code: def _create_replay_buffer_and_insert(env: EnvWrapper):
      env.seed(1)
      replay_buffer = ReplayBuffer(replay_capacity=6, batch_size=1)
      replay_buffer_inserter = make_replay_buffer_inserter(env)
      obs = env.reset()
      inserted = []
      terminal = False
      i = 0
      while not terminal and i < 5:
          logger.info(f"Iteration: {i}")
          action = env.action_space.sample()
          next_obs, reward, terminal, _ = env.step(action)
          inserted.append(
              {
                  "observation": obs,
                  "action": action,
                  "reward": reward,
                  "terminal": terminal,
              }
          )
          transition = Transition(
              mdp_id=0,
              sequence_number=i,
              observation=obs,
              action=action,
              reward=reward,
              terminal=terminal,
              log_prob=0.0,
          )
          replay_buffer_inserter(replay_buffer, transition)
          obs = next_obs
          i += 1
  
      return replay_buffer, inserted
  
file_path: ReAgent/reagent/gym/tests/preprocessors/test_replay_buffer_inserters.py
imports: import logging
  import unittest
  import gym
  import numpy
  import numpy.testing
  import torch
  from reagent.gym.envs import EnvWrapper
  from reagent.gym.preprocessors import make_replay_buffer_inserter
  from reagent.gym.types import Transition
  from reagent.replay_memory import ReplayBuffer
  from reagent.test.base.horizon_test_base import HorizonTestBase
label_desc: Use image node_id 1 for calling a global function with example usage: _create_replay_buffer_and_insert(env) and returns: replay_buffer,  inserted