


import argparse
import os

import torch

from transformers.utils import WEIGHTS_NAME


_lowerCamelCase     =  ['small', 'medium', 'large']

_lowerCamelCase     =  'lm_head.decoder.weight'
_lowerCamelCase     =  'lm_head.weight'


def __lowercase     (      lowerCamelCase_  :      str						,					lowerCamelCase_  :      str  ):
				SCREAMING_SNAKE_CASE__     							=				torch.load(lowerCamelCase_  )
				SCREAMING_SNAKE_CASE__     							=				d.pop(lowerCamelCase_  )
				os.makedirs(lowerCamelCase_						,					exist_ok=lowerCamelCase_  )
				torch.save(lowerCamelCase_						,					os.path.join(lowerCamelCase_						,					lowerCamelCase_  )  )


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




"""simple docstring"""






from math import pi


def __lowercase     (      lowerCamelCase_  :      int						,					lowerCamelCase_  :      int  ):
				return 2 * pi * radius * (angle / 360)


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