class_docstr: Represents a cluster as a set of "tasks", organized into "jobs".
  
  A `tf.train.ClusterSpec` represents the set of processes that
  participate in a distributed TensorFlow computation. Every
  `tf.distribute.Server` is constructed in a particular cluster.
  
  To create a cluster with two jobs and five tasks, you specify the
  mapping from job names to lists of network addresses (typically
  hostname-port pairs).
  
  ```python
  cluster = tf.train.ClusterSpec({"worker": ["worker0.example.com:2222",
                                             "worker1.example.com:2222",
                                             "worker2.example.com:2222"],
                                  "ps": ["ps0.example.com:2222",
                                         "ps1.example.com:2222"]})
  ```
  
  Each job may also be specified as a sparse mapping from task indices
  to network addresses. This enables a server to be configured without
  needing to know the identity of (for example) all other worker
  tasks:
  
  ```python
  cluster = tf.train.ClusterSpec({"worker": {1: "worker1.example.com:2222"},
                                  "ps": ["ps0.example.com:2222",
                                         "ps1.example.com:2222"]})
  ```
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code: def __repr__(self):
      key_values = self.as_dict()
      string_items = [
          repr(k) + ": " + repr(key_values[k])
          for k in sorted(key_values)
      ]
      return "ClusterSpec({" + ", ".join(string_items) + "})"
  
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 5 for calling the ClusterSpec obj's underlying member method code with example usage: obj.__repr__() and returns: unknown