# Module: tf.compat.v1.distribute.experimental

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Experimental Distribution Strategy library.

## Classes

[`class CentralStorageStrategy`](https://www.tensorflow.org/versions/r2.14/api_docs/python/tf/compat/v1/distribute/experimental/CentralStorageStrategy): A one-machine strategy that puts all variables on a single device.

[`class CollectiveCommunication`](https://www.tensorflow.org/versions/r2.14/api_docs/python/tf/distribute/experimental/CommunicationImplementation): Cross device communication implementation.

[`class CollectiveHints`](https://www.tensorflow.org/versions/r2.14/api_docs/python/tf/distribute/experimental/CollectiveHints): Hints for collective operations like AllReduce.

[`class CommunicationImplementation`](https://www.tensorflow.org/versions/r2.14/api_docs/python/tf/distribute/experimental/CommunicationImplementation): Cross device communication implementation.

[`class CommunicationOptions`](https://www.tensorflow.org/versions/r2.14/api_docs/python/tf/distribute/experimental/CommunicationOptions): Options for cross device communications like All-reduce.

[`class MultiWorkerMirroredStrategy`](https://www.tensorflow.org/versions/r2.14/api_docs/python/tf/compat/v1/distribute/experimental/MultiWorkerMirroredStrategy): A distribution strategy for synchronous training on multiple workers.

[`class ParameterServerStrategy`](https://www.tensorflow.org/versions/r2.14/api_docs/python/tf/compat/v1/distribute/experimental/ParameterServerStrategy): An asynchronous multi-worker parameter server tf.distribute strategy.

[`class TPUStrategy`](https://www.tensorflow.org/versions/r2.14/api_docs/python/tf/compat/v1/distribute/experimental/TPUStrategy): TPU distribution strategy implementation.