



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       =     None


_UpperCAmelCase       =     logging.get_logger(__name__)

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

_UpperCAmelCase       =     {
    """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       =     {
    """xlm-roberta-base""": 5_1_2,
    """xlm-roberta-large""": 5_1_2,
    """xlm-roberta-large-finetuned-conll02-dutch""": 5_1_2,
    """xlm-roberta-large-finetuned-conll02-spanish""": 5_1_2,
    """xlm-roberta-large-finetuned-conll03-english""": 5_1_2,
    """xlm-roberta-large-finetuned-conll03-german""": 5_1_2,
}
class    a		(					lowerCAmelCase__    ):
  UpperCamelCase		:			Dict         =   VOCAB_FILES_NAMES
  UpperCamelCase		:			List[str]         =   PRETRAINED_VOCAB_FILES_MAP
  UpperCamelCase		:			List[Any]         =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  UpperCamelCase		:			Dict         =   ["input_ids", "attention_mask"]
  UpperCamelCase		:			List[str]         =   XLMRobertaTokenizer



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


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_:	int            =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    ,						**_UpperCAmelCase    ,						)

     SCREAMING_SNAKE_CASE_:	List[Any]            =vocab_file
     SCREAMING_SNAKE_CASE_:	List[Any]            =False if not self.vocab_file else True



  def 		lowerCamelCase__    (  self	:   Union[str, Any]    ,						lowerCAmelCase	:   List[int]    ,						lowerCAmelCase	:   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]
     SCREAMING_SNAKE_CASE_:	Dict            =[self.cls_token_id]
     SCREAMING_SNAKE_CASE_:	Any            =[self.sep_token_id]
     return cls + token_ids_a + sep + sep + token_ids_a + sep



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


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_:	Optional[int]            =[self.sep_token_id]
     SCREAMING_SNAKE_CASE_:	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 		lowerCamelCase__    (  self	:   str    ,						lowerCAmelCase	:   str    ,						lowerCAmelCase	:   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
     SCREAMING_SNAKE_CASE_:	Tuple            =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,)








"""simple docstring"""
def        __magic_name__			(							lowercase = 1000	):
   SCREAMING_SNAKE_CASE_:	Dict            =0
   SCREAMING_SNAKE_CASE_:	Any            =0
   while 1:
      num += 3
      if num >= n:
         break
      total += num
      num += 2
      if num >= n:
         break
      total += num
      num += 1
      if num >= n:
         break
      total += num
      num += 3
      if num >= n:
         break
      total += num
      num += 1
      if num >= n:
         break
      total += num
      num += 2
      if num >= n:
         break
      total += num
      num += 3
      if num >= n:
         break
      total += num
   return total


if __name__ == "__main__":
   print(f"""{solution() = }""")



