





import argparse

import OmegaConf
import torch

from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel

def   a_    ( lowerCAmelCase_      :			Optional[int],	lowerCAmelCase_      :			Optional[int],	lowerCAmelCase_      :			Union[str, Any]	):
   __lowerCAmelCase								=	OmegaConf.load(lowerCAmelCase_	)
   __lowerCAmelCase								=	torch.load(lowerCAmelCase_,	map_location='cpu'	)['model']
   __lowerCAmelCase								=	list(state_dict.keys()	)

   # extract state_dict for VQVAE
   __lowerCAmelCase								=	{}
   __lowerCAmelCase								=	'first_stage_model.'
   for key in keys:
      if key.startswith(lowerCAmelCase_	):
         __lowerCAmelCase								=	state_dict[key]

    # extract state_dict for UNetLDM
   __lowerCAmelCase								=	{}
   __lowerCAmelCase								=	'model.diffusion_model.'
   for key in keys:
      if key.startswith(lowerCAmelCase_	):
         __lowerCAmelCase								=	state_dict[key]

   __lowerCAmelCase								=	config.model.params.first_stage_config.params
   __lowerCAmelCase								=	config.model.params.unet_config.params

   __lowerCAmelCase								=	VQModel(**lowerCAmelCase_	).eval()
   vqvae.load_state_dict(lowerCAmelCase_	)

   __lowerCAmelCase								=	UNetLDMModel(**lowerCAmelCase_	).eval()
   unet.load_state_dict(lowerCAmelCase_	)

   __lowerCAmelCase								=	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_,	)

   __lowerCAmelCase								=	LDMPipeline(lowerCAmelCase_,	lowerCAmelCase_,	lowerCAmelCase_	)
   pipeline.save_pretrained(lowerCAmelCase_	)


if __name__ == "__main__":
     _snake_case  :    Union[str, Any]						    =  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)
     _snake_case  :    Optional[Any]						    =  parser.parse_args()

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








from __future__ import annotations

import string
from itertools import cycle, product
from pathlib import Path

_snake_case  :    str						    =  (
    string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
_snake_case  :    list[int]						    =  [ord(letter) for letter in string.ascii_lowercase]
_snake_case  :    set[int]						    =  {ord(char) for char in VALID_CHARS}

_snake_case  :    list[str]						    =  ["the", "be", "to", "of", "and", "in", "that", "have"]

def   a_    ( lowerCAmelCase_      :			list[int],	lowerCAmelCase_      :			tuple[int, ...]	):
   __lowerCAmelCase								=	""
   __lowerCAmelCase								=	42
   __lowerCAmelCase								=	42
   __lowerCAmelCase								=	42

   for keychar, cipherchar in zip(cycle(lowerCAmelCase_	),	lowerCAmelCase_	):
      __lowerCAmelCase								=	cipherchar ^ keychar
      if decodedchar not in VALID_INTS:
         return None
      decoded += chr(lowerCAmelCase_	)

   return decoded

def   a_    ( lowerCAmelCase_      :			list[int]	):
   __lowerCAmelCase								=	[]
   for key in product(lowerCAmelCase_,	repeat=3	):
      __lowerCAmelCase								=	try_key(lowerCAmelCase_,	lowerCAmelCase_	)
      if encoded is not None:
         possibles.append(lowerCAmelCase_	)
   return possibles

def   a_    ( lowerCAmelCase_      :			list[str],	lowerCAmelCase_      :			str	):
   return [possible for possible in possibles if common_word in possible.lower()]

def   a_    ( lowerCAmelCase_      :			str = "p059_cipher.txt"	):
   __lowerCAmelCase								=	42
   __lowerCAmelCase								=	42
   __lowerCAmelCase								=	42
   __lowerCAmelCase								=	42
   __lowerCAmelCase								=	Path(lowerCAmelCase_	).parent.joinpath(lowerCAmelCase_	).read_text(encoding='utf-8'	)

   __lowerCAmelCase								=	[int(lowerCAmelCase_	) for number in data.strip().split(','	)]

   __lowerCAmelCase								=	filter_valid_chars(lowerCAmelCase_	)
   for common_word in COMMON_WORDS:
      __lowerCAmelCase								=	filter_common_word(lowerCAmelCase_,	lowerCAmelCase_	)
      if len(lowerCAmelCase_	) == 1:
         break

   __lowerCAmelCase								=	possibles[0]
   return sum(ord(lowerCAmelCase_	) for char in decoded_text	)


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

