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tf.contrib.training.RandomStrategy

Class RandomStrategy

Defined in tensorflow/contrib/training/python/training/device_setter.py.

Returns a random PS task for op placement.

This may perform better than the default round-robin placement if you have a large number of variables. Depending on your architecture and number of parameter servers, round-robin can lead to situations where all of one type of variable is placed on a single PS task, which may lead to contention issues.

This strategy uses a hash function on the name of each op for deterministic placement.

Methods

__init__

__init__(
    num_ps_tasks,
    seed=0
)

Creates a new RandomStrategy.

__call__

__call__(op)

Chooses a ps task index for the given Operation.

© 2018 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/contrib/training/RandomStrategy