


'''simple docstring'''






import json
from typing import TYPE_CHECKING, List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_deberta import DebertaTokenizer


if TYPE_CHECKING:
 from transformers.pipelines.conversational import Conversation


lowercase							=logging.get_logger(__name__)

lowercase							={'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

lowercase							={
    'vocab_file': {
        'microsoft/deberta-base': 'https://huggingface.co/microsoft/deberta-base/resolve/main/vocab.json',
        'microsoft/deberta-large': 'https://huggingface.co/microsoft/deberta-large/resolve/main/vocab.json',
        'microsoft/deberta-xlarge': 'https://huggingface.co/microsoft/deberta-xlarge/resolve/main/vocab.json',
        'microsoft/deberta-base-mnli': 'https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/vocab.json',
        'microsoft/deberta-large-mnli': 'https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/vocab.json',
        'microsoft/deberta-xlarge-mnli': (
            'https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/vocab.json'
        ),
    },
    'merges_file': {
        'microsoft/deberta-base': 'https://huggingface.co/microsoft/deberta-base/resolve/main/merges.txt',
        'microsoft/deberta-large': 'https://huggingface.co/microsoft/deberta-large/resolve/main/merges.txt',
        'microsoft/deberta-xlarge': 'https://huggingface.co/microsoft/deberta-xlarge/resolve/main/merges.txt',
        'microsoft/deberta-base-mnli': 'https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/merges.txt',
        'microsoft/deberta-large-mnli': 'https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/merges.txt',
        'microsoft/deberta-xlarge-mnli': (
            'https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/merges.txt'
        ),
    },
}

lowercase							={
    'microsoft/deberta-base': 512,
    'microsoft/deberta-large': 512,
    'microsoft/deberta-xlarge': 512,
    'microsoft/deberta-base-mnli': 512,
    'microsoft/deberta-large-mnli': 512,
    'microsoft/deberta-xlarge-mnli': 512,
}

lowercase							={
    'microsoft/deberta-base': {'do_lower_case': False},
    'microsoft/deberta-large': {'do_lower_case': False},
}






class 					__magic_name__							(		__SCREAMING_SNAKE_CASE				):
       UpperCAmelCase						      =VOCAB_FILES_NAMES
       UpperCAmelCase						      =PRETRAINED_VOCAB_FILES_MAP
       UpperCAmelCase						      =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       UpperCAmelCase						      =["input_ids", "attention_mask", "token_type_ids"]
       UpperCAmelCase						      =DebertaTokenizer






       def __init__(			self  ,							snake_case=None  ,							snake_case=None  ,							snake_case=None  ,							snake_case="replace"  ,							snake_case="[CLS]"  ,							snake_case="[SEP]"  ,							snake_case="[SEP]"  ,							snake_case="[CLS]"  ,							snake_case="[UNK]"  ,							snake_case="[PAD]"  ,							snake_case="[MASK]"  ,							snake_case=False  ,							**snake_case  ,							)						->  Dict:




          '''simple docstring'''
          super().__init__(
              lowerCAmelCase__  ,							lowerCAmelCase__  ,							tokenizer_file=lowerCAmelCase__  ,							errors=lowerCAmelCase__  ,							bos_token=lowerCAmelCase__  ,							eos_token=lowerCAmelCase__  ,							unk_token=lowerCAmelCase__  ,							sep_token=lowerCAmelCase__  ,							cls_token=lowerCAmelCase__  ,							pad_token=lowerCAmelCase__  ,							mask_token=lowerCAmelCase__  ,							add_prefix_space=lowerCAmelCase__  ,							**lowerCAmelCase__  ,							)
          _UpperCAmelCase   :   Optional[int]							    =kwargs.pop('add_bos_token'  ,							lowerCAmelCase__)

          _UpperCAmelCase   :   str							    =json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__())
          if pre_tok_state.get('add_prefix_space'  ,							lowerCAmelCase__) != add_prefix_space:
             _UpperCAmelCase   :   int							    =getattr(lowerCAmelCase__  ,							pre_tok_state.pop('type'))
             _UpperCAmelCase   :   Tuple							    =add_prefix_space
             _UpperCAmelCase   :   List[str]							    =pre_tok_class(**lowerCAmelCase__)

          _UpperCAmelCase   :   Optional[Any]							    =add_prefix_space






       @property
       def 			lowerCAmelCase		(			self)						->  Tuple:




          '''simple docstring'''




          if self._mask_token is None:
             if self.verbose:
                logger.error('Using mask_token, but it is not set yet.')
             return None
          return str(self._mask_token)






       @mask_token.setter
       def 			lowerCAmelCase		(			self  ,							snake_case)						->  str:




          '''simple docstring'''
          _UpperCAmelCase   :   Optional[Any]							    =AddedToken(lowerCAmelCase__  ,							lstrip=lowerCAmelCase__  ,							rstrip=lowerCAmelCase__) if isinstance(lowerCAmelCase__  ,							lowerCAmelCase__) else value
          _UpperCAmelCase   :   str							    =value






       def 			lowerCAmelCase		(			self  ,							snake_case  ,							snake_case = None)						->  Optional[int]:




          '''simple docstring'''




          if token_ids_a is None:
             return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
          _UpperCAmelCase   :   Union[str, Any]							    =[self.cls_token_id]
          _UpperCAmelCase   :   List[Any]							    =[self.sep_token_id]
          return cls + token_ids_a + sep + token_ids_a + sep






       def 			lowerCAmelCase		(			self  ,							snake_case  ,							snake_case = None)						->  Dict:




          '''simple docstring'''
          _UpperCAmelCase   :   Tuple							    =[self.sep_token_id]
          _UpperCAmelCase   :   Tuple							    =[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) * [0] + len(token_ids_a + sep) * [1]






       def 			lowerCAmelCase		(			self  ,							*snake_case  ,							**snake_case)						->  Dict:




          '''simple docstring'''
          _UpperCAmelCase   :   str							    =kwargs.get('is_split_into_words'  ,							lowerCAmelCase__)
          assert self.add_prefix_space or not is_split_into_words, (
              f"You need to instantiate {self.__class__.__name__} with add_prefix_space=True "
              "to use it with pretokenized inputs."
          )

          return super()._batch_encode_plus(*lowerCAmelCase__  ,							**lowerCAmelCase__)






       def 			lowerCAmelCase		(			self  ,							*snake_case  ,							**snake_case)						->  int:




          '''simple docstring'''
          _UpperCAmelCase   :   Tuple							    =kwargs.get('is_split_into_words'  ,							lowerCAmelCase__)

          assert self.add_prefix_space or not is_split_into_words, (
              f"You need to instantiate {self.__class__.__name__} with add_prefix_space=True "
              "to use it with pretokenized inputs."
          )

          return super()._encode_plus(*lowerCAmelCase__  ,							**lowerCAmelCase__)






       def 			lowerCAmelCase		(			self  ,							snake_case  ,							snake_case = None)						->  Optional[int]:




          '''simple docstring'''
          _UpperCAmelCase   :   Tuple							    =self._tokenizer.model.save(lowerCAmelCase__  ,							name=lowerCAmelCase__)
          return tuple(lowerCAmelCase__)






       def 			lowerCAmelCase		(			self  ,							snake_case)						->  Union[str, Any]:




          '''simple docstring'''
          _UpperCAmelCase   :   Dict							    =[]
          for is_user, text in conversation.iter_texts():
             input_ids.extend(self.encode(lowerCAmelCase__  ,							add_special_tokens=lowerCAmelCase__) + [self.eos_token_id])

          if len(lowerCAmelCase__) > self.model_max_length:
             _UpperCAmelCase   :   Optional[Any]							    =input_ids[-self.model_max_length :]
          return input_ids





import warnings

from ...utils import logging
from .image_processing_vilt import ViltImageProcessor


lowerCAmelCase__       :	int     				=logging.get_logger(__name__)







class      __lowercase  (__SCREAMING_SNAKE_CASE   ):





							"""simple docstring"""







							def __init__(	self       ,		*lowerCAmelCase__       ,		**lowerCAmelCase__    ):





										"""simple docstring"""




										warnings.warn(
										    'The class ViltFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
										    ' use ViltImageProcessor instead.'       ,		lowerCAmelCase__       ,		)
										super().__init__(*lowerCAmelCase__       ,		**lowerCAmelCase__    )





