



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


SCREAMING_SNAKE_CASE__   			=   {
    '''n_samples''': 6_4,
    '''horizon''': 3_2,
    '''num_inference_steps''': 2_0,
    '''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__":
							SCREAMING_SNAKE_CASE__   			=   '''hopper-medium-v2'''
							SCREAMING_SNAKE_CASE__   			=   gym.make(env_name)

							SCREAMING_SNAKE_CASE__   			=   ValueGuidedRLPipeline.from_pretrained(
							    '''bglick13/hopper-medium-v2-value-function-hor32''',
							    env=env,
							)

							env.seed(0)
							SCREAMING_SNAKE_CASE__   			=   env.reset()
							SCREAMING_SNAKE_CASE__   			=   0
							SCREAMING_SNAKE_CASE__   			=   0
							SCREAMING_SNAKE_CASE__   			=   1_0_0_0
							SCREAMING_SNAKE_CASE__   			=   [obs.copy()]
							try:
														for t in tqdm.tqdm(range(T)):
																					# call the policy
																					SCREAMING_SNAKE_CASE__   			=   pipeline(obs, planning_horizon=3_2)

																					# execute action in environment
																					SCREAMING_SNAKE_CASE__			,						SCREAMING_SNAKE_CASE__			,						SCREAMING_SNAKE_CASE__			,						SCREAMING_SNAKE_CASE__   			=   env.step(denorm_actions)
																					SCREAMING_SNAKE_CASE__   			=   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())

																					SCREAMING_SNAKE_CASE__   			=   next_observation
							except KeyboardInterrupt:
														pass

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











import os
import zipfile

import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links






def 				_UpperCAmelCase			(    A				,							A=7     ):




   '''simple docstring'''

   UpperCAmelCase__						=None
   if token is not None:
      UpperCAmelCase__						={"Accept": "application/vnd.github+json", "Authorization": F"""Bearer {token}"""}

   # The id of a workflow (not of a workflow run)
   UpperCAmelCase__						="636036"

   UpperCAmelCase__						=F"""https://api.github.com/repos/huggingface/transformers/actions/workflows/{workflow_id}/runs"""
   # On `main` branch + event being `schedule` + not returning PRs + only `num_runs` results
   url += F"""?branch=main&event=schedule&exclude_pull_requests=true&per_page={num_runs}"""

   UpperCAmelCase__						=requests.get(A				,							headers=A     ).json()

   return result["workflow_runs"]






def 				_UpperCAmelCase			(    A     ):




   '''simple docstring'''

   UpperCAmelCase__						=get_daily_ci_runs(A     )
   UpperCAmelCase__						=None
   for workflow_run in workflow_runs:
      if workflow_run["status"] == "completed":
         UpperCAmelCase__						=workflow_run["id"]
         break

   return workflow_run_id






def 				_UpperCAmelCase			(    A				,							A				,							A     ):




   '''simple docstring'''

   UpperCAmelCase__						=get_last_daily_ci_runs(A     )
   if workflow_run_id is not None:
      UpperCAmelCase__						=get_artifacts_links(worflow_run_id=A				,							token=A     )
      for artifact_name in artifact_names:
         if artifact_name in artifacts_links:
            UpperCAmelCase__						=artifacts_links[artifact_name]
            download_artifact(
                artifact_name=A				,							artifact_url=A				,							output_dir=A				,							token=A     )






def 				_UpperCAmelCase			(    A				,							A				,							A     ):




   '''simple docstring'''

   get_last_daily_ci_artifacts(A				,							A				,							A     )

   UpperCAmelCase__						={}
   for artifact_name in artifact_names:
      UpperCAmelCase__						=os.path.join(A				,							F"""{artifact_name}.zip"""     )
      if os.path.isfile(A     ):
         UpperCAmelCase__						={}
         with zipfile.ZipFile(A     ) as z:
            for filename in z.namelist():
               if not os.path.isdir(A     ):
                  # read the file
                  with z.open(A     ) as f:
                     UpperCAmelCase__						=f.read().decode("UTF-8"     )

   return results



