how to write caffe python layer with trainable parameters?

Question

I want to learn how to write caffe python layers.
But I only find examples about very simple layers like pyloss.

How to write python caffe with trainable parameters?

For example, how to write a fully connected python layer?

Answer 1

Caffe stores the layer's trainable parameters as a vector of blobs. By default this vector is empty and it is up to you to add parameters blobs to it in the setup of the layer. There is a simple example for a layer with parameters in test_python_layer.py.

See this post for more information about "Python" layers in caffe.