





A       :   Union[str, Any]					= tuple[float, float, float]
A       :   str					= tuple[float, float, float]







def   __lowerCamelCase   (				__a  :Pointad       ,	__a  :Pointad       )						->							Vectorad:






		"""simple docstring"""

		A__     =  end_pointa[0] - end_pointa[0]
		A__     =  end_pointa[1] - end_pointa[1]
		A__     =  end_pointa[2] - end_pointa[2]
		return (x, y, z)







def   __lowerCamelCase   (				__a  :Vectorad       ,	__a  :Vectorad       )						->							Vectorad:






		"""simple docstring"""

		A__     =  ab[1] * ac[2] - ab[2] * ac[1]  # *i
		A__     =  (ab[0] * ac[2] - ab[2] * ac[0]) * -1  # *j
		A__     =  ab[0] * ac[1] - ab[1] * ac[0]  # *k
		return (x, y, z)







def   __lowerCamelCase   (				__a  :Vectorad       ,	__a  :int       )						->							bool:






		"""simple docstring"""

		return tuple(round(__a       ,	__a       ) for x in vector       ) == (0, 0, 0)







def   __lowerCamelCase   (				__a  :Pointad       ,	__a  :Pointad       ,	__a  :Pointad       ,	__a  :int = 1_0       )						->							bool:






		"""simple docstring"""

		A__     =  create_vector(__a       ,	__a       )
		A__     =  create_vector(__a       ,	__a       )
		return is_zero_vector(get_ad_vectors_cross(__a       ,	__a       )       ,	__a       )










import argparse

from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection

from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline


if __name__ == "__main__":
					A       :   List[Any]					= 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       :   List[Any]					= parser.parse_args()

					A       :   int					= UnCLIPPipeline.from_pretrained(args.txtaimg_unclip)

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

					A       :   Tuple					= 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)



