
import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mpnet import MPNetTokenizer


snake_case_      :					Any				      =     logging.get_logger(__name__)

snake_case_      :					List[str]				      =     {"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"}

snake_case_      :					Optional[Any]				      =     {
    "vocab_file": {
        "microsoft/mpnet-base": "https://huggingface.co/microsoft/mpnet-base/resolve/main/vocab.txt",
    },
    "tokenizer_file": {
        "microsoft/mpnet-base": "https://huggingface.co/microsoft/mpnet-base/resolve/main/tokenizer.json",
    },
}

snake_case_      :					Optional[int]				      =     {
    "microsoft/mpnet-base": 5_1_2,
}

snake_case_      :					Union[str, Any]				      =     {
    "microsoft/mpnet-base": {"do_lower_case": True},
}





class 		__lowerCamelCase     (   __lowerCAmelCase		):
							lowerCamelCase__:				Any      =							VOCAB_FILES_NAMES
							lowerCamelCase__:				Optional[Any]      =							PRETRAINED_VOCAB_FILES_MAP
							lowerCamelCase__:				Dict      =							PRETRAINED_INIT_CONFIGURATION
							lowerCamelCase__:				int      =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							lowerCamelCase__:				Optional[Any]      =							MPNetTokenizer
							lowerCamelCase__:				Union[str, Any]      =							["input_ids", "attention_mask"]



							def __init__(     self	,				__snake_case=None	,				__snake_case=None	,				__snake_case=True	,				__snake_case="<s>"	,				__snake_case="</s>"	,				__snake_case="</s>"	,				__snake_case="<s>"	,				__snake_case="[UNK]"	,				__snake_case="<pad>"	,				__snake_case="<mask>"	,				__snake_case=True	,				__snake_case=None	,				**__snake_case	,				)						->     List[str]:






								"""simple docstring"""



								super().__init__(
								    lowerCamelCase__	,				tokenizer_file=lowerCamelCase__	,				do_lower_case=lowerCamelCase__	,				bos_token=lowerCamelCase__	,				eos_token=lowerCamelCase__	,				sep_token=lowerCamelCase__	,				cls_token=lowerCamelCase__	,				unk_token=lowerCamelCase__	,				pad_token=lowerCamelCase__	,				mask_token=lowerCamelCase__	,				tokenize_chinese_chars=lowerCamelCase__	,				strip_accents=lowerCamelCase__	,				**lowerCamelCase__	,				)

								UpperCAmelCase:					Optional[int] 						=     json.loads(self.backend_tokenizer.normalizer.__getstate__()							)
								if (
								    pre_tok_state.get("lowercase"	,				lowerCamelCase__							) != do_lower_case
								    or pre_tok_state.get("strip_accents"	,				lowerCamelCase__							) != strip_accents
								):
									UpperCAmelCase:					Optional[int] 						=     getattr(lowerCamelCase__	,				pre_tok_state.pop("type"							)							)
									UpperCAmelCase:					Dict 						=     do_lower_case
									UpperCAmelCase:					Tuple 						=     strip_accents
									UpperCAmelCase:					str 						=     pre_tok_class(**lowerCamelCase__							)

								UpperCAmelCase:					Optional[int] 						=     do_lower_case



							@property
							def     A__ (     self							)						->     str:






								"""simple docstring"""



								if self._mask_token is None:
									if self.verbose:
										logger.error("Using mask_token, but it is not set yet."							)
									return None
								return str(self._mask_token							)



							@mask_token.setter
							def     A__ (     self	,				__snake_case							)						->     Any:






								"""simple docstring"""



								UpperCAmelCase:					Optional[Any] 						=     AddedToken(lowerCamelCase__	,				lstrip=lowerCamelCase__	,				rstrip=lowerCamelCase__							) if isinstance(lowerCamelCase__	,				lowerCamelCase__							) else value
								UpperCAmelCase:					Optional[Any] 						=     value



							def     A__ (     self	,				__snake_case	,				__snake_case=None							)						->     List[Any]:






								"""simple docstring"""



								UpperCAmelCase:					List[Any] 						=     [self.bos_token_id] + token_ids_a + [self.eos_token_id]
								if token_ids_a is None:
									return output

								return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]



							def     A__ (     self	,				__snake_case	,				__snake_case = None							)						->     List[int]:






								"""simple docstring"""



								UpperCAmelCase:					Optional[int] 						=     [self.sep_token_id]
								UpperCAmelCase:					str 						=     [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 + sep + token_ids_a + sep							) * [0]




							def     A__ (     self	,				__snake_case	,				__snake_case = None							)						->     Tuple[str]:






								"""simple docstring"""



								UpperCAmelCase:					Tuple 						=     self._tokenizer.model.save(lowerCamelCase__	,				name=lowerCamelCase__							)
								return tuple(lowerCamelCase__							)




import unittest
import warnings
from dataclasses import dataclass

from transformers.convert_slow_tokenizer import SpmConverter
from transformers.testing_utils import get_tests_dir

@dataclass
class    __magic_name__						:
     A:		str



class    __magic_name__						(  unittest.TestCase):


     def   UpperCAmelCase__						(   self				:  Any      )	->   List[Any]:





      '''simple docstring'''






      UpperCamelCase__       :     Optional[Any] 							= get_tests_dir('''fixtures/test_sentencepiece.model'''      )
      UpperCamelCase__       :     Any 							= get_tests_dir('''fixtures/test_sentencepiece_with_bytefallback.model'''      )

      UpperCamelCase__       :     List[str] 							= FakeOriginalTokenizer(vocab_file=lowerCamelCase__      )

      with warnings.catch_warnings(record=lowerCamelCase__      ) as w:
       UpperCamelCase__       :     Optional[int] 							= SpmConverter(lowerCamelCase__      )
      self.assertEqual(len(lowerCamelCase__      )				,						0      )

      UpperCamelCase__       :     Tuple 							= FakeOriginalTokenizer(vocab_file=lowerCamelCase__      )

      with warnings.catch_warnings(record=lowerCamelCase__      ) as w:
       UpperCamelCase__       :     str 							= SpmConverter(lowerCamelCase__      )
      self.assertEqual(len(lowerCamelCase__      )				,						1      )

      self.assertIn(
          '''The sentencepiece tokenizer that you are converting to a fast tokenizer uses the byte fallback option'''
          ''' which is not implemented in the fast tokenizers.'''				,						str(w[0].message      )				,						)


