code: def add_decoder_args(parser):
      parser.add_argument(
          "--activation-fn",
          type=str,
          default="relu",
          choices=utils.get_available_activation_fns(),
          help="activation function to use",
      )
      parser.add_argument(
          "--decoder-dropout",
          type=float,
          metavar="D",
          help="dropout probability",
      )
      parser.add_argument(
          "--decoder-attention-dropout",
          type=float,
          metavar="D",
          help="dropout probability for attention weights",
      )
      parser.add_argument(
          "--decoder-activation-dropout",
          type=float,
          metavar="D",
          help="dropout probability after activation in FFN.",
      )
      parser.add_argument(
          "--decoder-embed-dim",
          type=int,
          metavar="N",
          help="decoder embedding dimension",
      )
      parser.add_argument(
          "--decoder-ffn-embed-dim",
          type=int,
          metavar="N",
          help="decoder embedding dimension for FFN",
      )
      parser.add_argument(
          "--decoder-layers",
          type=int,
          metavar="N",
          help="num decoder layers",
      )
      parser.add_argument(
          "--decoder-attention-heads",
          type=int,
          metavar="N",
          help="num decoder attention heads",
      )
      parser.add_argument(
          "--decoder-normalize-before",
          action="store_true",
          help="apply layernorm before each decoder block",
      )
      parser.add_argument(
          "--layernorm-embedding",
          action="store_true",
          help="add layernorm to embedding",
      )
      parser.add_argument(
          "--decoder-layerdrop",
          type=float,
          metavar="D",
          help="layerdrop probability for decoder",
      )
      parser.add_argument(
          "--decoder-learned-pos",
          action="store_true",
          help="learn positional embedding in decoder",
      )
      parser.add_argument(
          "--share-decoder-input-output-embed",
          action="store_true",
          help="share decoder input and output embeddings",
      )
      parser.add_argument(
          "--no-scale-embedding",
          action="store_true",
          help="if True, dont scale embeddings",
      )
      parser.add_argument(
          "--load-pretrained-decoder-from",
          type=str,
          metavar="STR",
          help="model to take decoder weights from (for initialization)",
      )
      parser.add_argument(
          "--finetune-decoder-params",
          type=str,
          metavar="STR",
          help="comma-separated param strings to finetune.",
      )
  
imports: import copy
  import logging
  from typing import Dict, List, Optional, Tuple
  import numpy
  import torch
  import torch.nn
  from torch import Tensor
  from fairseq import checkpoint_utils, utils
  from fairseq.data.data_utils import lengths_to_padding_mask
  from fairseq.models import FairseqEncoder, FairseqEncoderDecoderModel, FairseqEncoderModel, FairseqLanguageModel, register_model, register_model_architecture
  from fairseq.models.speech_to_speech.modules.ctc_decoder import CTCDecoder
  from fairseq.models.speech_to_text.hub_interface import S2THubInterface
  from fairseq.models.transformer import Embedding, TransformerDecoder, TransformerModelBase
  from fairseq.models.wav2vec import Wav2VecEncoder
  from fairseq.modules.layer_norm import LayerNorm
label_desc: Use image node_id 4 for calling a global function with example usage: add_decoder_args(parser) without return types