code: def set_default_transformer_decoder_args(args):
      args.decoder_embed_path = getattr(
          args, "decoder_embed_path", None
      )
      args.decoder_embed_dim = getattr(args, "decoder_embed_dim", 1024)
      args.decoder_ffn_embed_dim = getattr(
          args, "decoder_ffn_embed_dim", 4 * 1024
      )
      args.decoder_layers = getattr(args, "decoder_layers", 12)
      args.decoder_attention_heads = getattr(
          args, "decoder_attention_heads", 16
      )
      args.decoder_normalize_before = getattr(
          args, "decoder_normalize_before", False
      )
      args.decoder_learned_pos = getattr(
          args, "decoder_learned_pos", False
      )
      args.decoder_layerdrop = getattr(args, "decoder_layerdrop", 0.0)
      args.adaptive_input = getattr(args, "adaptive_input", False)
      args.decoder_attention_dropout = getattr(
          args, "decoder_attention_dropout", 0.0
      )
      args.decoder_activation_dropout = getattr(
          args, "decoder_activation_dropout", 0.0
      )
      args.decoder_dropout = getattr(args, "decoder_dropout", 0.1)
      args.adaptive_softmax_cutoff = getattr(
          args, "adaptive_softmax_cutoff", None
      )
      args.adaptive_softmax_dropout = getattr(
          args, "adaptive_softmax_dropout", 0
      )
      args.share_decoder_input_output_embed = getattr(
          args, "share_decoder_input_output_embed", False
      )
      args.no_token_positional_embeddings = getattr(
          args, "no_token_positional_embeddings", False
      )
  
      args.decoder_output_dim = getattr(
          args, "decoder_output_dim", args.decoder_embed_dim
      )
      args.decoder_input_dim = getattr(
          args, "decoder_input_dim", args.decoder_embed_dim
      )
  
      args.no_scale_embedding = getattr(
          args, "no_scale_embedding", False
      )
      args.quant_noise_pq = getattr(args, "quant_noise_pq", 0)
      args.layernorm_embedding = getattr(
          args, "layernorm_embedding", False
      )
  
      args.activation_fn = getattr(args, "activation_fn", "gelu")
      args.pooler_activation_fn = getattr(
          args, "pooler_activation_fn", "tanh"
      )
      args.pooler_dropout = getattr(args, "pooler_dropout", 0.0)
  
      args.finetune_decoder_params = getattr(
          args, "finetune_decoder_params", "all"
      )
  
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 8 for calling a global function with example usage: set_default_transformer_decoder_args(args) without return types