






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:
   A_						:						int						      =					None

A_						:						Tuple						      =					logging.get_logger(__name__)
A_						:						Union[str, Any]						      =					{'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}

A_						:						str						      =					{
    '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'
        ),
    },
}

A_						:						Optional[Any]						      =					{
    'google/bigbird-roberta-base': 4096,
    'google/bigbird-roberta-large': 4096,
    'google/bigbird-base-trivia-itc': 4096,
}


A_						:						List[str]						      =					'▁'




class 							_lowerCAmelCase(			UpperCamelCase_   ):





       """simple docstring"""







       a							:						List[str]										=VOCAB_FILES_NAMES
       a							:						Union[str, Any]										=PRETRAINED_VOCAB_FILES_MAP
       a							:						str										=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       a							:						Tuple										=BigBirdTokenizer
       a							:						Optional[Any]										=["""input_ids""", """attention_mask"""]
       a							:						List[int]										=[]





       def __init__(   self    ,     _lowerCamelCase=None    ,     _lowerCamelCase=None    ,     _lowerCamelCase="<unk>"    ,     _lowerCamelCase="<s>"    ,     _lowerCamelCase="</s>"    ,     _lowerCamelCase="<pad>"    ,     _lowerCamelCase="[SEP]"    ,     _lowerCamelCase="[MASK]"    ,     _lowerCamelCase="[CLS]"    ,     **_lowerCamelCase    ,     ):
         UpperCamelCase_:   Optional[int]        =							AddedToken(a__    ,     lstrip=a__    ,     rstrip=a__				) if isinstance(a__    ,     a__				) else bos_token
         UpperCamelCase_:   int        =							AddedToken(a__    ,     lstrip=a__    ,     rstrip=a__				) if isinstance(a__    ,     a__				) else eos_token
         UpperCamelCase_:   List[str]        =							AddedToken(a__    ,     lstrip=a__    ,     rstrip=a__				) if isinstance(a__    ,     a__				) else unk_token
         UpperCamelCase_:   List[str]        =							AddedToken(a__    ,     lstrip=a__    ,     rstrip=a__				) if isinstance(a__    ,     a__				) else pad_token
         UpperCamelCase_:   Tuple        =							AddedToken(a__    ,     lstrip=a__    ,     rstrip=a__				) if isinstance(a__    ,     a__				) else cls_token
         UpperCamelCase_:   str        =							AddedToken(a__    ,     lstrip=a__    ,     rstrip=a__				) if isinstance(a__    ,     a__				) else sep_token

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

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

         UpperCamelCase_:   Tuple        =							vocab_file
         UpperCamelCase_:   List[str]        =							False if not self.vocab_file else True





       def      _a       (   self    ,     _lowerCamelCase    ,     _lowerCamelCase = None				):
         UpperCamelCase_:   Optional[Any]        =							[self.sep_token_id]
         UpperCamelCase_:   List[str]        =							[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    ,     _lowerCamelCase    ,     _lowerCamelCase = None    ,     _lowerCamelCase = 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 None:
           return [1] + ([0] * len(a__				)) + [1]
         return [1] + ([0] * len(a__				)) + [1] + ([0] * len(a__				)) + [1]





       def      _a       (   self    ,     _lowerCamelCase    ,     _lowerCamelCase = None				):
         UpperCamelCase_:   Dict        =							[self.sep_token_id]
         UpperCamelCase_:   List[str]        =							[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    ,     _lowerCamelCase    ,     _lowerCamelCase = None				):

         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(a__				):
           logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''				)
           return
         UpperCamelCase_:   int        =							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 sys
import webbrowser

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

if __name__ == "__main__":
     print("""Googling.....""")
     snake_case									=    """https://www.google.com/search?q=""" + """ """.join(sys.argv[1:])
     snake_case									=    requests.get(url, headers={"""UserAgent""": UserAgent().random})
     # res.raise_for_status()
     with open("""project1a.html""", """wb""") as out_file:  # only for knowing the class
          for data in res.iter_content(1_00_00):
               out_file.write(data)
     snake_case									=    BeautifulSoup(res.text, """html.parser""")
     snake_case									=    list(soup.select(""".eZt8xd"""))[:5]

     print(len(links))
     for link in links:
          if link.text == "Maps":
               webbrowser.open(link.get("""href"""))
          else:
               webbrowser.open(f'https://google.com{link.get("href")}')





