class_docstr: Cartpole environment with masked velocity components.
  
  This environment is useful as a unit tests for agents that utilize recurrent
  networks.
class_docstr_tok: ["Cartpole","environment","with","masked","velocity","components",".","This","environment","is","useful","as","a","unit","tests","for","agents","that","utilize","recurrent","networks","."]
code: def __init__(self):
      super(MaskedCartPoleEnv, self).__init__()
      high = np.array(
          [
              self.x_threshold * 2,
              self.theta_threshold_radians * 2,
          ]
      )
  
      self.observation_space = gym.spaces.Box(-high, high)
  
file_path: agents/tf_agents/environments/examples/masked_cartpole.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import gym
  from gym.envs.classic_control import cartpole
  from gym.envs.registration import register
  import numpy
label_desc: Use image node_id 1 to create a new MaskedCartPoleEnv object from inherited base classes: cartpole with example: obj = MaskedCartPoleEnv()