def METHOD_NAME():
    from deepchem.models.torch_models.gnn3d import InfoMax3DModular
    data, _ = get_regression_dataset()
    model = InfoMax3DModular(hidden_dim=64,
                             target_dim=10,
                             aggregators=['sum', 'mean', 'max'],
                             readout_aggregators=['sum', 'mean'],
                             scalers=['identity'])
    model.fit(data, nb_epoch=1)
    model2 = InfoMax3DModular(hidden_dim=64,
                              target_dim=10,
                              aggregators=['sum', 'mean', 'max'],
                              readout_aggregators=['sum', 'mean'],
                              scalers=['identity'])
    model2.load_from_pretrained(model_dir=model.model_dir)
    assert model.components.keys() == model2.components.keys()
    keys_with_weights = [
        key for key in model.components.keys()
        if hasattr(model.components[key], 'weight')
    ]
    assert all(compare_weights(key, model, model2) for key in keys_with_weights)