tf.train.ClusterSpec     View source on GitHub    Represents a cluster as a set of "tasks", organized into "jobs".  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.train.ClusterSpec  
tf.train.ClusterSpec(
    cluster
)
 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). 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: cluster = tf.train.ClusterSpec({"worker": {1: "worker1.example.com:2222"},
                                "ps": ["ps0.example.com:2222",
                                       "ps1.example.com:2222"]})

 


 Args
  cluster   A dictionary mapping one or more job names to (i) a list of network addresses, or (ii) a dictionary mapping integer task indices to network addresses; or a tf.train.ClusterDef protocol buffer.   
 


 Raises
  TypeError   If cluster is not a dictionary mapping strings to lists of strings, and not a tf.train.ClusterDef protobuf.   
 


 Attributes
  jobs   Returns a list of job names in this cluster.    Methods as_cluster_def View source 
as_cluster_def()
 Returns a tf.train.ClusterDef protocol buffer based on this cluster. as_dict View source 
as_dict()
 Returns a dictionary from job names to their tasks. For each job, if the task index space is dense, the corresponding value will be a list of network addresses; otherwise it will be a dictionary mapping (sparse) task indices to the corresponding addresses.
 


 Returns   A dictionary mapping job names to lists or dictionaries describing the tasks in those jobs.  
 job_tasks View source 
job_tasks(
    job_name
)
 Returns a mapping from task ID to address in the given job. 
Note: For backwards compatibility, this method returns a list. If the given job was defined with a sparse set of task indices, the length of this list may not reflect the number of tasks defined in this job. Use the tf.train.ClusterSpec.num_tasks method to find the number of tasks defined in a particular job.

 


 Args
  job_name   The string name of a job in this cluster.   
 


 Returns   A list of task addresses, where the index in the list corresponds to the task index of each task. The list may contain None if the job was defined with a sparse set of task indices.  

 


 Raises
  ValueError   If job_name does not name a job in this cluster.    num_tasks View source 
num_tasks(
    job_name
)
 Returns the number of tasks defined in the given job.
 


 Args
  job_name   The string name of a job in this cluster.   
 


 Returns   The number of tasks defined in the given job.  

 


 Raises
  ValueError   If job_name does not name a job in this cluster.    task_address View source 
task_address(
    job_name, task_index
)
 Returns the address of the given task in the given job.
 


 Args
  job_name   The string name of a job in this cluster.  
  task_index   A non-negative integer.   
 


 Returns   The address of the given task in the given job.  

 


 Raises
  ValueError   If job_name does not name a job in this cluster, or no task with index task_index is defined in that job.    task_indices View source 
task_indices(
    job_name
)
 Returns a list of valid task indices in the given job.
 


 Args
  job_name   The string name of a job in this cluster.   
 


 Returns   A list of valid task indices in the given job.  

 


 Raises
  ValueError   If job_name does not name a job in this cluster, or no task with index task_index is defined in that job.    __bool__ View source 
__bool__()
 __eq__ View source 
__eq__(
    other
)
 Return self==value. __ne__ View source 
__ne__(
    other
)
 Return self!=value. __nonzero__ View source 
__nonzero__()