

'''simple docstring'''






# Lint as: python3
import itertools
import os
import re


lowerCAmelCase__											=	re.compile(R'''([A-Z]+)([A-Z][a-z])''')
lowerCAmelCase__											=	re.compile(R'''([a-z\d])([A-Z])''')

lowerCAmelCase__											=	re.compile(R'''(?<!_)_(?!_)''')
lowerCAmelCase__											=	re.compile(R'''(_{2,})''')

lowerCAmelCase__											=	R'''^\w+(\.\w+)*$'''

lowerCAmelCase__											=	R'''<>:/\|?*'''


def 		_A     (    A__      ):






 """simple docstring"""



 __lowercase							  = _uppercase_uppercase_re.sub(R'''\1_\2'''     ,				A__      )
 __lowercase							  = _lowercase_uppercase_re.sub(R'''\1_\2'''     ,				A__      )
 return name.lower()


def 		_A     (    A__      ):






 """simple docstring"""



 __lowercase							  = _single_underscore_re.split(A__      )
 __lowercase							  = [_multiple_underscores_re.split(A__      ) for n in name]
 return "".join(n.capitalize() for n in itertools.chain.from_iterable(A__      ) if n != ''''''      )


def 		_A     (    A__      ):






 """simple docstring"""



 if os.path.basename(A__      ) != name:
  raise ValueError(F"Should be a dataset name, not a path: {name}"      )
 return camelcase_to_snakecase(A__      )


def 		_A     (    A__     ,				A__      ):






 """simple docstring"""



 if os.path.basename(A__      ) != name:
  raise ValueError(F"Should be a dataset name, not a path: {name}"      )
 if not re.match(_split_re     ,				A__      ):
  raise ValueError(F"Split name should match '{_split_re}'' but got '{split}'."      )
 return F"{filename_prefix_for_name(A__      )}-{split}"


def 		_A     (    A__     ,				A__     ,				A__     ,				A__=None      ):






 """simple docstring"""



 __lowercase							  = filename_prefix_for_split(A__     ,				A__      )
 if filetype_suffix:
  prefix += F".{filetype_suffix}"
 __lowercase							  = os.path.join(A__     ,				A__      )
 return F"{filepath}*"






def 		_A     (    A__     ,				A__     ,				A__     ,				A__=None     ,				A__=None      ):






 """simple docstring"""



 __lowercase							  = filename_prefix_for_split(A__     ,				A__      )
 __lowercase							  = os.path.join(A__     ,				A__      )

 if shard_lengths:
  __lowercase							  = len(A__      )
  __lowercase							  = [F"{prefix}-{shard_id:05d}-of-{num_shards:05d}" for shard_id in range(A__      )]
  if filetype_suffix:
   __lowercase							  = [filename + F".{filetype_suffix}" for filename in filenames]
  return filenames
 else:
  __lowercase							  = prefix
  if filetype_suffix:
   filename += F".{filetype_suffix}"
  return [filename]




'''simple docstring'''






import argparse

from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection

from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline


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

 lowerCAmelCase__											=	parser.parse_args()

 lowerCAmelCase__											=	UnCLIPPipeline.from_pretrained(args.txtaimg_unclip)

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

 lowerCAmelCase__											=	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)

