code: def forward_embedding(self, src_tokens):
      x = self.embed_tokens(src_tokens)
      return x
  
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 LSTransformerEncoder obj's underlying member method code with example usage: obj.forward_embedding(src_tokens) and returns: x