class_docstr: Coin Game environment.
code: def __init__(self, config: Optional[Dict] = None):
      if config is None:
          config = {}
  
      self._validate_config(config)
  
      self._load_config(config)
      self.player_red_id, self.player_blue_id = self.players_ids
      self.n_features = self.grid_size**2 * (2 * self.NUM_AGENTS)
      self.observation_space = gym.spaces.Box(
          low=0,
          high=1,
          shape=(self.grid_size, self.grid_size, 4),
          dtype="uint8",
      )
  
      self.step_count_in_current_episode = None
      if self.output_additional_info:
          self._init_info()
  
imports: import copy
  import gymnasium
  import logging
  import numpy
  from gymnasium.spaces import Discrete
  from gymnasium.utils import seeding
  from ray.rllib.env.multi_agent_env import MultiAgentEnv
  from ray.rllib.utils import override
  from typing import Dict, Optional
  from ray.rllib.examples.env.utils.interfaces import InfoAccumulationInterface
label_desc: Use image node_id 1 to create a new CoinGame object from inherited base classes: InfoAccumulationInterface, MultiAgentEnv, gym with example: obj = CoinGame(config)