code: def __init__(self, max_steps=MAX_STEP):
      np.random.seed(123)
      torch.manual_seed(123)
      self.max_steps = max_steps
      self.reward_map = {}
      self._init_reward()
      logger.debug(self.reward_map)
      self.recent_actions = deque([], maxlen=SEQ_LEN)
      self.recent_states = deque([], maxlen=SEQ_LEN)
      self.cur_state = None
      self.action_space = Discrete(ACTION_DIM)
      self.observation_space = Box(low=0, high=1, shape=(STATE_DIM,))
      self.step_cnt = 0
      self.reset()
  
imports: import itertools
  import logging
  from collections import deque
  import numpy
  import torch
  from gym import Env
  from gym.spaces import Box, Discrete
label_desc: Use image node_id 1 to create a new StringGameEnv object from inherited base classes: Env with example: obj = StringGameEnv(max_steps)