
"""simple docstring"""





import argparse

from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection

from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline


if __name__ == "__main__":
 SCREAMING_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.''',
 )

 SCREAMING_SNAKE_CASE_												= parser.parse_args()

 SCREAMING_SNAKE_CASE_												= UnCLIPPipeline.from_pretrained(args.txtaimg_unclip)

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

 SCREAMING_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)






'''simple docstring'''





from __future__ import annotations





def   a_   (		_UpperCAmelCase    :      list[int]				)    ->  bool:
      return len(set(_UpperCAmelCase				)				) == len(_UpperCAmelCase				)


if __name__ == "__main__":
    import doctest

    doctest.testmod()



