

"""simple docstring"""



import argparse

from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection

from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline


if __name__ == "__main__":
 SCREAMING_SNAKE_CASE_					:	List[str]							  =						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_					:	Optional[int]							  =						parser.parse_args()

 SCREAMING_SNAKE_CASE_					:	List[Any]							  =						UnCLIPPipeline.from_pretrained(args.txtaimg_unclip)

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

 SCREAMING_SNAKE_CASE_					:	Dict							  =						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"""



import math
import sys





def  _snake_case     (    UpperCAmelCase_  :					int			):
     if number != int(UpperCAmelCase_			):
          raise ValueError("""the value of input must be a natural number"""			)
     if number < 0:
          raise ValueError("""the value of input must not be a negative number"""			)
     if number == 0:
          return 1
     A__										=  [-1] * (number + 1)
     A__										=  0
     for i in range(1					,   number + 1			):
          A__										=  sys.maxsize
          A__										=  int(math.sqrt(UpperCAmelCase_			)			)
          for j in range(1					,   root + 1			):
               A__										=  1 + answers[i - (j**2)]
               A__										=  min(UpperCAmelCase_					,   UpperCAmelCase_			)
          A__										=  answer
     return answers[number]


if __name__ == "__main__":
 import doctest

 doctest.testmod()






