code: def forward(self, node_data, is_candidate):
      embeddings = self.__node_embedding_module(**node_data)
      return torch.cat((embeddings, is_candidate.unsqueeze(-1)), dim=-1)
  
imports: import torch
  from torch import nn
  from typing import Any, Dict, Tuple
  from ptgnn.baseneuralmodel import AbstractNeuralModel
  from ptgnn.neuralmodels.embeddings.strelementrepresentationmodel import StrElementRepresentationModel
  from ptgnn.neuralmodels.gnn.structs import AbstractNodeEmbedder
label_desc: Use image node_id 2 for calling the CandidateNodeAnnotationModule obj's underlying member method code with example usage: obj.forward(node_data, is_candidate) and returns: torch