TensorFlow prediction using its C++ API.
Having this repo, you will not need TensorFlow-Serving
. This project has been tested on OSX.
Contains two examples:
- simple model
c = a * b
- an industrial deep model for large scale click through rate prediction
Covered knowledge points:
- save model and checkpoint
- freeze model with checkpoint
- replace part of nodes in the model for prediction
- transform libfm data into tfrecord
- load model in C++
- construct
SparseTensor
in C++ - prediction in C++
Follow the instruction build tensorflow from source
git clone --recursive https://github.com/tensorflow/tensorflow.git
cd tensorflow
sh tensorflow/contrib/makefile/build_all_linux.sh (works for linux and osx)
cd ..
Keep this repo in the same directory with tensorflow.
git clone https://github.com/formath/tensorflow-predictor-cpp.git
cd tensorflow-predictor-cpp
mkdir build && cd build
cmake ..
make
This demo used c = a * b
to show how to save the model and load it using C++ for prediction.
- Save model
- Load model
- Prediction
More detail in Chinese: tensorflow_c++_api_prediction
cd demo/simple_model
# train
sh train.sh
# predict
sh predict.sh
This demo show a real-world deep model usage in click through rate prediction.
- Transform LibFM data into TFRecord
- Save model and checkpoint
- Replace parts of model and freeze graph with checkpoint
- Load model and checkpoint
- Prediction
More detail in Chinese: tensorflow_c++_api_prediction
- LibFM format:
label fieldId:featureId:value ...
cd demo/deep_model
sh trans_data_to_tfrecord.sh
sh train.sh
sh freeze_graph.sh
sh predict.sh