code: def forward(self, src_tokens, trg_tokens):
      encoder_out, encoder_padding_mask = self.encoder(src_tokens)
      decoder_out = self.decoder(
          trg_tokens, encoder_out, encoder_padding_mask
      )
      return decoder_out
  
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 7 for calling the LSTransformer obj's underlying member method code with example usage: obj.forward(src_tokens, trg_tokens) and returns: decoder_out