





import warnings

from ...utils import logging
from .image_processing_deformable_detr import DeformableDetrImageProcessor


lowercase				:	List[str]      						=  logging.get_logger(__name__)





class 			A__   (							__UpperCAmelCase     ):




   """simple docstring"""



   def __init__( self ,  *lowercase ,  **lowercase)      ->						None:







          '''simple docstring'''

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









import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mvp import MvpTokenizer


lowercase				:	List[Any]      						=  logging.get_logger(__name__)


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

# See all MVP models at https://huggingface.co/models?filter=mvp
lowercase				:	Optional[Any]      						=  {
    """vocab_file""": {
        """RUCAIBox/mvp""": """https://huggingface.co/RUCAIBox/mvp/resolve/main/vocab.json""",
    },
    """added_tokens.json""": {
        """RUCAIBox/mvp""": """https://huggingface.co/RUCAIBox/mvp/resolve/main/added_tokens.json""",
    },
    """merges_file""": {
        """RUCAIBox/mvp""": """https://huggingface.co/RUCAIBox/mvp/resolve/main/merges.txt""",
    },
    """tokenizer_file""": {
        """RUCAIBox/mvp""": """https://huggingface.co/RUCAIBox/mvp/resolve/main/tokenizer.json""",
    },
}

lowercase				:	List[str]      						=  {
    """RUCAIBox/mvp""": 1_0_2_4,
}





class 			A__   (							__UpperCAmelCase     ):




   """simple docstring"""



   __A       :    Dict	  =  VOCAB_FILES_NAMES
   __A       :    str	  =  PRETRAINED_VOCAB_FILES_MAP
   __A       :    Tuple	  =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   __A       :    Any	  =  ['''input_ids''', '''attention_mask''']
   __A       :    Tuple	  =  MvpTokenizer

   def __init__( self ,  lowercase=None ,  lowercase=None ,  lowercase=None ,  lowercase="replace" ,  lowercase="<s>" ,  lowercase="</s>" ,  lowercase="</s>" ,  lowercase="<s>" ,  lowercase="<unk>" ,  lowercase="<pad>" ,  lowercase="<mask>" ,  lowercase=False ,  lowercase=True ,  **lowercase ,  )      ->						str:







          '''simple docstring'''

          super().__init__(
              lowercase ,  lowercase ,  tokenizer_file=lowercase ,  errors=lowercase ,  bos_token=lowercase ,  eos_token=lowercase ,  sep_token=lowercase ,  cls_token=lowercase ,  unk_token=lowercase ,  pad_token=lowercase ,  mask_token=lowercase ,  add_prefix_space=lowercase ,  trim_offsets=lowercase ,  **lowercase ,  )

          a__						:     Optional[int]			=    json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__())
          if pre_tok_state.get('add_prefix_space' ,  lowercase) != add_prefix_space:
                 a__						:     Dict			=    getattr(lowercase ,  pre_tok_state.pop('type'))
                 a__						:     str			=    add_prefix_space
                 a__						:     Union[str, Any]			=    pre_tok_class(**lowercase)

          a__						:     List[Any]			=    add_prefix_space

          # the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
          a__						:     Optional[int]			=    'post_processor'
          a__						:     Optional[int]			=    getattr(self.backend_tokenizer ,  lowercase ,  lowercase)
          if tokenizer_component_instance:
                 a__						:     str			=    json.loads(tokenizer_component_instance.__getstate__())

                 # The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
                 if "sep" in state:
                        a__						:     Any			=    tuple(state['sep'])
                 if "cls" in state:
                        a__						:     str			=    tuple(state['cls'])

                 a__						:     List[str]			=    False

                 if state.get('add_prefix_space' ,  lowercase) != add_prefix_space:
                        a__						:     List[str]			=    add_prefix_space
                        a__						:     List[str]			=    True

                 if state.get('trim_offsets' ,  lowercase) != trim_offsets:
                        a__						:     Optional[int]			=    trim_offsets
                        a__						:     List[str]			=    True

                 if changes_to_apply:
                        a__						:     Optional[int]			=    getattr(lowercase ,  state.pop('type'))
                        a__						:     Tuple			=    component_class(**lowercase)
                        setattr(self.backend_tokenizer ,  lowercase ,  lowercase)

   @property
   def 							__lowercase		( self)      ->						str:







          '''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 							__lowercase		( self ,  lowercase)      ->						Any:







          '''simple docstring'''

          a__						:     Tuple			=    AddedToken(lowercase ,  lstrip=lowercase ,  rstrip=lowercase) if isinstance(lowercase ,  lowercase) else value
          a__						:     str			=    value

   def 							__lowercase		( self ,  *lowercase ,  **lowercase)      ->						BatchEncoding:







          '''simple docstring'''

          a__						:     Optional[Any]			=    kwargs.get('is_split_into_words' ,  lowercase)

          if is_split_into_words and not self.add_prefix_space:
                 raise ValueError(
                     F'You need to instantiate {self.__class__.__name__} with add_prefix_space=True '
                     'to use it with pretokenized inputs.')

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

   def 							__lowercase		( self ,  *lowercase ,  **lowercase)      ->						BatchEncoding:







          '''simple docstring'''

          a__						:     List[str]			=    kwargs.get('is_split_into_words' ,  lowercase)

          if is_split_into_words and not self.add_prefix_space:
                 raise ValueError(
                     F'You need to instantiate {self.__class__.__name__} with add_prefix_space=True '
                     'to use it with pretokenized inputs.')

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

   def 							__lowercase		( self ,  lowercase ,  lowercase = None)      ->						Tuple[str]:







          '''simple docstring'''

          a__						:     List[str]			=    self._tokenizer.model.save(lowercase ,  name=lowercase)
          return tuple(lowercase)

   def 							__lowercase		( self ,  lowercase ,  lowercase=None)      ->						Union[str, Any]:







          '''simple docstring'''

          a__						:     List[Any]			=    [self.bos_token_id] + token_ids_a + [self.eos_token_id]
          if token_ids_a is None:
                 return output

          return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]

   def 							__lowercase		( self ,  lowercase ,  lowercase = None)      ->						List[int]:







          '''simple docstring'''

          a__						:     int			=    [self.sep_token_id]
          a__						:     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]


