code: def tensorize(
      self, datapoint: VarMisuseSample
  ) -> Optional[TensorizedVarMisuseSample]:
      graph = datapoint["ContextGraph"]
      all_correct_slots = [
          i
          for i, cand_symbol in enumerate(datapoint["SymbolCandidates"])
          if cand_symbol["IsCorrect"]
      ]
      assert len(all_correct_slots) == 1
  
      candidate_node_ids = {
          s["SymbolDummyNode"] for s in datapoint["SymbolCandidates"]
      }
      graph_data = GraphData(
          node_information=[
              (graph["NodeLabels"][str(i)], i in candidate_node_ids)
              for i in range(len(graph["NodeLabels"]))
          ],
          edges=graph["Edges"],
          reference_nodes={
              "candidate_nodes": [
                  s["SymbolDummyNode"]
                  for s in datapoint["SymbolCandidates"]
              ],
              "slot_node_idx": [datapoint["SlotDummyNode"]],
          },
      )
  
      if graph_data is None:
          return None
  
      self.__add_subtoken_vocab_nodes(graph_data)
      tensorized_graph_data = self.__gnn_model.tensorize(graph_data)
      if tensorized_graph_data is None:
          return None
  
      return TensorizedVarMisuseSample(
          graph=tensorized_graph_data,
          target_candidate_node_idx=all_correct_slots[0],
          num_candidate_nodes=len(datapoint["SymbolCandidates"]),
      )
  
imports: from typing_extensions import Final, TypedDict
  import re
  import torch
  from dpu_utils.codeutils import split_identifier_into_parts
  from itertools import chain
  from torch import nn
  from torch_scatter import scatter_log_softmax, scatter_max
  from typing import Any, Dict, Iterator, List, NamedTuple, Optional, Tuple, Union
  from ptgnn.baseneuralmodel import AbstractNeuralModel, ModuleWithMetrics
  from ptgnn.neuralmodels.gnn.graphneuralnetwork import GraphNeuralNetwork, GraphNeuralNetworkModel
  from ptgnn.neuralmodels.gnn.structs import GnnOutput, GraphData, TensorizedGraphData
label_desc: Use image node_id 5 for calling the VarMisuseModel obj's underlying member method code with example usage: obj.tensorize(datapoint) and returns: TensorizedVarMisuseSample, None, None