code: def testInfoMax3DModularClassification():
      import torch
      from deepchem.models.torch_models.gnn3d import InfoMax3DModular
  
      data, metric = get_classification_dataset()
  
      model = InfoMax3DModular(
          hidden_dim=128,
          aggregators=["sum", "mean", "max"],
          readout_aggregators=["sum", "mean"],
          scalers=["identity"],
          task="classification",
          n_tasks=1,
          n_classes=2,
          device=torch.device("cpu"),
      )
  
      model.fit(data, nb_epoch=10)
      scores = model.evaluate(data, [metric])
      assert scores["mean-roc_auc_score"] > 0.7
  
file_path: deepchem/deepchem/models/tests/test_gnn3d.py
imports: import os
  import pytest
label_desc: Use image node_id 9 for calling a global function with example usage: testInfoMax3DModularClassification() without return types