





"""simple docstring"""
import argparse

import OmegaConf
import torch

from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel



def 					__lowerCamelCase       (							a_					:		int			,       a_					:		Any			,       a_					:		List[Any]							)      ->				List[str]:
      __SCREAMING_SNAKE_CASE       :Dict		    =  OmegaConf.load(a_							)
      __SCREAMING_SNAKE_CASE       :Union[str, Any]		    =  torch.load(a_			,       map_location='''cpu'''							)['''model''']
      __SCREAMING_SNAKE_CASE       :Union[str, Any]		    =  list(state_dict.keys()							)

      # extract state_dict for VQVAE
      __SCREAMING_SNAKE_CASE       :Optional[Any]		    =  {}
      __SCREAMING_SNAKE_CASE       :Union[str, Any]		    =  '''first_stage_model.'''
      for key in keys:
            if key.startswith(a_							):
                  __SCREAMING_SNAKE_CASE       :List[str]		    =  state_dict[key]

    # extract state_dict for UNetLDM
      __SCREAMING_SNAKE_CASE       :List[str]		    =  {}
      __SCREAMING_SNAKE_CASE       :int		    =  '''model.diffusion_model.'''
      for key in keys:
            if key.startswith(a_							):
                  __SCREAMING_SNAKE_CASE       :List[str]		    =  state_dict[key]

      __SCREAMING_SNAKE_CASE       :int		    =  config.model.params.first_stage_config.params
      __SCREAMING_SNAKE_CASE       :Tuple		    =  config.model.params.unet_config.params

      __SCREAMING_SNAKE_CASE       :str		    =  VQModel(**a_							).eval()
      vqvae.load_state_dict(a_							)

      __SCREAMING_SNAKE_CASE       :Optional[Any]		    =  UNetLDMModel(**a_							).eval()
      unet.load_state_dict(a_							)

      __SCREAMING_SNAKE_CASE       :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=a_			,       )

      __SCREAMING_SNAKE_CASE       :int		    =  LDMPipeline(a_			,       a_			,       a_							)
      pipeline.save_pretrained(a_							)


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

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






"""simple docstring"""
from itertools import product



def 					__lowerCamelCase       (							a_					:		int			,       a_					:		int							)      ->				list[int]:
      __SCREAMING_SNAKE_CASE       :Tuple		    =  sides_number
      __SCREAMING_SNAKE_CASE       :List[Any]		    =  max_face_number * dice_number
      __SCREAMING_SNAKE_CASE       :List[Any]		    =  [0] * (max_total + 1)

      __SCREAMING_SNAKE_CASE       :Optional[int]		    =  1
      __SCREAMING_SNAKE_CASE       :Tuple		    =  range(a_			,       max_face_number + 1							)
      for dice_numbers in product(a_			,       repeat=a_							):
            __SCREAMING_SNAKE_CASE       :Any		    =  sum(a_							)
            totals_frequencies[total] += 1

      return totals_frequencies



def 					__lowerCamelCase       (							)      ->				float:
      __SCREAMING_SNAKE_CASE       :Dict		    =  total_frequency_distribution(
          sides_number=4			,       dice_number=9							)
      __SCREAMING_SNAKE_CASE       :Union[str, Any]		    =  total_frequency_distribution(
          sides_number=6			,       dice_number=6							)

      __SCREAMING_SNAKE_CASE       :Optional[Any]		    =  0
      __SCREAMING_SNAKE_CASE       :Any		    =  9
      __SCREAMING_SNAKE_CASE       :List[str]		    =  4 * 9
      __SCREAMING_SNAKE_CASE       :Dict		    =  6
      for peter_total in range(a_			,       max_peter_total + 1							):
            peter_wins_count += peter_totals_frequencies[peter_total] * sum(
                colin_totals_frequencies[min_colin_total:peter_total]							)

      __SCREAMING_SNAKE_CASE       :List[str]		    =  (4**9) * (6**6)
      __SCREAMING_SNAKE_CASE       :Union[str, Any]		    =  peter_wins_count / total_games_number

      __SCREAMING_SNAKE_CASE       :str		    =  round(a_			,       ndigits=7							)

      return rounded_peter_win_probability


if __name__ == "__main__":
  print(f'{solution() = }')