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tf.distribute.Server

An in-process TensorFlow server, for use in distributed training.

Used in the notebooks

Used in the guide Used in the tutorials

A tf.distribute.Server instance encapsulates a set of devices and a tf.compat.v1.Session target that can participate in distributed training. A server belongs to a cluster (specified by a tf.train.ClusterSpec), and corresponds to a particular task in a named job. The server can communicate with any other server in the same cluster.

server_or_cluster_def A tf.train.ServerDef or tf.train.ClusterDef protocol buffer, or a tf.train.ClusterSpec object, describing the server to be created and/or the cluster of which it is a member.
job_name (Optional.) Specifies the name of the job of which the server is a member. Defaults to the value in server_or_cluster_def, if specified.
task_index (Optional.) Specifies the task index of the server in its job. Defaults to the value in server_or_cluster_def, if specified. Otherwise defaults to 0 if the server's job has only one task.
protocol (Optional.) Specifies the protocol to be used by the server. Acceptable values include "grpc", "grpc+verbs". Defaults to the value in server_or_cluster_def, if specified. Otherwise defaults to "grpc".
config (Options.) A tf.compat.v1.ConfigProto that specifies default configuration options for all sessions that run on this server.
start (Optional.) Boolean, indicating whether to start the server after creating it. Defaults to True.

tf.errors.OpError Or one of its subclasses if an error occurs while creating the TensorFlow server.

server_def Returns the tf.train.ServerDef for this server.
target Returns the target for a tf.compat.v1.Session to connect to this server.

To create a tf.compat.v1.Session that connects to this server, use the following snippet:

server = tf.distribute.Server(...)
with tf.compat.v1.Session(server.target):
  # ...

Methods

create_local_server

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