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_					(						)					->     str:
							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=_UpperCAmelCase       ,  default=1       ,  help='''Number of TPU cores to use (1 or 8).'''							)

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

							return parser.parse_args()





def        SCREAMING_SNAKE_CASE_					(						)					->     Optional[int]:
							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(_UpperCAmelCase							)

							# 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()




lowercase__      :    dict[str, float]          =     {
    "kilogram": 1,
    "gram": pow(1_0, 3),
    "milligram": pow(1_0, 6),
    "metric-ton": pow(1_0, -3),
    "long-ton": 0.0_0_0_9_8_4_2_0_7_3,
    "short-ton": 0.0_0_1_1_0_2_3_1_2_2,
    "pound": 2.2_0_4_6_2_4_4_2_0_2,
    "stone": 0.1_5_7_4_7_3_1_7_2_8,
    "ounce": 3_5.2_7_3_9_9_0_7_2_3,
    "carrat": 5_0_0_0,
    "atomic-mass-unit": 6.0_22_13_66_52e26,
}

lowercase__      :    dict[str, float]          =     {
    "kilogram": 1,
    "gram": pow(1_0, -3),
    "milligram": pow(1_0, -6),
    "metric-ton": pow(1_0, 3),
    "long-ton": 1_0_1_6.0_4_6_0_8,
    "short-ton": 9_0_7.1_8_4,
    "pound": 0.4_5_3_5_9_2,
    "stone": 6.3_5_0_2_9,
    "ounce": 0.0_2_8_3_4_9_5,
    "carrat": 0.0_0_0_2,
    "atomic-mass-unit": 1.6_60_54_01_99e-27,
}

def        SCREAMING_SNAKE_CASE_					(						snake_case__       ,  snake_case__       ,  snake_case__							)					->     float:
							if to_type not in KILOGRAM_CHART or from_type not in WEIGHT_TYPE_CHART:
														lowerCAmelCase     		=		(
														    f"Invalid 'from_type' or 'to_type' value: {from_type!r}, {to_type!r}\n"
														    f"Supported values are: {', '.join(snake_case__							)}"
														)
														raise ValueError(snake_case__							)
							return value * KILOGRAM_CHART[to_type] * WEIGHT_TYPE_CHART[from_type]


if __name__ == "__main__":
	import doctest

	doctest.testmod()



