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deep-learningcaffe

How to remove layers by name from .prototxt in caffe using Python

I have a train.prototxt create with Python code and would like to remove the loss layers to create the deploy.prototxt automatically. However, I know only the method to remove a layer by an integer like this:

net_param = deploy_net.to_proto()
del net_param.layer[0]

Is there any possibility to remove a layer by its name? Where is the documentation for the Python API? I cannot really find it. Do I just have to look at the C++ code and try to convert it into Python code?

EDIT

I am initialising the net with.

net = caffe.NetSpec()
Solution

  • net.layer_dict is a dictionary of all the layer. So to delete you can do:

    del net.layer_dict['layer_name'];

    You can look into pycaffe.py for details of Python Api.