tf.distribute.ReductionToOneDevice

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

Inherits From: CrossDeviceOps

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

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

mirrored_strategy = tf.distribute.MirroredStrategy(
    cross_device_ops=tf.distribute.ReductionToOneDevice())

Args:

Methods

batch_reduce

View source

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.

This can be faster than multiple individual reduces because we can fuse several tensors into one or multiple packs before reduction.

Args:

Returns:

a list of Mirrored objects.

Raises:

broadcast

View source

broadcast(
    tensor, destinations
)

Broadcast the tensor to destinations.

Args:

Returns:

a Mirrored object.

reduce

View source

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:

Returns:

a Mirrored object.

Raises: