tf.distribute.Server     View source on GitHub    An in-process TensorFlow server, for use in distributed training.  View aliases  Compat aliases for migration 
See Migration 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
)
 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.
 


 Args
  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.   
 


 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 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 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 a tf.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.