
'''simple docstring'''
import argparse
import os

import torch

from transformers.utils import WEIGHTS_NAME


A__   :		Tuple 		=['small', 'medium', 'large']

A__   :		Dict 		='lm_head.decoder.weight'
A__   :		Optional[Any] 		='lm_head.weight'







def        A_     (						__SCREAMING_SNAKE_CASE						:  str			,     __SCREAMING_SNAKE_CASE						:  str )				->       Union[str, Any]:





  """simple docstring"""

  __A		:     str												=		torch.load(__SCREAMING_SNAKE_CASE )
  __A		:     int												=		d.pop(__SCREAMING_SNAKE_CASE )
  os.makedirs(__SCREAMING_SNAKE_CASE			,     exist_ok=__SCREAMING_SNAKE_CASE )
  torch.save(__SCREAMING_SNAKE_CASE			,     os.path.join(__SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE ) )


if __name__ == "__main__":
     A__   :		Any 		=argparse.ArgumentParser()
     parser.add_argument('--dialogpt_path', default='.', type=str)
     A__   :		Union[str, Any] 		=parser.parse_args()
     for MODEL in DIALOGPT_MODELS:
          A__   :		Dict 		=os.path.join(args.dialogpt_path, F"{MODEL}_ft.pkl")
          A__   :		Optional[int] 		=F"./DialoGPT-{MODEL}"
          convert_dialogpt_checkpoint(
              checkpoint_path,
              pytorch_dump_folder_path,
          )

'''simple docstring'''
A__   :		List[Any] 		=[
    'Audio',
    'Array2D',
    'Array3D',
    'Array4D',
    'Array5D',
    'ClassLabel',
    'Features',
    'Sequence',
    'Value',
    'Image',
    'Translation',
    'TranslationVariableLanguages',
]
from .audio import Audio
from .features import ArrayaD, ArrayaD, ArrayaD, ArrayaD, ClassLabel, Features, Sequence, Value
from .image import Image
from .translation import Translation, TranslationVariableLanguages



