code: def test_multiple_steps():
      max_steps = 20
      env_all = [init_env(max_steps, env_class) for env_class in ENVS]
      n_steps = int(max_steps * 0.75)
  
      for env in env_all:
          obs, info = env.reset()
          check_obs(obs, env)
          assert_logger_buffer_size_two_players(env, n_steps=0)
  
          for step_i in range(1, n_steps, 1):
              actions = {
                  policy_id: random.randint(0, env.NUM_ACTIONS - 1)
                  for policy_id in env.players_ids
              }
              obs, reward, done, truncated, info = env.step(actions)
              check_obs(obs, env)
              assert_logger_buffer_size_two_players(env, n_steps=step_i)
              assert not done["__all__"]
  
file_path: ray/rllib/examples/env/tests/test_matrix_sequential_social_dilemma.py
imports: import random
  from ray.rllib.examples.env.matrix_sequential_social_dilemma import IteratedPrisonersDilemma, IteratedChicken, IteratedStagHunt, IteratedBoS
label_desc: Use image node_id 6 for calling a global function with example usage: test_multiple_steps() without return types