2]], sess.run(node_ids_list)) + self.assertAllEqual([[1, 2], [1, 2]], self.evaluate(node_ids_list)) self.assertAllClose([[[0.0], [0.3965517]], [[-0.4], [-0.5]]], sess.run(left_node_contribs_list)) @@ -214,12 +214,12 @@ class StatsOpsTest(test_util.TensorFlowTestCase): min_node_weight=0, max_splits=max_splits) - self.assertAllEqual([[1, 2], [1, 2]], sess.run(node_ids_list)) + self.assertAllEqual([[1, 2], [1, 2]], self.evaluate(node_ids_list)) self.assertAllClose([[-3., -2.66068625], [-2.98120904, -2.66068625]], sess.run(gains_list)) - self.assertAllEqual([[0, 1], [1, 1]], sess.run(thresholds_list)) + self.assertAllEqual([[0, 1], [1, 1]], self.evaluate(thresholds_list)) # The left node contrib will be later added to the previous node value to # make the left node value, and the same for right node contrib. self.assertAllClose([[[0.], [.485294]], [[-.5], [-.6]]], @@ -266,9 +266,9 @@ class StatsOpsTest(test_util.TensorFlowTestCase): # We can't split node 1 on feature 1 and node 2 on feature 2 because of # the min node weight. - self.assertAllEqual([[2], [1]], sess.run(node_ids_list)) - self.assertAllClose([[0.384314], [0.098013]], sess.run(gains_list)) - self.assertAllEqual([[1], [1]], sess.run(thresholds_list)) + self.assertAllEqual([[2], [1]], self.evaluate(node_ids_list)) + self.assertAllClose([[0.384314], [0.098013]], self.evaluate(gains_list)) + self.assertAllEqual([[1], [1]], self.evaluate(thresholds_list)) self.assertAllClose([[[0.4852941]], [[-.6]]], sess.run(left_node_contribs_list)) self.assertAllClose([[[-0.75]], [[-0.014925]]], @@ -311,9 +311,9 @@ class StatsOpsTest(test_util.TensorFlowTestCase): max_splits=max_splits) # We can't split either of the nodes on the first feature - self.assertEqual(2, len(sess.run(node_ids_list))) - self.assertAllEqual([], sess.run(node_ids_list)[0]) - self.assertAllEqual([1], sess.run(node_ids_list)[1]) + self.assertEqual(2, len(self.evaluate(node_ids_list))) + self.assertAllEqual([], self.evaluate(node_ids_list)[0]) + self.assertAllEqual([1], self.evaluate(node_ids_list)[1]) # Now check when we can't split on any feature (node_ids_list, _, _, _, @@ -325,7 +325,7 @@ class StatsOpsTest(test_util.TensorFlowTestCase): tree_complexity=0.0, min_node_weight=10, max_splits=max_splits) - self.assertAllEqual([[], []], sess.run(node_ids_list)) + self.assertAllEqual([[], []], self.evaluate(node_ids_list)) def testMakeStatsSummarySimple(self): """Simple test for MakeStatsSummary.""" diff --git a/tensorflow/python/kernel_tests/bucketize_op_test.py b/tensorflow/python/kernel_tests/bucketize_op_test.py index 57413e6af50..9575b28899f 100644 --- a/tensorflow/python/kernel_tests/bucketize_op_test.py +++ b/tensorflow/python/kernel_tests/bucketize_op_test.py @@ -32,7 +32,7 @@ class BucketizationOpTest(test.TestCase): boundaries=[0, 3, 8, 11]) expected_out = [0, 1, 1, 2, 2, 3, 3, 4, 4] with self.session(use_gpu=True) as sess: - self.assertAllEqual(expected_out, sess.run(op)) + self.assertAllEqual(expected_out, self.evaluate(op)) def testFloat(self): op = math_ops._bucketize( @@ -40,7 +40,7 @@ class BucketizationOpTest(test.TestCase): boundaries=[0., 3., 8., 11.]) expected_out = [0, 1, 1, 2, 2, 3, 3, 4, 4] with self.session(use_gpu=True) as sess: - self.assertAllEqual(expected_out, sess.run(op)) + self.assertAllEqual(expected_out, self.evaluate(op)) def test2DInput(self): op = math_ops._bucketize( @@ -48,7 +48,7 @@ class BucketizationOpTest(test.TestCase): boundaries=[0, 3, 8, 11]) expected_out = [[0, 1, 1, 2, 2], [3, 3, 4, 4, 1]] with self.session(use_gpu=True) as sess: - self.assertAllEqual(expected_out, sess.run(op)) + self.assertAllEqual(expected_out, self.evaluate(op)) def testInvalidBoundariesOrder(self): op = math_ops._bucketize( diff --git a/tensorflow/python/kernel_tests/candidate_sampler_ops_test.py b/tensorflow/python/kernel_tests/candidate_sampler_ops_test.py index 46ab71537f5..031accee553 100644 --- a/tensorflow/python/kernel_tests/candidate_sampler_ops_test.py +++ b/tensorflow/python/kernel_tests/candidate_sampler_ops_test.py @@ -97,7 +97,7 @@ class RangeSamplerOpsTest(test.TestCase): true_classes, self.NUM_TRUE, self.NUM_SAMPLED, True) accidental_hits = candidate_sampling_ops.compute_accidental_hits( true_classes, sampled_candidates, self.NUM_TRUE) - indices, ids, weights = sess.run(accidental_hits) + indices, ids, weights = self.evaluate(accidental_hits) self.assertEqual(1, accidental_hits[0].get_shape().ndims) self.assertEqual(1, accidental_hits[1].get_shape().ndims) diff --git a/tensorflow/python/kernel_tests/cast_op_test.py b/tensorflow/python/kernel_tests/cast_op_test.py index bc49cd5a048..cdeaf7b6967 100644 --- a/tensorflow/python/kernel_tests/cast_op_test.py +++ b/tensorflow/python/kernel_tests/cast_op_test.py @@ -187,7 +187,7 @@ class CastOpTest(test.TestCase): y = variables.Variable(True, dtype=dtypes.bool) cast = math_ops.cast(y, x.dtype) variables.global_variables_initializer().run() - self.assertEqual(1.0, sess.run(cast)) + self.assertEqual(1.0, self.evaluate(cast)) def testGradients(self): t = [dtypes.float32, dtypes.float64, dtypes.complex64, dtypes.complex128] diff --git a/tensorflow/python/kernel_tests/concat_op_test.py b/tensorflow/python/kernel_tests/concat_op_test.py index 149302831b1..6944d73c5fe 100644 --- a/tensorflow/python/kernel_tests/concat_op_test.py +++ b/tensorflow/python/kernel_tests/concat_op_test.py @@ -627,7 +627,7 @@ class ConcatOffsetTest(test.TestCase): s1 = constant_op.constant([2, 7, 5], dtypes.int32) s2 = constant_op.constant([2, 20, 5], dtypes.int32) off = gen_array_ops.concat_offset(cdim, [s0, s1, s2]) - ans = sess.run(off) + ans = self.evaluate(off) self.assertAllEqual(ans, [[0, 0, 0], [0, 3, 0], [0, 10, 0]]) def testNotVector(self): @@ -679,7 +679,7 @@ class ConcatOffsetTest(test.TestCase): s1 = constant_op.constant([2, 7, 5], dtypes.int32) s2 = constant_op.constant([2, 20, 5], dtypes.int32) off = gen_array_ops.concat_offset(cdim, [s0, s1, s2]) - ans = sess.run(off) + ans = self.evaluate(off) self.assertAllEqual(ans, [[0, 0, 0], [0, 3, 0], [0, 10, 0]]) cdim = constant_op.constant(-3, dtypes.int32) @@ -687,7 +687,7 @@ class ConcatOffsetTest(test.TestCase): s1 = constant_op.constant([1, 3, 5], dtypes.int32) s2 = constant_op.constant([3, 3, 5], dtypes.int32) off = gen_array_ops.concat_offset(cdim, [s0, s1, s2]) - ans = sess.run(off) + ans = self.evaluate(off) self.assertAllEqual(ans, [[0, 0, 0], [2, 0, 0], [3, 0, 0]]) diff --git a/tensorflow/python/kernel_tests/conditional_accumulator_test.py b/tensorflow/python/kernel_tests/conditional_accumulator_test.py index 893cb7cce33..8388070c63a 100644 --- a/tensorflow/python/kernel_tests/conditional_accumulator_test.py +++ b/tensorflow/python/kernel_tests/conditional_accumulator_test.py @@ -424,7 +424,7 @@ class ConditionalAccumulatorTest(test.TestCase): takeg_t = q.take_grad(1) def apply_grad(accum_op): - sess.run(accum_op) + self.evaluate(accum_op) threads = [ self.checkedThread( @@ -451,7 +451,7 @@ class ConditionalAccumulatorTest(test.TestCase): def apply_grad(): for accum_op in accum_ops: time.sleep(1.0) - sess.run(accum_op) + self.evaluate(accum_op) apply_grad_thread = self.checkedThread(target=apply_grad) @@ -485,7 +485,7 @@ class ConditionalAccumulatorTest(test.TestCase): def apply_grad(): time.sleep(1.0) for accum_op in accum_ops: - sess.run(accum_op) + self.evaluate(accum_op) return_array = [] @@ -503,7 +503,7 @@ class ConditionalAccumulatorTest(test.TestCase): def _blocking_takeg(self, sess, takeg_op): with self.assertRaisesOpError("was cancelled"): - sess.run(takeg_op) + self.evaluate(takeg_op) def testAccumulatorCancel(self): with self.cached_session() as sess: 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 55654174d32..0d6d2cc6daf 100644 --- a/tensorflow/python/kernel_tests/control_flow_ops_py_test.py +++ b/tensorflow/python/kernel_tests/control_flow_ops_py_test.py @@ -579,7 +579,7 @@ class ControlFlowTest(test.TestCase): fn1 = lambda: [math_ops.add(x, 1), math_ops.add(x, 2)] fn2 = lambda: [y, y] r = control_flow_ops.cond(pred, fn1, fn2) - self.assertAllEqual([11, 12], sess.run(r)) + self.assertAllEqual([11, 12], self.evaluate(r)) def testCondListOutput(self): with self.cached_session() as sess: @@ -589,7 +589,7 @@ class ControlFlowTest(test.TestCase): fn1 = lambda: [math_ops.add(x, y), math_ops.add(x, y)] fn2 = lambda: [y, y] r = control_flow_ops.cond(pred, fn1, fn2) - test_result = sess.run(r) + test_result = self.evaluate(r) self.assertListEqual([210, 210], test_result) def testTupleOutput(self): @@ -600,7 +600,7 @@ class ControlFlowTest(test.TestCase): fn1 = lambda: (math_ops.add(x, y), math_ops.add(x, y)) fn2 = lambda: (y, y) r = control_flow_ops.cond(pred, fn1, fn2) - test_result = sess.run(r) + test_result = self.evaluate(r) self.assertTupleEqual((210, 210), test_result) def testDictOutput(self): @@ -611,7 +611,7 @@ class ControlFlowTest(test.TestCase): fn1 = lambda: {"a": math_ops.add(x, y), "b": math_ops.add(x, y)} fn2 = lambda: {"a": y, "b": y} r = control_flow_ops.cond(pred, fn1, fn2) - test_result = sess.run(r) + test_result = self.evaluate(r) self.assertDictEqual({"a": 210, "b": 210}, test_result) def testEmbeddedListOutput(self): @@ -624,7 +624,7 @@ class ControlFlowTest(test.TestCase): # Pass strict=True flag as cond_v2 allows for tensors to be # in nested output structures as singletons r = control_flow_ops.cond(pred, fn1, fn2, strict=True) - test_result = sess.run(r) + test_result = self.evaluate(r) self.assertListEqual([[210, 210]], test_result) def testEmbeddedTupleOutput(self): @@ -635,7 +635,7 @@ class ControlFlowTest(test.TestCase): fn1 = lambda: ((math_ops.add(x, y), math_ops.add(x, y))) fn2 = lambda: ((y, y)) r = control_flow_ops.cond(pred, fn1, fn2) - test_result = sess.run(r) + test_result = self.evaluate(r) self.assertTupleEqual(((210, 210)), test_result) def testEmbeddedDictOutput(self): @@ -648,7 +648,7 @@ class ControlFlowTest(test.TestCase): fn2 = lambda: {"a": {"c": y}, "b": {"d": y}} r = control_flow_ops.cond(pred, fn1, fn2) - test_result = sess.run(r) + test_result = self.evaluate(r) self.assertDictEqual({"a": {"c": 210}, "b": {"d": 210}}, test_result) def testCheckNestedOutputStruct(self): @@ -663,7 +663,7 @@ class ControlFlowTest(test.TestCase): with self.assertRaisesRegexp( ValueError, v2_msg if control_flow_ops.ENABLE_COND_V2 else v1_msg): r = control_flow_ops.cond(pred, fn1, fn2) - test_result = sess.run(r) + self.evaluate(r) def testCondRef(self): @@ -1036,7 +1036,7 @@ class ControlFlowTest(test.TestCase): self.assertEqual(r[0].dtype, dtypes.int32) self.assertEqual(r[1].dtype, dtypes.int32_ref) - value_i, value_x = sess.run(r) + value_i, value_x = self.evaluate(r) self.assertEqual(100, value_i) self.assertEqual(0, value_x) @@ -1628,7 +1628,7 @@ class ControlFlowTest(test.TestCase): with ops.control_dependencies([control_flow_ops.no_op()]): loop = control_flow_ops.while_loop(cond, body, (constant_op.constant(5),)) - self.assertEqual(0, sess.run(loop)) + self.assertEqual(0, self.evaluate(loop)) @test_util.disable_control_flow_v2("b/113324949 (ref vars)") def testWhileCondWithControl_1(self): @@ -2041,7 +2041,7 @@ class ControlFlowTest(test.TestCase): self.assertFalse(gpu_dev_name in dev) with self.session(graph=graph) as sess: - self.assertAllClose(1024.0, sess.run(r)) + self.assertAllClose(1024.0, self.evaluate(r)) @test_util.disable_control_flow_v2("b/116351701 (colocation)") def testWhileGrad_ColocateGradients(self): @@ -2533,8 +2533,8 @@ class ControlFlowTest(test.TestCase): res = outer_loop(inp) optimizer = adam.AdamOptimizer(learning_rate=0.001) train_op = optimizer.minimize(math_ops.reduce_mean(math_ops.square(res))) - sess.run(variables.global_variables_initializer()) - sess.run(train_op) + self.evaluate(variables.global_variables_initializer()) + self.evaluate(train_op) self.assertAllClose(2.999, self.evaluate(var)) def _testWhileCondGrad_Simple(self, use_gpu): @@ -2593,11 +2593,11 @@ class ControlFlowTest(test.TestCase): [i0.get_shape(), tensor_shape.TensorShape([None, 2])]) s = math_ops.reduce_sum(h) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) optimizer = gradient_descent.GradientDescentOptimizer(0.01) op = optimizer.minimize(s) sess.run(op) - self.assertAllClose([[0.98000002, 1.98000002]], sess.run(x)) + self.assertAllClose([[0.98000002, 1.98000002]], self.evaluate(x)) @test_util.disable_control_flow_v2("b/113324949 (RefVariable)") def testWhileWithRefsWithGradients_1(self): @@ -2691,7 +2691,7 @@ class ControlFlowTest(test.TestCase): output_grad = control_flow_ops.while_loop( c, b, [i0, constant_op.constant(0.0)]) - self.assertAllClose(600.0, sess.run(output_grad)[1]) + self.assertAllClose(600.0, self.evaluate(output_grad)[1]) def testWhileAndTensorArray(self): with self.cached_session() as sess: @@ -2710,7 +2710,7 @@ class ControlFlowTest(test.TestCase): r = control_flow_ops.while_loop(c, b, [n0, y0], parallel_iterations=1) r = gradients_impl.gradients(r, param)[0] - self.assertAllClose(107520.0, sess.run(r)) + self.assertAllClose(107520.0, self.evaluate(r)) def testWhileGrad_StopGrad(self): with self.cached_session(): @@ -2843,8 +2843,8 @@ class ControlFlowTest(test.TestCase): dy_dq, = gradients_impl.gradients(y, q) self.assertIsNotNone(dy_dq) with self.cached_session() as sess: - sess.run(q.initializer) - self.assertAllClose([0., 0.], sess.run(dy_dq)) + self.evaluate(q.initializer) + self.assertAllClose([0., 0.], self.evaluate(dy_dq)) @test_util.disable_control_flow_v2("b/113324949 (RefVariable)") def testWhileGradientWithNontrainablePath2(self): @@ -2861,8 +2861,8 @@ class ControlFlowTest(test.TestCase): dy_dq, = gradients_impl.gradients(y, q) self.assertIsNotNone(dy_dq) with self.cached_session() as sess: - sess.run(q.initializer) - self.assertAllClose([1., 1.], sess.run(dy_dq)) + self.evaluate(q.initializer) + self.assertAllClose([1., 1.], self.evaluate(dy_dq)) @test_util.disable_control_flow_v2("b/115920078 (gradients)") def testIssue16504(self): @@ -3281,7 +3281,7 @@ class ControlFlowTest(test.TestCase): result = control_flow_ops.while_loop(condition, body, [constant_op.constant(4)]) - self.assertEqual(10, sess.run(result)) + self.assertEqual(10, self.evaluate(result)) # Ensure that we cannot run a tensor that escapes the loop body # accidentally. @@ -3339,7 +3339,7 @@ class ControlFlowTest(test.TestCase): shape=[1], dtype=dtypes.qint8, name="v", container="", shared_name="") assign_op = state_ops.assign( var_qint, constant_op.constant(np.array([42]), dtypes.qint8)) - sess.run(assign_op) + self.evaluate(assign_op) cond = constant_op.constant(True, dtypes.bool) v_f, v_t = control_flow_ops.ref_switch(var_qint, cond) @@ -3660,7 +3660,7 @@ class WhileOpBenchmark(test.Benchmark): with session.Session() as sess, ops.device(default_device): # Get the initial id i, input x, and kernel. i, x, kernel = self._getInitVariables() - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) if static_unroll: for _ in xrange(steps): diff --git a/tensorflow/python/kernel_tests/conv_ops_3d_test.py b/tensorflow/python/kernel_tests/conv_ops_3d_test.py index 3924e135752..3ec5c29df7d 100644 --- a/tensorflow/python/kernel_tests/conv_ops_3d_test.py +++ b/tensorflow/python/kernel_tests/conv_ops_3d_test.py @@ -109,7 +109,7 @@ class Conv3DTest(test.TestCase): results.append(result) with self.cached_session() as sess: - values = sess.run(results) + values = self.evaluate(results) for value in values: print("expected = ", expected) print("actual = ", value) @@ -184,8 +184,8 @@ class Conv3DTest(test.TestCase): computed_results.append(computed) tolerance = 1e-2 if use_gpu else 1e-5 with self.cached_session() as sess: - expected_values = sess.run(expected_results) - computed_values = sess.run(computed_results) + expected_values = self.evaluate(expected_results) + computed_values = self.evaluate(computed_results) for e_value, c_value in zip(expected_values, computed_values): print("expected = ", e_value) print("actual = ", c_value) @@ -715,8 +715,8 @@ class Conv3DTest(test.TestCase): expected_grad = gradients_impl.gradients(expected, t1 if mode == "input" else t2)[0] # "values" consists of two tensors for two backprops - actual_value = sess.run(actual_grad) - expected_value = sess.run(expected_grad) + actual_value = self.evaluate(actual_grad) + expected_value = self.evaluate(expected_grad) self.assertShapeEqual(actual_value, actual_grad) self.assertShapeEqual(expected_value, expected_grad) print("expected = ", expected_value) diff --git a/tensorflow/python/kernel_tests/conv_ops_test.py b/tensorflow/python/kernel_tests/conv_ops_test.py index 835cc1504d1..2d21f6f4ae5 100644 --- a/tensorflow/python/kernel_tests/conv_ops_test.py +++ b/tensorflow/python/kernel_tests/conv_ops_test.py @@ -908,8 +908,8 @@ class Conv2DTest(test.TestCase): conv = gradients_impl.gradients(conv_forward, t1)[0] conv_2 = gradients_impl.gradients(conv_forward_2, t1)[0] # "values" consists of two tensors for two backprops - value = sess.run(conv) - value_2 = sess.run(conv_2) + value = self.evaluate(conv) + value_2 = self.evaluate(conv_2) self.assertShapeEqual(value, conv) self.assertShapeEqual(value_2, conv_2) tf_logging.info("expected = ", value_2) @@ -961,8 +961,8 @@ class Conv2DTest(test.TestCase): conv_forward_2 = test_util.NCHWToNHWC(conv_forward_2) conv = gradients_impl.gradients(conv_forward, t2)[0] conv_2 = gradients_impl.gradients(conv_forward, t2)[0] - value = sess.run(conv) - value_2 = sess.run(conv_2) + value = self.evaluate(conv) + value_2 = self.evaluate(conv_2) self.assertShapeEqual(value, conv) self.assertShapeEqual(value_2, conv_2) tf_logging.info("expected = ", value_2) @@ -1545,7 +1545,7 @@ class DepthwiseConv2DTest(test.TestCase): t2 = constant_op.constant(x2, shape=filter_in_sizes) conv = nn_impl.depthwise_conv2d( t1, t2, strides=[1, stride, stride, 1], padding=padding) - value = sess.run(conv) + value = self.evaluate(conv) tf_logging.info("value = ", value) self.assertArrayNear(expected, np.ravel(value), 1e-5) self.assertShapeEqual(value, conv) @@ -1667,7 +1667,7 @@ class SeparableConv2DTest(test.TestCase): if data_format == "NCHW": conv = array_ops.transpose(conv, [0, 2, 3, 1]) - value = sess.run(conv) + value = self.evaluate(conv) tf_logging.info("value = ", value) self.assertArrayNear(expected, np.ravel(value), 1e-3) self.assertShapeEqual(value, conv) diff --git a/tensorflow/python/kernel_tests/cwise_ops_test.py b/tensorflow/python/kernel_tests/cwise_ops_test.py index d7dbf5ab9ac..87248bf9c89 100644 --- a/tensorflow/python/kernel_tests/cwise_ops_test.py +++ b/tensorflow/python/kernel_tests/cwise_ops_test.py @@ -788,7 +788,7 @@ class RoundingTest(test.TestCase): y = np.rint(x) if y is None else np.asarray(y) with self.cached_session() as sess: tf_rint = math_ops.rint(x) - np_rint = sess.run(tf_rint) + np_rint = self.evaluate(tf_rint) self.assertAllEqual(y, np_rint) self.assertShapeEqual(y, tf_rint) @@ -881,7 +881,7 @@ class ComplexMakeRealImagTest(test.TestCase): force_gpu=use_gpu and test_util.is_gpu_available()) as sess: inx = ops.convert_to_tensor(cplx) tf_angle = math_ops.angle(inx) - tf_angle_val = sess.run(tf_angle) + tf_angle_val = self.evaluate(tf_angle) self.assertAllEqual(np_angle, tf_angle_val) self.assertShapeEqual(np_angle, tf_angle) diff --git a/tensorflow/python/kernel_tests/decode_jpeg_op_test.py b/tensorflow/python/kernel_tests/decode_jpeg_op_test.py index 66b3e0f22fd..8c4ccbd88e2 100644 --- a/tensorflow/python/kernel_tests/decode_jpeg_op_test.py +++ b/tensorflow/python/kernel_tests/decode_jpeg_op_test.py @@ -80,7 +80,7 @@ class DecodeJpegBenchmark(test.Benchmark): initializer=image_ops.encode_jpeg(tiled_image)) with session.Session() as sess: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) images = [] for _ in xrange(parallelism): if crop_window is None: 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 3ed7dba966b..0676664685d 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 @@ -43,7 +43,7 @@ class AssignOpTest(test.TestCase): variables.global_variables_initializer().run() def run_add(add_op): - sess.run(add_op) + self.evaluate(add_op) threads = [ self.checkedThread( @@ -70,7 +70,7 @@ class AssignOpTest(test.TestCase): variables.global_variables_initializer().run() def run_assign(assign_op): - sess.run(assign_op) + self.evaluate(assign_op) threads = [ self.checkedThread( @@ -103,7 +103,7 @@ class AssignOpTest(test.TestCase): p.initializer.run() def run_add(add_op): - sess.run(add_op) + self.evaluate(add_op) threads = [ self.checkedThread( @@ -131,7 +131,7 @@ class AssignOpTest(test.TestCase): p.initializer.run() def run_assign(assign_op): - sess.run(assign_op) + self.evaluate(assign_op) threads = [ self.checkedThread( diff --git a/tensorflow/python/kernel_tests/depthwise_conv_op_test.py b/tensorflow/python/kernel_tests/depthwise_conv_op_test.py index f65d0be3675..f6d834c2f85 100644 --- a/tensorflow/python/kernel_tests/depthwise_conv_op_test.py +++ b/tensorflow/python/kernel_tests/depthwise_conv_op_test.py @@ -162,7 +162,7 @@ class DepthwiseConv2DTest(test.TestCase): conv_native = array_ops.transpose(conv_native, [0, 2, 3, 1]) try: - native_result = sess.run(conv_native) + native_result = self.evaluate(conv_native) except errors.InvalidArgumentError as e: # Grouped convolution kernel is only registered for cuDNN 7. Silently # return when we are running on an earlier version or without GPU. @@ -174,7 +174,7 @@ class DepthwiseConv2DTest(test.TestCase): conv_interface = nn_impl.depthwise_conv2d( t1, t2, strides=[1, stride, stride, 1], padding=padding) - interface_result = sess.run(conv_interface) + interface_result = self.evaluate(conv_interface) tf_logging.info( "data_type: %r, use_gpu: %r, grouped_conv: %r, max diff = %f", @@ -269,7 +269,7 @@ class DepthwiseConv2DTest(test.TestCase): t2 = constant_op.constant(x2, shape=filter_in_sizes) conv = nn_ops.depthwise_conv2d_native( t1, t2, strides=[1, stride, stride, 1], padding=padding) - value = sess.run(conv) + value = self.evaluate(conv) tf_logging.info("value = %r", value) self.assertArrayNear(expected, np.ravel(value), 1e-5) self.assertShapeEqual(value, conv) diff --git a/tensorflow/python/kernel_tests/distributions/categorical_test.py b/tensorflow/python/kernel_tests/distributions/categorical_test.py index f116c54bd16..9c593d2737a 100644 --- a/tensorflow/python/kernel_tests/distributions/categorical_test.py +++ b/tensorflow/python/kernel_tests/distributions/categorical_test.py @@ -287,7 +287,7 @@ class CategoricalTest(test.TestCase, parameterized.TestCase): } with self.cached_session() as sess: - run_result = sess.run(to_run) + run_result = self.evaluate(to_run) self.assertAllEqual(run_result["cat_prob"].shape, run_result["norm_prob"].shape) @@ -462,7 +462,7 @@ class CategoricalTest(test.TestCase, parameterized.TestCase): b = categorical.Categorical(logits=b_logits) kl = kullback_leibler.kl_divergence(a, b) - kl_val = sess.run(kl) + kl_val = self.evaluate(kl) # Make sure KL(a||a) is 0 kl_same = sess.run(kullback_leibler.kl_divergence(a, a)) diff --git a/tensorflow/python/kernel_tests/dynamic_partition_op_test.py b/tensorflow/python/kernel_tests/dynamic_partition_op_test.py index 07da855a017..80da39dfde1 100644 --- a/tensorflow/python/kernel_tests/dynamic_partition_op_test.py +++ b/tensorflow/python/kernel_tests/dynamic_partition_op_test.py @@ -40,7 +40,7 @@ class DynamicPartitionTest(test.TestCase): indices = constant_op.constant([0, 0, 2, 3, 2, 1]) partitions = data_flow_ops.dynamic_partition( data, indices, num_partitions=4) - partition_vals = sess.run(partitions) + partition_vals = self.evaluate(partitions) self.assertEqual(4, len(partition_vals)) self.assertAllEqual([0, 13], partition_vals[0]) @@ -62,7 +62,7 @@ class DynamicPartitionTest(test.TestCase): indices = constant_op.constant([0, 0, 2, 3, 2, 1]) partitions = data_flow_ops.dynamic_partition( data, indices, num_partitions=4) - partition_vals = sess.run(partitions) + partition_vals = self.evaluate(partitions) self.assertEqual(4, len(partition_vals)) self.assertAllEqual([[0, 1, 2], [3, 4, 5]], partition_vals[0]) @@ -87,7 +87,7 @@ class DynamicPartitionTest(test.TestCase): indices = constant_op.constant(indices_list, dtype=dtypes.int32) partitions = data_flow_ops.dynamic_partition( data, indices, num_partitions=2) - partition_vals = sess.run(partitions) + partition_vals = self.evaluate(partitions) self.assertEqual(2, len(partition_vals)) self.assertAllEqual(part1, partition_vals[0]) @@ -109,7 +109,7 @@ class DynamicPartitionTest(test.TestCase): indices = constant_op.constant(indices_list, dtype=dtypes.int32) partitions = data_flow_ops.dynamic_partition( data, indices, num_partitions=num_partitions) - partition_vals = sess.run(partitions) + partition_vals = self.evaluate(partitions) self.assertEqual(num_partitions, len(partition_vals)) for i in range(num_partitions): @@ -125,7 +125,7 @@ class DynamicPartitionTest(test.TestCase): indices = constant_op.constant(indices_list, dtype=dtypes.int32) partitions = data_flow_ops.dynamic_partition( data, indices, num_partitions=2) - partition_vals = sess.run(partitions) + partition_vals = self.evaluate(partitions) self.assertEqual(2, len(partition_vals)) self.assertAllEqual([3 + 4j, 7 + 8j], partition_vals[0]) @@ -138,7 +138,7 @@ class DynamicPartitionTest(test.TestCase): indices = 3 partitions = data_flow_ops.dynamic_partition( data, indices, num_partitions=4) - partition_vals = sess.run(partitions) + partition_vals = self.evaluate(partitions) self.assertEqual(4, len(partition_vals)) self.assertAllEqual(np.array([], dtype=np.float64).reshape(-1, 4), @@ -164,7 +164,7 @@ class DynamicPartitionTest(test.TestCase): outputs = data_flow_ops.dynamic_partition( data_t, partitions_t, num_partitions=n) self.assertEqual(n, len(outputs)) - outputs_val = sess.run(outputs) + outputs_val = self.evaluate(outputs) for i, output in enumerate(outputs_val): self.assertAllEqual(output, data[partitions == i]) @@ -183,7 +183,7 @@ class DynamicPartitionTest(test.TestCase): indices = constant_op.constant(indices_list, dtype=dtypes.int32) partitions = data_flow_ops.dynamic_partition( data, indices, num_partitions=4) - partition_vals = sess.run(partitions) + partition_vals = self.evaluate(partitions) self.assertEqual(4, len(partition_vals)) self.assertAllEqual([], partition_vals[0]) @@ -199,7 +199,7 @@ class DynamicPartitionTest(test.TestCase): indices = constant_op.constant(indices_list, dtype=dtypes.int32) partitions = data_flow_ops.dynamic_partition( data, indices, num_partitions=3) - partition_vals = sess.run(partitions) + partition_vals = self.evaluate(partitions) self.assertEqual(3, len(partition_vals)) self.assertAllEqual([[]], partition_vals[0]) @@ -215,7 +215,7 @@ class DynamicPartitionTest(test.TestCase): indices = constant_op.constant(indices_list, dtype=dtypes.int32) partitions = data_flow_ops.dynamic_partition( data, indices, num_partitions=2) - partition_vals = sess.run(partitions) + partition_vals = self.evaluate(partitions) self.assertEqual(2, len(partition_vals)) self.assertAllEqual([], partition_vals[0]) @@ -236,7 +236,7 @@ class DynamicPartitionTest(test.TestCase): indices = constant_op.constant(indices_list, dtype=dtypes.int32) partitions = data_flow_ops.dynamic_partition( data, indices, num_partitions=2) - partition_vals = sess.run(partitions) + partition_vals = self.evaluate(partitions) self.assertEqual(2, len(partition_vals)) self.assertAllEqual([6], partition_vals[0]) @@ -257,7 +257,7 @@ class DynamicPartitionTest(test.TestCase): indices = constant_op.constant(indices_list, dtype=dtypes.int32) partitions = data_flow_ops.dynamic_partition( data, indices, num_partitions=5) - partition_vals = sess.run(partitions) + partition_vals = self.evaluate(partitions) self.assertEqual(5, len(partition_vals)) self.assertAllEqual([5], partition_vals[0]) @@ -281,7 +281,7 @@ class DynamicPartitionTest(test.TestCase): indices = constant_op.constant(indices_list, dtype=dtypes.int32) partitions = data_flow_ops.dynamic_partition( data, indices, num_partitions=40) - partition_vals = sess.run(partitions) + partition_vals = self.evaluate(partitions) self.assertEqual(40, len(partition_vals)) for i in range(40): @@ -335,7 +335,7 @@ class DynamicPartitionTest(test.TestCase): self.assertEqual(len(inds), x.shape[0]) partitioned = data_flow_ops.dynamic_partition(x, inds, 16) with self.cached_session() as sess: - res = sess.run(partitioned) + res = self.evaluate(partitioned) self.assertEqual(res[-1].shape[0], 192) diff --git a/tensorflow/python/kernel_tests/fifo_queue_test.py b/tensorflow/python/kernel_tests/fifo_queue_test.py index e3742f2e724..c184b93c80e 100644 --- a/tensorflow/python/kernel_tests/fifo_queue_test.py +++ b/tensorflow/python/kernel_tests/fifo_queue_test.py @@ -159,7 +159,7 @@ class FIFOQueueTest(test.TestCase): # Run one producer thread for each element in elems. def enqueue(enqueue_op): - sess.run(enqueue_op) + self.evaluate(enqueue_op) threads = [ self.checkedThread( @@ -240,7 +240,7 @@ class FIFOQueueTest(test.TestCase): # TODO(mrry): Figure out how to do this without sleeping. time.sleep(0.1) for enqueue_op in enqueue_ops: - sess.run(enqueue_op) + self.evaluate(enqueue_op) results = [] @@ -269,7 +269,7 @@ class FIFOQueueTest(test.TestCase): enqueue_op.run() for i in xrange(len(elems)): - x_val, y_val = sess.run(dequeued_t) + x_val, y_val = self.evaluate(dequeued_t) x, y = elems[i] self.assertEqual([x], x_val) self.assertEqual([y], y_val) @@ -356,7 +356,7 @@ class FIFOQueueTest(test.TestCase): enqueue_op.run() for i in range(8): - float_val, int_val = sess.run(dequeued_t) + float_val, int_val = self.evaluate(dequeued_t) self.assertEqual(float_elems[i % 4], float_val) self.assertAllEqual(int_elems[i % 4], int_val) @@ -399,17 +399,17 @@ class FIFOQueueTest(test.TestCase): enqueue_op.run() - float_val, int_val = sess.run(dequeued_t) + float_val, int_val = self.evaluate(dequeued_t) self.assertAllEqual(float_elems[0:4], float_val) self.assertAllEqual(int_elems[0:4], int_val) self.assertEqual(float_val.shape, dequeued_t[0].get_shape()) self.assertEqual(int_val.shape, dequeued_t[1].get_shape()) - float_val, int_val = sess.run(dequeued_t) + float_val, int_val = self.evaluate(dequeued_t) self.assertAllEqual(float_elems[4:8], float_val) self.assertAllEqual(int_elems[4:8], int_val) - float_val, int_val = sess.run(dequeued_single_t) + float_val, int_val = self.evaluate(dequeued_single_t) self.assertAllEqual(float_elems[8], float_val) self.assertAllEqual(int_elems[8], int_val) self.assertEqual(float_val.shape, dequeued_single_t[0].get_shape()) @@ -429,13 +429,13 @@ class FIFOQueueTest(test.TestCase): enqueue_op.run() - float_val, int_val = sess.run(dequeued_t) + float_val, int_val = self.evaluate(dequeued_t) self.assertAllEqual(float_elems[0:4], float_val) self.assertAllEqual(int_elems[0:4], int_val) self.assertEqual([None], dequeued_t[0].get_shape().as_list()) self.assertEqual([None, 2], dequeued_t[1].get_shape().as_list()) - float_val, int_val = sess.run(dequeued_t) + float_val, int_val = self.evaluate(dequeued_t) self.assertAllEqual(float_elems[4:8], float_val) self.assertAllEqual(int_elems[4:8], int_val) @@ -529,7 +529,7 @@ class FIFOQueueTest(test.TestCase): # Enqueue 100 items in parallel on 10 threads. def enqueue(): - sess.run(enqueue_op) + self.evaluate(enqueue_op) threads = [self.checkedThread(target=enqueue) for _ in range(10)] for thread in threads: @@ -596,11 +596,11 @@ class FIFOQueueTest(test.TestCase): def enqueue(): for _ in xrange(100): - sess.run(enqueue_op) + self.evaluate(enqueue_op) def dequeue(): for _ in xrange(100): - self.assertTrue(sess.run(dequeued_t) in (10.0, 20.0)) + self.assertTrue(self.evaluate(dequeued_t) in (10.0, 20.0)) enqueue_threads = [self.checkedThread(target=enqueue) for _ in range(10)] dequeue_threads = [self.checkedThread(target=dequeue) for _ in range(10)] @@ -632,7 +632,7 @@ class FIFOQueueTest(test.TestCase): def dequeue(): for i in xrange(250): - self.assertEqual(i, sess.run(dequeued_t)) + self.assertEqual(i, self.evaluate(dequeued_t)) dequeue_thread = self.checkedThread(target=dequeue) dequeue_thread.start() @@ -663,7 +663,7 @@ class FIFOQueueTest(test.TestCase): dequeuemany_t = q.dequeue_many(count_placeholder) def enqueue(): - sess.run(enqueue_op) + self.evaluate(enqueue_op) enqueue_thread = self.checkedThread(target=enqueue) enqueue_thread.start() @@ -701,7 +701,7 @@ class FIFOQueueTest(test.TestCase): # The enqueue_op should run after the dequeue op has blocked. # TODO(mrry): Figure out how to do this without sleeping. time.sleep(0.1) - sess.run(enqueue_op) + self.evaluate(enqueue_op) def dequeue(): dequeued_elems.extend(sess.run(dequeued_t).tolist()) @@ -728,7 +728,7 @@ class FIFOQueueTest(test.TestCase): # The enqueue_op should run after the dequeue op has blocked. # TODO(mrry): Figure out how to do this without sleeping. time.sleep(0.1) - sess.run(enqueue_op) + self.evaluate(enqueue_op) def dequeue(): dequeued_elems.extend(sess.run(dequeued_t).tolist()) @@ -797,7 +797,7 @@ class FIFOQueueTest(test.TestCase): def dequeue(): for elem in elems: - self.assertEqual([elem], sess.run(dequeued_t)) + self.assertEqual([elem], self.evaluate(dequeued_t)) # Expect the operation to fail due to the queue being closed. with self.assertRaisesRegexp(errors_impl.OutOfRangeError, "is closed and has insufficient"): @@ -842,7 +842,7 @@ class FIFOQueueTest(test.TestCase): enqueue_op.run() def dequeue(): - self.assertAllEqual(elems, sess.run(dequeued_t)) + self.assertAllEqual(elems, self.evaluate(dequeued_t)) # Expect the operation to fail due to the queue being closed. with self.assertRaisesRegexp(errors_impl.OutOfRangeError, "is closed and has insufficient"): @@ -867,7 +867,7 @@ class FIFOQueueTest(test.TestCase): enqueue_op.run() def dequeue(): - self.assertAllEqual(elems[:3], sess.run(dequeued_t)) + self.assertAllEqual(elems[:3], self.evaluate(dequeued_t)) # Expect the operation to fail due to the queue being closed. with self.assertRaisesRegexp(errors_impl.OutOfRangeError, "is closed and has insufficient"): @@ -892,8 +892,8 @@ class FIFOQueueTest(test.TestCase): enqueue_op.run() def dequeue(): - self.assertAllEqual(elems[:3], sess.run(dequeued_t)) - self.assertAllEqual(elems[3:], sess.run(dequeued_t)) + self.assertAllEqual(elems[:3], self.evaluate(dequeued_t)) + self.assertAllEqual(elems[3:], self.evaluate(dequeued_t)) dequeue_thread = self.checkedThread(target=dequeue) dequeue_thread.start() @@ -913,16 +913,16 @@ class FIFOQueueTest(test.TestCase): cleanup_dequeue_t = q.dequeue() def enqueue(): - sess.run(enqueue_op) + self.evaluate(enqueue_op) def dequeue(): - self.assertAllEqual(elems[0:3], sess.run(dequeued_t)) + self.assertAllEqual(elems[0:3], self.evaluate(dequeued_t)) with self.assertRaises(errors_impl.OutOfRangeError): sess.run(dequeued_t) - self.assertEqual(elems[3], sess.run(cleanup_dequeue_t)) + self.assertEqual(elems[3], self.evaluate(cleanup_dequeue_t)) def close(): - sess.run(close_op) + self.evaluate(close_op) enqueue_thread = self.checkedThread(target=enqueue) enqueue_thread.start() @@ -1051,7 +1051,7 @@ class FIFOQueueTest(test.TestCase): enqueue_op.run() def blocking_enqueue(): - sess.run(blocking_enqueue_op) + self.evaluate(blocking_enqueue_op) thread = self.checkedThread(target=blocking_enqueue) thread.start() @@ -1074,7 +1074,7 @@ class FIFOQueueTest(test.TestCase): enqueue_op.run() def blocking_enqueue(): - sess.run(blocking_enqueue_op) + self.evaluate(blocking_enqueue_op) thread = self.checkedThread(target=blocking_enqueue) thread.start() @@ -1103,7 +1103,7 @@ class FIFOQueueTest(test.TestCase): def blocking_enqueue(): # Expect the operation to succeed once the dequeue op runs. - sess.run(blocking_enqueue_op) + self.evaluate(blocking_enqueue_op) enqueue_thread = self.checkedThread(target=blocking_enqueue) enqueue_thread.start() @@ -1113,7 +1113,7 @@ class FIFOQueueTest(test.TestCase): time.sleep(0.1) def close(): - sess.run(close_op) + self.evaluate(close_op) close_thread = self.checkedThread(target=close) close_thread.start() @@ -1138,7 +1138,7 @@ class FIFOQueueTest(test.TestCase): enqueue_op.run() def blocking_enqueue(): - sess.run(blocking_enqueue_op) + self.evaluate(blocking_enqueue_op) enqueue_thread = self.checkedThread(target=blocking_enqueue) enqueue_thread.start() @@ -1148,7 +1148,7 @@ class FIFOQueueTest(test.TestCase): time.sleep(0.1) def close(): - sess.run(close_op) + self.evaluate(close_op) close_thread = self.checkedThread(target=close) close_thread.start() @@ -1266,19 +1266,19 @@ class FIFOQueueTest(test.TestCase): def _blockingDequeue(self, sess, dequeue_op): with self.assertRaisesOpError("was cancelled"): - sess.run(dequeue_op) + self.evaluate(dequeue_op) def _blockingDequeueMany(self, sess, dequeue_many_op): with self.assertRaisesOpError("was cancelled"): - sess.run(dequeue_many_op) + self.evaluate(dequeue_many_op) def _blockingEnqueue(self, sess, enqueue_op): with self.assertRaisesOpError("was cancelled"): - sess.run(enqueue_op) + self.evaluate(enqueue_op) def _blockingEnqueueMany(self, sess, enqueue_many_op): with self.assertRaisesOpError("was cancelled"): - sess.run(enqueue_many_op) + self.evaluate(enqueue_many_op) def testResetOfBlockingOperation(self): with self.cached_session() as sess: @@ -1331,14 +1331,14 @@ class FIFOQueueTest(test.TestCase): results = [] results.append(deq.eval()) # Will only complete after the enqueue starts. self.assertEqual(len(enq_done), 1) - self.assertEqual(sess.run(size_op), 5) + self.assertEqual(self.evaluate(size_op), 5) for _ in range(3): results.append(deq.eval()) time.sleep(0.1) self.assertEqual(len(enq_done), 1) - self.assertEqual(sess.run(size_op), 5) + self.assertEqual(self.evaluate(size_op), 5) # This dequeue will unblock the thread. results.append(deq.eval()) @@ -1405,7 +1405,7 @@ class FIFOQueueTest(test.TestCase): q.enqueue_many(input_tuple).run() output_tuple_t = q.dequeue_many(32) - output_tuple = sess.run(output_tuple_t) + output_tuple = self.evaluate(output_tuple_t) for (input_elem, output_elem) in zip(input_tuple, output_tuple): self.assertAllEqual(input_elem, output_elem) @@ -1507,7 +1507,7 @@ class FIFOQueueDictTest(test.TestCase): enqueue_op4 = q.enqueue_many({"f": [40.0, 50.0]}) dequeue = q.dequeue() dequeue_2 = q.dequeue_many(2) - sess.run(enqueue_op) + self.evaluate(enqueue_op) sess.run(enqueue_op2) sess.run(enqueue_op3) sess.run(enqueue_op4) @@ -1565,7 +1565,7 @@ class FIFOQueueDictTest(test.TestCase): }) dequeue = q.dequeue() dequeue_2 = q.dequeue_many(2) - sess.run(enqueue_op) + self.evaluate(enqueue_op) sess.run(enqueue_op2) sess.run(enqueue_op3) sess.run(enqueue_op4) @@ -1613,8 +1613,8 @@ class FIFOQueueWithTimeoutTest(test.TestCase): "Timed out waiting for notification"): sess.run(dequeued_t, options=config_pb2.RunOptions(timeout_in_ms=10)) - sess.run(enqueue_op) - self.assertEqual(37, sess.run(dequeued_t)) + self.evaluate(enqueue_op) + self.assertEqual(37, self.evaluate(dequeued_t)) class QueueContainerTest(test.TestCase): diff --git a/tensorflow/python/kernel_tests/functional_ops_test.py b/tensorflow/python/kernel_tests/functional_ops_test.py index 503569f3b18..0af32b048e3 100644 --- a/tensorflow/python/kernel_tests/functional_ops_test.py +++ b/tensorflow/python/kernel_tests/functional_ops_test.py @@ -567,8 +567,8 @@ class FunctionalOpsTest(test.TestCase): target="/job:worker/replica:0/task:0/cpu:1") with session.Session(worker[0].target) as sess: - sess.run(variables.global_variables_initializer()) - mul = sess.run(remote_op) + self.evaluate(variables.global_variables_initializer()) + mul = self.evaluate(remote_op) self.assertEqual(mul, [6]) def testRemoteFunctionDirectSession(self): @@ -591,8 +591,8 @@ class FunctionalOpsTest(test.TestCase): target="/job:localhost/replica:0/task:0/cpu:1") with self.test_session(config=worker_config) as sess: - sess.run(variables.global_variables_initializer()) - mul = sess.run(remote_op) + self.evaluate(variables.global_variables_initializer()) + mul = self.evaluate(remote_op) self.assertEqual(mul, [6]) def testRemoteFunctionSameDeviceDirectSession(self): @@ -610,8 +610,8 @@ class FunctionalOpsTest(test.TestCase): args=[a, b], Tout=[dtypes.int32], f=_remote_fn, target="/cpu:0") with self.cached_session() as sess: - sess.run(variables.global_variables_initializer()) - mul = sess.run(remote_op) + self.evaluate(variables.global_variables_initializer()) + mul = self.evaluate(remote_op) self.assertEqual(mul, [6]) def testRemoteFunctionCPUGPU(self): @@ -634,8 +634,8 @@ class FunctionalOpsTest(test.TestCase): target="/job:localhost/replica:0/task:0/device:GPU:0")[0] + 3.0 with self.cached_session() as sess: - sess.run(variables.global_variables_initializer()) - mul = sess.run(remote_op) + self.evaluate(variables.global_variables_initializer()) + mul = self.evaluate(remote_op) self.assertEqual(mul, 9.0) def testRemoteFunctionGPUCPU(self): @@ -658,8 +658,8 @@ class FunctionalOpsTest(test.TestCase): target="/job:localhost/replica:0/task:0/cpu:0")[0] + 3.0 with self.cached_session() as sess: - sess.run(variables.global_variables_initializer()) - mul = sess.run(remote_op) + self.evaluate(variables.global_variables_initializer()) + mul = self.evaluate(remote_op) self.assertEqual(mul, 9.0) def testRemoteFunctionGPUCPUStrings(self): @@ -677,7 +677,7 @@ class FunctionalOpsTest(test.TestCase): args=[a], Tout=[dtypes.string], f=_remote_fn, target="/cpu:0") with self.cached_session() as sess: - ret = sess.run(remote_op) + ret = self.evaluate(remote_op) self.assertAllEqual(ret, [b"a"]) def testRemoteFunctionCrossProcess(self): @@ -699,8 +699,8 @@ class FunctionalOpsTest(test.TestCase): target="/job:worker/replica:0/task:1/cpu:0")[0] + 3.0 with session.Session(workers[0].target) as sess: - sess.run(variables.global_variables_initializer()) - mul = sess.run(remote_op) + self.evaluate(variables.global_variables_initializer()) + mul = self.evaluate(remote_op) self.assertEqual(mul, 9) def testIf(self): @@ -857,11 +857,11 @@ class FunctionalOpsTest(test.TestCase): result_binary = functional_ops.While( [1.0, 0., 0.], function.Defun(*[dtypes.float32] * 3)(TestCond), TestBinary) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) assert len(result_unary) == 2 - self.assertEqual([10.0, 54.0], sess.run(result_unary)) + self.assertEqual([10.0, 54.0], self.evaluate(result_unary)) assert len(result_binary) == 3 - self.assertEqual([10.0, 54.0, 9.0], sess.run(result_binary)) + self.assertEqual([10.0, 54.0, 9.0], self.evaluate(result_binary)) def TestCondCapture(n, *args): del args @@ -892,7 +892,7 @@ class FunctionalOpsTest(test.TestCase): 100, 0, -1, [0.], Body, rewrite_with_while=rewrite_with_while) [0], ] - xvals = sess.run(xs) + xvals = self.evaluate(xs) self.assertAllEqual(210, xvals[0]) self.assertAllEqual(5050, xvals[1]) @@ -949,16 +949,16 @@ class FunctionalOpsTest(test.TestCase): result_binary = functional_ops.For( 1, 10, 1, [0., 0.], TestBinary, rewrite_with_while=rewrite_with_while) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) assert not result_nullary # The nullary variant doesn't return anything so we can't easily run it. # As a total hack, fetch the operation by name and run it. sess.run(ops.get_default_graph().get_operation_by_name( "While" if rewrite_with_while else "For")) assert len(result_unary) == 1 - self.assertEqual([54.0], sess.run(result_unary)) + self.assertEqual([54.0], self.evaluate(result_unary)) assert len(result_binary) == 2 - self.assertEqual([54.0, 9.0], sess.run(result_binary)) + self.assertEqual([54.0, 9.0], self.evaluate(result_binary)) def _tfMLP(self, xval, wsval, bsval, rewrite_with_while): # On GPU, don't rewrite using a while loop. @@ -1041,8 +1041,8 @@ class FunctionalOpsTest(test.TestCase): avals = [Poly(a), Grad(a)] b = constant_op.constant(1.) bvals = [Poly(b), Grad(b)] - self.assertAllEqual(sess.run(avals), [8., 4.]) - self.assertAllEqual(sess.run(bvals), [17., 16.]) + self.assertAllEqual(self.evaluate(avals), [8., 4.]) + self.assertAllEqual(self.evaluate(bvals), [17., 16.]) # TODO(akshayka): Replace `function.Defun` with tf.contrib.eager.defun` in the @@ -1193,7 +1193,7 @@ class PartitionedCallTest(test.TestCase): allow_soft_placement=False, log_device_placement=True, device_count={"CPU": 2})) as sess: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) expected = sess.run(sum_gather()) result = sess.run( functional_ops.partitioned_call( diff --git a/tensorflow/python/kernel_tests/gradient_correctness_test.py b/tensorflow/python/kernel_tests/gradient_correctness_test.py index 291a69ebac6..12b8a4c8e3b 100644 --- a/tensorflow/python/kernel_tests/gradient_correctness_test.py +++ b/tensorflow/python/kernel_tests/gradient_correctness_test.py @@ -35,7 +35,7 @@ class GradientCorrectnessTest(test.TestCase): yexp = math_ops.exp(x) yexplog = math_ops.log(yexp) grads = gradients_impl.gradients([yexp, yexplog], [x]) - grad_vals = sess.run(grads) + grad_vals = self.evaluate(grads) exp1_plus_one = (1.0 + np.exp(1.0)).astype(np.float32) # [dexp(x)/dx + d(log(exp(x)))/dx] @ x=1 == exp(1) + 1 self.assertAllClose(grad_vals[0], exp1_plus_one) @@ -44,13 +44,13 @@ class GradientCorrectnessTest(test.TestCase): x = constant_op.constant(3.) dx_dx, = gradients_impl.gradients(x, x) with self.cached_session() as sess: - self.assertAllClose(1., sess.run(dx_dx)) + self.assertAllClose(1., self.evaluate(dx_dx)) def testIntegerIdentityGradient(self): x = constant_op.constant(3) dx_dx, = gradients_impl.gradients(x, x) with self.cached_session() as sess: - self.assertAllClose(1, sess.run(dx_dx)) + self.assertAllClose(1, self.evaluate(dx_dx)) def testGradientWithIntegerPath(self): x = constant_op.constant([3.9, 4.1]) @@ -58,7 +58,7 @@ class GradientCorrectnessTest(test.TestCase): y = x * k dy_dx, = gradients_impl.gradients(y, x) with self.cached_session() as sess: - self.assertAllClose([3., 4.], sess.run(dy_dx)) + self.assertAllClose([3., 4.], self.evaluate(dy_dx)) def testNoIntegerGradient1(self): x = constant_op.constant([3.9, 4.1]) diff --git a/tensorflow/python/kernel_tests/init_ops_test.py b/tensorflow/python/kernel_tests/init_ops_test.py index a3f2c0ddd75..074985dd931 100644 --- a/tensorflow/python/kernel_tests/init_ops_test.py +++ b/tensorflow/python/kernel_tests/init_ops_test.py @@ -709,7 +709,7 @@ class ConvolutionDeltaOrthogonalInitializerTest(test.TestCase): t = self.evaluate(outputs) self.assertAllEqual(t.shape, outputs_shape) # Check isometry of the delta-orthogonal kernel. - self.assertAllClose(sess.run(ratio), gain, rtol=tol, atol=tol) + self.assertAllClose(self.evaluate(ratio), gain, rtol=tol, atol=tol) def testNonuniformity(self): value = 0 @@ -847,7 +847,7 @@ class ConvolutionOrthogonal1dInitializerTest(test.TestCase): t = self.evaluate(outputs) self.assertAllEqual(t.shape, outputs_shape) # Check isometry of the orthogonal kernel. - self.assertAllClose(sess.run(ratio), gain, rtol=tol, atol=tol) + self.assertAllClose(self.evaluate(ratio), gain, rtol=tol, atol=tol) class ConvolutionOrthogonal2dInitializerTest(test.TestCase): @@ -942,7 +942,7 @@ class ConvolutionOrthogonal2dInitializerTest(test.TestCase): t = self.evaluate(outputs) self.assertAllEqual(t.shape, outputs_shape) # Check isometry of the orthogonal kernel. - self.assertAllClose(sess.run(ratio), gain, rtol=tol, atol=tol) + self.assertAllClose(self.evaluate(ratio), gain, rtol=tol, atol=tol) class ConvolutionOrthogonal3dInitializerTest(test.TestCase): @@ -1067,7 +1067,7 @@ class ConvolutionOrthogonal3dInitializerTest(test.TestCase): t = self.evaluate(outputs) self.assertAllEqual(t.shape, outputs_shape) # Check isometry of the orthogonal kernel. - self.assertAllClose(sess.run(ratio), gain, rtol=tol, atol=tol) + self.assertAllClose(self.evaluate(ratio), gain, rtol=tol, atol=tol) class IdentityInitializerTest(test.TestCase): diff --git a/tensorflow/python/kernel_tests/lookup_ops_test.py b/tensorflow/python/kernel_tests/lookup_ops_test.py index 3efad4ea116..ab4c9c730bd 100644 --- a/tensorflow/python/kernel_tests/lookup_ops_test.py +++ b/tensorflow/python/kernel_tests/lookup_ops_test.py @@ -174,7 +174,7 @@ class HashTableOpTest(test.TestCase): constant_op.constant(sp_shape, dtypes.int64)) output = table.lookup(input_tensor) - out_indices, out_values, out_shape = sess.run(output) + out_indices, out_values, out_shape = self.evaluate(output) self.assertAllEqual([0, 1, -1], out_values) self.assertAllEqual(sp_indices, out_indices) diff --git a/tensorflow/python/kernel_tests/losses_test.py b/tensorflow/python/kernel_tests/losses_test.py index d3a907852a2..bda63bcaa92 100644 --- a/tensorflow/python/kernel_tests/losses_test.py +++ b/tensorflow/python/kernel_tests/losses_test.py @@ -1046,9 +1046,9 @@ class MeanPairwiseSquaredErrorTest(test.TestCase): init_op = variables.global_variables_initializer() with self.cached_session() as sess: - sess.run(init_op) + self.evaluate(init_op) for grad, _ in gradients_to_variables: - np_grad = sess.run(grad) + np_grad = self.evaluate(grad) self.assertFalse(np.isnan(np_grad).any()) def testNonZeroLossWithPythonScalarWeight(self): diff --git a/tensorflow/python/kernel_tests/map_stage_op_test.py b/tensorflow/python/kernel_tests/map_stage_op_test.py index d503f3d7c9f..4b5bd4059fa 100644 --- a/tensorflow/python/kernel_tests/map_stage_op_test.py +++ b/tensorflow/python/kernel_tests/map_stage_op_test.py @@ -148,7 +148,7 @@ class MapStageTest(test.TestCase): for i in range(n): self.assertTrue(sess.run(peek, feed_dict={gi: i})[0] == i) - self.assertTrue(sess.run(size) == 10) + self.assertTrue(self.evaluate(size) == 10) def testSizeAndClear(self): with ops.Graph().as_default() as G: @@ -170,11 +170,11 @@ class MapStageTest(test.TestCase): with self.session(use_gpu=True, graph=G) as sess: sess.run(stage, feed_dict={x: -1, pi: 3}) - self.assertEqual(sess.run(size), 1) + self.assertEqual(self.evaluate(size), 1) sess.run(stage, feed_dict={x: -1, pi: 1}) - self.assertEqual(sess.run(size), 2) + self.assertEqual(self.evaluate(size), 2) sess.run(clear) - self.assertEqual(sess.run(size), 0) + self.assertEqual(self.evaluate(size), 0) def testCapacity(self): capacity = 3 @@ -231,13 +231,13 @@ class MapStageTest(test.TestCase): capacity)) # Should have capacity elements in the staging area - self.assertTrue(sess.run(size) == capacity) + self.assertTrue(self.evaluate(size) == capacity) # Clear the staging area completely for i in range(n): sess.run(get) - self.assertTrue(sess.run(size) == 0) + self.assertTrue(self.evaluate(size) == 0) def testMemoryLimit(self): memory_limit = 512 * 1024 # 512K @@ -295,13 +295,13 @@ class MapStageTest(test.TestCase): capacity)) # Should have capacity elements in the staging area - self.assertTrue(sess.run(size) == capacity) + self.assertTrue(self.evaluate(size) == capacity) # Clear the staging area completely for i in range(n): sess.run(get) - self.assertTrue(sess.run(size) == 0) + self.assertTrue(self.evaluate(size) == 0) def testOrdering(self): import six @@ -332,14 +332,14 @@ class MapStageTest(test.TestCase): for i in keys: sess.run(stage, feed_dict={pi: i, x: i}) - self.assertTrue(sess.run(size) == n) + self.assertTrue(self.evaluate(size) == n) # Check that key, values come out in ascending order for i, k in enumerate(reversed(keys)): - get_key, values = sess.run(get) + get_key, values = self.evaluate(get) self.assertTrue(i == k == get_key == values) - self.assertTrue(sess.run(size) == 0) + self.assertTrue(self.evaluate(size) == 0) def testPartialDictInsert(self): with ops.Graph().as_default() as G: diff --git a/tensorflow/python/kernel_tests/matrix_inverse_op_test.py b/tensorflow/python/kernel_tests/matrix_inverse_op_test.py index 434458721c1..5cef4b79a32 100644 --- a/tensorflow/python/kernel_tests/matrix_inverse_op_test.py +++ b/tensorflow/python/kernel_tests/matrix_inverse_op_test.py @@ -146,7 +146,7 @@ class InverseOpTest(test.TestCase): inv1 = linalg_ops.matrix_inverse(matrix1, adjoint=adjoint_) inv2 = linalg_ops.matrix_inverse(matrix2, adjoint=adjoint_) all_ops += [inv1, inv2] - inv = sess.run(all_ops) + inv = self.evaluate(all_ops) self.assertAllEqual(inv[0], inv[1]) self.assertAllEqual(inv[2], inv[3]) diff --git a/tensorflow/python/kernel_tests/matrix_solve_op_test.py b/tensorflow/python/kernel_tests/matrix_solve_op_test.py index 1334d0c4cee..80badee8962 100644 --- a/tensorflow/python/kernel_tests/matrix_solve_op_test.py +++ b/tensorflow/python/kernel_tests/matrix_solve_op_test.py @@ -126,7 +126,7 @@ class MatrixSolveOpTest(test.TestCase): s1 = linalg_ops.matrix_solve(lhs1, rhs1, adjoint=adjoint_) s2 = linalg_ops.matrix_solve(lhs2, rhs2, adjoint=adjoint_) all_ops += [s1, s2] - val = sess.run(all_ops) + val = self.evaluate(all_ops) self.assertAllEqual(val[0], val[1]) self.assertAllEqual(val[2], val[3]) diff --git a/tensorflow/python/kernel_tests/matrix_square_root_op_test.py b/tensorflow/python/kernel_tests/matrix_square_root_op_test.py index 9212580313c..1f2144bdee9 100644 --- a/tensorflow/python/kernel_tests/matrix_square_root_op_test.py +++ b/tensorflow/python/kernel_tests/matrix_square_root_op_test.py @@ -108,7 +108,7 @@ class SquareRootOpTest(test.TestCase): sqrt1 = gen_linalg_ops.matrix_square_root(matrix1) sqrt2 = gen_linalg_ops.matrix_square_root(matrix2) all_ops = [sqrt1, sqrt2] - sqrt = sess.run(all_ops) + sqrt = self.evaluate(all_ops) self.assertAllEqual(sqrt[0], sqrt[1]) diff --git a/tensorflow/python/kernel_tests/metrics_test.py b/tensorflow/python/kernel_tests/metrics_test.py index 5dcdb9e4205..b68327105a7 100644 --- a/tensorflow/python/kernel_tests/metrics_test.py +++ b/tensorflow/python/kernel_tests/metrics_test.py @@ -203,10 +203,10 @@ class MeanTest(test.TestCase): mean, update_op = metrics.mean(values) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) for _ in range(4): - sess.run(update_op) - self.assertAlmostEqual(1.65, sess.run(mean), 5) + self.evaluate(update_op) + self.assertAlmostEqual(1.65, self.evaluate(mean), 5) def testUpdateOpsReturnsCurrentValue(self): with self.cached_session() as sess: @@ -220,14 +220,14 @@ class MeanTest(test.TestCase): mean, update_op = metrics.mean(values) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) - self.assertAlmostEqual(0.5, sess.run(update_op), 5) - self.assertAlmostEqual(1.475, sess.run(update_op), 5) - self.assertAlmostEqual(12.4 / 6.0, sess.run(update_op), 5) - self.assertAlmostEqual(1.65, sess.run(update_op), 5) + self.assertAlmostEqual(0.5, self.evaluate(update_op), 5) + self.assertAlmostEqual(1.475, self.evaluate(update_op), 5) + self.assertAlmostEqual(12.4 / 6.0, self.evaluate(update_op), 5) + self.assertAlmostEqual(1.65, self.evaluate(update_op), 5) - self.assertAlmostEqual(1.65, sess.run(mean), 5) + self.assertAlmostEqual(1.65, self.evaluate(mean), 5) def testUnweighted(self): values = _test_values((3, 2, 4, 1)) @@ -370,10 +370,10 @@ class MeanTensorTest(test.TestCase): mean, update_op = metrics.mean_tensor(values) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) for _ in range(4): - sess.run(update_op) - self.assertAllClose([[-0.9 / 4., 3.525]], sess.run(mean)) + self.evaluate(update_op) + self.assertAllClose([[-0.9 / 4., 3.525]], self.evaluate(mean)) def testMultiDimensional(self): with self.cached_session() as sess: @@ -391,10 +391,11 @@ class MeanTensorTest(test.TestCase): mean, update_op = metrics.mean_tensor(values) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) for _ in range(2): - sess.run(update_op) - self.assertAllClose([[[1, 2], [1, 2]], [[2, 3], [5, 6]]], sess.run(mean)) + self.evaluate(update_op) + self.assertAllClose([[[1, 2], [1, 2]], [[2, 3], [5, 6]]], + self.evaluate(mean)) def testUpdateOpsReturnsCurrentValue(self): with self.cached_session() as sess: @@ -408,14 +409,14 @@ class MeanTensorTest(test.TestCase): mean, update_op = metrics.mean_tensor(values) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) - self.assertAllClose([[0, 1]], sess.run(update_op), 5) - self.assertAllClose([[-2.1, 5.05]], sess.run(update_op), 5) - self.assertAllClose([[2.3 / 3., 10.1 / 3.]], sess.run(update_op), 5) - self.assertAllClose([[-0.9 / 4., 3.525]], sess.run(update_op), 5) + self.assertAllClose([[0, 1]], self.evaluate(update_op), 5) + self.assertAllClose([[-2.1, 5.05]], self.evaluate(update_op), 5) + self.assertAllClose([[2.3 / 3., 10.1 / 3.]], self.evaluate(update_op), 5) + self.assertAllClose([[-0.9 / 4., 3.525]], self.evaluate(update_op), 5) - self.assertAllClose([[-0.9 / 4., 3.525]], sess.run(mean), 5) + self.assertAllClose([[-0.9 / 4., 3.525]], self.evaluate(mean), 5) def testBinaryWeighted1d(self): with self.cached_session() as sess: @@ -439,10 +440,10 @@ class MeanTensorTest(test.TestCase): mean, update_op = metrics.mean_tensor(values, weights) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) for _ in range(4): - sess.run(update_op) - self.assertAllClose([[3.25, 0.5]], sess.run(mean), 5) + self.evaluate(update_op) + self.assertAllClose([[3.25, 0.5]], self.evaluate(mean), 5) def testWeighted1d(self): with self.cached_session() as sess: @@ -466,10 +467,10 @@ class MeanTensorTest(test.TestCase): mean, update_op = metrics.mean_tensor(values, weights) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) for _ in range(4): - sess.run(update_op) - self.assertAllClose([[0.8, 3.52]], sess.run(mean), 5) + self.evaluate(update_op) + self.assertAllClose([[0.8, 3.52]], self.evaluate(mean), 5) def testWeighted2d_1(self): with self.cached_session() as sess: @@ -493,10 +494,10 @@ class MeanTensorTest(test.TestCase): mean, update_op = metrics.mean_tensor(values, weights) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) for _ in range(4): - sess.run(update_op) - self.assertAllClose([[-2.1, 0.5]], sess.run(mean), 5) + self.evaluate(update_op) + self.assertAllClose([[-2.1, 0.5]], self.evaluate(mean), 5) def testWeighted2d_2(self): with self.cached_session() as sess: @@ -520,10 +521,10 @@ class MeanTensorTest(test.TestCase): mean, update_op = metrics.mean_tensor(values, weights) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) for _ in range(4): - sess.run(update_op) - self.assertAllClose([[0, 0.5]], sess.run(mean), 5) + self.evaluate(update_op) + self.assertAllClose([[0, 0.5]], self.evaluate(mean), 5) class AccuracyTest(test.TestCase): @@ -576,11 +577,11 @@ class AccuracyTest(test.TestCase): accuracy, update_op = metrics.accuracy(labels, predictions) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) # Run several updates. for _ in range(10): - sess.run(update_op) + self.evaluate(update_op) # Then verify idempotency. initial_accuracy = accuracy.eval() @@ -609,10 +610,10 @@ class AccuracyTest(test.TestCase): accuracy, update_op = metrics.accuracy(labels, predictions) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) for _ in xrange(3): - sess.run(update_op) - self.assertEqual(0.5, sess.run(update_op)) + self.evaluate(update_op) + self.assertEqual(0.5, self.evaluate(update_op)) self.assertEqual(0.5, accuracy.eval()) def testEffectivelyEquivalentSizes(self): @@ -621,7 +622,7 @@ class AccuracyTest(test.TestCase): with self.cached_session() as sess: accuracy, update_op = metrics.accuracy(labels, predictions) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) self.assertEqual(1.0, update_op.eval()) self.assertEqual(1.0, accuracy.eval()) @@ -631,7 +632,7 @@ class AccuracyTest(test.TestCase): with self.cached_session() as sess: accuracy, update_op = metrics.accuracy(labels, predictions, weights=2.0) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) self.assertEqual(1.0, update_op.eval()) self.assertEqual(1.0, accuracy.eval()) @@ -645,7 +646,7 @@ class AccuracyTest(test.TestCase): with self.cached_session() as sess: accuracy, update_op = metrics.accuracy(labels, predictions, weights) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) # if streaming_accuracy does not flatten the weight, accuracy would be # 0.33333334 due to an intended broadcast of weight. Due to flattening, # it will be higher than .95 @@ -666,7 +667,7 @@ class AccuracyTest(test.TestCase): accuracy, update_op = metrics.accuracy(labels, predictions, weights_placeholder) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) # if streaming_accuracy does not flatten the weight, accuracy would be # 0.33333334 due to an intended broadcast of weight. Due to flattening, # it will be higher than .95 @@ -704,10 +705,10 @@ class AccuracyTest(test.TestCase): accuracy, update_op = metrics.accuracy(labels, predictions, weights) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) for _ in xrange(3): - sess.run(update_op) - self.assertEqual(1.0, sess.run(update_op)) + self.evaluate(update_op) + self.assertEqual(1.0, self.evaluate(update_op)) self.assertEqual(1.0, accuracy.eval()) @@ -747,11 +748,11 @@ class PrecisionTest(test.TestCase): precision, update_op = metrics.precision(labels, predictions) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) # Run several updates. for _ in range(10): - sess.run(update_op) + self.evaluate(update_op) # Then verify idempotency. initial_precision = precision.eval() @@ -766,8 +767,8 @@ class PrecisionTest(test.TestCase): precision, update_op = metrics.precision(labels, predictions) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) - self.assertAlmostEqual(1, sess.run(update_op)) + self.evaluate(variables.local_variables_initializer()) + self.assertAlmostEqual(1, self.evaluate(update_op)) self.assertAlmostEqual(1, precision.eval()) def testSomeCorrect_multipleInputDtypes(self): @@ -779,7 +780,7 @@ class PrecisionTest(test.TestCase): precision, update_op = metrics.precision(labels, predictions) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) self.assertAlmostEqual(0.5, update_op.eval()) self.assertAlmostEqual(0.5, precision.eval()) @@ -882,8 +883,8 @@ class PrecisionTest(test.TestCase): precision, update_op = metrics.precision(labels, predictions) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) - sess.run(update_op) + self.evaluate(variables.local_variables_initializer()) + self.evaluate(update_op) self.assertAlmostEqual(0, precision.eval()) def testZeroTrueAndFalsePositivesGivesZeroPrecision(self): @@ -892,8 +893,8 @@ class PrecisionTest(test.TestCase): precision, update_op = metrics.precision(labels, predictions) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) - sess.run(update_op) + self.evaluate(variables.local_variables_initializer()) + self.evaluate(update_op) self.assertEqual(0.0, precision.eval()) @@ -934,11 +935,11 @@ class RecallTest(test.TestCase): recall, update_op = metrics.recall(labels, predictions) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) # Run several updates. for _ in range(10): - sess.run(update_op) + self.evaluate(update_op) # Then verify idempotency. initial_recall = recall.eval() @@ -953,8 +954,8 @@ class RecallTest(test.TestCase): recall, update_op = metrics.recall(labels, predictions) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) - sess.run(update_op) + self.evaluate(variables.local_variables_initializer()) + self.evaluate(update_op) self.assertEqual(1, recall.eval()) def testSomeCorrect_multipleInputDtypes(self): @@ -966,7 +967,7 @@ class RecallTest(test.TestCase): recall, update_op = metrics.recall(labels, predictions) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) self.assertAlmostEqual(0.5, update_op.eval()) self.assertAlmostEqual(0.5, recall.eval()) @@ -977,7 +978,7 @@ class RecallTest(test.TestCase): recall, update_op = metrics.recall(labels, predictions, weights=weights) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) weighted_tp = 2.0 + 5.0 weighted_t = (2.0 + 2.0) + (5.0 + 5.0) expected_precision = weighted_tp / weighted_t @@ -991,7 +992,7 @@ class RecallTest(test.TestCase): recall, update_op = metrics.recall(labels, predictions, weights=weights) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) weighted_tp = 3.0 + 1.0 weighted_t = (2.0 + 3.0) + (4.0 + 1.0) expected_precision = weighted_tp / weighted_t @@ -1006,8 +1007,8 @@ class RecallTest(test.TestCase): recall, update_op = metrics.recall(labels, predictions) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) - sess.run(update_op) + self.evaluate(variables.local_variables_initializer()) + self.evaluate(update_op) self.assertEqual(0, recall.eval()) def testZeroTruePositivesAndFalseNegativesGivesZeroRecall(self): @@ -1016,8 +1017,8 @@ class RecallTest(test.TestCase): recall, update_op = metrics.recall(labels, predictions) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) - sess.run(update_op) + self.evaluate(variables.local_variables_initializer()) + self.evaluate(update_op) self.assertEqual(0, recall.eval()) @@ -1056,11 +1057,11 @@ class AUCTest(test.TestCase): auc, update_op = metrics.auc(labels, predictions) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) # Run several updates. for _ in range(10): - sess.run(update_op) + self.evaluate(update_op) # Then verify idempotency. initial_auc = auc.eval() @@ -1078,8 +1079,8 @@ class AUCTest(test.TestCase): labels = constant_op.constant(inputs) auc, update_op = metrics.auc(labels, predictions, curve=curve) - sess.run(variables.local_variables_initializer()) - self.assertEqual(1, sess.run(update_op)) + self.evaluate(variables.local_variables_initializer()) + self.assertEqual(1, self.evaluate(update_op)) self.assertEqual(1, auc.eval()) @@ -1093,8 +1094,8 @@ class AUCTest(test.TestCase): constant_op.constant([0, 1, 1, 0], shape=(1, 4)), dtype=label_dtype) auc, update_op = metrics.auc(labels, predictions) - sess.run(variables.local_variables_initializer()) - self.assertAlmostEqual(0.5, sess.run(update_op)) + self.evaluate(variables.local_variables_initializer()) + self.assertAlmostEqual(0.5, self.evaluate(update_op)) self.assertAlmostEqual(0.5, auc.eval()) @@ -1106,8 +1107,8 @@ class AUCTest(test.TestCase): weights = constant_op.constant([2], shape=(1, 1)) auc, update_op = metrics.auc(labels, predictions, weights=weights) - sess.run(variables.local_variables_initializer()) - self.assertAlmostEqual(0.5, sess.run(update_op), 5) + self.evaluate(variables.local_variables_initializer()) + self.assertAlmostEqual(0.5, self.evaluate(update_op), 5) self.assertAlmostEqual(0.5, auc.eval(), 5) @@ -1119,8 +1120,8 @@ class AUCTest(test.TestCase): weights = constant_op.constant([1, 2, 3, 4], shape=(1, 4)) auc, update_op = metrics.auc(labels, predictions, weights=weights) - sess.run(variables.local_variables_initializer()) - self.assertAlmostEqual(0.7, sess.run(update_op), 5) + self.evaluate(variables.local_variables_initializer()) + self.assertAlmostEqual(0.7, self.evaluate(update_op), 5) self.assertAlmostEqual(0.7, auc.eval(), 5) @@ -1134,10 +1135,10 @@ class AUCTest(test.TestCase): auc, update_op = metrics.auc(labels, predictions, curve='PR', summation_method='careful_interpolation') - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) # expected ~= 0.79726744594 expected = 1 - math.log(1.5) / 2 - self.assertAlmostEqual(expected, sess.run(update_op), delta=1e-3) + self.assertAlmostEqual(expected, self.evaluate(update_op), delta=1e-3) self.assertAlmostEqual(expected, auc.eval(), delta=1e-3) def testCorrectAnotherAUCPRSpecialCase(self): @@ -1150,10 +1151,10 @@ class AUCTest(test.TestCase): auc, update_op = metrics.auc(labels, predictions, curve='PR', summation_method='careful_interpolation') - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) # expected ~= 0.61350593198 expected = (2.5 - 2 * math.log(4./3) - 0.25 * math.log(7./5)) / 3 - self.assertAlmostEqual(expected, sess.run(update_op), delta=1e-3) + self.assertAlmostEqual(expected, self.evaluate(update_op), delta=1e-3) self.assertAlmostEqual(expected, auc.eval(), delta=1e-3) def testThirdCorrectAUCPRSpecialCase(self): @@ -1166,10 +1167,10 @@ class AUCTest(test.TestCase): auc, update_op = metrics.auc(labels, predictions, curve='PR', summation_method='careful_interpolation') - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) # expected ~= 0.90410597584 expected = 1 - math.log(4./3) / 3 - self.assertAlmostEqual(expected, sess.run(update_op), delta=1e-3) + self.assertAlmostEqual(expected, self.evaluate(update_op), delta=1e-3) self.assertAlmostEqual(expected, auc.eval(), delta=1e-3) def testIncorrectAUCPRSpecialCase(self): @@ -1180,8 +1181,8 @@ class AUCTest(test.TestCase): auc, update_op = metrics.auc(labels, predictions, curve='PR', summation_method='trapezoidal') - sess.run(variables.local_variables_initializer()) - self.assertAlmostEqual(0.79166, sess.run(update_op), delta=1e-3) + self.evaluate(variables.local_variables_initializer()) + self.assertAlmostEqual(0.79166, self.evaluate(update_op), delta=1e-3) self.assertAlmostEqual(0.79166, auc.eval(), delta=1e-3) @@ -1195,8 +1196,8 @@ class AUCTest(test.TestCase): auc, update_op = metrics.auc(labels, predictions, curve='PR', summation_method='trapezoidal') - sess.run(variables.local_variables_initializer()) - self.assertAlmostEqual(0.610317, sess.run(update_op), delta=1e-3) + self.evaluate(variables.local_variables_initializer()) + self.assertAlmostEqual(0.610317, self.evaluate(update_op), delta=1e-3) self.assertAlmostEqual(0.610317, auc.eval(), delta=1e-3) @@ -1210,8 +1211,8 @@ class AUCTest(test.TestCase): auc, update_op = metrics.auc(labels, predictions, curve='PR', summation_method='trapezoidal') - sess.run(variables.local_variables_initializer()) - self.assertAlmostEqual(0.90277, sess.run(update_op), delta=1e-3) + self.evaluate(variables.local_variables_initializer()) + self.assertAlmostEqual(0.90277, self.evaluate(update_op), delta=1e-3) self.assertAlmostEqual(0.90277, auc.eval(), delta=1e-3) @@ -1223,8 +1224,8 @@ class AUCTest(test.TestCase): labels = constant_op.constant(1 - inputs, dtype=dtypes_lib.float32) auc, update_op = metrics.auc(labels, predictions) - sess.run(variables.local_variables_initializer()) - self.assertAlmostEqual(0, sess.run(update_op)) + self.evaluate(variables.local_variables_initializer()) + self.assertAlmostEqual(0, self.evaluate(update_op)) self.assertAlmostEqual(0, auc.eval()) @@ -1234,8 +1235,8 @@ class AUCTest(test.TestCase): labels = array_ops.zeros([4]) auc, update_op = metrics.auc(labels, predictions) - sess.run(variables.local_variables_initializer()) - self.assertAlmostEqual(1, sess.run(update_op), 6) + self.evaluate(variables.local_variables_initializer()) + self.assertAlmostEqual(1, self.evaluate(update_op), 6) self.assertAlmostEqual(1, auc.eval(), 6) @@ -1245,8 +1246,8 @@ class AUCTest(test.TestCase): labels = array_ops.ones([4]) auc, update_op = metrics.auc(labels, predictions, curve='PR') - sess.run(variables.local_variables_initializer()) - self.assertAlmostEqual(1, sess.run(update_op), 6) + self.evaluate(variables.local_variables_initializer()) + self.assertAlmostEqual(1, self.evaluate(update_op), 6) self.assertAlmostEqual(1, auc.eval(), 6) @@ -1317,9 +1318,9 @@ class AUCTest(test.TestCase): num_thresholds=500, weights=tf_weights) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) for i in range(num_batches): - sess.run(update_op) + self.evaluate(update_op) # Since this is only approximate, we can't expect a 6 digits match. # Although with higher number of samples/thresholds we should see the @@ -1371,11 +1372,11 @@ class SpecificityAtSensitivityTest(test.TestCase): labels, predictions, sensitivity=0.7) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) # Run several updates. for _ in range(10): - sess.run(update_op) + self.evaluate(update_op) # Then verify idempotency. initial_specificity = specificity.eval() @@ -1391,8 +1392,8 @@ class SpecificityAtSensitivityTest(test.TestCase): labels, predictions, sensitivity=0.7) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) - self.assertEqual(1, sess.run(update_op)) + self.evaluate(variables.local_variables_initializer()) + self.assertEqual(1, self.evaluate(update_op)) self.assertEqual(1, specificity.eval()) def testSomeCorrectHighSensitivity(self): @@ -1406,8 +1407,8 @@ class SpecificityAtSensitivityTest(test.TestCase): labels, predictions, sensitivity=0.8) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) - self.assertAlmostEqual(1.0, sess.run(update_op)) + self.evaluate(variables.local_variables_initializer()) + self.assertAlmostEqual(1.0, self.evaluate(update_op)) self.assertAlmostEqual(1.0, specificity.eval()) def testSomeCorrectLowSensitivity(self): @@ -1421,9 +1422,9 @@ class SpecificityAtSensitivityTest(test.TestCase): labels, predictions, sensitivity=0.4) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) - self.assertAlmostEqual(0.6, sess.run(update_op)) + self.assertAlmostEqual(0.6, self.evaluate(update_op)) self.assertAlmostEqual(0.6, specificity.eval()) def testWeighted1d_multipleLabelDtypes(self): @@ -1440,9 +1441,9 @@ class SpecificityAtSensitivityTest(test.TestCase): labels, predictions, weights=weights, sensitivity=0.4) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) - self.assertAlmostEqual(0.6, sess.run(update_op)) + self.assertAlmostEqual(0.6, self.evaluate(update_op)) self.assertAlmostEqual(0.6, specificity.eval()) def testWeighted2d(self): @@ -1458,9 +1459,9 @@ class SpecificityAtSensitivityTest(test.TestCase): labels, predictions, weights=weights, sensitivity=0.4) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) - self.assertAlmostEqual(8.0 / 15.0, sess.run(update_op)) + self.assertAlmostEqual(8.0 / 15.0, self.evaluate(update_op)) self.assertAlmostEqual(8.0 / 15.0, specificity.eval()) @@ -1508,11 +1509,11 @@ class SensitivityAtSpecificityTest(test.TestCase): labels, predictions, specificity=0.7) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) # Run several updates. for _ in range(10): - sess.run(update_op) + self.evaluate(update_op) # Then verify idempotency. initial_sensitivity = sensitivity.eval() @@ -1528,8 +1529,8 @@ class SensitivityAtSpecificityTest(test.TestCase): labels, predictions, specificity=0.7) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) - self.assertEqual(1, sess.run(update_op)) + self.evaluate(variables.local_variables_initializer()) + self.assertEqual(1, self.evaluate(update_op)) self.assertEqual(1, specificity.eval()) def testSomeCorrectHighSpecificity(self): @@ -1543,8 +1544,8 @@ class SensitivityAtSpecificityTest(test.TestCase): labels, predictions, specificity=0.8) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) - self.assertAlmostEqual(0.8, sess.run(update_op)) + self.evaluate(variables.local_variables_initializer()) + self.assertAlmostEqual(0.8, self.evaluate(update_op)) self.assertAlmostEqual(0.8, specificity.eval()) def testSomeCorrectLowSpecificity(self): @@ -1558,8 +1559,8 @@ class SensitivityAtSpecificityTest(test.TestCase): labels, predictions, specificity=0.4) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) - self.assertAlmostEqual(0.6, sess.run(update_op)) + self.evaluate(variables.local_variables_initializer()) + self.assertAlmostEqual(0.6, self.evaluate(update_op)) self.assertAlmostEqual(0.6, specificity.eval()) def testWeighted_multipleLabelDtypes(self): @@ -1577,8 +1578,8 @@ class SensitivityAtSpecificityTest(test.TestCase): labels, predictions, weights=weights, specificity=0.4) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) - self.assertAlmostEqual(0.675, sess.run(update_op)) + self.evaluate(variables.local_variables_initializer()) + self.assertAlmostEqual(0.675, self.evaluate(update_op)) self.assertAlmostEqual(0.675, specificity.eval()) @@ -1639,7 +1640,7 @@ class PrecisionRecallThresholdsTest(test.TestCase): rec, rec_op = metrics.recall_at_thresholds(labels, predictions, thresholds) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) # Run several updates, then verify idempotency. sess.run([prec_op, rec_op]) @@ -1663,7 +1664,7 @@ class PrecisionRecallThresholdsTest(test.TestCase): rec, rec_op = metrics.recall_at_thresholds(labels, predictions, thresholds) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) sess.run([prec_op, rec_op]) self.assertEqual(1, prec.eval()) @@ -1683,7 +1684,7 @@ class PrecisionRecallThresholdsTest(test.TestCase): rec, rec_op = metrics.recall_at_thresholds(labels, predictions, thresholds) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) sess.run([prec_op, rec_op]) self.assertAlmostEqual(0.5, prec.eval()) @@ -1701,7 +1702,7 @@ class PrecisionRecallThresholdsTest(test.TestCase): rec, rec_op = metrics.recall_at_thresholds(labels, predictions, thresholds) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) sess.run([prec_op, rec_op]) self.assertAlmostEqual(0, prec.eval()) @@ -1729,7 +1730,7 @@ class PrecisionRecallThresholdsTest(test.TestCase): rec_low = array_ops.reshape(rec_low, shape=()) rec_high = array_ops.reshape(rec_high, shape=()) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) sess.run([prec_op, rec_op]) self.assertAlmostEqual(1.0, prec_low.eval(), places=5) @@ -1759,7 +1760,7 @@ class PrecisionRecallThresholdsTest(test.TestCase): rec_low = array_ops.reshape(rec_low, shape=()) rec_high = array_ops.reshape(rec_high, shape=()) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) sess.run([prec_op, rec_op]) self.assertAlmostEqual(1.0, prec_low.eval(), places=5) @@ -1783,7 +1784,7 @@ class PrecisionRecallThresholdsTest(test.TestCase): [rec_low, rec_high] = array_ops.split( value=rec, num_or_size_splits=2, axis=0) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) sess.run([prec_op, rec_op]) self.assertAlmostEqual(0.75, prec_low.eval()) @@ -1801,7 +1802,7 @@ class PrecisionRecallThresholdsTest(test.TestCase): rec, rec_op = metrics.recall_at_thresholds(labels, predictions, thresholds) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) sess.run([prec_op, rec_op]) self.assertAlmostEqual(0, prec.eval(), 6) @@ -1869,7 +1870,7 @@ class PrecisionRecallThresholdsTest(test.TestCase): rec, rec_op = metrics.recall_at_thresholds(tf_labels, tf_predictions, thresholds) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) for _ in range(int(num_samples / batch_size)): sess.run([prec_op, rec_op]) # Since this is only approximate, we can't expect a 6 digits match. @@ -2802,11 +2803,11 @@ class MeanAbsoluteErrorTest(test.TestCase): error, update_op = metrics.mean_absolute_error(labels, predictions) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) # Run several updates. for _ in range(10): - sess.run(update_op) + self.evaluate(update_op) # Then verify idempotency. initial_error = error.eval() @@ -2823,8 +2824,8 @@ class MeanAbsoluteErrorTest(test.TestCase): error, update_op = metrics.mean_absolute_error(labels, predictions, weights) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) - self.assertEqual(3, sess.run(update_op)) + self.evaluate(variables.local_variables_initializer()) + self.assertEqual(3, self.evaluate(update_op)) self.assertEqual(3, error.eval()) @@ -2867,11 +2868,11 @@ class MeanRelativeErrorTest(test.TestCase): normalizer) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) # Run several updates. for _ in range(10): - sess.run(update_op) + self.evaluate(update_op) # Then verify idempotency. initial_error = error.eval() @@ -2892,8 +2893,8 @@ class MeanRelativeErrorTest(test.TestCase): labels, predictions, normalizer=labels) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) - self.assertEqual(expected_error, sess.run(update_op)) + self.evaluate(variables.local_variables_initializer()) + self.assertEqual(expected_error, self.evaluate(update_op)) self.assertEqual(expected_error, error.eval()) def testSingleUpdateNormalizedByZeros(self): @@ -2908,8 +2909,8 @@ class MeanRelativeErrorTest(test.TestCase): labels, predictions, normalizer=array_ops.zeros_like(labels)) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) - self.assertEqual(0.0, sess.run(update_op)) + self.evaluate(variables.local_variables_initializer()) + self.assertEqual(0.0, self.evaluate(update_op)) self.assertEqual(0.0, error.eval()) @@ -2946,11 +2947,11 @@ class MeanSquaredErrorTest(test.TestCase): error, update_op = metrics.mean_squared_error(labels, predictions) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) # Run several updates. for _ in range(10): - sess.run(update_op) + self.evaluate(update_op) # Then verify idempotency. initial_error = error.eval() @@ -2964,8 +2965,8 @@ class MeanSquaredErrorTest(test.TestCase): error, update_op = metrics.mean_squared_error(labels, predictions) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) - self.assertEqual(0, sess.run(update_op)) + self.evaluate(variables.local_variables_initializer()) + self.assertEqual(0, self.evaluate(update_op)) self.assertEqual(0, error.eval()) def testSingleUpdateWithError(self): @@ -2977,8 +2978,8 @@ class MeanSquaredErrorTest(test.TestCase): error, update_op = metrics.mean_squared_error(labels, predictions) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) - self.assertEqual(6, sess.run(update_op)) + self.evaluate(variables.local_variables_initializer()) + self.assertEqual(6, self.evaluate(update_op)) self.assertEqual(6, error.eval()) def testSingleUpdateWithErrorAndWeights(self): @@ -2991,8 +2992,8 @@ class MeanSquaredErrorTest(test.TestCase): error, update_op = metrics.mean_squared_error(labels, predictions, weights) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) - self.assertEqual(13, sess.run(update_op)) + self.evaluate(variables.local_variables_initializer()) + self.assertEqual(13, self.evaluate(update_op)) self.assertEqual(13, error.eval()) def testMultipleBatchesOfSizeOne(self): @@ -3013,9 +3014,9 @@ class MeanSquaredErrorTest(test.TestCase): error, update_op = metrics.mean_squared_error(labels, predictions) - sess.run(variables.local_variables_initializer()) - sess.run(update_op) - self.assertAlmostEqual(208.0 / 6, sess.run(update_op), 5) + self.evaluate(variables.local_variables_initializer()) + self.evaluate(update_op) + self.assertAlmostEqual(208.0 / 6, self.evaluate(update_op), 5) self.assertAlmostEqual(208.0 / 6, error.eval(), 5) @@ -3054,7 +3055,7 @@ class MeanSquaredErrorTest(test.TestCase): mse1, update_op1 = metrics.mean_squared_error( labels1, predictions1, name='msd1') - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) sess.run([update_op0, update_op1]) sess.run([update_op0, update_op1]) @@ -3081,7 +3082,7 @@ class MeanSquaredErrorTest(test.TestCase): mae, ma_update_op = metrics.mean_absolute_error(labels, predictions) mse, ms_update_op = metrics.mean_squared_error(labels, predictions) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) sess.run([ma_update_op, ms_update_op]) sess.run([ma_update_op, ms_update_op]) @@ -3123,11 +3124,11 @@ class RootMeanSquaredErrorTest(test.TestCase): error, update_op = metrics.root_mean_squared_error(labels, predictions) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) # Run several updates. for _ in range(10): - sess.run(update_op) + self.evaluate(update_op) # Then verify idempotency. initial_error = error.eval() @@ -3142,8 +3143,8 @@ class RootMeanSquaredErrorTest(test.TestCase): rmse, update_op = metrics.root_mean_squared_error(labels, predictions) - sess.run(variables.local_variables_initializer()) - self.assertEqual(0, sess.run(update_op)) + self.evaluate(variables.local_variables_initializer()) + self.assertEqual(0, self.evaluate(update_op)) self.assertEqual(0, rmse.eval()) @@ -3156,7 +3157,7 @@ class RootMeanSquaredErrorTest(test.TestCase): rmse, update_op = metrics.root_mean_squared_error(labels, predictions) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) self.assertAlmostEqual(math.sqrt(6), update_op.eval(), 5) self.assertAlmostEqual(math.sqrt(6), rmse.eval(), 5) @@ -3171,8 +3172,8 @@ class RootMeanSquaredErrorTest(test.TestCase): rmse, update_op = metrics.root_mean_squared_error(labels, predictions, weights) - sess.run(variables.local_variables_initializer()) - self.assertAlmostEqual(math.sqrt(13), sess.run(update_op)) + self.evaluate(variables.local_variables_initializer()) + self.assertAlmostEqual(math.sqrt(13), self.evaluate(update_op)) self.assertAlmostEqual(math.sqrt(13), rmse.eval(), 5) @@ -3221,11 +3222,11 @@ class MeanCosineDistanceTest(test.TestCase): error, update_op = metrics.mean_cosine_distance(labels, predictions, dim=1) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) # Run several updates. for _ in range(10): - sess.run(update_op) + self.evaluate(update_op) # Then verify idempotency. initial_error = error.eval() @@ -3243,8 +3244,8 @@ class MeanCosineDistanceTest(test.TestCase): error, update_op = metrics.mean_cosine_distance(labels, predictions, dim=2) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) - self.assertEqual(0, sess.run(update_op)) + self.evaluate(variables.local_variables_initializer()) + self.assertEqual(0, self.evaluate(update_op)) self.assertEqual(0, error.eval()) def testSingleUpdateWithError1(self): @@ -3259,8 +3260,8 @@ class MeanCosineDistanceTest(test.TestCase): error, update_op = metrics.mean_cosine_distance(labels, predictions, dim=2) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) - self.assertAlmostEqual(1, sess.run(update_op), 5) + self.evaluate(variables.local_variables_initializer()) + self.assertAlmostEqual(1, self.evaluate(update_op), 5) self.assertAlmostEqual(1, error.eval(), 5) def testSingleUpdateWithError2(self): @@ -3280,8 +3281,8 @@ class MeanCosineDistanceTest(test.TestCase): error, update_op = metrics.mean_cosine_distance(labels, predictions, dim=2) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) - self.assertAlmostEqual(1.0, sess.run(update_op), 5) + self.evaluate(variables.local_variables_initializer()) + self.assertAlmostEqual(1.0, self.evaluate(update_op), 5) self.assertAlmostEqual(1.0, error.eval(), 5) def testSingleUpdateWithErrorAndWeights1(self): @@ -3299,8 +3300,8 @@ class MeanCosineDistanceTest(test.TestCase): labels, predictions, dim=2, weights=weights) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) - self.assertEqual(0, sess.run(update_op)) + self.evaluate(variables.local_variables_initializer()) + self.assertEqual(0, self.evaluate(update_op)) self.assertEqual(0, error.eval()) def testSingleUpdateWithErrorAndWeights2(self): @@ -3318,7 +3319,7 @@ class MeanCosineDistanceTest(test.TestCase): labels, predictions, dim=2, weights=weights) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) self.assertEqual(1.5, update_op.eval()) self.assertEqual(1.5, error.eval()) @@ -3360,7 +3361,7 @@ class PcntBelowThreshTest(test.TestCase): pcnt1, update_op1 = metrics.percentage_below(values, 7, name='medium') pcnt2, update_op2 = metrics.percentage_below(values, 1, name='low') - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) sess.run([update_op0, update_op1, update_op2]) pcnt0, pcnt1, pcnt2 = sess.run([pcnt0, pcnt1, pcnt2]) @@ -3382,7 +3383,7 @@ class PcntBelowThreshTest(test.TestCase): pcnt2, update_op2 = metrics.percentage_below( values, 1, weights=weights, name='low') - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) self.assertListEqual([1.0, 0.5, 0.0], sess.run([update_op0, update_op1, update_op2])) @@ -3446,11 +3447,11 @@ class MeanIOUTest(test.TestCase): labels, predictions, num_classes=num_classes) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) # Run several updates. for _ in range(10): - sess.run(update_op) + self.evaluate(update_op) # Then verify idempotency. initial_mean_iou = mean_iou.eval() @@ -3482,9 +3483,9 @@ class MeanIOUTest(test.TestCase): miou, update_op = metrics.mean_iou(labels, predictions, num_classes) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) for _ in range(5): - sess.run(update_op) + self.evaluate(update_op) desired_output = np.mean([1.0 / 2.0, 1.0 / 4.0, 0.]) self.assertEqual(desired_output, miou.eval()) @@ -3529,7 +3530,7 @@ class MeanIOUTest(test.TestCase): variables.local_variables_initializer().run() for _ in range(6): - sess.run(update_op) + self.evaluate(update_op) desired_output = np.mean([2.0 / 3.0, 1.0 / 2.0]) self.assertAlmostEqual(desired_output, mean_iou.eval()) @@ -3563,9 +3564,9 @@ class MeanIOUTest(test.TestCase): miou, update_op = metrics.mean_iou(labels, predictions, num_classes) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) for _ in range(5): - sess.run(update_op) + self.evaluate(update_op) desired_output = np.mean([1.0 / 3.0, 2.0 / 4.0]) self.assertAlmostEqual(desired_output, miou.eval()) @@ -3587,7 +3588,7 @@ class MeanIOUTest(test.TestCase): num_classes = 2 with self.cached_session() as sess: miou, update_op = metrics.mean_iou(labels, predictions, num_classes) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) confusion_matrix = update_op.eval() self.assertAllEqual([[3, 0], [2, 5]], confusion_matrix) desired_miou = np.mean([3. / 5., 5. / 7.]) @@ -3599,7 +3600,7 @@ class MeanIOUTest(test.TestCase): num_classes = 1 with self.cached_session() as sess: miou, update_op = metrics.mean_iou(labels, predictions, num_classes) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) self.assertEqual(40, update_op.eval()[0]) self.assertEqual(1.0, miou.eval()) @@ -3609,7 +3610,7 @@ class MeanIOUTest(test.TestCase): num_classes = 2 with self.cached_session() as sess: miou, update_op = metrics.mean_iou(labels, predictions, num_classes) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) self.assertAllEqual([[0, 0], [40, 0]], update_op.eval()) self.assertEqual(0., miou.eval()) @@ -3640,7 +3641,7 @@ class MeanIOUTest(test.TestCase): with self.cached_session() as sess: miou, update_op = metrics.mean_iou( labels, predictions, num_classes, weights=weights) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) self.assertAllEqual([[2, 0], [2, 4]], update_op.eval()) desired_miou = np.mean([2. / 4., 4. / 6.]) self.assertAlmostEqual(desired_miou, miou.eval()) @@ -3659,7 +3660,7 @@ class MeanIOUTest(test.TestCase): num_classes = 3 with self.cached_session() as sess: miou, update_op = metrics.mean_iou(labels, predictions, num_classes) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) self.assertAllEqual([[7, 4, 3], [3, 5, 2], [0, 0, 0]], update_op.eval()) self.assertAlmostEqual( 1 / 3 * (7 / (7 + 3 + 7) + 5 / (5 + 4 + 5) + 0 / (0 + 5 + 0)), @@ -3671,7 +3672,7 @@ class MeanIOUTest(test.TestCase): num_classes = 2 with self.cached_session() as sess: miou, update_op = metrics.mean_iou(labels, predictions, num_classes) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) self.assertAllEqual([[1, 0], [0, 0]], update_op.eval()) self.assertAlmostEqual(1, miou.eval()) @@ -3689,7 +3690,7 @@ class MeanIOUTest(test.TestCase): num_classes = 3 with self.cached_session() as sess: miou, update_op = metrics.mean_iou(labels, predictions, num_classes) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) self.assertAllEqual([[9, 5, 0], [3, 7, 0], [0, 0, 0]], update_op.eval()) self.assertAlmostEqual( 1 / 2 * (9 / (9 + 3 + 5) + 7 / (7 + 5 + 3)), miou.eval()) @@ -3752,11 +3753,11 @@ class MeanPerClassAccuracyTest(test.TestCase): labels, predictions, num_classes=num_classes) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) # Run several updates. for _ in range(10): - sess.run(update_op) + self.evaluate(update_op) # Then verify idempotency. initial_mean_accuracy = mean_accuracy.eval() @@ -3788,9 +3789,9 @@ class MeanPerClassAccuracyTest(test.TestCase): mean_accuracy, update_op = metrics.mean_per_class_accuracy( labels, predictions, num_classes) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) for _ in range(5): - sess.run(update_op) + self.evaluate(update_op) desired_output = np.mean([1.0, 1.0 / 3.0, 0.0]) self.assertAlmostEqual(desired_output, mean_accuracy.eval()) @@ -3835,7 +3836,7 @@ class MeanPerClassAccuracyTest(test.TestCase): variables.local_variables_initializer().run() for _ in range(6): - sess.run(update_op) + self.evaluate(update_op) desired_output = np.mean([2.0 / 2.0, 0.5 / 1.5]) self.assertAlmostEqual(desired_output, mean_accuracy.eval()) @@ -3870,9 +3871,9 @@ class MeanPerClassAccuracyTest(test.TestCase): mean_accuracy, update_op = metrics.mean_per_class_accuracy( labels, predictions, num_classes) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) for _ in range(5): - sess.run(update_op) + self.evaluate(update_op) desired_output = np.mean([1.0 / 2.0, 2.0 / 3.0, 0.]) self.assertAlmostEqual(desired_output, mean_accuracy.eval()) @@ -3883,7 +3884,7 @@ class MeanPerClassAccuracyTest(test.TestCase): with self.cached_session() as sess: mean_accuracy, update_op = metrics.mean_per_class_accuracy( labels, predictions, num_classes) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) self.assertEqual(1.0, update_op.eval()[0]) self.assertEqual(1.0, mean_accuracy.eval()) @@ -3894,7 +3895,7 @@ class MeanPerClassAccuracyTest(test.TestCase): with self.cached_session() as sess: mean_accuracy, update_op = metrics.mean_per_class_accuracy( labels, predictions, num_classes) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) self.assertAllEqual([0.0, 0.0], update_op.eval()) self.assertEqual(0., mean_accuracy.eval()) @@ -3913,7 +3914,7 @@ class MeanPerClassAccuracyTest(test.TestCase): with self.cached_session() as sess: mean_accuracy, update_op = metrics.mean_per_class_accuracy( labels, predictions, num_classes, weights=weights) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) desired_accuracy = np.array([2. / 2., 4. / 6.], dtype=np.float32) self.assertAllEqual(desired_accuracy, update_op.eval()) desired_mean_accuracy = np.mean(desired_accuracy) @@ -3945,7 +3946,7 @@ class FalseNegativesTest(test.TestCase): labels=labels, predictions=predictions) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) self.assertAllClose(0., tn.eval()) self.assertAllClose(3., tn_update_op.eval()) self.assertAllClose(3., tn.eval()) @@ -3964,7 +3965,7 @@ class FalseNegativesTest(test.TestCase): labels=labels, predictions=predictions, weights=weights) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) self.assertAllClose(0., tn.eval()) self.assertAllClose(5., tn_update_op.eval()) self.assertAllClose(5., tn.eval()) @@ -3994,7 +3995,7 @@ class FalseNegativesAtThresholdsTest(test.TestCase): predictions=predictions, labels=labels, thresholds=[0.15, 0.5, 0.85]) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) self.assertAllEqual((0, 0, 0), fn.eval()) self.assertAllEqual((0, 2, 3), fn_update_op.eval()) self.assertAllEqual((0, 2, 3), fn.eval()) @@ -4013,7 +4014,7 @@ class FalseNegativesAtThresholdsTest(test.TestCase): thresholds=[0.15, 0.5, 0.85]) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) self.assertAllEqual((0.0, 0.0, 0.0), fn.eval()) self.assertAllEqual((0.0, 8.0, 11.0), fn_update_op.eval()) self.assertAllEqual((0.0, 8.0, 11.0), fn.eval()) @@ -4044,7 +4045,7 @@ class FalsePositivesTest(test.TestCase): labels=labels, predictions=predictions) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) self.assertAllClose(0., tn.eval()) self.assertAllClose(7., tn_update_op.eval()) self.assertAllClose(7., tn.eval()) @@ -4063,7 +4064,7 @@ class FalsePositivesTest(test.TestCase): labels=labels, predictions=predictions, weights=weights) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) self.assertAllClose(0., tn.eval()) self.assertAllClose(14., tn_update_op.eval()) self.assertAllClose(14., tn.eval()) @@ -4093,7 +4094,7 @@ class FalsePositivesAtThresholdsTest(test.TestCase): predictions=predictions, labels=labels, thresholds=[0.15, 0.5, 0.85]) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) self.assertAllEqual((0, 0, 0), fp.eval()) self.assertAllEqual((7, 4, 2), fp_update_op.eval()) self.assertAllEqual((7, 4, 2), fp.eval()) @@ -4114,7 +4115,7 @@ class FalsePositivesAtThresholdsTest(test.TestCase): thresholds=[0.15, 0.5, 0.85]) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) self.assertAllEqual((0.0, 0.0, 0.0), fp.eval()) self.assertAllEqual((125.0, 42.0, 12.0), fp_update_op.eval()) self.assertAllEqual((125.0, 42.0, 12.0), fp.eval()) @@ -4145,7 +4146,7 @@ class TrueNegativesTest(test.TestCase): labels=labels, predictions=predictions) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) self.assertAllClose(0., tn.eval()) self.assertAllClose(3., tn_update_op.eval()) self.assertAllClose(3., tn.eval()) @@ -4164,7 +4165,7 @@ class TrueNegativesTest(test.TestCase): labels=labels, predictions=predictions, weights=weights) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) self.assertAllClose(0., tn.eval()) self.assertAllClose(4., tn_update_op.eval()) self.assertAllClose(4., tn.eval()) @@ -4194,7 +4195,7 @@ class TrueNegativesAtThresholdsTest(test.TestCase): predictions=predictions, labels=labels, thresholds=[0.15, 0.5, 0.85]) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) self.assertAllEqual((0, 0, 0), tn.eval()) self.assertAllEqual((2, 5, 7), tn_update_op.eval()) self.assertAllEqual((2, 5, 7), tn.eval()) @@ -4213,7 +4214,7 @@ class TrueNegativesAtThresholdsTest(test.TestCase): thresholds=[0.15, 0.5, 0.85]) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) self.assertAllEqual((0.0, 0.0, 0.0), tn.eval()) self.assertAllEqual((5.0, 15.0, 23.0), tn_update_op.eval()) self.assertAllEqual((5.0, 15.0, 23.0), tn.eval()) @@ -4244,7 +4245,7 @@ class TruePositivesTest(test.TestCase): labels=labels, predictions=predictions) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) self.assertAllClose(0., tn.eval()) self.assertAllClose(7., tn_update_op.eval()) self.assertAllClose(7., tn.eval()) @@ -4263,7 +4264,7 @@ class TruePositivesTest(test.TestCase): labels=labels, predictions=predictions, weights=weights) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) self.assertAllClose(0., tn.eval()) self.assertAllClose(12., tn_update_op.eval()) self.assertAllClose(12., tn.eval()) @@ -4293,7 +4294,7 @@ class TruePositivesAtThresholdsTest(test.TestCase): predictions=predictions, labels=labels, thresholds=[0.15, 0.5, 0.85]) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) self.assertAllEqual((0, 0, 0), tp.eval()) self.assertAllEqual((3, 1, 0), tp_update_op.eval()) self.assertAllEqual((3, 1, 0), tp.eval()) @@ -4310,7 +4311,7 @@ class TruePositivesAtThresholdsTest(test.TestCase): thresholds=[0.15, 0.5, 0.85]) with self.cached_session() as sess: - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) self.assertAllEqual((0.0, 0.0, 0.0), tp.eval()) self.assertAllEqual((111.0, 37.0, 0.0), tp_update_op.eval()) self.assertAllEqual((111.0, 37.0, 0.0), tp.eval()) 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 15e38265421..87f1991aa78 100644 --- a/tensorflow/python/kernel_tests/neon_depthwise_conv_op_test.py +++ b/tensorflow/python/kernel_tests/neon_depthwise_conv_op_test.py @@ -142,8 +142,8 @@ class DepthwiseConv2DTest(test.TestCase): conv_interface = nn_impl.depthwise_conv2d( t1, t2, strides=[1, stride, stride, 1], padding=padding) - native_result = sess.run(conv_native) - interface_result = sess.run(conv_interface) + native_result = self.evaluate(conv_native) + interface_result = self.evaluate(conv_interface) print("depthwise conv_2d: ", tensor_in_sizes, "*", filter_in_sizes, ", stride:", stride, ", padding: ", padding, ", max diff: ", @@ -211,7 +211,7 @@ class DepthwiseConv2DTest(test.TestCase): t2 = constant_op.constant(x2, shape=filter_in_sizes) conv = nn_ops.depthwise_conv2d_native( t1, t2, strides=[1, stride, stride, 1], padding=padding) - value = sess.run(conv) + value = self.evaluate(conv) print("value = ", value) self.assertAllClose(expected, np.ravel(value), 1e-5) self.assertShapeEqual(value, conv) diff --git a/tensorflow/python/kernel_tests/norm_op_test.py b/tensorflow/python/kernel_tests/norm_op_test.py index e202b6e8a43..5ff0c58bf1b 100644 --- a/tensorflow/python/kernel_tests/norm_op_test.py +++ b/tensorflow/python/kernel_tests/norm_op_test.py @@ -70,7 +70,7 @@ def _GetNormOpTest(dtype_, shape_, ord_, axis_, keep_dims_, use_static_shape_): tf_matrix = constant_op.constant(matrix) tf_norm = linalg_ops.norm( tf_matrix, ord=ord_, axis=axis_, keepdims=keep_dims_) - tf_norm_val = sess.run(tf_norm) + tf_norm_val = self.evaluate(tf_norm) else: tf_matrix = array_ops.placeholder(dtype_) tf_norm = linalg_ops.norm( diff --git a/tensorflow/python/kernel_tests/nth_element_op_test.py b/tensorflow/python/kernel_tests/nth_element_op_test.py index 338b6cec010..6cd49746710 100644 --- a/tensorflow/python/kernel_tests/nth_element_op_test.py +++ b/tensorflow/python/kernel_tests/nth_element_op_test.py @@ -35,7 +35,7 @@ class NthElementTest(test.TestCase): with self.cached_session(use_gpu=False) as sess: inputs_op = ops.convert_to_tensor(inputs, dtype=dtype) values_op = nn_ops.nth_element(inputs_op, n, reverse=reverse) - values = sess.run(values_op) + values = self.evaluate(values_op) self.assertShapeEqual(np_expected_values, values_op) self.assertAllClose(np_expected_values, values) diff --git a/tensorflow/python/kernel_tests/padding_fifo_queue_test.py b/tensorflow/python/kernel_tests/padding_fifo_queue_test.py index 520b6633759..3696298132a 100644 --- a/tensorflow/python/kernel_tests/padding_fifo_queue_test.py +++ b/tensorflow/python/kernel_tests/padding_fifo_queue_test.py @@ -126,7 +126,7 @@ class PaddingFIFOQueueTest(test.TestCase): # Run one producer thread for each element in elems. def enqueue(enqueue_op): - sess.run(enqueue_op) + self.evaluate(enqueue_op) threads = [ self.checkedThread( @@ -193,7 +193,7 @@ class PaddingFIFOQueueTest(test.TestCase): # TODO(mrry): Figure out how to do this without sleeping. time.sleep(0.1) for enqueue_op in enqueue_ops: - sess.run(enqueue_op) + self.evaluate(enqueue_op) results = [] @@ -224,7 +224,7 @@ class PaddingFIFOQueueTest(test.TestCase): enqueue_op.run() for i in xrange(len(elems)): - x_val, y_val = sess.run(dequeued_t) + x_val, y_val = self.evaluate(dequeued_t) x, y = elems[i] self.assertEqual([x], x_val) self.assertEqual([y], y_val) @@ -327,7 +327,7 @@ class PaddingFIFOQueueTest(test.TestCase): enqueue_op.run() for i in range(8): - float_val, int_val = sess.run(dequeued_t) + float_val, int_val = self.evaluate(dequeued_t) self.assertEqual(float_elems[i % 4], float_val) self.assertAllEqual(int_elems[i % 4], int_val) @@ -344,7 +344,7 @@ class PaddingFIFOQueueTest(test.TestCase): enqueue_op.run() for i in range(8): - float_val, int_val = sess.run(dequeued_t) + float_val, int_val = self.evaluate(dequeued_t) self.assertEqual(float_elems[i % 4], float_val) self.assertAllEqual(int_elems[i % 4], int_val) @@ -387,17 +387,17 @@ class PaddingFIFOQueueTest(test.TestCase): enqueue_op.run() - float_val, int_val = sess.run(dequeued_t) + float_val, int_val = self.evaluate(dequeued_t) self.assertAllEqual(float_elems[0:4], float_val) self.assertAllEqual(int_elems[0:4], int_val) self.assertEqual(float_val.shape, dequeued_t[0].get_shape()) self.assertEqual(int_val.shape, dequeued_t[1].get_shape()) - float_val, int_val = sess.run(dequeued_t) + float_val, int_val = self.evaluate(dequeued_t) self.assertAllEqual(float_elems[4:8], float_val) self.assertAllEqual(int_elems[4:8], int_val) - float_val, int_val = sess.run(dequeued_single_t) + float_val, int_val = self.evaluate(dequeued_single_t) self.assertAllEqual(float_elems[8], float_val) self.assertAllEqual(int_elems[8], int_val) self.assertEqual(float_val.shape, dequeued_single_t[0].get_shape()) @@ -418,7 +418,7 @@ class PaddingFIFOQueueTest(test.TestCase): enqueue_op.run() - float_val, int_val = sess.run(dequeued_t) + float_val, int_val = self.evaluate(dequeued_t) self.assertAllEqual(float_elems[0:4], float_val) self.assertAllEqual(int_elems[0:4], int_val) self.assertTrue( @@ -428,11 +428,11 @@ class PaddingFIFOQueueTest(test.TestCase): tensor_shape.TensorShape(int_val.shape).is_compatible_with(dequeued_t[ 1].get_shape())) - float_val, int_val = sess.run(dequeued_t) + float_val, int_val = self.evaluate(dequeued_t) self.assertAllEqual(float_elems[4:8], float_val) self.assertAllEqual(int_elems[4:8], int_val) - float_val, int_val = sess.run(dequeued_single_t) + float_val, int_val = self.evaluate(dequeued_single_t) self.assertAllEqual(float_elems[8], float_val) self.assertAllEqual(int_elems[8], int_val) self.assertTrue( @@ -459,7 +459,7 @@ class PaddingFIFOQueueTest(test.TestCase): for enqueue_op in enqueue_ops: enqueue_op.run() - string_val, int_val = sess.run(dequeued_t) + string_val, int_val = self.evaluate(dequeued_t) self.assertAllEqual([[b"a", b"", b""], [b"ab", b"", b""], [b"abc", b"", b""], [b"abc", b"d", b""], @@ -473,7 +473,7 @@ class PaddingFIFOQueueTest(test.TestCase): tensor_shape.TensorShape(int_val.shape).is_compatible_with(dequeued_t[ 1].get_shape())) - string_val, int_val = sess.run(dequeued_single_t) + string_val, int_val = self.evaluate(dequeued_single_t) self.assertAllEqual([b"abc", b"d", b"e", b"f"], string_val) self.assertAllEqual([[1, 2, 3, 4]], int_val) self.assertTrue( @@ -500,7 +500,7 @@ class PaddingFIFOQueueTest(test.TestCase): for enqueue_op in enqueue_ops: enqueue_op.run() - string_val, int_val = sess.run(dequeued_t) + string_val, int_val = self.evaluate(dequeued_t) self.assertAllEqual([[b"a", b"", b""], [b"ab", b"", b""], [b"abc", b"", b""], [b"abc", b"d", b""], @@ -514,7 +514,7 @@ class PaddingFIFOQueueTest(test.TestCase): tensor_shape.TensorShape(int_val.shape).is_compatible_with(dequeued_t[ 1].get_shape())) - string_val, int_val = sess.run(dequeued_single_t) + string_val, int_val = self.evaluate(dequeued_single_t) self.assertAllEqual([b"abc", b"d", b"e", b"f"], string_val) self.assertAllEqual([[1, 2, 3, 4]], int_val) self.assertTrue( @@ -633,7 +633,7 @@ class PaddingFIFOQueueTest(test.TestCase): # Enqueue 100 items in parallel on 10 threads. def enqueue(): - sess.run(enqueue_op) + self.evaluate(enqueue_op) threads = [self.checkedThread(target=enqueue) for _ in range(10)] for thread in threads: @@ -700,11 +700,11 @@ class PaddingFIFOQueueTest(test.TestCase): def enqueue(): for _ in xrange(100): - sess.run(enqueue_op) + self.evaluate(enqueue_op) def dequeue(): for _ in xrange(100): - self.assertTrue(sess.run(dequeued_t) in (10.0, 20.0)) + self.assertTrue(self.evaluate(dequeued_t) in (10.0, 20.0)) enqueue_threads = [self.checkedThread(target=enqueue) for _ in range(10)] dequeue_threads = [self.checkedThread(target=dequeue) for _ in range(10)] @@ -736,7 +736,7 @@ class PaddingFIFOQueueTest(test.TestCase): def dequeue(): for i in xrange(250): - self.assertEqual(i, sess.run(dequeued_t)) + self.assertEqual(i, self.evaluate(dequeued_t)) dequeue_thread = self.checkedThread(target=dequeue) dequeue_thread.start() @@ -767,7 +767,7 @@ class PaddingFIFOQueueTest(test.TestCase): dequeuemany_t = q.dequeue_many(count_placeholder) def enqueue(): - sess.run(enqueue_op) + self.evaluate(enqueue_op) enqueue_thread = self.checkedThread(target=enqueue) enqueue_thread.start() @@ -805,7 +805,7 @@ class PaddingFIFOQueueTest(test.TestCase): # The enqueue_op should run after the dequeue op has blocked. # TODO(mrry): Figure out how to do this without sleeping. time.sleep(0.1) - sess.run(enqueue_op) + self.evaluate(enqueue_op) def dequeue(): dequeued_elems.extend(sess.run(dequeued_t).tolist()) @@ -832,7 +832,7 @@ class PaddingFIFOQueueTest(test.TestCase): # The enqueue_op should run after the dequeue op has blocked. # TODO(mrry): Figure out how to do this without sleeping. time.sleep(0.1) - sess.run(enqueue_op) + self.evaluate(enqueue_op) def dequeue(): dequeued_elems.extend(sess.run(dequeued_t).tolist()) @@ -901,7 +901,7 @@ class PaddingFIFOQueueTest(test.TestCase): def dequeue(): for elem in elems: - self.assertEqual([elem], sess.run(dequeued_t)) + self.assertEqual([elem], self.evaluate(dequeued_t)) # Expect the operation to fail due to the queue being closed. with self.assertRaisesRegexp(errors_impl.OutOfRangeError, "is closed and has insufficient"): @@ -926,8 +926,8 @@ class PaddingFIFOQueueTest(test.TestCase): enqueue_op.run() def dequeue(): - self.assertAllEqual(elems[:3], sess.run(dequeued_t)) - self.assertAllEqual(elems[3:], sess.run(dequeued_t)) + self.assertAllEqual(elems[:3], self.evaluate(dequeued_t)) + self.assertAllEqual(elems[3:], self.evaluate(dequeued_t)) dequeue_thread = self.checkedThread(target=dequeue) dequeue_thread.start() @@ -968,7 +968,7 @@ class PaddingFIFOQueueTest(test.TestCase): enqueue_op.run() def dequeue(): - self.assertAllEqual(elems, sess.run(dequeued_t)) + self.assertAllEqual(elems, self.evaluate(dequeued_t)) # Expect the operation to fail due to the queue being closed. with self.assertRaisesRegexp(errors_impl.OutOfRangeError, "is closed and has insufficient"): @@ -993,7 +993,7 @@ class PaddingFIFOQueueTest(test.TestCase): enqueue_op.run() def dequeue(): - self.assertAllEqual(elems[:3], sess.run(dequeued_t)) + self.assertAllEqual(elems[:3], self.evaluate(dequeued_t)) # Expect the operation to fail due to the queue being closed. with self.assertRaisesRegexp(errors_impl.OutOfRangeError, "is closed and has insufficient"): @@ -1017,16 +1017,16 @@ class PaddingFIFOQueueTest(test.TestCase): cleanup_dequeue_t = q.dequeue() def enqueue(): - sess.run(enqueue_op) + self.evaluate(enqueue_op) def dequeue(): - self.assertAllEqual(elems[0:3], sess.run(dequeued_t)) + self.assertAllEqual(elems[0:3], self.evaluate(dequeued_t)) with self.assertRaises(errors_impl.OutOfRangeError): sess.run(dequeued_t) - self.assertEqual(elems[3], sess.run(cleanup_dequeue_t)) + self.assertEqual(elems[3], self.evaluate(cleanup_dequeue_t)) def close(): - sess.run(close_op) + self.evaluate(close_op) enqueue_thread = self.checkedThread(target=enqueue) enqueue_thread.start() @@ -1155,7 +1155,7 @@ class PaddingFIFOQueueTest(test.TestCase): enqueue_op.run() def blocking_enqueue(): - sess.run(blocking_enqueue_op) + self.evaluate(blocking_enqueue_op) thread = self.checkedThread(target=blocking_enqueue) thread.start() @@ -1178,7 +1178,7 @@ class PaddingFIFOQueueTest(test.TestCase): enqueue_op.run() def blocking_enqueue(): - sess.run(blocking_enqueue_op) + self.evaluate(blocking_enqueue_op) thread = self.checkedThread(target=blocking_enqueue) thread.start() @@ -1207,7 +1207,7 @@ class PaddingFIFOQueueTest(test.TestCase): def blocking_enqueue(): # Expect the operation to succeed once the dequeue op runs. - sess.run(blocking_enqueue_op) + self.evaluate(blocking_enqueue_op) enqueue_thread = self.checkedThread(target=blocking_enqueue) enqueue_thread.start() @@ -1217,7 +1217,7 @@ class PaddingFIFOQueueTest(test.TestCase): time.sleep(0.1) def close(): - sess.run(close_op) + self.evaluate(close_op) close_thread = self.checkedThread(target=close) close_thread.start() @@ -1242,7 +1242,7 @@ class PaddingFIFOQueueTest(test.TestCase): enqueue_op.run() def blocking_enqueue(): - sess.run(blocking_enqueue_op) + self.evaluate(blocking_enqueue_op) enqueue_thread = self.checkedThread(target=blocking_enqueue) enqueue_thread.start() @@ -1252,7 +1252,7 @@ class PaddingFIFOQueueTest(test.TestCase): time.sleep(0.1) def close(): - sess.run(close_op) + self.evaluate(close_op) close_thread = self.checkedThread(target=close) close_thread.start() @@ -1379,19 +1379,19 @@ class PaddingFIFOQueueTest(test.TestCase): def _blockingDequeue(self, sess, dequeue_op): with self.assertRaisesOpError("was cancelled"): - sess.run(dequeue_op) + self.evaluate(dequeue_op) def _blockingDequeueMany(self, sess, dequeue_many_op): with self.assertRaisesOpError("was cancelled"): - sess.run(dequeue_many_op) + self.evaluate(dequeue_many_op) def _blockingEnqueue(self, sess, enqueue_op): with self.assertRaisesOpError("was cancelled"): - sess.run(enqueue_op) + self.evaluate(enqueue_op) def _blockingEnqueueMany(self, sess, enqueue_many_op): with self.assertRaisesOpError("was cancelled"): - sess.run(enqueue_many_op) + self.evaluate(enqueue_many_op) def testResetOfBlockingOperation(self): with self.cached_session() as sess: @@ -1444,14 +1444,14 @@ class PaddingFIFOQueueTest(test.TestCase): results = [] results.append(deq.eval()) # Will only complete after the enqueue starts. self.assertEqual(len(enq_done), 1) - self.assertEqual(sess.run(size_op), 5) + self.assertEqual(self.evaluate(size_op), 5) for _ in range(3): results.append(deq.eval()) time.sleep(0.1) self.assertEqual(len(enq_done), 1) - self.assertEqual(sess.run(size_op), 5) + self.assertEqual(self.evaluate(size_op), 5) # This dequeue will unblock the thread. results.append(deq.eval()) @@ -1517,7 +1517,7 @@ class PaddingFIFOQueueTest(test.TestCase): q.enqueue_many(input_tuple).run() output_tuple_t = q.dequeue_many(32) - output_tuple = sess.run(output_tuple_t) + output_tuple = self.evaluate(output_tuple_t) for (input_elem, output_elem) in zip(input_tuple, output_tuple): self.assertAllEqual(input_elem, output_elem) 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 a84895a287e..3f500872827 100644 --- a/tensorflow/python/kernel_tests/parse_single_example_op_test.py +++ b/tensorflow/python/kernel_tests/parse_single_example_op_test.py @@ -107,7 +107,7 @@ class ParseExampleTest(test.TestCase): for result_dict in [out, out_with_example_name]: result = flatten_values_tensors_or_sparse(result_dict.values()) # Check values. - tf_result = sess.run(result) + tf_result = self.evaluate(result) _compare_output_to_expected(self, result_dict, expected_values, tf_result) diff --git a/tensorflow/python/kernel_tests/parsing_ops_test.py b/tensorflow/python/kernel_tests/parsing_ops_test.py index 8f359bd32cd..d87adbfc2e5 100644 --- a/tensorflow/python/kernel_tests/parsing_ops_test.py +++ b/tensorflow/python/kernel_tests/parsing_ops_test.py @@ -101,7 +101,7 @@ class ParseExampleTest(test.TestCase): out = parsing_ops.parse_example(**kwargs) result = flatten_values_tensors_or_sparse(out.values()) # Check values. - tf_result = sess.run(result) + tf_result = self.evaluate(result) _compare_output_to_expected(self, out, expected_values, tf_result) # Check shapes; if serialized is a Tensor we need its size to @@ -1614,7 +1614,7 @@ class DecodeJSONExampleTest(test.TestCase): shape=examples.shape, dtype=dtypes.string) binary_tensor = parsing_ops.decode_json_example(json_tensor) - binary_val = sess.run(binary_tensor) + binary_val = self.evaluate(binary_tensor) if examples.shape: self.assertShapeEqual(binary_val, json_tensor) diff --git a/tensorflow/python/kernel_tests/pooling_ops_3d_test.py b/tensorflow/python/kernel_tests/pooling_ops_3d_test.py index e393c7a0229..a8e962bc3a6 100644 --- a/tensorflow/python/kernel_tests/pooling_ops_3d_test.py +++ b/tensorflow/python/kernel_tests/pooling_ops_3d_test.py @@ -81,7 +81,7 @@ class PoolingTest(test.TestCase): data_format=data_format) if data_format == "NCDHW": t = test_util.NCHWToNHWC(t) - vals = sess.run(t) + vals = self.evaluate(t) # Verifies values. actual = vals.flatten() self.assertAllClose(expected, actual) diff --git a/tensorflow/python/kernel_tests/priority_queue_test.py b/tensorflow/python/kernel_tests/priority_queue_test.py index 73a9c816382..a510fccaaa5 100644 --- a/tensorflow/python/kernel_tests/priority_queue_test.py +++ b/tensorflow/python/kernel_tests/priority_queue_test.py @@ -50,7 +50,7 @@ class PriorityQueueTest(test.TestCase): enq.run() deq = q.dequeue_many(100) - deq_elem, deq_value_0, deq_value_1 = sess.run(deq) + deq_elem, deq_value_0, deq_value_1 = self.evaluate(deq) allowed = {} missed = set() @@ -81,7 +81,7 @@ class PriorityQueueTest(test.TestCase): # Run one producer thread for each element in elems. def enqueue(enqueue_op): - sess.run(enqueue_op) + self.evaluate(enqueue_op) dequeue_op = q.dequeue_many(100) @@ -93,7 +93,7 @@ class PriorityQueueTest(test.TestCase): for t in enqueue_threads: t.start() - deq_elem, deq_value_0, deq_value_1 = sess.run(dequeue_op) + deq_elem, deq_value_0, deq_value_1 = self.evaluate(dequeue_op) for t in enqueue_threads: t.join() @@ -132,12 +132,12 @@ class PriorityQueueTest(test.TestCase): # Run one producer thread for each element in elems. def enqueue(enqueue_op): - sess.run(enqueue_op) + self.evaluate(enqueue_op) dequeued = [] def dequeue(dequeue_op): - (dequeue_indices, dequeue_values) = sess.run(dequeue_op) + (dequeue_indices, dequeue_values) = self.evaluate(dequeue_op) self.assertAllEqual(dequeue_indices, dequeue_values) dequeued.extend(dequeue_indices) @@ -184,10 +184,10 @@ class PriorityQueueTest(test.TestCase): # Run one producer thread for each element in elems. def enqueue(enqueue_op): - sess.run(enqueue_op) + self.evaluate(enqueue_op) def dequeue(dequeue_op, dequeued): - (dequeue_indices, dequeue_values) = sess.run(dequeue_op) + (dequeue_indices, dequeue_values) = self.evaluate(dequeue_op) self.assertAllEqual(dequeue_indices, dequeue_values) dequeue_wait.acquire() dequeued.extend(dequeue_indices) @@ -236,7 +236,7 @@ class PriorityQueueTest(test.TestCase): # Run one producer thread for each element in elems. def enqueue(enqueue_op): - sess.run(enqueue_op) + self.evaluate(enqueue_op) dequeue_op = q.dequeue_many(100) @@ -248,7 +248,7 @@ class PriorityQueueTest(test.TestCase): for t in enqueue_threads: t.start() - deq_elem, deq_value_0, deq_value_1 = sess.run(dequeue_op) + deq_elem, deq_value_0, deq_value_1 = self.evaluate(dequeue_op) for t in enqueue_threads: t.join() @@ -276,7 +276,7 @@ class PriorityQueueTest(test.TestCase): side_value_1 = np.random.rand(1000).astype(bytes) q.enqueue_many((elem, side_value_0, side_value_1)).run() deq = q.dequeue_many(1000) - deq_elem, deq_value_0, deq_value_1 = sess.run(deq) + deq_elem, deq_value_0, deq_value_1 = self.evaluate(deq) allowed = {} for e, v0, v1 in zip(elem, side_value_0, side_value_1): diff --git a/tensorflow/python/kernel_tests/py_func_test.py b/tensorflow/python/kernel_tests/py_func_test.py index b101da036e6..c9cbe44a7f3 100644 --- a/tensorflow/python/kernel_tests/py_func_test.py +++ b/tensorflow/python/kernel_tests/py_func_test.py @@ -307,9 +307,9 @@ class PyFuncTest(test.TestCase): with session_lib.Session() as sess: producer = iter(range(3)) x, = script_ops.py_func(lambda: next(producer), [], [dtypes.int64]) - self.assertEqual(sess.run(x), 0) - self.assertEqual(sess.run(x), 1) - self.assertEqual(sess.run(x), 2) + self.assertEqual(self.evaluate(x), 0) + self.assertEqual(self.evaluate(x), 1) + self.assertEqual(self.evaluate(x), 2) def testStateless(self): # Not using self.cached_session(), which disables optimization. @@ -317,9 +317,9 @@ class PyFuncTest(test.TestCase): producer = iter(range(3)) x, = script_ops.py_func( lambda: next(producer), [], [dtypes.int64], stateful=False) - self.assertEqual(sess.run(x), 0) - self.assertEqual(sess.run(x), 0) - self.assertEqual(sess.run(x), 0) + self.assertEqual(self.evaluate(x), 0) + self.assertEqual(self.evaluate(x), 0) + self.assertEqual(self.evaluate(x), 0) def testGradientFunction(self): # Input to tf.py_func is necessary, otherwise get_gradient_function() @@ -390,7 +390,7 @@ class PyFuncTest(test.TestCase): f = script_ops.py_func( do_nothing, [constant_op.constant(3, dtypes.int64)], [], stateful=False) with self.cached_session() as sess: - self.assertEqual(sess.run(f), []) + self.assertEqual(self.evaluate(f), []) def _testExceptionHandling(self, py_exp, tf_exp, eager=False): diff --git a/tensorflow/python/kernel_tests/qr_op_test.py b/tensorflow/python/kernel_tests/qr_op_test.py index 617b7242043..114481ed6a0 100644 --- a/tensorflow/python/kernel_tests/qr_op_test.py +++ b/tensorflow/python/kernel_tests/qr_op_test.py @@ -60,7 +60,7 @@ class QrOpTest(test.TestCase): q1, r1 = linalg_ops.qr(matrix1, full_matrices=full_matrices_) q2, r2 = linalg_ops.qr(matrix2, full_matrices=full_matrices_) all_ops += [q1, r1, q2, r2] - val = sess.run(all_ops) + val = self.evaluate(all_ops) for i in range(8): q = 4 * i self.assertAllEqual(val[q], val[q + 2]) # q1 == q2 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 0023506b77a..cab841741e7 100644 --- a/tensorflow/python/kernel_tests/random/multinomial_op_big_test.py +++ b/tensorflow/python/kernel_tests/random/multinomial_op_big_test.py @@ -39,7 +39,7 @@ class MultinomialTest(test.TestCase): num_samples=1000000, seed=15) for _ in range(100): - x = sess.run(samples) + x = self.evaluate(samples) indices, counts = np.unique(x, return_counts=True) for index, count in zip(indices, counts): if index in counts_by_indices.keys(): @@ -57,7 +57,7 @@ class MultinomialTest(test.TestCase): num_samples=1000000, seed=15) for _ in range(100): - x = sess.run(samples) + x = self.evaluate(samples) indices, counts = np.unique(x, return_counts=True) for index, count in zip(indices, counts): if index in counts_by_indices.keys(): @@ -79,7 +79,7 @@ class MultinomialTest(test.TestCase): # we'll run out of memory if we try to draw 1e9 samples directly # really should fit in 12GB of memory... for _ in range(100): - x = sess.run(samples) + x = self.evaluate(samples) indices, counts = np.unique(x, return_counts=True) for index, count in zip(indices, counts): if index in counts_by_indices.keys(): diff --git a/tensorflow/python/kernel_tests/random/multinomial_op_test.py b/tensorflow/python/kernel_tests/random/multinomial_op_test.py index cfec4d08fbe..8d2718c6d54 100644 --- a/tensorflow/python/kernel_tests/random/multinomial_op_test.py +++ b/tensorflow/python/kernel_tests/random/multinomial_op_test.py @@ -70,8 +70,8 @@ class MultinomialTest(test.TestCase): with self.test_session(use_gpu=True) as sess: sample_op1, _ = self._make_ops(10) # Consecutive runs shouldn't yield identical output. - sample1a = sess.run(sample_op1) - sample1b = sess.run(sample_op1) + sample1a = self.evaluate(sample_op1) + sample1b = self.evaluate(sample_op1) self.assertFalse(np.equal(sample1a, sample1b).all()) def testEagerOneOpMultipleStepsIndependent(self): @@ -160,7 +160,7 @@ class MultinomialTest(test.TestCase): with self.test_session(use_gpu=True) as sess: random_seed.set_random_seed(1618) op = sampler(constant_op.constant(logits), num_samples) - d = sess.run(op) + d = self.evaluate(op) batch_size, num_classes = logits.shape freqs_mat = [] @@ -225,8 +225,10 @@ def native_op_vs_composed_ops(batch_size, num_classes, num_samples, num_iters): native_op = control_flow_ops.group(native_sampler(logits, num_samples)) composed_op = control_flow_ops.group(composed_sampler(logits, num_samples)) - native_dt = timeit.timeit(lambda: sess.run(native_op), number=num_iters) - composed_dt = timeit.timeit(lambda: sess.run(composed_op), number=num_iters) + native_dt = timeit.timeit( + lambda: sess.run(native_op), number=num_iters) + composed_dt = timeit.timeit( + lambda: sess.run(composed_op), number=num_iters) return native_dt, composed_dt diff --git a/tensorflow/python/kernel_tests/random/random_gamma_test.py b/tensorflow/python/kernel_tests/random/random_gamma_test.py index 606e8862c47..d18e3feb045 100644 --- a/tensorflow/python/kernel_tests/random/random_gamma_test.py +++ b/tensorflow/python/kernel_tests/random/random_gamma_test.py @@ -48,7 +48,7 @@ class RandomGammaTest(test.TestCase): [num], alpha, beta=beta, dtype=dtype, seed=seed) ret = np.empty([10, num]) for i in xrange(10): - ret[i, :] = sess.run(rng) + ret[i, :] = self.evaluate(rng) return ret return func diff --git a/tensorflow/python/kernel_tests/random/random_ops_test.py b/tensorflow/python/kernel_tests/random/random_ops_test.py index 6de894846bc..76618316b24 100644 --- a/tensorflow/python/kernel_tests/random/random_ops_test.py +++ b/tensorflow/python/kernel_tests/random/random_ops_test.py @@ -49,9 +49,9 @@ class RandomOpTestCommon(test.TestCase): random_seed.set_random_seed(graph_seed) x = rng_func([num], min_or_mean, max_or_stddev, dtype=dtype, seed=op_seed) - y = sess.run(x) - z = sess.run(x) - w = sess.run(x) + y = self.evaluate(x) + z = self.evaluate(x) + w = self.evaluate(x) # We use exact equality here. If the random-number generator is producing # the same output, all three outputs will be bitwise identical. @@ -69,7 +69,7 @@ class RandomNormalTest(RandomOpTestCommon): [num], mean=mu, stddev=sigma, dtype=dtype, seed=seed) ret = np.empty([10, num]) for i in xrange(10): - ret[i, :] = sess.run(rng) + ret[i, :] = self.evaluate(rng) return ret return func @@ -160,7 +160,7 @@ class TruncatedNormalTest(test.TestCase): [num], mean=mu, stddev=sigma, dtype=dtype, seed=seed) ret = np.empty([10, num]) for i in xrange(10): - ret[i, :] = sess.run(rng) + ret[i, :] = self.evaluate(rng) return ret return func @@ -256,7 +256,7 @@ class RandomUniformTest(RandomOpTestCommon): [num], minval=minv, maxval=maxv, dtype=dtype, seed=seed) ret = np.empty([10, num]) for i in xrange(10): - ret[i, :] = sess.run(rng) + ret[i, :] = self.evaluate(rng) return ret return func diff --git a/tensorflow/python/kernel_tests/random/random_poisson_test.py b/tensorflow/python/kernel_tests/random/random_poisson_test.py index 95e48101f6f..47c0858db74 100644 --- a/tensorflow/python/kernel_tests/random/random_poisson_test.py +++ b/tensorflow/python/kernel_tests/random/random_poisson_test.py @@ -43,7 +43,7 @@ class RandomPoissonTest(test.TestCase): rng = random_ops.random_poisson(lam, [num], dtype=dtype, seed=seed) ret = np.empty([10, num]) for i in xrange(10): - ret[i, :] = sess.run(rng) + ret[i, :] = self.evaluate(rng) return ret return func diff --git a/tensorflow/python/kernel_tests/random/random_shuffle_queue_test.py b/tensorflow/python/kernel_tests/random/random_shuffle_queue_test.py index f3fcf1eff7a..5601b9864bd 100644 --- a/tensorflow/python/kernel_tests/random/random_shuffle_queue_test.py +++ b/tensorflow/python/kernel_tests/random/random_shuffle_queue_test.py @@ -84,7 +84,7 @@ class RandomShuffleQueueTest(test.TestCase): dequeue_t = q.dequeue() results = [] for _ in range(2): - a, b = sess.run(dequeue_t) + a, b = self.evaluate(dequeue_t) results.append((a, b)) a, b = sess.run(q.dequeue_many(3)) for i in range(3): @@ -101,7 +101,7 @@ class RandomShuffleQueueTest(test.TestCase): # Run one producer thread for each element in elems. def enqueue(enqueue_op): - sess.run(enqueue_op) + self.evaluate(enqueue_op) threads = [ self.checkedThread( @@ -167,7 +167,7 @@ class RandomShuffleQueueTest(test.TestCase): # TODO(mrry): Figure out how to do this without sleeping. time.sleep(0.1) for enqueue_op in enqueue_ops: - sess.run(enqueue_op) + self.evaluate(enqueue_op) results = [] @@ -197,7 +197,7 @@ class RandomShuffleQueueTest(test.TestCase): results = [] for _ in xrange(len(elems)): - x, y = sess.run(dequeued_t) + x, y = self.evaluate(dequeued_t) results.append((x, y)) self.assertItemsEqual(elems, results) @@ -321,7 +321,7 @@ class RandomShuffleQueueTest(test.TestCase): results = [] for _ in range(8): - float_val, int_val = sess.run(dequeued_t) + float_val, int_val = self.evaluate(dequeued_t) results.append((float_val, [int_val[0], int_val[1]])) expected = list(zip(float_elems, int_elems)) * 2 self.assertItemsEqual(expected, results) @@ -368,20 +368,20 @@ class RandomShuffleQueueTest(test.TestCase): enqueue_op.run() results = [] - float_val, int_val = sess.run(dequeued_t) + float_val, int_val = self.evaluate(dequeued_t) self.assertEqual(float_val.shape, dequeued_t[0].get_shape()) self.assertEqual(int_val.shape, dequeued_t[1].get_shape()) results.extend(zip(float_val, int_val.tolist())) - float_val, int_val = sess.run(dequeued_t) + float_val, int_val = self.evaluate(dequeued_t) results.extend(zip(float_val, int_val.tolist())) - float_val, int_val = sess.run(dequeued_single_t) + float_val, int_val = self.evaluate(dequeued_single_t) self.assertEqual(float_val.shape, dequeued_single_t[0].get_shape()) self.assertEqual(int_val.shape, dequeued_single_t[1].get_shape()) results.append((float_val, int_val.tolist())) - float_val, int_val = sess.run(dequeued_single_t) + float_val, int_val = self.evaluate(dequeued_single_t) results.append((float_val, int_val.tolist())) self.assertItemsEqual(zip(float_elems, int_elems), results) @@ -402,21 +402,21 @@ class RandomShuffleQueueTest(test.TestCase): enqueue_op.run() results = [] - float_val, int_val = sess.run(dequeued_t) + float_val, int_val = self.evaluate(dequeued_t) # dequeue_up_to has undefined shape. self.assertEqual([None], dequeued_t[0].get_shape().as_list()) self.assertEqual([None, 2], dequeued_t[1].get_shape().as_list()) results.extend(zip(float_val, int_val.tolist())) - float_val, int_val = sess.run(dequeued_t) + float_val, int_val = self.evaluate(dequeued_t) results.extend(zip(float_val, int_val.tolist())) - float_val, int_val = sess.run(dequeued_single_t) + float_val, int_val = self.evaluate(dequeued_single_t) self.assertEqual(float_val.shape, dequeued_single_t[0].get_shape()) self.assertEqual(int_val.shape, dequeued_single_t[1].get_shape()) results.append((float_val, int_val.tolist())) - float_val, int_val = sess.run(dequeued_single_t) + float_val, int_val = self.evaluate(dequeued_single_t) results.append((float_val, int_val.tolist())) self.assertItemsEqual(zip(float_elems, int_elems), results) @@ -442,7 +442,7 @@ class RandomShuffleQueueTest(test.TestCase): # Enqueue 100 items in parallel on 10 threads. def enqueue(): - sess.run(enqueue_op) + self.evaluate(enqueue_op) threads = [self.checkedThread(target=enqueue) for _ in range(10)] for thread in threads: @@ -515,7 +515,7 @@ class RandomShuffleQueueTest(test.TestCase): dequeued_elems = [] def dequeue(dequeue_op): - dequeued_elems.extend(sess.run(dequeue_op)) + dequeued_elems.extend(self.evaluate(dequeue_op)) threads = [] for dequeue_op in dequeue_ops: @@ -539,7 +539,7 @@ class RandomShuffleQueueTest(test.TestCase): # The enqueue_op should run after the dequeue op has blocked. # TODO(mrry): Figure out how to do this without sleeping. time.sleep(0.1) - sess.run(enqueue_op) + self.evaluate(enqueue_op) def dequeue(): dequeued_elems.extend(sess.run(dequeued_t).tolist()) @@ -566,7 +566,7 @@ class RandomShuffleQueueTest(test.TestCase): # The enqueue_op should run after the dequeue op has blocked. # TODO(mrry): Figure out how to do this without sleeping. time.sleep(0.1) - sess.run(enqueue_op) + self.evaluate(enqueue_op) def dequeue(): dequeued_elems.extend(sess.run(dequeued_t).tolist()) @@ -727,7 +727,7 @@ class RandomShuffleQueueTest(test.TestCase): progress = [] # Must be mutable def dequeue(): - self.assertItemsEqual(elems, sess.run(dequeued_t)) + self.assertItemsEqual(elems, self.evaluate(dequeued_t)) progress.append(1) # Expect the operation to fail due to the queue being closed. with self.assertRaisesRegexp(errors_impl.OutOfRangeError, @@ -922,7 +922,7 @@ class RandomShuffleQueueTest(test.TestCase): enqueue_op.run() def blocking_enqueue(): - sess.run(blocking_enqueue_op) + self.evaluate(blocking_enqueue_op) thread = self.checkedThread(target=blocking_enqueue) thread.start() @@ -950,7 +950,7 @@ class RandomShuffleQueueTest(test.TestCase): enqueue_op.run() def blocking_enqueue(): - sess.run(blocking_enqueue_op) + self.evaluate(blocking_enqueue_op) thread = self.checkedThread(target=blocking_enqueue) thread.start() @@ -987,11 +987,11 @@ class RandomShuffleQueueTest(test.TestCase): def blocking_enqueue(): # Expect the operation to succeed since it will complete # before the queue is closed. - sess.run(blocking_enqueue_op) + self.evaluate(blocking_enqueue_op) # Expect the operation to fail due to the queue being closed. with self.assertRaisesRegexp(errors_impl.CancelledError, "closed"): - sess.run(blocking_enqueue_op) + self.evaluate(blocking_enqueue_op) thread1 = self.checkedThread(target=blocking_enqueue) thread1.start() @@ -1001,7 +1001,7 @@ class RandomShuffleQueueTest(test.TestCase): time.sleep(0.1) def blocking_close(): - sess.run(close_op) + self.evaluate(close_op) thread2 = self.checkedThread(target=blocking_close) thread2.start() @@ -1032,7 +1032,7 @@ class RandomShuffleQueueTest(test.TestCase): def blocking_enqueue(): # This will block until the dequeue after the close. - sess.run(blocking_enqueue_op) + self.evaluate(blocking_enqueue_op) thread1 = self.checkedThread(target=blocking_enqueue) thread1.start() @@ -1050,7 +1050,7 @@ class RandomShuffleQueueTest(test.TestCase): time.sleep(0.1) def blocking_close(): - sess.run(close_op) + self.evaluate(close_op) thread2 = self.checkedThread(target=blocking_close) thread2.start() @@ -1064,7 +1064,7 @@ class RandomShuffleQueueTest(test.TestCase): # At this point the close operation will complete, so the next enqueue # will fail. with self.assertRaisesRegexp(errors_impl.CancelledError, "closed"): - sess.run(blocking_enqueue_op) + self.evaluate(blocking_enqueue_op) def testSharedQueueSameSession(self): with self.cached_session(): @@ -1216,23 +1216,23 @@ class RandomShuffleQueueTest(test.TestCase): def _blockingDequeue(self, sess, dequeue_op): with self.assertRaisesOpError("was cancelled"): - sess.run(dequeue_op) + self.evaluate(dequeue_op) def _blockingDequeueMany(self, sess, dequeue_many_op): with self.assertRaisesOpError("was cancelled"): - sess.run(dequeue_many_op) + self.evaluate(dequeue_many_op) def _blockingDequeueUpTo(self, sess, dequeue_up_to_op): with self.assertRaisesOpError("was cancelled"): - sess.run(dequeue_up_to_op) + self.evaluate(dequeue_up_to_op) def _blockingEnqueue(self, sess, enqueue_op): with self.assertRaisesOpError("was cancelled"): - sess.run(enqueue_op) + self.evaluate(enqueue_op) def _blockingEnqueueMany(self, sess, enqueue_many_op): with self.assertRaisesOpError("was cancelled"): - sess.run(enqueue_many_op) + self.evaluate(enqueue_many_op) def testResetOfBlockingOperation(self): with self.cached_session() as sess: @@ -1393,14 +1393,14 @@ class RandomShuffleQueueTest(test.TestCase): results = [] results.append(deq.eval()) # Will only complete after the enqueue starts. self.assertEqual(len(enq_done), 1) - self.assertEqual(sess.run(size_op), 5) + self.assertEqual(self.evaluate(size_op), 5) for _ in range(3): results.append(deq.eval()) time.sleep(0.1) self.assertEqual(len(enq_done), 1) - self.assertEqual(sess.run(size_op), 5) + self.assertEqual(self.evaluate(size_op), 5) # This dequeue will unblock the thread. results.append(deq.eval()) diff --git a/tensorflow/python/kernel_tests/reader_ops_test.py b/tensorflow/python/kernel_tests/reader_ops_test.py index 18a8a3d547f..4d9b26f4ebd 100644 --- a/tensorflow/python/kernel_tests/reader_ops_test.py +++ b/tensorflow/python/kernel_tests/reader_ops_test.py @@ -724,7 +724,7 @@ class AsyncReaderTest(test.TestCase): thread_data.append(thread_data_t(t, queue, output)) # Start all readers. They are all blocked waiting for queue entries. - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) for d in thread_data: d.thread.start() diff --git a/tensorflow/python/kernel_tests/record_input_test.py b/tensorflow/python/kernel_tests/record_input_test.py index ebb9872f226..74020667d93 100644 --- a/tensorflow/python/kernel_tests/record_input_test.py +++ b/tensorflow/python/kernel_tests/record_input_test.py @@ -54,7 +54,7 @@ class RecordInputOpTest(test.TestCase): batch_size=1, name="record_input").get_yield_op() - self.assertEqual(sess.run(yield_op), b"0000000000") + self.assertEqual(self.evaluate(yield_op), b"0000000000") def testRecordInputSimpleGzip(self): with self.cached_session() as sess: @@ -73,7 +73,7 @@ class RecordInputOpTest(test.TestCase): compression_type=tf_record.TFRecordCompressionType.GZIP).get_yield_op( ) - self.assertEqual(sess.run(yield_op), b"0000000000") + self.assertEqual(self.evaluate(yield_op), b"0000000000") def testRecordInputSimpleZlib(self): with self.cached_session() as sess: @@ -92,7 +92,7 @@ class RecordInputOpTest(test.TestCase): compression_type=tf_record.TFRecordCompressionType.ZLIB).get_yield_op( ) - self.assertEqual(sess.run(yield_op), b"0000000000") + self.assertEqual(self.evaluate(yield_op), b"0000000000") def testRecordInputEpochs(self): files = 100 @@ -117,7 +117,7 @@ class RecordInputOpTest(test.TestCase): for _ in range(3): epoch_set = set() for _ in range(int(files * records_per_file / batches)): - op_list = sess.run(yield_op) + op_list = self.evaluate(yield_op) self.assertTrue(len(op_list) is batches) for r in op_list: self.assertTrue(r[0] not in epoch_set) @@ -138,15 +138,15 @@ class RecordInputOpTest(test.TestCase): yield_op = records.get_yield_op() for _ in range(50): - sess.run(yield_op) + self.evaluate(yield_op) def testEmptyGlob(self): with self.cached_session() as sess: record_input = data_flow_ops.RecordInput(file_pattern="foo") yield_op = record_input.get_yield_op() - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) with self.assertRaises(NotFoundError): - sess.run(yield_op) + self.evaluate(yield_op) def testBufferTooSmall(self): files = 10 @@ -171,7 +171,7 @@ class RecordInputOpTest(test.TestCase): for _ in range(3): epoch_set = set() for _ in range(int(files * records_per_file / batches)): - op_list = sess.run(yield_op) + op_list = self.evaluate(yield_op) self.assertTrue(len(op_list) is batches) for r in op_list: self.assertTrue(r[0] not in epoch_set) diff --git a/tensorflow/python/kernel_tests/reduction_ops_test.py b/tensorflow/python/kernel_tests/reduction_ops_test.py index d1a295f42b4..612b2c56a55 100644 --- a/tensorflow/python/kernel_tests/reduction_ops_test.py +++ b/tensorflow/python/kernel_tests/reduction_ops_test.py @@ -185,7 +185,7 @@ class SumReductionTest(BaseReductionTest): for dtype in [dtypes.int64, dtypes.int32]: with self.cached_session(use_gpu=True) as sess: v = math_ops.reduce_sum([0, 0], constant_op.constant(0, dtype=dtype)) - tf_v = sess.run(v) + tf_v = self.evaluate(v) self.assertAllEqual(tf_v, 0) def testInfinity(self): @@ -216,7 +216,7 @@ class SumReductionTest(BaseReductionTest): tf_arr = variables.Variable(arr) variables.global_variables_initializer().run() tf_mean = math_ops.reduce_mean(tf_arr, 0, False) - tf_out_mean = sess.run(tf_mean) + tf_out_mean = self.evaluate(tf_mean) self.assertAllClose(tf_out_mean, 1.) def testFloat32(self): @@ -400,7 +400,7 @@ class MeanReductionTest(BaseReductionTest): for dtype in [dtypes.int64, dtypes.int32]: with self.cached_session(use_gpu=True) as sess: v = math_ops.reduce_mean([0, 0], constant_op.constant(0, dtype=dtype)) - tf_v = sess.run(v) + tf_v = self.evaluate(v) self.assertAllEqual(tf_v, 0) def testInfinity(self): @@ -473,7 +473,7 @@ class ProdReductionTest(BaseReductionTest): for dtype in [dtypes.int64, dtypes.int32]: with self.cached_session(use_gpu=True) as sess: v = math_ops.reduce_prod([0, 0], constant_op.constant(0, dtype=dtype)) - tf_v = sess.run(v) + tf_v = self.evaluate(v) self.assertAllEqual(tf_v, 0) def testInfinity(self): @@ -576,7 +576,7 @@ class MinReductionTest(test.TestCase): for dtype in [dtypes.int64, dtypes.int32]: with self.cached_session(use_gpu=True) as sess: v = math_ops.reduce_min([0, 0], constant_op.constant(0, dtype=dtype)) - tf_v = sess.run(v) + tf_v = self.evaluate(v) self.assertAllEqual(tf_v, 0) def testInfinity(self): @@ -689,7 +689,7 @@ class MaxReductionTest(test.TestCase): for dtype in [dtypes.int64, dtypes.int32]: with self.cached_session(use_gpu=True) as sess: v = math_ops.reduce_max([0, 0], constant_op.constant(0, dtype=dtype)) - tf_v = sess.run(v) + tf_v = self.evaluate(v) self.assertAllEqual(tf_v, 0) def testInfinity(self): @@ -817,7 +817,7 @@ class AllReductionTest(test.TestCase): with self.session(use_gpu=True) as sess: v = math_ops.reduce_all([True, True], constant_op.constant(0, dtype=dtype)) - tf_v = sess.run(v) + tf_v = self.evaluate(v) self.assertAllEqual(tf_v, True) def testAll3D(self): @@ -866,7 +866,7 @@ class AnyReductionTest(test.TestCase): with self.session(use_gpu=True) as sess: v = math_ops.reduce_any([True, True], constant_op.constant(0, dtype=dtype)) - tf_v = sess.run(v) + tf_v = self.evaluate(v) self.assertAllEqual(tf_v, True) def testAll3D(self): @@ -962,7 +962,7 @@ class CountNonzeroReductionTest(test.TestCase): # Test case for GitHub issue 18712 with self.cached_session() as sess: v = math_ops.count_nonzero(constant_op.constant(["test"])) - self.assertAllClose(sess.run(v), 1) + self.assertAllClose(self.evaluate(v), 1) def testStringReduce1D(self): # Create a 1D array of strings diff --git a/tensorflow/python/kernel_tests/resource_variable_ops_test.py b/tensorflow/python/kernel_tests/resource_variable_ops_test.py index 45b9ede813e..eedc2d263d7 100644 --- a/tensorflow/python/kernel_tests/resource_variable_ops_test.py +++ b/tensorflow/python/kernel_tests/resource_variable_ops_test.py @@ -153,7 +153,7 @@ class ResourceVariableOpsTest(test_util.TensorFlowTestCase): def testCachedValueReadBeforeWrite(self): with self.cached_session() as sess: v = resource_variable_ops.ResourceVariable(0.0, caching_device="cpu:0") - sess.run(v.initializer) + self.evaluate(v.initializer) value, _ = sess.run([v, v.assign_add(1.0)]) self.assertAllEqual(value, 0.0) diff --git a/tensorflow/python/kernel_tests/scatter_nd_ops_test.py b/tensorflow/python/kernel_tests/scatter_nd_ops_test.py index 952ef34456e..1f1249727c4 100644 --- a/tensorflow/python/kernel_tests/scatter_nd_ops_test.py +++ b/tensorflow/python/kernel_tests/scatter_nd_ops_test.py @@ -162,7 +162,7 @@ class StatefulScatterNdTest(test.TestCase): with self.session(use_gpu=True) as sess: sess.run(init) - result = sess.run(scatter) + result = self.evaluate(scatter) self.assertAllClose(result, expected) def testSimpleResource(self): @@ -190,7 +190,7 @@ class StatefulScatterNdTest(test.TestCase): with self.session(use_gpu=True) as sess: sess.run(init) - result = sess.run(scatter) + result = self.evaluate(scatter) self.assertAllClose(result, expected) def testSimple3(self): @@ -204,7 +204,7 @@ class StatefulScatterNdTest(test.TestCase): with self.session(use_gpu=True) as sess: sess.run(init) - result = sess.run(scatter) + result = self.evaluate(scatter) self.assertAllClose(result, expected) def testVariableRankUpdate(self): @@ -342,7 +342,7 @@ class StatefulScatterNdTest(test.TestCase): with session.Session() as sess: sess.run(init) - result = sess.run(scatter) + result = self.evaluate(scatter) assert np.allclose(result, expected_result) # TODO(fpmc): Re-enable this test when gpu_pip test actually runs on a GPU. @@ -421,7 +421,7 @@ class ScatterNdTest(test.TestCase): b"", b"", b"seven"]) scatter = self.scatter_nd(indices, updates, shape=(8,)) with self.cached_session() as sess: - result = sess.run(scatter) + result = self.evaluate(scatter) self.assertAllEqual(expected, result) # Same indice is updated twice by same value. @@ -432,7 +432,7 @@ class ScatterNdTest(test.TestCase): expected = np.array([b"", b"", b"", b"bb", b"a", b"", b"", b"c"]) scatter = self.scatter_nd(indices, updates, shape=(8,)) with self.cached_session() as sess: - result = sess.run(scatter) + result = self.evaluate(scatter) self.assertAllEqual(expected, result) # Same indice is updated twice by different value. @@ -444,7 +444,7 @@ class ScatterNdTest(test.TestCase): np.array([b"", b"", b"", b"cb", b"a", b"", b"", b"d"])] scatter = self.scatter_nd(indices, updates, shape=(8,)) with self.cached_session() as sess: - result = sess.run(scatter) + result = self.evaluate(scatter) self.assertTrue(np.array_equal(result, expected[0]) or np.array_equal(result, expected[1])) diff --git a/tensorflow/python/kernel_tests/self_adjoint_eig_op_test.py b/tensorflow/python/kernel_tests/self_adjoint_eig_op_test.py index 85756b769d8..8ca8e9dddf5 100644 --- a/tensorflow/python/kernel_tests/self_adjoint_eig_op_test.py +++ b/tensorflow/python/kernel_tests/self_adjoint_eig_op_test.py @@ -63,7 +63,7 @@ class SelfAdjointEigTest(test.TestCase): e1 = linalg_ops.self_adjoint_eigvals(matrix1) e2 = linalg_ops.self_adjoint_eigvals(matrix2) all_ops += [e1, e2] - val = sess.run(all_ops) + val = self.evaluate(all_ops) self.assertAllEqual(val[0], val[2]) # The algorithm is slightly different for compute_v being True and False, # so require approximate equality only here. diff --git a/tensorflow/python/kernel_tests/session_ops_test.py b/tensorflow/python/kernel_tests/session_ops_test.py index 03e1ae852fc..73d85ddc078 100644 --- a/tensorflow/python/kernel_tests/session_ops_test.py +++ b/tensorflow/python/kernel_tests/session_ops_test.py @@ -37,7 +37,7 @@ class SessionOpsTest(test.TestCase): b = constant_op.constant(5) c = math_ops.multiply(a, b) h = session_ops.get_session_handle(c) - h = sess.run(h) + h = self.evaluate(h) # Feed a tensor handle. f, x = session_ops.get_session_tensor(h.handle, dtypes.int32) @@ -51,7 +51,7 @@ class SessionOpsTest(test.TestCase): b = constant_op.constant(5) c = math_ops.multiply(a, b) h = session_ops.get_session_handle(c) - h = sess.run(h) + h = self.evaluate(h) # Get the tensor from its handle. self.assertEqual(50, h.eval()) @@ -94,7 +94,7 @@ class SessionOpsTest(test.TestCase): # Initialize a handle. a = constant_op.constant(0) h = session_ops.get_session_handle(a) - h = sess.run(h) + h = self.evaluate(h) # Do some computation. f, x = session_ops.get_session_tensor(h.handle, dtypes.int32) @@ -111,7 +111,7 @@ class SessionOpsTest(test.TestCase): # Initialize a handle. a = constant_op.constant(0) h = session_ops.get_session_handle(a) - h = sess.run(h) + h = self.evaluate(h) # Do some computation. f, x = session_ops.get_session_tensor(h.handle, dtypes.int32) @@ -133,7 +133,7 @@ class SessionOpsTest(test.TestCase): b = constant_op.constant(5) c = math_ops.multiply(a, b) h = session_ops.get_session_handle(c) - h = sess.run(h) + h = self.evaluate(h) # Feed a tensor handle. f, x = session_ops.get_session_tensor(h.handle, dtypes.int32) @@ -144,7 +144,7 @@ class SessionOpsTest(test.TestCase): with ops.device(test.gpu_device_name()): a = constant_op.constant(10) h = session_ops.get_session_handle(a) - h = sess.run(h) + h = self.evaluate(h) self.assertEqual(100, sess.run(y, feed_dict={f: h.handle})) def testHandleDelete(self): @@ -163,7 +163,7 @@ class SessionOpsTest(test.TestCase): b = constant_op.constant(5) c = math_ops.multiply(a, b) h = session_ops.get_session_handle(c) - h = sess.run(h) + h = self.evaluate(h) # Delete using a raw tensor handle. raw_h = h.get_raw_handle() @@ -219,8 +219,8 @@ class SessionOpsTest(test.TestCase): b = constant_op.constant(2.0) b_handle_op = session_ops.get_session_handle(b) - a_handle = sess.run(a_handle_op) - b_handle = sess.run(b_handle_op) + a_handle = self.evaluate(a_handle_op) + b_handle = self.evaluate(b_handle_op) a_p, a_t = session_ops.get_session_tensor(a_handle.handle, dtypes.float32) b_p, b_t = session_ops.get_session_tensor(b_handle.handle, dtypes.float32) @@ -288,10 +288,10 @@ class SessionOpsTest(test.TestCase): a = variables.Variable(12.0) inc_a = state_ops.assign_add(a, 2.0) b = math_ops.add(a, 5.0) - sess.run(a.initializer) + self.evaluate(a.initializer) h_a_read = sess.run(session_ops.get_session_handle(a.read_value())) - self.assertAllClose(12.0, sess.run(a)) + self.assertAllClose(12.0, self.evaluate(a)) self.assertAllClose(17.0, sess.run(b, feed_dict={a: h_a_read})) sess.run(inc_a) diff --git a/tensorflow/python/kernel_tests/sets_test.py b/tensorflow/python/kernel_tests/sets_test.py index 8335e9c139a..e037f51e0fc 100644 --- a/tensorflow/python/kernel_tests/sets_test.py +++ b/tensorflow/python/kernel_tests/sets_test.py @@ -159,7 +159,7 @@ class SetOpsTest(test_util.TensorFlowTestCase): self.assertEqual(None, op.get_shape().dims) self.assertEqual(dtypes.int32, op.dtype) with self.cached_session() as sess: - results = sess.run(ops) + results = self.evaluate(ops) self.assertAllEqual(results[0], results[1]) return results[0] diff --git a/tensorflow/python/kernel_tests/shape_ops_test.py b/tensorflow/python/kernel_tests/shape_ops_test.py index 3e0eae326bf..a0506fbfc57 100644 --- a/tensorflow/python/kernel_tests/shape_ops_test.py +++ b/tensorflow/python/kernel_tests/shape_ops_test.py @@ -73,8 +73,8 @@ class ShapeOpsTest(test.TestCase): with self.cached_session(use_gpu=use_gpu) as sess: tf_ans = array_ops.shape_n([x, x, x]) tf_ans_64 = array_ops.shape_n([x, x, x], out_type=dtypes.int64) - result = sess.run(tf_ans) - result_64 = sess.run(tf_ans_64) + result = self.evaluate(tf_ans) + result_64 = self.evaluate(tf_ans_64) for i in range(3): self.assertAllEqual(np_ans, result[i]) self.assertAllEqual(np_ans, result_64[i]) diff --git a/tensorflow/python/kernel_tests/signal/reconstruction_ops_test.py b/tensorflow/python/kernel_tests/signal/reconstruction_ops_test.py index c4e5b6f6740..de3351e543c 100644 --- a/tensorflow/python/kernel_tests/signal/reconstruction_ops_test.py +++ b/tensorflow/python/kernel_tests/signal/reconstruction_ops_test.py @@ -56,7 +56,7 @@ class ReconstructionOpsTest(test.TestCase): reconstruction = reconstruction_ops.overlap_and_add(signal, 2) with self.session(use_gpu=True) as sess: - output = sess.run(reconstruction) + output = self.evaluate(reconstruction) expected_output = np.array([1, 1, 2, 2, 3, 2, 2, 1, 1]) @@ -99,7 +99,7 @@ class ReconstructionOpsTest(test.TestCase): reconstruction = reconstruction_ops.overlap_and_add(signal, self.frame_hop) with self.session(use_gpu=True) as sess: - output = sess.run(reconstruction) + output = self.evaluate(reconstruction) string_output = [np.base_repr(x, self.bases[0]) for x in output] self.assertEqual(string_output, self.expected_string) @@ -109,7 +109,7 @@ class ReconstructionOpsTest(test.TestCase): reconstruction = reconstruction_ops.overlap_and_add(signal, self.frame_hop) with self.session(use_gpu=True) as sess: - output = sess.run(reconstruction) + output = self.evaluate(reconstruction) accumulator = True for i in range(self.batch_size): @@ -125,7 +125,7 @@ class ReconstructionOpsTest(test.TestCase): reconstruction = reconstruction_ops.overlap_and_add(signal, self.frame_hop) with self.session(use_gpu=True) as sess: - output = sess.run(reconstruction) + output = self.evaluate(reconstruction) string_output = [np.base_repr(int(x), self.bases[0]) for x in np.squeeze(output)] diff --git a/tensorflow/python/kernel_tests/sparse_add_op_test.py b/tensorflow/python/kernel_tests/sparse_add_op_test.py index a746830afb3..845950bca76 100644 --- a/tensorflow/python/kernel_tests/sparse_add_op_test.py +++ b/tensorflow/python/kernel_tests/sparse_add_op_test.py @@ -91,7 +91,7 @@ class SparseAddTest(test.TestCase): sp_sum = sparse_ops.sparse_add(sp_a, sp_b) self.assertAllEqual((3, 3), sp_sum.get_shape()) - sum_out = sess.run(sp_sum) + sum_out = self.evaluate(sp_sum) self.assertEqual(sp_sum.dense_shape.get_shape(), [2]) self.assertAllEqual(sum_out.indices, [[0, 1], [1, 0], [2, 0], [2, 1]]) @@ -104,7 +104,7 @@ class SparseAddTest(test.TestCase): sp_b = self._SparseTensor_3x3(negate=True) sp_sum = sparse_ops.sparse_add(sp_a, sp_b, 0.1) - sum_out = sess.run(sp_sum) + sum_out = self.evaluate(sp_sum) self.assertEqual(sp_sum.dense_shape.get_shape(), [2]) self.assertAllEqual(sum_out.indices, np.empty([0, 2])) @@ -123,7 +123,7 @@ class SparseAddTest(test.TestCase): # two values should vanish: |.1| < .21, and |-.2| < .21 sp_sum = sparse_ops.sparse_add(sp_a, sp_b, thresh=0.21) - sum_out = sess.run(sp_sum) + sum_out = self.evaluate(sp_sum) self.assertEqual(sp_sum.dense_shape.get_shape(), [2]) self.assertAllEqual(sum_out.indices, [[0, 1], [2, 0]]) @@ -132,7 +132,7 @@ class SparseAddTest(test.TestCase): # only .1 vanishes sp_sum = sparse_ops.sparse_add(sp_a, sp_b, thresh=0.11) - sum_out = sess.run(sp_sum) + sum_out = self.evaluate(sp_sum) self.assertEqual(sp_sum.dense_shape.get_shape(), [2]) self.assertAllEqual(sum_out.indices, [[0, 1], [2, 0], [2, 1]]) diff --git a/tensorflow/python/kernel_tests/sparse_concat_op_test.py b/tensorflow/python/kernel_tests/sparse_concat_op_test.py index 402c5eb4ea3..a3d136c8d51 100644 --- a/tensorflow/python/kernel_tests/sparse_concat_op_test.py +++ b/tensorflow/python/kernel_tests/sparse_concat_op_test.py @@ -147,7 +147,7 @@ class SparseConcatTest(test.TestCase): self.assertEqual(sp_concat.values.get_shape(), [4]) self.assertEqual(sp_concat.dense_shape.get_shape(), [2]) - concat_out = sess.run(sp_concat) + concat_out = self.evaluate(sp_concat) self.assertAllEqual(concat_out.indices, [[0, 2], [1, 0], [2, 0], [2, 2]]) @@ -169,7 +169,7 @@ class SparseConcatTest(test.TestCase): self.assertEqual(sp_concat.values.get_shape(), [8]) self.assertEqual(sp_concat.dense_shape.get_shape(), [2]) - concat_out = sess.run(sp_concat) + concat_out = self.evaluate(sp_concat) self.assertAllEqual(concat_out.indices, [[0, 2], [1, 0], [1, 4], [2, 0], [2, 2], [2, 3], @@ -195,7 +195,7 @@ class SparseConcatTest(test.TestCase): self.assertEqual(sp_concat.values.get_shape(), [7]) self.assertEqual(sp_concat.dense_shape.get_shape(), [2]) - concat_out = sess.run(sp_concat) + concat_out = self.evaluate(sp_concat) self.assertAllEqual( concat_out.indices, @@ -220,7 +220,7 @@ class SparseConcatTest(test.TestCase): self.assertEqual(sp_concat.values.get_shape(), [10]) self.assertEqual(sp_concat.dense_shape.get_shape(), [2]) - concat_out = sess.run(sp_concat) + concat_out = self.evaluate(sp_concat) self.assertAllEqual(concat_out.indices, [[0, 2], [1, 0], [1, 4], [1, 8], [2, 0], [2, 2], [2, 3], [2, 6], @@ -244,7 +244,7 @@ class SparseConcatTest(test.TestCase): self.assertEqual(sp_concat.values.get_shape(), [8]) self.assertEqual(sp_concat.dense_shape.get_shape(), [2]) - concat_out = sess.run(sp_concat) + concat_out = self.evaluate(sp_concat) self.assertAllEqual( concat_out.indices, @@ -302,8 +302,8 @@ class SparseConcatTest(test.TestCase): sp_concat_dim1 = sparse_ops.sparse_concat( concat_dim1, [sp_a, sp_b, sp_c, sp_d], expand_nonconcat_dim=True) - sp_concat_dim0_out = sess.run(sp_concat_dim0) - sp_concat_dim1_out = sess.run(sp_concat_dim1) + sp_concat_dim0_out = self.evaluate(sp_concat_dim0) + sp_concat_dim1_out = self.evaluate(sp_concat_dim1) self.assertAllEqual(sp_concat_dim0_out.indices, [[0, 2], [1, 0], [2, 0], [2, 2], [4, 1], [5, 0], diff --git a/tensorflow/python/kernel_tests/sparse_conditional_accumulator_test.py b/tensorflow/python/kernel_tests/sparse_conditional_accumulator_test.py index a824d5c8263..267275e771e 100644 --- a/tensorflow/python/kernel_tests/sparse_conditional_accumulator_test.py +++ b/tensorflow/python/kernel_tests/sparse_conditional_accumulator_test.py @@ -189,7 +189,7 @@ class IndexedSlicesConditionalAccumulatorTest(test.TestCase): accum_op.run() takeg_t = q.take_indexed_slices_grad(1) - val = sess.run(takeg_t) + val = self.evaluate(takeg_t) self.assertAllEqual([0, 1, 2], val.indices) self.assertAllEqual([[0.5, 0.5], [0, 2], [3, 0]], val.values) self.assertAllEqual([-1, 2], val.dense_shape) @@ -209,7 +209,7 @@ class IndexedSlicesConditionalAccumulatorTest(test.TestCase): accum_op.run() takeg_t = q.take_indexed_slices_grad(1) - val = sess.run(takeg_t) + val = self.evaluate(takeg_t) self.assertAllEqual([0, 1, 2], val.indices) self.assertAllEqual([[1, 1], [0, 2], [3, 0]], val.values) self.assertAllEqual([-1, 2], val.dense_shape) @@ -235,7 +235,7 @@ class IndexedSlicesConditionalAccumulatorTest(test.TestCase): accum_op.run() takeg_t = q.take_indexed_slices_grad(1) - val = sess.run(takeg_t) + val = self.evaluate(takeg_t) self.assertAllEqual(val.indices, [0, 1, 2]) self.assertAllEqual(val.values, [[0.5, 0.5], [0, 2], [3, 0]]) self.assertAllEqual(val.dense_shape, [-1, 2]) @@ -252,7 +252,7 @@ class IndexedSlicesConditionalAccumulatorTest(test.TestCase): accum_op.run() takeg_t = q.take_indexed_slices_grad(1) - val = sess.run(takeg_t) + val = self.evaluate(takeg_t) self.assertAllEqual(val.indices, [0, 1, 2]) self.assertAllEqual(val.values, [[5, 5], [0, 20], [30, 0]]) self.assertAllEqual(val.dense_shape, [-1, 2]) @@ -269,7 +269,7 @@ class IndexedSlicesConditionalAccumulatorTest(test.TestCase): takeg_t = q.take_indexed_slices_grad(1) def apply_indexed_slices_grad(accum_op): - sess.run(accum_op) + self.evaluate(accum_op) threads = [ self.checkedThread( @@ -281,7 +281,7 @@ class IndexedSlicesConditionalAccumulatorTest(test.TestCase): for thread in threads: thread.join() - val = sess.run(takeg_t) + val = self.evaluate(takeg_t) expected_val = sum(elems) / len(elems) self._assertEqual_nparray( @@ -303,7 +303,7 @@ class IndexedSlicesConditionalAccumulatorTest(test.TestCase): takeg_t = q.take_indexed_slices_grad(1) def apply_indexed_slices_grad(accum_op): - sess.run(accum_op) + self.evaluate(accum_op) threads = [ self.checkedThread(target=apply_indexed_slices_grad, args=(o,)) @@ -315,7 +315,7 @@ class IndexedSlicesConditionalAccumulatorTest(test.TestCase): for thread in threads: thread.join() - val = sess.run(takeg_t) + val = self.evaluate(takeg_t) expected_val = 550.0 self._assertEqual_nparray( @@ -338,13 +338,13 @@ class IndexedSlicesConditionalAccumulatorTest(test.TestCase): def apply_indexed_slices_grad(): for accum_op in accum_ops: time.sleep(1.0) - sess.run(accum_op) + self.evaluate(accum_op) apply_indexed_slices_grad_thread = self.checkedThread( target=apply_indexed_slices_grad) def take_grad(): - t = sess.run(takeg_t) + t = self.evaluate(takeg_t) results.append(t) threads = [self.checkedThread(target=take_grad) for _ in range(10)] @@ -378,7 +378,7 @@ class IndexedSlicesConditionalAccumulatorTest(test.TestCase): def apply_indexed_slices_grad(): for accum_op in accum_ops: - sess.run(accum_op) + self.evaluate(accum_op) def take_grad(): results.append(sess.run(takeg_t)) @@ -394,7 +394,7 @@ class IndexedSlicesConditionalAccumulatorTest(test.TestCase): def _blocking_takeg(self, sess, takeg_op): with self.assertRaisesOpError("was cancelled"): - sess.run(takeg_op) + self.evaluate(takeg_op) def testAccumulatorCancel(self): with self.cached_session() as sess: diff --git a/tensorflow/python/kernel_tests/sparse_cross_op_test.py b/tensorflow/python/kernel_tests/sparse_cross_op_test.py index 17e867439a8..8451b96c564 100644 --- a/tensorflow/python/kernel_tests/sparse_cross_op_test.py +++ b/tensorflow/python/kernel_tests/sparse_cross_op_test.py @@ -43,7 +43,7 @@ class SparseCrossOpTest(test.TestCase): 'batch2-FC1-F2_X_batch2-FC2-F1', 'batch2-FC1-F2_X_batch2-FC2-F2' ]]) with self.cached_session() as sess: - self._assert_sparse_tensor_equals(expected_out, sess.run(op)) + self._assert_sparse_tensor_equals(expected_out, self.evaluate(op)) def test_dense(self): """Tests only dense inputs.""" @@ -63,7 +63,7 @@ class SparseCrossOpTest(test.TestCase): 'batch2-FC1-F2_X_batch2-FC2-F1', 'batch2-FC1-F2_X_batch2-FC2-F2' ]]) with self.cached_session() as sess: - self._assert_sparse_tensor_equals(expected_out, sess.run(op)) + self._assert_sparse_tensor_equals(expected_out, self.evaluate(op)) def test_integer_mixed_string_sparse(self): """Tests mixed type.""" @@ -77,7 +77,7 @@ class SparseCrossOpTest(test.TestCase): '55555_X_batch2-FC2-F2' ]]) with self.cached_session() as sess: - self._assert_sparse_tensor_equals(expected_out, sess.run(op)) + self._assert_sparse_tensor_equals(expected_out, self.evaluate(op)) def test_integer_mixed_string_dense(self): """Tests mixed dense inputs.""" @@ -95,7 +95,7 @@ class SparseCrossOpTest(test.TestCase): '999999_X_batch2-FC2-F1', '999999_X_batch2-FC2-F2' ]]) with self.cached_session() as sess: - self._assert_sparse_tensor_equals(expected_out, sess.run(op)) + self._assert_sparse_tensor_equals(expected_out, self.evaluate(op)) def test_sparse_cross_dense(self): """Tests sparse and dense inputs.""" @@ -112,7 +112,7 @@ class SparseCrossOpTest(test.TestCase): 'batch2-FC1-F2_X_batch2-FC2-F1', 'batch2-FC1-F2_X_batch2-FC2-F2' ]]) with self.cached_session() as sess: - self._assert_sparse_tensor_equals(expected_out, sess.run(op)) + self._assert_sparse_tensor_equals(expected_out, self.evaluate(op)) def test_integer_sparse_input(self): """Tests mixed type sparse and dense inputs.""" @@ -128,7 +128,7 @@ class SparseCrossOpTest(test.TestCase): '5555_X_batch2-FC2-F1', '5555_X_batch2-FC2-F2' ]]) with self.cached_session() as sess: - self._assert_sparse_tensor_equals(expected_out, sess.run(op)) + self._assert_sparse_tensor_equals(expected_out, self.evaluate(op)) def test_permutation_3x3x3(self): """Tests 3x3x3 permutation.""" @@ -170,7 +170,7 @@ class SparseCrossOpTest(test.TestCase): 'batch1-FC1-F3_X_batch1-FC2-F3_X_batch1-FC3-F3' ]]) with self.cached_session() as sess: - self._assert_sparse_tensor_equals(expected_out, sess.run(op)) + self._assert_sparse_tensor_equals(expected_out, self.evaluate(op)) def test_permutation_3x1x2(self): """Tests 3x1x2 permutation.""" @@ -189,7 +189,7 @@ class SparseCrossOpTest(test.TestCase): 'batch1-FC1-F3_X_batch1-FC2-F1_X_batch1-FC3-F2' ]]) with self.cached_session() as sess: - self._assert_sparse_tensor_equals(expected_out, sess.run(op)) + self._assert_sparse_tensor_equals(expected_out, self.evaluate(op)) def test_large_batch(self): """Tests with large batch size to force multithreading.""" @@ -222,7 +222,7 @@ class SparseCrossOpTest(test.TestCase): expected_out = self._sparse_tensor(col_out) with self.cached_session() as sess: - self._assert_sparse_tensor_equals(expected_out, sess.run(op)) + self._assert_sparse_tensor_equals(expected_out, self.evaluate(op)) def test_one_column_empty(self): """Tests when one column is empty. @@ -235,7 +235,7 @@ class SparseCrossOpTest(test.TestCase): self._sparse_tensor([['batch1-FC3-F1', 'batch1-FC3-F2']]) ]) with self.cached_session() as sess: - self._assert_sparse_tensor_empty(sess.run(op)) + self._assert_sparse_tensor_empty(self.evaluate(op)) def test_some_columns_empty(self): """Tests when more than one columns are empty. @@ -254,7 +254,7 @@ class SparseCrossOpTest(test.TestCase): 'batch1-FC1-F2_X_batch1-FC2-F1_X_batch1-FC3-F2' ]], 2) with self.cached_session() as sess: - self._assert_sparse_tensor_equals(expected_out, sess.run(op)) + self._assert_sparse_tensor_equals(expected_out, self.evaluate(op)) def test_all_columns_empty(self): """Tests when all columns are empty. @@ -267,7 +267,7 @@ class SparseCrossOpTest(test.TestCase): self._sparse_tensor([]) ]) with self.cached_session() as sess: - self._assert_sparse_tensor_empty(sess.run(op)) + self._assert_sparse_tensor_empty(self.evaluate(op)) def test_hashed_zero_bucket_no_hash_key(self): op = sparse_ops.sparse_cross_hashed([ @@ -278,7 +278,7 @@ class SparseCrossOpTest(test.TestCase): # Check actual hashed output to prevent unintentional hashing changes. expected_out = self._sparse_tensor([[1971693436396284976]]) with self.cached_session() as sess: - self._assert_sparse_tensor_equals(expected_out, sess.run(op)) + self._assert_sparse_tensor_equals(expected_out, self.evaluate(op)) def test_hashed_zero_bucket(self): op = sparse_ops.sparse_cross_hashed( @@ -291,7 +291,7 @@ class SparseCrossOpTest(test.TestCase): # Check actual hashed output to prevent unintentional hashing changes. expected_out = self._sparse_tensor([[4847552627144134031]]) with self.cached_session() as sess: - self._assert_sparse_tensor_equals(expected_out, sess.run(op)) + self._assert_sparse_tensor_equals(expected_out, self.evaluate(op)) # TODO(sibyl-Aix6ihai): Add benchmark to compare Hashed vs Non-hashed. def test_hashed_no_hash_key(self): @@ -305,7 +305,7 @@ class SparseCrossOpTest(test.TestCase): # Check actual hashed output to prevent unintentional hashing changes. expected_out = self._sparse_tensor([[83]]) with self.cached_session() as sess: - self._assert_sparse_tensor_equals(expected_out, sess.run(op)) + self._assert_sparse_tensor_equals(expected_out, self.evaluate(op)) def test_hashed_output(self): op = sparse_ops.sparse_cross_hashed( @@ -319,7 +319,7 @@ class SparseCrossOpTest(test.TestCase): # Check actual hashed output to prevent unintentional hashing changes. expected_out = self._sparse_tensor([[31]]) with self.cached_session() as sess: - self._assert_sparse_tensor_equals(expected_out, sess.run(op)) + self._assert_sparse_tensor_equals(expected_out, self.evaluate(op)) def test_hashed__has_no_collision(self): """Tests that fingerprint concatenation has no collisions.""" @@ -345,7 +345,7 @@ class SparseCrossOpTest(test.TestCase): ], num_buckets=1000) with self.cached_session() as sess: - out = sess.run(op) + out = self.evaluate(op) self.assertEqual(6, len(out.values)) self.assertAllEqual([[0, i] for i in range(6)], out.indices) self.assertTrue(all(x < 1000 and x >= 0 for x in out.values)) diff --git a/tensorflow/python/kernel_tests/sparse_ops_test.py b/tensorflow/python/kernel_tests/sparse_ops_test.py index db3f6c44e22..ad253595d25 100644 --- a/tensorflow/python/kernel_tests/sparse_ops_test.py +++ b/tensorflow/python/kernel_tests/sparse_ops_test.py @@ -154,7 +154,7 @@ class SparseMergeTest(test_util.TensorFlowTestCase): sparse_tensor.SparseTensor.from_value(values_v)): sp_output = sparse_ops.sparse_merge(indices, values, vocab_size) - output = sess.run(sp_output) + output = self.evaluate(sp_output) self._AssertResultsSorted(output, vocab_size) def testInt64AndFloat32(self): @@ -163,7 +163,7 @@ class SparseMergeTest(test_util.TensorFlowTestCase): indices, values = self._SparseTensor_3x50(np.int64, np.float32) sp_output = sparse_ops.sparse_merge(indices, values, vocab_size) - output = sess.run(sp_output) + output = self.evaluate(sp_output) self._AssertResultsSorted(output, vocab_size) def testInt64AndFloat64(self): @@ -172,7 +172,7 @@ class SparseMergeTest(test_util.TensorFlowTestCase): indices, values = self._SparseTensor_3x50(np.int64, np.float64) sp_output = sparse_ops.sparse_merge(indices, values, vocab_size) - output = sess.run(sp_output) + output = self.evaluate(sp_output) self._AssertResultsSorted(output, vocab_size) def testInt32AndFloat32NonCanonicalOrder(self): @@ -182,7 +182,7 @@ class SparseMergeTest(test_util.TensorFlowTestCase): sp_output = sparse_ops.sparse_merge( indices, values, vocab_size, already_sorted=True) - output = sess.run(sp_output) + output = self.evaluate(sp_output) self._AssertResultsNotSorted(output, vocab_size) def testInt64AndFloat32NonCanonicalOrder(self): @@ -192,7 +192,7 @@ class SparseMergeTest(test_util.TensorFlowTestCase): sp_output = sparse_ops.sparse_merge( indices, values, vocab_size, already_sorted=True) - output = sess.run(sp_output) + output = self.evaluate(sp_output) self._AssertResultsNotSorted(output, vocab_size) def testInt64AndFloat64NonCanonicalOrder(self): @@ -203,7 +203,7 @@ class SparseMergeTest(test_util.TensorFlowTestCase): sp_output = sparse_ops.sparse_merge( indices, values, vocab_size_tensor, already_sorted=True) - output = sess.run(sp_output) + output = self.evaluate(sp_output) self._AssertResultsNotSorted(output, vocab_size) def testShouldSetLastDimensionInDynamicShape(self): @@ -261,7 +261,7 @@ class SparseMergeHighDimTest(test_util.TensorFlowTestCase): indices, values = self._SparseTensor_3x50(np.int64, np.float32) sp_output = sparse_ops.sparse_merge(indices, values, vocab_size) - output = sess.run(sp_output) + output = self.evaluate(sp_output) self._AssertResultsSorted(output, vocab_size) def testInt64AndFloat64(self): @@ -270,7 +270,7 @@ class SparseMergeHighDimTest(test_util.TensorFlowTestCase): indices, values = self._SparseTensor_3x50(np.int64, np.float64) sp_output = sparse_ops.sparse_merge(indices, values, vocab_size) - output = sess.run(sp_output) + output = self.evaluate(sp_output) self._AssertResultsSorted(output, vocab_size) def testInt64AndFloat64Shape(self): @@ -279,7 +279,7 @@ class SparseMergeHighDimTest(test_util.TensorFlowTestCase): indices, values = self._SparseTensor_3x50(np.int64, np.float64) sp_output = sparse_ops.sparse_merge(indices, values, vocab_size) - output = sess.run(sp_output) + output = self.evaluate(sp_output) self._AssertResultsSorted(output, vocab_size) @@ -302,7 +302,7 @@ class SparseRetainTest(test_util.TensorFlowTestCase): to_retain = np.array([1, 0, 0, 1, 1, 0], dtype=np.bool) sp_output = sparse_ops.sparse_retain(sp_input, to_retain) - output = sess.run(sp_output) + output = self.evaluate(sp_output) self.assertAllEqual(output.indices, [[0, 0], [1, 4], [3, 2]]) self.assertAllEqual(output.values, [0, 14, 32]) @@ -314,7 +314,7 @@ class SparseRetainTest(test_util.TensorFlowTestCase): to_retain = np.zeros((6,), dtype=np.bool) sp_output = sparse_ops.sparse_retain(sp_input, to_retain) - output = sess.run(sp_output) + output = self.evaluate(sp_output) self.assertAllEqual(output.indices, np.array([]).reshape((0, 2))) self.assertAllEqual(output.values, []) @@ -365,7 +365,7 @@ class SparseResetShapeTest(test_util.TensorFlowTestCase): new_shape = np.array([3, 6, 7], dtype=np.int64) sp_output = sparse_ops.sparse_reset_shape(sp_input, new_shape) - output = sess.run(sp_output) + output = self.evaluate(sp_output) self.assertAllEqual(output.indices, [[0, 0, 0], [0, 1, 0], [0, 1, 3], [1, 1, 4], [1, 3, 2], [1, 3, 3]]) @@ -378,7 +378,7 @@ class SparseResetShapeTest(test_util.TensorFlowTestCase): new_shape = np.array([3, 6, 7], dtype=np.int64) sp_output = sparse_ops.sparse_reset_shape(sp_input, new_shape) - output = sess.run(sp_output) + output = self.evaluate(sp_output) self.assertAllEqual(output.indices, [[0, 0, 0], [0, 1, 0], [0, 1, 3], [1, 1, 4], [1, 3, 2], [1, 3, 3]]) @@ -404,7 +404,7 @@ class SparseResetShapeTest(test_util.TensorFlowTestCase): sp_input = self._SparseTensor_2x5x6() sp_output = sparse_ops.sparse_reset_shape(sp_input) - output = sess.run(sp_output) + output = self.evaluate(sp_output) self.assertAllEqual(output.indices, [[0, 0, 0], [0, 1, 0], [0, 1, 3], [1, 1, 4], [1, 3, 2], [1, 3, 3]]) @@ -416,7 +416,7 @@ class SparseResetShapeTest(test_util.TensorFlowTestCase): sp_input = self._SparseTensor_2x5x6_Empty() sp_output = sparse_ops.sparse_reset_shape(sp_input) - output = sess.run(sp_output) + output = self.evaluate(sp_output) self.assertAllEqual(output.indices.shape, [0, 3]) self.assertAllEqual(output.values.shape, [0]) @@ -591,8 +591,8 @@ class SparseAddTest(test_util.TensorFlowTestCase): sp_output = sparse_ops.sparse_add(sp_input, sp_input) with self.session(use_gpu=False) as sess: - sess.run(variables.global_variables_initializer()) - output = sess.run(sp_output) + self.evaluate(variables.global_variables_initializer()) + output = self.evaluate(sp_output) self.assertAllEqual(output.values, [2]) diff --git a/tensorflow/python/kernel_tests/sparse_reorder_op_test.py b/tensorflow/python/kernel_tests/sparse_reorder_op_test.py index 7b83ae51779..bbf2f392026 100644 --- a/tensorflow/python/kernel_tests/sparse_reorder_op_test.py +++ b/tensorflow/python/kernel_tests/sparse_reorder_op_test.py @@ -60,7 +60,7 @@ class SparseReorderTest(test.TestCase): input_val = self._SparseTensorValue_5x6(np.arange(6)) sp_output = sparse_ops.sparse_reorder(input_val) - output_val = sess.run(sp_output) + output_val = self.evaluate(sp_output) self.assertAllEqual(output_val.indices, input_val.indices) self.assertAllEqual(output_val.values, input_val.values) self.assertAllEqual(output_val.dense_shape, input_val.dense_shape) @@ -83,7 +83,7 @@ class SparseReorderTest(test.TestCase): input_val = self._SparseTensorValue_5x6(np.random.permutation(6)) sp_output = sparse_ops.sparse_reorder(input_val) - output_val = sess.run(sp_output) + output_val = self.evaluate(sp_output) self.assertAllEqual(output_val.indices, expected_output_val.indices) self.assertAllEqual(output_val.values, expected_output_val.values) self.assertAllEqual(output_val.dense_shape, diff --git a/tensorflow/python/kernel_tests/sparse_reshape_op_test.py b/tensorflow/python/kernel_tests/sparse_reshape_op_test.py index f7be397c333..918af27091b 100644 --- a/tensorflow/python/kernel_tests/sparse_reshape_op_test.py +++ b/tensorflow/python/kernel_tests/sparse_reshape_op_test.py @@ -81,7 +81,7 @@ class SparseReshapeTest(test.TestCase): input_val = self._SparseTensorValue_5x6() sp_output = sparse_ops.sparse_reshape(input_val, [5, 6]) - output_val = sess.run(sp_output) + output_val = self.evaluate(sp_output) self.assertAllEqual(output_val.indices, input_val.indices) self.assertAllEqual(output_val.values, input_val.values) self.assertAllEqual(output_val.dense_shape, input_val.dense_shape) @@ -151,7 +151,7 @@ class SparseReshapeTest(test.TestCase): input_val = self._SparseTensorValue_5x6() sp_output = sparse_ops.sparse_reshape(input_val, [2, 3, 5]) - output_val = sess.run(sp_output) + output_val = self.evaluate(sp_output) self.assertAllEqual(output_val.indices, np.array([[0, 0, 0], [0, 1, 1], [0, 1, 4], [0, 2, 0], [1, 1, 0], [1, 1, 1]])) diff --git a/tensorflow/python/kernel_tests/sparse_serialization_ops_test.py b/tensorflow/python/kernel_tests/sparse_serialization_ops_test.py index b24a0869699..39a9ab9b491 100644 --- a/tensorflow/python/kernel_tests/sparse_serialization_ops_test.py +++ b/tensorflow/python/kernel_tests/sparse_serialization_ops_test.py @@ -73,7 +73,7 @@ class SerializeSparseTest(test.TestCase): serialized = serialize_fn(sp_input, out_type=out_type) sp_deserialized = deserialize_fn(serialized, dtype=dtypes.int32) - indices, values, shape = sess.run(sp_deserialized) + indices, values, shape = self.evaluate(sp_deserialized) self.assertAllEqual(indices, sp_input[0]) self.assertAllEqual(values, sp_input[1]) 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 e08464a701c..e63ba8f6970 100644 --- a/tensorflow/python/kernel_tests/sparse_tensors_map_ops_test.py +++ b/tensorflow/python/kernel_tests/sparse_tensors_map_ops_test.py @@ -88,7 +88,7 @@ class SparseTensorsMapTest(test.TestCase): sp_out = take_many_sparse_from_tensors_map( sparse_map_op=handle0.op, sparse_handles=handles_concat) - combined_indices, combined_values, combined_shape = sess.run(sp_out) + combined_indices, combined_values, combined_shape = self.evaluate(sp_out) self.assertAllEqual(combined_indices[:6, 0], [0] * 6) # minibatch 0 self.assertAllEqual(combined_indices[:6, 1:], sp_input0[0]) @@ -114,7 +114,8 @@ class SparseTensorsMapTest(test.TestCase): sp_roundtrip = take_many_sparse_from_tensors_map( sparse_map_op=handle.op, sparse_handles=sparse_handles) - combined_indices, combined_values, combined_shape = sess.run(sp_roundtrip) + combined_indices, combined_values, combined_shape = self.evaluate( + sp_roundtrip) self.assertAllEqual(combined_indices[:6, 0], [0] * 6) # minibatch 0 self.assertAllEqual(combined_indices[:6, 1:], input0_val[0]) @@ -171,7 +172,7 @@ class SparseTensorsMapTest(test.TestCase): with self.session(use_gpu=False) as sess: input_val = self._SparseTensorValue_5x6(np.arange(6)) handle = add_sparse_to_tensors_map(input_val) - handle_value = sess.run(handle) + handle_value = self.evaluate(handle) bad_handle = handle_value + 10 sp_roundtrip = take_many_sparse_from_tensors_map( sparse_map_op=handle.op, sparse_handles=[handle_value, bad_handle]) @@ -212,8 +213,8 @@ class BenchmarkSparseTensorsMapVsSerialization(test.Benchmark): variables.global_variables_initializer().run() - st_roundtrip_values = sess.run(st_roundtrip) - st_deserialized_values = sess.run(st_deserialized) + st_roundtrip_values = self.evaluate(st_roundtrip) + st_deserialized_values = self.evaluate(st_deserialized) np.testing.assert_equal(st_roundtrip_values.values, st_deserialized_values.values) np.testing.assert_equal(st_roundtrip_values.indices, diff --git a/tensorflow/python/kernel_tests/stage_op_test.py b/tensorflow/python/kernel_tests/stage_op_test.py index b814843b86c..b1e7ce5d621 100644 --- a/tensorflow/python/kernel_tests/stage_op_test.py +++ b/tensorflow/python/kernel_tests/stage_op_test.py @@ -152,11 +152,11 @@ class StageTest(test.TestCase): with self.session(use_gpu=True, graph=G) as sess: sess.run(stage, feed_dict={x: -1}) - self.assertEqual(sess.run(size), 1) + self.assertEqual(self.evaluate(size), 1) sess.run(stage, feed_dict={x: -1}) - self.assertEqual(sess.run(size), 2) + self.assertEqual(self.evaluate(size), 2) sess.run(clear) - self.assertEqual(sess.run(size), 0) + self.assertEqual(self.evaluate(size), 0) def testCapacity(self): capacity = 3 @@ -210,14 +210,14 @@ class StageTest(test.TestCase): capacity)) # Should have capacity elements in the staging area - self.assertTrue(sess.run(size) == capacity) + self.assertTrue(self.evaluate(size) == capacity) # Clear the staging area completely for i in range(n): - self.assertTrue(sess.run(ret) == [i]) + self.assertTrue(self.evaluate(ret) == [i]) # It should now be empty - self.assertTrue(sess.run(size) == 0) + self.assertTrue(self.evaluate(size) == 0) def testMemoryLimit(self): memory_limit = 512 * 1024 # 512K @@ -274,13 +274,13 @@ class StageTest(test.TestCase): capacity)) # Should have capacity elements in the staging area - self.assertTrue(sess.run(size) == capacity) + self.assertTrue(self.evaluate(size) == capacity) # Clear the staging area completely for i in range(n): - self.assertTrue(np.all(sess.run(ret)[0] == i)) + self.assertTrue(np.all(self.evaluate(ret)[0] == i)) - self.assertTrue(sess.run(size) == 0) + self.assertTrue(self.evaluate(size) == 0) if __name__ == '__main__': diff --git a/tensorflow/python/kernel_tests/string_length_op_test.py b/tensorflow/python/kernel_tests/string_length_op_test.py index 57db7302b15..0c68f0cadd0 100644 --- a/tensorflow/python/kernel_tests/string_length_op_test.py +++ b/tensorflow/python/kernel_tests/string_length_op_test.py @@ -29,7 +29,7 @@ class StringLengthOpTest(test.TestCase): with self.cached_session() as sess: lengths = string_ops.string_length(strings) - values = sess.run(lengths) + values = self.evaluate(lengths) self.assertAllEqual(values, [[[1, 2], [3, 4], [5, 6]]]) def testUnit(self): diff --git a/tensorflow/python/kernel_tests/string_split_op_test.py b/tensorflow/python/kernel_tests/string_split_op_test.py index b968e885eda..92e13db0f73 100644 --- a/tensorflow/python/kernel_tests/string_split_op_test.py +++ b/tensorflow/python/kernel_tests/string_split_op_test.py @@ -34,7 +34,7 @@ class StringSplitOpTest(test.TestCase): with self.cached_session() as sess: tokens = string_ops.string_split(strings) - indices, values, shape = sess.run(tokens) + indices, values, shape = self.evaluate(tokens) self.assertAllEqual(indices, [[0, 0], [0, 1], [0, 2], [0, 3], [1, 0]]) self.assertAllEqual(values, [b"pigs", b"on", b"the", b"wing", b"animals"]) self.assertAllEqual(shape, [2, 4]) @@ -44,7 +44,7 @@ class StringSplitOpTest(test.TestCase): with self.cached_session() as sess: tokens = string_ops.string_split(strings, delimiter="") - indices, values, shape = sess.run(tokens) + indices, values, shape = self.evaluate(tokens) self.assertAllEqual(indices, [[0, 0], [0, 1], [0, 2], [0, 3], [0, 4], [1, 0], [1, 1], [1, 2], [1, 3], [2, 0], [2, 1], [2, 2], [2, 3]]) @@ -62,7 +62,7 @@ class StringSplitOpTest(test.TestCase): with self.cached_session() as sess: tokens = string_ops.string_split(strings) - indices, values, shape = sess.run(tokens) + indices, values, shape = self.evaluate(tokens) self.assertAllEqual( indices, [[1, 0], [2, 0], [3, 0], [5, 0], [6, 0], [7, 0], [8, 0]]) @@ -74,7 +74,7 @@ class StringSplitOpTest(test.TestCase): with self.cached_session() as sess: tokens = string_ops.string_split(strings, delimiter=" .") - indices, values, shape = sess.run(tokens) + indices, values, shape = self.evaluate(tokens) self.assertAllEqual( indices, [[1, 0], [2, 0], [3, 0], [5, 0], [6, 0], [7, 0], [8, 0]]) @@ -92,13 +92,13 @@ class StringSplitOpTest(test.TestCase): ValueError, string_ops.string_split, strings, delimiter=["a"]) tokens = string_ops.string_split(strings, delimiter="|") - indices, values, shape = sess.run(tokens) + indices, values, shape = self.evaluate(tokens) self.assertAllEqual(indices, [[0, 0], [0, 1], [1, 0]]) self.assertAllEqual(values, [b"hello", b"world", b"hello world"]) self.assertAllEqual(shape, [2, 2]) tokens = string_ops.string_split(strings, delimiter="| ") - indices, values, shape = sess.run(tokens) + indices, values, shape = self.evaluate(tokens) self.assertAllEqual(indices, [[0, 0], [0, 1], [1, 0], [1, 1]]) self.assertAllEqual(values, [b"hello", b"world", b"hello", b"world"]) self.assertAllEqual(shape, [2, 2]) @@ -145,7 +145,7 @@ class StringSplitOpTest(test.TestCase): with self.cached_session() as sess: tokens = string_ops.string_split(strings, "#", skip_empty=False) - indices, values, shape = sess.run(tokens) + indices, values, shape = self.evaluate(tokens) self.assertAllEqual(indices, [[0, 0], [0, 1], [1, 0], [1, 1], [2, 0], [2, 1], [2, 2]]) @@ -154,7 +154,7 @@ class StringSplitOpTest(test.TestCase): with self.cached_session() as sess: tokens = string_ops.string_split(strings, "#") - indices, values, shape = sess.run(tokens) + indices, values, shape = self.evaluate(tokens) self.assertAllEqual(values, [b"a", b"b", b"c"]) self.assertAllEqual(indices, [[0, 0], [1, 0], [2, 0]]) self.assertAllEqual(shape, [3, 1]) @@ -167,7 +167,7 @@ class StringSplitV2OpTest(test.TestCase): with self.cached_session() as sess: tokens = string_ops.string_split_v2(strings) - indices, values, shape = sess.run(tokens) + indices, values, shape = self.evaluate(tokens) self.assertAllEqual(indices, [[0, 0], [0, 1], [0, 2], [0, 3], [1, 0]]) self.assertAllEqual(values, [b"pigs", b"on", b"the", b"wing", b"animals"]) self.assertAllEqual(shape, [2, 4]) @@ -182,7 +182,7 @@ class StringSplitV2OpTest(test.TestCase): with self.cached_session() as sess: tokens = string_ops.string_split_v2(strings, sep="<>") - indices, values, shape = sess.run(tokens) + indices, values, shape = self.evaluate(tokens) self.assertAllEqual( indices, [[0, 0], [0, 1], [0, 2], [1, 0], [1, 1], [1, 2], [1, 3], [1, 4], [1, 5], [1, 6]]) @@ -200,7 +200,7 @@ class StringSplitV2OpTest(test.TestCase): with self.cached_session() as sess: tokens = string_ops.string_split_v2(strings, sep=',') - indices, values, shape = sess.run(tokens) + indices, values, shape = self.evaluate(tokens) self.assertAllEqual(indices, [[0, 0], [0, 1], [0, 2], [1, 0], [1, 1], [1, 2], [1, 3], [1, 4]]) self.assertAllEqual(values, [b"1", b"2", b"3", @@ -217,7 +217,7 @@ class StringSplitV2OpTest(test.TestCase): with self.cached_session() as sess: tokens = string_ops.string_split_v2(strings) - indices, values, shape = sess.run(tokens) + indices, values, shape = self.evaluate(tokens) self.assertAllEqual(indices, [[0, 0], [0, 1], [0, 2], [1, 0], [1, 1], [1, 2]]) self.assertAllEqual(values, [b"1", b"2", b"3", b"4", b"5", b"6"]) @@ -233,7 +233,7 @@ class StringSplitV2OpTest(test.TestCase): with self.cached_session() as sess: tokens = string_ops.string_split_v2(strings, sep=',', maxsplit=1) - indices, values, shape = sess.run(tokens) + indices, values, shape = self.evaluate(tokens) self.assertAllEqual(indices, [[0, 0], [0, 1], [1, 0], [1, 1]]) self.assertAllEqual(values, [b"1", b"2,3", b"4", b"5,,6,"]) @@ -249,7 +249,7 @@ class StringSplitV2OpTest(test.TestCase): with self.cached_session() as sess: tokens = string_ops.string_split_v2(strings, maxsplit=1) - indices, values, shape = sess.run(tokens) + indices, values, shape = self.evaluate(tokens) self.assertAllEqual(indices, [[0, 0], [0, 1], [1, 0], [1, 1]]) self.assertAllEqual(values, [b"1", b"2 3", b"4", b"5 6 "]) diff --git a/tensorflow/python/kernel_tests/string_strip_op_test.py b/tensorflow/python/kernel_tests/string_strip_op_test.py index 1e404b71462..edff3862ff6 100644 --- a/tensorflow/python/kernel_tests/string_strip_op_test.py +++ b/tensorflow/python/kernel_tests/string_strip_op_test.py @@ -30,7 +30,7 @@ class StringStripOpTest(test.TestCase): with self.cached_session() as sess: output = string_ops.string_strip(strings) - output = sess.run(output) + output = self.evaluate(output) self.assertAllEqual(output, [b"pigs on the wing", b"animals"]) def test_string_strip_2d(self): @@ -39,7 +39,7 @@ class StringStripOpTest(test.TestCase): with self.cached_session() as sess: output = string_ops.string_strip(strings) - output = sess.run(output) + output = self.evaluate(output) self.assertAllEqual(output, [[b"pigs on the wing", b"animals"], [b"hello", b"world"]]) @@ -48,7 +48,7 @@ class StringStripOpTest(test.TestCase): with self.cached_session() as sess: output = string_ops.string_strip(strings) - output = sess.run(output) + output = self.evaluate(output) self.assertAllEqual(output, [b"hello", b"", b"world", b""]) diff --git a/tensorflow/python/kernel_tests/summary_v1_audio_op_test.py b/tensorflow/python/kernel_tests/summary_v1_audio_op_test.py index 63ce77b9d55..1547c55f8b0 100644 --- a/tensorflow/python/kernel_tests/summary_v1_audio_op_test.py +++ b/tensorflow/python/kernel_tests/summary_v1_audio_op_test.py @@ -60,7 +60,7 @@ class SummaryV1AudioOpTest(test.TestCase): sample_rate = 8000 summ = summary.audio( "snd", const, max_outputs=3, sample_rate=sample_rate) - value = sess.run(summ) + value = self.evaluate(summ) self.assertEqual([], summ.get_shape()) audio_summ = self._AsSummary(value) 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 094606944ff..e1b24756f3f 100644 --- a/tensorflow/python/kernel_tests/summary_v1_image_op_test.py +++ b/tensorflow/python/kernel_tests/summary_v1_image_op_test.py @@ -70,7 +70,7 @@ class SummaryV1ImageOpTest(test.TestCase): # Summarize summ = summary.image("img", const) - value = sess.run(summ) + value = self.evaluate(summ) self.assertEqual([], summ.get_shape()) image_summ = self._AsSummary(value) @@ -97,7 +97,7 @@ class SummaryV1ImageOpTest(test.TestCase): # Summarize summ = summary.image("img", tf_images) - value = sess.run(summ) + value = self.evaluate(summ) self.assertEqual([], summ.get_shape()) image_summ = self._AsSummary(value) diff --git a/tensorflow/python/kernel_tests/summary_v1_ops_test.py b/tensorflow/python/kernel_tests/summary_v1_ops_test.py index 6c4e106b118..1206cb7013f 100644 --- a/tensorflow/python/kernel_tests/summary_v1_ops_test.py +++ b/tensorflow/python/kernel_tests/summary_v1_ops_test.py @@ -42,7 +42,7 @@ class SummaryV1OpsTest(test.TestCase): with self.cached_session() as sess: const = constant_op.constant([10.0, 20.0]) summ = logging_ops.scalar_summary(["c1", "c2"], const, name="mysumm") - value = sess.run(summ) + value = self.evaluate(summ) self.assertEqual([], summ.get_shape()) self.assertProtoEquals(""" value { tag: "c1" simple_value: 10.0 } @@ -53,7 +53,7 @@ class SummaryV1OpsTest(test.TestCase): with self.cached_session() as sess: const = constant_op.constant([10.0, 20.0]) summ = logging_ops.scalar_summary(["c1", "c2"], const) - value = sess.run(summ) + value = self.evaluate(summ) self.assertEqual([], summ.get_shape()) self.assertProtoEquals(""" value { tag: "c1" simple_value: 10.0 } @@ -66,7 +66,7 @@ class SummaryV1OpsTest(test.TestCase): summ1 = summary.histogram("h", const) summ2 = logging_ops.scalar_summary("c", const) merge = summary.merge([summ1, summ2]) - value = sess.run(merge) + value = self.evaluate(merge) self.assertEqual([], merge.get_shape()) self.assertProtoEquals(""" value { diff --git a/tensorflow/python/kernel_tests/summary_v1_tensor_op_test.py b/tensorflow/python/kernel_tests/summary_v1_tensor_op_test.py index 34f771679ae..71251f5602a 100644 --- a/tensorflow/python/kernel_tests/summary_v1_tensor_op_test.py +++ b/tensorflow/python/kernel_tests/summary_v1_tensor_op_test.py @@ -68,7 +68,7 @@ class SummaryV1TensorOpTest(test.TestCase): with self.cached_session() as sess: const = constant_op.constant(10.0) summ = summary_lib.tensor_summary("foo", const) - result = sess.run(summ) + result = self.evaluate(summ) value = self._SummarySingleValue(result) n = tensor_util.MakeNdarray(value.tensor) @@ -79,7 +79,7 @@ class SummaryV1TensorOpTest(test.TestCase): with self.cached_session() as sess: const = constant_op.constant(s) summ = summary_lib.tensor_summary("foo", const) - result = sess.run(summ) + result = self.evaluate(summ) value = self._SummarySingleValue(result) n = tensor_util.MakeNdarray(value.tensor) @@ -89,7 +89,7 @@ class SummaryV1TensorOpTest(test.TestCase): with self.cached_session() as sess: const = array_ops.ones([5, 5, 5]) summ = summary_lib.tensor_summary("foo", const) - result = sess.run(summ) + result = self.evaluate(summ) value = self._SummarySingleValue(result) n = tensor_util.MakeNdarray(value.tensor) self._AssertNumpyEq(n, np.ones([5, 5, 5])) @@ -99,7 +99,7 @@ class SummaryV1TensorOpTest(test.TestCase): with self.cached_session() as sess: const = constant_op.constant(strings) summ = summary_lib.tensor_summary("foo", const) - result = sess.run(summ) + result = self.evaluate(summ) value = self._SummarySingleValue(result) n = tensor_util.MakeNdarray(value.tensor) self._AssertNumpyEq(n, strings) @@ -109,7 +109,7 @@ class SummaryV1TensorOpTest(test.TestCase): with self.cached_session() as sess: const = constant_op.constant(bools) summ = summary_lib.tensor_summary("foo", const) - result = sess.run(summ) + result = self.evaluate(summ) value = self._SummarySingleValue(result) n = tensor_util.MakeNdarray(value.tensor) @@ -119,7 +119,7 @@ class SummaryV1TensorOpTest(test.TestCase): with self.cached_session() as sess: def get_description(summary_op): - summ_str = sess.run(summary_op) + summ_str = self.evaluate(summary_op) summ = summary_pb2.Summary() summ.ParseFromString(summ_str) return summ.value[0].metadata diff --git a/tensorflow/python/kernel_tests/svd_op_test.py b/tensorflow/python/kernel_tests/svd_op_test.py index 32c97a7b191..589172e4b72 100644 --- a/tensorflow/python/kernel_tests/svd_op_test.py +++ b/tensorflow/python/kernel_tests/svd_op_test.py @@ -68,7 +68,7 @@ class SvdOpTest(test.TestCase): s2 = linalg_ops.svd( matrix2, compute_uv=compute_uv_, full_matrices=full_matrices_) all_ops += [s1, s2] - val = sess.run(all_ops) + val = self.evaluate(all_ops) for i in range(2): s = 6 * i self.assertAllEqual(val[s], val[s + 3]) # s1 == s2 @@ -158,7 +158,7 @@ def _GetSvdOpTest(dtype_, shape_, use_static_shape_, compute_uv_, s_tf = linalg_ops.svd( x_tf, compute_uv=compute_uv_, full_matrices=full_matrices_) if use_static_shape_: - s_tf_val = sess.run(s_tf) + s_tf_val = self.evaluate(s_tf) else: s_tf_val = sess.run(s_tf, feed_dict={x_tf: x_np}) diff --git a/tensorflow/python/kernel_tests/template_test.py b/tensorflow/python/kernel_tests/template_test.py index 9dcdaa61ed2..a187fa115ce 100644 --- a/tensorflow/python/kernel_tests/template_test.py +++ b/tensorflow/python/kernel_tests/template_test.py @@ -104,10 +104,10 @@ class TemplateTest(test.TestCase): train_op = optimizer.minimize(train_loss) with session.Session() as sess: - sess.run(variables.global_variables_initializer()) - initial_test_loss = sess.run(test_loss) - sess.run(train_op) - final_test_loss = sess.run(test_loss) + self.evaluate(variables.global_variables_initializer()) + initial_test_loss = self.evaluate(test_loss) + self.evaluate(train_op) + final_test_loss = self.evaluate(test_loss) # Parameters are tied, so the loss should have gone down when we trained it. self.assertLess(final_test_loss, initial_test_loss) diff --git a/tensorflow/python/kernel_tests/tensor_array_ops_test.py b/tensorflow/python/kernel_tests/tensor_array_ops_test.py index 7e8db8947b9..4ee1c27a87f 100644 --- a/tensorflow/python/kernel_tests/tensor_array_ops_test.py +++ b/tensorflow/python/kernel_tests/tensor_array_ops_test.py @@ -751,7 +751,7 @@ class TensorArrayTest(test.TestCase): [-0.5, 1.5], # read(0) gradient [20.0, 30.0, 40.0, 50.0] ]) # concat gradient - grad_vals = sess.run(grad_r) # 2 + 2 entries + grad_vals = self.evaluate(grad_r) # 2 + 2 entries self.assertAllClose([2.0 - 0.5 + 20.0, 3.0 + 1.5 + 30.0], grad_vals[0]) self.assertAllEqual([4.0 + 40.0, 5.0 + 50.0], grad_vals[1]) @@ -1286,7 +1286,7 @@ class TensorArrayTest(test.TestCase): r = w1.stack() self.assertAllEqual(np.array([1.0, 2.0, 3.0, 4.0]), self.evaluate(r)) grad = gradients_impl.gradients(ys=[r], xs=[x]) - self.assertAllEqual(np.array([1.0, 1.0, 1.0]), sess.run(grad)[0]) + self.assertAllEqual(np.array([1.0, 1.0, 1.0]), self.evaluate(grad)[0]) @test_util.disable_control_flow_v2("b/117943489") def testSkipEagerTensorArrayUnpackDynamic(self): @@ -1303,7 +1303,7 @@ class TensorArrayTest(test.TestCase): r = w1.concat() self.assertAllEqual(np.array([1.0, 2.0, 3.0, 4.0]), self.evaluate(r)) grad = gradients_impl.gradients(ys=[r], xs=[x]) - self.assertAllEqual(np.array([1.0, 1.0, 1.0]), sess.run(grad)[0]) + self.assertAllEqual(np.array([1.0, 1.0, 1.0]), self.evaluate(grad)[0]) def _testTensorArrayEvalEmpty(self): with self.cached_session(use_gpu=True): diff --git a/tensorflow/python/kernel_tests/unicode_transcode_op_test.py b/tensorflow/python/kernel_tests/unicode_transcode_op_test.py index 4ad5ee4103e..d1c7b41c7b1 100644 --- a/tensorflow/python/kernel_tests/unicode_transcode_op_test.py +++ b/tensorflow/python/kernel_tests/unicode_transcode_op_test.py @@ -42,7 +42,7 @@ class UnicodeTranscodeOpTest(test.TestCase, parameterized.TestCase): errors="replace", replacement_char=ord(" "), replace_control_characters=False) - values = sess.run(outputs) + values = self.evaluate(outputs) self.assertAllEqual(values, strings) outputs = string_ops.unicode_transcode( @@ -52,7 +52,7 @@ class UnicodeTranscodeOpTest(test.TestCase, parameterized.TestCase): errors="replace", replacement_char=ord(" "), replace_control_characters=False) - values = sess.run(outputs) + values = self.evaluate(outputs) self.assertAllEqual(values, strings) outputs = string_ops.unicode_transcode( @@ -62,7 +62,7 @@ class UnicodeTranscodeOpTest(test.TestCase, parameterized.TestCase): errors="replace", replacement_char=ord(" "), replace_control_characters=False) - values = sess.run(outputs) + values = self.evaluate(outputs) self.assertAllEqual(values, strings) def test_transcode_utf16_to_utf8(self): @@ -77,7 +77,7 @@ class UnicodeTranscodeOpTest(test.TestCase, parameterized.TestCase): errors="replace", replacement_char=ord(" "), replace_control_characters=False) - values = sess.run(outputs) + values = self.evaluate(outputs) self.assertAllEqual(values, expected) def test_transcode_bad_utf8(self): @@ -90,7 +90,7 @@ class UnicodeTranscodeOpTest(test.TestCase, parameterized.TestCase): errors="replace", replacement_char=ord(" "), replace_control_characters=True) - values = sess.run(outputs) + values = self.evaluate(outputs) self.assertAllEqual(values, b" ") outputs = string_ops.unicode_transcode( @@ -100,7 +100,7 @@ class UnicodeTranscodeOpTest(test.TestCase, parameterized.TestCase): errors="replace", replacement_char=ord(" "), replace_control_characters=False) - values = sess.run(outputs) + values = self.evaluate(outputs) self.assertAllEqual(values, b"\x00 ") def test_transcode_bad_utf8_with_some_good(self): @@ -113,7 +113,7 @@ class UnicodeTranscodeOpTest(test.TestCase, parameterized.TestCase): errors="replace", replacement_char=ord(" "), replace_control_characters=False) - values = sess.run(outputs) + values = self.evaluate(outputs) self.assertAllEqual(values, b"abc abcdefg") def test_transcode_bad_utf8_with_defaults(self): @@ -121,7 +121,7 @@ class UnicodeTranscodeOpTest(test.TestCase, parameterized.TestCase): with self.cached_session() as sess: outputs = string_ops.unicode_transcode( bad_string, input_encoding="UTF-8", output_encoding="UTF-8") - values = sess.run(outputs) + values = self.evaluate(outputs) self.assertAllEqual(values, b"\x00\xef\xbf\xbd") def test_transcode_bad_utf8_with_space_replacement(self): @@ -130,7 +130,7 @@ class UnicodeTranscodeOpTest(test.TestCase, parameterized.TestCase): outputs = string_ops.unicode_transcode( bad_string, input_encoding="UTF-8", output_encoding="UTF-8", replacement_char=ord(" ")) - values = sess.run(outputs) + values = self.evaluate(outputs) self.assertAllEqual(values, b"\x00 ") def test_transcode_bad_utf8_with_strict_errors(self): @@ -165,7 +165,7 @@ class UnicodeTranscodeOpTest(test.TestCase, parameterized.TestCase): input_encoding="UTF-8", output_encoding="UTF-8", errors="ignore") - values = sess.run(outputs) + values = self.evaluate(outputs) self.assertAllEqual(values, b"\x00") def test_transcode_bad_utf8_with_elision_including_control_chars(self): @@ -177,7 +177,7 @@ class UnicodeTranscodeOpTest(test.TestCase, parameterized.TestCase): output_encoding="UTF-8", errors="ignore", replace_control_characters=True) - values = sess.run(outputs) + values = self.evaluate(outputs) self.assertAllEqual(values, b"") def test_transcode_bad_utf8_termination_with_defaults(self): @@ -185,7 +185,7 @@ class UnicodeTranscodeOpTest(test.TestCase, parameterized.TestCase): with self.cached_session() as sess: outputs = string_ops.unicode_transcode( bad_string, input_encoding="UTF-8", output_encoding="UTF-8") - values = sess.run(outputs) + values = self.evaluate(outputs) self.assertAllEqual(values, b"a\xef\xbf\xbd") # 0xFFFD def test_transcode_utf8_with_replacement_char(self): @@ -194,13 +194,13 @@ class UnicodeTranscodeOpTest(test.TestCase, parameterized.TestCase): outputs = string_ops.unicode_transcode( strings, input_encoding="UTF-8", output_encoding="UTF-8", errors="strict") - values = sess.run(outputs) + values = self.evaluate(outputs) self.assertAllEqual(values, [b"a\xef\xbf\xbd"]) outputs = string_ops.unicode_transcode( strings, input_encoding="UTF-8", output_encoding="UTF-8", errors="replace", replacement_char=ord("?")) - values = sess.run(outputs) + values = self.evaluate(outputs) self.assertAllEqual(values, [b"a\xef\xbf\xbd"]) def test_transcode_utf8_to_utf16(self): @@ -214,7 +214,7 @@ class UnicodeTranscodeOpTest(test.TestCase, parameterized.TestCase): output_encoding="UTF-16-BE", replacement_char=ord(" "), replace_control_characters=False) - values = sess.run(outputs) + values = self.evaluate(outputs) print("values=", values) self.assertAllEqual(values, expected) @@ -230,7 +230,7 @@ class UnicodeTranscodeOpTest(test.TestCase, parameterized.TestCase): output_encoding="UTF-8", replacement_char=ord(" "), replace_control_characters=False) - values = sess.run(outputs) + values = self.evaluate(outputs) self.assertAllEqual(values, expected) def test_transcode_utf8_to_utf32(self): @@ -243,7 +243,7 @@ class UnicodeTranscodeOpTest(test.TestCase, parameterized.TestCase): output_encoding="UTF-32-BE", replacement_char=ord(" "), replace_control_characters=False) - values = sess.run(outputs) + values = self.evaluate(outputs) self.assertAllEqual(values, expected) # Documentation in ICU suggests that getNextUChar may produce a different @@ -258,7 +258,7 @@ class UnicodeTranscodeOpTest(test.TestCase, parameterized.TestCase): output_encoding="UTF-8", replacement_char=ord(" "), replace_control_characters=False) - values = sess.run(outputs) + values = self.evaluate(outputs) self.assertAllEqual(values, strings) def test_transcode_utf8_with_bom(self): @@ -266,12 +266,12 @@ class UnicodeTranscodeOpTest(test.TestCase, parameterized.TestCase): with self.cached_session() as sess: outputs = string_ops.unicode_transcode( bom_string, input_encoding="UTF-8", output_encoding="UTF-8") - values = sess.run(outputs) + values = self.evaluate(outputs) self.assertAllEqual(values, b"\xef\xbb\xbfabcdefg") # BOM preserved outputs = string_ops.unicode_transcode( bom_string, input_encoding="UTF-8", output_encoding="UTF-16-BE") - values = sess.run(outputs) + values = self.evaluate(outputs) utf16expected = bom_string.decode("UTF-8").encode("UTF-16-BE") self.assertAllEqual(values, utf16expected) @@ -280,20 +280,20 @@ class UnicodeTranscodeOpTest(test.TestCase, parameterized.TestCase): with self.cached_session() as sess: outputs = string_ops.unicode_transcode( bom_string, input_encoding="UTF-16-BE", output_encoding="UTF-8") - values = sess.run(outputs) + values = self.evaluate(outputs) # BOM is preserved in output self.assertAllEqual(values, b"\xef\xbb\xbfa") outputs = string_ops.unicode_transcode( bom_string, input_encoding="UTF-16-LE", output_encoding="UTF-8") - values = sess.run(outputs) + values = self.evaluate(outputs) # mangled BOM and value from (incorrect) LE encoding self.assertAllEqual(values, b"\xef\xbf\xbe\xe6\x84\x80") bom_string = b"\xff\xfe\x61\x00" # Little-endian BOM with 'a' encoded outputs = string_ops.unicode_transcode( bom_string, input_encoding="UTF-16-LE", output_encoding="UTF-8") - values = sess.run(outputs) + values = self.evaluate(outputs) self.assertAllEqual(values, b"\xef\xbb\xbfa") @parameterized.parameters( diff --git a/tensorflow/python/kernel_tests/variable_scope_test.py b/tensorflow/python/kernel_tests/variable_scope_test.py index 0aac4adfa6e..838838e0ac6 100644 --- a/tensorflow/python/kernel_tests/variable_scope_test.py +++ b/tensorflow/python/kernel_tests/variable_scope_test.py @@ -438,15 +438,15 @@ class VariableScopeTest(test.TestCase): sess.run(v0) # We should be able to initialize and run v1 without initializing # v0, even if the variable was created with a control dep on v0. - sess.run(v1.initializer) - self.assertEqual(1, sess.run(v1)) + self.evaluate(v1.initializer) + self.assertEqual(1, self.evaluate(v1)) # v0 should still be uninitialized. with self.assertRaisesRegexp(errors.OpError, "uninitialized"): sess.run(v0) with self.assertRaisesRegexp(errors.OpError, "uninitialized"): sess.run(add) # If we initialize v0 we should be able to run 'add'. - sess.run(v0.initializer) + self.evaluate(v0.initializer) sess.run(add) # TODO(mihaimaruseac): Not converted to use wrap_function because of @@ -490,10 +490,10 @@ class VariableScopeTest(test.TestCase): v2 = var_dict["v2"] # We should be able to initialize and run v1 and v2 without initializing # v0, even if the variable was created with a control dep on v0. - sess.run(v1.initializer) - self.assertEqual([1], sess.run(v1)) - sess.run(v2.initializer) - self.assertEqual([2], sess.run(v2)) + self.evaluate(v1.initializer) + self.assertEqual([1], self.evaluate(v1)) + self.evaluate(v2.initializer) + self.assertEqual([2], self.evaluate(v2)) # v0 should still be uninitialized. with self.assertRaisesRegexp(errors.OpError, "uninitialized"): sess.run(v0) @@ -501,7 +501,7 @@ class VariableScopeTest(test.TestCase): with self.assertRaisesRegexp(errors.OpError, "uninitialized"): sess.run(add) # If we initialize v0 we should be able to run 'add'. - sess.run(v0.initializer) + self.evaluate(v0.initializer) sess.run(add) # TODO(mihaimaruseac): Not converted to use wrap_function because of diff --git a/tensorflow/python/kernel_tests/variables_test.py b/tensorflow/python/kernel_tests/variables_test.py index 6213f862721..d15801f31bd 100644 --- a/tensorflow/python/kernel_tests/variables_test.py +++ b/tensorflow/python/kernel_tests/variables_test.py @@ -149,10 +149,10 @@ class VariablesTestCase(test.TestCase): name="foo", trainable=False, collections=[ops.GraphKeys.LOCAL_VARIABLES]) - sess.run(variables.local_variables_initializer()) + self.evaluate(variables.local_variables_initializer()) old_value = array.value() copy_op = array.assign(old_value) - self.assertEqual([], list(sess.run(copy_op))) + self.assertEqual([], list(self.evaluate(copy_op))) def _countUpToTest(self, dtype): with self.cached_session(): @@ -221,10 +221,10 @@ class VariablesTestCase(test.TestCase): v2 = var_dict["v2"] # We should be able to initialize and run v1 and v2 without initializing # v0, even if the variable was created with a control dep on v0. - sess.run(v1.initializer) - self.assertEqual([1], sess.run(v1)) - sess.run(v2.initializer) - self.assertEqual([2], sess.run(v2)) + self.evaluate(v1.initializer) + self.assertEqual([1], self.evaluate(v1)) + self.evaluate(v2.initializer) + self.assertEqual([2], self.evaluate(v2)) # v0 should still be uninitialized. with self.assertRaisesRegexp(errors_impl.OpError, "uninitialized"): sess.run(v0) @@ -232,7 +232,7 @@ class VariablesTestCase(test.TestCase): with self.assertRaisesRegexp(errors_impl.OpError, "uninitialized"): sess.run(add) # If we initialize v0 we should be able to run 'add'. - sess.run(v0.initializer) + self.evaluate(v0.initializer) sess.run(add) def testControlFlowInitialization(self): @@ -386,7 +386,7 @@ class VariablesTestCase(test.TestCase): with self.cached_session() as sess: var = variables.Variable([1, 12]) variables.global_variables_initializer().run() - self.assertAllClose([1, 12], sess.run(var)) + self.assertAllClose([1, 12], self.evaluate(var)) def testDevicePlacement(self): with self.cached_session() as sess: @@ -396,7 +396,7 @@ class VariablesTestCase(test.TestCase): init_op = variables.global_variables_initializer() self.assertEqual(var.op.device, init_value.device) self.assertEqual(var.op.device, init_op.device) - sess.run(init_op) + self.evaluate(init_op) def testColocation(self): with ops.device("/job:ps"): @@ -543,7 +543,7 @@ class IsInitializedTest(test.TestCase): def testNoVars(self): with ops.Graph().as_default(), self.cached_session() as sess: uninited = variables.report_uninitialized_variables() - self.assertEqual(0, sess.run(uninited).size) + self.assertEqual(0, self.evaluate(uninited).size) def testAssertVariablesInitialized(self): with ops.Graph().as_default(), self.cached_session() as sess: @@ -551,27 +551,27 @@ class IsInitializedTest(test.TestCase): w = variables.Variable([3, 4], name="w") _ = v, w uninited = variables.report_uninitialized_variables() - self.assertAllEqual(np.array([b"v", b"w"]), sess.run(uninited)) + self.assertAllEqual(np.array([b"v", b"w"]), self.evaluate(uninited)) variables.global_variables_initializer().run() - self.assertEqual(0, sess.run(uninited).size) + self.assertEqual(0, self.evaluate(uninited).size) def testVariableList(self): with ops.Graph().as_default(), self.cached_session() as sess: v = variables.VariableV1([1, 2], name="v") w = variables.VariableV1([3, 4], name="w") uninited = variables.report_uninitialized_variables() - self.assertAllEqual(np.array([b"v", b"w"]), sess.run(uninited)) - sess.run(w.initializer) - self.assertAllEqual(np.array([b"v"]), sess.run(uninited)) + self.assertAllEqual(np.array([b"v", b"w"]), self.evaluate(uninited)) + self.evaluate(w.initializer) + self.assertAllEqual(np.array([b"v"]), self.evaluate(uninited)) v.initializer.run() - self.assertEqual(0, sess.run(uninited).size) + self.assertEqual(0, self.evaluate(uninited).size) def testZeroSizeVarInitialized(self): with ops.Graph().as_default(), self.cached_session() as sess: v = variables.Variable(array_ops.zeros([0, 2]), name="v") uninited = variables.report_uninitialized_variables() v.initializer.run() # not strictly necessary - self.assertEqual(0, sess.run(uninited).size) + self.assertEqual(0, self.evaluate(uninited).size) def testTrainingWithZeroSizeVar(self): with ops.Graph().as_default(), self.cached_session() as sess: @@ -610,7 +610,7 @@ class ObsoleteIsInitializedTest(test.TestCase): inited = variables.assert_variables_initialized([v]) with self.assertRaisesOpError("Attempting to use uninitialized value"): inited.op.run() - sess.run(w.initializer) + self.evaluate(w.initializer) with self.assertRaisesOpError("Attempting to use uninitialized value"): inited.op.run() v.initializer.run() diff --git a/tensorflow/python/kernel_tests/while_v2_test.py b/tensorflow/python/kernel_tests/while_v2_test.py index 0634dfa2d8c..48b32f06aa1 100644 --- a/tensorflow/python/kernel_tests/while_v2_test.py +++ b/tensorflow/python/kernel_tests/while_v2_test.py @@ -48,8 +48,8 @@ class WhileV2Test(test.TestCase, parameterized.TestCase): ret = while_loop_v2(lambda v: v < 8., lambda v: v * v, [x]) grad = gradients_impl.gradients(ret, [x]) with self.cached_session() as sess: - self.assertEqual(sess.run(ret), 16.) - self.assertSequenceEqual(sess.run(grad), [32.]) + self.assertEqual(self.evaluate(ret), 16.) + self.assertSequenceEqual(self.evaluate(grad), [32.]) def testMultipleLoopVarsBasic(self): x = constant_op.constant(5.) @@ -65,8 +65,8 @@ class WhileV2Test(test.TestCase, parameterized.TestCase): # Note: This is simply d_ret[0]/d_x since d_ret[1]/d_x is 0. grad = gradients_impl.gradients(ret, [x]) # [2*x*y] with self.cached_session() as sess: - self.assertSequenceEqual(sess.run(ret), [45., 3.]) - self.assertSequenceEqual(sess.run(grad), [9.]) + self.assertSequenceEqual(self.evaluate(ret), [45., 3.]) + self.assertSequenceEqual(self.evaluate(grad), [9.]) def testMultipleLoopVars(self): x = constant_op.constant(5.) @@ -88,13 +88,13 @@ class WhileV2Test(test.TestCase, parameterized.TestCase): grady_1 = gradients_impl.gradients(ret[1], [y]) # [x + 1] grady_2 = gradients_impl.gradients(ret, [y]) # [2*x*y + x**2 + x + 1] with self.cached_session() as sess: - self.assertSequenceEqual(sess.run(ret), [120., 23.]) - self.assertSequenceEqual(sess.run(gradx_0), [39.]) - self.assertSequenceEqual(sess.run(gradx_1), [4.]) - self.assertSequenceEqual(sess.run(gradx_2), [43.]) - self.assertSequenceEqual(sess.run(grady_0), [55.]) - self.assertSequenceEqual(sess.run(grady_1), [6.]) - self.assertSequenceEqual(sess.run(grady_2), [61.]) + self.assertSequenceEqual(self.evaluate(ret), [120., 23.]) + self.assertSequenceEqual(self.evaluate(gradx_0), [39.]) + self.assertSequenceEqual(self.evaluate(gradx_1), [4.]) + self.assertSequenceEqual(self.evaluate(gradx_2), [43.]) + self.assertSequenceEqual(self.evaluate(grady_0), [55.]) + self.assertSequenceEqual(self.evaluate(grady_1), [6.]) + self.assertSequenceEqual(self.evaluate(grady_2), [61.]) def testMultipleWhileLoops(self): x = constant_op.constant(2.) @@ -103,8 +103,8 @@ class WhileV2Test(test.TestCase, parameterized.TestCase): grad = gradients_impl.gradients(ret2, [x]) # 4x**3 grad_grad = gradients_impl.gradients(grad, [x]) # 12x**2 with self.cached_session() as sess: - self.assertSequenceEqual(sess.run(grad), [32.]) - self.assertSequenceEqual(sess.run(grad_grad), [48.]) + self.assertSequenceEqual(self.evaluate(grad), [32.]) + self.assertSequenceEqual(self.evaluate(grad_grad), [48.]) def testDoubleDerivative(self): x = constant_op.constant(2.) @@ -112,9 +112,9 @@ class WhileV2Test(test.TestCase, parameterized.TestCase): grad = gradients_impl.gradients(ret, [x]) # 4x**3 grad_grad = gradients_impl.gradients(grad, [x]) # 12x**2 with self.cached_session() as sess: - self.assertEqual(sess.run(ret), 16.) - self.assertSequenceEqual(sess.run(grad), [32.]) - self.assertSequenceEqual(sess.run(grad_grad), [48.]) + self.assertEqual(self.evaluate(ret), 16.) + self.assertSequenceEqual(self.evaluate(grad), [32.]) + self.assertSequenceEqual(self.evaluate(grad_grad), [48.]) def testPruning(self): x = constant_op.constant(1) @@ -157,8 +157,8 @@ class WhileV2Test(test.TestCase, parameterized.TestCase): ret = while_loop_v2(lambda v: v + y < 9., lambda v: v * 3., [x]) grad = gradients_impl.gradients(ret, [x]) with self.cached_session() as sess: - self.assertEqual(sess.run(ret), 18.) - self.assertSequenceEqual(sess.run(grad), [9.]) + self.assertEqual(self.evaluate(ret), 18.) + self.assertSequenceEqual(self.evaluate(grad), [9.]) def testCaptureExternalTensorInBody(self): x = constant_op.constant(2.) @@ -166,8 +166,8 @@ class WhileV2Test(test.TestCase, parameterized.TestCase): ret = while_loop_v2(lambda v: v < 8., lambda v: v * y, [x]) grad = gradients_impl.gradients(ret, [x]) with self.cached_session() as sess: - self.assertEqual(sess.run(ret), 18.) - self.assertSequenceEqual(sess.run(grad), [9.]) + self.assertEqual(self.evaluate(ret), 18.) + self.assertSequenceEqual(self.evaluate(grad), [9.]) def testLoopWithTensorListPushBack(self): x = constant_op.constant(2.) @@ -188,7 +188,7 @@ class WhileV2Test(test.TestCase, parameterized.TestCase): grad = gradients_impl.gradients(ret[0], x) with self.cached_session() as sess: self.assertEqual(sess.run(ret[0]), 16.) - self.assertSequenceEqual(sess.run(grad), [32.]) + self.assertSequenceEqual(self.evaluate(grad), [32.]) def testDuplicateAccumulator(self): x = constant_op.constant(2.) @@ -222,7 +222,7 @@ class WhileV2Test(test.TestCase, parameterized.TestCase): grad = gradients_impl.gradients(ret[0], x) with self.cached_session() as sess: self.assertEqual(sess.run(ret[0]), 16.) - self.assertSequenceEqual(sess.run(grad), [32.]) + self.assertSequenceEqual(self.evaluate(grad), [32.]) @parameterized.named_parameters( ("UnknownShape", None), @@ -315,9 +315,9 @@ class WhileV2Test(test.TestCase, parameterized.TestCase): y0 = constant_op.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], name="elems") # map_fn uses TensorArray internally. r = functional_ops.map_fn(lambda x: math_ops.multiply(x, param), y0) - self.assertAllClose([2.0, 4.0, 6.0, 8.0, 10.0, 12.0], sess.run(r)) + self.assertAllClose([2.0, 4.0, 6.0, 8.0, 10.0, 12.0], self.evaluate(r)) r = gradients_impl.gradients(r, param)[0] - self.assertAllClose(21.0, sess.run(r)) + self.assertAllClose(21.0, self.evaluate(r)) def testNestedWhile(self): # Compute sum of geometric progression: n^0 + n^1 + ... + n^m @@ -334,8 +334,8 @@ class WhileV2Test(test.TestCase, parameterized.TestCase): result = while_loop_v2(lambda i, _: i >= 0, Body, [m, sum_of_powers])[1] grad = gradients_impl.gradients(result, [n]) with self.cached_session() as sess: - self.assertEqual(sess.run(result), 364.) - self.assertSequenceEqual(sess.run(grad), [547.]) + self.assertEqual(self.evaluate(result), 364.) + self.assertSequenceEqual(self.evaluate(grad), [547.]) def testIdentityNodeInBody(self): @@ -348,8 +348,8 @@ class WhileV2Test(test.TestCase, parameterized.TestCase): ret = while_loop_v2(lambda v: v < 8., Body, [x]) grad = gradients_impl.gradients(ret, [x]) with self.cached_session() as sess: - self.assertEqual(sess.run(ret), 16.) - self.assertSequenceEqual(sess.run(grad), [32.]) + self.assertEqual(self.evaluate(ret), 16.) + self.assertSequenceEqual(self.evaluate(grad), [32.]) 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 c3c7f867a1e..bd3142132c7 100644 --- a/tensorflow/python/kernel_tests/xent_op_test.py +++ b/tensorflow/python/kernel_tests/xent_op_test.py @@ -65,7 +65,7 @@ class XentTest(test.TestCase): with self.cached_session(use_gpu=use_gpu) as sess: loss = nn_ops.softmax_cross_entropy_with_logits( labels=np_labels, logits=np_features, dim=dim) - tf_loss = sess.run(loss) + tf_loss = self.evaluate(loss) print("np_loss:", np_loss) print("tf_loss:", tf_loss) self.assertAllCloseAccordingToType(np_loss, tf_loss) @@ -280,7 +280,7 @@ class XentTest(test.TestCase): with self.session(use_gpu=True) as sess: loss = nn_ops.softmax_cross_entropy_with_logits( labels=labels, logits=features) - tf_loss = sess.run(loss) + tf_loss = self.evaluate(loss) self.assertAllEqual(np_loss, tf_loss) diff --git a/tensorflow/python/layers/convolutional_test.py b/tensorflow/python/layers/convolutional_test.py index 257fa271567..d3200fa5b57 100644 --- a/tensorflow/python/layers/convolutional_test.py +++ b/tensorflow/python/layers/convolutional_test.py @@ -276,8 +276,8 @@ class ConvTest(test.TestCase): # Check the names of weights in order. self.assertTrue('kernel' in weights[0].name) self.assertTrue('bias' in weights[1].name) - sess.run(variables.global_variables_initializer()) - weights = sess.run(weights) + self.evaluate(variables.global_variables_initializer()) + weights = self.evaluate(weights) # Check that the kernel weights got initialized to ones (from scope) self.assertAllClose(weights[0], np.ones((3, 3, 3, 32))) # Check that the bias still got initialized to zeros. @@ -663,8 +663,8 @@ class SeparableConv2DTest(test.TestCase): self.assertTrue('depthwise_kernel' in weights[0].name) self.assertTrue('pointwise_kernel' in weights[1].name) self.assertTrue('bias' in weights[2].name) - sess.run(variables.global_variables_initializer()) - weights = sess.run(weights) + self.evaluate(variables.global_variables_initializer()) + weights = self.evaluate(weights) # Check that the kernel weights got initialized to ones (from scope) self.assertAllClose(weights[0], np.ones((3, 3, 3, 1))) self.assertAllClose(weights[1], np.ones((1, 1, 3, 32))) @@ -902,8 +902,8 @@ class Conv2DTransposeTest(test.TestCase): # Check the names of weights in order. self.assertTrue('kernel' in weights[0].name) self.assertTrue('bias' in weights[1].name) - sess.run(variables.global_variables_initializer()) - weights = sess.run(weights) + self.evaluate(variables.global_variables_initializer()) + weights = self.evaluate(weights) # Check that the kernel weights got initialized to ones (from scope) self.assertAllClose(weights[0], np.ones((3, 3, 32, 3))) # Check that the bias still got initialized to zeros. @@ -1084,8 +1084,8 @@ class Conv3DTransposeTest(test.TestCase): # Check the names of weights in order. self.assertTrue('kernel' in weights[0].name) self.assertTrue('bias' in weights[1].name) - sess.run(variables.global_variables_initializer()) - weights = sess.run(weights) + self.evaluate(variables.global_variables_initializer()) + weights = self.evaluate(weights) # Check that the kernel weights got initialized to ones (from scope) self.assertAllClose(weights[0], np.ones((3, 3, 3, 4, 32))) # Check that the bias still got initialized to zeros. diff --git a/tensorflow/python/layers/core_test.py b/tensorflow/python/layers/core_test.py index 0343bfa8bd2..a61639b2db8 100644 --- a/tensorflow/python/layers/core_test.py +++ b/tensorflow/python/layers/core_test.py @@ -443,7 +443,7 @@ class DropoutTest(test.TestCase): dp = core_layers.Dropout(rate, name='dropout') inputs = array_ops.ones((5, 5)) dropped = dp.apply(inputs, training=True) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) np_output = sess.run(dropped, feed_dict={rate: 0.5}) self.assertAlmostEqual(0., np_output.min()) np_output = sess.run(dropped, feed_dict={rate: 0.0}) diff --git a/tensorflow/python/layers/normalization_test.py b/tensorflow/python/layers/normalization_test.py index ba2bf10cf3a..febc3587fe9 100644 --- a/tensorflow/python/layers/normalization_test.py +++ b/tensorflow/python/layers/normalization_test.py @@ -78,7 +78,7 @@ class BNTest(test.TestCase): if restore: saver.restore(sess, checkpoint_path) else: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) np.random.seed(0) for _ in range(2): image_val = np.random.rand(*shape).astype(dtype.as_numpy_dtype) @@ -321,7 +321,7 @@ class BNTest(test.TestCase): with self.cached_session() as sess: # Test training with placeholder learning phase. - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) np_gamma, np_beta = sess.run([bn.gamma, bn.beta]) np_gamma = np.reshape(np_gamma, (1, 4, 1)) @@ -337,7 +337,7 @@ class BNTest(test.TestCase): # Verify that the statistics are updated during training. moving_mean, moving_var = sess.run([bn.moving_mean, bn.moving_variance]) - np_inputs = sess.run(inputs) + np_inputs = self.evaluate(inputs) mean = np.mean(np_inputs, axis=(0, 2)) std = np.std(np_inputs, axis=(0, 2)) variance = np.square(std) @@ -363,7 +363,7 @@ class BNTest(test.TestCase): with self.cached_session() as sess: # Test training with placeholder learning phase. - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) np_gamma, np_beta = sess.run([bn.gamma, bn.beta]) np_gamma = np.reshape(np_gamma, (1, 1, 3)) np_beta = np.reshape(np_beta, (1, 1, 3)) @@ -377,7 +377,7 @@ class BNTest(test.TestCase): # Verify that the statistics are updated during training. moving_mean, moving_var = sess.run([bn.moving_mean, bn.moving_variance]) - np_inputs = sess.run(inputs) + np_inputs = self.evaluate(inputs) mean = np.mean(np_inputs, axis=(0, 1)) std = np.std(np_inputs, axis=(0, 1)) variance = np.square(std) @@ -404,7 +404,7 @@ class BNTest(test.TestCase): with self.session(use_gpu=True) as sess: # Test training with placeholder learning phase. - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) np_gamma, np_beta = sess.run([bn.gamma, bn.beta]) np_gamma = np.reshape(np_gamma, (1, 4, 1, 1)) np_beta = np.reshape(np_beta, (1, 4, 1, 1)) @@ -418,7 +418,7 @@ class BNTest(test.TestCase): # Verify that the statistics are updated during training. moving_mean, moving_var = sess.run([bn.moving_mean, bn.moving_variance]) - np_inputs = sess.run(inputs) + np_inputs = self.evaluate(inputs) mean = np.mean(np_inputs, axis=(0, 2, 3)) std = np.std(np_inputs, axis=(0, 2, 3)) variance = np.square(std) @@ -444,7 +444,7 @@ class BNTest(test.TestCase): with self.cached_session() as sess: # Test training with placeholder learning phase. - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) np_gamma, np_beta = sess.run([bn.gamma, bn.beta]) np_gamma = np.reshape(np_gamma, (1, 1, 3, 1)) np_beta = np.reshape(np_beta, (1, 1, 3, 1)) @@ -458,7 +458,7 @@ class BNTest(test.TestCase): # Verify that the statistics are updated during training. moving_mean, moving_var = sess.run([bn.moving_mean, bn.moving_variance]) - np_inputs = sess.run(inputs) + np_inputs = self.evaluate(inputs) mean = np.mean(np_inputs, axis=(0, 1, 3)) std = np.std(np_inputs, axis=(0, 1, 3)) variance = np.square(std) @@ -484,7 +484,7 @@ class BNTest(test.TestCase): with self.cached_session() as sess: # Test training with placeholder learning phase. - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) np_gamma, np_beta = sess.run([bn.gamma, bn.beta]) np_gamma = np.reshape(np_gamma, (1, 1, 1, 6)) np_beta = np.reshape(np_beta, (1, 1, 1, 6)) @@ -498,7 +498,7 @@ class BNTest(test.TestCase): # Verify that the statistics are updated during training. moving_mean, moving_var = sess.run([bn.moving_mean, bn.moving_variance]) - np_inputs = sess.run(inputs) + np_inputs = self.evaluate(inputs) mean = np.mean(np_inputs, axis=(0, 1, 2)) std = np.std(np_inputs, axis=(0, 1, 2)) variance = np.square(std) @@ -524,7 +524,7 @@ class BNTest(test.TestCase): with self.cached_session() as sess: # Test training with placeholder learning phase. - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) np_gamma, np_beta = sess.run([bn.gamma, bn.beta]) np_gamma = np.reshape(np_gamma, (1, 1, 1, 6)) np_beta = np.reshape(np_beta, (1, 1, 1, 6)) @@ -538,7 +538,7 @@ class BNTest(test.TestCase): # Verify that the statistics are updated during training. moving_mean, moving_var = sess.run([bn.moving_mean, bn.moving_variance]) - np_inputs = sess.run(inputs) + np_inputs = self.evaluate(inputs) mean = np.mean(np_inputs, axis=(0, 1, 2)) std = np.std(np_inputs, axis=(0, 1, 2)) variance = np.square(std) @@ -565,7 +565,7 @@ class BNTest(test.TestCase): with self.cached_session() as sess: # Test training with placeholder learning phase. - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) np_gamma, np_beta = sess.run([bn.gamma, bn.beta]) np_gamma = np.reshape(np_gamma, (1, 4, 1, 1)) np_beta = np.reshape(np_beta, (1, 4, 1, 1)) @@ -579,7 +579,7 @@ class BNTest(test.TestCase): # Verify that the statistics are updated during training. moving_mean, moving_var = sess.run([bn.moving_mean, bn.moving_variance]) - np_inputs = sess.run(inputs) + np_inputs = self.evaluate(inputs) mean = np.mean(np_inputs, axis=(0, 2, 3)) std = np.std(np_inputs, axis=(0, 2, 3)) variance = np.square(std) @@ -605,7 +605,7 @@ class BNTest(test.TestCase): with self.cached_session() as sess: # Test training with placeholder learning phase. - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) np_gamma, np_beta = sess.run([bn.gamma, bn.beta]) np_gamma = np.reshape(np_gamma, (1, 1, 1, 6)) np_beta = np.reshape(np_beta, (1, 1, 1, 6)) @@ -620,7 +620,7 @@ class BNTest(test.TestCase): # Verify that the statistics are updated during training. moving_mean, moving_var = sess.run([bn.moving_mean, bn.moving_variance]) - np_inputs = sess.run(inputs) + np_inputs = self.evaluate(inputs) mean = np.mean(np_inputs, axis=(0, 1, 2)) std = np.std(np_inputs, axis=(0, 1, 2)) variance = np.square(std) @@ -646,7 +646,7 @@ class BNTest(test.TestCase): with self.cached_session() as sess: # Test training with placeholder learning phase. - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) np_gamma, np_beta = sess.run([bn.gamma, bn.beta]) np_gamma = np.reshape(np_gamma, (1, 1, 1, 6)) np_beta = np.reshape(np_beta, (1, 1, 1, 6)) @@ -659,7 +659,7 @@ class BNTest(test.TestCase): # Verify that the statistics are updated during training. moving_mean, moving_var = sess.run([bn.moving_mean, bn.moving_variance]) - np_inputs = sess.run(inputs) + np_inputs = self.evaluate(inputs) mean = np.mean(np_inputs, axis=(0, 1, 2)) std = np.std(np_inputs, axis=(0, 1, 2)) variance = np.square(std) @@ -667,7 +667,7 @@ class BNTest(test.TestCase): self.assertAllClose(variance, moving_var, atol=1e-2) # Test inference with placeholder learning phase. - np_output = sess.run(outputs_infer) + np_output = self.evaluate(outputs_infer) # Verify that the axis is normalized during inference. normed_np_output = ((np_output - epsilon) * np_gamma) + np_beta @@ -696,7 +696,7 @@ class BNTest(test.TestCase): with self.cached_session() as sess: # Test training with placeholder learning phase. - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) np_gamma, np_beta = sess.run([gamma, beta]) np_gamma = np.reshape(np_gamma, (1, 1, 1, 6)) np_beta = np.reshape(np_beta, (1, 1, 1, 6)) @@ -710,7 +710,7 @@ class BNTest(test.TestCase): # Verify that the statistics are updated during training. np_moving_mean, np_moving_var = sess.run([moving_mean, moving_variance]) - np_inputs = sess.run(inputs) + np_inputs = self.evaluate(inputs) np_mean = np.mean(np_inputs, axis=(0, 1, 2)) np_std = np.std(np_inputs, axis=(0, 1, 2)) np_variance = np.square(np_std) @@ -758,14 +758,14 @@ class BNTest(test.TestCase): with self.cached_session() as sess: # Test training with placeholder learning phase. - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) for _ in range(100): np_output, _, _ = sess.run([outputs2] + updates, feed_dict={training: True}) # Verify that the statistics are updated during training. np_moving_mean, np_moving_var = sess.run([moving_mean, moving_variance]) - np_inputs = sess.run(inputs2) + np_inputs = self.evaluate(inputs2) np_mean = np.mean(np_inputs, axis=(0, 1, 2)) np_std = np.std(np_inputs, axis=(0, 1, 2)) np_variance = np.square(np_std) @@ -885,7 +885,7 @@ class BNTest(test.TestCase): renorm_mean = renorm_stddev = 0. renorm_weight = 0. with self.session(use_gpu=True) as sess: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) for _ in range(5): x = np.random.random(shape) @@ -937,7 +937,7 @@ class BNTest(test.TestCase): moving_mean = 0. moving_variance = 1. with self.session(use_gpu=True) as sess: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) for _ in range(5): x = np.random.random(shape) yt_val_train, adj_scale_val, adj_bias_val = sess.run( @@ -990,7 +990,7 @@ class BNTest(test.TestCase): renorm_mean = renorm_stddev = 0. renorm_weight = 0. with self.session(use_gpu=True) as sess: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) for _ in range(5): x = np.random.random(shape) yt_val_train, adj_scale_val, adj_bias_val = sess.run( @@ -1040,7 +1040,7 @@ class BNTest(test.TestCase): out1.shape.as_list(), out2.shape.as_list()) with self.session(use_gpu=True) as sess: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) x = np.random.random(shape) y1, y2 = sess.run([out1, out2], feed_dict={inp: x}) @@ -1062,7 +1062,7 @@ class BNTest(test.TestCase): inp, virtual_batch_size=2) with self.session(use_gpu=True) as sess: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) x = np.random.random(np_shape) y = sess.run(out, feed_dict={inp: x}) @@ -1093,7 +1093,7 @@ class BNTest(test.TestCase): shape[1]]) with self.session(use_gpu=True) as sess: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) for _ in range(5): x = np.random.random(shape) @@ -1146,7 +1146,7 @@ class BNTest(test.TestCase): shape[1:]) with self.session(use_gpu=True) as sess: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) for _ in range(5): x = np.random.random(shape) @@ -1200,7 +1200,7 @@ class BNTest(test.TestCase): shape[1:]) with self.session(use_gpu=True) as sess: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) for _ in range(5): x = np.random.random(shape) @@ -1256,7 +1256,7 @@ class BNTest(test.TestCase): with self.cached_session() as sess: # Test training with placeholder learning phase. - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) np_gamma, np_beta = sess.run([bn.gamma, bn.beta]) @@ -1270,7 +1270,7 @@ class BNTest(test.TestCase): # Verify that the statistics are updated during training. moving_mean, moving_var = sess.run([bn.moving_mean, bn.moving_variance]) - np_inputs = sess.run(inputs) + np_inputs = self.evaluate(inputs) mean = np.mean(np_inputs, axis=0, keepdims=True) std = np.std(np_inputs, axis=0, keepdims=True) variance = np.square(std) @@ -1296,7 +1296,7 @@ class BNTest(test.TestCase): with self.cached_session() as sess: # Test training with placeholder learning phase. - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) np_gamma, np_beta = sess.run([bn.gamma, bn.beta]) @@ -1310,7 +1310,7 @@ class BNTest(test.TestCase): # Verify that the statistics are updated during training. moving_mean, moving_var = sess.run([bn.moving_mean, bn.moving_variance]) - np_inputs = sess.run(inputs) + np_inputs = self.evaluate(inputs) mean = np.mean(np_inputs, axis=(0, 4), keepdims=True) std = np.std(np_inputs, axis=(0, 4), keepdims=True) variance = np.square(std) @@ -1350,7 +1350,7 @@ class BNTest(test.TestCase): shape[1:]) with self.session(use_gpu=True) as sess: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) for _ in range(5): x = np.random.random(shape) diff --git a/tensorflow/python/ops/control_flow_ops_test.py b/tensorflow/python/ops/control_flow_ops_test.py index 47675d3f343..260af95a3bd 100644 --- a/tensorflow/python/ops/control_flow_ops_test.py +++ b/tensorflow/python/ops/control_flow_ops_test.py @@ -209,7 +209,7 @@ class SwitchTestCase(test_util.TensorFlowTestCase): optimizer = momentum.MomentumOptimizer(0.1, 0.9) train_op = optimizer.minimize(cost) with self.cached_session() as sess: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) for _ in range(10): sess.run([train_op]) @@ -232,7 +232,7 @@ class SwitchTestCase(test_util.TensorFlowTestCase): cond, body, [constant_op.constant(0), constant_op.constant(0.0)]) with self.cached_session() as sess: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) self.assertAllEqual(10.0, self.evaluate(cost)) def doTestIndexedSlicesGradientInCondInWhileLoop(self, use_resource=False): @@ -269,7 +269,7 @@ class SwitchTestCase(test_util.TensorFlowTestCase): static_grads.indices) with self.cached_session() as sess: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) self.assertAllEqual(*sess.run([static_grads, dynamic_grads])) def testIndexedSlicesGradientInCondInWhileLoop(self): @@ -398,9 +398,9 @@ class CondTest(test_util.TensorFlowTestCase): pred=bool_var, true_fn=lambda: state_ops.assign(bool_var, False), false_fn=lambda: True) - sess.run(bool_var.initializer) - self.assertEquals(sess.run(cond_on_bool_var), False) - self.assertEquals(sess.run(cond_on_bool_var), True) + self.evaluate(bool_var.initializer) + self.assertEquals(self.evaluate(cond_on_bool_var), False) + self.assertEquals(self.evaluate(cond_on_bool_var), True) def testCondMissingArg1(self): with ops.Graph().as_default(): diff --git a/tensorflow/python/ops/gradients_test.py b/tensorflow/python/ops/gradients_test.py index 262b62e0131..a9058c4a341 100644 --- a/tensorflow/python/ops/gradients_test.py +++ b/tensorflow/python/ops/gradients_test.py @@ -365,7 +365,7 @@ class GradientsTest(test_util.TensorFlowTestCase): grads = gradients.gradients( [y], [x], unconnected_gradients="zero") with self.cached_session() as sess: - self.assertAllEqual([[0.0, 0.0], [0.0, 0.0]], sess.run(grads)[0]) + self.assertAllEqual([[0.0, 0.0], [0.0, 0.0]], self.evaluate(grads)[0]) def testUnconnectedGradientsZeroConnectedGradients(self): with ops.Graph().as_default(): @@ -374,7 +374,7 @@ class GradientsTest(test_util.TensorFlowTestCase): grad = gradients.gradients( [y], [x], unconnected_gradients="zero") with self.cached_session() as sess: - self.assertEquals(3.0, sess.run(grad)[0]) + self.assertEquals(3.0, self.evaluate(grad)[0]) def testUnknownUnconnectedGradientsValueGiven(self): with ops.Graph().as_default(): @@ -438,8 +438,8 @@ class FunctionGradientsTest(test_util.TensorFlowTestCase): grads = gradients.gradients(y, [x, b1]) with self.cached_session() as sess: - self.assertAllEqual([40.0], sess.run(grads)[0]) - self.assertAllEqual([10.0], sess.run(grads)[1]) + self.assertAllEqual([40.0], self.evaluate(grads)[0]) + self.assertAllEqual([10.0], self.evaluate(grads)[1]) def testFunctionGradientsWithGradFunc(self): g = ops.Graph() @@ -487,7 +487,7 @@ class FunctionGradientsTest(test_util.TensorFlowTestCase): f = Foo() with self.cached_session() as sess: - self.assertEqual(sess.run(f), 2.0) + self.assertEqual(self.evaluate(f), 2.0) def testGradientOfCaptured(self): with ops.Graph().as_default(): @@ -501,7 +501,7 @@ class FunctionGradientsTest(test_util.TensorFlowTestCase): f = Foo() with self.cached_session() as sess: - self.assertEqual(sess.run(f), 2.0) + self.assertEqual(self.evaluate(f), 2.0) def testCapturedResourceVariable(self): with ops.Graph().as_default(): @@ -515,8 +515,8 @@ class FunctionGradientsTest(test_util.TensorFlowTestCase): f = Foo() with self.cached_session() as sess: - sess.run(variables.global_variables_initializer()) - self.assertEqual(sess.run(f), 2.0) + self.evaluate(variables.global_variables_initializer()) + self.assertEqual(self.evaluate(f), 2.0) def testCapturedNested(self): with ops.Graph().as_default(): @@ -541,9 +541,9 @@ class FunctionGradientsTest(test_util.TensorFlowTestCase): x1_grad, x2_grad = Outer() with self.cached_session() as sess: # 1.0 + None + 2.0 + 1.0 = 4.0 - self.assertEqual(sess.run(x1_grad), 4.0) + self.assertEqual(self.evaluate(x1_grad), 4.0) # None + 1.0 + 1.0 + None = 2.0 - self.assertEqual(sess.run(x2_grad), 2.0) + self.assertEqual(self.evaluate(x2_grad), 2.0) def testCapturedFromFunction(self): with ops.Graph().as_default(): @@ -563,7 +563,7 @@ class FunctionGradientsTest(test_util.TensorFlowTestCase): z_grad = Outer() with self.cached_session() as sess: - self.assertEqual(sess.run(z_grad), 3.0) + self.assertEqual(self.evaluate(z_grad), 3.0) def testCapturedEagerTensors(self): # Test that we can handle captured eager tensors unrelated to the gradient @@ -873,7 +873,7 @@ class CustomGradientTest(test_util.TensorFlowTestCase): y = MyMultiply(x1, x2) dy = gradients.gradients(y, [x1, x2]) with session.Session() as sess: - self.assertAllEqual([3., 5.], sess.run(dy)) + self.assertAllEqual([3., 5.], self.evaluate(dy)) def testCustomGradientErrors(self): @@ -914,7 +914,7 @@ class CustomGradientTest(test_util.TensorFlowTestCase): for g in grads: self.assertTrue(g is not None) with session.Session() as sess: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) dw = sess.run(math_ops.reduce_sum(grads[1])) self.assertEqual(12., dw) @@ -1074,7 +1074,7 @@ class TensorListGradientsTest(test_util.TensorFlowTestCase): grad = gradients.gradients(tl, a, grad_ys=grad_tl)[0] with self.cached_session() as sess: - self.assertEquals(sess.run(grad), 5.) + self.assertEquals(self.evaluate(grad), 5.) if __name__ == "__main__": diff --git a/tensorflow/python/ops/image_grad_test.py b/tensorflow/python/ops/image_grad_test.py index 32c2f37c0b7..0ea15b0d23f 100644 --- a/tensorflow/python/ops/image_grad_test.py +++ b/tensorflow/python/ops/image_grad_test.py @@ -44,7 +44,7 @@ class ResizeNearestNeighborOpTest(test.TestCase): out_shape[1:3]) self.assertEqual(out_shape, list(resize_out.get_shape())) - resize_out = sess.run(resize_out) + resize_out = self.evaluate(resize_out) self.assertEqual(out_shape, list(resize_out.shape)) def testGradFromResizeToLargerInBothDims(self): @@ -113,7 +113,7 @@ class ResizeBilinearOpTest(test.TestCase): resize_out = image_ops.resize_bilinear(input_tensor, out_shape[1:3]) self.assertEqual(out_shape, list(resize_out.get_shape())) - resize_out = sess.run(resize_out) + resize_out = self.evaluate(resize_out) self.assertEqual(out_shape, list(resize_out.shape)) def testGradFromResizeToLargerInBothDims(self): @@ -196,7 +196,7 @@ class ResizeBicubicOpTest(test.TestCase): align_corners=align_corners) self.assertEqual(out_shape, list(resize_out.get_shape())) - resize_out = sess.run(resize_out) + resize_out = self.evaluate(resize_out) self.assertEqual(out_shape, list(resize_out.shape)) def testGradFromResizeToLargerInBothDims(self): @@ -273,7 +273,7 @@ class CropAndResizeOpTest(test.TestCase): constant_op.constant( crop_size, shape=[2])) self.assertEqual(crops_shape, list(crops.get_shape())) - crops = sess.run(crops) + crops = self.evaluate(crops) self.assertEqual(crops_shape, list(crops.shape)) def _randomUniformAvoidAnchors(self, low, high, anchors, radius, num_samples): diff --git a/tensorflow/python/ops/image_ops_test.py b/tensorflow/python/ops/image_ops_test.py index 07406982c5b..7eee70c0e3d 100644 --- a/tensorflow/python/ops/image_ops_test.py +++ b/tensorflow/python/ops/image_ops_test.py @@ -488,11 +488,11 @@ class FlipImageBenchmark(test.Benchmark): trainable=False, dtype=dtypes.float32) run_op = image_ops.flip_left_right(inputs) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) for i in xrange(warmup_rounds + benchmark_rounds): if i == warmup_rounds: start = time.time() - sess.run(run_op) + self.evaluate(run_op) end = time.time() step_time = (end - start) / benchmark_rounds tag = device + "_%s" % (cpu_count if cpu_count is not None else "_all") @@ -518,11 +518,11 @@ class FlipImageBenchmark(test.Benchmark): trainable=False, dtype=dtypes.float32) run_op = image_ops.random_flip_left_right(inputs) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) for i in xrange(warmup_rounds + benchmark_rounds): if i == warmup_rounds: start = time.time() - sess.run(run_op) + self.evaluate(run_op) end = time.time() step_time = (end - start) / benchmark_rounds tag = device + "_%s" % (cpu_count if cpu_count is not None else "_all") @@ -548,11 +548,11 @@ class FlipImageBenchmark(test.Benchmark): trainable=False, dtype=dtypes.float32) run_op = image_ops.random_flip_left_right(inputs) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) for i in xrange(warmup_rounds + benchmark_rounds): if i == warmup_rounds: start = time.time() - sess.run(run_op) + self.evaluate(run_op) end = time.time() step_time = (end - start) / benchmark_rounds tag = device + "_%s" % (cpu_count if cpu_count is not None else "_all") @@ -610,11 +610,11 @@ class AdjustHueBenchmark(test.Benchmark): delta = constant_op.constant(0.1, dtype=dtypes.float32) outputs = image_ops.adjust_hue(inputs, delta) run_op = control_flow_ops.group(outputs) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) for i in xrange(warmup_rounds + benchmark_rounds): if i == warmup_rounds: start = time.time() - sess.run(run_op) + self.evaluate(run_op) end = time.time() step_time = (end - start) / benchmark_rounds tag = device + "_%s" % (cpu_count if cpu_count is not None else "_all") @@ -653,12 +653,12 @@ class AdjustSaturationBenchmark(test.Benchmark): delta = constant_op.constant(0.1, dtype=dtypes.float32) outputs = image_ops.adjust_saturation(inputs, delta) run_op = control_flow_ops.group(outputs) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) for _ in xrange(warmup_rounds): - sess.run(run_op) + self.evaluate(run_op) start = time.time() for _ in xrange(benchmark_rounds): - sess.run(run_op) + self.evaluate(run_op) end = time.time() step_time = (end - start) / benchmark_rounds tag = device + "_%s" % (cpu_count if cpu_count is not None else "_all") @@ -698,7 +698,7 @@ class ResizeBilinearBenchmark(test.Benchmark): benchmark_op = control_flow_ops.group(*deps) with self.benchmark_session() as sess: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) results = self.run_op_benchmark( sess, benchmark_op, @@ -746,7 +746,7 @@ class ResizeBicubicBenchmark(test.Benchmark): benchmark_op = control_flow_ops.group(*deps) with self.benchmark_session() as sess: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) results = self.run_op_benchmark( sess, benchmark_op, @@ -803,7 +803,7 @@ class ResizeAreaBenchmark(test.Benchmark): benchmark_op = control_flow_ops.group(*deps) with self.benchmark_session() as sess: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) results = self.run_op_benchmark( sess, benchmark_op, @@ -4110,7 +4110,7 @@ class MultiscaleSSIMTest(test_util.TensorFlowTestCase): images = [ops.convert_to_tensor(x, dtype=dtypes.float32) for x in images] msssim_ops = [image_ops.ssim_multiscale(x, y, 1.0) for x, y in itertools.combinations(images, 2)] - msssim = sess.run(msssim_ops) + msssim = self.evaluate(msssim_ops) msssim = np.squeeze(msssim) self.assertTrue(np.all(msssim >= 0.0)) diff --git a/tensorflow/python/ops/init_ops_test.py b/tensorflow/python/ops/init_ops_test.py index 5693c3caaf5..1f222480046 100644 --- a/tensorflow/python/ops/init_ops_test.py +++ b/tensorflow/python/ops/init_ops_test.py @@ -45,8 +45,8 @@ class InitializersTest(test.TestCase): output = variable.numpy() else: sess = ops.get_default_session() - sess.run(variable.initializer) - output = sess.run(variable) + self.evaluate(variable.initializer) + output = self.evaluate(variable) lim = 3e-2 if target_std is not None: self.assertGreater(lim, abs(output.std() - target_std)) diff --git a/tensorflow/python/ops/math_ops_test.py b/tensorflow/python/ops/math_ops_test.py index dc46f1cbd18..e0329f66ff3 100644 --- a/tensorflow/python/ops/math_ops_test.py +++ b/tensorflow/python/ops/math_ops_test.py @@ -373,7 +373,7 @@ class AddNTest(test_util.TensorFlowTestCase): for i in range(0, num_inputs) ] addn = math_ops.add_n(input_vars) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) add_n_grad = gradients.gradients(addn, input_vars) self.assertAllEqual(np.repeat(1.0, num_inputs), # d/dx (x + y + ...) = 1 [g.eval() for g in add_n_grad]) @@ -461,7 +461,7 @@ class DivAndModTest(test_util.TensorFlowTestCase): a = variables.Variable(2.) b = variables.Variable(4.) with self.cached_session() as sess: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) c_grad = gradients.gradients(math_ops.divide(a, b), [a, b]) self.assertAllEqual([x.eval() for x in c_grad], [.25, -.125]) c_grad = gradients.gradients(math_ops.div(a, b), [a, b]) diff --git a/tensorflow/python/ops/nn_fused_batchnorm_test.py b/tensorflow/python/ops/nn_fused_batchnorm_test.py index a6c582fcac8..552b274b833 100644 --- a/tensorflow/python/ops/nn_fused_batchnorm_test.py +++ b/tensorflow/python/ops/nn_fused_batchnorm_test.py @@ -82,7 +82,7 @@ class BatchNormalizationTest(test.TestCase): epsilon=epsilon, data_format=data_format, is_training=False) - y_val = sess.run(y) + y_val = self.evaluate(y) y_ref = self._inference_ref(x, scale, offset, mean, var, epsilon, data_format) # An atol value of 1e-3 is too small for float16's, because some adjacent diff --git a/tensorflow/python/ops/nn_test.py b/tensorflow/python/ops/nn_test.py index af6c728694f..14cc1c6b5ad 100644 --- a/tensorflow/python/ops/nn_test.py +++ b/tensorflow/python/ops/nn_test.py @@ -978,7 +978,7 @@ class LeakyReluTest(test_lib.TestCase): np_values = np.array([-2, -1, 0, 1, 2], dtype=dtype) outputs = nn_ops.leaky_relu(constant_op.constant(np_values)) with self.cached_session() as sess: - outputs = sess.run(outputs) + outputs = self.evaluate(outputs) tol = 2e-3 if dtype == np.float16 else 1e-6 self.assertAllClose( outputs, [-0.4, -0.2, 0.0, 1.0, 2.0], rtol=tol, atol=tol) @@ -1095,7 +1095,7 @@ class DataFormatDimMapTest(test_lib.TestCase): x = constant_op.constant(x_val) y = nn_ops.data_format_dim_map(x) with self.cached_session(use_gpu=test_lib.is_gpu_available()) as sess: - y_val = sess.run(y) + y_val = self.evaluate(y) self.assertAllEqual(y_val, y_val_expected) def test(self): @@ -1118,7 +1118,7 @@ class DataFormatDimMapTest(test_lib.TestCase): x = constant_op.constant(x_val) y = nn_ops.data_format_dim_map(x, src_format="NHWC", dst_format="NCHW") with self.session(use_gpu=test_lib.is_gpu_available()) as sess: - y_val = sess.run(y) + y_val = self.evaluate(y) self.assertAllEqual(y_val, y_val_expected) def testNHWCtoHWNC(self): @@ -1127,7 +1127,7 @@ class DataFormatDimMapTest(test_lib.TestCase): x = constant_op.constant(x_val) y = nn_ops.data_format_dim_map(x, src_format="NHWC", dst_format="HWNC") with self.session(use_gpu=test_lib.is_gpu_available()) as sess: - y_val = sess.run(y) + y_val = self.evaluate(y) self.assertAllEqual(y_val, y_val_expected) def testNHWCtoWHCN(self): @@ -1136,7 +1136,7 @@ class DataFormatDimMapTest(test_lib.TestCase): x = constant_op.constant(x_val) y = nn_ops.data_format_dim_map(x, src_format="NHWC", dst_format="WHCN") with self.session(use_gpu=test_lib.is_gpu_available()) as sess: - y_val = sess.run(y) + y_val = self.evaluate(y) self.assertAllEqual(y_val, y_val_expected) def testArbitraryASCII(self): @@ -1145,7 +1145,7 @@ class DataFormatDimMapTest(test_lib.TestCase): x = constant_op.constant(x_val) y = nn_ops.data_format_dim_map(x, src_format="qwer", dst_format="rewq") with self.session(use_gpu=test_lib.is_gpu_available()) as sess: - y_val = sess.run(y) + y_val = self.evaluate(y) self.assertAllEqual(y_val, y_val_expected) @@ -1156,7 +1156,7 @@ class DataFormatVectorPermuteTest(test_lib.TestCase): x = constant_op.constant(x_val) y = nn_ops.data_format_vec_permute(x) with self.session(use_gpu=test_lib.is_gpu_available()) as sess: - y_val = sess.run(y) + y_val = self.evaluate(y) self.assertAllEqual(y_val, [7, 3, 4, 9]) def testNCHWToNHWC(self): @@ -1164,7 +1164,7 @@ class DataFormatVectorPermuteTest(test_lib.TestCase): x = constant_op.constant(x_val) y = nn_ops.data_format_vec_permute(x, src_format="NCHW", dst_format="NHWC") with self.session(use_gpu=test_lib.is_gpu_available()) as sess: - y_val = sess.run(y) + y_val = self.evaluate(y) self.assertAllEqual(y_val, [7, 9, 3, 4]) def testNHWCToHWNC(self): @@ -1172,7 +1172,7 @@ class DataFormatVectorPermuteTest(test_lib.TestCase): x = constant_op.constant(x_val) y = nn_ops.data_format_vec_permute(x, src_format="NHWC", dst_format="HWNC") with self.session(use_gpu=test_lib.is_gpu_available()) as sess: - y_val = sess.run(y) + y_val = self.evaluate(y) self.assertAllEqual(y_val, [4, 9, 7, 3]) def testHWNCToNHWC(self): @@ -1180,7 +1180,7 @@ class DataFormatVectorPermuteTest(test_lib.TestCase): x = constant_op.constant(x_val) y = nn_ops.data_format_vec_permute(x, src_format="HWNC", dst_format="NHWC") with self.session(use_gpu=test_lib.is_gpu_available()) as sess: - y_val = sess.run(y) + y_val = self.evaluate(y) self.assertAllEqual(y_val, [9, 7, 4, 3]) def testNHWCToNCHW2D(self): @@ -1188,7 +1188,7 @@ class DataFormatVectorPermuteTest(test_lib.TestCase): x = constant_op.constant(x_val) y = nn_ops.data_format_vec_permute(x) with self.session(use_gpu=test_lib.is_gpu_available()) as sess: - y_val = sess.run(y) + y_val = self.evaluate(y) self.assertAllEqual(y_val, [[7, 4], [5, 1], [9, 3], [4, 5]]) def testNHWCToHWNC2D(self): @@ -1196,7 +1196,7 @@ class DataFormatVectorPermuteTest(test_lib.TestCase): x = constant_op.constant(x_val) y = nn_ops.data_format_vec_permute(x, src_format="NHWC", dst_format="HWNC") with self.session(use_gpu=test_lib.is_gpu_available()) as sess: - y_val = sess.run(y) + y_val = self.evaluate(y) self.assertAllEqual(y_val, [[9, 3], [4, 5], [7, 4], [5, 1]]) def testHWNCToNHWC2D(self): @@ -1204,7 +1204,7 @@ class DataFormatVectorPermuteTest(test_lib.TestCase): x = constant_op.constant(x_val) y = nn_ops.data_format_vec_permute(x, src_format="HWNC", dst_format="NHWC") with self.session(use_gpu=test_lib.is_gpu_available()) as sess: - y_val = sess.run(y) + y_val = self.evaluate(y) self.assertAllEqual(y_val, [[4, 5], [7, 4], [9, 3], [5, 1]]) def testNCHWToNHWC2D(self): @@ -1212,7 +1212,7 @@ class DataFormatVectorPermuteTest(test_lib.TestCase): x = constant_op.constant(x_val) y = nn_ops.data_format_vec_permute(x, src_format="NCHW", dst_format="NHWC") with self.session(use_gpu=test_lib.is_gpu_available()) as sess: - y_val = sess.run(y) + y_val = self.evaluate(y) self.assertAllEqual(y_val, [[7, 4], [4, 5], [5, 1], [9, 3]]) diff --git a/tensorflow/python/ops/parallel_for/gradients_test.py b/tensorflow/python/ops/parallel_for/gradients_test.py index 5a058bae825..b2be24e1106 100644 --- a/tensorflow/python/ops/parallel_for/gradients_test.py +++ b/tensorflow/python/ops/parallel_for/gradients_test.py @@ -472,7 +472,7 @@ class GradientsTest(test.TestCase): with session.Session() as sess: init = variables.global_variables_initializer() sess.run(init) - pfor = sess.run(pfor_jacobian) + pfor = self.evaluate(pfor_jacobian) for i in range(4): while_i = sess.run(while_gradients[i]) self.assertAllClose(while_i, pfor[:, i, ...]) diff --git a/tensorflow/python/ops/quantized_conv_ops_test.py b/tensorflow/python/ops/quantized_conv_ops_test.py index f7fa264461e..6b469a954f6 100644 --- a/tensorflow/python/ops/quantized_conv_ops_test.py +++ b/tensorflow/python/ops/quantized_conv_ops_test.py @@ -73,7 +73,7 @@ class Conv2DTest(test.TestCase): max_input=x1_max, min_filter=x2_min, max_filter=x2_max) - value = sess.run(conv) + value = self.evaluate(conv) quantized_output = value[0] output_min = value[1] output_max = value[2] diff --git a/tensorflow/python/ops/quantized_ops_test.py b/tensorflow/python/ops/quantized_ops_test.py index 0f3b04e4ad0..b81843d1748 100644 --- a/tensorflow/python/ops/quantized_ops_test.py +++ b/tensorflow/python/ops/quantized_ops_test.py @@ -41,7 +41,7 @@ class QuantizedOpsTest(test.TestCase): x_min = 0.0 x_max = 255.0 op = array_ops.quantize(x, x_min, x_max, dtypes.quint8, mode="MIN_FIRST") - value = sess.run(op) + value = self.evaluate(op) self.assertArrayNear(expected_output, value.output, 0.1) def testDequantizeOp(self): @@ -52,7 +52,7 @@ class QuantizedOpsTest(test.TestCase): x_min = 0.0 x_max = 255.0 op = array_ops.dequantize(x, x_min, x_max, mode="MIN_FIRST") - value = sess.run(op) + value = self.evaluate(op) self.assertArrayNear(expected_output, value, 0.1) 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 dcf1feaa696..c52db9e2a16 100644 --- a/tensorflow/python/ops/ragged/ragged_gather_nd_op_test.py +++ b/tensorflow/python/ops/ragged/ragged_gather_nd_op_test.py @@ -190,7 +190,7 @@ class RaggedGatherNdOpTest(test_util.TensorFlowTestCase, with self.test_session() as sess: if hasattr(expected, 'tolist'): expected = expected.tolist() - self.assertEqual(sess.run(result).tolist(), expected) + self.assertEqual(self.evaluate(result).tolist(), expected) def testRaggedGatherNdUnknownRankError(self): params = ragged.constant([['a', 'b'], ['c', 'd']]) diff --git a/tensorflow/python/profiler/model_analyzer_test.py b/tensorflow/python/profiler/model_analyzer_test.py index 94c685274a7..8648f0b5148 100644 --- a/tensorflow/python/profiler/model_analyzer_test.py +++ b/tensorflow/python/profiler/model_analyzer_test.py @@ -93,10 +93,10 @@ class PrintModelAnalysisTest(test.TestCase): config=self._no_rewrite_session_config()) as sess, ops.device(dev): x = lib.BuildSmallModel() - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) pctx.trace_next_step() pctx.dump_next_step() - _ = sess.run(x) + _ = self.evaluate(x) pctx.profiler.profile_name_scope(options=opts) @@ -160,7 +160,7 @@ class PrintModelAnalysisTest(test.TestCase): ) as sess, ops.device('/device:CPU:0'): x = lib.BuildSmallModel() - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) run_meta = config_pb2.RunMetadata() _ = sess.run(x, options=config_pb2.RunOptions( @@ -186,7 +186,7 @@ class PrintModelAnalysisTest(test.TestCase): with session.Session(config=self._no_rewrite_session_config()) as sess: x = lib.BuildSmallModel() - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) run_meta = config_pb2.RunMetadata() _ = sess.run(x, options=config_pb2.RunOptions( @@ -220,9 +220,9 @@ class PrintModelAnalysisTest(test.TestCase): with session.Session(config=self._no_rewrite_session_config()) as sess: x = lib.BuildFullModel() - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) pctx.trace_next_step() - _ = sess.run(x) + _ = self.evaluate(x) tfprof_node = pctx.profiler.profile_python(options=opts) # pylint: disable=line-too-long @@ -281,7 +281,7 @@ class PrintModelAnalysisTest(test.TestCase): with session.Session(config=self._no_rewrite_session_config()) as sess: x = lib.BuildSmallModel() - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) run_meta = config_pb2.RunMetadata() _ = sess.run(x, options=config_pb2.RunOptions( @@ -309,7 +309,7 @@ class PrintModelAnalysisTest(test.TestCase): with session.Session(config=self._no_rewrite_session_config()) as sess: x = lib.BuildFullModel() - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) run_meta = config_pb2.RunMetadata() _ = sess.run( x, @@ -345,7 +345,7 @@ class PrintModelAnalysisTest(test.TestCase): with session.Session(config=self._no_rewrite_session_config()) as sess: x = lib.BuildFullModel() - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) run_meta = config_pb2.RunMetadata() _ = sess.run(x, options=config_pb2.RunOptions( @@ -391,7 +391,7 @@ class PrintModelAnalysisTest(test.TestCase): with session.Session(config=self._no_rewrite_session_config()) as sess: x = lib.BuildFullModel() - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) run_meta = config_pb2.RunMetadata() _ = sess.run( x, @@ -424,7 +424,7 @@ class PrintModelAnalysisTest(test.TestCase): with session.Session(config=self._no_rewrite_session_config()) as sess: x = lib.BuildFullModel() - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) run_meta = config_pb2.RunMetadata() _ = sess.run( x, @@ -490,7 +490,7 @@ class PrintModelAnalysisTest(test.TestCase): with session.Session(config=self._no_rewrite_session_config()) as sess: x = lib.BuildSmallModel() - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) run_meta = config_pb2.RunMetadata() _ = sess.run(x, options=config_pb2.RunOptions( @@ -555,7 +555,7 @@ class PrintModelAnalysisTest(test.TestCase): with session.Session(config=self._no_rewrite_session_config()) as sess: x = lib.BuildSmallModel() - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) run_meta = config_pb2.RunMetadata() _ = sess.run(x, options=config_pb2.RunOptions( @@ -587,10 +587,10 @@ class PrintModelAnalysisTest(test.TestCase): def _trainLoop(self, train_op, train_steps, time_dir, time_step, memory_dir, memory_step, profile_dir, dump_step): with session.Session(config=self._no_rewrite_session_config()) as sess: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) # start from 1 because variable_initializer took one step. for i in range(1, train_steps + 1): - _ = sess.run(train_op) + _ = self.evaluate(train_op) if i in time_step: ret = gfile.ListDirectory(time_dir) self.assertEqual(len(ret), 1) diff --git a/tensorflow/python/profiler/profile_context_test.py b/tensorflow/python/profiler/profile_context_test.py index 107ad443c32..abbeb8bedfd 100644 --- a/tensorflow/python/profiler/profile_context_test.py +++ b/tensorflow/python/profiler/profile_context_test.py @@ -48,7 +48,7 @@ class ProfilerContextTest(test.TestCase): with profile_context.ProfileContext(test.get_temp_dir()) as pctx: pctx.add_auto_profiling("op", options=opts, profile_steps=[15, 50, 100]) with session.Session() as sess: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) total_steps = 101 for i in range(total_steps): sess.run(x) @@ -75,7 +75,7 @@ class ProfilerContextTest(test.TestCase): with profile_context.ProfileContext(test.get_temp_dir(), debug=True): with session.Session() as sess: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) for _ in range(10): sess.run(x) for f in gfile.ListDirectory(test.get_temp_dir()): @@ -96,7 +96,7 @@ class ProfilerContextTest(test.TestCase): with profile_context.ProfileContext(test.get_temp_dir(), enabled=False) as pctx: with session.Session() as sess: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) for _ in range(10): sess.run(x) self.assertTrue(pctx.profiler is None) @@ -105,7 +105,7 @@ class ProfilerContextTest(test.TestCase): with profile_context.ProfileContext(test.get_temp_dir()) as pctx: with session.Session() as sess: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) for _ in range(10): sess.run(x) self.assertFalse(pctx.profiler is None) diff --git a/tensorflow/python/saved_model/loader_test.py b/tensorflow/python/saved_model/loader_test.py index 648c1c59284..0b97a734415 100644 --- a/tensorflow/python/saved_model/loader_test.py +++ b/tensorflow/python/saved_model/loader_test.py @@ -50,7 +50,7 @@ class SavedModelLoaderTest(test.TestCase): x = variables.VariableV1(5, name="x") y = variables.VariableV1(11, name="y") z = x + y - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) foo_sig_def = signature_def_utils.build_signature_def( {"foo_input": utils.build_tensor_info(x)}, @@ -138,7 +138,7 @@ class SavedModelLoaderTest(test.TestCase): y = variables.VariableV1(0, name="y") z = x * y - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) # There are variables to restore, so a saver must be created. with self.assertRaises(ValueError): diff --git a/tensorflow/python/saved_model/saved_model_test.py b/tensorflow/python/saved_model/saved_model_test.py index ab43e938536..a04f4dd0991 100644 --- a/tensorflow/python/saved_model/saved_model_test.py +++ b/tensorflow/python/saved_model/saved_model_test.py @@ -61,7 +61,7 @@ class SavedModelTest(test.TestCase): def _init_and_validate_variable(self, sess, variable_name, variable_value): v = variables.VariableV1(variable_value, name=variable_name) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) self.assertEqual(variable_value, self.evaluate(v)) def _build_asset_collection(self, asset_file_name, asset_file_contents, @@ -385,7 +385,7 @@ class SavedModelTest(test.TestCase): a = ops.get_default_graph().get_tensor_by_name(constant_5_name) b = constant_op.constant(6.0) c = a * b - self.assertEqual(30.0, sess.run(c)) + self.assertEqual(30.0, self.evaluate(c)) # Restore the graph with tag "bar". with self.session(graph=ops.Graph()) as sess: @@ -394,7 +394,7 @@ class SavedModelTest(test.TestCase): a = ops.get_default_graph().get_tensor_by_name(constant_6_name) b = constant_op.constant(5.0) c = a * b - self.assertEqual(30.0, sess.run(c)) + self.assertEqual(30.0, self.evaluate(c)) def testNoOverwrite(self): export_dir = self._get_export_dir("test_no_overwrite") @@ -460,7 +460,7 @@ class SavedModelTest(test.TestCase): with self.session(graph=ops.Graph()) as sess: v = variables.VariableV1(42, name="v") ops.add_to_collection("foo_vars", v) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) self.assertEqual(42, self.evaluate(v)) builder.add_meta_graph_and_variables(sess, ["foo"]) @@ -470,7 +470,7 @@ class SavedModelTest(test.TestCase): with self.session(graph=ops.Graph()) as sess: v = variables.VariableV1(43, name="v") ops.add_to_collection("bar_vars", v) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) self.assertEqual(43, self.evaluate(v)) builder.add_meta_graph(["bar"]) @@ -794,7 +794,7 @@ class SavedModelTest(test.TestCase): add_v1_v2 = math_ops.add(v1._ref(), v2._ref()) custom_main_op = control_flow_ops.group(state_ops.assign(v3, add_v1_v2)) - sess.run(custom_main_op) + self.evaluate(custom_main_op) builder.add_meta_graph_and_variables( sess, ["foo"], main_op=custom_main_op) @@ -828,7 +828,7 @@ class SavedModelTest(test.TestCase): assign_v3 = state_ops.assign(v3, math_ops.add(v1, v2)) legacy_init_op = control_flow_ops.group(assign_v3, name="legacy_init_op") - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) builder.add_meta_graph_and_variables( sess, ["foo"], legacy_init_op=legacy_init_op) @@ -871,7 +871,7 @@ class SavedModelTest(test.TestCase): assign_v2 = state_ops.assign(v2, v1) init_op = control_flow_ops.group(assign_v2, name="init_op") - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) ops.add_to_collection(key, control_flow_ops.no_op()) # ValueError should be raised since the LEGACY_INIT_OP_KEY collection @@ -894,10 +894,10 @@ class SavedModelTest(test.TestCase): v2 = variables.VariableV1(2, name="v2") ops.add_to_collection("v", v2) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) train_op = state_ops.assign_add(v1, v2) - sess.run(train_op) + self.evaluate(train_op) # TODO(karmel): remove explicit call when in the public method. builder._add_train_op(train_op) builder.add_meta_graph_and_variables(sess, ["foo"]) @@ -923,10 +923,10 @@ class SavedModelTest(test.TestCase): v2 = variables.VariableV1(2, name="v2") ops.add_to_collection("v", v2) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) train_op = control_flow_ops.group() - sess.run(train_op) + self.evaluate(train_op) # TODO(karmel): remove explicit call when in the public method. builder._add_train_op(train_op) builder.add_meta_graph_and_variables(sess, ["foo"]) @@ -952,11 +952,11 @@ class SavedModelTest(test.TestCase): v2 = variables.VariableV1(2, name="v2") ops.add_to_collection("v", v2) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) builder.add_meta_graph_and_variables(sess, ["pre_foo"]) train_op = state_ops.assign_add(v1, v2) - sess.run(train_op) + self.evaluate(train_op) # TODO(karmel): remove explicit call when in the public method. builder._add_train_op(train_op) builder.add_meta_graph(["foo"]) @@ -1086,7 +1086,7 @@ class SavedModelTest(test.TestCase): ops.add_to_collection("v", v3) ops.add_to_collection("init_op", init_op) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) self.assertEqual(1, ops.get_collection("v")[0].eval()) self.assertEqual(2, ops.get_collection("v")[1].eval()) @@ -1141,7 +1141,7 @@ class SavedModelTest(test.TestCase): with self.session(graph=ops.Graph()) as sess: variables.VariableV1(1, name="v1") - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) custom_saver = training.Saver(name="my_saver") builder.add_meta_graph_and_variables(sess, ["tag"], saver=custom_saver) @@ -1163,7 +1163,7 @@ class SavedModelTest(test.TestCase): with self.session(graph=ops.Graph()) as sess: variables.VariableV1(1, name="v1") - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) training.Saver(name="my_saver") builder.add_meta_graph_and_variables(sess, ["tag"]) @@ -1185,7 +1185,7 @@ class SavedModelTest(test.TestCase): with self.session(graph=ops.Graph()) as sess: variables.VariableV1(1, name="v1") - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) builder.add_meta_graph_and_variables(sess, ["tag_0"]) saver_1 = training.Saver() @@ -1296,7 +1296,7 @@ class SavedModelTest(test.TestCase): real_num = variables.VariableV1(1.0, dtype=dtypes.float32, name="real") imag_num = variables.VariableV1(2.0, dtype=dtypes.float32, name="imag") math_ops.complex(real_num, imag_num, name="complex") - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) builder.add_meta_graph_and_variables( sess, ["foo"], strip_default_attrs=True) @@ -1306,7 +1306,7 @@ class SavedModelTest(test.TestCase): real_num = variables.VariableV1(1.0, dtype=dtypes.float32, name="real") imag_num = variables.VariableV1(2.0, dtype=dtypes.float32, name="imag") math_ops.complex(real_num, imag_num, name="complex") - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) builder.add_meta_graph(["bar"], strip_default_attrs=False) # Save the SavedModel to disk in text format. @@ -1368,7 +1368,7 @@ class SavedModelTest(test.TestCase): with session.Session(graph=ops.Graph()) as sess: variables.VariableV1(1.0, dtype=dtypes.float64, name="var") test_ops.test_attr(T=dtypes.float32, name="test_attr") - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) builder.add_meta_graph_and_variables(sess, ["foo"]) # Save the SavedModel to disk in text format. diff --git a/tensorflow/python/saved_model/simple_save_test.py b/tensorflow/python/saved_model/simple_save_test.py index 2d404dcea44..0d0665072ac 100644 --- a/tensorflow/python/saved_model/simple_save_test.py +++ b/tensorflow/python/saved_model/simple_save_test.py @@ -33,7 +33,7 @@ class SimpleSaveTest(test.TestCase): def _init_and_validate_variable(self, sess, variable_name, variable_value): v = variables.Variable(variable_value, name=variable_name) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) self.assertEqual(variable_value, self.evaluate(v)) return v diff --git a/tensorflow/python/tools/strip_unused_test.py b/tensorflow/python/tools/strip_unused_test.py index 7cf0c3e3ed9..e906ff94ba8 100644 --- a/tensorflow/python/tools/strip_unused_test.py +++ b/tensorflow/python/tools/strip_unused_test.py @@ -50,7 +50,7 @@ class StripUnusedTest(test_util.TensorFlowTestCase): wanted_input_node, 2.0, name="output_node") math_ops.add(output_node, 2.0, name="later_node") sess = session.Session() - output = sess.run(output_node) + output = self.evaluate(output_node) self.assertNear(-4.0, output, 0.00001) graph_io.write_graph(sess.graph, self.get_temp_dir(), input_graph_name) @@ -113,7 +113,7 @@ class StripUnusedTest(test_util.TensorFlowTestCase): input_node1, input_node2, name="output_node") math_ops.add(output_node, 2.0, name="later_node") sess = session.Session() - output = sess.run(output_node) + output = self.evaluate(output_node) self.assertNear(6.0, output, 0.00001) graph_io.write_graph(sess.graph, self.get_temp_dir(), input_graph_name) diff --git a/tensorflow/python/training/basic_session_run_hooks_test.py b/tensorflow/python/training/basic_session_run_hooks_test.py index 2d469634e0e..13c9e9aa67b 100644 --- a/tensorflow/python/training/basic_session_run_hooks_test.py +++ b/tensorflow/python/training/basic_session_run_hooks_test.py @@ -243,7 +243,7 @@ class LoggingTensorHookTest(test.TestCase): tensors=[t.name], at_end=True) hook.begin() mon_sess = monitored_session._HookedSession(sess, [hook]) - sess.run(variables_lib.global_variables_initializer()) + self.evaluate(variables_lib.global_variables_initializer()) self.logged_message = '' for _ in range(3): mon_sess.run(train_op) @@ -261,7 +261,7 @@ class LoggingTensorHookTest(test.TestCase): tensors=[t.name], every_n_iter=10, at_end=at_end) hook.begin() mon_sess = monitored_session._HookedSession(sess, [hook]) - sess.run(variables_lib.global_variables_initializer()) + self.evaluate(variables_lib.global_variables_initializer()) mon_sess.run(train_op) self.assertRegexpMatches(str(self.logged_message), t.name) for _ in range(3): @@ -308,7 +308,7 @@ class LoggingTensorHookTest(test.TestCase): tensors={'foo': t}, every_n_iter=1) hook.begin() mon_sess = monitored_session._HookedSession(sess, [hook]) - sess.run(variables_lib.global_variables_initializer()) + self.evaluate(variables_lib.global_variables_initializer()) mon_sess.run(train_op) self.assertRegexpMatches(str(self.logged_message), 'foo') # in first run, elapsed time is None. @@ -322,7 +322,7 @@ class LoggingTensorHookTest(test.TestCase): tensors=[t.name], every_n_secs=1.0, at_end=at_end) hook.begin() mon_sess = monitored_session._HookedSession(sess, [hook]) - sess.run(variables_lib.global_variables_initializer()) + self.evaluate(variables_lib.global_variables_initializer()) mon_sess.run(train_op) self.assertRegexpMatches(str(self.logged_message), t.name) @@ -366,7 +366,7 @@ class LoggingTensorHookTest(test.TestCase): formatter=lambda items: 'qqq=%s' % items[t.name]) hook.begin() mon_sess = monitored_session._HookedSession(sess, [hook]) - sess.run(variables_lib.global_variables_initializer()) + self.evaluate(variables_lib.global_variables_initializer()) mon_sess.run(train_op) self.assertEqual(self.logged_message[0], 'qqq=42.0') @@ -921,7 +921,7 @@ class StepCounterHookTest(test.TestCase): hook = basic_session_run_hooks.StepCounterHook( summary_writer=summary_writer, every_n_steps=10) hook.begin() - sess.run(variables_lib.global_variables_initializer()) + self.evaluate(variables_lib.global_variables_initializer()) mon_sess = monitored_session._HookedSession(sess, [hook]) with test.mock.patch.object(tf_logging, 'warning') as mock_log: for _ in range(30): @@ -950,7 +950,7 @@ class StepCounterHookTest(test.TestCase): summary_writer=summary_writer, every_n_steps=None, every_n_secs=0.1) hook.begin() - sess.run(variables_lib.global_variables_initializer()) + self.evaluate(variables_lib.global_variables_initializer()) mon_sess = monitored_session._HookedSession(sess, [hook]) mon_sess.run(train_op) time.sleep(0.2) @@ -987,7 +987,7 @@ class StepCounterHookTest(test.TestCase): summary_writer=summary_writer, every_n_steps=1, every_n_secs=None) hook.begin() - sess.run(variables_lib.global_variables_initializer()) + self.evaluate(variables_lib.global_variables_initializer()) mon_sess = monitored_session._HookedSession(sess, [hook]) mon_sess.run(train_op) mon_sess.run(train_op) @@ -1007,7 +1007,7 @@ class StepCounterHookTest(test.TestCase): with ops.Graph().as_default(), session_lib.Session() as sess: variables.get_or_create_global_step() train_op = training_util._increment_global_step(0) # keep same. - sess.run(variables_lib.global_variables_initializer()) + self.evaluate(variables_lib.global_variables_initializer()) hook = basic_session_run_hooks.StepCounterHook( every_n_steps=1, every_n_secs=None) hook.begin() @@ -1034,7 +1034,7 @@ class StepCounterHookTest(test.TestCase): summary_writer=self.summary_writer, every_n_steps=every_n_steps) self.hook._set_steps_per_run(steps_per_run) self.hook.begin() - sess.run(variables_lib.global_variables_initializer()) + self.evaluate(variables_lib.global_variables_initializer()) self.mon_sess = monitored_session._HookedSession(sess, [self.hook]) def test_steps_per_run_less_than_every_n_steps(self): @@ -1147,7 +1147,7 @@ class SummarySaverHookTest(test.TestCase): with self.cached_session() as sess: hook.begin() - sess.run(variables_lib.global_variables_initializer()) + self.evaluate(variables_lib.global_variables_initializer()) mon_sess = monitored_session._HookedSession(sess, [hook]) for _ in range(30): mon_sess.run(self.train_op) @@ -1179,7 +1179,7 @@ class SummarySaverHookTest(test.TestCase): with self.cached_session() as sess: hook.begin() - sess.run(variables_lib.global_variables_initializer()) + self.evaluate(variables_lib.global_variables_initializer()) mon_sess = monitored_session._HookedSession(sess, [hook]) for _ in range(10): mon_sess.run(self.train_op) @@ -1207,7 +1207,7 @@ class SummarySaverHookTest(test.TestCase): with self.cached_session() as sess: hook.begin() - sess.run(variables_lib.global_variables_initializer()) + self.evaluate(variables_lib.global_variables_initializer()) mon_sess = monitored_session._HookedSession(sess, [hook]) for _ in range(4): mon_sess.run(self.train_op) @@ -1242,7 +1242,7 @@ class SummarySaverHookTest(test.TestCase): with self.cached_session() as sess: hook.begin() - sess.run(variables_lib.global_variables_initializer()) + self.evaluate(variables_lib.global_variables_initializer()) mon_sess = monitored_session._HookedSession(sess, [hook]) for _ in range(8): mon_sess.run(self.train_op) @@ -1285,7 +1285,7 @@ class GlobalStepWaiterHookTest(test.TestCase): hook = basic_session_run_hooks.GlobalStepWaiterHook(wait_until_step=1000) hook.begin() with session_lib.Session() as sess: - sess.run(variables_lib.global_variables_initializer()) + self.evaluate(variables_lib.global_variables_initializer()) waiter = threading.Thread( target=hook.before_run, args=(session_run_hook.SessionRunContext( @@ -1390,7 +1390,7 @@ class ResourceSummarySaverHookTest(test.TestCase): with self.cached_session() as sess: hook.begin() - sess.run(variables_lib.global_variables_initializer()) + self.evaluate(variables_lib.global_variables_initializer()) mon_sess = monitored_session._HookedSession(sess, [hook]) for _ in range(30): mon_sess.run(self.train_op) diff --git a/tensorflow/python/training/checkpoint_ops_test.py b/tensorflow/python/training/checkpoint_ops_test.py index 38d4acf85fc..21ad3df1c8f 100644 --- a/tensorflow/python/training/checkpoint_ops_test.py +++ b/tensorflow/python/training/checkpoint_ops_test.py @@ -47,7 +47,7 @@ class LoadAndRemapWrappersTest(test.TestCase): with variable_scope.variable_scope('some_scope'): variable_scope.get_variable(name='embeddings', shape=[5, 16], initializer=initializer) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) saver = saver_lib.Saver() saver.save(sess, checkpoint_prefix, global_step=5) self.checkpoint_file = '{}-5'.format(checkpoint_prefix) diff --git a/tensorflow/python/training/input_test.py b/tensorflow/python/training/input_test.py index e5aac5da187..31c2cc56c09 100644 --- a/tensorflow/python/training/input_test.py +++ b/tensorflow/python/training/input_test.py @@ -474,7 +474,7 @@ class BatchTest(test_lib.TestCase): threads = queue_runner_impl.start_queue_runners() for i in range(num_batches): - results = sess.run(batched_fetch) + results = self.evaluate(batched_fetch) self.assertAllEqual(results[0], np.arange(i * batch_size, (i + 1) * batch_size)) self.assertAllEqual( @@ -539,7 +539,7 @@ class BatchTest(test_lib.TestCase): threads = queue_runner_impl.start_queue_runners() for i in range(num_batches): - results = sess.run(batched) + results = self.evaluate(batched) expected_results = np.arange(i * batch_size, (i + 1) * batch_size) max_len = expected_results[-1] self.assertAllEqual(results[0], expected_results) @@ -571,7 +571,7 @@ class BatchTest(test_lib.TestCase): threads = queue_runner_impl.start_queue_runners() for i in range(num_batches): - results = sess.run(batched) + results = self.evaluate(batched) self.assertAllEqual(results[0], np.arange(i * batch_size, (i + 1) * batch_size)) self.assertAllEqual( @@ -610,7 +610,7 @@ class BatchTest(test_lib.TestCase): all_counts = [] for i in range(num_batches): - results = sess.run(batched) + results = self.evaluate(batched) tf_logging.info("Batch %d: %s", i, results[0]) self.assertEqual(len(results[0]), batch_size) self.assertAllEqual(results[0], results[1].values) @@ -651,7 +651,7 @@ class BatchTest(test_lib.TestCase): threads = queue_runner_impl.start_queue_runners() for i in range(num_batches): - results = sess.run(batched) + results = self.evaluate(batched) self.assertAllEqual(results[0], np.arange(i * batch_size, (i + 1) * batch_size)) self.assertAllEqual( @@ -667,7 +667,7 @@ class BatchTest(test_lib.TestCase): self.assertAllEqual(results[2], [b"string"] * batch_size) # Reached the final batch with extra_elements. - results = sess.run(batched) + results = self.evaluate(batched) self.assertAllEqual(results[0], np.arange(num_batches * batch_size, num_batches * batch_size + extra_elements)) @@ -709,7 +709,7 @@ class BatchTest(test_lib.TestCase): all_counts = [] for i in range(num_batches): - results = sess.run(batched) + results = self.evaluate(batched) tf_logging.info("Batch %d: %s", i, results[0]) self.assertEqual(len(results[0]), batch_size) self.assertAllEqual(results[0], results[1].values) @@ -721,7 +721,7 @@ class BatchTest(test_lib.TestCase): self.assertAllEqual(results[2], [b"string"] * batch_size) # Reached the final batch with extra_elements. - results = sess.run(batched) + results = self.evaluate(batched) tf_logging.info("Last Batch: %s", results[0]) self.assertEqual(len(results[0]), extra_elements) self.assertAllEqual(results[0], results[1].values) @@ -827,7 +827,7 @@ class BatchTest(test_lib.TestCase): threads = queue_runner_impl.start_queue_runners() for _ in range(num_batches): - results = sess.run(batched) + results = self.evaluate(batched) self.assertAllEqual([0] * batch_size, np.mod(results[0], 2)) self.assertAllEqual([0] * batch_size, np.mod(results[1].values, 2)) self.assertAllEqual([b"string"] * batch_size, results[2]) @@ -1020,7 +1020,7 @@ class BatchJoinTest(test_lib.TestCase): saw_both = 0 num_batches = (num_a + num_b) // batch_size for i in range(num_batches): - results = sess.run(batched_fetch) + results = self.evaluate(batched_fetch) self.assertEqual(3, len(results)) self.assertEqual(batch_size, len(results[0])) self.assertEqual(batch_size, len(results[2])) @@ -1116,7 +1116,7 @@ class BatchJoinTest(test_lib.TestCase): saw_both = 0 num_batches = (num_a + num_b) // batch_size for i in range(num_batches): - results = sess.run(batched) + results = self.evaluate(batched) self.assertEqual(2, len(results)) self.assertEqual(len(results[0]), batch_size) self.assertEqual(len(results[1]), batch_size) @@ -1201,7 +1201,7 @@ class BatchJoinTest(test_lib.TestCase): saw_both = 0 num_batches = (num_a + num_b) // batch_size for i in range(num_batches): - results = sess.run(batched) + results = self.evaluate(batched) tf_logging.info("Batch %d: %s", i, results[0]) self.assertEqual(len(results[0]), batch_size) self.assertEqual(len(results[2]), batch_size) @@ -1221,7 +1221,7 @@ class BatchJoinTest(test_lib.TestCase): [results[0][i] for i in which_b]) # Reached the final batch with 2 * extra_elements. - results = sess.run(batched) + results = self.evaluate(batched) tf_logging.info("Last Batch: %s", results[0]) self.assertEqual(len(results[0]), 2 * extra_elements) self.assertEqual(len(results[2]), 2 * extra_elements) @@ -1296,7 +1296,7 @@ class BatchJoinTest(test_lib.TestCase): saw_both = 0 num_batches = (num_a + num_b) // batch_size for i in range(num_batches): - results = sess.run(batched) + results = self.evaluate(batched) tf_logging.info("Batch %d: %s", i, results[0]) self.assertEqual(len(results[0]), batch_size) self.assertEqual(len(results[1]), batch_size) @@ -1316,7 +1316,7 @@ class BatchJoinTest(test_lib.TestCase): [results[0][i] for i in which_b]) # Reached the final batch with 2 * extra_elements. - results = sess.run(batched) + results = self.evaluate(batched) tf_logging.info("Last Batch: %s", results[0]) self.assertEqual(len(results[0]), 2 * extra_elements) self.assertEqual(len(results[1]), 2 * extra_elements) @@ -1410,7 +1410,7 @@ class BatchJoinTest(test_lib.TestCase): threads = queue_runner_impl.start_queue_runners() for _ in range(num_batches): - results = sess.run(batched) + results = self.evaluate(batched) self.assertAllEqual( [0] * batch_size, np.mod(results[0], 2),) @@ -1579,7 +1579,7 @@ class ShuffleBatchTest(test_lib.TestCase): all_counts = [] for i in range(num_batches): - results = sess.run(batched_fetch) + results = self.evaluate(batched_fetch) self.assertEqual(len(results[0]), batch_size) all_counts.extend(results[0]) self.assertAllEqual( @@ -1634,7 +1634,7 @@ class ShuffleBatchTest(test_lib.TestCase): all_counts = [] for _ in range(num_batches): - results = sess.run(batched_fetch) + results = self.evaluate(batched_fetch) self.assertEqual(len(results[0]), batch_size) all_counts.extend(results[0]) self.assertAllEqual( @@ -1645,7 +1645,7 @@ class ShuffleBatchTest(test_lib.TestCase): self.assertAllEqual(results[2], [b"string"] * batch_size) # Reached the final batch with extra elements. - results = sess.run(batched) + results = self.evaluate(batched) self.assertAllEqual(results[1].dense_shape, [extra_elements, 1]) self.assertAllEqual(results[2], [b"string"] * extra_elements) all_counts.extend(results[0]) @@ -1687,7 +1687,7 @@ class ShuffleBatchTest(test_lib.TestCase): all_counts = [] for i in range(num_batches): - results = sess.run(batched) + results = self.evaluate(batched) tf_logging.info("Batch %d: %s", i, results[0]) self.assertEqual(len(results[0]), batch_size) all_counts.extend(results[0]) @@ -1737,7 +1737,7 @@ class ShuffleBatchTest(test_lib.TestCase): all_counts = [] for i in range(num_batches): - results = sess.run(batched) + results = self.evaluate(batched) tf_logging.info("Batch %d: %s", i, results[0]) self.assertEqual(len(results[0]), batch_size) all_counts.extend(results[0]) @@ -1749,7 +1749,7 @@ class ShuffleBatchTest(test_lib.TestCase): self.assertAllEqual(results[2], [b"string"] * batch_size) # Reached the final batch with extra elements. - results = sess.run(batched) + results = self.evaluate(batched) self.assertAllEqual(results[0].shape, [extra_elements]) self.assertAllEqual(results[1].dense_shape, [extra_elements, 1]) self.assertAllEqual(results[2], [b"string"] * extra_elements) @@ -1817,7 +1817,7 @@ class ShuffleBatchTest(test_lib.TestCase): threads = queue_runner_impl.start_queue_runners() for _ in range(num_batches): - results = sess.run(batched) + results = self.evaluate(batched) self.assertAllEqual([0] * batch_size, np.mod(results[0], 2)) self.assertAllEqual([0] * batch_size, np.mod(results[1].values, 2)) self.assertAllEqual([b"string"] * batch_size, results[2]) @@ -1990,7 +1990,7 @@ class ShuffleBatchJoinTest(test_lib.TestCase): saw_both = 0 num_batches = (num_a + num_b) // batch_size for i in range(num_batches): - results = sess.run(batched_fetch) + results = self.evaluate(batched_fetch) self.assertEqual(3, len(results)) self.assertEqual(len(results[0]), batch_size) self.assertEqual(len(results[2]), batch_size) @@ -2082,7 +2082,7 @@ class ShuffleBatchJoinTest(test_lib.TestCase): saw_both = 0 num_batches = (num_a + num_b) // batch_size for i in range(num_batches): - results = sess.run(batched) + results = self.evaluate(batched) tf_logging.info("Batch %d: %s", i, results[0]) self.assertEqual(len(results[0]), batch_size) self.assertEqual(len(results[2]), batch_size) @@ -2102,7 +2102,7 @@ class ShuffleBatchJoinTest(test_lib.TestCase): [results[0][i] for i in which_b]) # Reached end with 2 * extra_elements left - results = sess.run(batched) + results = self.evaluate(batched) self.assertEqual(len(results[0]), 2 * extra_elements) self.assertAllEqual(results[1].dense_shape, [2 * extra_elements, 1]) self.assertEqual(len(results[2]), 2 * extra_elements) @@ -2203,7 +2203,7 @@ class ShuffleBatchJoinTest(test_lib.TestCase): threads = queue_runner_impl.start_queue_runners() for _ in range(num_batches): - results = sess.run(batched) + results = self.evaluate(batched) self.assertAllEqual([0] * batch_size, np.mod(results[0], 2)) self.assertAllEqual([0] * batch_size, np.mod(results[1].values, 2)) self.assertAllEqual([b"string"] * batch_size, results[2]) diff --git a/tensorflow/python/training/monitored_session_test.py b/tensorflow/python/training/monitored_session_test.py index c870d99de9e..ebe2f15a559 100644 --- a/tensorflow/python/training/monitored_session_test.py +++ b/tensorflow/python/training/monitored_session_test.py @@ -1178,7 +1178,7 @@ class HookedSessionTest(test.TestCase): mock_run = FakeSession(sess) mon_sess = monitored_session._HookedSession(sess=mock_run, hooks=[]) a_tensor = constant_op.constant([0], name='a_tensor') - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) output = mon_sess.run(fetches=a_tensor, feed_dict='a_feed', options='an_option', @@ -1197,7 +1197,7 @@ class HookedSessionTest(test.TestCase): mon_sess = monitored_session._HookedSession( sess=sess, hooks=[mock_hook, mock_hook2]) a_tensor = constant_op.constant([0], name='a_tensor') - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) mon_sess.run(a_tensor) for hook in [mock_hook, mock_hook2]: @@ -1222,7 +1222,7 @@ class HookedSessionTest(test.TestCase): mon_sess = monitored_session._HookedSession( sess=sess, hooks=[mock_hook, mock_hook2]) constant_op.constant([0], name='a_tensor') - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) mon_sess.run(fetches='a_tensor') self.assertFalse(mon_sess.should_stop()) @@ -1242,7 +1242,7 @@ class HookedSessionTest(test.TestCase): third_tensor = constant_op.constant([10], name='third_tensor') mock_hook.request = session_run_hook.SessionRunArgs([another_tensor]) mock_hook2.request = session_run_hook.SessionRunArgs([third_tensor]) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) output = mon_sess.run(fetches=a_tensor) self.assertEqual(output, [0]) @@ -1262,7 +1262,7 @@ class HookedSessionTest(test.TestCase): None, feed_dict={a_tensor: [5]}) mock_hook2.request = session_run_hook.SessionRunArgs( None, feed_dict={b_tensor: [10]}) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) self.assertEqual(mon_sess.run(fetches=add_tensor), [15]) @@ -1280,7 +1280,7 @@ class HookedSessionTest(test.TestCase): None, feed_dict={a_tensor: [5]}) mock_hook2.request = session_run_hook.SessionRunArgs( None, feed_dict={b_tensor: [10]}) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) feed_dict = {c_tensor: [20]} self.assertEqual( @@ -1301,7 +1301,7 @@ class HookedSessionTest(test.TestCase): None, feed_dict={a_tensor: [5]}) mock_hook2.request = session_run_hook.SessionRunArgs( None, feed_dict={a_tensor: [10]}) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) with self.assertRaisesRegexp(RuntimeError, 'Same tensor is fed'): mon_sess.run(fetches=add_tensor) @@ -1319,7 +1319,7 @@ class HookedSessionTest(test.TestCase): None, feed_dict={a_tensor: [5]}) mock_hook2.request = session_run_hook.SessionRunArgs( None, feed_dict={b_tensor: [10]}) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) with self.assertRaisesRegexp(RuntimeError, 'Same tensor is fed'): mon_sess.run(fetches=add_tensor, feed_dict={b_tensor: [10]}) diff --git a/tensorflow/python/training/moving_averages_test.py b/tensorflow/python/training/moving_averages_test.py index 8009e3c24e7..41e9dcea842 100644 --- a/tensorflow/python/training/moving_averages_test.py +++ b/tensorflow/python/training/moving_averages_test.py @@ -274,14 +274,14 @@ class ExponentialMovingAverageTest(test.TestCase): self.assertEqual([], v1_avg.value().op.control_inputs) self.assertEqual([], v1_avg.value().op.control_inputs) # We should be able to initialize v1_avg before v0. - sess.run(v1_avg.initializer) - sess.run(v0.initializer) - self.assertEqual([10.0], sess.run(v1_avg)) + self.evaluate(v1_avg.initializer) + self.evaluate(v0.initializer) + self.assertEqual([10.0], self.evaluate(v1_avg)) # running ema_op should add to v0 (in addition to updating v1_avg) sess.run(assign_to_v1) - sess.run(ema_op) - self.assertEqual(1, sess.run(v0)) - self.assertEqual([17.5], sess.run(v1_avg)) + self.evaluate(ema_op) + self.assertEqual(1, self.evaluate(v0)) + self.assertEqual([17.5], self.evaluate(v1_avg)) @test_util.run_in_graph_and_eager_modes def testBasicEager(self): diff --git a/tensorflow/python/training/saver_test.py b/tensorflow/python/training/saver_test.py index eb2690985d5..7bc0a178a48 100644 --- a/tensorflow/python/training/saver_test.py +++ b/tensorflow/python/training/saver_test.py @@ -227,7 +227,7 @@ class SaverTest(test.TestCase): w1 = resource_variable_ops.ResourceVariable(1.0, name="w1") w2 = resource_variable_ops.ResourceVariable(2.0, name="w2") graph_saver = saver_module.Saver([w1, w2]) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) graph_saver.save(sess, graph_ckpt_prefix) with context.eager_mode(): @@ -260,7 +260,7 @@ class SaverTest(test.TestCase): w3 = resource_variable_ops.ResourceVariable(0.0, name="w3") w4 = resource_variable_ops.ResourceVariable(0.0, name="w4") graph_saver = saver_module.Saver([w3, w4]) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) graph_saver.restore(sess, eager_ckpt_prefix) self.assertAllEqual(w3.eval(), 3.0) self.assertAllEqual(w4.eval(), 4.0) @@ -326,7 +326,7 @@ class SaverTest(test.TestCase): with self.cached_session() as sess: # Initialize all variables - sess.run(init_all_op) + self.evaluate(init_all_op) # Check that the parameter nodes have been initialized. self.assertEqual(10.0, v0.eval()) @@ -376,7 +376,7 @@ class SaverTest(test.TestCase): with self.cached_session() as sess: tensor = sess.graph.get_tensor_by_name( save.saver_def.filename_tensor_name) - self.assertEqual(sess.run(tensor), filename) + self.assertEqual(self.evaluate(tensor), filename) def testInvalidPath(self): v0 = variables.VariableV1(0, name="v0") @@ -742,7 +742,7 @@ class SaverTest(test.TestCase): try: with self.cached_session() as sess: # Initialize all variables - sess.run(init_all_op) + self.evaluate(init_all_op) # Check that the parameter nodes have been initialized. self.assertEqual(10.0, v0.eval()) @@ -777,7 +777,7 @@ class SaverTest(test.TestCase): with self.cached_session() as sess: # Initialize all variables - sess.run(init_all_op) + self.evaluate(init_all_op) # Check that the parameter nodes have been initialized. self.assertEqual(10.0, v0.eval()) @@ -824,11 +824,11 @@ class SaverTest(test.TestCase): save_graph = ops_lib.Graph() with save_graph.as_default(), self.session(graph=save_graph) as sess: orig_vars = _model() - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) save = saver_module.Saver(max_to_keep=1) variables.global_variables_initializer().run() save.save(sess, save_dir) - orig_vals = sess.run(orig_vars) + orig_vals = self.evaluate(orig_vars) restore_graph = ops_lib.Graph() with restore_graph.as_default(), self.session( @@ -836,7 +836,7 @@ class SaverTest(test.TestCase): restored_vars = _model() save = saver_module.Saver(max_to_keep=1) save.restore(sess, save_dir) - restored_vals = sess.run(restored_vars) + restored_vals = self.evaluate(restored_vars) for orig, restored in zip(orig_vals, restored_vals): self.assertAllEqual(orig, restored) @@ -1949,7 +1949,7 @@ class MetaGraphTest(test.TestCase): with self.cached_session() as sess: # Initializes all the variables. - sess.run(init_all_op) + self.evaluate(init_all_op) # Runs to logit. sess.run(logits) # Creates a saver. @@ -1991,7 +1991,7 @@ class MetaGraphTest(test.TestCase): ops_lib.add_to_collection("train_op", train_op) # Runs train_op. - sess.run(train_op) + self.evaluate(train_op) # Generates MetaGraphDef. saver_module.export_meta_graph(train_filename) @@ -2005,7 +2005,7 @@ class MetaGraphTest(test.TestCase): # Restores from checkpoint. new_saver.restore(sess, saver0_ckpt) train_op = ops_lib.get_collection("train_op")[0] - sess.run(train_op) + self.evaluate(train_op) def testGraphExtension(self): test_dir = self._get_test_dir("graph_extension") @@ -2037,7 +2037,7 @@ class MetaGraphTest(test.TestCase): # Generate a MetaGraphDef containing the while loop. with session.Session() as sess: - sess.run(init_op) + self.evaluate(init_op) sess.run(output) saver = saver_module.Saver() saver.save(sess, saver_ckpt) @@ -2053,8 +2053,8 @@ class MetaGraphTest(test.TestCase): no_constfold_config.graph_options.rewrite_options.constant_folding = ( rewriter_config_pb2.RewriterConfig.OFF) with session.Session(config=no_constfold_config) as sess: - sess.run(init_op) - expected_grad_value = sess.run(grad) + self.evaluate(init_op) + expected_grad_value = self.evaluate(grad) # Restore the MetaGraphDef into a new Graph. with ops_lib.Graph().as_default(): @@ -2070,8 +2070,8 @@ class MetaGraphTest(test.TestCase): init_op = variables.global_variables_initializer() with session.Session(config=no_constfold_config) as sess: - sess.run(init_op) - actual_grad_value = sess.run(grad) + self.evaluate(init_op) + actual_grad_value = self.evaluate(grad) self.assertEqual(expected_grad_value, actual_grad_value) def _testWhileLoopAndGradientSerDes(self, outer_body_fn): @@ -2209,7 +2209,7 @@ class MetaGraphTest(test.TestCase): logits=logit, name="cost") adam.AdamOptimizer().minimize(cost, name="optimize") saver = saver_module.Saver() - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) saver.save(sess, filename) graph = ops_lib.Graph() @@ -2246,7 +2246,7 @@ class MetaGraphTest(test.TestCase): # Create a variable in graph_2 under scope "my_scope". variables.VariableV1(array_ops.zeros([10]), name="my_scope/my_var") - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) # Restore the checkpoint into a different scope "subgraph_2". new_saver_2 = saver_module.import_meta_graph( filename + ".meta", graph=graph_2, import_scope="subgraph_2") @@ -2279,7 +2279,7 @@ class MetaGraphTest(test.TestCase): logits=logit, name="cost") adam.AdamOptimizer().minimize(cost, name="optimize") saver = saver_module.Saver() - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) saver.save(sess, filename) graph = ops_lib.Graph() @@ -2316,12 +2316,12 @@ class MetaGraphTest(test.TestCase): meta_graph_def, clear_devices=False, import_scope="new_model") # Device refers to GPU, which is not available here. with self.assertRaises(errors_impl.InvalidArgumentError): - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) with session.Session(graph=ops_lib.Graph()) as sess: saver_module.import_meta_graph( meta_graph_def, clear_devices=True, import_scope="new_model") - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) sess.run(["new_model/optimize"], { "new_model/image:0": np.random.random([1, 784]), "new_model/label:0": np.random.randint( @@ -2348,7 +2348,7 @@ class MetaGraphTest(test.TestCase): with session.Session(graph=ops_lib.Graph()) as sess: saver_module.import_meta_graph(meta_graph_def, import_scope="new_model") - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) sess.run(["new_model/optimize"], { "new_model/image:0": np.random.random([1, 784]), "new_model/label:0": np.random.randint( @@ -2374,7 +2374,7 @@ class MetaGraphTest(test.TestCase): meta_graph_def_from_graph_def]: with session.Session(graph=ops_lib.Graph()) as sess: saver_module.import_meta_graph(meta_graph_def, import_scope="new_model") - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) for i in range(10): self.assertEqual(i * i, sess.run("new_model/output:0")) with self.assertRaises(errors.OutOfRangeError): @@ -2400,7 +2400,7 @@ class CheckpointReaderTest(test.TestCase): save_path = os.path.join(self.get_temp_dir(), "ckpt_for_debug_string" + str(self._WRITE_VERSION)) with self.cached_session() as sess: - sess.run(init_all_op) + self.evaluate(init_all_op) # Saves a checkpoint. save.save(sess, save_path) @@ -2546,7 +2546,7 @@ class ScopedGraphTest(test.TestCase): self.assertEqual(["biases:0", "weights:0"], sorted(var_list.keys())) with self.session(graph=graph) as sess: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) saver = saver_module.Saver(var_list=var_list, max_to_keep=1) saver.save(sess, os.path.join(test_dir, ckpt_filename), write_state=False) @@ -2611,7 +2611,7 @@ class ScopedGraphTest(test.TestCase): # Verify that we have restored weights1 and biases1. sess.run([weights1, biases1]) # Initialize the rest of the variables and run logits. - sess.run(init_rest_op) + self.evaluate(init_rest_op) sess.run(logits) # Verifies that we can save the subgraph under "hidden1" and restore it @@ -2640,7 +2640,7 @@ class ScopedGraphTest(test.TestCase): # Run the graph and save scoped checkpoint. with self.session(graph=graph1) as sess: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) _, var_list_1 = meta_graph.export_scoped_meta_graph( export_scope="hidden1") saver = saver_module.Saver(var_list=var_list_1, max_to_keep=1) @@ -2696,7 +2696,7 @@ class ScopedGraphTest(test.TestCase): # Run the graph and save scoped checkpoint. with self.session(graph=graph1) as sess: - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) _, var_list_1 = meta_graph.export_scoped_meta_graph( graph_def=graph1.as_graph_def(), export_scope="hidden1") saver = saver_module.Saver(var_list=var_list_1, max_to_keep=1) @@ -2964,7 +2964,7 @@ class CheckpointableCompatibilityTests(test.TestCase): a_saver = saver_module.Saver([a]) b_saver = saver_module.Saver([b]) with self.cached_session() as sess: - sess.run(a.initializer) + self.evaluate(a.initializer) save_path = a_saver.save(sess=sess, save_path=checkpoint_prefix) with self.assertRaisesRegexp( errors.NotFoundError, "Key b not found in checkpoint"): @@ -2986,7 +2986,7 @@ class CheckpointableCompatibilityTests(test.TestCase): a_saver = saver_module.Saver([a]) with self.session(graph=g) as sess: - sess.run(a.initializer) + self.evaluate(a.initializer) save_path = a_saver.save(sess=sess, save_path=checkpoint_prefix) with ops_lib.Graph().as_default() as g: diff --git a/tensorflow/python/training/server_lib_sparse_job_test.py b/tensorflow/python/training/server_lib_sparse_job_test.py index 1a6b44b90e8..8c2745b51aa 100644 --- a/tensorflow/python/training/server_lib_sparse_job_test.py +++ b/tensorflow/python/training/server_lib_sparse_job_test.py @@ -36,7 +36,7 @@ class SparseJobTest(test.TestCase): a = constant_op.constant(1.0) with session.Session(server.target) as sess: - self.assertEqual(1.0, sess.run(a)) + self.assertEqual(1.0, self.evaluate(a)) if __name__ == "__main__": diff --git a/tensorflow/python/training/supervisor_test.py b/tensorflow/python/training/supervisor_test.py index b734e9653ea..9dc88d78ccc 100644 --- a/tensorflow/python/training/supervisor_test.py +++ b/tensorflow/python/training/supervisor_test.py @@ -100,7 +100,7 @@ class SupervisorTest(test.TestCase): sv = supervisor.Supervisor(logdir=logdir) sess = sv.prepare_or_wait_for_session("") for _ in xrange(10): - sess.run(my_op) + self.evaluate(my_op) sess.close() sv.stop() @@ -111,7 +111,7 @@ class SupervisorTest(test.TestCase): sv = supervisor.Supervisor(logdir=logdir) with sv.managed_session("") as sess: for _ in xrange(10): - sess.run(my_op) + self.evaluate(my_op) # Supervisor has been stopped. self.assertTrue(sv.should_stop()) @@ -128,7 +128,7 @@ class SupervisorTest(test.TestCase): if step == 1: raise RuntimeError("failing here") else: - sess.run(my_op) + self.evaluate(my_op) # Supervisor has been stopped. self.assertTrue(sv.should_stop()) self.assertEqual(1, last_step) @@ -146,7 +146,7 @@ class SupervisorTest(test.TestCase): raise errors_impl.OutOfRangeError(my_op.op.node_def, my_op.op, "all done") else: - sess.run(my_op) + self.evaluate(my_op) # Supervisor has been stopped. OutOfRangeError was not thrown. self.assertTrue(sv.should_stop()) self.assertEqual(3, last_step) @@ -335,7 +335,7 @@ class SupervisorTest(test.TestCase): sess = sv.prepare_or_wait_for_session( "", config=config_pb2.ConfigProto(device_count={"CPU": 2})) for _ in xrange(10): - sess.run(my_op) + self.evaluate(my_op) sess.close() sv.stop() diff --git a/tensorflow/python/training/warm_starting_util_test.py b/tensorflow/python/training/warm_starting_util_test.py index b575b8d364c..f1e719e6dbe 100644 --- a/tensorflow/python/training/warm_starting_util_test.py +++ b/tensorflow/python/training/warm_starting_util_test.py @@ -49,7 +49,7 @@ class WarmStartingUtilTest(test.TestCase): return vocab_file def _write_checkpoint(self, sess): - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) saver = saver_lib.Saver() ckpt_prefix = os.path.join(self.get_temp_dir(), "model") saver.save(sess, ckpt_prefix, global_step=0) @@ -125,7 +125,7 @@ class WarmStartingUtilTest(test.TestCase): prev_tensor_name, var = ws_util._get_var_info(fruit_weights) checkpoint_utils.init_from_checkpoint(self.get_temp_dir(), {prev_tensor_name: var}) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) self.assertAllClose(prev_val, fruit_weights.eval(sess)) def testWarmStartVarPrevVarPartitioned(self): @@ -143,7 +143,7 @@ class WarmStartingUtilTest(test.TestCase): prev_tensor_name, var = ws_util._get_var_info(fruit_weights) checkpoint_utils.init_from_checkpoint(self.get_temp_dir(), {prev_tensor_name: var}) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) self.assertAllClose(prev_val, fruit_weights.eval(sess)) def testWarmStartVarCurrentVarPartitioned(self): @@ -162,7 +162,7 @@ class WarmStartingUtilTest(test.TestCase): prev_tensor_name, var = ws_util._get_var_info(fruit_weights) checkpoint_utils.init_from_checkpoint(self.get_temp_dir(), {prev_tensor_name: var}) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) fruit_weights = fruit_weights._get_variable_list() new_val = np.concatenate( [fruit_weights[0].eval(sess), fruit_weights[1].eval(sess)], axis=0) @@ -189,7 +189,7 @@ class WarmStartingUtilTest(test.TestCase): fruit_weights, prev_tensor_name="old_scope/fruit_weights") checkpoint_utils.init_from_checkpoint(self.get_temp_dir(), {prev_tensor_name: var}) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) fruit_weights = fruit_weights._get_variable_list() new_val = np.concatenate( [fruit_weights[0].eval(sess), fruit_weights[1].eval(sess)], axis=0) @@ -211,7 +211,7 @@ class WarmStartingUtilTest(test.TestCase): "fruit_weights", initializer=[[0.], [0.], [0.], [0.], [0.]]) ws_util._warm_start_var_with_vocab(fruit_weights, new_vocab_path, 5, self.get_temp_dir(), prev_vocab_path) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) self.assertAllClose([[2.], [1.5], [1.], [0.5], [0.]], fruit_weights.eval(sess)) @@ -236,7 +236,7 @@ class WarmStartingUtilTest(test.TestCase): prev_ckpt=self.get_temp_dir(), prev_vocab_path=prev_vocab_path, axis=1) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) self.assertAllClose([[0.3, 0.5, 0.], [0.8, 1.0, 0.], [1.2, 1.5, 0.], [2.3, 2., 0.]], fruit_output_layer.eval(sess)) @@ -261,7 +261,7 @@ class WarmStartingUtilTest(test.TestCase): self.get_temp_dir(), prev_vocab_path, previous_vocab_size=2) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) # Old vocabulary limited to ['apple', 'banana']. self.assertAllClose([[0.], [0.], [1.], [0.5], [0.]], fruit_weights.eval(sess)) @@ -285,7 +285,7 @@ class WarmStartingUtilTest(test.TestCase): "fruit_weights", initializer=[[0.], [0.], [0.], [0.], [0.]]) ws_util._warm_start_var_with_vocab(fruit_weights, new_vocab_path, 5, self.get_temp_dir(), prev_vocab_path) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) self.assertAllClose([[2.], [1.5], [1.], [0.5], [0.]], fruit_weights.eval(sess)) @@ -312,7 +312,7 @@ class WarmStartingUtilTest(test.TestCase): prev_ckpt=self.get_temp_dir(), prev_vocab_path=prev_vocab_path, axis=1) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) self.assertAllClose([[0.3, 0.5, 0.], [0.8, 1.0, 0.], [1.2, 1.5, 0.], [2.3, 2., 0.]], fruit_output_layer.eval(sess)) @@ -340,7 +340,7 @@ class WarmStartingUtilTest(test.TestCase): self.get_temp_dir(), prev_vocab_path, current_oov_buckets=1) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) self.assertTrue( isinstance(fruit_weights, variables.PartitionedVariable)) fruit_weights_vars = fruit_weights._get_variable_list() @@ -372,7 +372,7 @@ class WarmStartingUtilTest(test.TestCase): prev_ckpt=self.get_temp_dir(), prev_vocab_path=prev_vocab_path, axis=1) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) self.assertTrue( isinstance(fruit_output_layer, variables.PartitionedVariable)) fruit_output_layer_vars = fruit_output_layer._get_variable_list() @@ -404,7 +404,7 @@ class WarmStartingUtilTest(test.TestCase): partitioner=lambda shape, dtype: [2, 1]) ws_util._warm_start_var_with_vocab(fruit_weights, new_vocab_path, 6, self.get_temp_dir(), prev_vocab_path) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) self.assertTrue( isinstance(fruit_weights, variables.PartitionedVariable)) fruit_weights_vars = fruit_weights._get_variable_list() @@ -438,7 +438,7 @@ class WarmStartingUtilTest(test.TestCase): prev_ckpt=self.get_temp_dir(), prev_vocab_path=prev_vocab_path, axis=1) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) self.assertTrue( isinstance(fruit_output_layer, variables.PartitionedVariable)) fruit_output_layer_vars = fruit_output_layer._get_variable_list() @@ -463,7 +463,7 @@ class WarmStartingUtilTest(test.TestCase): shape=[10, 1], initializer=zeros()) ws_util.warm_start(self.get_temp_dir(), vars_to_warm_start=[var]) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) # Verify weights were correctly warm-started (init overridden to ones). self.assertAllEqual(var.eval(), prev_int_val) @@ -483,7 +483,7 @@ class WarmStartingUtilTest(test.TestCase): shape=[10, 1], initializer=zeros()) ws_util.warm_start(self.get_temp_dir(), vars_to_warm_start=["v1"]) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) # Verify weights were correctly warm-started (init overridden to ones). self.assertAllEqual(var.eval(), prev_int_val) @@ -519,7 +519,7 @@ class WarmStartingUtilTest(test.TestCase): # This warm-starts both v1 and v1/Momentum, but only # v2 (and not v2/Momentum). vars_to_warm_start=["v1", "v2[^/]"]) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) # Verify the selection of weights were correctly warm-started (init # overridden to ones). self.assertAllEqual(v1.eval(), prev_v1_val) @@ -542,7 +542,7 @@ class WarmStartingUtilTest(test.TestCase): with ops.Graph().as_default() as g: with self.session(graph=g) as sess: cols_to_vars = self._create_linear_model([sc_int], partitioner) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) # Without warm-starting, the weights should be initialized using default # initializer (which is init_ops.zeros_initializer). self._assert_cols_to_vars(cols_to_vars, {sc_int: [np.zeros([10, 1])]}, @@ -553,7 +553,7 @@ class WarmStartingUtilTest(test.TestCase): with self.session(graph=g) as sess: cols_to_vars = self._create_linear_model([sc_int], partitioner) ws_util.warm_start(self.get_temp_dir(), vars_to_warm_start=".*sc_int.*") - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) # Verify weights were correctly warm-started. self._assert_cols_to_vars(cols_to_vars, {sc_int: [prev_int_val]}, sess) @@ -571,7 +571,7 @@ class WarmStartingUtilTest(test.TestCase): with ops.Graph().as_default() as g: with self.session(graph=g) as sess: cols_to_vars = self._create_linear_model([sc_hash], partitioner) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) # Without warm-starting, the weights should be initialized using default # initializer (which is init_ops.zeros_initializer). self._assert_cols_to_vars(cols_to_vars, {sc_hash: [np.zeros([15, 1])]}, @@ -583,7 +583,7 @@ class WarmStartingUtilTest(test.TestCase): cols_to_vars = self._create_linear_model([sc_hash], partitioner) ws_util.warm_start( self.get_temp_dir(), vars_to_warm_start=".*sc_hash.*") - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) # Verify weights were correctly warm-started. self._assert_cols_to_vars(cols_to_vars, {sc_hash: [prev_hash_val]}, sess) @@ -605,7 +605,7 @@ class WarmStartingUtilTest(test.TestCase): with ops.Graph().as_default() as g: with self.session(graph=g) as sess: cols_to_vars = self._create_linear_model([sc_vocab], partitioner) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) # Without warm-starting, the weights should be initialized using default # initializer (which is init_ops.zeros_initializer). self._assert_cols_to_vars(cols_to_vars, {sc_vocab: [np.zeros([4, 1])]}, @@ -619,7 +619,7 @@ class WarmStartingUtilTest(test.TestCase): # vocab is assumed to be same as new vocab. ws_util.warm_start( self.get_temp_dir(), vars_to_warm_start=".*sc_vocab.*") - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) # Verify weights were correctly warm-started. self._assert_cols_to_vars(cols_to_vars, {sc_vocab: [prev_vocab_val]}, sess) @@ -641,7 +641,7 @@ class WarmStartingUtilTest(test.TestCase): with ops.Graph().as_default() as g: with self.session(graph=g) as sess: cols_to_vars = self._create_linear_model([sc_vocab], partitioner) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) # Without warm-starting, the weights should be initialized using default # initializer (which is init_ops.zeros_initializer). self._assert_cols_to_vars(cols_to_vars, {sc_vocab: [np.zeros([4, 1])]}, @@ -657,7 +657,7 @@ class WarmStartingUtilTest(test.TestCase): # Explicitly provide the file prefix instead of just the dir. os.path.join(self.get_temp_dir(), "model-0"), vars_to_warm_start=".*sc_vocab.*") - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) # Verify weights were correctly warm-started. self._assert_cols_to_vars(cols_to_vars, {sc_vocab: [prev_vocab_val]}, sess) @@ -686,7 +686,7 @@ class WarmStartingUtilTest(test.TestCase): with ops.Graph().as_default() as g: with self.session(graph=g) as sess: cols_to_vars = self._create_linear_model([sc_vocab], partitioner) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) # Without warm-starting, the weights should be initialized using default # initializer (which is init_ops.zeros_initializer). self._assert_cols_to_vars(cols_to_vars, {sc_vocab: [np.zeros([2, 1])]}, @@ -708,7 +708,7 @@ class WarmStartingUtilTest(test.TestCase): var_name_to_vocab_info={ "linear_model/sc_vocab/weights": vocab_info }) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) # Verify weights were correctly warm-started. 'banana' isn't in the # first two entries of the old vocabulary, so it's newly initialized. self._assert_cols_to_vars(cols_to_vars, {sc_vocab: [[[1], [0]]]}, sess) @@ -729,7 +729,7 @@ class WarmStartingUtilTest(test.TestCase): with ops.Graph().as_default() as g: with self.session(graph=g) as sess: cols_to_vars = self._create_linear_model([real_bucket], partitioner) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) # Without warm-starting, the weights should be initialized using default # initializer (which is init_ops.zeros_initializer). self._assert_cols_to_vars(cols_to_vars, @@ -741,7 +741,7 @@ class WarmStartingUtilTest(test.TestCase): cols_to_vars = self._create_linear_model([real_bucket], partitioner) ws_util.warm_start( self.get_temp_dir(), vars_to_warm_start=".*real_bucketized.*") - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) # Verify weights were correctly warm-started. self._assert_cols_to_vars(cols_to_vars, {real_bucket: [prev_bucket_val]}, sess) @@ -800,7 +800,7 @@ class WarmStartingUtilTest(test.TestCase): with ops.Graph().as_default() as g: with self.session(graph=g) as sess: cols_to_vars = self._create_linear_model(all_linear_cols, partitioner) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) # Without warm-starting, all weights should be initialized using default # initializer (which is init_ops.zeros_initializer). self._assert_cols_to_vars(cols_to_vars, { @@ -826,7 +826,7 @@ class WarmStartingUtilTest(test.TestCase): var_name_to_vocab_info={ "linear_model/sc_vocab/weights": vocab_info }) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) # Verify weights were correctly warm-started. self._assert_cols_to_vars(cols_to_vars, { sc_int: [prev_int_val], @@ -865,7 +865,7 @@ class WarmStartingUtilTest(test.TestCase): "linear_model/sc_vocab/weights", initializer=[[0.5], [1.], [2.], [3.]]) self._write_checkpoint(sess) - prev_keys_val = sess.run(sc_keys_weights) + prev_keys_val = self.evaluate(sc_keys_weights) def _partitioner(shape, dtype): # pylint:disable=unused-argument # Partition each var into 2 equal slices. @@ -892,7 +892,7 @@ class WarmStartingUtilTest(test.TestCase): ws_util._infer_var_name(cols_to_vars[sc_keys]): "some_other_name" }) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) # Verify weights were correctly warm-started. Var corresponding to # sc_hash should not be warm-started. Var corresponding to sc_vocab # should be correctly warm-started after vocab remapping. @@ -933,7 +933,7 @@ class WarmStartingUtilTest(test.TestCase): "linear_model/sc_vocab/weights", initializer=[[0.5], [1.], [2.], [3.]]) self._write_checkpoint(sess) - prev_keys_val = sess.run(sc_keys_weights) + prev_keys_val = self.evaluate(sc_keys_weights) # New graph, new session with warm-starting. with ops.Graph().as_default() as g: @@ -955,7 +955,7 @@ class WarmStartingUtilTest(test.TestCase): ws_util._infer_var_name(cols_to_vars[sc_keys]): "some_other_name" }) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) # Verify weights were correctly warm-started. Var corresponding to # sc_hash should not be warm-started. Var corresponding to sc_vocab # should be correctly warm-started after vocab remapping. @@ -1024,7 +1024,7 @@ class WarmStartingUtilTest(test.TestCase): ws_util._infer_var_name(cols_to_vars[sc_keys]): "some_other_name" }) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) # Verify weights were correctly warm-started. Var corresponding to # sc_vocab should be correctly warm-started after vocab remapping, # and neither of the other two should be warm-started.. @@ -1091,7 +1091,7 @@ class WarmStartingUtilTest(test.TestCase): ws_util._infer_var_name(cols_to_vars[emb_vocab_column]): vocab_info }) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) # Verify weights were correctly warm-started. Var corresponding to # emb_vocab_column should be correctly warm-started after vocab # remapping. Missing values are filled in with the EmbeddingColumn's @@ -1163,7 +1163,7 @@ class WarmStartingUtilTest(test.TestCase): var_name_to_vocab_info={ "linear_model/sc_vocab_embedding/embedding_weights": vocab_info }) - sess.run(variables.global_variables_initializer()) + self.evaluate(variables.global_variables_initializer()) # Verify weights were correctly warm-started. Var corresponding to # emb_vocab should be correctly warm-started after vocab remapping. # Missing values are filled in with the EmbeddingColumn's initializer.