Can offset convolution network parameter be optimized during training?

[THHHomas]

The predicted offset by the convolution network is used as the index to interpolate the feature in feature map. Therefore, the gradient cannot back-propagate to the convolution network parameter(Because the predicted offset do not participate in the calculation directly but is as the index). During training, the offset convolution network is still. Is my understanding right?