code: def __init__(self, max_steps=MAX_STEP):
      np.random.seed(123)
      torch.manual_seed(123)
      self.max_steps = max_steps
      self.reward_map = defaultdict(float)
      self.terminal_probs = defaultdict(float)
      self._init_reward_and_terminal_probs()
      self.recent_actions = deque([], maxlen=MAX_STEP)
      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 logging
  from collections import defaultdict, 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 StringGameEnvV1 object from inherited base classes: Env with example: obj = StringGameEnvV1(max_steps)