



"""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_distilbert import DistilBertTokenizer


A		=						logging.get_logger(__name__)

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

A		=						{
    'vocab_file': {
        'distilbert-base-uncased': 'https://huggingface.co/distilbert-base-uncased/resolve/main/vocab.txt',
        'distilbert-base-uncased-distilled-squad': (
            'https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/vocab.txt'
        ),
        'distilbert-base-cased': 'https://huggingface.co/distilbert-base-cased/resolve/main/vocab.txt',
        'distilbert-base-cased-distilled-squad': (
            'https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/vocab.txt'
        ),
        'distilbert-base-german-cased': 'https://huggingface.co/distilbert-base-german-cased/resolve/main/vocab.txt',
        'distilbert-base-multilingual-cased': (
            'https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/vocab.txt'
        ),
    },
    'tokenizer_file': {
        'distilbert-base-uncased': 'https://huggingface.co/distilbert-base-uncased/resolve/main/tokenizer.json',
        'distilbert-base-uncased-distilled-squad': (
            'https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/tokenizer.json'
        ),
        'distilbert-base-cased': 'https://huggingface.co/distilbert-base-cased/resolve/main/tokenizer.json',
        'distilbert-base-cased-distilled-squad': (
            'https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/tokenizer.json'
        ),
        'distilbert-base-german-cased': (
            'https://huggingface.co/distilbert-base-german-cased/resolve/main/tokenizer.json'
        ),
        'distilbert-base-multilingual-cased': (
            'https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/tokenizer.json'
        ),
    },
}

A		=						{
    'distilbert-base-uncased': 5_1_2,
    'distilbert-base-uncased-distilled-squad': 5_1_2,
    'distilbert-base-cased': 5_1_2,
    'distilbert-base-cased-distilled-squad': 5_1_2,
    'distilbert-base-german-cased': 5_1_2,
    'distilbert-base-multilingual-cased': 5_1_2,
}


A		=						{
    'distilbert-base-uncased': {'do_lower_case': True},
    'distilbert-base-uncased-distilled-squad': {'do_lower_case': True},
    'distilbert-base-cased': {'do_lower_case': False},
    'distilbert-base-cased-distilled-squad': {'do_lower_case': False},
    'distilbert-base-german-cased': {'do_lower_case': False},
    'distilbert-base-multilingual-cased': {'do_lower_case': False},
}

class       _a  ( SCREAMING_SNAKE_CASE__):
			__magic_name__     					=     VOCAB_FILES_NAMES
			__magic_name__     					=     PRETRAINED_VOCAB_FILES_MAP
			__magic_name__     					=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			__magic_name__     					=     PRETRAINED_INIT_CONFIGURATION
			__magic_name__     					=     ["""input_ids""", """attention_mask"""]
			__magic_name__     					=     DistilBertTokenizer



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

									snake_case   :			Dict						    = json.loads(self.backend_tokenizer.normalizer.__getstate__()		)
									if (
									    normalizer_state.get("lowercase"   ,	_lowercase		) != do_lower_case
									    or normalizer_state.get("strip_accents"   ,	_lowercase		) != strip_accents
									    or normalizer_state.get("handle_chinese_chars"   ,	_lowercase		) != tokenize_chinese_chars
									):
															snake_case   :			Union[str, Any]						    = getattr(_lowercase   ,	normalizer_state.pop("type"		)		)
															snake_case   :			Dict						    = do_lower_case
															snake_case   :			Any						    = strip_accents
															snake_case   :			Tuple						    = tokenize_chinese_chars
															snake_case   :			int						    = normalizer_class(**_lowercase		)

									snake_case   :			Dict						    = do_lower_case



			def 				__lowercase					(			self							:				Optional[Any]   ,	_lowercase							:				Union[str, Any]   ,	_lowercase							:				Any=None		)							->					Any:
									snake_case   :			Tuple						    = [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 				__lowercase					(			self							:				Any   ,	_lowercase							:				List[int]   ,	_lowercase							:				Optional[List[int]] = None		)							->					List[int]:
									snake_case   :			Tuple						    = [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 				__lowercase					(			self							:				Optional[int]   ,	_lowercase							:				str   ,	_lowercase							:				Optional[str] = None		)							->					Tuple[str]:
									snake_case   :			int						    = self._tokenizer.model.save(_lowercase   ,	name=_lowercase		)
									return tuple(_lowercase		)








"""simple docstring"""







import math
import sys

def  __SCREAMING_SNAKE_CASE		(			lowerCamelCase_:							int ):
						"""simple docstring"""






						if number != int(lowerCamelCase_ ):
												raise ValueError("the value of input must be a natural number" )
						if number < 0:
												raise ValueError("the value of input must not be a negative number" )
						if number == 0:
												return 1
						snake_case   :			List[str]						    = [-1] * (number + 1)
						snake_case   :			str						    = 0
						for i in range(1     ,		number + 1 ):
												snake_case   :			Tuple						    = sys.maxsize
												snake_case   :			Optional[Any]						    = int(math.sqrt(lowerCamelCase_ ) )
												for j in range(1     ,		root + 1 ):
																		snake_case   :			List[str]						    = 1 + answers[i - (j**2)]
																		snake_case   :			List[str]						    = min(lowerCamelCase_     ,		lowerCamelCase_ )
												snake_case   :			Dict						    = answer
						return answers[number]


if __name__ == "__main__":
			import doctest

			doctest.testmod()



