class_docstr: Step a single env in a separate process for lock free paralellism.
class_docstr_tok: ["Step","a","single","env","in","a","separate","process","for","lock","free","paralellism","."]
docstr: Asynchronously call a method of the external environment.
  
  Args:
    name: Name of the method to call.
    *args: Positional arguments to forward to the method.
    **kwargs: Keyword arguments to forward to the method.
  
  Returns:
    The attribute.
docstr_tok: ["Asynchronously","call","a","method","of","the","external","environment",".","Args",":","name",":","Name","of","the","method","to","call",".","*","args",":","Positional","arguments","to","forward","to","the","method",".","*","*","kwargs",":","Keyword","arguments","to","forward","to","the","method",".","Returns",":","The","attribute","."]
code: def call(self, name: Text, *args, **kwargs) -> Promise:
      """Asynchronously call a method of the external environment.
  
      Args:
        name: Name of the method to call.
        *args: Positional arguments to forward to the method.
        **kwargs: Keyword arguments to forward to the method.
  
      Returns:
        The attribute.
      """
      payload = name, args, kwargs
      self._conn.send((self._CALL, payload))
      return self._receive
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import atexit
  import sys
  import traceback
  from typing import Any, Callable, Sequence, Text, Union
  from absl import logging
  import cloudpickle
  import gin
  import numpy
  import tensorflow
  from tf_agents.environments import py_environment
  from tf_agents.system import system_multiprocessing
  from tf_agents.trajectories import time_step
  from tf_agents.typing import types
  from tf_agents.utils import nest_utils
label_desc: Use image node_id 8 for calling the ProcessPyEnvironment obj's underlying member method code with example usage: obj.call(name) and returns: self