code: def _module_metrics(self) -> Dict[str, Any]:
      return {
          "Accuracy": int(self.__sum_accuracy) / int(self.__num_samples)
      }
  
imports: from typing_extensions import TypedDict
  import numpy
  import torch
  from dpu_utils.mlutils import Vocabulary
  from torch import nn
  from typing import Any, Counter, Dict, Iterator, List, NamedTuple, Optional, Tuple, Union
  from ptgnn.baseneuralmodel import AbstractNeuralModel, ModuleWithMetrics
  from ptgnn.baseneuralmodel.utils.data import enforce_not_None
  from ptgnn.neuralmodels.gnn import GnnOutput, GraphData, TensorizedGraphData
  from ptgnn.neuralmodels.gnn.graphneuralnetwork import GraphNeuralNetwork, GraphNeuralNetworkModel
label_desc: Use image node_id 3 for calling the Graph2ClassModule obj's underlying member method code with example usage: obj._module_metrics() and returns: dict