class_docstr: Atari environment wrapper for gym.Env.
  
  This wrapper convert the observations returned from baselines wrapped
  environment, which is a LazyFrames object into numpy arrays.
  
  Args:
      env (gym.Env): The environment to be wrapped.
class_docstr_tok: ["Atari","environment","wrapper","for","gym.Env",".","This","wrapper","convert","the","observations","returned","from","baselines","wrapped","environment",",","which","is","a","LazyFrames","object","into","numpy","arrays",".","Args",":","env","(","gym.Env",")",":","The","environment","to","be","wrapped","."]
docstr: gym.Env step function.
docstr_tok: ["gym.Env","step","function","."]
code: def step(self, action):
      """gym.Env step function."""
      obs, reward, done, info = self.env.step(action)
      return np.asarray(obs), reward, done, info
  
imports: import gym
  import numpy
label_desc: Use image node_id 2 for calling the AtariEnv obj's underlying member method code with example usage: obj.step(action) and returns: np,  reward,  done,  info