

"""simple docstring"""





import warnings

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







class 				SCREAMING_SNAKE_CASE					(		UpperCAmelCase__       ):






					"""simple docstring"""



					lowercase__				 =       ["image_processor", "tokenizer"]
					lowercase__				 =       "ViTImageProcessor"
					lowercase__				 =       ("CLIPTokenizer", "CLIPTokenizerFast")







					def __init__(       self			:				str   ,lowercase_			:				Any=None   ,lowercase_			:				Optional[Any]=None   ,**lowercase_			:				int		):
						lowerCAmelCase__	:						List[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.'''   ,lowercase_   ,)
							lowerCAmelCase__	:						Union[str, Any]  				=	kwargs.pop('''feature_extractor'''		)

						lowerCAmelCase__	:						int  				=	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__(lowercase_   ,lowercase_		)







					def __call__(       self			:				Optional[Any]   ,lowercase_			:				str=None   ,lowercase_			:				Optional[int]=None   ,lowercase_			:				Dict=None   ,lowercase_			:				List[Any]=None   ,**lowercase_			:				int		):


						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__	:						Optional[Any]  				=	self.tokenizer(lowercase_   ,return_tensors=lowercase_   ,**lowercase_		)

						if visual_prompt is not None:
							lowerCAmelCase__	:						Union[str, Any]  				=	self.image_processor(lowercase_   ,return_tensors=lowercase_   ,**lowercase_		)

						if images is not None:
							lowerCAmelCase__	:						Optional[int]  				=	self.image_processor(lowercase_   ,return_tensors=lowercase_   ,**lowercase_		)

						if visual_prompt is not None and images is not None:
							lowerCAmelCase__	:						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:
							lowerCAmelCase__	:						int  				=	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(**lowercase_		)   ,tensor_type=lowercase_		)







					def        __lowerCAmelCase (       self			:				Tuple   ,*lowercase_			:				str   ,**lowercase_			:				List[Any]		):
						return self.tokenizer.batch_decode(*lowercase_   ,**lowercase_		)







					def        __lowerCAmelCase (       self			:				Optional[int]   ,*lowercase_			:				Union[str, Any]   ,**lowercase_			:				List[str]		):
						return self.tokenizer.decode(*lowercase_   ,**lowercase_		)







					@property
					def        __lowerCAmelCase (       self			:				Optional[int]		):
						warnings.warn(
						    '''`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.'''   ,lowercase_   ,)
						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.'''   ,lowercase_   ,)
						return self.image_processor












"""simple docstring"""






import warnings

from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor


UpperCAmelCase_   : Any   			= logging.get_logger(__name__)




class 							lowerCAmelCase__				(			UpperCAmelCase__ ):






      '''simple docstring'''

      def __init__(						self     :  Union[str, Any]						,	*lowercase_     :  List[str]						,	**lowercase_     :  List[str]):




          '''simple docstring'''


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


