

'''simple docstring'''





def   _UpperCamelCase	(		__UpperCamelCase    ,__UpperCamelCase	)       ->			str:

					if not (isinstance(__UpperCamelCase    ,__UpperCamelCase	) and isinstance(__UpperCamelCase    ,__UpperCamelCase	)):
										raise ValueError('longest_common_substring() takes two strings for inputs'	)

					lowerCamelCase_  				=      len(__UpperCamelCase	)
					lowerCamelCase_  				=      len(__UpperCamelCase	)

					lowerCamelCase_  				=      [[0] * (texta_length + 1) for _ in range(texta_length + 1	)]
					lowerCamelCase_  				=      0
					lowerCamelCase_  				=      0

					for i in range(1    ,texta_length + 1	):
										for j in range(1    ,texta_length + 1	):
															if texta[i - 1] == texta[j - 1]:
																				lowerCamelCase_  				=      1 + dp[i - 1][j - 1]
																				if dp[i][j] > ans_length:
																									lowerCamelCase_  				=      i
																									lowerCamelCase_  				=      dp[i][j]

					return texta[ans_index - ans_length : ans_index]


if __name__ == "__main__":
				import doctest

				doctest.testmod()








"""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_squeezebert import SqueezeBertTokenizer


a_							=    logging.get_logger(__name__)

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

a_							=    {
    """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"""
        ),
    },
}

a_							=    {
    """squeezebert/squeezebert-uncased""": 5_12,
    """squeezebert/squeezebert-mnli""": 5_12,
    """squeezebert/squeezebert-mnli-headless""": 5_12,
}


a_							=    {
    """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"""



			a_       :			Union[str, Any]												=			VOCAB_FILES_NAMES
			a_       :			List[str]												=			PRETRAINED_VOCAB_FILES_MAP
			a_       :			Optional[Any]												=			PRETRAINED_INIT_CONFIGURATION
			a_       :			Tuple												=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			a_       :			Optional[int]												=			SqueezeBertTokenizer
			def __init__(	self				,   A=None				,   A=None				,   A=True				,   A="[UNK]"				,   A="[SEP]"				,   A="[PAD]"				,   A="[CLS]"				,   A="[MASK]"				,   A=True				,   A=None				,   **A				,   ):
						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				,   )

						_lowerCamelCase					:					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
						):
									_lowerCamelCase					:					List[Any]	       =    getattr(A				,   normalizer_state.pop('type'							)							)
									_lowerCamelCase					:					Optional[Any]	       =    do_lower_case
									_lowerCamelCase					:					str	       =    strip_accents
									_lowerCamelCase					:					Any	       =    tokenize_chinese_chars
									_lowerCamelCase					:					int	       =    normalizer_class(**A							)

						_lowerCamelCase					:					Dict	       =    do_lower_case
			def    _lowerCAmelCase		(	self				,   A				,   A=None							):
						_lowerCamelCase					:					Dict	       =    [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    _lowerCAmelCase		(	self				,   A				,   A = None							):
						_lowerCamelCase					:					Union[str, Any]	       =    [self.sep_token_id]
						_lowerCamelCase					:					Optional[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    _lowerCAmelCase		(	self				,   A				,   A = None							):
						_lowerCamelCase					:					str	       =    self._tokenizer.model.save(A				,   name=A							)
						return tuple(A							)





