code: def make_environment(
      task: str = "MountainCarContinuous-v0",
  ) -> dm_env.Environment:
      """Creates an OpenAI Gym environment."""
  
      # Load the gym environment.
      environment = gym.make(task)
  
      # Make sure the environment obeys the dm_env.Environment interface.
      environment = wrappers.GymWrapper(environment)
      # Clip the action returned by the agent to the environment spec.
      environment = wrappers.CanonicalSpecWrapper(
          environment, clip=True
      )
      environment = wrappers.SinglePrecisionWrapper(environment)
  
      return environment
  
file_path: acme/examples/baselines/imitation/helpers.py
imports: from typing import Tuple
  from acme import wrappers
  import dm_env
  import gym
  import numpy
  import tensorflow
label_desc: Use image node_id 3 for calling a global function with example usage: make_environment(task) and returns: environment