dreadlord1984 / caffe_remove_bn

Caffe

Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by the Berkeley Vision and Learning Center (BVLC) and community contributors.

This repository added a tool named caffe_remove_bn, which is designed to remove the BatchNorm and Scale layer inside the network topologies like ResNet, Inception v3/v4, etc. (Of course, ONLY for inference, as the inference uses the global mean and variance, which can be combined into the convolution layer)

It will take a trained model as input, and output a transformed model.

Usage example: .build_release/tools/remove_bn_layer.bin ResNet-50-deploy.prototxt ResNet-50-model.caffemodel bn_removed.prototxt bn_removed.caffemodel

Please note: Many special cases are not considered in the implementation. Please modifiy the code if needed.

Happy brewing!

Modifications

modified: include/caffe/net.hpp modified: src/caffe/net.cpp Added: tools/remove_bn_layer.cpp

License and Citation

Caffe is released under the BSD 2-Clause license. The BVLC reference models are released for unrestricted use.

Please cite Caffe in your publications if it helps your research:

@article{jia2014caffe,
  Author = {Jia, Yangqing and Shelhamer, Evan and Donahue, Jeff and Karayev, Sergey and Long, Jonathan and Girshick, Ross and Guadarrama, Sergio and Darrell, Trevor},
  Journal = {arXiv preprint arXiv:1408.5093},
  Title = {Caffe: Convolutional Architecture for Fast Feature Embedding},
  Year = {2014}
}