TASO can be built from source code using the following instructions. We also provide prebuilt TASO docker images with all dependencies preinstalled.
- CMAKE 3.2 or higher
- ProtocolBuffer 3.6.1 or higher
- Cython 0.28 or higher
- ONNX 1.5 or higher
- CUDA 9.0 or higher and CUDNN 7.0 or higher
- To get started, clone the TASO source code from github.
git clone --recursive https://www.github.com/jiazhihao/taso
cd taso
The TASO_HOME
environment is used for building and running TASO. You can add the following line in ~/.bashrc
.
export TASO_HOME=/path/to/taso
- Build the TASO runtime library. The configuration of the TASO runtime can be modified by
config.cmake
. The default configuration builds the CUDA backend and automatically finds the CUDA libraries (e.g., cuDNN, cuBLAS). You can manually choose a CUDA path by changingset(USE_CUDA ON)
toset(USE_CUDA /path/to/cuda/library
). MKL support is coming soon.
mkdir build; cd build; cmake ..
sudo make install -j 4
- Install the TASO python package.
cd ../python
python setup.py install
We require docker and nvidia-docker to run the TASO docker images.
- First, clone the TASO gitpub repository to obtain the necessary scripts
git clone --recursive https://www.github.com/jiazhihao/taso
- Second, we can use the following command to run a TASO docker image for CUDA 10.0.
/path/to/taso/docker/run_docker.sh tasoml/cuda100
- You are ready to use TASO now. Try some of our example DNN architectures.
python /path/to/taso/examples/resnext10.py