


import os
from datetime import datetime as dt

from github import Github


snake_case__				:	List[Any]					       =					[
    '''good first issue''',
    '''feature request''',
    '''wip''',
]


def    __lowerCamelCase   (      )     ->    List[str]:
   lowerCamelCase_						:   int		= Github(os.environ["""GITHUB_TOKEN"""]					)
   lowerCamelCase_						:   int		= g.get_repo("""huggingface/accelerate"""					)
   lowerCamelCase_						:   Optional[Any]		= repo.get_issues(state="""open"""					)

   for issue in open_issues:
      lowerCamelCase_						:   Dict		= sorted([comment for comment in issue.get_comments()]						,						key=lambda A__					: i.created_at						,						reverse=__snake_case					)
      lowerCamelCase_						:   int		= comments[0] if len(__snake_case					) > 0 else None
      lowerCamelCase_						:   List[str]		= dt.utcnow()
      lowerCamelCase_						:   int		= (current_time - issue.updated_at).days
      lowerCamelCase_						:   Dict		= (current_time - issue.created_at).days
      if (
          last_comment is not None
          and last_comment.user.login == "github-actions[bot]"
          and days_since_updated > 7
          and days_since_creation >= 30
          and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()					)
      ):
         # Close issue since it has been 7 days of inactivity since bot mention.
         issue.edit(state="""closed"""					)
      elif (
          days_since_updated > 23
          and days_since_creation >= 30
          and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()					)
      ):
         # Add stale comment
         issue.create_comment(
             """This issue has been automatically marked as stale because it has not had """
             """recent activity. If you think this still needs to be addressed """
             """please comment on this thread.\n\nPlease note that issues that do not follow the """
             """[contributing guidelines](https://github.com/huggingface/accelerate/blob/main/CONTRIBUTING.md) """
             """are likely to be ignored."""					)


if __name__ == "__main__":
      main()






'''simple docstring'''






import unittest

import numpy as np
import torch

from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device


_UpperCAmelCase    :     List[Any]         =       False







class lowercase_       (		unittest.TestCase			):







   """simple docstring"""

   pass







@slow
@require_torch_gpu
class lowercase_       (		unittest.TestCase			):







   """simple docstring"""

   def 	__UpperCAmelCase   (      self      :			List[str]     )  ->			Dict:
        _A    		=  VersatileDiffusionImageVariationPipeline.from_pretrained('shi-labs/versatile-diffusion'     )
        pipe.to(UpperCamelCase__     )
        pipe.set_progress_bar_config(disable=UpperCamelCase__     )

        _A    		=  load_image(
            'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/versatile_diffusion/benz.jpg'     )
        _A    		=  torch.manual_seed(0     )
        _A    		=  pipe(
            image=UpperCamelCase__, generator=UpperCamelCase__, guidance_scale=7.5, num_inference_steps=50, output_type='numpy', ).images

        _A    		=  image[0, 2_53:2_56, 2_53:2_56, -1]

        assert image.shape == (1, 5_12, 5_12, 3)
        _A    		=  np.array([0.0_441, 0.0_469, 0.0_507, 0.0_575, 0.0_632, 0.0_650, 0.0_865, 0.0_909, 0.0_945]     )

        assert np.abs(image_slice.flatten() - expected_slice     ).max() < 1e-2



