


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


lowerCAmelCase           =		logging.get_logger(__name__)

lowerCAmelCase           =		{'''vocab_file''': '''vocab.txt''', '''tokenizer_file''': '''tokenizer.json'''}

lowerCAmelCase           =		{
    '''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'''
        ),
    },
}

lowerCAmelCase           =		{
    '''bert-base-uncased''': 5_1_2,
    '''bert-large-uncased''': 5_1_2,
    '''bert-base-cased''': 5_1_2,
    '''bert-large-cased''': 5_1_2,
    '''bert-base-multilingual-uncased''': 5_1_2,
    '''bert-base-multilingual-cased''': 5_1_2,
    '''bert-base-chinese''': 5_1_2,
    '''bert-base-german-cased''': 5_1_2,
    '''bert-large-uncased-whole-word-masking''': 5_1_2,
    '''bert-large-cased-whole-word-masking''': 5_1_2,
    '''bert-large-uncased-whole-word-masking-finetuned-squad''': 5_1_2,
    '''bert-large-cased-whole-word-masking-finetuned-squad''': 5_1_2,
    '''bert-base-cased-finetuned-mrpc''': 5_1_2,
    '''bert-base-german-dbmdz-cased''': 5_1_2,
    '''bert-base-german-dbmdz-uncased''': 5_1_2,
    '''TurkuNLP/bert-base-finnish-cased-v1''': 5_1_2,
    '''TurkuNLP/bert-base-finnish-uncased-v1''': 5_1_2,
    '''wietsedv/bert-base-dutch-cased''': 5_1_2,
}

lowerCAmelCase           =		{
    '''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    (   A_ ):
							UpperCamelCase_   :							Dict       =VOCAB_FILES_NAMES
							UpperCamelCase_   :							Any       =PRETRAINED_VOCAB_FILES_MAP
							UpperCamelCase_   :							Optional[Any]       =PRETRAINED_INIT_CONFIGURATION
							UpperCamelCase_   :							str       =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							UpperCamelCase_   :							Union[str, Any]       =BertTokenizer


							def __init__(self      ,				lowerCAmelCase=None      ,				lowerCAmelCase=None      ,				lowerCAmelCase=True      ,				lowerCAmelCase="[UNK]"      ,				lowerCAmelCase="[SEP]"      ,				lowerCAmelCase="[PAD]"      ,				lowerCAmelCase="[CLS]"      ,				lowerCAmelCase="[MASK]"      ,				lowerCAmelCase=True      ,				lowerCAmelCase=None      ,				**lowerCAmelCase      ,				):
									super().__init__(
									    lowerCAmelCase      ,				tokenizer_file=lowerCAmelCase      ,				do_lower_case=lowerCAmelCase      ,				unk_token=lowerCAmelCase      ,				sep_token=lowerCAmelCase      ,				pad_token=lowerCAmelCase      ,				cls_token=lowerCAmelCase      ,				mask_token=lowerCAmelCase      ,				tokenize_chinese_chars=lowerCAmelCase      ,				strip_accents=lowerCAmelCase      ,				**lowerCAmelCase      ,				)

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

									__lowercase=			do_lower_case


							def 			_A       (self      ,				lowerCAmelCase      ,				lowerCAmelCase=None					):
									__lowercase=			[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 			_A       (self      ,				lowerCAmelCase      ,				lowerCAmelCase = None					):
									__lowercase=			[self.sep_token_id]
									__lowercase=			[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					):
									__lowercase=			self._tokenizer.model.save(lowerCAmelCase      ,				name=lowerCAmelCase					)
									return tuple(lowerCAmelCase					)










from math import isqrt







def        _lowerCamelCase(	lowercase__	)						->	bool:

		'''simple docstring'''







		return all(number % divisor != 0 for divisor in range(2   , isqrt(lowercase__	) + 1	)	)







def        _lowerCamelCase(	lowercase__ = 1_0**6	)						->	int:

		'''simple docstring'''







		__lowercase=			0
		__lowercase=			1
		__lowercase=			7
		while prime_candidate < max_prime:
				primes_count += is_prime(lowercase__	)

				cube_index += 1
				prime_candidate += 6 * cube_index

		return primes_count


if __name__ == "__main__":
	print(F'{solution() = }')






