code: def test_needs_reset(self):
      steps = 10
  
      outdir = tempfile.mkdtemp()
  
      agent = mock.Mock()
      agent.batch_act_and_train.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, False, {}),
                  (("state", 3), 0, 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), 0, False, {"needs_reset": True}),
                  (("state", 3), 0, False, {"needs_reset": True}),
                  (("state", 5), -0.5, False, {}),
                  (("state", 6), 0, False, {}),
                  (("state", 7), 1, True, {}),
              ]
          return env
  
      vec_env = chainerrl.envs.SerialVectorEnv(
          [make_env(i) for i in range(2)]
      )
  
      chainerrl.experiments.train_agent_batch(
          agent=agent,
          env=vec_env,
          steps=steps,
          outdir=outdir,
      )
  
      self.assertEqual(vec_env.envs[0].reset.call_count, 2)
      self.assertEqual(vec_env.envs[0].step.call_count, 5)
      self.assertEqual(vec_env.envs[1].reset.call_count, 3)
      self.assertEqual(vec_env.envs[1].step.call_count, 5)
  
file_path: chainerrl/tests/experiments_tests/test_train_agent_batch.py
imports: import math
  import tempfile
  import unittest
  from unittest import mock
  from chainer import testing
  import chainerrl
label_desc: Use image node_id 1 for calling the TestTrainAgentBatchNeedsReset obj's underlying member method code with example usage: obj.test_needs_reset() and returns: env