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tf.contrib.cluster_resolver.ClusterResolver

Class ClusterResolver

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

Abstract class for all implementations of ClusterResolvers.

This defines the skeleton for all implementations of ClusterResolvers. ClusterResolvers are a way for TensorFlow to communicate with various cluster management systems (e.g. GCE, AWS, etc...).

By letting TensorFlow communicate with these systems, we will be able to automatically discover and resolve IP addresses for various TensorFlow workers. This will eventually allow us to automatically recover from underlying machine failures and scale TensorFlow worker clusters up and down.

Methods

cluster_spec

cluster_spec()

Retrieve the current state of the cluster and returns a ClusterSpec.

Returns:

A ClusterSpec representing the state of the cluster at the moment this function is called.

Implementors of this function must take care in ensuring that the ClusterSpec returned is up-to-date at the time of calling this function. This usually means retrieving the information from the underlying cluster management system every time this function is invoked and reconstructing a cluster_spec, rather than attempting to cache anything.

master

master()

...

© 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/cluster_resolver/ClusterResolver