"""simple docstring"""






def 						SCREAMING_SNAKE_CASE					(  __UpperCAmelCase  ,					__UpperCAmelCase  ,					__UpperCAmelCase  ,					__UpperCAmelCase       )							->   Dict:
				global f  # a global dp table for knapsack
				if f[i][j] < 0:
								if j < wt[i - 1]:
												SCREAMING_SNAKE_CASE__		  =				mf_knapsack(i - 1  ,					_SCREAMING_SNAKE_CASE  ,					_SCREAMING_SNAKE_CASE  ,					_SCREAMING_SNAKE_CASE       )
								else:
												SCREAMING_SNAKE_CASE__		  =				max(
												    mf_knapsack(i - 1  ,					_SCREAMING_SNAKE_CASE  ,					_SCREAMING_SNAKE_CASE  ,					_SCREAMING_SNAKE_CASE       )  ,					mf_knapsack(i - 1  ,					_SCREAMING_SNAKE_CASE  ,					_SCREAMING_SNAKE_CASE  ,					j - wt[i - 1]       ) + val[i - 1]  ,					)
								SCREAMING_SNAKE_CASE__		  =				val
				return f[i][j]




def 						SCREAMING_SNAKE_CASE					(  __UpperCAmelCase  ,					__UpperCAmelCase  ,					__UpperCAmelCase  ,					__UpperCAmelCase       )							->   int:
				SCREAMING_SNAKE_CASE__		  =				[[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_:
																SCREAMING_SNAKE_CASE__		  =				max(val[i - 1] + dp[i - 1][w_ - wt[i - 1]]  ,					dp[i - 1][w_]       )
												else:
																SCREAMING_SNAKE_CASE__		  =				dp[i - 1][w_]

				return dp[n][w_], dp




def 						SCREAMING_SNAKE_CASE					(  __UpperCAmelCase  ,					__UpperCAmelCase  ,					__UpperCAmelCase       )							->   Union[str, Any]:



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

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

				SCREAMING_SNAKE_CASE__  ,       SCREAMING_SNAKE_CASE__		  =				knapsack(_SCREAMING_SNAKE_CASE  ,					_SCREAMING_SNAKE_CASE  ,					_SCREAMING_SNAKE_CASE  ,					_SCREAMING_SNAKE_CASE       )
				SCREAMING_SNAKE_CASE__		  =				set()
				_construct_solution(_SCREAMING_SNAKE_CASE  ,					_SCREAMING_SNAKE_CASE  ,					_SCREAMING_SNAKE_CASE  ,					_SCREAMING_SNAKE_CASE  ,					_SCREAMING_SNAKE_CASE       )

				return optimal_val, example_optional_set




def 						SCREAMING_SNAKE_CASE					(  __UpperCAmelCase  ,					__UpperCAmelCase  ,					__UpperCAmelCase  ,					__UpperCAmelCase  ,					__UpperCAmelCase       )							->   Union[str, Any]:



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


if __name__ == "__main__":
						_A   					=    [3, 2, 4, 4]
						_A   					=    [4, 3, 2, 3]
						_A   					=    4
						_A   					=    6
						_A   					=    [[0] * (w + 1)] + [[0] + [-1] * (w + 1) for _ in range(n + 1)]
						_A   					=    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
						_A   					=    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 typing import TYPE_CHECKING

from ...utils import _LazyModule


_A   					=    {'processing_wav2vec2_with_lm': ['Wav2Vec2ProcessorWithLM']}


if TYPE_CHECKING:
						from .processing_wavaveca_with_lm import WavaVecaProcessorWithLM
else:
						import sys

						_A   					=    _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




