






'''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_albert import AlbertTokenizer
else:
  a_ 		=       None

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

a_ 		=       {
    '''vocab_file''': {
        '''albert-base-v1''': '''https://huggingface.co/albert-base-v1/resolve/main/spiece.model''',
        '''albert-large-v1''': '''https://huggingface.co/albert-large-v1/resolve/main/spiece.model''',
        '''albert-xlarge-v1''': '''https://huggingface.co/albert-xlarge-v1/resolve/main/spiece.model''',
        '''albert-xxlarge-v1''': '''https://huggingface.co/albert-xxlarge-v1/resolve/main/spiece.model''',
        '''albert-base-v2''': '''https://huggingface.co/albert-base-v2/resolve/main/spiece.model''',
        '''albert-large-v2''': '''https://huggingface.co/albert-large-v2/resolve/main/spiece.model''',
        '''albert-xlarge-v2''': '''https://huggingface.co/albert-xlarge-v2/resolve/main/spiece.model''',
        '''albert-xxlarge-v2''': '''https://huggingface.co/albert-xxlarge-v2/resolve/main/spiece.model''',
    },
    '''tokenizer_file''': {
        '''albert-base-v1''': '''https://huggingface.co/albert-base-v1/resolve/main/tokenizer.json''',
        '''albert-large-v1''': '''https://huggingface.co/albert-large-v1/resolve/main/tokenizer.json''',
        '''albert-xlarge-v1''': '''https://huggingface.co/albert-xlarge-v1/resolve/main/tokenizer.json''',
        '''albert-xxlarge-v1''': '''https://huggingface.co/albert-xxlarge-v1/resolve/main/tokenizer.json''',
        '''albert-base-v2''': '''https://huggingface.co/albert-base-v2/resolve/main/tokenizer.json''',
        '''albert-large-v2''': '''https://huggingface.co/albert-large-v2/resolve/main/tokenizer.json''',
        '''albert-xlarge-v2''': '''https://huggingface.co/albert-xlarge-v2/resolve/main/tokenizer.json''',
        '''albert-xxlarge-v2''': '''https://huggingface.co/albert-xxlarge-v2/resolve/main/tokenizer.json''',
    },
}

a_ 		=       {
    '''albert-base-v1''': 5_1_2,
    '''albert-large-v1''': 5_1_2,
    '''albert-xlarge-v1''': 5_1_2,
    '''albert-xxlarge-v1''': 5_1_2,
    '''albert-base-v2''': 5_1_2,
    '''albert-large-v2''': 5_1_2,
    '''albert-xlarge-v2''': 5_1_2,
    '''albert-xxlarge-v2''': 5_1_2,
}

a_ 		=       '''▁'''






class    __SCREAMING_SNAKE_CASE					(	_lowerCAmelCase ):
 snake_case_     							=							VOCAB_FILES_NAMES
 snake_case_     							=							PRETRAINED_VOCAB_FILES_MAP
 snake_case_     							=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 snake_case_     							=							AlbertTokenizer




 def __init__(					self		:							Union[str, Any]    ,					__lowercase		:							int=None    ,					__lowercase		:							Dict=None    ,					__lowercase		:							Tuple=True    ,					__lowercase		:							Optional[int]=True    ,					__lowercase		:							List[Any]=False    ,					__lowercase		:							Optional[int]="[CLS]"    ,					__lowercase		:							List[str]="[SEP]"    ,					__lowercase		:							Optional[int]="<unk>"    ,					__lowercase		:							Optional[int]="[SEP]"    ,					__lowercase		:							Optional[int]="<pad>"    ,					__lowercase		:							Dict="[CLS]"    ,					__lowercase		:							List[str]="[MASK]"    ,					**__lowercase		:							str    ,					)		->  Optional[int]:
       SCREAMING_SNAKE_CASE__   : Dict													=(
           AddedToken(__lowercase    ,					lstrip=__lowercase    ,					rstrip=__lowercase    ,					normalized=__lowercase					)
           if isinstance(__lowercase    ,					__lowercase					)
           else mask_token
       )

       super().__init__(
           __lowercase    ,					tokenizer_file=__lowercase    ,					do_lower_case=__lowercase    ,					remove_space=__lowercase    ,					keep_accents=__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__   : int													=do_lower_case
       SCREAMING_SNAKE_CASE__   : Union[str, Any]													=remove_space
       SCREAMING_SNAKE_CASE__   : Any													=keep_accents
       SCREAMING_SNAKE_CASE__   : List[str]													=vocab_file
       SCREAMING_SNAKE_CASE__   : Any													=False if not self.vocab_file else True




 def    __magic_name__		(					self		:							List[str]    ,					__lowercase		:							List[int]    ,					__lowercase		:							Optional[List[int]] = None					)		->  List[Any]:
       SCREAMING_SNAKE_CASE__   : int													=[self.sep_token_id]
       SCREAMING_SNAKE_CASE__   : 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    __magic_name__		(					self		:							Tuple    ,					__lowercase		:							List[int]    ,					__lowercase		:							Optional[List[int]] = None					)		->  List[str]:
       SCREAMING_SNAKE_CASE__   : Tuple													=[self.sep_token_id]
       SCREAMING_SNAKE_CASE__   : 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    __magic_name__		(					self		:							List[str]    ,					__lowercase		:							str    ,					__lowercase		:							Optional[str] = None					)		->  Dict:




       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__   : Union[str, Any]													=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,)






'''simple docstring'''


import sys
import webbrowser

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

if __name__ == "__main__":
 print('''Googling.....''')
 lowerCAmelCase					:     str												='''https://www.google.com/search?q=''' + ''' '''.join(sys.argv[1:])
 lowerCAmelCase					:     List[str]												=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(10_000):
   out_file.write(data)
 lowerCAmelCase					:     List[Any]												=BeautifulSoup(res.text, '''html.parser''')
 lowerCAmelCase					:     List[Any]												=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')}''')


