
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:
				lowercase__				:				Dict						=      None


lowercase__				:				Any						=      logging.get_logger(__name__)

lowercase__				:				Union[str, Any]						=      {"vocab_file": "sentencepiece.bpe.model", "tokenizer_file": "tokenizer.json"}

lowercase__				:				str						=      {
    "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"
        ),
    },
}

lowercase__				:				Optional[Any]						=      {
    "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 							SCREAMING_SNAKE_CASE__     (				A__     ):

							"""simple docstring"""






							_snake_case  		=	VOCAB_FILES_NAMES
							_snake_case  		=	PRETRAINED_VOCAB_FILES_MAP
							_snake_case  		=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							_snake_case  		=	['''input_ids''', '''attention_mask''']
							_snake_case  		=	XLMRobertaTokenizer



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





													'''simple docstring'''






													__UpperCamelCase  	=      AddedToken(SCREAMING_SNAKE_CASE_  ,						lstrip=SCREAMING_SNAKE_CASE_  ,						rstrip=SCREAMING_SNAKE_CASE_      ) if isinstance(SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_      ) else mask_token

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

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



							def      A__		(	self  ,						SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_ = None      )-> Optional[Any]:





													'''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      A__		(	self  ,						SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_ = None      )-> Tuple:





													'''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      A__		(	self  ,						SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_ = None      )-> Optional[Any]:





													'''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(SCREAMING_SNAKE_CASE_      ):
																			logger.error(F"Vocabulary path ({save_directory}) should be a directory."      )
																			return
													__UpperCamelCase  	=      os.path.join(
													    SCREAMING_SNAKE_CASE_  ,						(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']      )

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

													return (out_vocab_file,)






'''simple docstring'''







from ..utils import DummyObject, requires_backends







class 		snake_case_       (						metaclass=A__						):



   """simple docstring"""





   __lowerCAmelCase	:							List[str]								=['''torch''', '''librosa''']







   def __init__( self			,   *UpperCamelCase			,   **UpperCamelCase):
          requires_backends(self			,   ["torch", "librosa"])







   @classmethod
   def     __UpperCAmelCase      ( cls			,   *UpperCamelCase			,   **UpperCamelCase):
          requires_backends(cls			,   ["torch", "librosa"])







   @classmethod
   def     __UpperCAmelCase      ( cls			,   *UpperCamelCase			,   **UpperCamelCase):
          requires_backends(cls			,   ["torch", "librosa"])







class 		snake_case_       (						metaclass=A__						):



   """simple docstring"""





   __lowerCAmelCase	:							Union[str, Any]								=['''torch''', '''librosa''']







   def __init__( self			,   *UpperCamelCase			,   **UpperCamelCase):
          requires_backends(self			,   ["torch", "librosa"])







   @classmethod
   def     __UpperCAmelCase      ( cls			,   *UpperCamelCase			,   **UpperCamelCase):
          requires_backends(cls			,   ["torch", "librosa"])







   @classmethod
   def     __UpperCAmelCase      ( cls			,   *UpperCamelCase			,   **UpperCamelCase):
          requires_backends(cls			,   ["torch", "librosa"])

