

def 			_SCREAMING_SNAKE_CASE      (	_lowerCamelCase				:    Union[str, Any])      ->					int:






							'''simple docstring'''





							__UpperCamelCase			:     Tuple         =      0
							for ch in input_str:
														__UpperCamelCase			:     str         =      ord(A_)
														__UpperCamelCase			:     Optional[Any]         =      pow(2		,						A_)

														# If we already turned on bit for current character's unicode
														if bitmap >> ch_unicode & 1 == 1:
																					return False
														bitmap |= ch_bit_index_on
							return True


if __name__ == "__main__":
		import doctest

		doctest.testmod()

import argparse

from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection

from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline


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

		lowercase						:      int									= parser.parse_args()

		lowercase						:      str									= UnCLIPPipeline.from_pretrained(args.txtaimg_unclip)

		lowercase						:      int									= CLIPImageProcessor()
		lowercase						:      Optional[int]									= CLIPVisionModelWithProjection.from_pretrained('openai/clip-vit-large-patch14')

		lowercase						:      int									= 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)