code: def test_timesteps(self):
      agent = mock.Mock()
      agent.batch_act.side_effect = [[1, 1]] * 5
  
      def make_env(idx):
          env = mock.Mock()
          if idx == 0:
              # First episode: 0 -> 1 -> 2 -> 3 (reset)
              # Second episode: 4 -> 5 -> 6 -> 7 (done)
              env.reset.side_effect = [("state", 0), ("state", 4)]
              env.step.side_effect = [
                  (("state", 1), 0, False, {}),
                  (("state", 2), 0.1, False, {}),
                  (("state", 3), 0.2, False, {"needs_reset": True}),
                  (("state", 5), -0.5, False, {}),
                  (("state", 6), 0, False, {}),
                  (("state", 7), 1, True, {}),
              ]
          else:
              # First episode: 0 -> 1 (reset)
              # Second episode: 2 -> 3 (reset)
              # Third episode: 4 -> 5 -> 6 -> 7 (done)
              env.reset.side_effect = [
                  ("state", 0),
                  ("state", 2),
                  ("state", 4),
              ]
              env.step.side_effect = [
                  (("state", 1), 2, False, {"needs_reset": True}),
                  (("state", 3), 3, False, {"needs_reset": True}),
                  (("state", 5), -0.6, False, {}),
                  (("state", 6), 0, False, {}),
                  (("state", 7), 1, True, {}),
              ]
          return env
  
      vec_env = chainerrl.envs.SerialVectorEnv(
          [make_env(i) for i in range(2)]
      )
      if self.n_episodes:
          with self.assertRaises(AssertionError):
              scores = evaluator.batch_run_evaluation_episodes(
                  vec_env,
                  agent,
                  n_steps=self.n_timesteps,
                  n_episodes=self.n_episodes,
              )
      else:
          # First Env:  [1   2   (3_a)  5  6   (7_a)]
          # Second Env: [(1)(3_b) 5     6 (7_b)]
          scores = evaluator.batch_run_evaluation_episodes(
              vec_env,
              agent,
              n_steps=self.n_timesteps,
              n_episodes=self.n_episodes,
          )
          if self.n_timesteps == 2:
              self.assertAlmostEqual(len(scores), 1)
              self.assertAlmostEqual(scores[0], 0.1)
              self.assertEqual(agent.batch_observe.call_count, 2)
          else:
              self.assertAlmostEqual(len(scores), 3)
              self.assertAlmostEqual(scores[0], 0.3)
              self.assertAlmostEqual(scores[1], 2.0)
              self.assertAlmostEqual(scores[2], 3.0)
          # batch_reset should be all True
          self.assertTrue(all(agent.batch_observe.call_args[0][3]))
  
imports: import tempfile
  import unittest
  from unittest import mock
  from chainer import testing
  import chainerrl
  from chainerrl.experiments import evaluator
label_desc: Use image node_id 1 for calling the TestBatchRunTimeBasedEvaluationEpisode obj's underlying member method code with example usage: obj.test_timesteps() and returns: env