


"""simple docstring"""







import argparse

from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection

from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline


if __name__ == "__main__":
       lowerCamelCase_   :   int									=  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_   :   Dict									=  parser.parse_args()

       lowerCamelCase_   :   Tuple									=  UnCLIPPipeline.from_pretrained(args.txtaimg_unclip)

       lowerCamelCase_   :   List[Any]									=  CLIPImageProcessor()
       lowerCamelCase_   :   Tuple									=  CLIPVisionModelWithProjection.from_pretrained("""openai/clip-vit-large-patch14""")

       lowerCamelCase_   :   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"""



_UpperCamelCase		:  List[str]						=		{
    'meter': 'm',
    'kilometer': 'km',
    'megametre': 'Mm',
    'gigametre': 'Gm',
    'terametre': 'Tm',
    'petametre': 'Pm',
    'exametre': 'Em',
    'zettametre': 'Zm',
    'yottametre': 'Ym',
}
# Exponent of the factor(meter)
_UpperCamelCase		:  str						=		{
    'm': 0,
    'km': 3,
    'Mm': 6,
    'Gm': 9,
    'Tm': 1_2,
    'Pm': 1_5,
    'Em': 1_8,
    'Zm': 2_1,
    'Ym': 2_4,
}
def 						_SCREAMING_SNAKE_CASE (    __snake_case			:  float		,					__snake_case			:  str		,					__snake_case			:  str    ):





  '''simple docstring'''





  lowercase							    =       from_type.lower().strip('s'    )
  lowercase							    =       to_type.lower().strip('s'    )

  lowercase							    =       UNIT_SYMBOL.get(__snake_case		,					__snake_case    )
  lowercase							    =       UNIT_SYMBOL.get(__snake_case		,					__snake_case    )

  if from_sanitized not in METRIC_CONVERSION:
    lowercase							    =       (
        f'Invalid \'from_type\' value: {from_type!r}.\n'
        f'Conversion abbreviations are: {", ".join(__snake_case    )}'
    )
    raise ValueError(__snake_case    )
  if to_sanitized not in METRIC_CONVERSION:
    lowercase							    =       (
        f'Invalid \'to_type\' value: {to_type!r}.\n'
        f'Conversion abbreviations are: {", ".join(__snake_case    )}'
    )
    raise ValueError(__snake_case    )
  lowercase							    =       METRIC_CONVERSION[from_sanitized]
  lowercase							    =       METRIC_CONVERSION[to_sanitized]
  lowercase							    =       1

  if from_exponent > to_exponent:
    lowercase							    =       from_exponent - to_exponent
  else:
    lowercase							    =       -(to_exponent - from_exponent)

  return value * pow(10		,					__snake_case    )


if __name__ == "__main__":
    from doctest import testmod

    testmod()


