code: def _module_metrics(self) -> Dict[str, Any]:
      return {
          "f1_score": self.__sum_f1 / self.__num_samples,
          "pr_score": self.__sum_pr / self.__num_samples,
          "re_score": self.__sum_re / self.__num_samples,
      }
  
imports: import numpy
  import torch
  from torch import nn
  from typing import Any, Dict, Iterable, NamedTuple, Optional, Union
  from ptgnn.baseneuralmodel import AbstractNeuralModel, ModuleWithMetrics
  from ptgnn.baseneuralmodel.utils.data import enforce_not_None
  from ptgnn.implementations.ppi.dataloader import PPIGraphSample
  from ptgnn.neuralmodels.gnn.graphneuralnetwork import GraphNeuralNetwork, GraphNeuralNetworkModel
  from ptgnn.neuralmodels.gnn.structs import GnnOutput, GraphData, TensorizedGraphData
label_desc: Use image node_id 3 for calling the PPIClassification obj's underlying member method code with example usage: obj._module_metrics() and returns: dict