


import argparse

import OmegaConf
import torch

from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel




def  a   (lowerCAmelCase__		,				lowerCAmelCase__		,				lowerCAmelCase__   ):
   __a					=  OmegaConf.load(lowerCAmelCase__   )
   __a					=  torch.load(lowerCAmelCase__		,				map_location="""cpu"""   )["""model"""]
   __a					=  list(state_dict.keys()   )

   # extract state_dict for VQVAE
   __a					=  {}
   __a					=  """first_stage_model."""
   for key in keys:
      if key.startswith(lowerCAmelCase__   ):
         __a					=  state_dict[key]

    # extract state_dict for UNetLDM
   __a					=  {}
   __a					=  """model.diffusion_model."""
   for key in keys:
      if key.startswith(lowerCAmelCase__   ):
         __a					=  state_dict[key]

   __a					=  config.model.params.first_stage_config.params
   __a					=  config.model.params.unet_config.params

   __a					=  VQModel(**lowerCAmelCase__   ).eval()
   vqvae.load_state_dict(lowerCAmelCase__   )

   __a					=  UNetLDMModel(**lowerCAmelCase__   ).eval()
   unet.load_state_dict(lowerCAmelCase__   )

   __a					=  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=lowerCAmelCase__		,				)

   __a					=  LDMPipeline(lowerCAmelCase__		,				lowerCAmelCase__		,				lowerCAmelCase__   )
   pipeline.save_pretrained(lowerCAmelCase__   )


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

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







"""simple docstring"""



import math
from collections.abc import Iterator
from itertools import takewhile







def     __lowerCAmelCase		(		lowercase    :    int					)      ->		bool:


    """simple docstring"""





    if 1 < number < 4:
        # 2 and 3 are primes
        return True
    elif number < 2 or number % 2 == 0 or number % 3 == 0:
        # Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
        return False

    # All primes number are in format of 6k +/- 1
    for i in range(5		,				int(math.sqrt(lowercase					) + 1					)		,				6					):
        if number % i == 0 or number % (i + 2) == 0:
            return False
    return True







def     __lowerCAmelCase		(		)      ->		Iterator[int]:


    """simple docstring"""





    snake_case       : Optional[int]    =       2
    while True:
        if is_prime(lowercase					):
            yield num
        num += 1







def     __lowerCAmelCase		(		lowercase    :    int = 200_0000					)      ->		int:


    """simple docstring"""





    return sum(takewhile(lambda lowercase					: x < n		,				prime_generator()					)					)


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





