class_docstr: Batch of environments inside the TensorFlow graph.
  
  The batch of environments will be stepped and reset inside of the graph using
  a tf.py_func(). The current batch of observations, actions, rewards, and done
  flags are held in according variables.
docstr: Access the variable holding the current observation.
docstr_tok: ["Access","the","variable","holding","the","current","observation","."]
code: def observ(self):
      """Access the variable holding the current observation."""
      return self._observ.read_value()
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import copy
  import os
  import numpy
  from tensor2tensor.data_generators.gym_env import DummyWorldModelProblem
  from tensor2tensor.layers import common_layers
  from tensor2tensor.layers import common_video
  from tensor2tensor.rl.envs import in_graph_batch_env
  from tensor2tensor.utils import registry
  from tensor2tensor.utils import trainer_lib
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 7 for calling the SimulatedBatchEnv obj's underlying member method code with example usage: obj.observ() and returns: self