




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:
   lowerCamelCase__			:       str         =							None

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

lowerCamelCase__			:       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""",
    },
}

lowerCamelCase__			:       Any         =							{
    """albert-base-v1""": 512,
    """albert-large-v1""": 512,
    """albert-xlarge-v1""": 512,
    """albert-xxlarge-v1""": 512,
    """albert-base-v2""": 512,
    """albert-large-v2""": 512,
    """albert-xlarge-v2""": 512,
    """albert-xxlarge-v2""": 512,
}

lowerCamelCase__			:       List[Any]         =							"""▁"""





class 	UpperCAmelCase_							(				__UpperCamelCase ):


 '''simple docstring'''







 lowercase_       =   VOCAB_FILES_NAMES
 lowercase_       =   PRETRAINED_VOCAB_FILES_MAP
 lowercase_       =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 lowercase_       =   AlbertTokenizer



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

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

       SCREAMING_SNAKE_CASE_     						=      do_lower_case
       SCREAMING_SNAKE_CASE_     						=      remove_space
       SCREAMING_SNAKE_CASE_     						=      keep_accents
       SCREAMING_SNAKE_CASE_     						=      vocab_file
       SCREAMING_SNAKE_CASE_     						=      False if not self.vocab_file else True



 def 				lowerCAmelCase_  (							self  :		List[str]    ,    _lowerCAmelCase  :		List[int]    ,    _lowerCAmelCase  :		Optional[List[int]] = None						):
       SCREAMING_SNAKE_CASE_     						=      [self.sep_token_id]
       SCREAMING_SNAKE_CASE_     						=      [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 				lowerCAmelCase_  (							self  :		Tuple    ,    _lowerCAmelCase  :		List[int]    ,    _lowerCAmelCase  :		Optional[List[int]] = None						):
       SCREAMING_SNAKE_CASE_     						=      [self.sep_token_id]
       SCREAMING_SNAKE_CASE_     						=      [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 				lowerCAmelCase_  (							self  :		Optional[int]    ,    _lowerCAmelCase  :		str    ,    _lowerCAmelCase  :		Optional[str] = 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(_lowerCAmelCase						):
             logger.error(F"Vocabulary path ({save_directory}) should be a directory"						)
             return
       SCREAMING_SNAKE_CASE_     						=      os.path.join(
           _lowerCAmelCase    ,    (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']						)

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

       return (out_vocab_file,)





from json import JSONDecodeError  # Workaround for requests.exceptions.JSONDecodeError

import requests

def  UpperCAmelCase_							(				__UpperCAmelCase						:     str = "isbn/0140328726"							) ->			dict:
      SCREAMING_SNAKE_CASE_     						=      olid.strip().strip('/'							)  # Remove leading/trailing whitespace & slashes
      if new_olid.count('/'							) != 1:
            SCREAMING_SNAKE_CASE_     						=      f"{olid} is not a valid Open Library olid"
            raise ValueError(__UpperCAmelCase							)
      return requests.get(f"https://openlibrary.org/{new_olid}.json"							).json()

def  UpperCAmelCase_							(				__UpperCAmelCase						:     dict							) ->			dict:
      SCREAMING_SNAKE_CASE_     						=      {
          'title': 'Title',
          'publish_date': 'Publish date',
          'authors': 'Authors',
          'number_of_pages': 'Number of pages:',
          'first_sentence': 'First sentence',
          'isbn_10': 'ISBN (10)',
          'isbn_13': 'ISBN (13)',
      }
      SCREAMING_SNAKE_CASE_     						=      {better_key: ol_book_data[key] for key, better_key in desired_keys.items()}
      SCREAMING_SNAKE_CASE_     						=      [
          get_openlibrary_data(author['key']							)['name'] for author in data['Authors']
      ]
      SCREAMING_SNAKE_CASE_     						=      data['First sentence']['value']
      for key, value in data.items():
            if isinstance(__UpperCAmelCase      ,      __UpperCAmelCase							):
                  SCREAMING_SNAKE_CASE_     						=      ', '.join(__UpperCAmelCase							)
      return data


if __name__ == "__main__":
   import doctest

   doctest.testmod()

   while True:
      lowerCamelCase__			:       Optional[Any]         =							input('\nEnter the ISBN code to search (or \'quit\' to stop): ').strip()
      if isbn.lower() in ("", "q", "quit", "exit", "stop"):
         break

      if len(isbn) not in (10, 13) or not isbn.isdigit():
         print(f'''Sorry, {isbn} is not a valid ISBN.  Please, input a valid ISBN.''')
         continue

      print(f'''\nSearching Open Library for ISBN: {isbn}...\n''')

      try:
         lowerCamelCase__			:       Union[str, Any]         =							summarize_book(get_openlibrary_data(f'''isbn/{isbn}'''))
         print('\n'.join(f'''{key}: {value}''' for key, value in book_summary.items()))
      except JSONDecodeError:  # Workaround for requests.exceptions.RequestException:
         print(f'''Sorry, there are no results for ISBN: {isbn}.''')