import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
      from .tokenization_camembert import CamembertTokenizer
else:
      UpperCamelCase__											=					None


UpperCamelCase__											=					logging.get_logger(__name__)

UpperCamelCase__											=					{'vocab_file': 'sentencepiece.bpe.model', 'tokenizer_file': 'tokenizer.json'}

UpperCamelCase__											=					{
    'vocab_file': {
        'camembert-base': 'https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model',
    },
    'tokenizer_file': {
        'camembert-base': 'https://huggingface.co/camembert-base/resolve/main/tokenizer.json',
    },
}

UpperCamelCase__											=					{
    'camembert-base': 5_1_2,
}

UpperCamelCase__											=					'▁'





class      A							(				UpperCAmelCase_     ):
   __UpperCAmelCase : str      =			VOCAB_FILES_NAMES
   __UpperCAmelCase : Dict      =			PRETRAINED_VOCAB_FILES_MAP
   __UpperCAmelCase : Optional[Any]      =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   __UpperCAmelCase : int      =			['input_ids', 'attention_mask']
   __UpperCAmelCase : Tuple      =			CamembertTokenizer


   def __init__(self     :						Optional[Any]       ,  __UpperCAmelCase     :						List[str]=None       ,  __UpperCAmelCase     :						Any=None       ,  __UpperCAmelCase     :						Tuple="<s>"       ,  __UpperCAmelCase     :						int="</s>"       ,  __UpperCAmelCase     :						Union[str, Any]="</s>"       ,  __UpperCAmelCase     :						Optional[int]="<s>"       ,  __UpperCAmelCase     :						str="<unk>"       ,  __UpperCAmelCase     :						int="<pad>"       ,  __UpperCAmelCase     :						Dict="<mask>"       ,  __UpperCAmelCase     :						Union[str, Any]=["<s>NOTUSED", "</s>NOTUSED"]       ,  **__UpperCAmelCase     :						List[Any]       ,  )						->				Any:
         """simple docstring"""



         UpperCAmelCase__								=  AddedToken(__UpperCAmelCase       ,  lstrip=__UpperCAmelCase       ,  rstrip=__UpperCAmelCase		) if isinstance(__UpperCAmelCase       ,  __UpperCAmelCase		) else mask_token

         super().__init__(
             __UpperCAmelCase       ,  tokenizer_file=__UpperCAmelCase       ,  bos_token=__UpperCAmelCase       ,  eos_token=__UpperCAmelCase       ,  sep_token=__UpperCAmelCase       ,  cls_token=__UpperCAmelCase       ,  unk_token=__UpperCAmelCase       ,  pad_token=__UpperCAmelCase       ,  mask_token=__UpperCAmelCase       ,  additional_special_tokens=__UpperCAmelCase       ,  **__UpperCAmelCase       ,  )

         UpperCAmelCase__								=  vocab_file
         UpperCAmelCase__								=  False if not self.vocab_file else True


   def 			lowercase_      (self     :						Any       ,  __UpperCAmelCase     :						List[int]       ,  __UpperCAmelCase     :						Optional[List[int]] = None		)						->				List[int]:
         """simple docstring"""



         if token_ids_a is None:
               return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
         UpperCAmelCase__								=  [self.cls_token_id]
         UpperCAmelCase__								=  [self.sep_token_id]
         return cls + token_ids_a + sep + sep + token_ids_a + sep


   def 			lowercase_      (self     :						Any       ,  __UpperCAmelCase     :						List[int]       ,  __UpperCAmelCase     :						Optional[List[int]] = None		)						->				List[int]:
         """simple docstring"""



         UpperCAmelCase__								=  [self.sep_token_id]
         UpperCAmelCase__								=  [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 			lowercase_      (self     :						Optional[Any]       ,  __UpperCAmelCase     :						str       ,  __UpperCAmelCase     :						Optional[str] = None		)						->				Tuple[str]:
         """simple docstring"""



         if not self.can_save_slow_tokenizer:
               raise ValueError(
                   "Your fast tokenizer does not have the necessary information to save the vocabulary for a slow "
                   "tokenizer."		)

         if not os.path.isdir(__UpperCAmelCase		):
               logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""		)
               return
         UpperCAmelCase__								=  os.path.join(
             __UpperCAmelCase       ,  (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]		)

         if os.path.abspath(self.vocab_file		) != os.path.abspath(__UpperCAmelCase		):
               copyfile(self.vocab_file       ,  __UpperCAmelCase		)

         return (out_vocab_file,)










def    __lowerCamelCase					(							__a   :str    )		->				list:






		"""simple docstring"""

		A__        =   [0] * len(__a    )

		for i in range(1    ,     len(__a    )    ):
				# use last results for better performance - dynamic programming
				A__        =   prefix_result[i - 1]
				while j > 0 and input_string[i] != input_string[j]:
						A__        =   prefix_result[j - 1]

				if input_string[i] == input_string[j]:
						j += 1
				A__        =   j

		return prefix_result







def    __lowerCamelCase					(							__a   :str    )		->				int:






		"""simple docstring"""

		return max(prefix_function(__a    )    )


if __name__ == "__main__":
					import doctest

					doctest.testmod()



