/TensorFlow 2.4


An Op to exchange data across TPU replicas.

On each replica, the input is split into split_count blocks along split_dimension and send to the other replicas given group_assignment. After receiving split_count - 1 blocks from other replicas, we concatenate the blocks along concat_dimension as the output.

For example, suppose there are 2 TPU replicas: replica 0 receives input: [[A, B]] replica 1 receives input: [[C, D]]

group_assignment=[[0, 1]] concat_dimension=0 split_dimension=1 split_count=2

replica 0's output: [[A], [C]] replica 1's output: [[B], [D]]

input A Tensor. Must be one of the following types: float32, float64, int32, uint8, int16, int8, complex64, int64, qint8, quint8, qint32, bfloat16, uint16, complex128, half, uint32, uint64, bool. The local input to the sum.
group_assignment A Tensor of type int32. An int32 tensor with shape [num_groups, num_replicas_per_group]. group_assignment[i] represents the replica ids in the ith subgroup.
concat_dimension An int. The dimension number to concatenate.
split_dimension An int. The dimension number to split.
split_count An int. The number of splits, this number must equal to the sub-group size(group_assignment.get_shape()[1])
name A name for the operation (optional).
A Tensor. Has the same type as input.

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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.