class_docstr: ClusterResolver for system with Slurm workload manager.
  
  This is an implementation of ClusterResolver for Slurm clusters. This allows
  the specification of jobs and task counts, number of tasks per node, number
  of GPUs on each node and number of GPUs for each task. It retrieves system
  attributes by Slurm environment variables, resolves allocated computing node
  names, constructs a cluster and returns a ClusterResolver object which can be
  used for distributed TensorFlow.
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docstr: Returns job name and task_id for the process which calls this.
  
  This returns the job name and task index for the process which calls this
  function according to its rank and cluster specification. The job name and
  task index are set after a cluster is constructed by cluster_spec otherwise
  defaults to None.
  
  Returns:
    A string specifying job name the process belongs to and an integer
      specifying the task index the process belongs to in that job.
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code: def get_task_info(self):
      """Returns job name and task_id for the process which calls this.
  
      This returns the job name and task index for the process which calls this
      function according to its rank and cluster specification. The job name and
      task index are set after a cluster is constructed by cluster_spec otherwise
      defaults to None.
  
      Returns:
        A string specifying job name the process belongs to and an integer
          specifying the task index the process belongs to in that job.
      """
      return self.task_type, self.task_id
  
imports: import os
  import re
  import subprocess
  from tensorflow.python.distribute.cluster_resolver.cluster_resolver import ClusterResolver
  from tensorflow.python.distribute.cluster_resolver.cluster_resolver import format_master_url
  from tensorflow.python.training.server_lib import ClusterSpec
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 7 for calling the SlurmClusterResolver obj's underlying member method code with example usage: obj.get_task_info() and returns: self,  self