


"""simple docstring"""
def 				_snake_case      (   __snake_case							:      int						, __snake_case							:      Dict						, __snake_case							:      int						, __snake_case							:      int   ):




   """simple docstring"""







   global f  # a global dp table for knapsack
   if f[i][j] < 0:
      if j < wt[i - 1]:
         _lowerCamelCase	:					Dict   =		mf_knapsack(i - 1						, __snake_case						, __snake_case						, __snake_case   )
      else:
         _lowerCamelCase	:					Union[str, Any]   =		max(
             mf_knapsack(i - 1						, __snake_case						, __snake_case						, __snake_case   )						, mf_knapsack(i - 1						, __snake_case						, __snake_case						, j - wt[i - 1]   ) + val[i - 1]						, )
      _lowerCamelCase	:					List[Any]   =		val
   return f[i][j]

def 				_snake_case      (   __snake_case							:      Dict						, __snake_case							:      Tuple						, __snake_case							:      str						, __snake_case							:      List[Any]   ):




   """simple docstring"""







   _lowerCamelCase	:					Tuple   =		[[0] * (w + 1) for _ in range(n + 1   )]

   for i in range(1						, n + 1   ):
      for w_ in range(1						, w + 1   ):
         if wt[i - 1] <= w_:
            _lowerCamelCase	:					List[str]   =		max(val[i - 1] + dp[i - 1][w_ - wt[i - 1]]						, dp[i - 1][w_]   )
         else:
            _lowerCamelCase	:					Union[str, Any]   =		dp[i - 1][w_]

   return dp[n][w_], dp

def 				_snake_case      (   __snake_case							:      int						, __snake_case							:      list						, __snake_case							:      list   ):




   """simple docstring"""







   if not (isinstance(__snake_case						, (list, tuple)   ) and isinstance(__snake_case						, (list, tuple)   )):
      raise ValueError(
          """Both the weights and values vectors must be either lists or tuples"""   )

   _lowerCamelCase	:					int   =		len(__snake_case   )
   if num_items != len(__snake_case   ):
      _lowerCamelCase	:					List[Any]   =		(
          """The number of weights must be the same as the number of values.\n"""
          F'But got {num_items} weights and {len(__snake_case   )} values'
      )
      raise ValueError(__snake_case   )
   for i in range(__snake_case   ):
      if not isinstance(wt[i]						, __snake_case   ):
         _lowerCamelCase	:					List[Any]   =		(
             """All weights must be integers but got weight of """
             F'type {type(wt[i]   )} at index {i}'
         )
         raise TypeError(__snake_case   )

   _lowerCamelCase   ,    _lowerCamelCase	:					int   =		knapsack(__snake_case						, __snake_case						, __snake_case						, __snake_case   )
   _lowerCamelCase	:					set   =		set()
   _construct_solution(__snake_case						, __snake_case						, __snake_case						, __snake_case						, __snake_case   )

   return optimal_val, example_optional_set

def 				_snake_case      (   __snake_case							:      list						, __snake_case							:      list						, __snake_case							:      int						, __snake_case							:      int						, __snake_case							:      set   ):




   """simple docstring"""







   if i > 0 and j > 0:
      if dp[i - 1][j] == dp[i][j]:
         _construct_solution(__snake_case						, __snake_case						, i - 1						, __snake_case						, __snake_case   )
      else:
         optimal_set.add(__snake_case   )
         _construct_solution(__snake_case						, __snake_case						, i - 1						, j - wt[i - 1]						, __snake_case   )


if __name__ == "__main__":
 UpperCAmelCase				=						[3, 2, 4, 4]
 UpperCAmelCase				=						[4, 3, 2, 3]
 UpperCAmelCase				=						4
 UpperCAmelCase				=						6
 UpperCAmelCase				=						[[0] * (w + 1)] + [[0] + [-1] * (w + 1) for _ in range(n + 1)]
 UpperCAmelCase			,  UpperCAmelCase				=						knapsack(w, wt, val, n)
 print(optimal_solution)
 print(mf_knapsack(n, wt, val, w))  # switched the n and w

 # testing the dynamic programming problem with example
 # the optimal subset for the above example are items 3 and 4
 UpperCAmelCase			,  UpperCAmelCase				=						knapsack_with_example_solution(w, wt, val)
 assert optimal_solution == 8
 assert optimal_subset == {3, 4}
 print("""optimal_value = """, optimal_solution)
 print("""An optimal subset corresponding to the optimal value""", optimal_subset)





"""simple docstring"""
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments

def 				_snake_case      (   ):




   """simple docstring"""







   _lowerCamelCase	:					Any   =		HfArgumentParser(__snake_case   )
   _lowerCamelCase	:					int   =		parser.parse_args_into_dataclasses()[0]
   _lowerCamelCase	:					Dict   =		TensorFlowBenchmark(args=__snake_case   )
   try:
      _lowerCamelCase	:					Optional[int]   =		parser.parse_args_into_dataclasses()[0]
   except ValueError as e:
      _lowerCamelCase	:					Union[str, Any]   =		"""Arg --no_{0} is no longer used, please use --no-{0} instead."""
      _lowerCamelCase	:					List[str]   =		""" """.join(str(__snake_case   ).split(""" """   )[:-1]   )
      _lowerCamelCase	:					Dict   =		""""""
      _lowerCamelCase	:					List[Any]   =		eval(str(__snake_case   ).split(""" """   )[-1]   )
      _lowerCamelCase	:					Tuple   =		[]
      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(__snake_case   )
      if len(__snake_case   ) > 0:
         _lowerCamelCase	:					Tuple   =		full_error_msg + begin_error_msg + str(__snake_case   )
      raise ValueError(__snake_case   )
   benchmark.run()


if __name__ == "__main__":
 main()

