def METHOD_NAME(training_ctrl, model, mock_dataloader, calc_loss_fn):
    optimizer = SGD(model.parameters(), lr=1e-02, weight_decay=1e-02)
    training_ctrl.set_training_lr_scheduler_args(optimizer, len(mock_dataloader))
    training_ctrl.scheduler.epoch_step()
    training_ctrl.multi_elasticity_handler.activate_minimum_subnet()
    model.train()
    output_storage = []
    for _, (input_, __) in enumerate(mock_dataloader):
        input_ = input_.to(get_model_device(model))
        output = model(input_)
        output_storage.append(output)
        loss = calc_loss_fn(output, input_)
        optimizer.zero_grad()
        loss.backward()
        optimizer.step()
    return output_storage