An Op to exchange data across TPU replicas.
tf.raw_ops.AllToAll(
    input, group_assignment, concat_dimension, split_dimension, split_count,
    name=None
)
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]]
Args | |
|---|---|
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). | 
Returns | |
|---|---|
A Tensor. Has the same type as input.
 |