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 					snake_case__       (				lowerCAmelCase__							):
   _SCREAMING_SNAKE_CASE	: List[str]						    =      VOCAB_FILES_NAMES
   _SCREAMING_SNAKE_CASE	: Optional[int]						    =      PRETRAINED_VOCAB_FILES_MAP
   _SCREAMING_SNAKE_CASE	: Tuple						    =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   _SCREAMING_SNAKE_CASE	: int						    =      ["input_ids", "attention_mask"]
   _SCREAMING_SNAKE_CASE	: Any						    =      XLMRobertaTokenizer



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




         '''simple docstring'''




         snake_case_     :			Any       =       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			,	)

         snake_case_     :			Any       =       vocab_file
         snake_case_     :			Union[str, Any]       =       False if not self.vocab_file else True



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




         '''simple docstring'''




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



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




         '''simple docstring'''




         snake_case_     :			Tuple       =       [self.sep_token_id]
         snake_case_     :			Dict       =       [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   :   int			,	A__   :   List[Any]			,	A__   :   Union[str, Any] = 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
         snake_case_     :			str       =       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,)




from __future__ import annotations

UpperCAmelCase							=       "Alexander Joslin"






def 					SCREAMING_SNAKE_CASE_			(		lowerCAmelCase_: int     ):

      if number <= 0:
            snake_case_     :			Dict       =       f"n must be greater than 0. Got n = {number}"
            raise ValueError(lowerCAmelCase_     )

      snake_case_     :			Tuple       =       [number + 1] * (number + 1)

      # starting position
      snake_case_     :			Union[str, Any]       =       0
      for i in range(1 ,	lowerCAmelCase_     ):
            snake_case_     :			int       =       min(table[i + 1] ,	table[i] + 1     )
            # check if out of bounds
            if i * 2 <= number:
                  snake_case_     :			Tuple       =       min(table[i * 2] ,	table[i] + 1     )
            # check if out of bounds
            if i * 3 <= number:
                  snake_case_     :			Dict       =       min(table[i * 3] ,	table[i] + 1     )
      return table[number]


if __name__ == "__main__":
     import doctest

     doctest.testmod()



