


def 						lowercase_(    SCREAMING_SNAKE_CASE_      ):


  '''simple docstring'''

  if not isinstance(_lowercase ,		_lowercase      ):
    raise TypeError("only integers accepted as input"      )
  else:
    lowerCamelCase					:   List[Any]       =							str(abs(_lowercase      )      )
    lowerCamelCase					:   List[str]       =							[list(_lowercase      ) for char in range(len(_lowercase      )      )]
    for index in range(len(_lowercase      )      ):
      num_transpositions[index].pop(_lowercase      )
    return max(
        int("".join(list(_lowercase      )      )      ) for transposition in num_transpositions      )


if __name__ == "__main__":
   __import__('''doctest''').testmod()







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)


