code: def test_infograph():
      from deepchem.models.torch_models.infograph import InfoGraphModel
      import torch
  
      torch.manual_seed(123)
      dataset, _ = get_regression_dataset()
      num_feat = 30
      edge_dim = 11
      model = InfoGraphModel(num_feat, edge_dim)
      # first iteration loss is around 50
      loss = model.fit(dataset, nb_epoch=20)
      assert loss < 25
  
imports: import os
  import pytest
  import numpy
  import deepchem
  from deepchem.feat.molecule_featurizers import MolGraphConvFeaturizer
label_desc: Use image node_id 13 for calling a global function with example usage: test_infograph() without return types