
import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_splinter import SplinterTokenizer


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

A  :			Tuple     				=				{'vocab_file': 'vocab.txt'}

A  :			Tuple     				=				{
    'vocab_file': {
        'tau/splinter-base': 'https://huggingface.co/tau/splinter-base/resolve/main/vocab.txt',
        'tau/splinter-base-qass': 'https://huggingface.co/tau/splinter-base-qass/resolve/main/vocab.txt',
        'tau/splinter-large': 'https://huggingface.co/tau/splinter-large/resolve/main/vocab.txt',
        'tau/splinter-large-qass': 'https://huggingface.co/tau/splinter-large-qass/resolve/main/vocab.txt',
    }
}

A  :			Optional[int]     				=				{
    'tau/splinter-base': 5_1_2,
    'tau/splinter-base-qass': 5_1_2,
    'tau/splinter-large': 5_1_2,
    'tau/splinter-large-qass': 5_1_2,
}

A  :			int     				=				{
    'tau/splinter-base': {'do_lower_case': False},
    'tau/splinter-base-qass': {'do_lower_case': False},
    'tau/splinter-large': {'do_lower_case': False},
    'tau/splinter-large-qass': {'do_lower_case': False},
}







class     __A(				a    ):
				snake_case_		     =					VOCAB_FILES_NAMES
				snake_case_		     =					PRETRAINED_VOCAB_FILES_MAP
				snake_case_		     =					PRETRAINED_INIT_CONFIGURATION
				snake_case_		     =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				snake_case_		     =					SplinterTokenizer




				def __init__(  self	,  _snake_case=None	,  _snake_case=None	,  _snake_case=True	,  _snake_case="[UNK]"	,  _snake_case="[SEP]"	,  _snake_case="[PAD]"	,  _snake_case="[CLS]"	,  _snake_case="[MASK]"	,  _snake_case="[QUESTION]"	,  _snake_case=True	,  _snake_case=None	,  **_snake_case	,  )					->   List[Any]:


								'''simple docstring'''




								super().__init__(
								    _snake_case	,  tokenizer_file=_snake_case	,  do_lower_case=_snake_case	,  unk_token=_snake_case	,  sep_token=_snake_case	,  pad_token=_snake_case	,  cls_token=_snake_case	,  mask_token=_snake_case	,  tokenize_chinese_chars=_snake_case	,  strip_accents=_snake_case	,  additional_special_tokens=(question_token,)	,  **_snake_case	,  )

								__a    							=					json.loads(self.backend_tokenizer.normalizer.__getstate__()       )
								if (
								    pre_tok_state.get('''lowercase'''	,  _snake_case       ) != do_lower_case
								    or pre_tok_state.get('''strip_accents'''	,  _snake_case       ) != strip_accents
								):
												__a    							=					getattr(_snake_case	,  pre_tok_state.pop('''type'''       )       )
												__a    							=					do_lower_case
												__a    							=					strip_accents
												__a    							=					pre_tok_class(**_snake_case       )

								__a    							=					do_lower_case




				@property
				def        SCREAMING_SNAKE_CASE_	(  self       )					->   Optional[int]:


								'''simple docstring'''




								return self.convert_tokens_to_ids(self.question_token       )




				def        SCREAMING_SNAKE_CASE_	(  self	,  _snake_case	,  _snake_case = None       )					->   List[int]:


								'''simple docstring'''




								if token_ids_a is None:
												return [self.cls_token_id] + token_ids_a + [self.sep_token_id]

								__a    							=					[self.cls_token_id]
								__a    							=					[self.sep_token_id]
								__a    							=					[self.question_token_id] + [self.convert_tokens_to_ids('''.'''       )]
								if self.padding_side == "right":
												# Input is question-then-context
												return cls + token_ids_a + question_suffix + sep + token_ids_a + sep
								else:
												# Input is context-then-question
												return cls + token_ids_a + sep + token_ids_a + question_suffix + sep




				def        SCREAMING_SNAKE_CASE_	(  self	,  _snake_case	,  _snake_case = None       )					->   List[int]:


								'''simple docstring'''




								__a    							=					[self.sep_token_id]
								__a    							=					[self.cls_token_id]
								__a    							=					[self.question_token_id] + [self.convert_tokens_to_ids('''.'''       )]
								if token_ids_a is None:
												return len(cls + token_ids_a + sep       ) * [0]

								if self.padding_side == "right":
												# Input is question-then-context
												return len(cls + token_ids_a + question_suffix + sep       ) * [0] + len(token_ids_a + sep       ) * [1]
								else:
												# Input is context-then-question
												return len(cls + token_ids_a + sep       ) * [0] + len(token_ids_a + question_suffix + sep       ) * [1]




				def        SCREAMING_SNAKE_CASE_	(  self	,  _snake_case	,  _snake_case = None       )					->   Tuple[str]:


								'''simple docstring'''




								__a    							=					self._tokenizer.model.save(_snake_case	,  name=_snake_case       )
								return tuple(_snake_case       )

def 					__lowerCAmelCase    (    a__ = 99_8001						) ->						int:
				__a    							=					0
				for i in range(999		,					99		,					-1						):  # 3 digit numbers range from 999 down to 100
								for j in range(999		,					99		,					-1						):
												__a    							=					str(i * j						)
												if product_string == product_string[::-1] and i * j < n:
																__a    							=					max(a__		,					i * j						)
				return answer


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