diff --git a/tensorflow/python/data/experimental/kernel_tests/optimization/inject_prefetch_test.py b/tensorflow/python/data/experimental/kernel_tests/optimization/inject_prefetch_test.py index 17115474529..4e908ead618 100644 --- a/tensorflow/python/data/experimental/kernel_tests/optimization/inject_prefetch_test.py +++ b/tensorflow/python/data/experimental/kernel_tests/optimization/inject_prefetch_test.py @@ -19,7 +19,6 @@ from __future__ import print_function from absl.testing import parameterized -from tensorflow.python.compat import compat from tensorflow.python.data.experimental.ops import testing from tensorflow.python.data.kernel_tests import test_base from tensorflow.python.data.ops import dataset_ops @@ -37,11 +36,8 @@ class InjectPrefetchTest(test_base.DatasetTestBase, parameterized.TestCase): @combinations.generate(test_base.default_test_combinations()) def testParallelMap(self): dataset = dataset_ops.Dataset.range(100) - parallel_map = "ParallelMap" - if compat.forward_compatible(2020, 3, 6): - parallel_map = "ParallelMapV2" dataset = dataset.apply( - testing.assert_next([parallel_map, "Prefetch", "FiniteTake"])) + testing.assert_next(["ParallelMapV2", "Prefetch", "FiniteTake"])) dataset = dataset.map( lambda x: x + 1, num_parallel_calls=dataset_ops.AUTOTUNE) dataset = dataset.take(50) @@ -64,11 +60,8 @@ class InjectPrefetchTest(test_base.DatasetTestBase, parameterized.TestCase): @combinations.generate(test_base.default_test_combinations()) def testParallelInterleave(self): dataset = dataset_ops.Dataset.range(100) - parallel_interleave = "ParallelInterleaveV3" - if compat.forward_compatible(2020, 3, 6): - parallel_interleave = "ParallelInterleaveV4" dataset = dataset.apply( - testing.assert_next([parallel_interleave, "Prefetch", "FiniteTake"])) + testing.assert_next(["ParallelInterleaveV4", "Prefetch", "FiniteTake"])) dataset = dataset.interleave( lambda x: dataset_ops.Dataset.from_tensors(x + 1), num_parallel_calls=dataset_ops.AUTOTUNE) @@ -79,15 +72,9 @@ class InjectPrefetchTest(test_base.DatasetTestBase, parameterized.TestCase): @combinations.generate(test_base.default_test_combinations()) def testChainedParallelDatasets(self): dataset = dataset_ops.Dataset.range(100) - parallel_interleave = "ParallelInterleaveV3" - if compat.forward_compatible(2020, 3, 6): - parallel_interleave = "ParallelInterleaveV4" - parallel_map = "ParallelMap" - if compat.forward_compatible(2020, 3, 6): - parallel_map = "ParallelMapV2" dataset = dataset.apply( testing.assert_next([ - parallel_map, "Prefetch", parallel_interleave, "Prefetch", + "ParallelMapV2", "Prefetch", "ParallelInterleaveV4", "Prefetch", "MapAndBatch", "Prefetch", "FiniteTake" ])) dataset = dataset.map( diff --git a/tensorflow/python/data/experimental/kernel_tests/optimization/map_vectorization_test.py b/tensorflow/python/data/experimental/kernel_tests/optimization/map_vectorization_test.py index 4b3f811119b..d1a68931d38 100644 --- a/tensorflow/python/data/experimental/kernel_tests/optimization/map_vectorization_test.py +++ b/tensorflow/python/data/experimental/kernel_tests/optimization/map_vectorization_test.py @@ -25,7 +25,6 @@ import numpy as np from tensorflow.core.example import example_pb2 from tensorflow.core.example import feature_pb2 -from tensorflow.python.compat import compat from tensorflow.python.data.experimental.ops import batching from tensorflow.python.data.experimental.ops import testing from tensorflow.python.data.kernel_tests import test_base @@ -222,9 +221,7 @@ class MapVectorizationTest(test_base.DatasetTestBase, parameterized.TestCase): """ map_node_name = "Map" if num_parallel_calls is not None: - map_node_name = "ParallelMap" - if compat.forward_compatible(2020, 3, 6): - map_node_name = "ParallelMapV2" + map_node_name = "ParallelMapV2" def _make_dataset(node_names): dataset = base_dataset.apply(testing.assert_next(node_names)) diff --git a/tensorflow/python/data/experimental/kernel_tests/optimization/noop_elimination_test.py b/tensorflow/python/data/experimental/kernel_tests/optimization/noop_elimination_test.py index b5cbc56e2f0..f564fac4f1b 100644 --- a/tensorflow/python/data/experimental/kernel_tests/optimization/noop_elimination_test.py +++ b/tensorflow/python/data/experimental/kernel_tests/optimization/noop_elimination_test.py @@ -21,7 +21,6 @@ import functools from absl.testing import parameterized -from tensorflow.python.compat import compat from tensorflow.python.data.experimental.ops import testing from tensorflow.python.data.kernel_tests import test_base from tensorflow.python.data.ops import dataset_ops @@ -51,8 +50,7 @@ def _test_combinations(): ds = ds.map(lambda x: (x, x), num_parallel_calls=2) # Not eliminated return ds.map(lambda x, y: (x, y)) # Eliminated - parallel_map_name = "ParallelMapV2" if compat.forward_compatible( - 2020, 3, 6) else "ParallelMap" + parallel_map_name = "ParallelMapV2" cases = [ ("Skip0", lambda ds: ds.skip(0), None), diff --git a/tensorflow/python/data/experimental/ops/parsing_ops.py b/tensorflow/python/data/experimental/ops/parsing_ops.py index 8cd9300e01e..ca947abe3cc 100644 --- a/tensorflow/python/data/experimental/ops/parsing_ops.py +++ b/tensorflow/python/data/experimental/ops/parsing_ops.py @@ -17,7 +17,6 @@ from __future__ import absolute_import from __future__ import division from __future__ import print_function -from tensorflow.python.compat import compat from tensorflow.python.data.ops import dataset_ops from tensorflow.python.data.util import structure from tensorflow.python.framework import dtypes @@ -85,35 +84,20 @@ class _ParseExampleDataset(dataset_ops.UnaryDataset): self._element_spec[key] = ragged_tensor.RaggedTensorSpec( input_dataset_shape.concatenate([None]), value_type, 1, splits_type) - if deterministic is not None or compat.forward_compatible(2020, 3, 6): - variant_tensor = ( - gen_experimental_dataset_ops.parse_example_dataset_v2( - self._input_dataset._variant_tensor, # pylint: disable=protected-access - self._num_parallel_calls, - self._dense_defaults, - self._sparse_keys, - self._dense_keys, - self._sparse_types, - self._dense_shapes, - deterministic=self._deterministic, - ragged_keys=self._ragged_keys, - ragged_value_types=self._ragged_value_types, - ragged_split_types=self._ragged_split_types, - **self._flat_structure)) - else: - variant_tensor = ( - gen_experimental_dataset_ops.parse_example_dataset( - self._input_dataset._variant_tensor, # pylint: disable=protected-access - self._num_parallel_calls, - self._dense_defaults, - self._sparse_keys, - self._dense_keys, - self._sparse_types, - self._dense_shapes, - ragged_keys=self._ragged_keys, - ragged_value_types=self._ragged_value_types, - ragged_split_types=self._ragged_split_types, - **self._flat_structure)) + variant_tensor = ( + gen_experimental_dataset_ops.parse_example_dataset_v2( + self._input_dataset._variant_tensor, # pylint: disable=protected-access + self._num_parallel_calls, + self._dense_defaults, + self._sparse_keys, + self._dense_keys, + self._sparse_types, + self._dense_shapes, + deterministic=self._deterministic, + ragged_keys=self._ragged_keys, + ragged_value_types=self._ragged_value_types, + ragged_split_types=self._ragged_split_types, + **self._flat_structure)) super(_ParseExampleDataset, self).__init__(input_dataset, variant_tensor) @property diff --git a/tensorflow/python/data/ops/readers.py b/tensorflow/python/data/ops/readers.py index e37e68a0256..dbc580ce331 100644 --- a/tensorflow/python/data/ops/readers.py +++ b/tensorflow/python/data/ops/readers.py @@ -18,7 +18,6 @@ from __future__ import division from __future__ import print_function from tensorflow.python import tf2 -from tensorflow.python.compat import compat from tensorflow.python.data.ops import dataset_ops from tensorflow.python.data.util import convert from tensorflow.python.framework import dtypes @@ -249,9 +248,6 @@ class ParallelInterleaveDataset(dataset_ops.UnaryDataset): cycle_length, dtype=dtypes.int64, name="cycle_length") self._block_length = ops.convert_to_tensor( block_length, dtype=dtypes.int64, name="block_length") - if sloppy is not None: - self._sloppy = ops.convert_to_tensor( - sloppy, dtype=dtypes.bool, name="sloppy") self._buffer_output_elements = convert.optional_param_to_tensor( "buffer_output_elements", buffer_output_elements, @@ -260,34 +256,22 @@ class ParallelInterleaveDataset(dataset_ops.UnaryDataset): "prefetch_input_elements", prefetch_input_elements, argument_default=2 * cycle_length) - if sloppy is None or compat.forward_compatible(2020, 3, 6): - if sloppy is None: - self._deterministic = "default" - elif sloppy: - self._deterministic = "false" - else: - self._deterministic = "true" - variant_tensor = ged_ops.legacy_parallel_interleave_dataset_v2( - self._input_dataset._variant_tensor, # pylint: disable=protected-access - self._map_func.function.captured_inputs, - self._cycle_length, - self._block_length, - self._buffer_output_elements, - self._prefetch_input_elements, - f=self._map_func.function, - deterministic=self._deterministic, - **self._flat_structure) + if sloppy is None: + self._deterministic = "default" + elif sloppy: + self._deterministic = "false" else: - variant_tensor = ged_ops.parallel_interleave_dataset( - self._input_dataset._variant_tensor, # pylint: disable=protected-access - self._map_func.function.captured_inputs, - self._cycle_length, - self._block_length, - self._sloppy, - self._buffer_output_elements, - self._prefetch_input_elements, - f=self._map_func.function, - **self._flat_structure) + self._deterministic = "true" + variant_tensor = ged_ops.legacy_parallel_interleave_dataset_v2( + self._input_dataset._variant_tensor, # pylint: disable=protected-access + self._map_func.function.captured_inputs, + self._cycle_length, + self._block_length, + self._buffer_output_elements, + self._prefetch_input_elements, + f=self._map_func.function, + deterministic=self._deterministic, + **self._flat_structure) super(ParallelInterleaveDataset, self).__init__(input_dataset, variant_tensor)