
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path

import torch_xla.distributed.xla_multiprocessing as xmp


def 				SCREAMING_SNAKE_CASE_   (      ):
      UpperCamelCase__     : Tuple											=					ArgumentParser(
          description=(
              '''PyTorch TPU distributed training launch helper utility that will spawn up multiple distributed processes'''
          )		)

      # Optional arguments for the launch helper
      parser.add_argument('''--num_cores'''			,		type=UpperCamelCase__			,		default=1			,		help='''Number of TPU cores to use (1 or 8).'''		)

      # positional
      parser.add_argument(
          '''training_script'''			,		type=UpperCamelCase__			,		help=(
              '''The full path to the single TPU training '''
              '''program/script to be launched in parallel, '''
              '''followed by all the arguments for the '''
              '''training script'''
          )			,		)

      # rest from the training program
      parser.add_argument('''training_script_args'''			,		nargs=UpperCamelCase__		)

      return parser.parse_args()


def 				SCREAMING_SNAKE_CASE_   (      ):
      UpperCamelCase__     : str											=					parse_args()

      # Import training_script as a module.
      UpperCamelCase__     : Any											=					Path(args.training_script		)
      sys.path.append(str(script_fpath.parent.resolve()		)		)
      UpperCamelCase__     : Optional[Any]											=					script_fpath.stem
      UpperCamelCase__     : Optional[Any]											=					importlib.import_module(UpperCamelCase__		)

      # Patch sys.argv
      UpperCamelCase__     : Any											=					[args.training_script] + args.training_script_args + ['''--tpu_num_cores''', str(args.num_cores		)]

      xmp.spawn(mod._mp_fn			,		args=()			,		nprocs=args.num_cores		)


if __name__ == "__main__":
    main()




def 				SCREAMING_SNAKE_CASE_   (      UpperCamelCase__			,		UpperCamelCase__		):

      def get_matched_characters(UpperCamelCase__			,		UpperCamelCase__		) -> str:
            UpperCamelCase__     : Union[str, Any]											=					[]
            UpperCamelCase__     : Union[str, Any]											=					min(len(_stra		)			,		len(_stra		)		) // 2
            for i, l in enumerate(_stra		):
                  UpperCamelCase__     : Optional[int]											=					int(max(0			,		i - limit		)		)
                  UpperCamelCase__     : List[str]											=					int(min(i + limit + 1			,		len(_stra		)		)		)
                  if l in _stra[left:right]:
                        matched.append(UpperCamelCase__		)
                        UpperCamelCase__     : List[str]											=					f'''{_stra[0:_stra.index(UpperCamelCase__		)]} {_stra[_stra.index(UpperCamelCase__		) + 1:]}'''

            return "".join(UpperCamelCase__		)

      # matching characters
      UpperCamelCase__     : Any											=					get_matched_characters(UpperCamelCase__			,		UpperCamelCase__		)
      UpperCamelCase__     : Union[str, Any]											=					get_matched_characters(UpperCamelCase__			,		UpperCamelCase__		)
      UpperCamelCase__     : List[Any]											=					len(UpperCamelCase__		)

      # transposition
      UpperCamelCase__     : str											=					(
          len([(ca, ca) for ca, ca in zip(UpperCamelCase__			,		UpperCamelCase__		) if ca != ca]		) // 2
      )

      if not match_count:
            UpperCamelCase__     : Union[str, Any]											=					0.0
      else:
            UpperCamelCase__     : Optional[int]											=					(
                1
                / 3
                * (
                    match_count / len(UpperCamelCase__		)
                    + match_count / len(UpperCamelCase__		)
                    + (match_count - transpositions) / match_count
                )
            )

      # common prefix up to 4 characters
      UpperCamelCase__     : Dict											=					0
      for ca, ca in zip(stra[:4]			,		stra[:4]		):
            if ca == ca:
                  prefix_len += 1
            else:
                  break

      return jaro + 0.1 * prefix_len * (1 - jaro)


if __name__ == "__main__":
    import doctest

    doctest.testmod()
    print(jaro_winkler("hello", "world"))


