class_docstr: Structured environment version of the cutting 2D environment.
  The environment alternates between the two sub-steps:
  
  - Select cutting piece
  - Select cutting configuration (cutting order and cutting orientation)
  
  :param maze_env: The "flat" cutting 2D environment to wrap.
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docstr: Returns the count of agents for individual sub-steps (or -1 for dynamic agent count).
  
  This env has two sub-steps (0 and 1), in each of which one agent gets to act. Hence, we return
  {0: 1, 1: 1}.
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code: def agent_counts_dict(self) -> Dict[Union[str, int], int]:
      """Returns the count of agents for individual sub-steps (or -1 for dynamic agent count).
  
      This env has two sub-steps (0 and 1), in each of which one agent gets to act. Hence, we return
      {0: 1, 1: 1}.
      """
      return {0: 1, 1: 1}
  
imports: from copy import deepcopy
  from typing import Dict, Any, Union, Tuple, Optional, List
  import gym
  import numpy
  from maze.core.env.maze_action import MazeActionType
  from maze.core.env.maze_env import MazeEnv
  from maze.core.env.maze_state import MazeStateType
  from maze.core.env.structured_env import StructuredEnv, ActorID
  from maze.core.env.structured_env_spaces_mixin import StructuredEnvSpacesMixin
  from maze.core.wrappers.wrapper import Wrapper
  from .maze_env import maze_env_factory
label_desc: Use image node_id 10 for calling the StructuredCutting2DEnvironment obj's underlying member method code with example usage: obj.agent_counts_dict() and returns: dict