code: def dualinputs2ttransformer_m(args):
      args.encoder_embed_dim = getattr(args, "encoder_embed_dim", 512)
      args.encoder_ffn_embed_dim = getattr(
          args, "encoder_ffn_embed_dim", 512 * 4
      )
      args.encoder_attention_heads = getattr(
          args, "encoder_attention_heads", 8
      )
      args.decoder_attention_heads = getattr(
          args, "decoder_attention_heads", 8
      )
      args.dropout = getattr(args, "dropout", 0.15)
      args.speech_encoder_layers = getattr(
          args, "speech_encoder_layers", 10
      )
      args.text_encoder_layers = getattr(args, "text_encoder_layers", 6)
      args.decoder_layers = getattr(args, "decoder_layers", 6)
      dualinputs2ttransformer_base(args)
  
imports: import logging
  from collections import namedtuple
  import torch
  import torch.nn
  from fairseq import checkpoint_utils
  from fairseq import utils
  from fairseq.models import FairseqEncoder, FairseqDecoder, FairseqEncoderDecoderModel, register_model, register_model_architecture
  from fairseq.models.fairseq_encoder import EncoderOut
  from fairseq.models.speech_to_text import TransformerDecoder, S2TTransformerEncoder
  from fairseq.models.transformer import TransformerEncoder
  from fairseq.modules import TransformerEncoderLayer, GradMultiply, LayerNorm
label_desc: Use image node_id 3 for calling a global function with example usage: dualinputs2ttransformer_m(args) without return types