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/external/tensorflow/tensorflow/python/data/experimental/kernel_tests/optimization/
Dinject_prefetch_test.py32 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(
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Dchoose_fastest_branch_dataset_test.py39 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))
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/external/tensorflow/tensorflow/python/data/experimental/kernel_tests/
Dauto_shard_dataset_test.py52 def getAllDatasetElements(self, dataset): argument
54 next_fn = self.getNext(dataset)
62 def assertDatasetProducesWithShuffle(self, dataset, expected, batch, argument
66 next_fn = self.getNext(dataset)
78 self.assertDatasetProduces(dataset, list(chunk(expected, batch)))
85 dataset = dataset_ops.Dataset.list_files(
87 dataset = dataset.flat_map(core_readers.TFRecordDataset)
88 dataset = dataset.batch(5)
89 dataset = distribute._AutoShardDataset(dataset, 5, 3)
96 self.assertDatasetProducesWithShuffle(dataset, expected, 5, 4, shuffle)
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Dprefetch_with_slack_test.py40 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())
50 dataset.options()._graph_rewrite_configs())
67 dataset = dataset_ops.Dataset.range(10)
68 dataset = dataset.prefetch(1)
71 dataset = dataset.with_options(options)
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Dnon_serializable_test.py33 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)
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Dsnapshot_test.py94 dataset = dataset_ops.Dataset.range(1000)
95 dataset = dataset.apply(snapshot.snapshot(tmpdir))
96 self.assertDatasetProduces(dataset, list(range(1000)))
98 dataset = dataset_ops.Dataset.range(1001)
99 dataset = dataset.apply(snapshot.snapshot(tmpdir))
100 self.assertDatasetProduces(dataset, list(range(1001)))
153 dataset = dataset_ops.Dataset.range(1000)
154 dataset = dataset.apply(snapshot.snapshot(tmpdir, compression=compression))
155 self.assertDatasetProduces(dataset, list(range(1000)))
163 dataset = dataset_ops.Dataset.range(10)
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Drebatch_dataset_test.py48 def _flat_shapes(dataset): argument
49 return nest.flatten(dataset_ops.get_legacy_output_shapes(dataset))
58 dataset = dataset_ops.Dataset.range(1024).batch(
60 rebatched_dataset = distribute._RebatchDataset(dataset, num_replicas=4)
69 dataset = dataset_ops.Dataset.from_tensors("xxx")
72 dataset = dataset.map(image_ops.decode_image)
73 self.assertEqual([tensor_shape.TensorShape(None)], _flat_shapes(dataset))
74 rebatched_dataset = distribute._RebatchDataset(dataset, num_replicas=4)
81 dataset = dataset_ops.Dataset.range(1000)
82 dataset = dataset.batch(10, drop_remainder=False)
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Doptimize_dataset_test.py110 dataset = dataset_ops.Dataset.range(
114 dataset = dataset.with_options(options)
115 get_next = self.getNext(dataset)
122 dataset = dataset_ops.Dataset.from_tensors(input_t)
125 dataset = dataset.with_options(options)
126 iterator = dataset_ops.make_initializable_iterator(dataset)
138 dataset = dataset_ops.Dataset.from_tensor_slices(input_t)
141 dataset = dataset.with_options(options)
142 iterator = dataset_ops.make_initializable_iterator(dataset)
154 dataset = dataset_ops.Dataset.from_tensors(0)
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/external/tensorflow/tensorflow/python/data/experimental/benchmarks/
Dsnapshot_dataset_benchmark.py50 dataset = dataset_ops.Dataset.from_tensor_slices([1.0])
51 dataset = dataset.map(
53 dataset = dataset.repeat(num_elems)
54 dataset = dataset.apply(snapshot.snapshot(tmp_dir, compression=compression))
56 return dataset
58 def _consumeDataset(self, dataset, num_elems): argument
59 dataset = dataset.skip(num_elems)
60 next_element = dataset_ops.make_one_shot_iterator(dataset).get_next()
69 dataset = self._createSimpleDataset(
72 self.run_and_report_benchmark(dataset, num_elems, "write_gzip",
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Dautotune_benchmark.py34 def _run_benchmark(self, dataset, autotune, autotune_buffers, argument
40 dataset = dataset.with_options(options)
41 iterator = dataset_ops.make_one_shot_iterator(dataset)
76 dataset = dataset_ops.Dataset.from_tensors(
78 dataset = dataset.map(
81 dataset,
98 dataset = dataset_ops.Dataset.from_tensors(
100 dataset = dataset.map(
102 dataset = dataset.batch(batch_size=batch_size)
104 dataset,
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Dunbatch_benchmark.py39 dataset = dataset_ops.Dataset.from_tensors("element").repeat(None)
41 dataset = dataset.batch(batch_size_placeholder)
42 dataset = dataset.unbatch()
43 dataset = dataset.skip(elems_per_trial)
46 dataset = dataset.with_options(options)
47 iterator = dataset_ops.make_initializable_iterator(dataset)
76 dataset = dataset_ops.Dataset.from_tensors("element").repeat(None)
78 dataset = dataset.batch(batch_size_placeholder)
79 dataset = dataset.flat_map(dataset_ops.Dataset.from_tensor_slices)
80 dataset = dataset.skip(elems_per_trial)
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/external/tensorflow/tensorflow/python/distribute/
Dinput_ops_test.py47 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(
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/external/tensorflow/tensorflow/python/data/kernel_tests/
Dmap_test.py63 def new_map_fn(dataset, *args, **kwargs): argument
64 return dataset.map(*args, **kwargs)
66 def legacy_map_fn(dataset, *args, **kwargs): argument
67 return dataset.map_with_legacy_function(*args, **kwargs)
84 def new_map_fn(dataset, *args, **kwargs): argument
85 return dataset.map(*args, **kwargs)
148 dataset = dataset_ops.Dataset.range(num_elements)
149 dataset = apply_map(dataset, map_fn, num_parallel_calls).with_options(options)
150 return dataset, coordination_events
160 dataset = dataset_ops.Dataset.from_tensor_slices(components)
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Dfilter_test.py35 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)
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Dfrom_tensors_test.py48 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)])
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Dshard_test.py33 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)())
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Ddataset_test.py53 dataset = dataset_ops.Dataset.range(10)
55 self.evaluate(dataset._as_serialized_graph()))
59 dataset = dataset_ops.Dataset.range(10).map(
63 dataset._as_serialized_graph(external_state_policy=distribute_options
93 def _testNumInputs(self, dataset, num_inputs): argument
94 self.assertLen(dataset._inputs(), num_inputs)
98 dataset = readers.FixedLengthRecordDataset("", 42)
99 self._testNumInputs(dataset, 0)
106 dataset = dataset_ops.Dataset.from_generator(gen, dtypes.int32)
107 self._testNumInputs(dataset, 1)
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/external/tensorflow/tensorflow/python/keras/engine/
Dtraining_dataset_test.py71 dataset = dataset_ops.Dataset.from_tensor_slices((inputs, targets))
72 dataset = dataset.repeat(100)
73 dataset = dataset.batch(10)
76 model.fit(dataset, epochs=1, steps_per_epoch=2, verbose=0,
77 validation_data=dataset, validation_steps=2)
78 model.fit(dataset, epochs=1, steps_per_epoch=2, verbose=0,
79 validation_data=dataset, validation_steps=2)
97 dataset = dataset_ops.Dataset.from_tensor_slices((inputs, targets))
98 dataset = dataset.repeat() # Infinite dataset.
99 dataset = dataset.batch(10)
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/external/protobuf/benchmarks/cpp/
Dcpp_benchmark.cc54 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()
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/external/tensorflow/tensorflow/python/data/benchmarks/
Dmeta_benchmark.py45 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))
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/external/tensorflow/tensorflow/python/data/experimental/kernel_tests/serialization/
Dchoose_fastest_branch_dataset_serialization_test.py41 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
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/external/guava/guava/src/com/google/common/math/
DQuantiles.java232 public double compute(Collection<? extends Number> dataset) { in compute() argument
233 return computeInPlace(Doubles.toArray(dataset)); in compute()
243 public double compute(double... dataset) { in compute() argument
244 return computeInPlace(dataset.clone()); in compute()
255 public double compute(long... dataset) { in compute() argument
256 return computeInPlace(longsToDoubles(dataset)); in compute()
266 public double compute(int... dataset) { in compute() argument
267 return computeInPlace(intsToDoubles(dataset)); in compute()
277 public double computeInPlace(double... dataset) { in computeInPlace() argument
278 checkArgument(dataset.length > 0, "Cannot calculate quantiles of an empty dataset"); in computeInPlace()
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/external/guava/android/guava/src/com/google/common/math/
DQuantiles.java232 public double compute(Collection<? extends Number> dataset) { in compute() argument
233 return computeInPlace(Doubles.toArray(dataset)); in compute()
243 public double compute(double... dataset) { in compute() argument
244 return computeInPlace(dataset.clone()); in compute()
255 public double compute(long... dataset) { in compute() argument
256 return computeInPlace(longsToDoubles(dataset)); in compute()
266 public double compute(int... dataset) { in compute() argument
267 return computeInPlace(intsToDoubles(dataset)); in compute()
277 public double computeInPlace(double... dataset) { in computeInPlace() argument
278 checkArgument(dataset.length > 0, "Cannot calculate quantiles of an empty dataset"); in computeInPlace()
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/external/tensorflow/tensorflow/python/data/experimental/ops/
Dreaders.py207 dataset, num_epochs, shuffle, shuffle_buffer_size, shuffle_seed): argument
210 dataset = dataset.shuffle(shuffle_buffer_size, shuffle_seed)
212 dataset = dataset.repeat(num_epochs)
213 return dataset
286 dataset = core_readers.TFRecordDataset(
292 dataset = _maybe_shuffle_and_repeat(
293 dataset, num_epochs, shuffle, shuffle_buffer_size, shuffle_seed)
302 dataset = dataset.batch(batch_size, drop_remainder=drop_final_batch)
304 dataset = dataset.map(
306 dataset = dataset.batch(batch_size, drop_remainder=drop_final_batch)
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/external/tensorflow/tensorflow/core/kernels/data/
Dfixed_length_record_dataset_op.cc140 input_buffer_->ReadNBytes(dataset()->record_bytes_, &record)); in GetNextInternal()
142 dataset()->record_bytes_); in GetNextInternal()
160 if (current_file_index_ == dataset()->filenames_.size()) { in GetNextInternal()
168 dataset()->filenames_[current_file_index_], &file_size)); in GetNextInternal()
169 file_pos_limit_ = file_size - dataset()->footer_bytes_; in GetNextInternal()
172 file_size - (dataset()->header_bytes_ + dataset()->footer_bytes_); in GetNextInternal()
174 if (body_size % dataset()->record_bytes_ != 0) { in GetNextInternal()
176 "Excluding the header (", dataset()->header_bytes_, in GetNextInternal()
177 " bytes) and footer (", dataset()->footer_bytes_, in GetNextInternal()
179 dataset()->filenames_[current_file_index_], "\" has body length ", in GetNextInternal()
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