

'''simple docstring'''



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

import torch_xla.distributed.xla_multiprocessing as xmp
def 						__lowerCamelCase	(       )	->							List[Any]:






						"""simple docstring"""





						A__					:       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=__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 						__lowerCamelCase	(       )	->							Dict:






						"""simple docstring"""





						A__					:       Any     =parse_args()

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

						# Patch sys.argv
						A__					:       str     =[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'''



from __future__ import annotations
def 						__lowerCamelCase	(       __snake_case					:		list[int]	)	->							bool:






						"""simple docstring"""





						return len(set(__snake_case	)	) == len(__snake_case	)


if __name__ == "__main__":
		import doctest

		doctest.testmod()

