





import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer


__lowercase       :List[str]       =  logging.get_logger(__name__)

__lowercase       :Tuple       =  {"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"}

__lowercase       :Union[str, Any]       =  {
    "vocab_file": {
        "squeezebert/squeezebert-uncased": (
            "https://huggingface.co/squeezebert/squeezebert-uncased/resolve/main/vocab.txt"
        ),
        "squeezebert/squeezebert-mnli": "https://huggingface.co/squeezebert/squeezebert-mnli/resolve/main/vocab.txt",
        "squeezebert/squeezebert-mnli-headless": (
            "https://huggingface.co/squeezebert/squeezebert-mnli-headless/resolve/main/vocab.txt"
        ),
    },
    "tokenizer_file": {
        "squeezebert/squeezebert-uncased": (
            "https://huggingface.co/squeezebert/squeezebert-uncased/resolve/main/tokenizer.json"
        ),
        "squeezebert/squeezebert-mnli": (
            "https://huggingface.co/squeezebert/squeezebert-mnli/resolve/main/tokenizer.json"
        ),
        "squeezebert/squeezebert-mnli-headless": (
            "https://huggingface.co/squeezebert/squeezebert-mnli-headless/resolve/main/tokenizer.json"
        ),
    },
}

__lowercase       :List[Any]       =  {
    "squeezebert/squeezebert-uncased": 512,
    "squeezebert/squeezebert-mnli": 512,
    "squeezebert/squeezebert-mnli-headless": 512,
}


__lowercase       :str       =  {
    "squeezebert/squeezebert-uncased": {"do_lower_case": True},
    "squeezebert/squeezebert-mnli": {"do_lower_case": True},
    "squeezebert/squeezebert-mnli-headless": {"do_lower_case": True},
}



class    _a     (				__SCREAMING_SNAKE_CASE							):






							"""simple docstring"""

							snake_case_							 =						VOCAB_FILES_NAMES
							snake_case_							 =						PRETRAINED_VOCAB_FILES_MAP
							snake_case_							 =						PRETRAINED_INIT_CONFIGURATION
							snake_case_							 =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							snake_case_							 =						SqueezeBertTokenizer

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

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

													SCREAMING_SNAKE_CASE__     :				Any   =					do_lower_case

							def      A_  (      self				:     int							,	a				:     Dict							,	a				:     Dict=None    )	->str:
													SCREAMING_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				:     Any							,	a				:     List[int]							,	a				:     Optional[List[int]] = None    )	->Dict:
													SCREAMING_SNAKE_CASE__     :				Dict   =					[self.sep_token_id]
													SCREAMING_SNAKE_CASE__     :				Union[str, 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				:     Optional[int]							,	a				:     str							,	a				:     Optional[str] = None    )	->str:
													SCREAMING_SNAKE_CASE__     :				Union[str, Any]   =					self._tokenizer.model.save(_a							,	name=_a    )
													return tuple(_a    )










def       UpperCAmelCase							(     _lowerCamelCase      :  int = 4_000_000     ):





						'''simple docstring'''


						SCREAMING_SNAKE_CASE__     :				Any   =					[0, 1]
						SCREAMING_SNAKE_CASE__     :				List[Any]   =					0
						while fib[i] <= n:
												fib.append(fib[i] + fib[i + 1]     )
												if fib[i + 2] > n:
																		break
												i += 1
						SCREAMING_SNAKE_CASE__     :				Optional[Any]   =					0
						for j in range(len(_lowerCamelCase     ) - 1     ):
												if fib[j] % 2 == 0:
																		total += fib[j]

						return total


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