tf.distribute.ReductionToOneDevice

Always do reduction to one device first and then do broadcasting.

Compat aliases for migration

See Migration guide for more details.

tf.distribute.ReductionToOneDevice(
    reduce_to_device=None, accumulation_fn=None
)

Batch reduction is done by reduction on each element one by one.

Args
`reduce_to_device`	the intermediate device to reduce to. If None, reduce to the first device in `destinations` of the reduce() method.
`accumulation_fn`	a function that does accumulation. If None, then `tf.math.add_n` is used.

Methods

batch_reduce(
    reduce_op, value_destination_pairs
)

Reduce PerReplica objects in a batch.

Reduce each first element in value_destination_pairs to each second element which indicates the destinations.

Args
`reduce_op`	Indicates how per_replica_value will be reduced. Accepted values are `tf.distribute.ReduceOp.SUM`, `tf.distribute.ReduceOp.MEAN`.
`value_destination_pairs`	a list or a tuple of tuples of PerReplica objects (or tensors with device set if there is one device) and destinations.

Returns
a list of Mirrored objects.

Raises
`ValueError`	if `value_destination_pairs` is not a list or a tuple of tuples of PerReplica objects and destinations

broadcast(
    tensor, destinations
)

Broadcast the tensor to destinations.

Args
`tensor`	the tensor to broadcast.
`destinations`	the broadcast destinations.

Returns
a Mirrored object.

reduce(
    reduce_op, per_replica_value, destinations
)

Reduce per_replica_value to destinations.

It runs the reduction operation defined by reduce_op and put the result on destinations.

Args
`reduce_op`	Indicates how per_replica_value will be reduced. Accepted values are `tf.distribute.ReduceOp.SUM`, `tf.distribute.ReduceOp.MEAN`.
`per_replica_value`	a PerReplica object or a tensor with device set.
`destinations`	the reduction destinations.

Returns
a Mirrored object.

Raises
`ValueError`	if per_replica_value can't be converted to a PerReplica object.