class_docstr: Constructs a Wav2Vec2 processor which wraps a Wav2Vec2 feature extractor and a Wav2Vec2 CTC tokenizer into a single
  processor.
  
  [`Wav2Vec2Processor`] offers all the functionalities of [`Wav2Vec2FeatureExtractor`] and [`PreTrainedTokenizer`].
  See the docstring of [`~Wav2Vec2Processor.__call__`] and [`~Wav2Vec2Processor.decode`] for more information.
  
  Args:
      feature_extractor (`Wav2Vec2FeatureExtractor`):
          An instance of [`Wav2Vec2FeatureExtractor`]. The feature extractor is a required input.
      tokenizer ([`PreTrainedTokenizer`]):
          An instance of [`PreTrainedTokenizer`]. The tokenizer is a required input.
docstr: When used in normal mode, this method forwards all its arguments to Wav2Vec2FeatureExtractor's
  [`~Wav2Vec2FeatureExtractor.__call__`] and returns its output. If used in the context
  [`~Wav2Vec2Processor.as_target_processor`] this method forwards all its arguments to PreTrainedTokenizer's
  [`~PreTrainedTokenizer.__call__`]. Please refer to the docstring of the above two methods for more information.
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code: def __call__(self, *args, **kwargs):
      """
      When used in normal mode, this method forwards all its arguments to Wav2Vec2FeatureExtractor's
      [`~Wav2Vec2FeatureExtractor.__call__`] and returns its output. If used in the context
      [`~Wav2Vec2Processor.as_target_processor`] this method forwards all its arguments to PreTrainedTokenizer's
      [`~PreTrainedTokenizer.__call__`]. Please refer to the docstring of the above two methods for more information.
      """
      # For backward compatibility
      if self._in_target_context_manager:
          return self.current_processor(*args, **kwargs)
  
      if "raw_speech" in kwargs:
          warnings.warn(
              "Using `raw_speech` as a keyword argument is deprecated. Use `audio` instead."
          )
          audio = kwargs.pop("raw_speech")
      else:
          audio = kwargs.pop("audio", None)
      text = kwargs.pop("text", None)
      if len(args) > 0:
          audio = args[0]
          args = args[1:]
  
      if audio is None and text is None:
          raise ValueError(
              "You need to specify either an `audio` or `text` input to process."
          )
  
      if audio is not None:
          inputs = self.feature_extractor(audio, *args, **kwargs)
      if text is not None:
          encodings = self.tokenizer(text, **kwargs)
  
      if text is None:
          return inputs
      elif audio is None:
          return encodings
      else:
          inputs["labels"] = encodings["input_ids"]
          return inputs
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/src/transformers/models/wav2vec2/processing_wav2vec2.py
imports: import warnings
  from contextlib import contextmanager
  from ...processing_utils import ProcessorMixin
  from .feature_extraction_wav2vec2 import Wav2Vec2FeatureExtractor
  from .tokenization_wav2vec2 import Wav2Vec2CTCTokenizer
label_desc: Use image node_id 3 for calling the Wav2Vec2Processor obj's underlying member method code with example usage: obj.__call__() and returns: self, inputs, encodings, inputs