



"""simple docstring"""






import argparse

from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection

from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline


if __name__ == "__main__":
		_lowercase				:				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.",
		)

		_lowercase				:				Dict   		=		parser.parse_args()

		_lowercase				:				Optional[int]   		=		UnCLIPPipeline.from_pretrained(args.txtaimg_unclip)

		_lowercase				:				int   		=		CLIPImageProcessor()
		_lowercase				:				Any   		=		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)









"""simple docstring"""






def   snake_case__     (	__lowerCamelCase       :					int = 4000000			):
			"""simple docstring"""
			lowerCamelCase__	:	Dict				=[]
			lowerCamelCase__			,     lowerCamelCase__	:	Union[str, Any]				=0, 1
			while b <= n:
						if b % 2 == 0:
									even_fibs.append(__lowerCamelCase			)
						lowerCamelCase__			,     lowerCamelCase__	:	Union[str, Any]				=b, a + b
			return sum(__lowerCamelCase			)


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




