






'''simple docstring'''

SCREAMING_SNAKE_CASE__											=     6_5_5_2_1







def 					lowercase__				(   __UpperCamelCase					)->				int:
      UpperCamelCase       						=      1
      UpperCamelCase       						=      0
      for plain_chr in plain_text:
            UpperCamelCase       						=      (a + ord(__UpperCamelCase					)) % MOD_ADLER
            UpperCamelCase       						=      (b + a) % MOD_ADLER
      return (b << 16) | a








'''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)
