code: def extend_minibatch_with(
      self,
      tensorized_datapoint: TensorizedPPIData,
      partial_minibatch: Dict[str, Any],
  ) -> bool:
      continue_adding = self.__gnn_model.extend_minibatch_with(
          tensorized_datapoint.gnn_data, partial_minibatch["graph_data"]
      )
      partial_minibatch["labels"].append(tensorized_datapoint.targets)
      return continue_adding
  
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 7 for calling the PPIMulticlassClassification obj's underlying member method code with example usage: obj.extend_minibatch_with(tensorized_datapoint, partial_minibatch) and returns: continue_adding