code: def __init__(self, encoder, decoder):
      super().__init__(encoder, decoder)
  
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 3 to create a new XMTransformerModel object from inherited base classes: FairseqEncoderDecoderModel with example: obj = XMTransformerModel(encoder, decoder)