code: def __init__(self, args, encoder, decoder):
      super().__init__(encoder, decoder)
      self.args = args
  
imports: import torch
  import torch.nn
  from fairseq import utils
  from fairseq.models import FairseqEncoder, FairseqEncoderDecoderModel, FairseqIncrementalDecoder, register_model, register_model_architecture
  from fairseq.models.fairseq_encoder import EncoderOut
  from fairseq.modules import LayerNorm
  from lightseq.training.ops.pytorch.layer_base import TransformerEmbeddingLayerBase
  from lightseq.training.ops.pytorch.quantization import QuantLinear, disable_quant, enable_quant, ptq_mode, qat_mode
label_desc: Use image node_id 1 to create a new LSTransformerModel object from inherited base classes: FairseqEncoderDecoderModel with example: obj = LSTransformerModel(args, encoder, decoder)