class_docstr: A wrapper skipping the first few steps by taking random actions.
  This is useful for skipping irrelevant initial parts of a trajectory or for introducing randomness in the training
  process.
  
  :param env: Environment/wrapper to wrap.
  :param min_skip_steps: Minimum number of steps to skip.
  :param max_skip_steps: Maximum number of steps to skip.
class_docstr_tok: ["A","wrapper","skipping","the","first","few","steps","by","taking","random","actions",".","This","is","useful","for","skipping","irrelevant","initial","parts","of","a","trajectory","or","for","introducing","randomness","in","the","training","process",".",":","param","env",":","Environment\/wrapper","to","wrap",".",":","param","min_skip_steps",":","Minimum","number","of","steps","to","skip",".",":","param","max_skip_steps",":","Maximum","number","of","steps","to","skip","."]
docstr: This wrapper does not modify observations and actions.
docstr_tok: ["This","wrapper","does","not","modify","observations","and","actions","."]
code: def get_observation_and_action_dicts(
      self,
      maze_state: Optional[MazeStateType],
      maze_action: Optional[MazeActionType],
      first_step_in_episode: bool,
  ) -> Tuple[
      Optional[Dict[Union[int, str], Any]],
      Optional[Dict[Union[int, str], Any]],
  ]:
      """This wrapper does not modify observations and actions."""
      return self.env.get_observation_and_action_dicts(
          maze_state, maze_action, first_step_in_episode
      )
  
file_path: maze/maze/core/wrappers/random_reset_wrapper.py
imports: from typing import Any, Union, Optional, Dict, Tuple
  import numpy
  from maze.core.annotations import override
  from maze.core.env.base_env import BaseEnv
  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.simulated_env_mixin import SimulatedEnvMixin
  from maze.core.env.structured_env import StructuredEnv
  from maze.core.env.structured_env_spaces_mixin import StructuredEnvSpacesMixin
  from maze.core.utils.seeding import MazeSeeding
  from maze.core.wrappers.wrapper import Wrapper, EnvType
label_desc: Use image node_id 4 for calling the RandomResetWrapper obj's underlying member method code with example usage: obj.get_observation_and_action_dicts(maze_state, maze_action, first_step_in_episode) and returns: self