Searched refs:per_replica_values (Results 1 – 3 of 3) sorted by relevance
| /external/tensorflow/tensorflow/python/distribute/ |
| D | cross_device_ops.py | 429 def _group_value_by_device(per_replica_values): argument
447 destinations = per_replica_values[0].devices
449 for per_replica_value in per_replica_values:
711 def _batch_all_reduce(self, reduce_op, per_replica_values): argument
714 cross_device_utils.split_by_sparsity(per_replica_values))
910 def _batch_all_reduce(self, reduce_op, per_replica_values): argument
917 (len(per_replica_values), self._all_reduce_spec, self._num_packs,
920 device_grads = _group_value_by_device(per_replica_values)
956 return _ungroup_and_make_mirrored(aggregated_grads, per_replica_values[0],
1057 def _make_gradient_chunks(self, per_replica_values, num_packs): argument
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| D | input_lib_test.py | 584 def map_fn(per_replica_values): argument
587 map(sparse_tensor.is_sparse, per_replica_values.values)) else
588 math_ops.reduce_sum, (per_replica_values,))
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| /external/tensorflow/tensorflow/python/keras/distribute/ |
| D | distributed_training_utils.py | 216 def flatten_per_replica_values(distribution_strategy, per_replica_values): argument
236 return [e for flattened in nest.flatten(per_replica_values)
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