def METHOD_NAME(lbann):
    """Construct LBANN experiment. 
    args: 
        lbann (module): Module for LBANN Python frontend
    """
    trainer = lbann.Trainer(mini_batch_size=mini_batch_size)
    callbacks = [lbann.CallbackPrint(), lbann.CallbackTimer(), lbann.CallbackGPUMemoryUsage()]
    model = Sparse_Graph_Trainer.make_model(kernel_type = 'Graph',
                                            num_epochs = num_epochs,
                                            callbacks = callbacks)
    reader = data.PROTEINS.make_data_reader()
    # No validation set
    optimizer = lbann.Adam(learn_rate=0.01, beta1=0.9, beta2=0.99, eps=1e-8 )
    return trainer, model, reader, optimizer