





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




class 	UpperCamelCase_							(  UpperCamelCase__     ):
							lowerCamelCase_							     =       ["image_processor", "tokenizer"]
							lowerCamelCase_							     =       "AutoImageProcessor"
							lowerCamelCase_							     =       "AutoTokenizer"


							def __init__(				self     :Optional[int]				,					__A     :Optional[Any]				,					__A     :Dict		) -> Dict:



									"""simple docstring"""



									super().__init__(__A				,					__A		)
									SCREAMING_SNAKE_CASE__								=   self.image_processor


							def __call__(				self     :int				,					__A     :str=None				,					__A     :int=None				,					__A     :Union[str, Any]=None				,					**__A     :str		) -> Optional[Any]:



									"""simple docstring"""



									if text is None and images is None:
											raise ValueError("""You have to specify either text or images. Both cannot be none."""		)

									if text is not None:
											SCREAMING_SNAKE_CASE__								=   self.tokenizer(__A				,					return_tensors=__A				,					**__A		)

									if images is not None:
											SCREAMING_SNAKE_CASE__								=   self.image_processor(__A				,					return_tensors=__A				,					**__A		)

									if text is not None and images is not None:
											SCREAMING_SNAKE_CASE__								=   image_features.pixel_values
											return encoding
									elif text is not None:
											return encoding
									else:
											return BatchEncoding(data=dict(**__A		)				,					tensor_type=__A		)


							def   _snake_case	(				self     :str				,					*__A     :List[str]				,					**__A     :List[str]		) -> List[Any]:



									"""simple docstring"""



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


							def   _snake_case	(				self     :List[str]				,					*__A     :Any				,					**__A     :Any		) -> Tuple:



									"""simple docstring"""



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


							@property
							def   _snake_case	(				self     :Dict		) -> List[Any]:



									"""simple docstring"""



									return ["input_ids", "attention_mask", "pixel_values"]





import warnings

from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor


UpperCamelCase__ :   str						=							logging.get_logger(__name__)







class 				lowerCAmelCase_       (					lowerCamelCase_							):






				def __init__(			self      ,*snake_case__      ,**snake_case__ ):
							warnings.warn(
							    'The class PoolFormerFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
							    ' Please use PoolFormerImageProcessor instead.'      ,snake_case__      ,)
							super().__init__(*snake_case__      ,**snake_case__ )



