


from __future__ import annotations







def        SCREAMING_SNAKE_CASE_						(			__A :			list[int]  ,    __A :			int				)	->		list[list[int]]:

       """simple docstring"""

       a_					:		list[list[int]]							=  []
       a_					:		list[int]							=  []
       a_					:		Dict							=  0
       a_					:		Optional[int]							=  sum(__A				)
       create_state_space_tree(__A  ,    __A  ,    __A  ,    __A  ,    __A  ,    __A				)
       return result







def        SCREAMING_SNAKE_CASE_						(			__A :			list[int]  ,    __A :			int  ,    __A :			int  ,    __A :			list[int]  ,    __A :			list[list[int]]  ,    __A :			int  ,    )	->		None:

       """simple docstring"""

       if sum(__A				) > max_sum or (remaining_nums_sum + sum(__A				)) < max_sum:
              return
       if sum(__A				) == max_sum:
              result.append(__A				)
              return
       for index in range(__A  ,    len(__A				)				):
              create_state_space_tree(
                  __A  ,    __A  ,    index + 1  ,    [*path, nums[index]]  ,    __A  ,    remaining_nums_sum - nums[index]  ,    )
UpperCAmelCase_      : str  					=       [3, 34, 4, 12, 5, 2]
UpperCAmelCase_      : Optional[Any]  					=       9
UpperCAmelCase_      : str  					=       generate_sum_of_subsets_soln(nums, max_sum)
print(*result)






from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments







def        SCREAMING_SNAKE_CASE_						(			)	->		Any:

       """simple docstring"""

       a_					:		Optional[Any]							=  HfArgumentParser(__A				)
       a_					:		Optional[int]							=  parser.parse_args_into_dataclasses()[0]
       a_					:		List[Any]							=  TensorFlowBenchmark(args=__A				)
       try:
              a_					:		List[str]							=  parser.parse_args_into_dataclasses()[0]
       except ValueError as e:
              a_					:		Dict							=  'Arg --no_{0} is no longer used, please use --no-{0} instead.'
              a_					:		Dict							=  ' '.join(str(__A				).split(' '				)[:-1]				)
              a_					:		int							=  ''
              a_					:		int							=  eval(str(__A				).split(' '				)[-1]				)
              a_					:		Any							=  []
              for arg in depreciated_args:
                     # arg[2:] removes '--'
                     if arg[2:] in TensorFlowBenchmark.deprecated_args:
                            # arg[5:] removes '--no_'
                            full_error_msg += arg_error_msg.format(arg[5:]				)
                     else:
                            wrong_args.append(__A				)
              if len(__A				) > 0:
                     a_					:		str							=  full_error_msg + begin_error_msg + str(__A				)
              raise ValueError(__A				)
       benchmark.run()


if __name__ == "__main__":
   main()


