code: def build_model(self, config):
      encoder_embed_tokens = self.build_embedding(config)
      decoder_embed_tokens = self.build_embedding(config)
  
      self.encoder = self.build_encoder(config, encoder_embed_tokens)
      self.decoder = self.build_decoder(config, decoder_embed_tokens)
  
imports: from dataclasses import dataclass
  import torch
  import torch.nn
  from lightseq.training import LSTransformerEmbeddingLayer, LSTransformerEncoderLayer, LSTransformerDecoderLayer
  from lightseq.training.ops.pytorch.util import MODEL_ARCH
  from lightseq.training.ops.pytorch.quantization import QuantLinear
label_desc: Use image node_id 3 for calling the LSTransformer obj's underlying member method code with example usage: obj.build_model(config) without return types