class_docstr: Constructs a VisionTextDualEncoder processor which wraps a vision feature extractor and a tokenizer into a single
  processor.
  
  [`VisionTextDualEncoderProcessor`] offers all the functionalities of [`AutoFeatureExtractor`] and
  [`AutoTokenizer`]. See the [`~VisionTextDualEncoderProcessor.__call__`] and
  [`~VisionTextDualEncoderProcessor.decode`] for more information.
  
  Args:
      feature_extractor ([`AutoFeatureExtractor`]):
          The feature extractor is a required input.
      tokenizer ([`PreTrainedTokenizer`]):
          The tokenizer is a required input.
docstr: This method forwards all its arguments to VisionTextDualEncoderTokenizer's
  [`~PreTrainedTokenizer.batch_decode`]. Please refer to the docstring of this method for more information.
docstr_tok: ["This","method","forwards","all","its","arguments","to","VisionTextDualEncoderTokenizer's","[","`","~PreTrainedTokenizer.batch_decode","`","]",".","Please","refer","to","the","docstring","of","this","method","for","more","information","."]
code: def batch_decode(self, *args, **kwargs):
      """
      This method forwards all its arguments to VisionTextDualEncoderTokenizer's
      [`~PreTrainedTokenizer.batch_decode`]. Please refer to the docstring of this method for more information.
      """
      return self.tokenizer.batch_decode(*args, **kwargs)
  
imports: from ...processing_utils import ProcessorMixin
  from ...tokenization_utils_base import BatchEncoding
label_desc: Use image node_id 3 for calling the VisionTextDualEncoderProcessor obj's underlying member method code with example usage: obj.batch_decode() and returns: self