/external/tensorflow/tensorflow/python/data/experimental/kernel_tests/ |
D | bucket_by_sequence_length_test.py | 85 batch_sizes = [10, 8, 4, 2] 102 for length, batch_size, bucket_elements in zip(lengths, batch_sizes, 141 batch_sizes, 162 for length, batch_size, bucket_elements in zip(lengths, batch_sizes, 210 batch_sizes = [10, 8, 4, 2] 217 for batch_size, length in zip(batch_sizes, lengths): 239 batch_sizes, 260 self.assertEqual(sum(batch_sizes_val), sum(batch_sizes)) 261 self.assertEqual(sorted(batch_sizes), sorted(batch_sizes_val)) 270 batch_sizes = [10, 8, 4, 2] [all …]
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D | rebatch_dataset_test.py | 56 for batch_sizes in batch_sizes_list: 58 self.assertLen(batch_sizes, num_workers * num_replicas_per_worker) 60 self.assertAllEqual(np.sum(batch_sizes), global_batch_size) 66 for batch_sizes in batch_sizes_list: 67 actual_global_batch += np.sum(batch_sizes[offset:offset + 88 batch_sizes = distribute.batch_sizes_for_worker(global_batch_size, 93 tensor_util.constant_value(batch_sizes)) 170 dataset, batch_sizes=[2, 1, 1]) 180 dataset, batch_sizes=[2, 2], drop_remainder=drop_remainder) 189 dataset, batch_sizes=[2, 2], drop_remainder=False) [all …]
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D | auto_shard_dataset_test.py | 622 dataset = distribute._RebatchDataset(dataset, batch_sizes=[2, 1, 2]) 649 dataset, batch_sizes=[2, 1, 1]) 658 dataset, batch_sizes=[1, 1, 2]) 667 dataset, batch_sizes=[1, 2, 1])
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/external/tensorflow/tensorflow/python/eager/benchmarks/resnet50/ |
D | hvp_test.py | 117 def _hvp_benchmark(self, hvp_fn, label, batch_sizes, argument 121 for batch_size in batch_sizes: 147 batch_sizes=[8]) 152 batch_sizes=[8]) 157 batch_sizes=[8]) 162 batch_sizes=[8]) 167 batch_sizes=[8]) 172 batch_sizes=[8]) 177 batch_sizes=[8])
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/external/tensorflow/tensorflow/python/data/experimental/benchmarks/ |
D | unbatch_benchmark.py | 28 batch_sizes = [1, 2, 5, 10, 20, 50] 31 for batch_size in batch_sizes: 46 batch_sizes = [1, 2, 5, 10, 20, 50] 49 for batch_size in batch_sizes:
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/external/tensorflow/tensorflow/core/kernels/data/experimental/ |
D | rebatch_dataset_op.cc | 296 std::vector<int64> batch_sizes; in MakeDataset() local 297 batch_sizes.reserve(batch_sizes_tensor->NumElements()); in MakeDataset() 299 batch_sizes.push_back(batch_sizes_tensor->flat<int64>()(i)); in MakeDataset() 306 *output = new Dataset(ctx, input, std::move(batch_sizes), drop_remainder, in MakeDataset() 314 std::vector<int64>&& batch_sizes, bool drop_remainder, in Dataset() argument 319 batch_sizes_(std::move(batch_sizes)), in Dataset() 324 {{"batch_sizes", absl::StrJoin(batch_sizes, ",")}}) { in Dataset() 359 Node* batch_sizes = nullptr; in AsGraphDefInternal() local 360 TF_RETURN_IF_ERROR(b->AddVector(batch_sizes_, &batch_sizes)); in AsGraphDefInternal() 364 this, {input_graph_node, batch_sizes, drop_remainder}, output)); in AsGraphDefInternal()
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/external/tensorflow/tensorflow/python/data/experimental/ops/ |
D | distribute.py | 120 def __init__(self, input_dataset, batch_sizes, drop_remainder=False): argument 135 batch_sizes, dtype=dtypes.int64, name="batch_sizes") 149 batch_sizes=batch_sizes,
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D | grouping.py | 207 batch_sizes = constant_op.constant(bucket_batch_sizes, dtype=dtypes.int64) 225 window_size = batch_sizes[bucket_id]
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/external/tensorflow/tensorflow/python/keras/layers/ |
D | merge.py | 98 batch_sizes = {s[0] for s in input_shape if s} - {None} 99 if len(batch_sizes) > 1: 197 batch_sizes = {s[0] for s in input_shape if s is not None} - {None} 198 if len(batch_sizes) == 1: 199 output_shape = (list(batch_sizes)[0],) + output_shape
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/external/tensorflow/tensorflow/core/ops/compat/ops_history_v2/ |
D | RebatchDatasetV2.pbtxt | 8 name: "batch_sizes"
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/external/tensorflow/tensorflow/core/api_def/base_api/ |
D | api_def_RebatchDatasetV2.pbtxt | 11 name: "batch_sizes"
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/external/tensorflow/tensorflow/python/data/experimental/kernel_tests/serialization/ |
D | rebatch_dataset_serialization_test.py | 57 batch_sizes=[batch_size, batch_size])
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/external/tensorflow/tensorflow/python/keras/preprocessing/ |
D | sequence_test.py | 209 batch_sizes = (6, 6, 6, 5, 6, 6, 6) 213 batch_sizes, shuffles):
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/external/tensorflow/tensorflow/python/distribute/ |
D | input_lib.py | 1065 batch_sizes = distribute.batch_sizes_for_worker( 1068 dataset, batch_sizes).prefetch(num_replicas_per_worker)
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D | input_lib_test.py | 1355 batch_sizes = dataset_ops.Dataset.from_tensor_slices([8, 4]) 1357 dataset = dataset_ops.Dataset.zip((offsets, batch_sizes))
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/external/tensorflow/tensorflow/tools/api/golden/v2/ |
D | tensorflow.raw_ops.pbtxt | 3381 …argspec: "args=[\'input_dataset\', \'batch_sizes\', \'drop_remainder\', \'output_types\', \'output…
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/external/tensorflow/tensorflow/tools/api/golden/v1/ |
D | tensorflow.raw_ops.pbtxt | 3381 …argspec: "args=[\'input_dataset\', \'batch_sizes\', \'drop_remainder\', \'output_types\', \'output…
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/external/tensorflow/tensorflow/go/op/ |
D | wrappers.go | 10373 func RebatchDatasetV2(scope *Scope, input_dataset tf.Output, batch_sizes tf.Output, drop_remainder … 10381 input_dataset, batch_sizes, drop_remainder,
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/external/tensorflow/tensorflow/core/ops/ |
D | ops.pbtxt | 36220 name: "batch_sizes"
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