



'''simple docstring'''





import argparse

from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection

from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline


if __name__ == "__main__":
  lowercase_									=    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_									=    parser.parse_args()

  lowercase_									=    UnCLIPPipeline.from_pretrained(args.txtaimg_unclip)

  lowercase_									=    CLIPImageProcessor()
  lowercase_									=    CLIPVisionModelWithProjection.from_pretrained("openai/clip-vit-large-patch14")

  lowercase_									=    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 __future__ import annotations

def  lowercase     (_lowerCAmelCase						):
						__lowerCAmelCase     =  2
						__lowerCAmelCase     =  []
						while i * i <= n:
												if n % i:
																		i += 1
												else:
																		n //= i
																		factors.append(_lowerCAmelCase						)
						if n > 1:
												factors.append(_lowerCAmelCase						)
						return factors


if __name__ == "__main__":
			import doctest

			doctest.testmod()
