def start_server(self):
        """
        Creates and stores a tf server (and optionally joins it if we are a parameter-server).
        Only relevant, if we are running in distributed mode.
        """
        self.server = tf.train.Server(
            server_or_cluster_def=self.distributed_spec["cluster_spec"],
            job_name=self.distributed_spec["job"],
            task_index=self.distributed_spec["task_index"],
            protocol=self.distributed_spec.get("protocol"),
            config=self.distributed_spec.get("session_config"),
            start=True
        )
        if self.distributed_spec["job"] == "ps":
            self.server.join()
            # This is unreachable?
            quit()
def start_server(self):
        """
        Creates and stores a tf server (and optionally joins it if we are a parameter-server).
        Only relevant, if we are running in distributed mode.
        """
        self.server = tf.train.Server(
            server_or_cluster_def=self.distributed_spec["cluster_spec"],
            job_name=self.distributed_spec["job"],
            task_index=self.distributed_spec["task_index"],
            protocol=self.distributed_spec.get("protocol"),
            config=self.distributed_spec.get("session_config"),
            start=True
        )
        if self.distributed_spec["job"] == "ps":
            self.server.join()
            # This is unreachable?
            quit()
def start_server ( self ) : self . server = tf . train . Server ( server_or_cluster_def = self . distributed_spec [ "cluster_spec" ] , job_name = self . distributed_spec [ "job" ] , task_index = self . distributed_spec [ "task_index" ] , protocol = self . distributed_spec . get ( "protocol" ) , config = self . distributed_spec . get ( "session_config" ) , start = True ) if self . distributed_spec [ "job" ] == "ps" : self . server . join ( ) # This is unreachable? quit ( )
Creates and stores a tf server (and optionally joins it if we are a parameter-server).
        Only relevant, if we are running in distributed mode.
Creates and stores a tf server ( and optionally joins it if we are a parameter - server ) . Only relevant if we are running in distributed mode .