code: def test_auto_reset(self):
      time_step = self.evaluate(self.random_env.reset())
      random_action = self.evaluate(
          tensor_spec.sample_spec_nest(
              self.action_spec, outer_dims=(1,)
          )
      )
  
      attempts = 0
  
      # With a 1/10 chance of resetting on each step, the probability of failure
      # after 500 attempts should be 0.9^500, roughly 1e-23. If we miss more than
      # 500 attempts, we can safely assume the test is broken.
      while not time_step.is_last() and attempts < 500:
          time_step = self.evaluate(self.random_env.step(random_action))
          attempts += 1
  
      self.assertLess(attempts, 500)
      self.assertTrue(time_step.is_last())
  
      current_time_step = self.evaluate(
          self.random_env.current_time_step()
      )
      self.assertTrue(current_time_step.is_last())
  
      first_time_step = self.evaluate(
          self.random_env.step(random_action)
      )
      self.assertTrue(first_time_step.is_first())
  
file_path: agents/tf_agents/environments/random_tf_environment_test.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import tensorflow
  from tf_agents.environments import random_tf_environment
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import time_step
  from tf_agents.utils import test_utils
label_desc: Use image node_id 4 for calling the RandomTFEnvironmentTest obj's underlying member method code with example usage: obj.test_auto_reset() without return types