






"""simple docstring"""



from string import ascii_uppercase

__A		:       List[Any]  				=		{char: i for i, char in enumerate(ascii_uppercase)}
__A		:       Optional[int]  				=		dict(enumerate(ascii_uppercase))



def 						lowercase    (				__snake_case				: str		,					__snake_case				: str	):
		lowercase_ : List[Any]							       =   len(__snake_case	)
		lowercase_ : Dict							       =   0
		while True:
				if x == i:
						lowercase_ : Optional[Any]							       =   0
				if len(__snake_case	) == len(__snake_case	):
						break
				key += key[i]
				i += 1
		return key



def 						lowercase    (				__snake_case				: str		,					__snake_case				: str	):
		lowercase_ : Dict							       =   ''''''
		lowercase_ : List[str]							       =   0
		for letter in message:
				if letter == " ":
						cipher_text += " "
				else:
						lowercase_ : Dict							       =   (dicta[letter] - dicta[key_new[i]]) % 2_6
						i += 1
						cipher_text += dicta[x]
		return cipher_text



def 						lowercase    (				__snake_case				: str		,					__snake_case				: str	):
		lowercase_ : Dict							       =   ''''''
		lowercase_ : Optional[int]							       =   0
		for letter in cipher_text:
				if letter == " ":
						or_txt += " "
				else:
						lowercase_ : int							       =   (dicta[letter] + dicta[key_new[i]] + 2_6) % 2_6
						i += 1
						or_txt += dicta[x]
		return or_txt



def 						lowercase    (				):
		lowercase_ : Dict							       =   '''THE GERMAN ATTACK'''
		lowercase_ : Optional[Any]							       =   '''SECRET'''
		lowercase_ : int							       =   generate_key(__snake_case		,					__snake_case	)
		lowercase_ : List[Any]							       =   cipher_text(__snake_case		,					__snake_case	)
		print(F'''Encrypted Text = {s}'''	)
		print(F'''Original Text = {original_text(__snake_case		,					__snake_case	)}'''	)


if __name__ == "__main__":
						import doctest

						doctest.testmod()
						main()











"""simple docstring"""



import argparse

from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection

from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline


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

						__A		:       str  				=		parser.parse_args()

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

						__A		:       Dict  				=		CLIPImageProcessor()
						__A		:       Union[str, Any]  				=		CLIPVisionModelWithProjection.from_pretrained('''openai/clip-vit-large-patch14''')

						__A		:       List[str]  				=		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)



