





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			(      ):
       _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=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     SCREAMING_SNAKE_CASE			(      ):
       _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(lowercase__					)

       # 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()













from __future__ import annotations

import math


def     SCREAMING_SNAKE_CASE			(      lowerCAmelCase					):

       if 1 < number < 4:
              # 2 and 3 are primes
              return True
       elif number < 2 or number % 2 == 0 or number % 3 == 0:
              # Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
              return False

       # All primes number are in format of 6k +/- 1
       for i in range(5    ,       int(math.sqrt(lowerCAmelCase					) + 1					)    ,       6					):
              if number % i == 0 or number % (i + 2) == 0:
                     return False
       return True


lowercase    : Tuple    	=  [num for num in range(3, 10_0001, 2) if not is_prime(num)]


def     SCREAMING_SNAKE_CASE			(      lowerCAmelCase					):
       if not isinstance(lowerCAmelCase    ,       lowerCAmelCase					):
              raise ValueError('''n must be an integer'''					)
       if n <= 0:
              raise ValueError('''n must be >= 0'''					)

       _UpperCamelCase              =						[]
       for num in range(len(lowerCAmelCase					)					):
              _UpperCamelCase              =						0
              while 2 * i * i <= odd_composites[num]:
                     _UpperCamelCase              =						odd_composites[num] - 2 * i * i
                     if is_prime(lowerCAmelCase					):
                            break
                     i += 1
              else:
                     list_nums.append(odd_composites[num]					)
                     if len(lowerCAmelCase					) == n:
                            return list_nums

       return []


def     SCREAMING_SNAKE_CASE			(      ):
       return compute_nums(1					)[0]


if __name__ == "__main__":
       print(F'''{solution() = }''')






