


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

import torch_xla.distributed.xla_multiprocessing as xmp




def     UpperCamelCase    (      )					->							Optional[int]:
					'''simple docstring'''





					lowercase_       :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=_a       ,		default=1       ,		help='''Number of TPU cores to use (1 or 8).'''		)

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

					return parser.parse_args()




def     UpperCamelCase    (      )					->							Dict:
					'''simple docstring'''





					lowercase_       :Optional[int]     =       parse_args()

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

					# Patch sys.argv
					lowercase_       :Optional[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()





def     UpperCamelCase    (      _a       ,		_a       ,		_a		)					->							int:
     '''simple docstring'''





     def count_of_possible_combinations(_a		) -> int:
          if target < 0:
               return 0
          if target == 0:
               return 1
          return sum(count_of_possible_combinations(target - item		) for item in array		)

     return count_of_possible_combinations(_a		)




def     UpperCamelCase    (      _a       ,		_a       ,		_a		)					->							int:
     '''simple docstring'''





     def count_of_possible_combinations_with_dp_array(
         _a       ,		_a		) -> int:
          if target < 0:
               return 0
          if target == 0:
               return 1
          if dp_array[target] != -1:
               return dp_array[target]
          lowercase_       :Optional[int]     =       sum(
              count_of_possible_combinations_with_dp_array(target - item       ,		_a		)
              for item in array		)
          lowercase_       :List[Any]     =       answer
          return answer

     lowercase_       :Dict     =       [-1] * (target + 1)
     return count_of_possible_combinations_with_dp_array(_a       ,		_a		)




def     UpperCamelCase    (      _a       ,		_a       ,		_a		)					->							int:
     '''simple docstring'''





     lowercase_       :Optional[int]     =       [0] * (target + 1)
     lowercase_       :int     =       1

     for i in range(1       ,		target + 1		):
          for j in range(_a		):
               if i - array[j] >= 0:
                    dp_array[i] += dp_array[i - array[j]]

     return dp_array[target]


if __name__ == "__main__":
   import doctest

   doctest.testmod()
   SCREAMING_SNAKE_CASE       :		Optional[Any]         =				3
   SCREAMING_SNAKE_CASE       :		Tuple         =				5
   SCREAMING_SNAKE_CASE       :		List[Any]         =				[1, 2, 5]
   print(combination_sum_iv(n, array, target))

