


'''simple docstring'''
def       a				(      __a			, __a			, __a			, __a       )  ->     Optional[Any]:



					'''simple docstring'''






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


def       a				(      __a			, __a			, __a			, __a       )  ->     Optional[Any]:



					'''simple docstring'''






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

					return dp[n][w_], dp


def       a				(      __a			, __a			, __a       )  ->     Optional[Any]:



					'''simple docstring'''






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

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

					UpperCamelCase__ ,    UpperCamelCase__       :Optional[int]							 =			knapsack(__a			, __a			, __a			, __a       )
					UpperCamelCase__       :List[str]							 =			set()
					_construct_solution(__a			, __a			, __a			, __a			, __a       )

					return optimal_val, example_optional_set


def       a				(      __a			, __a			, __a			, __a			, __a       )  ->     Optional[Any]:



					'''simple docstring'''






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


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

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__snake_case											=					logging.get_logger(__name__)

__snake_case											=					{
    '''distilbert-base-uncased''': '''https://huggingface.co/distilbert-base-uncased/resolve/main/config.json''',
    '''distilbert-base-uncased-distilled-squad''': (
        '''https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/config.json'''
    ),
    '''distilbert-base-cased''': '''https://huggingface.co/distilbert-base-cased/resolve/main/config.json''',
    '''distilbert-base-cased-distilled-squad''': (
        '''https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/config.json'''
    ),
    '''distilbert-base-german-cased''': '''https://huggingface.co/distilbert-base-german-cased/resolve/main/config.json''',
    '''distilbert-base-multilingual-cased''': (
        '''https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/config.json'''
    ),
    '''distilbert-base-uncased-finetuned-sst-2-english''': (
        '''https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english/resolve/main/config.json'''
    ),
}
class        lowercase     (							A__ ):

		"""simple docstring"""

		_a   			=    'distilbert'
		_a   			=    {
		    'hidden_size': 'dim',
		    'num_attention_heads': 'n_heads',
		    'num_hidden_layers': 'n_layers',
		}




		def __init__(		self   ,       UpperCamelCase_=30522   ,       UpperCamelCase_=512   ,       UpperCamelCase_=False   ,       UpperCamelCase_=6   ,       UpperCamelCase_=12   ,       UpperCamelCase_=768   ,       UpperCamelCase_=4 * 768   ,       UpperCamelCase_=0.1   ,       UpperCamelCase_=0.1   ,       UpperCamelCase_="gelu"   ,       UpperCamelCase_=0.02   ,       UpperCamelCase_=0.1   ,       UpperCamelCase_=0.2   ,       UpperCamelCase_=0   ,       **UpperCamelCase_   ,       ):

							'''simple docstring'''


							UpperCamelCase__       :List[Any]							 =			vocab_size
							UpperCamelCase__       :Dict							 =			max_position_embeddings
							UpperCamelCase__       :str							 =			sinusoidal_pos_embds
							UpperCamelCase__       :Any							 =			n_layers
							UpperCamelCase__       :str							 =			n_heads
							UpperCamelCase__       :Tuple							 =			dim
							UpperCamelCase__       :str							 =			hidden_dim
							UpperCamelCase__       :Dict							 =			dropout
							UpperCamelCase__       :int							 =			attention_dropout
							UpperCamelCase__       :Optional[Any]							 =			activation
							UpperCamelCase__       :Optional[int]							 =			initializer_range
							UpperCamelCase__       :Union[str, Any]							 =			qa_dropout
							UpperCamelCase__       :Dict							 =			seq_classif_dropout
							super().__init__(**UpperCamelCase_   ,       pad_token_id=UpperCamelCase_							)



class        lowercase     (							A__ ):

		"""simple docstring"""

		@property
		def    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							if self.task == "multiple-choice":
												UpperCamelCase__       :str							 =			{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
							else:
												UpperCamelCase__       :str							 =			{0: '''batch''', 1: '''sequence'''}
							return OrderedDict(
							    [
							        ('''input_ids''', dynamic_axis),
							        ('''attention_mask''', dynamic_axis),
							    ]							)