





"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
  from .tokenization_big_bird import BigBirdTokenizer
else:
  lowerCamelCase_								=		None

lowerCamelCase_								=		logging.get_logger(__name__)
lowerCamelCase_								=		{"vocab_file": "spiece.model", "tokenizer_file": "tokenizer.json"}

lowerCamelCase_								=		{
    "vocab_file": {
        "google/bigbird-roberta-base": "https://huggingface.co/google/bigbird-roberta-base/resolve/main/spiece.model",
        "google/bigbird-roberta-large": (
            "https://huggingface.co/google/bigbird-roberta-large/resolve/main/spiece.model"
        ),
        "google/bigbird-base-trivia-itc": (
            "https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/spiece.model"
        ),
    },
    "tokenizer_file": {
        "google/bigbird-roberta-base": (
            "https://huggingface.co/google/bigbird-roberta-base/resolve/main/tokenizer.json"
        ),
        "google/bigbird-roberta-large": (
            "https://huggingface.co/google/bigbird-roberta-large/resolve/main/tokenizer.json"
        ),
        "google/bigbird-base-trivia-itc": (
            "https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/tokenizer.json"
        ),
    },
}

lowerCamelCase_								=		{
    "google/bigbird-roberta-base": 4_0_9_6,
    "google/bigbird-roberta-large": 4_0_9_6,
    "google/bigbird-base-trivia-itc": 4_0_9_6,
}


lowerCamelCase_								=		"▁"






class 					_SCREAMING_SNAKE_CASE(   _UpperCAmelCase  ):
       SCREAMING_SNAKE_CASE_   :      Optional[int]							=  VOCAB_FILES_NAMES
       SCREAMING_SNAKE_CASE_   :      Optional[int]							=  PRETRAINED_VOCAB_FILES_MAP
       SCREAMING_SNAKE_CASE_   :      Union[str, Any]							=  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       SCREAMING_SNAKE_CASE_   :      List[Any]							=  BigBirdTokenizer
       SCREAMING_SNAKE_CASE_   :      int							=  ['''input_ids''', '''attention_mask''']
       SCREAMING_SNAKE_CASE_   :      Optional[Any]							=  []




       def __init__(						self		,SCREAMING_SNAKE_CASE__=None		,SCREAMING_SNAKE_CASE__=None		,SCREAMING_SNAKE_CASE__="<unk>"		,SCREAMING_SNAKE_CASE__="<s>"		,SCREAMING_SNAKE_CASE__="</s>"		,SCREAMING_SNAKE_CASE__="<pad>"		,SCREAMING_SNAKE_CASE__="[SEP]"		,SCREAMING_SNAKE_CASE__="[MASK]"		,SCREAMING_SNAKE_CASE__="[CLS]"		,**SCREAMING_SNAKE_CASE__		,)			->      Any:





             """simple docstring"""






             __SCREAMING_SNAKE_CASE   :Any						=  AddedToken(lowercase_		,lstrip=lowercase_		,rstrip=lowercase_							) if isinstance(lowercase_		,lowercase_							) else bos_token
             __SCREAMING_SNAKE_CASE   :Tuple						=  AddedToken(lowercase_		,lstrip=lowercase_		,rstrip=lowercase_							) if isinstance(lowercase_		,lowercase_							) else eos_token
             __SCREAMING_SNAKE_CASE   :List[Any]						=  AddedToken(lowercase_		,lstrip=lowercase_		,rstrip=lowercase_							) if isinstance(lowercase_		,lowercase_							) else unk_token
             __SCREAMING_SNAKE_CASE   :List[str]						=  AddedToken(lowercase_		,lstrip=lowercase_		,rstrip=lowercase_							) if isinstance(lowercase_		,lowercase_							) else pad_token
             __SCREAMING_SNAKE_CASE   :Any						=  AddedToken(lowercase_		,lstrip=lowercase_		,rstrip=lowercase_							) if isinstance(lowercase_		,lowercase_							) else cls_token
             __SCREAMING_SNAKE_CASE   :Tuple						=  AddedToken(lowercase_		,lstrip=lowercase_		,rstrip=lowercase_							) if isinstance(lowercase_		,lowercase_							) else sep_token

             # Mask token behave like a normal word, i.e. include the space before it
             __SCREAMING_SNAKE_CASE   :int						=  AddedToken(lowercase_		,lstrip=lowercase_		,rstrip=lowercase_							) if isinstance(lowercase_		,lowercase_							) else mask_token

             super().__init__(
                 lowercase_		,tokenizer_file=lowercase_		,bos_token=lowercase_		,eos_token=lowercase_		,unk_token=lowercase_		,sep_token=lowercase_		,pad_token=lowercase_		,cls_token=lowercase_		,mask_token=lowercase_		,**lowercase_		,)

             __SCREAMING_SNAKE_CASE   :str						=  vocab_file
             __SCREAMING_SNAKE_CASE   :List[Any]						=  False if not self.vocab_file else True




       def     _UpperCamelCase     (						self		,SCREAMING_SNAKE_CASE__		,SCREAMING_SNAKE_CASE__ = None							)			->      List[int]:





             """simple docstring"""






             __SCREAMING_SNAKE_CASE   :int						=  [self.sep_token_id]
             __SCREAMING_SNAKE_CASE   :Dict						=  [self.cls_token_id]
             if token_ids_a is None:
                   return cls + token_ids_a + sep
             return cls + token_ids_a + sep + token_ids_a + sep




       def     _UpperCamelCase     (						self		,SCREAMING_SNAKE_CASE__		,SCREAMING_SNAKE_CASE__ = None		,SCREAMING_SNAKE_CASE__ = False							)			->      List[int]:





             """simple docstring"""






             if already_has_special_tokens:
                   if token_ids_a is not None:
                         raise ValueError(
                             '''You should not supply a second sequence if the provided sequence of '''
                             '''ids is already formatted with special tokens for the model.'''							)
                   return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

             if token_ids_a is None:
                   return [1] + ([0] * len(lowercase_							)) + [1]
             return [1] + ([0] * len(lowercase_							)) + [1] + ([0] * len(lowercase_							)) + [1]




       def     _UpperCamelCase     (						self		,SCREAMING_SNAKE_CASE__		,SCREAMING_SNAKE_CASE__ = None							)			->      List[int]:





             """simple docstring"""






             __SCREAMING_SNAKE_CASE   :Tuple						=  [self.sep_token_id]
             __SCREAMING_SNAKE_CASE   :Dict						=  [self.cls_token_id]

             if token_ids_a is None:
                   return len(cls + token_ids_a + sep							) * [0]
             return len(cls + token_ids_a + sep							) * [0] + len(token_ids_a + sep							) * [1]




       def     _UpperCamelCase     (						self		,SCREAMING_SNAKE_CASE__		,SCREAMING_SNAKE_CASE__ = None							)			->      Tuple[str]:





             """simple docstring"""






             if not self.can_save_slow_tokenizer:
                   raise ValueError(
                       '''Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '''
                       '''tokenizer.'''							)

             if not os.path.isdir(lowercase_							):
                   logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''							)
                   return
             __SCREAMING_SNAKE_CASE   :Optional[int]						=  os.path.join(
                 lowercase_		,(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']							)

             if os.path.abspath(self.vocab_file							) != os.path.abspath(lowercase_							):
                   copyfile(self.vocab_file		,lowercase_							)

             return (out_vocab_file,)


def 						_snake_case(    SCREAMING_SNAKE_CASE__			:	Union[str, Any]    ,			SCREAMING_SNAKE_CASE__			:	Tuple    ,			SCREAMING_SNAKE_CASE__			:	Union[str, Any]    ,			SCREAMING_SNAKE_CASE__			:	Any      )							->      Optional[int]:





    '''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    ,			SCREAMING_SNAKE_CASE__    ,			SCREAMING_SNAKE_CASE__    ,			SCREAMING_SNAKE_CASE__      )
        else:
            A__          =   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]    ,			)
        A__          =   val
    return f[i][j]
def 						_snake_case(    SCREAMING_SNAKE_CASE__			:	Tuple    ,			SCREAMING_SNAKE_CASE__			:	Optional[int]    ,			SCREAMING_SNAKE_CASE__			:	Optional[int]    ,			SCREAMING_SNAKE_CASE__			:	Optional[int]      )							->      Tuple:





    '''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 						_snake_case(    SCREAMING_SNAKE_CASE__			:	int    ,			SCREAMING_SNAKE_CASE__			:	list    ,			SCREAMING_SNAKE_CASE__			:	list      )							->      Union[str, Any]:





    '''simple docstring'''






    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'      )

    A__          =   len(SCREAMING_SNAKE_CASE__      )
    if num_items != len(SCREAMING_SNAKE_CASE__      ):
        A__          =   (
            '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__      ):
            A__          =   (
                'All weights must be integers but got weight of '
                f'type {type(wt[i]      )} at index {i}'
            )
            raise TypeError(SCREAMING_SNAKE_CASE__      )

    A__      ,						A__          =   knapsack(SCREAMING_SNAKE_CASE__    ,			SCREAMING_SNAKE_CASE__    ,			SCREAMING_SNAKE_CASE__    ,			SCREAMING_SNAKE_CASE__      )
    A__          =   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 						_snake_case(    SCREAMING_SNAKE_CASE__			:	list    ,			SCREAMING_SNAKE_CASE__			:	list    ,			SCREAMING_SNAKE_CASE__			:	int    ,			SCREAMING_SNAKE_CASE__			:	int    ,			SCREAMING_SNAKE_CASE__			:	set      )							->      Optional[int]:





    '''simple docstring'''






    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__":
     lowercase_       		=  [3, 2, 4, 4]
     lowercase_       		=  [4, 3, 2, 3]
     lowercase_       		=  4
     lowercase_       		=  6
     lowercase_       		=  [[0] * (w + 1)] + [[0] + [-1] * (w + 1) for _ in range(n + 1)]
     lowercase_		,			lowercase_       		=  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_       		=  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)

