tfr.keras.strategy_utils.get_strategy

Creates and initializes the requested tf.distribute strategy.

tfr.keras.strategy_utils.get_strategy(
    strategy: str,
    cluster_resolver: Optional[tf.distribute.cluster_resolver.ClusterResolver] = None,
    variable_partitioner: Optional[tf.distribute.experimental.partitioners.Partitioner] = _USE_DEFAULT_VARIABLE_PARTITIONER,
    tpu: Optional[str] = ''
) -> Union[None, tf.distribute.MirroredStrategy, tf.distribute.
    MultiWorkerMirroredStrategy, tf.distribute.experimental.
    ParameterServerStrategy, tf.distribute.experimental.TPUStrategy]

Example usage:

strategy = get_strategy("MirroredStrategy")

Args
strategy	Key for a tf.distribute strategy to be used to train the model. Choose from ["MirroredStrategy", "MultiWorkerMirroredStrategy", "ParameterServerStrategy", "TPUStrategy"]. If None, no distributed strategy will be used.
cluster_resolver	A cluster_resolver to build strategy.
variable_partitioner	Variable partitioner to be used in ParameterServerStrategy. If the argument is not specified, a recommended tf.distribute.experimental.partitioners.MinSizePartitioner is used. If the argument is explicitly specified as None, no partitioner is used and that variables are not partitioned. This arg is used only when the strategy is tf.distribute.experimental.ParameterServerStrategy. See tf.distribute.experimental.ParameterServerStrategy class doc for more information.
tpu	TPU address for TPUStrategy. Not used for other strategy.

Returns
A strategy will be used for distributed training.

Raises
ValueError if strategy is not supported.