
'''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""": 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        UpperCAmelCase_       (						A							):

 '''simple docstring'''
 lowercase_				:						Union[str, Any]				=       VOCAB_FILES_NAMES
 lowercase_				:						Dict				=       PRETRAINED_VOCAB_FILES_MAP
 lowercase_				:						List[str]				=       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 lowercase_				:						List[str]				=       ["input_ids", "attention_mask"]
 lowercase_				:						Dict				=       XLMRobertaTokenizer







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



   '''simple docstring'''




   UpperCAmelCase__			:				Optional[int]												=       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__ ,							)

   UpperCAmelCase__			:				Optional[int]												=       vocab_file
   UpperCAmelCase__			:				Tuple												=       False if not self.vocab_file else True







 def        UpperCamelCase     (				self		:     int ,							snake_case__		:     List[int] ,							snake_case__		:     Optional[List[int]] = None   ):



   '''simple docstring'''




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







 def        UpperCamelCase     (				self		:     Union[str, Any] ,							snake_case__		:     List[int] ,							snake_case__		:     Optional[List[int]] = None   ):



   '''simple docstring'''




   UpperCAmelCase__			:				int												=       [self.sep_token_id]
   UpperCAmelCase__			:				Union[str, 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        UpperCamelCase     (				self		:     int ,							snake_case__		:     str ,							snake_case__		:     Optional[str] = None   ):



   '''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
   UpperCAmelCase__			:				Optional[int]												=       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'''





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


SCREAMING_SNAKE_CASE    =					{"""configuration_visual_bert""": ["""VISUAL_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """VisualBertConfig"""]}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE    =					[
          """VISUAL_BERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """VisualBertForMultipleChoice""",
          """VisualBertForPreTraining""",
          """VisualBertForQuestionAnswering""",
          """VisualBertForRegionToPhraseAlignment""",
          """VisualBertForVisualReasoning""",
          """VisualBertLayer""",
          """VisualBertModel""",
          """VisualBertPreTrainedModel""",
      ]


if TYPE_CHECKING:
      from .configuration_visual_bert import VISUAL_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, VisualBertConfig

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_visual_bert import (
                VISUAL_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                VisualBertForMultipleChoice,
                VisualBertForPreTraining,
                VisualBertForQuestionAnswering,
                VisualBertForRegionToPhraseAlignment,
                VisualBertForVisualReasoning,
                VisualBertLayer,
                VisualBertModel,
                VisualBertPreTrainedModel,
            )


else:
      import sys

      SCREAMING_SNAKE_CASE    =					_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



