This is a bunch of code to port Keras neural network model into pure C++. Neural network weights and architecture are stored in plain text file and input is presented as vector<vector<vector<float> > >
in case of image. The code is prepared to support simple Convolutional network (from MNIST example) but can be easily extended. There are implemented only ReLU and Softmax activations.
It is working with the Theano backend.
dump_to_simple_cpp.py
script.keras_model.h
and keras_model.cc
files - see example below.example/mnist_cnn_one_iteration.py
script. It will produce files with architecture example/my_nn_arch.json
and weights in HDF5 format example/my_nn_weights.h5
.python dump_to_simple_cpp.py -a example/my_nn_arch.json -w example/my_nn_weights.h5 -o example/dumped.nnet
.g++ -std=c++11 keras_model.cc example_main.cc
- see code in example_main.cc
../a.out
- you shoul get the same output as in step one from Keras.If you want to test dumping for your network, please use test_run.sh
script. Please provide there your network architecture and weights. The script do following job: