tf.distribute.cluster_resolver.SimpleClusterResolver

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Simple implementation of ClusterResolver that accepts a ClusterSpec.

Inherits From: ClusterResolver

tf.distribute.cluster_resolver.SimpleClusterResolver(
    cluster_spec, master='', task_type=None, task_id=None, environment='',
    num_accelerators=None, rpc_layer=None
)

Attributes:

Methods

cluster_spec

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cluster_spec()

Returns the ClusterSpec passed into the constructor.

master

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master(
    task_type=None, task_id=None, rpc_layer=None
)

Returns the master address to use when creating a session.

Args:

Returns:

The name or URL of the session master.

If a task_type and task_id is given, this will override the master string passed into the initialization function.

num_accelerators

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num_accelerators(
    task_type=None, task_id=None, config_proto=None
)

Returns the number of accelerator cores per worker.

The SimpleClusterResolver does not do automatic detection of accelerators, so a TensorFlow session will never be created, and thus all arguments are unused and we simply assume that the type of accelerator is a GPU and return the value in provided to us in the constructor.

Args: