






import warnings

from .generation import TFGenerationMixin





class 						SCREAMING_SNAKE_CASE				( snake_case					):





							"""simple docstring"""

							warnings.warn(
							    "Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will "
							    "be removed in Transformers v5. Import as `from transformers import TFGenerationMixin` instead."  ,	snake_case  ,	)











def      __A					(     _lowercase					,			_lowercase					,			_lowercase					,			_lowercase ):

					'''simple docstring'''







					global f  # a global dp table for knapsack
					if f[i][j] < 0:
										if j < wt[i - 1]:
															_A								= mf_knapsack(i - 1					,			_lowercase					,			_lowercase					,			_lowercase )
										else:
															_A								= max(
															    mf_knapsack(i - 1					,			_lowercase					,			_lowercase					,			_lowercase )					,			mf_knapsack(i - 1					,			_lowercase					,			_lowercase					,			j - wt[i - 1] ) + val[i - 1]					,			)
										_A								= val
					return f[i][j]




def      __A					(     _lowercase					,			_lowercase					,			_lowercase					,			_lowercase ):

					'''simple docstring'''







					_A								= [[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_:
																				_A								= max(val[i - 1] + dp[i - 1][w_ - wt[i - 1]]					,			dp[i - 1][w_] )
															else:
																				_A								= dp[i - 1][w_]

					return dp[n][w_], dp




def      __A					(     _lowercase					,			_lowercase					,			_lowercase ):

					'''simple docstring'''







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

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

					_A							,_A								= knapsack(_lowercase					,			_lowercase					,			_lowercase					,			_lowercase )
					_A								= set()
					_construct_solution(_lowercase					,			_lowercase					,			_lowercase					,			_lowercase					,			_lowercase )

					return optimal_val, example_optional_set




def      __A					(     _lowercase					,			_lowercase					,			_lowercase					,			_lowercase					,			_lowercase ):

					'''simple docstring'''







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


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 ,  __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 ,  __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)



