/external/tensorflow/tensorflow/python/data/experimental/kernel_tests/optimization/ |
D | autotune_buffer_sizes_test.py | 32 def _enable_autotune_buffers(self, dataset): argument 35 return dataset.with_options(options) 39 dataset = dataset_ops.Dataset.range(100) 40 dataset = dataset.apply( 42 dataset = dataset.map( 44 dataset = dataset.take(50) 45 dataset = self._enable_autotune_buffers(dataset) 46 self.assertDatasetProduces(dataset, range(1, 51)) 50 dataset = dataset_ops.Dataset.range(100) 51 dataset = dataset.apply( [all …]
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D | reorder_data_discarding_ops_test.py | 35 dataset = dataset_ops.Dataset.range(100) 36 dataset = dataset.apply( 39 dataset = dataset.map(lambda x: x + 1, num_parallel_calls=10) 40 dataset = dataset.skip(10) 41 dataset = dataset.prefetch(1) 42 dataset = dataset.take(50) 43 dataset = dataset.shard(2, 0) 47 dataset = dataset.with_options(options) 48 self.assertDatasetProduces(dataset, range(11, 61, 2)) 53 dataset = dataset_ops.Dataset.range(100) [all …]
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D | choose_fastest_branch_dataset_test.py | 39 dataset = dataset_ops.Dataset.from_tensor_slices([0, 1, 2, 3, 4]) 41 def branch(dataset): argument 42 return dataset.map(lambda x: x) 45 dataset, [branch, branch]) 50 expected_shapes=dataset_ops.get_legacy_output_shapes(dataset)) 54 dataset = dataset_ops.Dataset.range(10) 59 def branch_0(dataset): argument 60 return dataset.map(lambda x: x + const_64) 62 def branch_1(dataset): argument 63 return dataset.map(lambda x: x + math_ops.cast(const_32, dtypes.int64)) [all …]
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/external/tensorflow/tensorflow/python/data/experimental/kernel_tests/ |
D | auto_shard_dataset_test.py | 60 def getAllDatasetElements(self, dataset): argument 62 next_fn = self.getNext(dataset) 70 def assertDatasetProducesWithShuffle(self, dataset, expected, batch, argument 74 next_fn = self.getNext(dataset) 86 self.assertDatasetProduces(dataset, list(chunk(expected, batch))) 93 dataset = dataset_ops.Dataset.list_files( 95 dataset = dataset.flat_map(core_readers.TFRecordDataset) 96 dataset = dataset.batch(5) 97 dataset = distribute._AutoShardDataset(dataset, 5, 3) 104 self.assertDatasetProducesWithShuffle(dataset, expected, 5, 4, shuffle) [all …]
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D | prefetch_with_slack_test.py | 40 dataset = dataset_ops.Dataset.range(10) 41 dataset = dataset.prefetch(1) 44 dataset = dataset.with_options(options) 46 dataset, ["/cpu:1", "/cpu:2"]) 47 dataset = multi_device_iterator._dataset # pylint: disable=protected-access 48 self.assertIn("slack", dataset.options()._graph_rewrites().enabled) 50 dataset.options()._graph_rewrite_configs(autotune=True)) 67 dataset = dataset_ops.Dataset.range(10) 68 dataset = dataset.prefetch(1) 71 dataset = dataset.with_options(options) [all …]
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D | rebatch_dataset_test.py | 153 def _flat_shapes(dataset): argument 156 for ts in nest.flatten(dataset_ops.get_legacy_output_shapes(dataset)) 168 dataset = dataset_ops.Dataset.range(8).batch(4, drop_remainder=True) 170 dataset, batch_sizes=[2, 1, 1]) 178 dataset = dataset_ops.Dataset.range(8).batch(4, drop_remainder=True) 180 dataset, batch_sizes=[2, 2], drop_remainder=drop_remainder) 187 dataset = dataset_ops.Dataset.range(8).batch(4, drop_remainder=False) 189 dataset, batch_sizes=[2, 2], drop_remainder=False) 196 dataset = dataset_ops.Dataset.range(8).batch(4, drop_remainder=False) 198 dataset, batch_sizes=[2, 2], drop_remainder=True) [all …]
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D | optimize_dataset_test.py | 133 dataset = dataset_ops.Dataset.range( 137 dataset = dataset.with_options(options) 138 get_next = self.getNext(dataset) 145 dataset = dataset_ops.Dataset.from_tensors(input_t) 148 dataset = dataset.with_options(options) 149 iterator = dataset_ops.make_initializable_iterator(dataset) 161 dataset = dataset_ops.Dataset.from_tensor_slices(input_t) 164 dataset = dataset.with_options(options) 165 iterator = dataset_ops.make_initializable_iterator(dataset) 177 dataset = dataset_ops.Dataset.from_tensors(0) [all …]
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D | snapshot_test.py | 67 def assertDatasetProducesSet(self, dataset, expected): argument 69 next_fn = self.getNext(dataset) 109 dataset = dataset_ops.Dataset.from_tensors([1, 2, 3]) 110 dataset.apply(snapshot.snapshot(self._snapshot_dir)) 122 dataset = core_readers._TFRecordDataset(filenames) 123 dataset = dataset.apply(snapshot.snapshot(self._snapshot_dir)) 124 self.assertDatasetProduces(dataset, expected) 146 dataset = core_readers._TFRecordDataset(filenames) 147 dataset = dataset.apply( 149 self.assertDatasetProduces(dataset, expected) [all …]
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D | non_serializable_test.py | 33 dataset = dataset_ops.Dataset.from_tensors(0) 34 dataset = dataset.apply(testing.assert_next(["FiniteSkip"])) 35 dataset = dataset.skip(0) # Should not be removed by noop elimination 36 dataset = dataset.apply(testing.non_serializable()) 37 dataset = dataset.apply(testing.assert_next(["MemoryCacheImpl"])) 38 dataset = dataset.skip(0) # Should be removed by noop elimination 39 dataset = dataset.cache() 43 dataset = dataset.with_options(options) 44 self.assertDatasetProduces(dataset, expected_output=[0]) 49 dataset = dataset_ops.Dataset.from_tensors(0) [all …]
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/external/tensorflow/tensorflow/python/data/experimental/benchmarks/ |
D | snapshot_dataset_benchmark.py | 48 dataset = dataset_ops.Dataset.from_tensor_slices([1.0]) 49 dataset = dataset.map( 51 dataset = dataset.repeat(num_elements) 52 dataset = dataset.apply( 55 return dataset 59 dataset = self._createSimpleDataset( 63 dataset=dataset, 71 dataset = self._createSimpleDataset( 75 dataset=dataset, 83 dataset = self._createSimpleDataset(num_elements=num_elements) [all …]
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D | autotune_benchmark.py | 31 def _run_benchmark(self, dataset, autotune, autotune_buffers, argument 37 dataset = dataset.with_options(options) 43 dataset=dataset, 61 dataset = dataset_ops.Dataset.from_tensors( 63 dataset = dataset.map(math_ops.matmul) 64 dataset = dataset.batch( 67 dataset, 83 dataset = dataset_ops.Dataset.from_tensors( 85 dataset = dataset.map( 88 dataset=dataset, [all …]
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D | choose_fastest_benchmark.py | 30 dataset = dataset_ops.Dataset.range(1000**2).repeat() 33 dataset = dataset.with_options(options) 34 map_batch_dataset = dataset.map(lambda x: x + 1).batch(100) 35 batch_map_dataset = dataset.batch(100).map(lambda x: x + 1) 39 self._benchmark(dataset=map_batch_dataset, name="map_batch_dataset") 40 self._benchmark(dataset=batch_map_dataset, name="batch_map_dataset") 41 self._benchmark(dataset=merge_dataset, name="merge_dataset") 45 dataset = dataset_ops.Dataset.range(1000**2).repeat() 48 dataset = dataset.with_options(options) 49 map_batch_dataset = dataset.map(lambda x: x + 1).batch(100) [all …]
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D | parameter_value_benchmark.py | 32 dataset = dataset_ops.Dataset.from_tensors( 34 dataset = dataset.map( 36 dataset = dataset.prefetch(buffer_size=buffer_size) 39 dataset=dataset, 66 dataset = dataset_ops.Dataset.from_tensors( 68 dataset = dataset.map( 70 dataset = dataset.batch(batch_size=batch_size) 71 dataset = dataset.prefetch(buffer_size=buffer_size) 74 dataset=dataset, 101 dataset = dataset_ops.Dataset.from_tensors( [all …]
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D | optimize_benchmark.py | 41 dataset = dataset_ops.Dataset.from_tensors(0).repeat(None) 43 dataset = dataset.map(lambda x: x) 48 dataset = dataset.with_options(options) 52 dataset=dataset, 70 dataset = dataset_ops.Dataset.from_tensors(0).repeat(None) 72 dataset = dataset.map(lambda x: x + 5).filter( 78 dataset = dataset.with_options(options) 82 dataset=dataset, 102 dataset = dataset_ops.Dataset.from_tensors(5).repeat(None) 104 dataset = dataset.filter(lambda x: math_ops.greater_equal(x - 5, 0)) [all …]
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/external/tensorflow/tensorflow/python/data/kernel_tests/ |
D | map_test.py | 65 def new_map_fn(dataset, *args, **kwargs): argument 66 return dataset.map(*args, **kwargs) 68 def legacy_map_fn(dataset, *args, **kwargs): argument 69 return dataset.map_with_legacy_function(*args, **kwargs) 86 def new_map_fn(dataset, *args, **kwargs): argument 87 return dataset.map(*args, **kwargs) 150 dataset = dataset_ops.Dataset.range(num_elements) 151 dataset = apply_map(dataset, fn, num_parallel_calls).with_options(options) 152 return dataset, coordination_events 169 dataset = dataset_ops.Dataset.from_tensor_slices(components) [all …]
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D | from_tensors_test.py | 48 dataset = dataset_ops.Dataset.from_tensors(components) 52 nest.flatten(dataset_ops.get_legacy_output_shapes(dataset))) 54 self.assertDatasetProduces(dataset, expected_output=[components]) 59 dataset = dataset_ops.Dataset.from_tensors(dataset_ops.Dataset.range(10)) 60 dataset = dataset.flat_map(lambda x: x) 61 self.assertDatasetProduces(dataset, expected_output=range(10)) 70 dataset = dataset_ops.Dataset.from_tensors(components) 73 dataset, expected_output=[[1.0, 2.0]], requires_initialization=True) 87 dataset = dataset_ops.Dataset.from_tensors(components) 91 [shape for shape in dataset_ops.get_legacy_output_shapes(dataset)]) [all …]
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D | filter_test.py | 35 def filter_fn(dataset, predicate): argument 36 return dataset.filter(predicate) 38 def legacy_filter_fn(dataset, predicate): argument 39 return dataset.filter_with_legacy_function(predicate) 68 dataset = dataset_ops.Dataset.from_tensor_slices(components).map( 71 dataset = apply_filter( 72 dataset, 77 [shape for shape in dataset_ops.get_legacy_output_shapes(dataset)]) 78 get_next = self.getNext(dataset) 95 dataset = dataset_ops.Dataset.range(4) [all …]
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D | dataset_test.py | 54 dataset = dataset_ops.Dataset.range(10) 56 self.evaluate(dataset._as_serialized_graph())) 60 dataset = dataset_ops.Dataset.range(10).map( 64 dataset._as_serialized_graph(external_state_policy=distribute_options 94 def _testNumInputs(self, dataset, num_inputs): argument 95 self.assertLen(dataset._inputs(), num_inputs) 99 dataset = readers.FixedLengthRecordDataset("", 42) 100 self._testNumInputs(dataset, 0) 107 dataset = dataset_ops.Dataset.from_generator(gen, dtypes.int32) 108 self._testNumInputs(dataset, 1) [all …]
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D | shard_test.py | 33 dataset = dataset_ops.Dataset.range(10).shard(5, 2) 34 self.assertDatasetProduces(dataset, expected_output=[2, 7]) 40 dataset = dataset_ops.Dataset.zip((dataset_a, dataset_b)).shard(5, 2) 41 self.assertDatasetProduces(dataset, expected_output=[(2, 8), (7, 3)]) 45 dataset = dataset_ops.Dataset.range(10).shard(5, 0) 46 self.assertDatasetProduces(dataset, expected_output=[0, 5]) 51 dataset = dataset_ops.Dataset.range(10).shard(5, 7) 52 self.evaluate(self.getNext(dataset)()) 57 dataset = dataset_ops.Dataset.range(10).shard(5, -3) 58 self.evaluate(self.getNext(dataset)()) [all …]
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/external/tensorflow/tensorflow/python/distribute/ |
D | input_ops_test.py | 47 def _getNext(self, dataset): argument 49 iterator = iter(dataset) 52 iterator = dataset_ops.make_one_shot_iterator(dataset) 103 def _verifySimpleShardingOutput(self, dataset, record_fn): argument 104 next_element_fn = self._getNext(dataset) 114 dataset = readers.TFRecordDataset(self._createTFRecordFiles()) 115 dataset = input_ops.auto_shard_dataset( 116 dataset, self._num_shards, self._shard_index) 118 self._verifySimpleShardingOutput(dataset, self._record) 122 dataset = dataset_ops.Dataset.from_tensor_slices( [all …]
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/external/tensorflow/tensorflow/python/keras/engine/ |
D | training_dataset_test.py | 69 dataset = dataset_ops.Dataset.from_tensor_slices((inputs, targets)) 70 dataset = dataset.repeat(100) 71 dataset = dataset.batch(10) 75 dataset, 79 validation_data=dataset, 82 dataset, 86 validation_data=dataset, 104 dataset = dataset_ops.Dataset.from_tensor_slices((inputs, targets)) 105 dataset = dataset.repeat() # Infinite dataset. 106 dataset = dataset.batch(10) [all …]
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/external/protobuf/benchmarks/cpp/ |
D | cpp_benchmark.cc | 54 Fixture(const BenchmarkDataset& dataset, const std::string& suffix) { in Fixture() argument 55 for (int i = 0; i < dataset.payload_size(); i++) { in Fixture() 56 payloads_.push_back(dataset.payload(i)); in Fixture() 61 dataset.message_name()); in Fixture() 64 std::cerr << "Couldn't find message named '" << dataset.message_name() in Fixture() 69 SetName((dataset.name() + suffix).c_str()); in Fixture() 97 ParseNewFixture(const BenchmarkDataset& dataset) in ParseNewFixture() argument 98 : Fixture(dataset, "_parse_new") {} in ParseNewFixture() 118 ParseNewArenaFixture(const BenchmarkDataset& dataset) in ParseNewArenaFixture() argument 119 : Fixture(dataset, "_parse_newarena") {} in ParseNewArenaFixture() [all …]
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/external/tensorflow/tensorflow/python/data/benchmarks/ |
D | meta_benchmark.py | 45 dataset = self.setup_fast_dataset() 46 self.run_benchmark_with_only_cpp_iterations(dataset) 49 dataset = self.setup_fast_dataset() 50 self.run_benchmark_with_session_run(dataset) 53 dataset = self.setup_fast_dataset() 54 self.run_benchmark_with_session_run(dataset, make_callable=True) 58 dataset = self.setup_fast_dataset() 59 self.run_benchmark_in_eager(dataset) 62 dataset = self.setup_fast_dataset() 65 return dataset.apply(testing.sleep(1000)) [all …]
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D | map_benchmark.py | 39 dataset = dataset_ops.Dataset.range(10000) 41 dataset = dataset_ops.MapDataset( 42 dataset, fn, use_inter_op_parallelism=use_inter_op_parallelism) 44 dataset, 58 dataset = dataset_ops.Dataset.from_tensors( 60 dataset = dataset_ops.MapDataset( 61 dataset, fn, use_inter_op_parallelism=use_inter_op_parallelism) 63 dataset, 75 dataset = dataset_ops.Dataset.range(1000).repeat() 76 dataset = dataset.map(lambda x: x + 1, num_parallel_calls=32) [all …]
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/external/tensorflow/tensorflow/python/data/experimental/kernel_tests/serialization/ |
D | choose_fastest_branch_dataset_serialization_test.py | 41 dataset = dataset_ops.Dataset.range(size) 43 def branch_0(dataset): argument 44 return dataset.map(lambda x: x).batch(10) 46 def branch_1(dataset): argument 47 return dataset.batch(10).map(lambda x: x) 50 dataset, [branch_0, branch_1], 60 dataset = dataset_ops.Dataset.range(10) 64 def branch_0(dataset): argument 65 return dataset.map(lambda x: x + const_64) 67 def branch_1(dataset): argument [all …]
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