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

import torch_xla.distributed.xla_multiprocessing as xmp
def 		a_       (   ):
  lowerCAmelCase__								=			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=_A      ,   default=1      ,   help='''Number of TPU cores to use (1 or 8).'''							)

  # positional
  parser.add_argument(
      '''training_script'''      ,   type=_A      ,   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=_A							)

  return parser.parse_args()
def 		a_       (   ):
  lowerCAmelCase__								=			parse_args()

  # Import training_script as a module.
  lowerCAmelCase__								=			Path(args.training_script							)
  sys.path.append(str(script_fpath.parent.resolve()							)							)
  lowerCAmelCase__								=			script_fpath.stem
  lowerCAmelCase__								=			importlib.import_module(_A							)

  # Patch sys.argv
  lowerCAmelCase__								=			[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()







from __future__ import annotations

from collections.abc import Iterator
from typing import Any





class 						SCREAMING_SNAKE_CASE__		:
     def __init__(	self  :		int					,	__lowerCamelCase  :		Any	):



       """simple docstring"""
       lowerCAmelCase__								=			data
       lowerCAmelCase__								=			None



     def __str__(	self  :		int	):



       """simple docstring"""
       return F"""{self.data}"""





class 						SCREAMING_SNAKE_CASE__		:
     def __init__(	self  :		Union[str, Any]	):



       """simple docstring"""
       lowerCAmelCase__								=			None
       lowerCAmelCase__								=			None
     def __iter__(	self  :		List[Any]	):



       """simple docstring"""
       lowerCAmelCase__								=			self.front
       while node:
         yield node.data
         lowerCAmelCase__								=			node.next
     def __len__(	self  :		int	):



       """simple docstring"""
       return len(tuple(iter(self	)	)	)
     def __str__(	self  :		Optional[int]	):



       """simple docstring"""
       return " <- ".join(str(__lowerCamelCase	) for item in self	)
     def 					A__			(	self  :		Tuple	):



       """simple docstring"""
       return len(self	) == 0
     def 					A__			(	self  :		str					,	__lowerCamelCase  :		Any	):



       """simple docstring"""
       lowerCAmelCase__								=			Node(__lowerCamelCase	)
       if self.is_empty():
         lowerCAmelCase__								=			lowerCAmelCase__								=			node
       else:
         assert isinstance(self.rear					,	__lowerCamelCase	)
         lowerCAmelCase__								=			node
         lowerCAmelCase__								=			node
     def 					A__			(	self  :		Optional[Any]	):



       """simple docstring"""
       if self.is_empty():
         raise IndexError('''dequeue from empty queue'''	)
       assert isinstance(self.front					,	__lowerCamelCase	)
       lowerCAmelCase__								=			self.front
       lowerCAmelCase__								=			self.front.next
       if self.front is None:
         lowerCAmelCase__								=			None
       return node.data



     def 					A__			(	self  :		Tuple	):



       """simple docstring"""
       lowerCAmelCase__								=			lowerCAmelCase__								=			None


if __name__ == "__main__":
      from doctest import testmod

      testmod()

