



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


__snake_case     :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__":
				__snake_case     :List[Any]			       ='hopper-medium-v2'
				__snake_case     :List[Any]			       =gym.make(env_name)

				__snake_case     :Optional[int]			       =ValueGuidedRLPipeline.from_pretrained(
				    'bglick13/hopper-medium-v2-value-function-hor32',
				    env=env,
				)

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

												# execute action in environment
												__snake_case       ,				__snake_case       ,				__snake_case       ,				__snake_case     :Union[str, Any]			       =env.step(denorm_actions)
												__snake_case     :Dict			       =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())

												__snake_case     :Dict			       =next_observation
				except KeyboardInterrupt:
								pass

				print(F'''Total reward: {total_reward}''')




from bisect import bisect
from itertools import accumulate






def  lowerCamelCase_	(      lowerCAmelCase__	:	int			,	lowerCAmelCase__	:	str			,	lowerCAmelCase__	:	List[str]			,	lowerCAmelCase__	:	List[Any]				)       ->							Union[str, Any]:

							'''simple docstring'''






							A      						=    sorted(zip(lowerCAmelCase__			,	lowerCAmelCase__				)			,	key=lambda lowerCAmelCase__				: x[0] / x[1]			,	reverse=lowerCAmelCase__				)
							A						,   A      						=    [i[0] for i in r], [i[1] for i in r]
							A      						=    list(accumulate(lowerCAmelCase__				)				)
							A      						=    bisect(lowerCAmelCase__			,	lowerCAmelCase__				)
							return (
							    0
							    if k == 0
							    else sum(vl[:k]				) + (w - acc[k - 1]) * (vl[k]) / (wt[k])
							    if k != n
							    else sum(vl[:k]				)
							)


if __name__ == "__main__":
				import doctest

				doctest.testmod()