

"""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						(					):
 '''simple docstring'''





 UpperCAmelCase__					:  Union[str, Any]					   =					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=_lowercase							,    default=1							,    help="""Number of TPU cores to use (1 or 8)."""      )

 # positional
 parser.add_argument(
     """training_script"""							,    type=_lowercase							,    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=_lowercase      )

 return parser.parse_args()
def   lowerCAmelCase						(					):
 '''simple docstring'''





 UpperCAmelCase__					:  List[Any]					   =					parse_args()

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

 # Patch sys.argv
 UpperCAmelCase__					:  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"""




__UpperCAmelCase =				'Tobias Carryer'

from time import time







class      __lowercase			:

  def __init__(  self		:			Union[str, Any]					,A		:			Dict					,A		:			Optional[int]					,A		:			Union[str, Any]					,A		:			int=int(time()    )    ):  # noqa: B008






   '''simple docstring'''
   UpperCAmelCase__					:  int					   =					multiplier
   UpperCAmelCase__					:  Union[str, Any]					   =					increment
   UpperCAmelCase__					:  Dict					   =					modulo
   UpperCAmelCase__					:  Tuple					   =					seed




  def    __lowercase       (  self		:			Dict    ):






   '''simple docstring'''
   UpperCAmelCase__					:  Any					   =					(self.multiplier * self.seed + self.increment) % self.modulo
   return self.seed


if __name__ == "__main__":
      # Show the LCG in action.
      __UpperCAmelCase =				LinearCongruentialGenerator(166_4525, 10_1390_4223, 2 << 31)
      while True:
            print(lcg.next_number())





