code: def test_gcn_model(self):
      train_smiles = [
          "C1CCC1",
          "CCC",
          "C1CCC1",
          "CCC",
          "C1CCC1",
          "CCC",
          "C1CCC1",
          "CCC",
          "C1CCC1",
          "CCC",
      ]
      train_labels = [0.0, 1.0, 0.0, 1.0, 0.0, 1.0, 0.0, 1.0, 0.0, 1.0]
  
      model = GCNModel(
          mode="classification",
          n_tasks=1,
          batch_size=2,
          learning_rate=0.001,
      )
  
      featurizer = dc.feat.MolGraphConvFeaturizer()
      X = featurizer.featurize(train_smiles)
      sample = dc.data.NumpyDataset(X=X, y=train_labels)
  
      smiles_datasetmodule = DCLightningDatasetModule(
          sample, 2, collate_dataset_wrapper
      )
  
      lightning_module = DCLightningModule(model)
      trainer = L.Trainer(max_epochs=1)
      trainer.fit(lightning_module, smiles_datasetmodule)
  
imports: import unittest
  import deepchem
  import numpy
label_desc: Use image node_id 2 for calling the TestDCLightningModule obj's underlying member method code with example usage: obj.test_gcn_model() without return types