






'''simple docstring'''




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   :					int   							=					logging.get_logger(__name__)

__lowerCamelCase   :					Optional[int]   							=					{'''vocab_file''': '''vocab.txt''', '''tokenizer_file''': '''tokenizer.json'''}

__lowerCamelCase   :					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'''
        ),
    },
}

__lowerCamelCase   :					List[str]   							=					{
    '''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,
}

__lowerCamelCase   :					Optional[int]   							=					{
    '''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_							):
							"""simple docstring"""




							a__   		=	VOCAB_FILES_NAMES
							a__   		=	PRETRAINED_VOCAB_FILES_MAP
							a__   		=	PRETRAINED_INIT_CONFIGURATION
							a__   		=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							a__   		=	BertTokenizer

							def __init__(		self			:int       ,							lowerCAmelCase__			:List[str]=None       ,							lowerCAmelCase__			:Dict=None       ,							lowerCAmelCase__			:List[Any]=True       ,							lowerCAmelCase__			:List[str]="[UNK]"       ,							lowerCAmelCase__			:List[str]="[SEP]"       ,							lowerCAmelCase__			:int="[PAD]"       ,							lowerCAmelCase__			:Optional[int]="[CLS]"       ,							lowerCAmelCase__			:List[str]="[MASK]"       ,							lowerCAmelCase__			:Dict=True       ,							lowerCAmelCase__			:Any=None       ,							**lowerCAmelCase__			:List[Any]       ,							)				->  List[Any]:


										'''simple docstring'''




										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__       ,							)

										snake_case_				:					Any   =       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
										):
													snake_case_				:					Dict   =       getattr(lowerCAmelCase__       ,							normalizer_state.pop("type"				)				)
													snake_case_				:					int   =       do_lower_case
													snake_case_				:					Tuple   =       strip_accents
													snake_case_				:					int   =       tokenize_chinese_chars
													snake_case_				:					Dict   =       normalizer_class(**lowerCAmelCase__				)

										snake_case_				:					Dict   =       do_lower_case

							def 							_A	(		self			:List[Any]       ,							lowerCAmelCase__			:Any       ,							lowerCAmelCase__			:List[str]=None				)				->  List[Any]:


										'''simple docstring'''




										snake_case_				:					Any   =       [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			:List[Any]       ,							lowerCAmelCase__			:List[int]       ,							lowerCAmelCase__			:Optional[List[int]] = None				)				->  List[int]:


										'''simple docstring'''




										snake_case_				:					Optional[Any]   =       [self.sep_token_id]
										snake_case_				:					List[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 							_A	(		self			:Tuple       ,							lowerCAmelCase__			:str       ,							lowerCAmelCase__			:Optional[str] = None				)				->  Tuple[str]:


										'''simple docstring'''




										snake_case_				:					Optional[Any]   =       self._tokenizer.model.save(lowerCAmelCase__       ,							name=lowerCAmelCase__				)
										return tuple(lowerCAmelCase__				)












'''simple docstring'''




def 	__UpperCAmelCase       ( __magic_name__						)->    list[int]:



			"""simple docstring"""



			if length <= 0 or not isinstance(__magic_name__     ,__magic_name__						):
						raise ValueError("Length must be a positive integer."						)
			return [n * (2 * n - 1) for n in range(__magic_name__						)]


if __name__ == "__main__":
		print(hexagonal_numbers(length=5))
		print(hexagonal_numbers(length=10))




