





import pprint

import requests

snake_case__					:							Tuple													=     'https://zenquotes.io/api'



def _a				(	)	->						list:







      '''simple docstring'''






      return requests.get(API_ENDPOINT_URL + '''/today''' ).json()



def _a				(	)	->						list:







      '''simple docstring'''






      return requests.get(API_ENDPOINT_URL + '''/random''' ).json()


if __name__ == "__main__":
       snake_case__					:							Tuple													=     random_quotes()
       pprint.pprint(response)












import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer


snake_case__					:							List[Any]													=     logging.get_logger(__name__)

snake_case__					:							Union[str, Any]													=     {'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}

snake_case__					:							int													=     {
    'vocab_file': {
        'bert-base-uncased': 'https://huggingface.co/bert-base-uncased/resolve/main/vocab.txt',
        'bert-large-uncased': 'https://huggingface.co/bert-large-uncased/resolve/main/vocab.txt',
        'bert-base-cased': 'https://huggingface.co/bert-base-cased/resolve/main/vocab.txt',
        'bert-large-cased': 'https://huggingface.co/bert-large-cased/resolve/main/vocab.txt',
        'bert-base-multilingual-uncased': (
            'https://huggingface.co/bert-base-multilingual-uncased/resolve/main/vocab.txt'
        ),
        'bert-base-multilingual-cased': 'https://huggingface.co/bert-base-multilingual-cased/resolve/main/vocab.txt',
        'bert-base-chinese': 'https://huggingface.co/bert-base-chinese/resolve/main/vocab.txt',
        'bert-base-german-cased': 'https://huggingface.co/bert-base-german-cased/resolve/main/vocab.txt',
        'bert-large-uncased-whole-word-masking': (
            'https://huggingface.co/bert-large-uncased-whole-word-masking/resolve/main/vocab.txt'
        ),
        'bert-large-cased-whole-word-masking': (
            'https://huggingface.co/bert-large-cased-whole-word-masking/resolve/main/vocab.txt'
        ),
        'bert-large-uncased-whole-word-masking-finetuned-squad': (
            'https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad/resolve/main/vocab.txt'
        ),
        'bert-large-cased-whole-word-masking-finetuned-squad': (
            'https://huggingface.co/bert-large-cased-whole-word-masking-finetuned-squad/resolve/main/vocab.txt'
        ),
        'bert-base-cased-finetuned-mrpc': (
            'https://huggingface.co/bert-base-cased-finetuned-mrpc/resolve/main/vocab.txt'
        ),
        'bert-base-german-dbmdz-cased': 'https://huggingface.co/bert-base-german-dbmdz-cased/resolve/main/vocab.txt',
        'bert-base-german-dbmdz-uncased': (
            'https://huggingface.co/bert-base-german-dbmdz-uncased/resolve/main/vocab.txt'
        ),
        'TurkuNLP/bert-base-finnish-cased-v1': (
            'https://huggingface.co/TurkuNLP/bert-base-finnish-cased-v1/resolve/main/vocab.txt'
        ),
        'TurkuNLP/bert-base-finnish-uncased-v1': (
            'https://huggingface.co/TurkuNLP/bert-base-finnish-uncased-v1/resolve/main/vocab.txt'
        ),
        'wietsedv/bert-base-dutch-cased': (
            'https://huggingface.co/wietsedv/bert-base-dutch-cased/resolve/main/vocab.txt'
        ),
    },
    'tokenizer_file': {
        'bert-base-uncased': 'https://huggingface.co/bert-base-uncased/resolve/main/tokenizer.json',
        'bert-large-uncased': 'https://huggingface.co/bert-large-uncased/resolve/main/tokenizer.json',
        'bert-base-cased': 'https://huggingface.co/bert-base-cased/resolve/main/tokenizer.json',
        'bert-large-cased': 'https://huggingface.co/bert-large-cased/resolve/main/tokenizer.json',
        'bert-base-multilingual-uncased': (
            'https://huggingface.co/bert-base-multilingual-uncased/resolve/main/tokenizer.json'
        ),
        'bert-base-multilingual-cased': (
            'https://huggingface.co/bert-base-multilingual-cased/resolve/main/tokenizer.json'
        ),
        'bert-base-chinese': 'https://huggingface.co/bert-base-chinese/resolve/main/tokenizer.json',
        'bert-base-german-cased': 'https://huggingface.co/bert-base-german-cased/resolve/main/tokenizer.json',
        'bert-large-uncased-whole-word-masking': (
            'https://huggingface.co/bert-large-uncased-whole-word-masking/resolve/main/tokenizer.json'
        ),
        'bert-large-cased-whole-word-masking': (
            'https://huggingface.co/bert-large-cased-whole-word-masking/resolve/main/tokenizer.json'
        ),
        'bert-large-uncased-whole-word-masking-finetuned-squad': (
            'https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad/resolve/main/tokenizer.json'
        ),
        'bert-large-cased-whole-word-masking-finetuned-squad': (
            'https://huggingface.co/bert-large-cased-whole-word-masking-finetuned-squad/resolve/main/tokenizer.json'
        ),
        'bert-base-cased-finetuned-mrpc': (
            'https://huggingface.co/bert-base-cased-finetuned-mrpc/resolve/main/tokenizer.json'
        ),
        'bert-base-german-dbmdz-cased': (
            'https://huggingface.co/bert-base-german-dbmdz-cased/resolve/main/tokenizer.json'
        ),
        'bert-base-german-dbmdz-uncased': (
            'https://huggingface.co/bert-base-german-dbmdz-uncased/resolve/main/tokenizer.json'
        ),
        'TurkuNLP/bert-base-finnish-cased-v1': (
            'https://huggingface.co/TurkuNLP/bert-base-finnish-cased-v1/resolve/main/tokenizer.json'
        ),
        'TurkuNLP/bert-base-finnish-uncased-v1': (
            'https://huggingface.co/TurkuNLP/bert-base-finnish-uncased-v1/resolve/main/tokenizer.json'
        ),
        'wietsedv/bert-base-dutch-cased': (
            'https://huggingface.co/wietsedv/bert-base-dutch-cased/resolve/main/tokenizer.json'
        ),
    },
}

snake_case__					:							int													=     {
    'bert-base-uncased': 512,
    'bert-large-uncased': 512,
    'bert-base-cased': 512,
    'bert-large-cased': 512,
    'bert-base-multilingual-uncased': 512,
    'bert-base-multilingual-cased': 512,
    'bert-base-chinese': 512,
    'bert-base-german-cased': 512,
    'bert-large-uncased-whole-word-masking': 512,
    'bert-large-cased-whole-word-masking': 512,
    'bert-large-uncased-whole-word-masking-finetuned-squad': 512,
    'bert-large-cased-whole-word-masking-finetuned-squad': 512,
    'bert-base-cased-finetuned-mrpc': 512,
    'bert-base-german-dbmdz-cased': 512,
    'bert-base-german-dbmdz-uncased': 512,
    'TurkuNLP/bert-base-finnish-cased-v1': 512,
    'TurkuNLP/bert-base-finnish-uncased-v1': 512,
    'wietsedv/bert-base-dutch-cased': 512,
}

snake_case__					:							str													=     {
    'bert-base-uncased': {'do_lower_case': True},
    'bert-large-uncased': {'do_lower_case': True},
    'bert-base-cased': {'do_lower_case': False},
    'bert-large-cased': {'do_lower_case': False},
    'bert-base-multilingual-uncased': {'do_lower_case': True},
    'bert-base-multilingual-cased': {'do_lower_case': False},
    'bert-base-chinese': {'do_lower_case': False},
    'bert-base-german-cased': {'do_lower_case': False},
    'bert-large-uncased-whole-word-masking': {'do_lower_case': True},
    'bert-large-cased-whole-word-masking': {'do_lower_case': False},
    'bert-large-uncased-whole-word-masking-finetuned-squad': {'do_lower_case': True},
    'bert-large-cased-whole-word-masking-finetuned-squad': {'do_lower_case': False},
    'bert-base-cased-finetuned-mrpc': {'do_lower_case': False},
    'bert-base-german-dbmdz-cased': {'do_lower_case': False},
    'bert-base-german-dbmdz-uncased': {'do_lower_case': True},
    'TurkuNLP/bert-base-finnish-cased-v1': {'do_lower_case': False},
    'TurkuNLP/bert-base-finnish-uncased-v1': {'do_lower_case': True},
    'wietsedv/bert-base-dutch-cased': {'do_lower_case': False},
}





class A_					(			_lowerCamelCase   ):
   lowerCAmelCase__        = VOCAB_FILES_NAMES
   lowerCAmelCase__        = PRETRAINED_VOCAB_FILES_MAP
   lowerCAmelCase__        = PRETRAINED_INIT_CONFIGURATION
   lowerCAmelCase__        = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   lowerCAmelCase__        = BertTokenizer




   def __init__(self	:List[str]    ,   _UpperCamelCase	:List[str]=None    ,   _UpperCamelCase	:Optional[Any]=None    ,   _UpperCamelCase	:str=True    ,   _UpperCamelCase	:Optional[Any]="[UNK]"    ,   _UpperCamelCase	:Tuple="[SEP]"    ,   _UpperCamelCase	:List[Any]="[PAD]"    ,   _UpperCamelCase	:int="[CLS]"    ,   _UpperCamelCase	:Optional[int]="[MASK]"    ,   _UpperCamelCase	:Union[str, Any]=True    ,   _UpperCamelCase	:str=None    ,   **_UpperCamelCase	:List[str]    ,   )->					str:
         super().__init__(
             _UpperCamelCase    ,   tokenizer_file=_UpperCamelCase    ,   do_lower_case=_UpperCamelCase    ,   unk_token=_UpperCamelCase    ,   sep_token=_UpperCamelCase    ,   pad_token=_UpperCamelCase    ,   cls_token=_UpperCamelCase    ,   mask_token=_UpperCamelCase    ,   tokenize_chinese_chars=_UpperCamelCase    ,   strip_accents=_UpperCamelCase    ,   **_UpperCamelCase    ,   )

         __A          =				json.loads(self.backend_tokenizer.normalizer.__getstate__() )
         if (
             normalizer_state.get('''lowercase'''    ,   _UpperCamelCase ) != do_lower_case
             or normalizer_state.get('''strip_accents'''    ,   _UpperCamelCase ) != strip_accents
             or normalizer_state.get('''handle_chinese_chars'''    ,   _UpperCamelCase ) != tokenize_chinese_chars
         ):
               __A          =				getattr(_UpperCamelCase    ,   normalizer_state.pop('''type''' ) )
               __A          =				do_lower_case
               __A          =				strip_accents
               __A          =				tokenize_chinese_chars
               __A          =				normalizer_class(**_UpperCamelCase )

         __A          =				do_lower_case




   def _lowerCAmelCase      (self	:Any    ,   _UpperCamelCase	:int    ,   _UpperCamelCase	:List[str]=None )->					List[Any]:
         __A          =				[self.cls_token_id] + token_ids_a + [self.sep_token_id]

         if token_ids_a:
               output += token_ids_a + [self.sep_token_id]

         return output




   def _lowerCAmelCase      (self	:List[str]    ,   _UpperCamelCase	:List[int]    ,   _UpperCamelCase	:Optional[List[int]] = None )->					List[int]:
         __A          =				[self.sep_token_id]
         __A          =				[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	:Any    ,   _UpperCamelCase	:str    ,   _UpperCamelCase	:Optional[str] = None )->					Tuple[str]:
         __A          =				self._tokenizer.model.save(_UpperCamelCase    ,   name=_UpperCamelCase )
         return tuple(_UpperCamelCase )





