class_docstr: Class to count number of episodes run by an observer.
class_docstr_tok: ["Class","to","count","number","of","episodes","run","by","an","observer","."]
code: def __init__(self, variable_scope="num_episodes_step_observer"):
      with tf.compat.v1.variable_scope(variable_scope):
          self._num_episodes = common.create_variable(
              "num_episodes", 0, shape=[], dtype=tf.int32
          )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from typing import Any
  import numpy
  import tensorflow
  from tf_agents import specs
  from tf_agents.environments import py_environment
  from tf_agents.policies import py_policy
  from tf_agents.policies import tf_policy
  from tf_agents.replay_buffers import tf_uniform_replay_buffer
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import policy_step
  from tf_agents.trajectories import time_step
  from tf_agents.trajectories import trajectory
  from tf_agents.utils import common
label_desc: Use image node_id 1 to create a new NumEpisodesObserver object from inherited base classes: object with example: obj = NumEpisodesObserver(variable_scope)