docstr: Sample initial states by taking random number of no-ops on reset.
  
  No-op is assumed to be action 0.
docstr_tok: ["Sample","initial","states","by","taking","random","number","of","no-ops","on","reset",".","No-op","is","assumed","to","be","action","0","."]
code: def __init__(self, env, noop_max=30):
      """Sample initial states by taking random number of no-ops on reset.
  
      No-op is assumed to be action 0.
      """
      gym.Wrapper.__init__(self, env)
      self.noop_max = noop_max
      self.override_num_noops = None
      self.noop_action = 0
      assert env.unwrapped.get_action_meanings()[0] == "NOOP"
  
imports: from collections import deque
  import gym
  import numpy
  from gym import spaces
  import chainerrl
label_desc: Use image node_id 1 to create a new NoopResetEnv object from inherited base classes: gym with example: obj = NoopResetEnv(env, noop_max)