





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__							(	)   ->    Union[str, Any]:
  _lowercase						    =			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=snake_case__      ,				default=1      ,				help='Number of TPU cores to use (1 or 8).'  )

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

  return parser.parse_args()

def 				SCREAMING_SNAKE_CASE__							(	)   ->    int:
  _lowercase						    =			parse_args()

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

  # Patch sys.argv
  _lowercase						    =			[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()




'''simple docstring'''

def 	__lowerCamelCase	( lowerCAmelCase_ = 1000000    )     -> int:
		_a	: Optional[int]								=				set(range(3		,     lowerCAmelCase_		,     2    )    )
		primes.add(2    )
		for p in range(3		,     lowerCAmelCase_		,     2    ):
				if p not in primes:
						continue
				primes.difference_update(set(range(p * p		,     lowerCAmelCase_		,     lowerCAmelCase_    )    )    )

		_a	: Tuple								=				[float(lowerCAmelCase_    ) for n in range(limit + 1    )]

		for p in primes:
				for n in range(lowerCAmelCase_		,     limit + 1		,     lowerCAmelCase_    ):
						phi[n] *= 1 - 1 / p

		return int(sum(phi[2:]    )    )


if __name__ == "__main__":
							print(f"""{solution() = }""")




