
import argparse

from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection

from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline


if __name__ == "__main__":
						__a  			=					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  			=					parser.parse_args()

						__a  			=					UnCLIPPipeline.from_pretrained(args.txtaimg_unclip)

						__a  			=					CLIPImageProcessor()
						__a  			=					CLIPVisionModelWithProjection.from_pretrained('openai/clip-vit-large-patch14')

						__a  			=					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"""





from diffusers.utils.testing_utils import require_onnxruntime


@require_onnxruntime
class A_	:




  '''simple docstring'''
  pass


