class_docstr: An in-process TensorFlow server, for use in distributed training.
  
  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.
class_docstr_tok: ["An","in-process","TensorFlow","server",",","for","use","in","distributed","training",".","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","."]
docstr: 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:
  
  ```python
  server = tf.distribute.Server(...)
  with tf.compat.v1.Session(server.target):
    # ...
  ```
  
  Returns:
    A string containing a session target for this server.
docstr_tok: ["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",":","``","`","python","server","=","tf.distribute.Server","(","...",")","with","tf.compat.v1.Session","(","server.target",")",":","#","...","``","`","Returns",":","A","string","containing","a","session","target","for","this","server","."]
code: def target(self):
      """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:
  
      ```python
      server = tf.distribute.Server(...)
      with tf.compat.v1.Session(server.target):
        # ...
      ```
  
      Returns:
        A string containing a session target for this server.
      """
      return c_api.TF_ServerTarget(self._server)
  
imports: from tensorflow.core.protobuf import cluster_pb2
  from tensorflow.core.protobuf import device_filters_pb2
  from tensorflow.core.protobuf import tensorflow_server_pb2
  from tensorflow.python.client import pywrap_tf_session
  from tensorflow.python.framework import errors
  from tensorflow.python.util import compat
  from tensorflow.python.util import deprecation
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 6 for calling the Server obj's underlying member method code with example usage: obj.target() and returns: c_api