class_docstr: Based on openai/atari-reset implementation.
code: def __init__(self, env, p=0.25):
      gym.Wrapper.__init__(self, env)
      self.p = p
      self.last_action = 0
  
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 1 to create a new StickyActionEnv object from inherited base classes: gym with example: obj = StickyActionEnv(env, p)