tf.contrib.cluster_resolver.GceClusterResolver

Class GceClusterResolver

Inherits From: ClusterResolver

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

Cluster Resolver for Google Compute Engine.

This is an implementation of cluster resolvers for the Google Compute Engine instance group platform. By specifying a project, zone, and instance group, this will retrieve the IP address of all the instances within the instance group and return a Cluster Resolver object suitable for use for distributed TensorFlow.

Methods

__init__

__init__(
    project,
    zone,
    instance_group,
    port,
    job_name='worker',
    credentials='default',
    service=None
)

Creates a new GceClusterResolver object.

This takes in a few parameters and creates a GceClusterResolver project. It will then use these parameters to query the GCE API for the IP addresses of each instance in the instance group.

Args:

• project: Name of the GCE project
• zone: Zone of the GCE instance group
• instance_group: Name of the GCE instance group
• port: Port of the listening TensorFlow server (default: 8470)
• job_name: Name of the TensorFlow job this set of instances belongs to
• credentials: GCE Credentials. If nothing is specified, this defaults to GoogleCredentials.get_application_default()
• service: The GCE API object returned by the googleapiclient.discovery function. (Default: discovery.build('compute', 'v1')). If you specify a custom service object, then the credentials parameter will be ignored.

Raises:

• ImportError: If the googleapiclient is not installed.

cluster_spec

cluster_spec()

Returns a ClusterSpec object based on the latest instance group info.

This returns a ClusterSpec object for use based on information from the specified instance group. We will retrieve the information from the GCE APIs every time this method is called.

Returns:

A ClusterSpec containing host information retrieved from GCE.

master

master()

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