class_docstr: Constructs a Speech2Text2 processor which wraps a Speech2Text2 feature extractor and a Speech2Text2 tokenizer into
  a single processor.
  
  [`Speech2Text2Processor`] offers all the functionalities of [`AutoFeatureExtractor`] and [`Speech2Text2Tokenizer`].
  See the [`~Speech2Text2Processor.__call__`] and [`~Speech2Text2Processor.decode`] for more information.
  
  Args:
      feature_extractor (`AutoFeatureExtractor`):
          An instance of [`AutoFeatureExtractor`]. The feature extractor is a required input.
      tokenizer (`Speech2Text2Tokenizer`):
          An instance of [`Speech2Text2Tokenizer`]. The tokenizer is a required input.
docstr: This method forwards all its arguments to Speech2Text2Tokenizer'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 Speech2Text2Tokenizer's [`~PreTrainedTokenizer.batch_decode`]. Please
      refer to the docstring of this method for more information.
      """
      return self.tokenizer.batch_decode(*args, **kwargs)
  
file_path: transformers/src/transformers/models/speech_to_text_2/processing_speech_to_text_2.py
imports: import warnings
  from contextlib import contextmanager
  from ...processing_utils import ProcessorMixin
label_desc: Use image node_id 3 for calling the Speech2Text2Processor obj's underlying member method code with example usage: obj.batch_decode() and returns: self