


import argparse

import OmegaConf
import torch

from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel

def   _UpperCAmelCase       (     UpperCAmelCase      :			List[str]						,	UpperCAmelCase      :			Optional[Any]						,	UpperCAmelCase      :			str      ):
      """simple docstring"""




      __lowerCamelCase     :      Optional[Any]       						=						OmegaConf.load(UpperCAmelCase      )
      __lowerCamelCase     :      Union[str, Any]       						=						torch.load(UpperCAmelCase						,	map_location="""cpu"""      )["""model"""]
      __lowerCamelCase     :      str       						=						list(state_dict.keys()      )

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

    # extract state_dict for UNetLDM
      __lowerCamelCase     :      Optional[int]       						=						{}
      __lowerCamelCase     :      Optional[Any]       						=						"""model.diffusion_model."""
      for key in keys:
            if key.startswith(UpperCAmelCase      ):
                  __lowerCamelCase     :      Optional[int]       						=						state_dict[key]

      __lowerCamelCase     :      Dict       						=						config.model.params.first_stage_config.params
      __lowerCamelCase     :      str       						=						config.model.params.unet_config.params

      __lowerCamelCase     :      Any       						=						VQModel(**UpperCAmelCase      ).eval()
      vqvae.load_state_dict(UpperCAmelCase      )

      __lowerCamelCase     :      List[str]       						=						UNetLDMModel(**UpperCAmelCase      ).eval()
      unet.load_state_dict(UpperCAmelCase      )

      __lowerCamelCase     :      str       						=						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						,	)

      __lowerCamelCase     :      Union[str, Any]       						=						LDMPipeline(UpperCAmelCase						,	UpperCAmelCase						,	UpperCAmelCase      )
      pipeline.save_pretrained(UpperCAmelCase      )


if __name__ == "__main__":
    __UpperCamelCase    :						Tuple     =							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)
    __UpperCamelCase    :						List[str]     =							parser.parse_args()

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







def   _UpperCAmelCase       (     ):
      """simple docstring"""




      __lowerCamelCase     :      Optional[int]       						=						[31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]

      __lowerCamelCase     :      str       						=						6
      __lowerCamelCase     :      Optional[int]       						=						1
      __lowerCamelCase     :      Optional[int]       						=						1_901

      __lowerCamelCase     :      Optional[Any]       						=						0

      while year < 2_001:
            day += 7

            if (year % 4 == 0 and year % 100 != 0) or (year % 400 == 0):
                  if day > days_per_month[month - 1] and month != 2:
                        month += 1
                        __lowerCamelCase     :      Tuple       						=						day - days_per_month[month - 2]
                  elif day > 29 and month == 2:
                        month += 1
                        __lowerCamelCase     :      str       						=						day - 29
            else:
                  if day > days_per_month[month - 1]:
                        month += 1
                        __lowerCamelCase     :      Any       						=						day - days_per_month[month - 2]

            if month > 12:
                  year += 1
                  __lowerCamelCase     :      Optional[Any]       						=						1

            if year < 2_001 and day == 1:
                  sundays += 1
      return sundays


if __name__ == "__main__":
    print(solution())



