


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]:
				lowerCAmelCase_	: 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=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]:
				lowerCAmelCase_	: Tuple      			=			parse_args()

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

				# Patch sys.argv
				lowerCAmelCase_	: Union[str, 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()



import math







class 			snake_case__:







						'''simple docstring'''




						def __init__(			self				,  __lowercase				,  __lowercase				,  __lowercase							)   ->      Tuple:
										lowerCAmelCase_	: List[str]      			=			x
										lowerCAmelCase_	: Dict      			=			y
										lowerCAmelCase_	: List[Any]      			=			z




						def __repr__(			self							)   ->      str:
										return f"""Point({self.x}, {self.y}, {self.z})"""






def      lowerCAmelCase	(						lowerCAmelCase_	,				lowerCAmelCase_	)->	float:
				return math.sqrt(abs((b.x - a.x) ** 2 + (b.y - a.y) ** 2 + (b.z - a.z) ** 2	)	)


if __name__ == "__main__":
						import doctest

						doctest.testmod()