




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

import torch_xla.distributed.xla_multiprocessing as xmp



def   lowerCAmelCase						(						):




 """simple docstring"""







 UpperCAmelCase__								=  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						(						):




 """simple docstring"""







 UpperCAmelCase__								=  parse_args()

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

 # Patch sys.argv
 UpperCAmelCase__								=  [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()











_lowerCAmelCase  :				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,
}

_lowerCAmelCase  :				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   lowerCAmelCase						(						_lowerCAmelCase							:				str  ,							_lowerCAmelCase							:				str  ,							_lowerCAmelCase							:				float		):




 """simple docstring"""







 if to_type not in KILOGRAM_CHART or from_type not in WEIGHT_TYPE_CHART:
  UpperCAmelCase__								=  (
      F'''Invalid \'from_type\' or \'to_type\' value: {from_type!r}, {to_type!r}\n'''
      F'''Supported values are: {", ".join(_lowerCAmelCase		)}'''
  )
  raise ValueError(_lowerCAmelCase		)
 return value * KILOGRAM_CHART[to_type] * WEIGHT_TYPE_CHART[from_type]


if __name__ == "__main__":
  import doctest

  doctest.testmod()





