Why should FNet，and SRNet be trained respectively ？because of gradient back propagation？

[hzg456]

Why should FNet，and SRNet be trained respectively(I mean using two Optimizers）？
because the function tfa.image.dense_image_warp cannot be used for gradient back propagation？

[eewindfly]

The pro is that you can fine-tine two networks separately, however, in the source code, no different hyper-parameters are applied.
Therefore, I think respective training is not a must.
If I am wrong, please correct me.