


'''simple docstring'''
import warnings

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




class      lowerCamelCase_  (      __a ):
      lowerCAmelCase__							=	['image_processor', 'tokenizer']
      lowerCAmelCase__							=	'ViTImageProcessor'
      lowerCAmelCase__							=	('CLIPTokenizer', 'CLIPTokenizerFast')






      def __init__(   self							:       int		,		_A							:       Tuple=None		,		_A							:       Optional[Any]=None		,		**_A							:       Any					):


          '''simple docstring'''


          UpperCAmelCase__     :						Dict						=							None
          if "feature_extractor" in kwargs:
              warnings.warn(
                  '''The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'''
                  ''' instead.'''		,		_A		,		)
              UpperCAmelCase__     :						Optional[Any]						=							kwargs.pop('''feature_extractor'''					)

          UpperCAmelCase__     :						Optional[Any]						=							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__(_A		,		_A					)






      def __call__(   self							:       Optional[Any]		,		_A							:       str=None		,		_A							:       Union[str, Any]=None		,		_A							:       int=None		,		_A							:       Tuple=None		,		**_A							:       int					):


          '''simple docstring'''


          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:
              UpperCAmelCase__     :						List[str]						=							self.tokenizer(_A		,		return_tensors=_A		,		**_A					)

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

          if images is not None:
              UpperCAmelCase__     :						List[Any]						=							self.image_processor(_A		,		return_tensors=_A		,		**_A					)

          if visual_prompt is not None and images is not None:
              UpperCAmelCase__     :						Optional[Any]						=							{
                  '''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:
              UpperCAmelCase__     :						Optional[Any]						=							image_features.pixel_values
              return encoding
          elif text is not None:
              return encoding
          elif visual_prompt is not None:
              UpperCAmelCase__     :						List[str]						=							{
                  '''conditional_pixel_values''': prompt_features.pixel_values,
              }
              return encoding
          else:
              return BatchEncoding(data=dict(**_A					)		,		tensor_type=_A					)






      def lowercase_				(   self							:       Optional[Any]		,		*_A							:       List[Any]		,		**_A							:       List[str]					):


          '''simple docstring'''


          return self.tokenizer.batch_decode(*_A		,		**_A					)






      def lowercase_				(   self							:       Tuple		,		*_A							:       List[Any]		,		**_A							:       List[str]					):


          '''simple docstring'''


          return self.tokenizer.decode(*_A		,		**_A					)






      @property
      def lowercase_				(   self							:       Tuple					):


          '''simple docstring'''


          warnings.warn(
              '''`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.'''		,		_A		,		)
          return self.image_processor_class






      @property
      def lowercase_				(   self							:       Dict					):


          '''simple docstring'''


          warnings.warn(
              '''`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.'''		,		_A		,		)
          return self.image_processor







"""simple docstring"""


import warnings


warnings.warn(
    "memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: "
    "`from accelerate import find_executable_batch_size` to avoid this warning.",
    FutureWarning,
)
