"""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:
       _UpperCamelCase   :						List[Any]      =    None

_UpperCamelCase   :						Optional[Any]      =    logging.get_logger(__name__)
_UpperCamelCase   :						Dict      =    {"vocab_file": "spiece.model", "tokenizer_file": "tokenizer.json"}

_UpperCamelCase   :						List[str]      =    {
    "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",
    },
}

_UpperCamelCase   :						Optional[int]      =    {
    "albert-base-v1": 5_12,
    "albert-large-v1": 5_12,
    "albert-xlarge-v1": 5_12,
    "albert-xxlarge-v1": 5_12,
    "albert-base-v2": 5_12,
    "albert-large-v2": 5_12,
    "albert-xlarge-v2": 5_12,
    "albert-xxlarge-v2": 5_12,
}

_UpperCamelCase   :						Optional[int]      =    "▁"


class      UpperCAmelCase_	(    _a):
      lowerCamelCase__		:    Dict   =  VOCAB_FILES_NAMES
      lowerCamelCase__		:    Optional[Any]   =  PRETRAINED_VOCAB_FILES_MAP
      lowerCamelCase__		:    Any   =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      lowerCamelCase__		:    List[str]   =  AlbertTokenizer


      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		,			)       ->					Optional[int]:
             # Mask token behave like a normal word, i.e. include the space before it and
             # is included in the raw text, there should be a match in a non-normalized sentence.
             lowercase__			:		Dict       =	(
                 AddedToken(a		,			lstrip=a		,			rstrip=a		,			normalized=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		,			)

             lowercase__			:		int       =	do_lower_case
             lowercase__			:		Any       =	remove_space
             lowercase__			:		Optional[int]       =	keep_accents
             lowercase__			:		int       =	vocab_file
             lowercase__			:		Tuple       =	False if not self.vocab_file else True


      def 		_UpperCAmelCase       (   self		,			a		,			a = None							)       ->					List[int]:
             lowercase__			:		Dict       =	[self.sep_token_id]
             lowercase__			:		Union[str, Any]       =	[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		,			a		,			a = None							)       ->					List[int]:
             lowercase__			:		Union[str, Any]       =	[self.sep_token_id]
             lowercase__			:		Optional[Any]       =	[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		,			a		,			a = None							)       ->					Tuple[str]:
             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
             lowercase__			:		List[str]       =	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,)







import sys
import webbrowser

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

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