class_docstr: SimulatedBatchEnv in a Gym-like interface, environments are  batched.
code: def reset(self, indices=None):
      if indices is None:
          indices = np.array(range(self.batch_size))
      obs = self._sess.run(
          self._reset_op, feed_dict={self._indices_t: indices}
      )
      return obs
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from gym import Env
  import numpy
  from tensor2tensor.rl.envs.simulated_batch_env import SimulatedBatchEnv
  import tensorflow.compat.v1
label_desc: Use image node_id 6 for calling the SimulatedBatchGymEnv obj's underlying member method code with example usage: obj.reset(indices) and returns: obs