code: def __build_env_action(self, agent_action):
      # encode users action as environment action
      env_action = np.array(
          [
              0
              for _ in range(
                  self.num_delta_buttons + self.num_binary_buttons
              )
          ],
          dtype=np.float32,
      )
      self.__parse_delta_buttons(env_action, agent_action)
      self.__parse_binary_buttons(env_action, agent_action)
      return env_action
  
imports: import itertools
  import warnings
  from typing import Optional
  import gym
  import numpy
  import pygame
  from gym.utils import EzPickle
  import vizdoom.vizdoom
label_desc: Use image node_id 5 for calling the VizdoomEnv obj's underlying member method code with example usage: obj.__build_env_action(agent_action) and returns: env_action