class_docstr: Holds the test environment information.
  
  Tests should modify the attributes of the instance returned by `env()` in the
  main process if needed, and it will be passed to the worker processes each
  time a test case is run.
class_docstr_tok: ["Holds","the","test","environment","information",".","Tests","should","modify","the","attributes","of","the","instance","returned","by","`","env","(",")","`","in","the","main","process","if","needed",",","and","it","will","be","passed","to","the","worker","processes","each","time","a","test","case","is","run","."]
code: def __init__(self):
      self.tf_data_service_dispatcher = None
      # Note that this includes GPUs that may not be visible to the current
      # worker.
      self.total_phsyical_gpus = None
  
imports: import collections
  import copy
  import re
  import sys
  import types
  import unittest
  from absl import app
  import six
  from tensorflow.python.client import session
  from tensorflow.python.distribute import collective_all_reduce_strategy
  from tensorflow.python.distribute import distribute_lib
  from tensorflow.python.distribute import multi_process_runner
  from tensorflow.python.distribute import multi_worker_test_base
  from tensorflow.python.eager import context
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import combinations
  from tensorflow.python.framework import config
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_combinations
  from tensorflow.python.framework import test_util
  from tensorflow.python.platform import flags
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.util import tf_decorator
  from tensorflow.python.util import tf_inspect
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 1 to create a new TestEnvironment object from inherited base classes: object with example: obj = TestEnvironment()