class_docstr: Constructs a Wav2Vec2 processor which wraps a Wav2Vec2 feature extractor, a Wav2Vec2 CTC tokenizer and a decoder
  with language model support into a single processor for language model boosted speech recognition decoding.
  
  Args:
      feature_extractor ([`Wav2Vec2FeatureExtractor`]):
          An instance of [`Wav2Vec2FeatureExtractor`]. The feature extractor is a required input.
      tokenizer ([`Wav2Vec2CTCTokenizer`]):
          An instance of [`Wav2Vec2CTCTokenizer`]. The tokenizer is a required input.
      decoder (`pyctcdecode.BeamSearchDecoderCTC`):
          An instance of [`pyctcdecode.BeamSearchDecoderCTC`]. The decoder is a required input.
docstr: When used in normal mode, this method forwards all its arguments to Wav2Vec2FeatureExtractor's
  [`~Wav2Vec2FeatureExtractor.pad`] and returns its output. If used in the context
  [`~Wav2Vec2ProcessorWithLM.as_target_processor`] this method forwards all its arguments to
  Wav2Vec2CTCTokenizer's [`~Wav2Vec2CTCTokenizer.pad`]. Please refer to the docstring of the above two methods
  for more information.
docstr_tok: ["When","used","in","normal","mode",",","this","method","forwards","all","its","arguments","to","Wav2Vec2FeatureExtractor's","[","`","~Wav2Vec2FeatureExtractor.pad","`","]","and","returns","its","output",".","If","used","in","the","context","[","`","~Wav2Vec2ProcessorWithLM.as_target_processor","`","]","this","method","forwards","all","its","arguments","to","Wav2Vec2CTCTokenizer","'s","[","`","~Wav2Vec2CTCTokenizer.pad","`","]",".","Please","refer","to","the","docstring","of","the","above","two","methods","for","more","information","."]
code: def pad(self, *args, **kwargs):
      """
      When used in normal mode, this method forwards all its arguments to Wav2Vec2FeatureExtractor's
      [`~Wav2Vec2FeatureExtractor.pad`] and returns its output. If used in the context
      [`~Wav2Vec2ProcessorWithLM.as_target_processor`] this method forwards all its arguments to
      Wav2Vec2CTCTokenizer's [`~Wav2Vec2CTCTokenizer.pad`]. 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.pad(*args, **kwargs)
  
      input_features = kwargs.pop("input_features", None)
      labels = kwargs.pop("labels", None)
      if len(args) > 0:
          input_features = args[0]
          args = args[1:]
  
      if input_features is not None:
          input_features = self.feature_extractor.pad(
              input_features, *args, **kwargs
          )
      if labels is not None:
          labels = self.tokenizer.pad(labels, **kwargs)
  
      if labels is None:
          return input_features
      elif input_features is None:
          return labels
      else:
          input_features["labels"] = labels["input_ids"]
          return input_features
  
imports: import os
  import warnings
  from contextlib import contextmanager, nullcontext
  from dataclasses import dataclass
  from multiprocessing import Pool, get_context, get_start_method
  from typing import TYPE_CHECKING, Dict, Iterable, List, Optional, Union
  import numpy
  from ...processing_utils import ProcessorMixin
  from ...utils import ModelOutput, logging, requires_backends
label_desc: Use image node_id 8 for calling the Wav2Vec2ProcessorWithLM obj's underlying member method code with example usage: obj.pad() and returns: self, input_features, labels, input_features