






import warnings

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





class        a__      (	lowerCAmelCase__		):
		UpperCAmelCase_							:       str 					= ['image_processor', 'tokenizer']
		UpperCAmelCase_							:       int 					= 'VideoMAEImageProcessor'
		UpperCAmelCase_							:       Optional[Any] 					= ('CLIPTokenizer', 'CLIPTokenizerFast')






		def __init__(      self							, lowercase__=None							, lowercase__=None							, **lowercase__						)				->				Tuple:
				__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."							, lowercase__							, )
						__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__(lowercase__							, lowercase__						)
				__A    =							self.image_processor






		def __call__(      self							, lowercase__=None							, lowercase__=None							, lowercase__=None							, **lowercase__						)				->				Any:

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

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

				if videos is not None:
						__A    =							self.image_processor(lowercase__							, return_tensors=lowercase__							, **lowercase__						)

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






		def 					_lowerCamelCase					(      self							, *lowercase__							, **lowercase__						)				->				Optional[int]:
				return self.tokenizer.batch_decode(*lowercase__							, **lowercase__						)






		def 					_lowerCamelCase					(      self							, *lowercase__							, **lowercase__						)				->				Tuple:
				return self.tokenizer.decode(*lowercase__							, **lowercase__						)






		@property
		def 					_lowerCamelCase					(      self						)				->				Optional[int]:
				return ["input_ids", "attention_mask", "position_ids", "pixel_values"]






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






def 				UpperCAmelCase__		(					_SCREAMING_SNAKE_CASE :						str					)->str:
      return " ".join(sorted(set(sentence.split()					)					)					)


if __name__ == "__main__":
    import doctest

    doctest.testmod()