RandomStrategy
Defined in tensorflow/contrib/training/python/training/device_setter.py
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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.
__init__
__init__( num_ps_tasks, seed=0 )
Creates a new RandomStrategy
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__call__
__call__(op)
Chooses a ps task index for the given Operation
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© 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