



"""simple docstring"""
import re

def       _snake_case						(						UpperCamelCase						:		str						):
 UpperCAmelCase	:					Optional[int]	=	re.compile(
     R"""^(?:0|94|\+94|0{2}94)""" R"""7(0|1|2|4|5|6|7|8)""" R"""(-| |)""" R"""\d{7}$"""						)

 return bool(re.search(UpperCamelCase			,		UpperCamelCase						)						)


if __name__ == "__main__":
      A:   int								=		"0094702343221"

      print(is_sri_lankan_phone_number(phone))





"""simple docstring"""
import argparse
import os

import torch

from transformers.utils import WEIGHTS_NAME


_lowerCAmelCase    :int     =					['small', 'medium', 'large']

_lowerCAmelCase    :int     =					'lm_head.decoder.weight'
_lowerCAmelCase    :Dict     =					'lm_head.weight'





def  lowerCamelCase_						(UpperCamelCase__		:		str     ,       UpperCamelCase__		:		str							):
    _UpperCAmelCase							:  List[Any]											=    torch.load(UpperCamelCase__							)
    _UpperCAmelCase							:  List[str]											=    d.pop(UpperCamelCase__							)
    os.makedirs(UpperCamelCase__     ,       exist_ok=UpperCamelCase__							)
    torch.save(UpperCamelCase__     ,       os.path.join(UpperCamelCase__     ,       UpperCamelCase__							)							)


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


