




"""simple docstring"""



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:
      SCREAMING_SNAKE_CASE       = None


SCREAMING_SNAKE_CASE       = logging.get_logger(__name__)

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

SCREAMING_SNAKE_CASE       = {
    "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"
        ),
    },
}

SCREAMING_SNAKE_CASE       = {
    "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 			UpperCAmelCase_						(		A_							):
    lowercase__		      =   VOCAB_FILES_NAMES
    lowercase__		      =   PRETRAINED_VOCAB_FILES_MAP
    lowercase__		      =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    lowercase__		      =   ['''input_ids''', '''attention_mask''']
    lowercase__		      =   XLMRobertaTokenizer




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




     '''simple docstring'''

     A__ =       AddedToken(snake_case_			,				lstrip=snake_case_			,				rstrip=snake_case_   ) if isinstance(snake_case_			,				snake_case_   ) else mask_token

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

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




    def 							__magic_name__							(					self		: Optional[int]			,				snake_case_		: List[int]			,				snake_case_		: 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]
     A__ =       [self.cls_token_id]
     A__ =       [self.sep_token_id]
     return cls + token_ids_a + sep + sep + token_ids_a + sep




    def 							__magic_name__							(					self		: Union[str, Any]			,				snake_case_		: List[int]			,				snake_case_		: Optional[List[int]] = None   )   ->							List[int]:




     '''simple docstring'''

     A__ =       [self.sep_token_id]
     A__ =       [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 							__magic_name__							(					self		: Optional[int]			,				snake_case_		: str			,				snake_case_		: 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(snake_case_   ):
      logger.error(F"""Vocabulary path ({save_directory}) should be a directory."""   )
      return
     A__ =       os.path.join(
         snake_case_			,				(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]   )

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

     return (out_vocab_file,)











"""simple docstring"""



def 						_SCREAMING_SNAKE_CASE     (							lowercase_		)		->	str:
 return " ".join(sorted(set(sentence.split()		)		)		)


if __name__ == "__main__":
      import doctest

      doctest.testmod()





