


'''simple docstring'''
import string


def      a (     __a  )    ->      str:



					'''simple docstring'''






					UpperCamelCase__  :List[Any]				   =					''''''
					for i in sequence:
										UpperCamelCase__  :Dict				   =					ord(__a  )
										if 65 <= extract <= 90:
															output += chr(155 - extract  )
										elif 97 <= extract <= 122:
															output += chr(219 - extract  )
										else:
															output += i
					return output


def      a (     __a  )    ->      str:



					'''simple docstring'''






					UpperCamelCase__  :List[Any]				   =					string.ascii_letters
					UpperCamelCase__  :List[str]				   =					string.ascii_lowercase[::-1] + string.ascii_uppercase[::-1]
					return "".join(
					    letters_reversed[letters.index(__a  )] if c in letters else c for c in sequence  )


def      a (     )    ->      None:



					'''simple docstring'''






					from timeit import timeit

					print('''Running performance benchmarks...'''  )
					UpperCamelCase__  :int				   =					'''from string import printable ; from __main__ import atbash, atbash_slow'''
					print(f'''> atbash_slow(): {timeit("atbash_slow(printable)"					,   setup=__a  )} seconds'''  )
					print(f'''>      atbash(): {timeit("atbash(printable)"					,   setup=__a  )} seconds'''  )


if __name__ == "__main__":
		for example in ("ABCDEFGH", "123GGjj", "testStringtest", "with space"):
				print(F"""{example} encrypted in atbash: {atbash(example)}""")
		benchmark()



'''simple docstring'''
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)