class_docstr: Interface specifying the conversion of agent actions to actual environment MazeActions.
      
class_docstr_tok: ["Interface","specifying","the","conversion","of","agent","actions","to","actual","environment","MazeActions","."]
docstr: Calculate a hash of the given action. Can be used for identifying and de-duplicating
  same actions when creating/evaluating action scenarios.
  
  :param action: Action to hash
  :return: Hash of a given action, either as a string, or integer (should be of the same type for all actions)
docstr_tok: ["Calculate","a","hash","of","the","given","action",".","Can","be","used","for","identifying","and","de-duplicating","same","actions","when","creating\/evaluating","action","scenarios",".",":","param","action",":","Action","to","hash",":","return",":","Hash","of","a","given","action",",","either","as","a","string",",","or","integer","(","should","be","of","the","same","type","for","all","actions",")"]
code: def create_action_hash(self, action: ActionType) -> Union[int, str]:
      """Calculate a hash of the given action. Can be used for identifying and de-duplicating
      same actions when creating/evaluating action scenarios.
  
      :param action: Action to hash
      :return: Hash of a given action, either as a string, or integer (should be of the same type for all actions)
      """
  
file_path: maze/maze/core/env/action_conversion.py
imports: from abc import ABC, abstractmethod
  from typing import Dict, Union
  import numpy
  import torch
  from gym import spaces
  from maze.core.env.maze_action import MazeActionType
  from maze.core.env.maze_state import MazeStateType
label_desc: Use image node_id 5 for calling the ActionConversionInterface obj's underlying member method code with example usage: obj.create_action_hash(action) without return types