| /external/tensorflow/tensorflow/core/util/tensor_bundle/ |
| naming.cc | 28 string DataFilename(StringPiece prefix, int32 shard_id, int32 num_shards) {
29 DCHECK_GT(num_shards, 0);
30 DCHECK_LT(shard_id, num_shards);
33 shard_id, num_shards);
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| naming.h | 24 // DataFilename(prefix, shard_id, num_shards): pathname of a data file.
42 string DataFilename(StringPiece prefix, int32 shard_id, int32 num_shards);
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| /external/tensorflow/tensorflow/contrib/boosted_trees/lib/utils/ |
| parallel_for.cc | 30 const int num_shards = std::max<int>( local
32 const int64 block_size = (batch_size + num_shards - 1) / num_shards;
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| /external/tensorflow/tensorflow/contrib/linear_optimizer/python/ops/ |
| sharded_mutable_dense_hashtable_test.py | 32 for num_shards in [1, 3, 10]:
43 num_shards=num_shards)
55 for num_shards in [1, 3, 10]:
68 num_shards=num_shards)
85 num_shards = 2
93 num_shards=num_shards)
100 self.assertAllEqual(num_shards, len(keys_list)
[all...] |
| sharded_mutable_dense_hashtable.py | 40 The _ShardedMutableDenseHashTable keeps `num_shards` MutableDenseHashTable
51 num_shards=1,
57 for i in range(num_shards):
64 name='%s-%d-of-%d' % (name, i + 1, num_shards)))
109 num_shards = self._num_shards
110 if num_shards == 1:
116 num_shards)
119 for i in range(num_shards)
126 num_shards)
134 num_shards = self._num_shard
[all...] |
| sdca_ops.py | 149 num_shards=self._num_table_shards(),
176 num_shards = self._options.get('num_table_shards')
177 return 1 if num_shards is None else num_shards
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| /external/tensorflow/tensorflow/core/util/ |
| work_sharder_test.cc | 33 int64 num_shards = 0; local
37 [=, &mu, &num_shards, &num_done_work, &work](int64 start, int64 limit) {
42 ++num_shards;
51 << num_shards; local
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| work_sharder.cc | 39 // We shard [0, total) into "num_shards" shards.
40 // 1 <= num_shards <= num worker threads
46 const int num_shards = local
56 const int64 block_size = (total + num_shards - 1) / num_shards;
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| /external/tensorflow/tensorflow/contrib/tpu/python/tpu/ |
| tpu_optimizer.py | 76 num_shards = tpu_function.get_tpu_context().number_of_shards
77 if num_shards is None:
81 num_shards = 1
82 if num_shards > 1 and self._reduction == losses.Reduction.MEAN:
83 scale = 1.0 / num_shards
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| tpu_config.py | 45 'num_shards',
58 num_shards: (Deprecated, ignored by TPUEstimator).
62 product(computation_shape) * num_shards.
91 num_shards=None,
101 # Check num_shards.
102 if num_shards is not None:
103 util_lib.check_positive_integer(num_shards, 'TPUConfig num_shards')
129 num_shards=num_shards,
[all...] |
| tpu.py | 393 num_shards=1,
404 `input_shard_axes`). Each input is split into `num_shards` pieces
431 `num_shards`.
432 num_shards: The number of shards.
457 ValueError: If num_shards <= 0
462 if num_shards <= 0:
463 raise ValueError("num_shards must be a positive integer.")
478 array_ops.split(x, num_shards, axis=axis)
484 transposed_inputs = [[]] * num_shards
493 # There must be at least one shard since num_shards > 0
[all...] |
| /external/tensorflow/tensorflow/python/kernel_tests/ |
| embedding_ops_test.py | 131 def _EmbeddingParams(num_shards,
141 for i in range(num_shards):
142 shard_shape = [vocab_size // num_shards] + shape
143 if i < vocab_size % num_shards: # Excess goes evenly on the first shards
161 def _EmbeddingParamsAsPartitionedVariable(num_shards,
167 num_shards, vocab_size, dtype=dtype, shape=shape)
174 max_partitions=num_shards, min_slice_size=1),
181 num_shards,
200 val = np.copy(params[_PName(i % num_shards) + ":0"][
201 i // num_shards, :]) * weight_valu
[all...] |
| /external/tensorflow/tensorflow/contrib/layers/python/layers/ |
| embedding_ops_test.py | 45 def _random_weights(self, vocab_size=4, embed_dim=4, num_shards=1):
48 assert num_shards > 0
49 assert num_shards <= vocab_size
53 slicing=[num_shards, 1],
154 embedding_weights = self._random_weights(num_shards=3)
168 embedding_weights = self._random_weights(num_shards=3)
228 embedding_weights = self._random_weights(num_shards=3)
245 embedding_weights = self._random_weights(num_shards=3)
264 def _random_weights(self, size=50, num_shards=1):
266 assert num_shards >
[all...] |
| /external/tensorflow/tensorflow/core/lib/core/ |
| blocking_counter_test.cc | 57 const int num_shards = num_threads * shards_per_thread; local
60 BlockingCounter bc(num_shards);
|
| /external/tensorflow/tensorflow/core/kernels/ |
| topk_op_gpu.cu.cc | 262 // mergeShards performs a top-k merge on `num_shards` many sorted streams that
264 // |s_1 1st|s_2 1st|...s_{num_shards} 1st|s_1 2nd|s_2 2nd|...
269 __device__ void mergeShards(int num_shards, int k,
273 // If k < num_shards, we can use a min-heap with k elements to get the top k
275 // If k > num_shards, we can initialize a min-heap with the top element from
277 const int heap_size = k < num_shards ? k : num_shards;
290 // Now perform top k with the remaining shards (if num_shards > heap_size).
291 for (int shard = heap_size; shard < num_shards; shard++) {
323 int next_shard_index = shard_index + num_shards;
[all...] |
| range_sampler.h | 217 int32 num_shards, int32 shard);
221 int32 num_shards, int32 shard);
|
| candidate_sampler_ops.cc | 171 int64 num_shards; local
172 OP_REQUIRES_OK(context, context->GetAttr("num_shards", &num_shards));
179 num_shards, shard));
182 num_reserved_ids, num_shards, shard));
|
| range_sampler.cc | 236 int32 num_shards, int32 shard)
239 num_shards_(num_shards),
252 int32 num_shards, int32 shard)
255 num_shards_(num_shards),
|
| /external/tensorflow/tensorflow/contrib/factorization/python/ops/ |
| factorization_ops.py | 304 def _shard_sizes(cls, dims, num_shards):
305 """Helper function to split dims values into num_shards."""
306 shard_size, residual = divmod(dims, num_shards)
307 return [shard_size + 1] * residual + [shard_size] * (num_shards - residual)
310 def _create_factors(cls, rows, cols, num_shards, init, name):
315 assert len(init) == num_shards
318 elif num_shards == 1:
321 sizes = cls._shard_sizes(rows, num_shards)
322 assert len(sizes) == num_shards
344 def _create_weights(cls, wt_init, num_wts, num_shards, name)
[all...] |
| /external/tensorflow/tensorflow/python/ops/ |
| candidate_sampling_ops.py | 210 num_shards=1,
260 num_shards: A sampler can be used to sample from a subset of the original
266 parameter (together with `num_shards`) indicates the particular partition
289 num_reserved_ids=num_reserved_ids, num_shards=num_shards, shard=shard,
|
| partitioned_variables.py | 221 def fixed_size_partitioner(num_shards, axis=0):
225 num_shards: `int`, number of shards to partition variable.
234 partitions_list[axis] = min(num_shards, shape[axis].value)
|
| /external/tensorflow/tensorflow/contrib/linear_optimizer/python/kernel_tests/ |
| sdca_ops_test.py | 203 for num_shards in _SHARD_NUMBERS:
210 num_table_shards=num_shards,
251 for num_shards in _SHARD_NUMBERS:
260 num_table_shards=num_shards,
315 for num_shards in _SHARD_NUMBERS:
322 num_table_shards=num_shards,
372 for num_shards in _SHARD_NUMBERS:
380 num_table_shards=num_shards,
413 for num_shards in _SHARD_NUMBERS:
420 num_table_shards=num_shards,
[all...] |
| /external/tensorflow/tensorflow/contrib/all_reduce/python/ |
| all_reduce_test.py | 180 def _buildShuffle(self, num_workers, num_gpus, num_shards):
183 for _ in range(num_shards)]
187 def _testShuffleAllReduce(self, num_workers, num_gpus, shape, num_shards):
189 build_f = self._buildShuffle(num_workers, num_gpus, num_shards)
|
| /external/autotest/server/cros/ap_configurators/ |
| pyauto_utils.py | 168 def Shard(ilist, shard_index, num_shards):
174 num_shards: shard count
176 chunk_size = len(ilist) / num_shards
178 if shard_index == num_shards - 1: # Exhaust the remainder in the last shard.
|
| /external/tensorflow/tensorflow/contrib/kfac/python/ops/ |
| utils.py | 346 num_shards = tpu_function.get_tpu_context().number_of_shards
347 if num_shards is None:
350 if num_shards == 1:
352 return tpu_ops.cross_replica_sum(tensor / num_shards)
|
