



"""simple docstring"""





def 	__lowerCAmelCase						(		__UpperCamelCase      :			Union[str, Any]					, __UpperCamelCase      :			Union[str, Any]					, __UpperCamelCase      :			Dict					, __UpperCamelCase      :			List[str]    ):


						'''simple docstring'''






						global f  # a global dp table for knapsack
						if f[i][j] < 0:
												if j < wt[i - 1]:
																		snake_case_   : str						=			mf_knapsack(i - 1					, __UpperCamelCase					, __UpperCamelCase					, __UpperCamelCase    )
												else:
																		snake_case_   : Tuple						=			max(
																		    mf_knapsack(i - 1					, __UpperCamelCase					, __UpperCamelCase					, __UpperCamelCase    )					, mf_knapsack(i - 1					, __UpperCamelCase					, __UpperCamelCase					, j - wt[i - 1]    ) + val[i - 1]					, )
												snake_case_   : int						=			val
						return f[i][j]
def 	__lowerCAmelCase						(		__UpperCamelCase      :			Union[str, Any]					, __UpperCamelCase      :			Tuple					, __UpperCamelCase      :			Optional[int]					, __UpperCamelCase      :			List[str]    ):


						'''simple docstring'''






						snake_case_   : 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_:
																								snake_case_   : Optional[Any]						=			max(val[i - 1] + dp[i - 1][w_ - wt[i - 1]]					, dp[i - 1][w_]    )
																		else:
																								snake_case_   : str						=			dp[i - 1][w_]

						return dp[n][w_], dp
def 	__lowerCAmelCase						(		__UpperCamelCase      :			int					, __UpperCamelCase      :			list					, __UpperCamelCase      :			list    ):


						'''simple docstring'''






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

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

						snake_case_			,		snake_case_   : Optional[int]						=			knapsack(__UpperCamelCase					, __UpperCamelCase					, __UpperCamelCase					, __UpperCamelCase    )
						snake_case_   : set						=			set()
						_construct_solution(__UpperCamelCase					, __UpperCamelCase					, __UpperCamelCase					, __UpperCamelCase					, __UpperCamelCase    )

						return optimal_val, example_optional_set
def 	__lowerCAmelCase						(		__UpperCamelCase      :			list					, __UpperCamelCase      :			list					, __UpperCamelCase      :			int					, __UpperCamelCase      :			int					, __UpperCamelCase      :			set    ):


						'''simple docstring'''






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


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





import json
import os
import unittest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin



@require_tokenizers
class    _lowerCAmelCase    (				SCREAMING_SNAKE_CASE__  ,				unittest.TestCase		):





		"""simple docstring"""






		_lowerCamelCase			  =       MgpstrTokenizer
		_lowerCamelCase			  =       False
		_lowerCamelCase			  =       {}
		_lowerCamelCase			  =       False





		def    UpperCAmelCase__							(					self   ) ->						Tuple:







								'''simple docstring'''

								super().setUp()

								# fmt: off
								snake_case_   : Optional[Any]						=			["""[GO]""", """[s]""", """0""", """1""", """2""", """3""", """4""", """5""", """6""", """7""", """8""", """9""", """a""", """b""", """c""", """d""", """e""", """f""", """g""", """h""", """i""", """j""", """k""", """l""", """m""", """n""", """o""", """p""", """q""", """r""", """s""", """t""", """u""", """v""", """w""", """x""", """y""", """z"""]
								# fmt: on
								snake_case_   : str						=			dict(zip(_lowercase							,    range(len(_lowercase   )   )   )   )

								snake_case_   : Tuple						=			os.path.join(self.tmpdirname							,    VOCAB_FILES_NAMES["""vocab_file"""]   )
								with open(self.vocab_file							,    """w"""							,    encoding="""utf-8"""   ) as fp:
														fp.write(json.dumps(_lowercase   ) + """\n"""   )





		def    UpperCAmelCase__							(					self							,    **_lowercase   ) ->						Union[str, Any]:







								'''simple docstring'''

								return MgpstrTokenizer.from_pretrained(self.tmpdirname							,    **_lowercase   )





		def    UpperCAmelCase__							(					self							,    _lowercase   ) ->						Optional[Any]:







								'''simple docstring'''

								snake_case_   : Tuple						=			"""tester"""
								snake_case_   : Tuple						=			"""tester"""
								return input_text, output_text





		@unittest.skip("""MGP-STR always lower cases letters."""   )
		def    UpperCAmelCase__							(					self   ) ->						List[Any]:







								'''simple docstring'''

								pass





		def    UpperCAmelCase__							(					self   ) ->						str:







								'''simple docstring'''

								snake_case_   : Dict						=			self.get_tokenizers(do_lower_case=_lowercase   )
								for tokenizer in tokenizers:
														with self.subTest(f'{tokenizer.__class__.__name__}'   ):
																				snake_case_   : Optional[Any]						=			"""[SPECIAL_TOKEN]"""

																				tokenizer.add_special_tokens({"""cls_token""": special_token}   )
																				snake_case_   : Union[str, Any]						=			tokenizer.encode([special_token]							,    add_special_tokens=_lowercase   )
																				self.assertEqual(len(_lowercase   )							,    1   )

																				snake_case_   : List[Any]						=			tokenizer.decode(_lowercase							,    skip_special_tokens=_lowercase   )
																				self.assertTrue(special_token not in decoded   )





		def    UpperCAmelCase__							(					self   ) ->						Dict:







								'''simple docstring'''

								snake_case_   : List[Any]						=			self.get_tokenizers()
								for tokenizer in tokenizers:
														with self.subTest(f'{tokenizer.__class__.__name__}'   ):
																				snake_case_			,		snake_case_   : Union[str, Any]						=			self.get_input_output_texts(_lowercase   )

																				snake_case_   : List[Any]						=			tokenizer.tokenize(_lowercase   )
																				snake_case_   : Union[str, Any]						=			tokenizer.convert_tokens_to_ids(_lowercase   )
																				snake_case_   : Union[str, Any]						=			tokenizer.encode(_lowercase							,    add_special_tokens=_lowercase   )
																				self.assertListEqual(_lowercase							,    _lowercase   )

																				snake_case_   : List[str]						=			tokenizer.convert_ids_to_tokens(_lowercase   )
																				self.assertNotEqual(len(_lowercase   )							,    0   )
																				snake_case_   : str						=			tokenizer.decode(_lowercase   )
																				self.assertIsInstance(_lowercase							,    _lowercase   )

																				self.assertEqual(text_a.replace(""" """							,    """"""   )							,    _lowercase   )





		@unittest.skip("""MGP-STR tokenizer only handles one sequence."""   )
		def    UpperCAmelCase__							(					self   ) ->						int:







								'''simple docstring'''

								pass





		@unittest.skip("""inputs cannot be pretokenized in MgpstrTokenizer"""   )
		def    UpperCAmelCase__							(					self   ) ->						Any:







								'''simple docstring'''

								pass

