code: def make(
      id: Union[str, EnvSpec],
      max_episode_steps: Optional[int] = None,
      autoreset: bool = False,
      apply_api_compatibility: Optional[bool] = None,
      disable_env_checker: Optional[bool] = None,
      **kwargs,
  ) -> Env:
      """Create an environment according to the given ID.
  
      To find all available environments use `gym.envs.registry.keys()` for all valid ids.
  
      Args:
          id: Name of the environment. Optionally, a module to import can be included, eg. 'module:Env-v0'
          max_episode_steps: Maximum length of an episode (TimeLimit wrapper).
          autoreset: Whether to automatically reset the environment after each episode (AutoResetWrapper).
          apply_api_compatibility: Whether to wrap the environment with the `StepAPICompatibility` wrapper that
              converts the environment step from a done bool to return termination and truncation bools.
              By default, the argument is None to which the environment specification `apply_api_compatibility` is used
              which defaults to False. Otherwise, the value of `apply_api_compatibility` is used.
              If `True`, the wrapper is applied otherwise, the wrapper is not applied.
          disable_env_checker: If to run the env checker, None will default to the environment specification `disable_env_checker`
              (which is by default False, running the environment checker),
              otherwise will run according to this parameter (`True` = not run, `False` = run)
          kwargs: Additional arguments to pass to the environment constructor.
  
      Returns:
          An instance of the environment.
  
      Raises:
          Error: If the ``id`` doesn't exist then an error is raised
      """
      if isinstance(id, EnvSpec):
          spec_ = id
      else:
          module, id = (None, id) if ":" not in id else id.split(":")
          if module is not None:
              try:
                  importlib.import_module(module)
              except ModuleNotFoundError as e:
                  raise ModuleNotFoundError(
                      f"{e}. Environment registration via importing a module failed. "
                      f"Check whether '{module}' contains env registration and can be imported."
                  )
          spec_ = registry.get(id)
  
          ns, name, version = parse_env_id(id)
          latest_version = find_highest_version(ns, name)
          if (
              version is not None
              and latest_version is not None
              and latest_version > version
          ):
              logger.warn(
                  f"The environment {id} is out of date. You should consider "
                  f"upgrading to version `v{latest_version}`."
              )
          if version is None and latest_version is not None:
              version = latest_version
              new_env_id = get_env_id(ns, name, version)
              spec_ = registry.get(new_env_id)
              logger.warn(
                  f"Using the latest versioned environment `{new_env_id}` "
                  f"instead of the unversioned environment `{id}`."
              )
  
          if spec_ is None:
              _check_version_exists(ns, name, version)
              raise error.Error(f"No registered env with id: {id}")
  
      _kwargs = spec_.kwargs.copy()
      _kwargs.update(kwargs)
  
      if spec_.entry_point is None:
          raise error.Error(
              f"{spec_.id} registered but entry_point is not specified"
          )
      elif callable(spec_.entry_point):
          env_creator = spec_.entry_point
      else:
          # Assume it's a string
          env_creator = load(spec_.entry_point)
  
      mode = _kwargs.get("render_mode")
      apply_human_rendering = False
      apply_render_collection = False
  
      # If we have access to metadata we check that "render_mode" is valid and see if the HumanRendering wrapper needs to be applied
      if mode is not None and hasattr(env_creator, "metadata"):
          assert isinstance(
              env_creator.metadata, dict
          ), f"Expect the environment creator ({env_creator}) metadata to be dict, actual type: {type(env_creator.metadata)}"
  
          if "render_modes" in env_creator.metadata:
              render_modes = env_creator.metadata["render_modes"]
              if not isinstance(render_modes, Sequence):
                  logger.warn(
                      f"Expects the environment metadata render_modes to be a Sequence (tuple or list), actual type: {type(render_modes)}"
                  )
  
              # Apply the `HumanRendering` wrapper, if the mode=="human" but "human" not in render_modes
              if (
                  mode == "human"
                  and "human" not in render_modes
                  and (
                      "rgb_array" in render_modes
                      or "rgb_array_list" in render_modes
                  )
              ):
                  logger.warn(
                      "You are trying to use 'human' rendering for an environment that doesn't natively support it. "
                      "The HumanRendering wrapper is being applied to your environment."
                  )
                  apply_human_rendering = True
                  if "rgb_array" in render_modes:
                      _kwargs["render_mode"] = "rgb_array"
                  else:
                      _kwargs["render_mode"] = "rgb_array_list"
              elif (
                  mode not in render_modes
                  and mode.endswith("_list")
                  and mode[: -len("_list")] in render_modes
              ):
                  _kwargs["render_mode"] = mode[: -len("_list")]
                  apply_render_collection = True
              elif mode not in render_modes:
                  logger.warn(
                      f"The environment is being initialised with mode ({mode}) that is not in the possible render_modes ({render_modes})."
                  )
          else:
              logger.warn(
                  f"The environment creator metadata doesn't include `render_modes`, contains: {list(env_creator.metadata.keys())}"
              )
  
      if apply_api_compatibility is True or (
          apply_api_compatibility is None
          and spec_.apply_api_compatibility is True
      ):
          # If we use the compatibility layer, we treat the render mode explicitly and don't pass it to the env creator
          render_mode = _kwargs.pop("render_mode", None)
      else:
          render_mode = None
  
      try:
          env = env_creator(**_kwargs)
      except TypeError as e:
          if (
              str(e).find(
                  "got an unexpected keyword argument 'render_mode'"
              )
              >= 0
              and apply_human_rendering
          ):
              raise error.Error(
                  f"You passed render_mode='human' although {id} doesn't implement human-rendering natively. "
                  "Gym tried to apply the HumanRendering wrapper but it looks like your environment is using the old "
                  "rendering API, which is not supported by the HumanRendering wrapper."
              )
          else:
              raise e
  
      # Copies the environment creation specification and kwargs to add to the environment specification details
      spec_ = copy.deepcopy(spec_)
      spec_.kwargs = _kwargs
      env.unwrapped.spec = spec_
  
      # Add step API wrapper
      if apply_api_compatibility is True or (
          apply_api_compatibility is None
          and spec_.apply_api_compatibility is True
      ):
          env = EnvCompatibility(env, render_mode)
  
      # Run the environment checker as the lowest level wrapper
      if disable_env_checker is False or (
          disable_env_checker is None
          and spec_.disable_env_checker is False
      ):
          env = PassiveEnvChecker(env)
  
      # Add the order enforcing wrapper
      if spec_.order_enforce:
          env = OrderEnforcing(env)
  
      # Add the time limit wrapper
      if max_episode_steps is not None:
          env = TimeLimit(env, max_episode_steps)
      elif spec_.max_episode_steps is not None:
          env = TimeLimit(env, spec_.max_episode_steps)
  
      # Add the autoreset wrapper
      if autoreset:
          env = AutoResetWrapper(env)
  
      # Add human rendering wrapper
      if apply_human_rendering:
          env = HumanRendering(env)
      elif apply_render_collection:
          env = RenderCollection(env)
  
      return env
  
imports: import contextlib
  import copy
  import difflib
  import importlib
  import importlib.util
  import re
  import sys
  import warnings
  from dataclasses import dataclass, field
  from typing import Callable, Dict, List, Optional, Sequence, SupportsFloat, Tuple, Union, overload
  import numpy
  from gym.wrappers import AutoResetWrapper, HumanRendering, OrderEnforcing, RenderCollection, TimeLimit
  from gym.wrappers.compatibility import EnvCompatibility
  from gym.wrappers.env_checker import PassiveEnvChecker
  from gym import Env, error, logger
label_desc: Use image node_id 27 for calling a global function with example usage: make(id, max_episode_steps, autoreset, apply_api_compatibility, disable_env_checker) and returns: env