

# This code is adapted from OpenAI's release
# https://github.com/openai/human-eval/blob/master/human_eval/execution.py

import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile





def    __lowerCamelCase      (					UpperCamelCase__  ,				UpperCamelCase__  ,				UpperCamelCase__  ,				UpperCamelCase__ ):







							'''simple docstring'''






							snake_case_     							=       multiprocessing.Manager()
							snake_case_     							=       manager.list()

							snake_case_     							=       multiprocessing.Process(target=UpperCamelCase__  ,				args=(check_program, result, timeout) )
							p.start()
							p.join(timeout=timeout + 1 )
							if p.is_alive():
														p.kill()

							if not result:
														result.append('timed out' )

							return {
							    "task_id": task_id,
							    "passed": result[0] == "passed",
							    "result": result[0],
							    "completion_id": completion_id,
							}





def    __lowerCamelCase      (					UpperCamelCase__  ,				UpperCamelCase__  ,				UpperCamelCase__ ):







							'''simple docstring'''






							with create_tempdir():
														# These system calls are needed when cleaning up tempdir.
														import os
														import shutil

														snake_case_     							=       shutil.rmtree
														snake_case_     							=       os.rmdir
														snake_case_     							=       os.chdir

														# Disable functionalities that can make destructive changes to the test.
														reliability_guard()

														# Run program.
														try:
																					snake_case_     							=       {}
																					with swallow_io():
																												with time_limit(UpperCamelCase__ ):
																																			exec(UpperCamelCase__  ,				UpperCamelCase__ )
																					result.append('passed' )
														except TimeoutException:
																					result.append('timed out' )
														except BaseException as e:
																					result.append(F'''failed: {e}''' )

														# Needed for cleaning up.
														snake_case_     							=       rmtree
														snake_case_     							=       rmdir
														snake_case_     							=       chdir





@contextlib.contextmanager
def    __lowerCamelCase      (					UpperCamelCase__ ):







							'''simple docstring'''






							def signal_handler(UpperCamelCase__  ,				UpperCamelCase__ ):
														raise TimeoutException('Timed out!' )

							signal.setitimer(signal.ITIMER_REAL  ,				UpperCamelCase__ )
							signal.signal(signal.SIGALRM  ,				UpperCamelCase__ )
							try:
														yield
							finally:
														signal.setitimer(signal.ITIMER_REAL  ,				0 )





@contextlib.contextmanager
def    __lowerCamelCase      (					):







							'''simple docstring'''






							snake_case_     							=       WriteOnlyStringIO()
							with contextlib.redirect_stdout(UpperCamelCase__ ):
														with contextlib.redirect_stderr(UpperCamelCase__ ):
																					with redirect_stdin(UpperCamelCase__ ):
																												yield





@contextlib.contextmanager
def    __lowerCamelCase      (					):







							'''simple docstring'''






							with tempfile.TemporaryDirectory() as dirname:
														with chdir(UpperCamelCase__ ):
																					yield dirname







class 					lowercase							(			lowercase_     ):
				pass







class 					lowercase							(			io.StringIO     ):




				def        a				(   self ,  *snake_case ,  **snake_case			):
											raise OSError




				def        a				(   self ,  *snake_case ,  **snake_case			):
											raise OSError




				def        a				(   self ,  *snake_case ,  **snake_case			):
											raise OSError




				def        a				(   self ,  *snake_case ,  **snake_case			):
											return False







class 					lowercase							(			contextlib._RedirectStream     ):  # type: ignore
				__SCREAMING_SNAKE_CASE   :					Tuple			     =     '''stdin'''





@contextlib.contextmanager
def    __lowerCamelCase      (					UpperCamelCase__ ):







							'''simple docstring'''






							if root == ".":
														yield
														return
							snake_case_     							=       os.getcwd()
							os.chdir(UpperCamelCase__ )
							try:
														yield
							except BaseException as exc:
														raise exc
							finally:
														os.chdir(UpperCamelCase__ )





def    __lowerCamelCase      (					UpperCamelCase__=None ):







							'''simple docstring'''






							if maximum_memory_bytes is not None:
														import resource

														resource.setrlimit(resource.RLIMIT_AS  ,				(maximum_memory_bytes, maximum_memory_bytes) )
														resource.setrlimit(resource.RLIMIT_DATA  ,				(maximum_memory_bytes, maximum_memory_bytes) )
														if not platform.uname().system == "Darwin":
																					resource.setrlimit(resource.RLIMIT_STACK  ,				(maximum_memory_bytes, maximum_memory_bytes) )

							faulthandler.disable()

							import builtins

							snake_case_     							=       None
							snake_case_     							=       None

							import os

							snake_case_     							=       '1'

							snake_case_     							=       None
							snake_case_     							=       None
							snake_case_     							=       None
							snake_case_     							=       None
							snake_case_     							=       None
							snake_case_     							=       None
							snake_case_     							=       None
							snake_case_     							=       None
							snake_case_     							=       None
							snake_case_     							=       None
							snake_case_     							=       None
							snake_case_     							=       None
							snake_case_     							=       None
							snake_case_     							=       None
							snake_case_     							=       None
							snake_case_     							=       None
							snake_case_     							=       None
							snake_case_     							=       None
							snake_case_     							=       None
							snake_case_     							=       None
							snake_case_     							=       None
							snake_case_     							=       None
							snake_case_     							=       None
							snake_case_     							=       None
							snake_case_     							=       None
							snake_case_     							=       None
							snake_case_     							=       None

							import shutil

							snake_case_     							=       None
							snake_case_     							=       None
							snake_case_     							=       None

							import subprocess

							snake_case_     							=       None  # type: ignore

							snake_case_     							=       None

							import sys

							snake_case_     							=       None
							snake_case_     							=       None
							snake_case_     							=       None
							snake_case_     							=       None
							snake_case_     							=       None







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


_UpperCAmelCase						:  List[Any]									=			{
    """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__":
					_UpperCAmelCase						:  List[str]									=			"""hopper-medium-v2"""
					_UpperCAmelCase						:  Any									=			gym.make(env_name)

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

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

															# execute action in environment
															_UpperCAmelCase							,		_UpperCAmelCase							,		_UpperCAmelCase							,		_UpperCAmelCase						:  str									=			env.step(denorm_actions)
															_UpperCAmelCase						:  Tuple									=			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())

															_UpperCAmelCase						:  Dict									=			next_observation
					except KeyboardInterrupt:
										pass

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




