Defined in tensorflow/_api/v1/distribute/__init__.py
.
Library for running a computation across multiple devices.
Classes
class InputContext
: A class wrapping information needed by an input function.
class InputReplicationMode
: Replication mode for input function.
class MirroredStrategy
: Mirrors vars to distribute across multiple devices and machines.
class ReduceOp
: Indicates how a set of values should be reduced.
class ReplicaContext
: tf.distribute.Strategy
API when in a replica context.
class Server
: An in-process TensorFlow server, for use in distributed training.
class Strategy
: A list of devices with a state & compute distribution policy.
class StrategyExtended
: Additional APIs for algorithms that need to be distribution-aware.
Functions
get_loss_reduction(...)
: tf.distribute.ReduceOp
corresponding to the last loss reduction.
get_replica_context(...)
: Returns the current tf.distribute.ReplicaContext
or None
.
get_strategy(...)
: Returns the current tf.distribute.Strategy
object.
has_strategy(...)
: Return if there is a current non-default tf.distribute.Strategy
.
in_cross_replica_context(...)
: Returns True if in a cross-replica context.