tf.distribute.Server  |  TensorFlow v2.16.1 (original) (raw)

tf.distribute.Server

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

View aliases

Compat aliases for migration

SeeMigration guide for more details.

tf.compat.v1.distribute.Server, tf.compat.v1.train.Server

tf.distribute.Server(
    server_or_cluster_def,
    job_name=None,
    task_index=None,
    protocol=None,
    config=None,
    start=True
)

Used in the notebooks

Used in the guide Used in the tutorials
Migrate multi-worker CPU/GPU training Parameter server training with ParameterServerStrategy

A tf.distribute.Server instance encapsulates a set of devices and atf.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.

Args
server_or_cluster_def A tf.train.ServerDef or tf.train.ClusterDefprotocol 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.
Raises
tf.errors.OpError Or one of its subclasses if an error occurs while creating the TensorFlow server.
Attributes
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 atf.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

View source

@staticmethod create_local_server( config=None, start=True )

Creates a new single-process cluster running on the local host.

This method is a convenience wrapper for creating atf.distribute.Server with a tf.train.ServerDef that specifies a single-process cluster containing a single task in a job called"local".

Args
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.
Returns
A local tf.distribute.Server.

join

View source

join()

Blocks until the server has shut down.

This method currently blocks forever.

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

start

View source

start()

Starts this server.

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