def alltoall(self, x, mesh_axis, split_axis, concat_axis):
"""Grouped alltoall (like MPI alltoall with splitting and concatenation).
Args:
x: a LaidOutTensor
mesh_axis: an integer the mesh axis along which to group
split_axis: an integer (the Tensor axis along which to split)
concat_axis: an integer (the Tensor axis along which to concatenate)
Returns:
a LaidOutTensor
"""
x = x.to_laid_out_tensor()
t = x.one_slice
group_assignment = self._create_group_assignment([mesh_axis])
dtype = t.dtype
if dtype == tf.float32:
# There seems to be a bug with float32 alltoall.
# Do it in bfloat16 until the bug is fixed.
# TODO(noam): file a bug
t = tf.to_bfloat16(t)
t = tpu_ops.all_to_all(t,
concat_dimension=concat_axis,
split_dimension=split_axis,
split_count=len(group_assignment[0]),
group_assignment=group_assignment)
t = tf.cast(t, dtype)
x = self.LaidOutTensor([t])
return x
def alltoall(self, x, mesh_axis, split_axis, concat_axis):
"""Grouped alltoall (like MPI alltoall with splitting and concatenation).
Args:
x: a LaidOutTensor
mesh_axis: an integer the mesh axis along which to group
split_axis: an integer (the Tensor axis along which to split)
concat_axis: an integer (the Tensor axis along which to concatenate)
Returns:
a LaidOutTensor
"""
x = x.to_laid_out_tensor()
t = x.one_slice
group_assignment = self._create_group_assignment([mesh_axis])
t = tpu_ops.all_to_all(
t,
concat_dimension=concat_axis,
split_dimension=split_axis,
split_count=len(group_assignment[0]),
group_assignment=group_assignment)
x = self.LaidOutTensor([t])
return x
