



'''simple docstring'''





import warnings

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding






class 			lowerCAmelCase_(							__lowerCAmelCase	):
  '''simple docstring'''




  __lowercase				: Any           = ['''image_processor''', '''tokenizer''']
  __lowercase				: Optional[int]           = '''ViTImageProcessor'''
  __lowercase				: int           = ('''CLIPTokenizer''', '''CLIPTokenizerFast''')




  def __init__(       self    ,__UpperCAmelCase=None    ,__UpperCAmelCase=None    ,**__UpperCAmelCase )       ->						Any:
      lowerCAmelCase__					:    Any				 =   None
      if "feature_extractor" in kwargs:
          warnings.warn(
              """The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"""
              """ instead."""    ,_UpperCAmelCase    ,)
          lowerCAmelCase__					:    List[Any]				 =   kwargs.pop("""feature_extractor""" )

      lowerCAmelCase__					:    Tuple				 =   image_processor if image_processor is not None else feature_extractor
      if image_processor is None:
          raise ValueError("""You need to specify an `image_processor`.""" )
      if tokenizer is None:
          raise ValueError("""You need to specify a `tokenizer`.""" )

      super().__init__(_UpperCAmelCase    ,_UpperCAmelCase )




  def __call__(       self    ,__UpperCAmelCase=None    ,__UpperCAmelCase=None    ,__UpperCAmelCase=None    ,__UpperCAmelCase=None    ,**__UpperCAmelCase )       ->						List[Any]:
      if text is None and visual_prompt is None and images is None:
          raise ValueError("""You have to specify either text, visual prompt or images.""" )

      if text is not None and visual_prompt is not None:
          raise ValueError("""You have to specify exactly one type of prompt. Either text or visual prompt.""" )

      if text is not None:
          lowerCAmelCase__					:    Union[str, Any]				 =   self.tokenizer(_UpperCAmelCase    ,return_tensors=_UpperCAmelCase    ,**_UpperCAmelCase )

      if visual_prompt is not None:
          lowerCAmelCase__					:    List[Any]				 =   self.image_processor(_UpperCAmelCase    ,return_tensors=_UpperCAmelCase    ,**_UpperCAmelCase )

      if images is not None:
          lowerCAmelCase__					:    List[str]				 =   self.image_processor(_UpperCAmelCase    ,return_tensors=_UpperCAmelCase    ,**_UpperCAmelCase )

      if visual_prompt is not None and images is not None:
          lowerCAmelCase__					:    Tuple				 =   {
              """pixel_values""": image_features.pixel_values,
              """conditional_pixel_values""": prompt_features.pixel_values,
          }
          return encoding
      elif text is not None and images is not None:
          lowerCAmelCase__					:    Optional[Any]				 =   image_features.pixel_values
          return encoding
      elif text is not None:
          return encoding
      elif visual_prompt is not None:
          lowerCAmelCase__					:    int				 =   {
              """conditional_pixel_values""": prompt_features.pixel_values,
          }
          return encoding
      else:
          return BatchEncoding(data=dict(**_UpperCAmelCase )    ,tensor_type=_UpperCAmelCase )




  def 				UpperCAmelCase_      (       self    ,*__UpperCAmelCase    ,**__UpperCAmelCase )       ->						Any:
      return self.tokenizer.batch_decode(*_UpperCAmelCase    ,**_UpperCAmelCase )




  def 				UpperCAmelCase_      (       self    ,*__UpperCAmelCase    ,**__UpperCAmelCase )       ->						Tuple:
      return self.tokenizer.decode(*_UpperCAmelCase    ,**_UpperCAmelCase )




  @property
  def 				UpperCAmelCase_      (       self )       ->						Optional[int]:
      warnings.warn(
          """`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead."""    ,_UpperCAmelCase    ,)
      return self.image_processor_class






  @property
  def 				UpperCAmelCase_      (       self )       ->						Dict:
      warnings.warn(
          """`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead."""    ,_UpperCAmelCase    ,)
      return self.image_processor








"""simple docstring"""

import warnings

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding





class 							lowercase_			(	__lowerCAmelCase				):



 '''simple docstring'''
 UpperCAmelCase       :	Any     =      ['''image_processor''', '''tokenizer''']
 UpperCAmelCase       :	Optional[int]     =      '''ViTImageProcessor'''
 UpperCAmelCase       :	int     =      ('''CLIPTokenizer''', '''CLIPTokenizerFast''')

 def __init__(					self			:			Tuple       ,				_UpperCAmelCase			:			int=None       ,				_UpperCAmelCase			:			Tuple=None       ,				**_UpperCAmelCase			:			Dict						):
       _A     =  None
       if "feature_extractor" in kwargs:
             warnings.warn(
                 'The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'
                 ' instead.'       ,				_UpperCAmelCase       ,				)
             _A     =  kwargs.pop('feature_extractor'						)

       _A     =  image_processor if image_processor is not None else feature_extractor
       if image_processor is None:
             raise ValueError('You need to specify an `image_processor`.'						)
       if tokenizer is None:
             raise ValueError('You need to specify a `tokenizer`.'						)

       super().__init__(_UpperCAmelCase       ,				_UpperCAmelCase						)

 def __call__(					self			:			Optional[Any]       ,				_UpperCAmelCase			:			int=None       ,				_UpperCAmelCase			:			int=None       ,				_UpperCAmelCase			:			Optional[Any]=None       ,				_UpperCAmelCase			:			Optional[int]=None       ,				**_UpperCAmelCase			:			Union[str, Any]						):
       if text is None and visual_prompt is None and images is None:
             raise ValueError('You have to specify either text, visual prompt or images.'						)

       if text is not None and visual_prompt is not None:
             raise ValueError('You have to specify exactly one type of prompt. Either text or visual prompt.'						)

       if text is not None:
             _A     =  self.tokenizer(_UpperCAmelCase       ,				return_tensors=_UpperCAmelCase       ,				**_UpperCAmelCase						)

       if visual_prompt is not None:
             _A     =  self.image_processor(_UpperCAmelCase       ,				return_tensors=_UpperCAmelCase       ,				**_UpperCAmelCase						)

       if images is not None:
             _A     =  self.image_processor(_UpperCAmelCase       ,				return_tensors=_UpperCAmelCase       ,				**_UpperCAmelCase						)

       if visual_prompt is not None and images is not None:
             _A     =  {
                 'pixel_values': image_features.pixel_values,
                 'conditional_pixel_values': prompt_features.pixel_values,
             }
             return encoding
       elif text is not None and images is not None:
             _A     =  image_features.pixel_values
             return encoding
       elif text is not None:
             return encoding
       elif visual_prompt is not None:
             _A     =  {
                 'conditional_pixel_values': prompt_features.pixel_values,
             }
             return encoding
       else:
             return BatchEncoding(data=dict(**_UpperCAmelCase						)       ,				tensor_type=_UpperCAmelCase						)

 def      lowerCAmelCase_				(					self			:			str       ,				*_UpperCAmelCase			:			List[Any]       ,				**_UpperCAmelCase			:			Union[str, Any]						):
       return self.tokenizer.batch_decode(*_UpperCAmelCase       ,				**_UpperCAmelCase						)

 def      lowerCAmelCase_				(					self			:			Union[str, Any]       ,				*_UpperCAmelCase			:			List[str]       ,				**_UpperCAmelCase			:			Union[str, Any]						):
       return self.tokenizer.decode(*_UpperCAmelCase       ,				**_UpperCAmelCase						)

 @property
 def      lowerCAmelCase_				(					self			:			Dict						):
       warnings.warn(
           '`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.'       ,				_UpperCAmelCase       ,				)
       return self.image_processor_class



 @property
 def      lowerCAmelCase_				(					self			:			Tuple						):
       warnings.warn(
           '`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.'       ,				_UpperCAmelCase       ,				)
       return self.image_processor

