





"""simple docstring"""





import copy
import re




class 							snake_case							:

      '''simple docstring'''



      _A     :       Any         =       'hp'
      _A     :       int         =       {}
      _A     :       Any         =       None

      @classmethod
      def       A_					(							cls       :      Optional[Any]						,				__lowercase       :      Any						,				__lowercase       :      List[str] ):


        '''simple docstring'''




        __UpperCAmelCase    :						str       =						prefix
        __UpperCAmelCase    :						str       =						defaults
        cls.build_naming_info()

      @staticmethod
      def       A_					(							__lowercase       :      Any						,				__lowercase       :      Tuple ):


        '''simple docstring'''




        if len(__lowercase ) == 0:
          return ""
        __UpperCAmelCase    :						List[Any]       =						None
        if any(char.isdigit() for char in word ):
          raise Exception(f'''Parameters should not contain numbers: \'{word}\' contains a number''' )
        if word in info["short_word"]:
          return info["short_word"][word]
        for prefix_len in range(1						,				len(__lowercase ) + 1 ):
          __UpperCAmelCase    :						Union[str, Any]       =						word[:prefix_len]
          if prefix in info["reverse_short_word"]:
            continue
          else:
            __UpperCAmelCase    :						List[Any]       =						prefix
            break

        if short_word is None:
          # Paranoid fallback
          def int_to_alphabetic(__lowercase       :      List[Any] ):
            __UpperCAmelCase    :						Optional[int]       =						''''''
            while integer != 0:
              __UpperCAmelCase    :						Any       =						chr(ord('''A''' ) + integer % 10 ) + s
              integer //= 10
            return s

          __UpperCAmelCase    :						List[str]       =						0
          while True:
            __UpperCAmelCase    :						str       =						word + '''#''' + int_to_alphabetic(__lowercase )
            if sword in info["reverse_short_word"]:
              continue
            else:
              __UpperCAmelCase    :						str       =						sword
              break

        __UpperCAmelCase    :						List[Any]       =						short_word
        __UpperCAmelCase    :						str       =						word
        return short_word

      @staticmethod
      def       A_					(							__lowercase       :      Any						,				__lowercase       :      List[str] ):


        '''simple docstring'''




        __UpperCAmelCase    :						List[Any]       =						param_name.split('''_''' )

        __UpperCAmelCase    :						Tuple       =						[TrialShortNamer.shortname_for_word(__lowercase						,				__lowercase ) for word in words]

        # We try to create a separatorless short name, but if there is a collision we have to fallback
        # to a separated short name
        __UpperCAmelCase    :						Tuple       =						['''''', '''_''']

        for separator in separators:
          __UpperCAmelCase    :						Optional[Any]       =						separator.join(__lowercase )
          if shortname not in info["reverse_short_param"]:
            __UpperCAmelCase    :						Any       =						shortname
            __UpperCAmelCase    :						Dict       =						param_name
            return shortname

        return param_name

      @staticmethod
      def       A_					(							__lowercase       :      Optional[int]						,				__lowercase       :      int ):


        '''simple docstring'''




        __UpperCAmelCase    :						Union[str, Any]       =						TrialShortNamer.shortname_for_key(__lowercase						,				__lowercase )
        __UpperCAmelCase    :						List[Any]       =						short_name
        __UpperCAmelCase    :						Union[str, Any]       =						param_name

      @classmethod
      def       A_					(							cls       :      int ):


        '''simple docstring'''




        if cls.NAMING_INFO is not None:
          return

        __UpperCAmelCase    :						Union[str, Any]       =						{
            '''short_word''': {},
            '''reverse_short_word''': {},
            '''short_param''': {},
            '''reverse_short_param''': {},
        }

        __UpperCAmelCase    :						int       =						list(cls.DEFAULTS.keys() )

        for k in field_keys:
          cls.add_new_param_name(__lowercase						,				__lowercase )

        __UpperCAmelCase    :						Optional[int]       =						info

      @classmethod
      def       A_					(							cls       :      Optional[int]						,				__lowercase       :      List[str] ):


        '''simple docstring'''




        cls.build_naming_info()
        assert cls.PREFIX is not None
        __UpperCAmelCase    :						Optional[Any]       =						[copy.copy(cls.PREFIX )]

        for k, v in params.items():
          if k not in cls.DEFAULTS:
            raise Exception(f'''You should provide a default value for the param name {k} with value {v}''' )
          if v == cls.DEFAULTS[k]:
            # The default value is not added to the name
            continue

          __UpperCAmelCase    :						int       =						cls.NAMING_INFO['''short_param'''][k]

          if isinstance(__lowercase						,				__lowercase ):
            __UpperCAmelCase    :						Any       =						1 if v else 0

          __UpperCAmelCase    :						str       =						'''''' if isinstance(__lowercase						,				(int, float) ) else '''-'''
          __UpperCAmelCase    :						Union[str, Any]       =						f'''{key}{sep}{v}'''
          name.append(__lowercase )

        return "_".join(__lowercase )







      @classmethod
      def       A_					(							cls       :      List[Any]						,				__lowercase       :      Optional[int] ):


        '''simple docstring'''




        __UpperCAmelCase    :						int       =						repr[len(cls.PREFIX ) + 1 :]
        if repr == "":
          __UpperCAmelCase    :						Optional[int]       =						[]
        else:
          __UpperCAmelCase    :						Optional[Any]       =						repr.split('''_''' )

        __UpperCAmelCase    :						str       =						{}

        for value in values:
          if "-" in value:
            __UpperCAmelCase       ,     __UpperCAmelCase    :						Any       =						value.split('''-''' )
          else:
            __UpperCAmelCase    :						str       =						re.sub('''[0-9.]'''						,				''''''						,				__lowercase )
            __UpperCAmelCase    :						List[str]       =						float(re.sub('''[^0-9.]'''						,				''''''						,				__lowercase ) )

          __UpperCAmelCase    :						List[str]       =						cls.NAMING_INFO['''reverse_short_param'''][p_k]

          __UpperCAmelCase    :						str       =						p_v

        for k in cls.DEFAULTS:
          if k not in parameters:
            __UpperCAmelCase    :						Union[str, Any]       =						cls.DEFAULTS[k]

        return parameters






"""simple docstring"""





import argparse

import OmegaConf
import torch

from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel


def       lowerCamelCase_       (   UpperCAmelCase_  ,			UpperCAmelCase_  ,			UpperCAmelCase_  )						->Optional[Any]:





  """simple docstring"""


  __UpperCAmelCase    :						int       =						OmegaConf.load(UpperCAmelCase_  )
  __UpperCAmelCase    :						Union[str, Any]       =						torch.load(UpperCAmelCase_  ,			map_location='''cpu'''  )['''model''']
  __UpperCAmelCase    :						List[Any]       =						list(state_dict.keys()  )

  # extract state_dict for VQVAE
  __UpperCAmelCase    :						Dict       =						{}
  __UpperCAmelCase    :						Tuple       =						'''first_stage_model.'''
  for key in keys:
    if key.startswith(UpperCAmelCase_  ):
      __UpperCAmelCase    :						List[Any]       =						state_dict[key]

    # extract state_dict for UNetLDM
  __UpperCAmelCase    :						Union[str, Any]       =						{}
  __UpperCAmelCase    :						Any       =						'''model.diffusion_model.'''
  for key in keys:
    if key.startswith(UpperCAmelCase_  ):
      __UpperCAmelCase    :						int       =						state_dict[key]

  __UpperCAmelCase    :						Any       =						config.model.params.first_stage_config.params
  __UpperCAmelCase    :						Dict       =						config.model.params.unet_config.params

  __UpperCAmelCase    :						Tuple       =						VQModel(**UpperCAmelCase_  ).eval()
  vqvae.load_state_dict(UpperCAmelCase_  )

  __UpperCAmelCase    :						Any       =						UNetLDMModel(**UpperCAmelCase_  ).eval()
  unet.load_state_dict(UpperCAmelCase_  )

  __UpperCAmelCase    :						Union[str, Any]       =						DDIMScheduler(
      timesteps=config.model.params.timesteps  ,			beta_schedule='''scaled_linear'''  ,			beta_start=config.model.params.linear_start  ,			beta_end=config.model.params.linear_end  ,			clip_sample=UpperCAmelCase_  ,			)

  __UpperCAmelCase    :						Tuple       =						LDMPipeline(UpperCAmelCase_  ,			UpperCAmelCase_  ,			UpperCAmelCase_  )
  pipeline.save_pretrained(UpperCAmelCase_  )


if __name__ == "__main__":
  lowercase__				:str				   =       argparse.ArgumentParser()
  parser.add_argument('--checkpoint_path', type=str, required=True)
  parser.add_argument('--config_path', type=str, required=True)
  parser.add_argument('--output_path', type=str, required=True)
  lowercase__				:Dict				   =       parser.parse_args()

  convert_ldm_original(args.checkpoint_path, args.config_path, args.output_path)