How to add a custom layer and loss function into a pretrained CNN model by matconvnet?

Question

I'm new to matconvnet. Recently, I'd like to try a new loss function instead of the existing one in pretrained model, e.g., vgg-16, which usually uses softmax loss layer. What's more, I want to use a new feature extractor layer, instead of pooling layer or max layer. I know there are 2 CNN wrappers in matconvnet, simpleNN and DagNN respectively, since I'm using vgg-16,a linear model which has a linear sequence of building blocks. So, in simpleNN wrapper, how to create a custom layer in detail, espectially the procedure and the relevant concept, e.g., do I need to remove layers behind the new feature extractor layer or just leave them ? And I know how to compute the derivative of the loss function so the details of computation inside the layer is not that important in this question, I just want to know the procedure represented by codes. Could someone help me? I'll appreciate it a lot !

Answer 1

You can remove the older error or objective layer net.layer('abc')=[]; and you can add new error code in vl_nnloss() file