


import os
from datetime import datetime as dt

from github import Github


_snake_case			 =	[
    '''good first issue''',
    '''feature request''',
    '''wip''',
]






def 						lowercase_(    ):


  '''simple docstring'''

  lowerCamelCase					:   Optional[Any]       =							Github(os.environ["GITHUB_TOKEN"]      )
  lowerCamelCase					:   Tuple       =							g.get_repo("huggingface/accelerate"      )
  lowerCamelCase					:   Any       =							repo.get_issues(state="open"      )

  for issue in open_issues:
    lowerCamelCase					:   List[str]       =							sorted([comment for comment in issue.get_comments()] ,		key=lambda SCREAMING_SNAKE_CASE_      : i.created_at ,		reverse=_lowercase      )
    lowerCamelCase					:   Tuple       =							comments[0] if len(_lowercase      ) > 0 else None
    lowerCamelCase					:   Optional[Any]       =							dt.utcnow()
    lowerCamelCase					:   Dict       =							(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()







import argparse

from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection

from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline


if __name__ == "__main__":
    __snake_case   							=						argparse.ArgumentParser()

    parser.add_argument('''--dump_path''', default=None, type=str, required=True, help='''Path to the output model.''')

    parser.add_argument(
        '''--txt2img_unclip''',
        default='''kakaobrain/karlo-v1-alpha''',
        type=str,
        required=False,
        help='''The pretrained txt2img unclip.''',
    )

    __snake_case   							=						parser.parse_args()

    __snake_case   							=						UnCLIPPipeline.from_pretrained(args.txtaimg_unclip)

    __snake_case   							=						CLIPImageProcessor()
    __snake_case   							=						CLIPVisionModelWithProjection.from_pretrained('''openai/clip-vit-large-patch14''')

    __snake_case   							=						UnCLIPImageVariationPipeline(
        decoder=txtaimg.decoder,
        text_encoder=txtaimg.text_encoder,
        tokenizer=txtaimg.tokenizer,
        text_proj=txtaimg.text_proj,
        feature_extractor=feature_extractor,
        image_encoder=image_encoder,
        super_res_first=txtaimg.super_res_first,
        super_res_last=txtaimg.super_res_last,
        decoder_scheduler=txtaimg.decoder_scheduler,
        super_res_scheduler=txtaimg.super_res_scheduler,
    )

    imgaimg.save_pretrained(args.dump_path)


