from typing import Dict, List, Optional, Tuple

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


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







class __snake_case							(		lowerCamelCase_						):
   lowerCAmelCase_								=				["input_ids", "attention_mask"]




   def __init__(       self     :							List[str]			,      _lowercase     :							Tuple="[PAD]"			,      _lowercase     :							Optional[Any]="[BOS]"			,      _lowercase     :							Tuple="[EOS]"			,      _lowercase     :							Dict="[MASK]"			,      _lowercase     :							List[str]="[CLS]"			,      _lowercase     :							Optional[Any]="[SEP]"			,      _lowercase     :							List[Any]=20_48			,      **_lowercase     :							str			,      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__     				= AddedToken(_lowercase			,      lstrip=_lowercase			,      rstrip=_lowercase ) if isinstance(_lowercase			,      _lowercase ) else pad_token
     SCREAMING_SNAKE_CASE__     				= AddedToken(_lowercase			,      lstrip=_lowercase			,      rstrip=_lowercase ) if isinstance(_lowercase			,      _lowercase ) else bos_token
     SCREAMING_SNAKE_CASE__     				= AddedToken(_lowercase			,      lstrip=_lowercase			,      rstrip=_lowercase ) if isinstance(_lowercase			,      _lowercase ) else eos_token
     SCREAMING_SNAKE_CASE__     				= AddedToken(_lowercase			,      lstrip=_lowercase			,      rstrip=_lowercase ) if isinstance(_lowercase			,      _lowercase ) else mask_token
     SCREAMING_SNAKE_CASE__     				= AddedToken(_lowercase			,      lstrip=_lowercase			,      rstrip=_lowercase ) if isinstance(_lowercase			,      _lowercase ) else cls_token
     SCREAMING_SNAKE_CASE__     				= AddedToken(_lowercase			,      lstrip=_lowercase			,      rstrip=_lowercase ) if isinstance(_lowercase			,      _lowercase ) else sep_token

     super().__init__(
         pad_token=_lowercase			,      bos_token=_lowercase			,      eos_token=_lowercase			,      mask_token=_lowercase			,      cls_token=_lowercase			,      sep_token=_lowercase			,      model_max_length=_lowercase			,      **_lowercase			,      )

     SCREAMING_SNAKE_CASE__     				= 2**8  # utf is 8 bits

     # define special tokens dict
     SCREAMING_SNAKE_CASE__     				= {
         self.pad_token: 0,
         self.bos_token: 1,
         self.eos_token: 2,
         self.mask_token: 3,
         self.cls_token: 4,
         self.sep_token: 5,
     }
     SCREAMING_SNAKE_CASE__     				= len(self.special_tokens_encoder )
     SCREAMING_SNAKE_CASE__     				= {v: k for k, v in self.special_tokens_encoder.items()}




   def       __a		(       self     :							List[str] ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__     				= self.special_tokens_encoder.copy()
     vocab.update(self.added_tokens_encoder )
     for i in range(self._utf_vocab_size ):
       SCREAMING_SNAKE_CASE__     				= chr(_lowercase )
       SCREAMING_SNAKE_CASE__     				= i + len(self.special_tokens_encoder )
     return vocab




   @property
   def       __a		(       self     :							Optional[Any] ):



     """simple docstring"""






     return self._utf_vocab_size + self._num_special_tokens




   def       __a		(       self     :							List[Any]			,      _lowercase     :							List[int]			,      _lowercase     :							Optional[List[int]] = None			,      _lowercase     :							bool = False ):



     """simple docstring"""






     if already_has_special_tokens:
       return super().get_special_tokens_mask(
           token_ids_a=_lowercase			,      token_ids_a=_lowercase			,      already_has_special_tokens=_lowercase )

     # normal case: some special tokens
     if token_ids_a is None:
       return [1] + [0] * len(_lowercase ) + [1]
     return [1] + ([0] * len(_lowercase )) + [1] + ([0] * len(_lowercase )) + [1]




   def       __a		(       self     :							Tuple			,      _lowercase     :							List[int]			,      _lowercase     :							Optional[List[int]] = None ):



     """simple docstring"""






     if token_ids_a is None:
       return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
     else:
       return [self.cls_token_id] + token_ids_a + [self.sep_token_id] + token_ids_a + [self.sep_token_id]




   def       __a		(       self     :							Optional[Any]			,      _lowercase     :							str ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__     				= [chr(_lowercase ) for i in text.encode("""utf-8""" )]
     return tokens




   def       __a		(       self     :							Tuple			,      _lowercase     :							str ):



     """simple docstring"""






     if token in self.special_tokens_encoder:
       SCREAMING_SNAKE_CASE__     				= self.special_tokens_encoder[token]
     elif token in self.added_tokens_encoder:
       SCREAMING_SNAKE_CASE__     				= self.added_tokens_encoder[token]
     elif len(_lowercase ) != 1:
       SCREAMING_SNAKE_CASE__     				= self.unk_token_id
     else:
       SCREAMING_SNAKE_CASE__     				= ord(_lowercase ) + self._num_special_tokens
     return token_id




   def       __a		(       self     :							Tuple			,      _lowercase     :							Union[str, Any] ):



     """simple docstring"""






     if index in self.special_tokens_decoder:
       SCREAMING_SNAKE_CASE__     				= self.special_tokens_decoder[index]
     elif index in self.added_tokens_decoder:
       SCREAMING_SNAKE_CASE__     				= self.added_tokens_decoder[index]
     else:
       SCREAMING_SNAKE_CASE__     				= chr(index - self._num_special_tokens )
     return token




   def       __a		(       self     :							int			,      _lowercase     :							Dict ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__     				= b""""""
     for token in tokens:
       if token in self.special_tokens_decoder:
         SCREAMING_SNAKE_CASE__     				= self.special_tokens_decoder[token].encode("""utf-8""" )
       elif token in self.added_tokens_decoder:
         SCREAMING_SNAKE_CASE__     				= self.special_tokens_decoder[token].encode("""utf-8""" )
       elif token in self.special_tokens_encoder:
         SCREAMING_SNAKE_CASE__     				= token.encode("""utf-8""" )
       elif token in self.added_tokens_encoder:
         SCREAMING_SNAKE_CASE__     				= token.encode("""utf-8""" )
       else:
         SCREAMING_SNAKE_CASE__     				= bytes([ord(_lowercase )] )
       bstring += tok_string
     SCREAMING_SNAKE_CASE__     				= bstring.decode("""utf-8"""			,      errors="""replace""" )
     return string




   def       __a		(       self     :							int			,      _lowercase     :							str			,      _lowercase     :							Optional[str] = None ):



     """simple docstring"""






     return ()

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


__lowerCamelCase     :					Optional[int]				  =						{'''configuration_vilt''': ['''VILT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViltConfig''']}

try:
   if not is_vision_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __lowerCamelCase     :					Dict				  =						['''ViltFeatureExtractor''']
   __lowerCamelCase     :					Dict				  =						['''ViltImageProcessor''']
   __lowerCamelCase     :					str				  =						['''ViltProcessor''']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __lowerCamelCase     :					Any				  =						[
       '''VILT_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''ViltForImageAndTextRetrieval''',
       '''ViltForImagesAndTextClassification''',
       '''ViltForTokenClassification''',
       '''ViltForMaskedLM''',
       '''ViltForQuestionAnswering''',
       '''ViltLayer''',
       '''ViltModel''',
       '''ViltPreTrainedModel''',
   ]


if TYPE_CHECKING:
   from .configuration_vilt import VILT_PRETRAINED_CONFIG_ARCHIVE_MAP, ViltConfig

   try:
      if not is_vision_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .feature_extraction_vilt import ViltFeatureExtractor
      from .image_processing_vilt import ViltImageProcessor
      from .processing_vilt import ViltProcessor

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_vilt import (
          VILT_PRETRAINED_MODEL_ARCHIVE_LIST,
          ViltForImageAndTextRetrieval,
          ViltForImagesAndTextClassification,
          ViltForMaskedLM,
          ViltForQuestionAnswering,
          ViltForTokenClassification,
          ViltLayer,
          ViltModel,
          ViltPreTrainedModel,
      )


else:
   import sys

   __lowerCamelCase     :					List[str]				  =						_LazyModule(__name__, globals()['''__file__'''], _import_structure)
