"""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_rembert import RemBertTokenizer
else:
     _a      :		Optional[Any]           =   None

_a      :		Tuple           =   logging.get_logger(__name__)
_a      :		Dict           =   {'vocab_file': 'sentencepiece.model', 'tokenizer_file': 'tokenizer.json'}

_a      :		Tuple           =   {
    'vocab_file': {
        'google/rembert': 'https://huggingface.co/google/rembert/resolve/main/sentencepiece.model',
    },
    'tokenizer_file': {
        'google/rembert': 'https://huggingface.co/google/rembert/resolve/main/tokenizer.json',
    },
}

_a      :		List[str]           =   {
    'google/rembert': 256,
}

_a      :		Dict           =   '▁'
class 						__A							( __snake_case		):
     _UpperCamelCase							:			List[Any]							=		VOCAB_FILES_NAMES
     _UpperCamelCase							:			Any							=		PRETRAINED_VOCAB_FILES_MAP
     _UpperCamelCase							:			Optional[int]							=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     _UpperCamelCase							:			Union[str, Any]							=		RemBertTokenizer






     def __init__(		self				,     a__=None				,     a__=None				,     a__=True				,     a__=True				,     a__=False				,     a__="[CLS]"				,     a__="[SEP]"				,     a__="<unk>"				,     a__="[SEP]"				,     a__="<pad>"				,     a__="[CLS]"				,     a__="[MASK]"				,     **a__				,     ):
       _lowerCAmelCase						:       Optional[Any]  			=     AddedToken(a__				,     lstrip=a__				,     rstrip=a__  ) if isinstance(a__				,     a__  ) else mask_token

       super().__init__(
           a__				,     tokenizer_file=a__				,     do_lower_case=a__				,     remove_space=a__				,     keep_accents=a__				,     bos_token=a__				,     eos_token=a__				,     unk_token=a__				,     sep_token=a__				,     pad_token=a__				,     cls_token=a__				,     mask_token=a__				,     **a__				,     )

       _lowerCAmelCase						:       List[Any]  			=     do_lower_case
       _lowerCAmelCase						:       str  			=     remove_space
       _lowerCAmelCase						:       int  			=     keep_accents
       _lowerCAmelCase						:       Union[str, Any]  			=     vocab_file
       _lowerCAmelCase						:       List[Any]  			=     False if not self.vocab_file else True






     def     __A  (		self				,     a__				,     a__ = None  ):
       _lowerCAmelCase						:       List[Any]  			=     [self.sep_token_id]
       _lowerCAmelCase						:       Tuple  			=     [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     __A  (		self				,     a__				,     a__ = None				,     a__ = False  ):






       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 not None:
         return [1] + ([0] * len(a__  )) + [1] + ([0] * len(a__  )) + [1]
       return [1] + ([0] * len(a__  )) + [1]






     def     __A  (		self				,     a__				,     a__ = None  ):
       _lowerCAmelCase						:       Tuple  			=     [self.sep_token_id]
       _lowerCAmelCase						:       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     __A  (		self				,     a__				,     a__ = None  ):






       if not os.path.isdir(a__  ):
         logger.error("""Vocabulary path ({}) should be a directory""".format(a__  )  )
         return
       _lowerCAmelCase						:       Any  			=     os.path.join(
           a__				,     (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]  )

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

       return (out_vocab_file,)






'''simple docstring'''




import requests
from bsa import BeautifulSoup







def 		lowerCAmelCase_				(   snake_case__		,				snake_case__						):




    '''simple docstring'''



    A       :   str					=						BeautifulSoup(requests.get(snake_case__		,				params=snake_case__						).content		,				'''html.parser'''						)
    A       :   Dict					=						soup.find('''div'''		,				attrs={'''class''': '''gs_ri'''}						)
    A       :   Optional[int]					=						div.find('''div'''		,				attrs={'''class''': '''gs_fl'''}						).find_all('''a'''						)
    return anchors[2].get_text()


if __name__ == "__main__":
      lowercase			:				str    		=			{
          'title': (
              'Precisely geometry controlled microsupercapacitors for ultrahigh areal '
              'capacitance, volumetric capacitance, and energy density'
          ),
          'journal': 'Chem. Mater.',
          'volume': 30,
          'pages': '3979-3990',
          'year': 20_18,
          'hl': 'en',
      }
      print(get_citation('https://scholar.google.com/scholar_lookup', params=params))




