class_docstr: Based on openai/atari-reset implementation.
code: def step(self, action):
      if np.random.uniform() < self.p:
          action = self.last_action
      self.last_action = action
      obs, reward, done, info = self.env.step(action)
      return obs, reward, done, info
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  from absl import logging
  import gym
  import gym.wrappers
  import numpy
  from PIL import Image
label_desc: Use image node_id 2 for calling the StickyActionEnv obj's underlying member method code with example usage: obj.step(action) and returns: obs,  reward,  done,  info