code: def add_args(parser):
      TransformerModel.add_args(parser)
      SpeechWavTransformerEncoder.add_args(parser)
      parser.add_argument(
          "--speech-sup-mask-prob",
          type=float,
          help="probability of replacing a token with mask (sup-speech)",
      )
      parser.add_argument(
          "--speech-unsup-mask-prob",
          type=float,
          help="probability of replacing a token with mask (unsup-speech)",
      )
      parser.add_argument(
          "--load-pretrained-mbart-encoder-from",
          type=str,
          metavar="STR",
          help="model to take text encoder  weights from (for initialization)",
      )
  
      parser.add_argument(
          "--load-pretrained-mbart-decoder-from",
          type=str,
          metavar="STR",
          help="model to take text decoder  weights from (for initialization)",
      )
  
      parser.add_argument(
          "--load-pretrained-feature-extractor-from",
          type=str,
          metavar="STR",
          help="model to take feature extractor weights from (for initialization)",
      )
  
      parser.add_argument(
          "--speech-unsup-dropout",
          type=float,
          default=0,
          help="dropout for unsupervised speech encoder",
      )
  
      parser.add_argument(
          "--speech-unsup-feature-dropout",
          type=float,
          default=0,
          help="dropout for unsupervised speech feature encoder",
      )
  
      parser.add_argument(
          "--encoder-shared-text-layers-from-begin",
          type=int,
          help="number of text encoder layers shared with speech encoder (from first layer)",
      )
  
      parser.add_argument(
          "--stacked-encoder",
          default="none",
          choices=["none", "s2s", "all"],
          help="stack speech and text encoders",
      )
  
      parser.add_argument(
          "--use-decoder-output-proj", action="store_true"
      )
  
imports: import logging
  from collections import OrderedDict, namedtuple
  from typing import Dict, Optional
  import torch
  import torch.nn
  import torch.nn.functional
  from torch import Tensor
  from fairseq import checkpoint_utils, utils
  from fairseq.file_io import PathManager
  from fairseq.models import FairseqDecoder, FairseqEncoderDecoderModel, register_model, register_model_architecture
  from fairseq.models.speech_to_text import MultiInputDecoder, MultiModalityEncoder, SpeechWavTransformerEncoder, StackedSpeechWavTransformerEncoder
  from fairseq.models.transformer import TransformerDecoder, TransformerEncoder, TransformerModel
label_desc: Use image node_id 6 for calling the SpeechTextPreTrainModel obj's underlying member method code with example usage: obj.add_args(parser) without return types