


from __future__ import annotations

import string
from itertools import cycle, product
from pathlib import Path

__snake_case   							=						(
    string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
__snake_case   							=						[ord(letter) for letter in string.ascii_lowercase]
__snake_case   							=						{ord(char) for char in VALID_CHARS}

__snake_case   							=						["the", "be", "to", "of", "and", "in", "that", "have"]






def 		_A		(		_lowercase					,  _lowercase )					-> str | None:


     """simple docstring"""


     __UpperCamelCase =			""
     __UpperCamelCase =			42
     __UpperCamelCase =			42
     __UpperCamelCase =			42

     for keychar, cipherchar in zip(cycle(_lowercase )					,  _lowercase ):
          __UpperCamelCase =			cipherchar ^ keychar
          if decodedchar not in VALID_INTS:
               return None
          decoded += chr(_lowercase )

     return decoded






def 		_A		(		_lowercase )					-> list[str]:


     """simple docstring"""


     __UpperCamelCase =			[]
     for key in product(_lowercase					,  repeat=3 ):
          __UpperCamelCase =			try_key(_lowercase					,  _lowercase )
          if encoded is not None:
               possibles.append(_lowercase )
     return possibles






def 		_A		(		_lowercase					,  _lowercase )					-> list[str]:


     """simple docstring"""


     return [possible for possible in possibles if common_word in possible.lower()]






def 		_A		(		_lowercase = "p059_cipher.txt" )					-> int:


     """simple docstring"""


     __UpperCamelCase =			42
     __UpperCamelCase =			42
     __UpperCamelCase =			42
     __UpperCamelCase =			42
     __UpperCamelCase =			Path(_lowercase ).parent.joinpath(_lowercase ).read_text(encoding='utf-8' )

     __UpperCamelCase =			[int(_lowercase ) for number in data.strip().split(',' )]

     __UpperCamelCase =			filter_valid_chars(_lowercase )
     for common_word in COMMON_WORDS:
          __UpperCamelCase =			filter_common_word(_lowercase					,  _lowercase )
          if len(_lowercase ) == 1:
               break

     __UpperCamelCase =			possibles[0]
     return sum(ord(_lowercase ) for char in decoded_text )


if __name__ == "__main__":
    print(f"""{solution() = }""")






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)


