


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_xlm_roberta import XLMRobertaTokenizer
else:
       __UpperCamelCase							:							str    							=					None


__UpperCamelCase							:							str    							=					logging.get_logger(__name__)

__UpperCamelCase							:							Tuple    							=					{"vocab_file": "sentencepiece.bpe.model", "tokenizer_file": "tokenizer.json"}

__UpperCamelCase							:							Optional[Any]    							=					{
    "vocab_file": {
        "xlm-roberta-base": "https://huggingface.co/xlm-roberta-base/resolve/main/sentencepiece.bpe.model",
        "xlm-roberta-large": "https://huggingface.co/xlm-roberta-large/resolve/main/sentencepiece.bpe.model",
        "xlm-roberta-large-finetuned-conll02-dutch": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/sentencepiece.bpe.model"
        ),
        "xlm-roberta-large-finetuned-conll02-spanish": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/sentencepiece.bpe.model"
        ),
        "xlm-roberta-large-finetuned-conll03-english": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/sentencepiece.bpe.model"
        ),
        "xlm-roberta-large-finetuned-conll03-german": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/sentencepiece.bpe.model"
        ),
    },
    "tokenizer_file": {
        "xlm-roberta-base": "https://huggingface.co/xlm-roberta-base/resolve/main/tokenizer.json",
        "xlm-roberta-large": "https://huggingface.co/xlm-roberta-large/resolve/main/tokenizer.json",
        "xlm-roberta-large-finetuned-conll02-dutch": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/tokenizer.json"
        ),
        "xlm-roberta-large-finetuned-conll02-spanish": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/tokenizer.json"
        ),
        "xlm-roberta-large-finetuned-conll03-english": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/tokenizer.json"
        ),
        "xlm-roberta-large-finetuned-conll03-german": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/tokenizer.json"
        ),
    },
}

__UpperCamelCase							:							Union[str, Any]    							=					{
    "xlm-roberta-base": 512,
    "xlm-roberta-large": 512,
    "xlm-roberta-large-finetuned-conll02-dutch": 512,
    "xlm-roberta-large-finetuned-conll02-spanish": 512,
    "xlm-roberta-large-finetuned-conll03-english": 512,
    "xlm-roberta-large-finetuned-conll03-german": 512,
}

class    __magic_name__						(  _SCREAMING_SNAKE_CASE):
     A:		List[Any]								=   VOCAB_FILES_NAMES
     A:		List[Any]								=   PRETRAINED_VOCAB_FILES_MAP
     A:		Optional[Any]								=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     A:		Optional[int]								=   ["input_ids", "attention_mask"]
     A:		Union[str, Any]								=   XLMRobertaTokenizer


     def __init__(   self				:  str				,						lowerCamelCase__				:  Union[str, Any]=None				,						lowerCamelCase__				:  Any=None				,						lowerCamelCase__				:  Union[str, Any]="<s>"				,						lowerCamelCase__				:  Tuple="</s>"				,						lowerCamelCase__				:  List[Any]="</s>"				,						lowerCamelCase__				:  Any="<s>"				,						lowerCamelCase__				:  str="<unk>"				,						lowerCamelCase__				:  int="<pad>"				,						lowerCamelCase__				:  Any="<mask>"				,						**lowerCamelCase__				:  str				,						)	->   Union[str, Any]:





      '''simple docstring'''






      UpperCamelCase__       :     List[str] 							= AddedToken(lowerCamelCase__				,						lstrip=lowerCamelCase__				,						rstrip=lowerCamelCase__      ) if isinstance(lowerCamelCase__				,						lowerCamelCase__      ) else mask_token

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

      UpperCamelCase__       :     Optional[int] 							= vocab_file
      UpperCamelCase__       :     str 							= False if not self.vocab_file else True


     def   UpperCAmelCase__						(   self				:  List[Any]				,						lowerCamelCase__				:  List[int]				,						lowerCamelCase__				:  Optional[List[int]] = None      )	->   Any:





      '''simple docstring'''






      if token_ids_a is None:
       return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
      UpperCamelCase__       :     Dict 							= [self.cls_token_id]
      UpperCamelCase__       :     Optional[int] 							= [self.sep_token_id]
      return cls + token_ids_a + sep + sep + token_ids_a + sep


     def   UpperCAmelCase__						(   self				:  Any				,						lowerCamelCase__				:  List[int]				,						lowerCamelCase__				:  Optional[List[int]] = None      )	->   List[Any]:





      '''simple docstring'''






      UpperCamelCase__       :     Union[str, Any] 							= [self.sep_token_id]
      UpperCamelCase__       :     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 + sep + token_ids_a + sep      ) * [0]


     def   UpperCAmelCase__						(   self				:  Dict				,						lowerCamelCase__				:  str				,						lowerCamelCase__				:  Optional[str] = None      )	->   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(lowerCamelCase__      ):
       logger.error(F"Vocabulary path ({save_directory}) should be a directory."      )
       return
      UpperCamelCase__       :     int 							= os.path.join(
          lowerCamelCase__				,						(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']      )

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

      return (out_vocab_file,)








def        __SCREAMING_SNAKE_CASE (	lowercase_   )							->						str:

    """simple docstring"""


    return " ".join(sorted(set(sentence.split()   )   )   )


if __name__ == "__main__":
 import doctest

 doctest.testmod()






