

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__	:       Optional[Any]			      =      None


UpperCAmelCase__	:       int			      =      logging.get_logger(__name__)

UpperCAmelCase__	:       List[str]			      =      {"""vocab_file""": """sentencepiece.bpe.model""", """tokenizer_file""": """tokenizer.json"""}

UpperCAmelCase__	:       Dict			      =      {
    """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__	:       int			      =      {
    """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     a__    (				UpperCAmelCase    ):







  """simple docstring"""




  UpperCAmelCase__ :	Optional[int]         =VOCAB_FILES_NAMES
  UpperCAmelCase__ :	Union[str, Any]         =PRETRAINED_VOCAB_FILES_MAP
  UpperCAmelCase__ :	Any         =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  UpperCAmelCase__ :	Tuple         =["""input_ids""", """attention_mask"""]
  UpperCAmelCase__ :	Optional[Any]         =XLMRobertaTokenizer


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







        SCREAMING_SNAKE_CASE	: Any					       =				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	: int					       =				vocab_file
        SCREAMING_SNAKE_CASE	: Optional[int]					       =				False if not self.vocab_file else True


  def 	_lowercase (     self      :	List[Any]			,			UpperCAmelCase__      :	List[int]			,			UpperCAmelCase__      :	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	: List[str]					       =				[self.sep_token_id]
        return cls + token_ids_a + sep + sep + token_ids_a + sep


  def 	_lowercase (     self      :	Dict			,			UpperCAmelCase__      :	List[int]			,			UpperCAmelCase__      :	Optional[List[int]] = None						)   ->List[int]:
        """simple docstring"""







        SCREAMING_SNAKE_CASE	: Tuple					       =				[self.sep_token_id]
        SCREAMING_SNAKE_CASE	: 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 	_lowercase (     self      :	int			,			UpperCAmelCase__      :	str			,			UpperCAmelCase__      :	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	: str					       =				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,)







import os
import unittest

import pytest
from parameterized import parameterized

from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device


# skipping in unittest tests

UpperCAmelCase__	:       Dict			      =      [(1,)]






def    __lowercase (       )       ->  Tuple:
      SCREAMING_SNAKE_CASE	: Optional[Any]					       =				bool(os.getenv("""RUN_SLOW"""  ,      0     )     )
      if run_slow:
            assert True
      else:
            assert False, "should have been skipped"






def    __lowercase (       )       ->  Optional[Any]:
      SCREAMING_SNAKE_CASE	: Dict					       =				bool(os.getenv("""RUN_SLOW"""  ,      0     )     )
      if run_slow and torch_device == "cuda":
            assert True
      else:
            assert False, "should have been skipped"







@require_torch
class     a__    (				unittest.TestCase    ):







  """simple docstring"""




  @slow
  @require_torch_gpu
  def 	_lowercase (     self      :	Any						)   ->Optional[Any]:
        """simple docstring"""







        check_slow_torch_cuda()


  @require_torch_gpu
  @slow
  def 	_lowercase (     self      :	Optional[Any]						)   ->Any:
        """simple docstring"""







        check_slow_torch_cuda()




  @parameterized.expand(UpperCAmelCase__						)
  @slow
  def 	_lowercase (     self      :	Optional[int]			,			UpperCAmelCase__      :	Dict=None						)   ->Optional[Any]:
        """simple docstring"""







        check_slow()






@slow
@require_torch_gpu
def    __lowercase (       )       ->  Optional[int]:
      check_slow_torch_cuda()






@require_torch_gpu
@slow
def    __lowercase (       )       ->  int:
      check_slow_torch_cuda()






@slow
@pytest.mark.parametrize("""param"""  ,      [1]     )
def    __lowercase (       _A     )       ->  Optional[int]:
      check_slow()







@pytest.mark.parametrize("""param"""  ,      [1]     )
@slow
def    __lowercase (       _A     )       ->  str:
      check_slow()




