





'''simple docstring'''

import darl  # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline


__lowerCAmelCase							:     Optional[int]		     ={
    "n_samples": 64,
    "horizon": 32,
    "num_inference_steps": 20,
    "n_guide_steps": 2,  # can set to 0 for faster sampling, does not use value network
    "scale_grad_by_std": True,
    "scale": 0.1,
    "eta": 0.0,
    "t_grad_cutoff": 2,
    "device": "cpu",
}


if __name__ == "__main__":
  __lowerCAmelCase							:     Tuple		     ="hopper-medium-v2"
  __lowerCAmelCase							:     List[str]		     =gym.make(env_name)

  __lowerCAmelCase							:     Any		     =ValueGuidedRLPipeline.from_pretrained(
      "bglick13/hopper-medium-v2-value-function-hor32",
      env=env,
  )

  env.seed(0)
  __lowerCAmelCase							:     Union[str, Any]		     =env.reset()
  __lowerCAmelCase							:     List[Any]		     =0
  __lowerCAmelCase							:     Optional[Any]		     =0
  __lowerCAmelCase							:     Tuple		     =1000
  __lowerCAmelCase							:     int		     =[obs.copy()]
  try:
    for t in tqdm.tqdm(range(T)):
      # call the policy
      __lowerCAmelCase							:     List[str]		     =pipeline(obs, planning_horizon=32)

      # execute action in environment
      __lowerCAmelCase     ,					__lowerCAmelCase     ,					__lowerCAmelCase     ,					__lowerCAmelCase							:     int		     =env.step(denorm_actions)
      __lowerCAmelCase							:     Optional[int]		     =env.get_normalized_score(total_reward)

      # update return
      total_reward += reward
      total_score += score
      print(
          f"""Step: {t}, Reward: {reward}, Total Reward: {total_reward}, Score: {score}, Total Score:"""
          f""" {total_score}"""
      )

      # save observations for rendering
      rollout.append(next_observation.copy())

      __lowerCAmelCase							:     str		     =next_observation
  except KeyboardInterrupt:
    pass

  print(f"""Total reward: {total_reward}""")










'''simple docstring'''

def 						UpperCamelCase    (							_lowerCamelCase : int	):

    if not isinstance(_lowerCamelCase						,	_lowerCamelCase	):
        A__    =      F"Input value of [number={number}] must be an integer"
        raise TypeError(_lowerCamelCase	)

    if number < 1:
        A__    =      F"Input value of [number={number}] must be > 0"
        raise ValueError(_lowerCamelCase	)

    A__    =      1

    for i in range(1						,	_lowerCamelCase	):
        current_number *= 4 * i - 2
        current_number //= i + 1

    return current_number


if __name__ == "__main__":
  import doctest

  doctest.testmod()



