

import argparse
import os

import torch

from transformers.utils import WEIGHTS_NAME


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

lowerCAmelCase     :   str						     =  'lm_head.decoder.weight'
lowerCAmelCase     :   List[Any]						     =  'lm_head.weight'

def    A_  (							a					,   a  ):

      """simple docstring"""



      SCREAMING_SNAKE_CASE_				:  str           =     torch.load(a  )
      SCREAMING_SNAKE_CASE_				:  Union[str, Any]           =     d.pop(a  )
      os.makedirs(a					,   exist_ok=a  )
      torch.save(a					,   os.path.join(a					,   a  )  )


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









from math import pi

def    A_  (							a					,   a  ):

      """simple docstring"""



      return 2 * pi * radius * (angle / 3_6_0)


if __name__ == "__main__":
    print(arc_length(90, 10))






