code: def __init__(self, bit_length=16, max_steps=None, mean_zero=False):
      super(BitFlip, self).__init__()
      if bit_length < 1:
          raise ValueError(
              "bit_length must be >= 1, found {}".format(bit_length)
          )
      self.bit_length = bit_length
      self.mean_zero = mean_zero
  
      if max_steps is None:
          # default to bit_length
          self.max_steps = bit_length
      elif max_steps == 0:
          self.max_steps = None
      else:
          self.max_steps = max_steps
  
      # spaces documentation: https://gym.openai.com/docs/
      self.action_space = spaces.Discrete(bit_length)
      self.observation_space = spaces.Dict(
          {
              "state": spaces.Box(low=0, high=1, shape=(bit_length,)),
              "desired_goal": spaces.Box(
                  low=0, high=1, shape=(bit_length,)
              ),
              "achieved_goal": spaces.Box(
                  low=0, high=1, shape=(bit_length,)
              ),
          }
      )
  
      self.reset()
  
file_path: coach/rl_coach/environments/toy_problems/bit_flip.py
imports: import random
  import gym
  import numpy
  from gym import spaces
label_desc: Use image node_id 1 to create a new BitFlip object from inherited base classes: gym with example: obj = BitFlip(bit_length, max_steps, mean_zero)