| /external/tensorflow/tensorflow/python/data/experimental/kernel_tests/ |
| D | rebatch_dataset_test.py | 165 dataset = dataset_ops.Dataset.range(8).batch(4, drop_remainder=True)
173 combinations.combine(drop_remainder=[True, False])))
174 def testShapeInferenceInputBatchDimDivisible(self, drop_remainder): argument
175 dataset = dataset_ops.Dataset.range(8).batch(4, drop_remainder=True)
177 dataset, batch_sizes=[2, 2], drop_remainder=drop_remainder)
184 dataset = dataset_ops.Dataset.range(8).batch(4, drop_remainder=False)
186 dataset, batch_sizes=[2, 2], drop_remainder=False)
193 dataset = dataset_ops.Dataset.range(8).batch(4, drop_remainder=False)
195 dataset, batch_sizes=[2, 2], drop_remainder=True)
202 dataset = dataset_ops.Dataset.range(10).batch(5, drop_remainder=True)
[all …]
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| D | map_and_batch_test.py | 121 combinations.combine(drop_remainder=[True, False])))
122 def testMapAndBatchPartialBatch(self, drop_remainder): argument
128 drop_remainder=drop_remainder)))
130 if drop_remainder:
137 if not drop_remainder:
183 lambda x: x, batch_size=100, drop_remainder=True))
425 combinations.combine(drop_remainder=[True, False])))
426 def testNumParallelBatches(self, verify_fn, drop_remainder): argument
433 if drop_remainder:
438 def build_ds(range_start, drop_remainder): argument
[all …]
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| D | dense_to_ragged_batch_test.py | 111 drop_remainder=[True, False])))
112 def testBasic(self, make_dataset, nrows, batch_size, drop_remainder): argument
122 batching.dense_to_ragged_batch(batch_size, drop_remainder))
126 if end_row > nrows and drop_remainder:
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| /external/tensorflow/tensorflow/python/data/experimental/ops/ |
| D | batching.py | 34 drop_remainder=False, argument
93 ragged_dataset, batch_size=batch_size, drop_remainder=drop_remainder)
153 drop_remainder=False, argument
202 num_parallel_calls, drop_remainder,
217 drop_remainder=False, argument
266 num_parallel_calls, drop_remainder)
336 drop_remainder, use_legacy_function=False): argument
349 drop_remainder, dtype=dtypes.bool, name="drop_remainder")
372 drop_remainder=self._drop_remainder_t,
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| /external/tensorflow/tensorflow/core/kernels/data/ |
| D | batch_dataset_op.cc | 50 Dataset(OpKernelContext* ctx, int64_t batch_size, bool drop_remainder, in Dataset() argument
58 reserve_size_(drop_remainder ? batch_size in Dataset()
60 drop_remainder_(drop_remainder), in Dataset()
67 {"drop_remainder", drop_remainder ? "true" : "false"}, in Dataset()
167 Node* drop_remainder = nullptr; in AsGraphDefInternal() local
168 TF_RETURN_IF_ERROR(b->AddScalar(drop_remainder_, &drop_remainder)); in AsGraphDefInternal()
172 b->AddDataset(this, {input_graph_node, batch_size, drop_remainder}, in AsGraphDefInternal()
303 bool drop_remainder = false; in MakeDataset() local
306 ctx, ParseScalarArgument<bool>(ctx, kDropRemainder, &drop_remainder)); in MakeDataset()
309 *output = new Dataset(ctx, batch_size, drop_remainder, parallel_copy_, input, in MakeDataset()
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| D | padded_batch_dataset_op.cc | 52 Dataset(OpKernelContext* ctx, int64_t batch_size, bool drop_remainder, in Dataset() argument
58 drop_remainder_(drop_remainder), in Dataset()
67 {"drop_remainder", drop_remainder ? "true" : "false"}, in Dataset()
162 Node* drop_remainder = nullptr; in AsGraphDefInternal() local
163 TF_RETURN_IF_ERROR(b->AddScalar(drop_remainder_, &drop_remainder)); in AsGraphDefInternal()
175 this, {{0, input_graph_node}, {1, batch_size}, {4, drop_remainder}}, in AsGraphDefInternal()
432 bool drop_remainder = false; in MakeDataset() local
435 ctx, ParseScalarArgument<bool>(ctx, kDropRemainder, &drop_remainder)); in MakeDataset()
479 *output = new Dataset(ctx, batch_size, drop_remainder, parallel_copy_, in MakeDataset()
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| D | parallel_batch_dataset_op.cc | 72 bool drop_remainder, bool parallel_copy, const DatasetBase* input, in Dataset() argument
80 reserve_size_(drop_remainder ? batch_size in Dataset()
83 drop_remainder_(drop_remainder), in Dataset()
92 {"drop_remainder", drop_remainder ? "true" : "false"}, in Dataset()
165 Node* drop_remainder = nullptr; in AsGraphDefInternal() local
166 TF_RETURN_IF_ERROR(b->AddScalar(drop_remainder_, &drop_remainder)); in AsGraphDefInternal()
181 {input_graph_node, batch_size, num_parallel_calls, drop_remainder}, in AsGraphDefInternal()
660 bool drop_remainder = false; in MakeDataset() local
662 ctx, ParseScalarArgument<bool>(ctx, kDropRemainder, &drop_remainder)); in MakeDataset()
664 *output = new Dataset(ctx, batch_size, num_parallel_calls, drop_remainder, in MakeDataset()
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| D | parallel_batch_dataset_op_test.cc | 30 int64_t num_parallel_calls, bool drop_remainder, in ParallelBatchDatasetParams() argument
39 drop_remainder_(drop_remainder), in ParallelBatchDatasetParams()
53 Tensor drop_remainder = in GetInputTensors() local
55 return {batch_size, num_parallel_calls, drop_remainder}; in GetInputTensors()
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| /external/tensorflow/tensorflow/python/data/kernel_tests/ |
| D | window_test.py | 43 drop_remainder=[True, False]) + combinations.combine(
48 drop_remainder=[True, False])))
49 def testWindowDataset(self, count, size, shift, stride, drop_remainder): argument
68 drop_remainder=drop_remainder).flat_map(_flat_map_fn)
83 if not drop_remainder:
129 drop_remainder=True).flat_map(lambda x: x.batch(batch_size=5))
152 drop_remainder=True).flat_map(lambda x: x.batch(batch_size=5))
179 drop_remainder=True).flat_map(lambda x: x.batch(batch_size=4)).window(
181 drop_remainder=True).flat_map(lambda x: x.batch(batch_size=3))
223 drop_remainder=True).flat_map(lambda x: x.batch(batch_size=2))
[all …]
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| D | batch_test.py | 53 drop_remainder=[True, False],
55 def testBasic(self, count, batch_size, drop_remainder, num_parallel_calls): argument
77 _map_fn).repeat(count).batch(batch_size, drop_remainder,
81 if drop_remainder:
97 if not drop_remainder and (count * 7) % batch_size > 0:
368 drop_remainder=[True, False])))
369 def testBasic(self, count, batch_size, drop_remainder): argument
379 batch_size=batch_size, drop_remainder=drop_remainder)
386 has_remainder = (not drop_remainder) and (count % batch_size != 0)
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| D | cardinality_test.py | 41 lambda: dataset_ops.Dataset.range(5).batch(2, drop_remainder=True), 2),
43 lambda: dataset_ops.Dataset.range(5).batch(2, drop_remainder=False), 3),
98 2, [], drop_remainder=True), 2),
100 2, [], drop_remainder=False), 3),
149 size=2, shift=2, drop_remainder=True), 2),
151 size=2, shift=2, drop_remainder=False), 3),
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| /external/tensorflow/tensorflow/python/ops/ragged/ |
| D | ragged_factory_ops_test.py | 108 def testRaggedWithMultiDeviceIterator(self, ragged_factory, drop_remainder): argument
113 2, drop_remainder)
133 drop_remainder): argument
172 drop_remainder): argument
215 def testIntStringWithDistributedDataset(self, string_factory, drop_remainder): argument
221 2, drop_remainder)
277 def testOpsWithDistributedDataset(self, string_factory, drop_remainder): argument
282 2, drop_remainder)
326 drop_remainder): argument
337 2, drop_remainder)
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| /external/tensorflow/tensorflow/core/ops/compat/ops_history_v2/ |
| D | ParallelBatchDataset.pbtxt | 16 name: "drop_remainder"
51 name: "drop_remainder"
93 name: "drop_remainder"
142 name: "drop_remainder"
198 name: "drop_remainder"
261 name: "drop_remainder"
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| D | BatchDatasetV2.pbtxt | 12 name: "drop_remainder"
43 name: "drop_remainder"
81 name: "drop_remainder"
126 name: "drop_remainder"
178 name: "drop_remainder"
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| D | WindowDataset.pbtxt | 20 name: "drop_remainder"
59 name: "drop_remainder"
105 name: "drop_remainder"
158 name: "drop_remainder"
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| D | PaddedBatchDatasetV2.pbtxt | 21 name: "drop_remainder"
67 name: "drop_remainder"
120 name: "drop_remainder"
180 name: "drop_remainder"
247 name: "drop_remainder"
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| D | ExperimentalMapAndBatchDataset.pbtxt | 20 name: "drop_remainder"
68 name: "drop_remainder"
123 name: "drop_remainder"
185 name: "drop_remainder"
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| D | RebatchDatasetV2.pbtxt | 12 name: "drop_remainder"
43 name: "drop_remainder"
81 name: "drop_remainder"
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| D | MapAndBatchDataset.pbtxt | 20 name: "drop_remainder"
75 name: "drop_remainder"
137 name: "drop_remainder"
206 name: "drop_remainder"
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| /external/tensorflow/tensorflow/python/distribute/ |
| D | input_lib_test.py | 553 drop_remainder=[True, False],
559 drop_remainder, distribution): argument
563 2, drop_remainder=drop_remainder)
568 if drop_remainder:
583 drop_remainder=[True, False],
589 iteration_type, drop_remainder, argument
609 return dataset.batch(2, drop_remainder=drop_remainder)
614 if drop_remainder and input_type == "dataset":
643 drop_remainder=[True, False],
650 drop_remainder, argument
[all …]
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| /external/tensorflow/tensorflow/core/kernels/data/experimental/ |
| D | rebatch_dataset_op.cc | 308 bool drop_remainder; in MakeDataset() local
310 ctx, ParseScalarArgument<bool>(ctx, "drop_remainder", &drop_remainder)); in MakeDataset()
312 *output = new Dataset(ctx, input, std::move(batch_sizes), drop_remainder, in MakeDataset()
320 std::vector<int64_t>&& batch_sizes, bool drop_remainder, in Dataset() argument
326 drop_remainder_(drop_remainder), in Dataset()
373 Node* drop_remainder = nullptr; in AsGraphDefInternal() local
374 TF_RETURN_IF_ERROR(b->AddScalar(drop_remainder_, &drop_remainder)); in AsGraphDefInternal()
376 this, {input_graph_node, batch_sizes, drop_remainder}, output)); in AsGraphDefInternal()
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| /external/tensorflow/tensorflow/core/ops/compat/ops_history_v1/ |
| D | BatchDatasetV2.pbtxt | 12 name: "drop_remainder"
43 name: "drop_remainder"
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| D | PaddedBatchDatasetV2.pbtxt | 21 name: "drop_remainder"
67 name: "drop_remainder"
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| D | ExperimentalMapAndBatchDataset.pbtxt | 20 name: "drop_remainder"
68 name: "drop_remainder"
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| /external/tensorflow/tensorflow/core/grappler/optimizers/data/ |
| D | auto_shard.cc | 512 const NodeDef* drop_remainder = nullptr; in GetDropRemainder() local
515 drop_remainder = graph.GetNode(batch_node.input(2)); in GetDropRemainder()
517 drop_remainder = graph.GetNode(batch_node.input(3)); in GetDropRemainder()
526 drop_remainder = graph.GetNode(batch_node.input(drop_remainder_index)); in GetDropRemainder()
531 if (!IsConstant(*drop_remainder)) { in GetDropRemainder()
535 if (!GetNodeAttr(*drop_remainder, "value", &drop_remainder_value).ok()) { in GetDropRemainder()
854 DropRemainderValue drop_remainder = GetDropRemainder(graph, *input_node); in IsEligibleRewriteBatchSize() local
863 if (drop_remainder == DropRemainderValue::kFalse || in IsEligibleRewriteBatchSize()
868 if (drop_remainder == DropRemainderValue::kUnknown) { in IsEligibleRewriteBatchSize()
874 if (drop_remainder == DropRemainderValue::kTrue && in IsEligibleRewriteBatchSize()
|