
def        UpperCamelCase    (							lowerCAmelCase__ ,			lowerCAmelCase__ ,			lowerCAmelCase__ ,			lowerCAmelCase__		):
					'''simple docstring'''
					global f  # a global dp table for knapsack
					if f[i][j] < 0:
										if j < wt[i - 1]:
															lowercase							=						mf_knapsack(i - 1 ,			lowerCAmelCase__ ,			lowerCAmelCase__ ,			lowerCAmelCase__		)
										else:
															lowercase							=						max(
															    mf_knapsack(i - 1 ,			lowerCAmelCase__ ,			lowerCAmelCase__ ,			lowerCAmelCase__		) ,			mf_knapsack(i - 1 ,			lowerCAmelCase__ ,			lowerCAmelCase__ ,			j - wt[i - 1]		) + val[i - 1] ,			)
										lowercase							=						val
					return f[i][j]



def        UpperCamelCase    (							lowerCAmelCase__ ,			lowerCAmelCase__ ,			lowerCAmelCase__ ,			lowerCAmelCase__		):
					'''simple docstring'''
					lowercase							=						[[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_:
																				lowercase							=						max(val[i - 1] + dp[i - 1][w_ - wt[i - 1]] ,			dp[i - 1][w_]		)
															else:
																				lowercase							=						dp[i - 1][w_]

					return dp[n][w_], dp



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

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

					lowercase	,						lowercase							=						knapsack(lowerCAmelCase__ ,			lowerCAmelCase__ ,			lowerCAmelCase__ ,			lowerCAmelCase__		)
					lowercase							=						set()
					_construct_solution(lowerCAmelCase__ ,			lowerCAmelCase__ ,			lowerCAmelCase__ ,			lowerCAmelCase__ ,			lowerCAmelCase__		)

					return optimal_val, example_optional_set



def        UpperCamelCase    (							lowerCAmelCase__ ,			lowerCAmelCase__ ,			lowerCAmelCase__ ,			lowerCAmelCase__ ,			lowerCAmelCase__		):
					'''simple docstring'''
					# for the current item i at a maximum weight j to be part of an optimal subset,
					# the optimal value at (i, j) must be greater than the optimal value at (i-1, j).
					# where i - 1 means considering only the previous items at the given maximum weight
					if i > 0 and j > 0:
										if dp[i - 1][j] == dp[i][j]:
															_construct_solution(lowerCAmelCase__ ,			lowerCAmelCase__ ,			i - 1 ,			lowerCAmelCase__ ,			lowerCAmelCase__		)
										else:
															optimal_set.add(lowerCAmelCase__		)
															_construct_solution(lowerCAmelCase__ ,			lowerCAmelCase__ ,			i - 1 ,			j - wt[i - 1] ,			lowerCAmelCase__		)


if __name__ == "__main__":
							lowercase__		:Dict   =    [3, 2, 4, 4]
							lowercase__		:Union[str, Any]   =    [4, 3, 2, 3]
							lowercase__		:int   =    4
							lowercase__		:List[str]   =    6
							lowercase__		:Tuple   =    [[0] * (w + 1)] + [[0] + [-1] * (w + 1) for _ in range(n + 1)]
							lowercase__  ,     lowercase__		:str   =    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
							lowercase__  ,     lowercase__		:int   =    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)






import unittest

from transformers import SPIECE_UNDERLINE, XLNetTokenizer, XLNetTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


lowercase__		:List[Any]   =    get_tests_dir("fixtures/test_sentencepiece.model")







@require_sentencepiece
@require_tokenizers
class 				lowercase		(					SCREAMING_SNAKE_CASE__       ,  unittest.TestCase		):
							lowercase_       :       str       					=XLNetTokenizer
							lowercase_       :       Dict       					=XLNetTokenizerFast
							lowercase_       :       str       					=True
							lowercase_       :       str       					=True




							def  A__      (				self):
												super().setUp()

												# We have a SentencePiece fixture for testing
												lowercase							=						XLNetTokenizer(A__   ,keep_accents=A__)
												tokenizer.sanitize_special_tokens()
												tokenizer.save_pretrained(self.tmpdirname)




							def  A__      (				self):
												lowercase							=						'''<s>'''
												lowercase							=						1

												self.assertEqual(self.get_tokenizer()._convert_token_to_id(A__)   ,A__)
												self.assertEqual(self.get_tokenizer()._convert_id_to_token(A__)   ,A__)




							def  A__      (				self):
												lowercase							=						list(self.get_tokenizer().get_vocab().keys())

												self.assertEqual(vocab_keys[0]   ,'''<unk>''')
												self.assertEqual(vocab_keys[1]   ,'''<s>''')
												self.assertEqual(vocab_keys[-1]   ,'''<eod>''')
												self.assertEqual(len(A__)   ,1_0_0_6)




							def  A__      (				self):
												self.assertEqual(self.get_tokenizer().vocab_size   ,1_0_0_0)




							def  A__      (				self):
												lowercase							=						XLNetTokenizer(A__   ,keep_accents=A__)

												lowercase							=						tokenizer.tokenize('''This is a test''')
												self.assertListEqual(A__   ,['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est'''])

												self.assertListEqual(tokenizer.convert_tokens_to_ids(A__)   ,[2_8_5, 4_6, 1_0, 1_7_0, 3_8_2])

												lowercase							=						tokenizer.tokenize('''I was born in 92000, and this is falsé.''')
												self.assertListEqual(
												    A__   ,[
												        SPIECE_UNDERLINE + '''I''',
												        SPIECE_UNDERLINE + '''was''',
												        SPIECE_UNDERLINE + '''b''',
												        '''or''',
												        '''n''',
												        SPIECE_UNDERLINE + '''in''',
												        SPIECE_UNDERLINE + '''''',
												        '''9''',
												        '''2''',
												        '''0''',
												        '''0''',
												        '''0''',
												        ''',''',
												        SPIECE_UNDERLINE + '''and''',
												        SPIECE_UNDERLINE + '''this''',
												        SPIECE_UNDERLINE + '''is''',
												        SPIECE_UNDERLINE + '''f''',
												        '''al''',
												        '''s''',
												        '''é''',
												        '''.''',
												    ]   ,)
												lowercase							=						tokenizer.convert_tokens_to_ids(A__)
												self.assertListEqual(A__   ,[8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 0, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 0, 4])

												lowercase							=						tokenizer.convert_ids_to_tokens(A__)
												self.assertListEqual(
												    A__   ,[
												        SPIECE_UNDERLINE + '''I''',
												        SPIECE_UNDERLINE + '''was''',
												        SPIECE_UNDERLINE + '''b''',
												        '''or''',
												        '''n''',
												        SPIECE_UNDERLINE + '''in''',
												        SPIECE_UNDERLINE + '''''',
												        '''<unk>''',
												        '''2''',
												        '''0''',
												        '''0''',
												        '''0''',
												        ''',''',
												        SPIECE_UNDERLINE + '''and''',
												        SPIECE_UNDERLINE + '''this''',
												        SPIECE_UNDERLINE + '''is''',
												        SPIECE_UNDERLINE + '''f''',
												        '''al''',
												        '''s''',
												        '''<unk>''',
												        '''.''',
												    ]   ,)




							def  A__      (				self):
												lowercase							=						XLNetTokenizer(A__   ,do_lower_case=A__)
												lowercase							=						tokenizer.tokenize('''I was born in 92000, and this is falsé.''')
												self.assertListEqual(
												    A__   ,[
												        SPIECE_UNDERLINE + '''''',
												        '''i''',
												        SPIECE_UNDERLINE + '''was''',
												        SPIECE_UNDERLINE + '''b''',
												        '''or''',
												        '''n''',
												        SPIECE_UNDERLINE + '''in''',
												        SPIECE_UNDERLINE + '''''',
												        '''9''',
												        '''2''',
												        '''0''',
												        '''0''',
												        '''0''',
												        ''',''',
												        SPIECE_UNDERLINE + '''and''',
												        SPIECE_UNDERLINE + '''this''',
												        SPIECE_UNDERLINE + '''is''',
												        SPIECE_UNDERLINE + '''f''',
												        '''al''',
												        '''se''',
												        '''.''',
												    ]   ,)
												self.assertListEqual(tokenizer.tokenize('''H\u00E9llo''')   ,['''▁he''', '''ll''', '''o'''])




							def  A__      (				self):
												lowercase							=						XLNetTokenizer(A__   ,do_lower_case=A__)
												lowercase							=						tokenizer.tokenize('''I was born in 92000, and this is falsé.''')
												self.assertListEqual(
												    A__   ,[
												        SPIECE_UNDERLINE + '''I''',
												        SPIECE_UNDERLINE + '''was''',
												        SPIECE_UNDERLINE + '''b''',
												        '''or''',
												        '''n''',
												        SPIECE_UNDERLINE + '''in''',
												        SPIECE_UNDERLINE + '''''',
												        '''9''',
												        '''2''',
												        '''0''',
												        '''0''',
												        '''0''',
												        ''',''',
												        SPIECE_UNDERLINE + '''and''',
												        SPIECE_UNDERLINE + '''this''',
												        SPIECE_UNDERLINE + '''is''',
												        SPIECE_UNDERLINE + '''f''',
												        '''al''',
												        '''se''',
												        '''.''',
												    ]   ,)




							@slow
							def  A__      (				self):
												lowercase							=						XLNetTokenizer.from_pretrained('''xlnet-base-cased''')

												lowercase							=						tokenizer.encode('''sequence builders'''   ,add_special_tokens=A__)
												lowercase							=						tokenizer.encode('''multi-sequence build'''   ,add_special_tokens=A__)

												lowercase							=						tokenizer.build_inputs_with_special_tokens(A__)
												lowercase							=						tokenizer.build_inputs_with_special_tokens(A__   ,A__)

												assert encoded_sentence == text + [4, 3]
												assert encoded_pair == text + [4] + text_a + [4, 3]





							@slow
							def  A__      (				self):
												# fmt: off
												lowercase							=						{'''input_ids''': [[1_7, 2_1_4_4_2, 2_7_0, 1_7, 1_0, 1_4_6_4_5, 3_1_8, 3_4, 1_7, 4_5_4_6, 3_1_4_5, 7_8_7, 1_3, 7_7_5_2, 2_2_0_1_8, 2_3, 2_1, 1_7, 4_5_4_6, 3_1_4_5, 7_8_7, 1_3, 3_3_5_2, 1_4_4_3_1, 1_3, 5_5_0_0, 1_1, 1_1_7_6, 5_8_0, 1_3, 1_6_8_1_9, 4_7_9_7, 2_3, 1_7, 1_0, 1_7_1_3_5, 6_5_8, 1_9, 4_5_7, 7_9_3_2, 1_3, 1_8_4, 1_9, 3_1_5_4, 1_7_1_3_5, 6_4_6_8, 1_9, 1_4_0_4, 1_2_2_6_9, 1_9, 4_2_2_9, 5_3_5_6, 1_6_2_6_4, 4_6, 1_9, 1_7, 2_0_5_4_5, 1_0_3_9_5, 9, 9, 9, 1_1, 2_8, 6_4_2_1, 9_5_3_1, 2_0_7_2_9, 1_7, 1_0, 3_5_3, 1_7_0_2_2, 1_1, 2_1, 6_4_2_1, 9_5_3_1, 1_6_9_4_9, 1_7, 1_0, 1_1_5_0_9, 7_5_3, 1_1, 3_3, 9_5, 2_4_2_1, 7_3_8_5, 9_5_6, 1_4_4_3_1, 2_6_2_6, 2_5, 8_4_2, 7_3_8_5, 4_8_3_6, 2_1, 1_4_2_9, 2_2_7_2, 9_8_5_5, 3_1_2_0, 1_6_1, 2_4_7_3_8, 1_9, 1_3_2_0_3, 6_5_8, 2_1_8, 7_8_7, 2_1, 4_3_0, 1_8_4_8_2, 8_4_7, 2_6_3_7, 9, 4, 3], [5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 3_2_2, 2_2_1_7_8, 2_7, 1_0_6_4, 2_2, 9_5_6, 1_3, 1_1_1_0_1, 1_4_2_9, 5_8_5_4, 2_4_3_1_3, 1_8_9_5_3, 4_0, 4_2_2, 2_4_3_6_6, 6_8, 1_7_5_8, 3_7, 1_0_4_8_3, 1_4_2_5_7, 3_1, 2_0_7, 2_6_3, 2_1, 2_0_3, 3_7_7_3, 2_5, 7_1, 9_7_3_5, 9, 4, 3], [5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 3_2, 2_0_4_9, 3_4_4_2, 1_7, 1_3_8_9_4, 3_3_8_0, 2_3, 9_5, 1_8, 1_7_6_3_4, 2_2_8_8, 9, 4, 3]], '''token_type_ids''': [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2], [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2], [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2]], '''attention_mask''': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}  # noqa: E501
												# fmt: on

												self.tokenizer_integration_test_util(
												    expected_encoding=A__   ,model_name='''xlnet-base-cased'''   ,revision='''c841166438c31ec7ca9a106dee7bb312b73ae511'''   ,)




