


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

import torch_xla.distributed.xla_multiprocessing as xmp

def 		__lowerCAmelCase   (							)    ->				Optional[Any]:






      '''simple docstring'''

      lowerCamelCase__:						int							   = 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=_lowerCAmelCase       ,			default=1       ,			help="""Number of TPU cores to use (1 or 8)."""		)

      # positional
      parser.add_argument(
          """training_script"""       ,			type=_lowerCAmelCase       ,			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=_lowerCAmelCase		)

      return parser.parse_args()

def 		__lowerCAmelCase   (							)    ->				List[str]:






      '''simple docstring'''

      lowerCamelCase__:						Dict							   = parse_args()

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

      # Patch sys.argv
      lowerCamelCase__:						Dict							   = [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





def 						_lowerCAmelCase							(     _lowerCAmelCase			)    ->						list[int]:


						'''simple docstring'''






						__snake_case				=		2
						__snake_case				=		[]
						while i * i <= n:
												if n % i:
																		i += 1
												else:
																		n //= i
																		factors.append(_lowerCAmelCase			)
						if n > 1:
												factors.append(_lowerCAmelCase			)
						return factors


if __name__ == "__main__":
	import doctest

	doctest.testmod()





