code: def convtransformer_espnet(args):
      args.encoder_embed_dim = getattr(args, "encoder_embed_dim", 256)
      args.encoder_layers = getattr(args, "encoder_layers", 12)
      args.encoder_attention_heads = getattr(
          args, "encoder_attention_heads", 4
      )
      args.decoder_attention_heads = getattr(
          args, "decoder_attention_heads", 4
      )
  
imports: import logging
  import math
  from typing import Dict, List, Optional, Tuple
  import torch
  import torch.nn
  import torch.nn.functional
  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, register_model, register_model_architecture
  from fairseq.models.speech_to_text.modules.convolution import infer_conv_output_dim
  from fairseq.models.transformer import Embedding, TransformerDecoder
  from fairseq.modules import LayerNorm, PositionalEmbedding, TransformerEncoderLayer
label_desc: Use image node_id 2 for calling a global function with example usage: convtransformer_espnet(args) without return types