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# tf.raw_ops.AllToAll

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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