Ilya Matveev
7f00e581b5
* [gradle-plugin] Depend on Kotlin 0.9.0-native * [gradle-plugin] Use test artifacts from eap repo
Torch demo
Trains a handwritten digit classifier using the Torch C backend. Like other Torch clients, most prominently PyTorch, this example is built on top of the ATen C API, showing how a Torch client for Kotlin/Native could look like.
Installation
To build ATen (Torch for C), make sure you have Python 2.X and pyyaml installed:
# macOS: if you don't have pip
sudo easy_install pip
# Linux: if you don't have pip
apt-get -y install python-pip
# if you don't have pyyaml or typing
sudo pip install pyyaml typing
Now
./downloadTorch.sh
will install it into $HOME/.konan/third-party/torch (if not yet done). One may override the location of
third-party/torch by setting the KONAN_DATA_DIR environment variable.
To build use ../gradlew build or ./build.sh.
./downloadMNIST.sh
will download and unzip the MNIST dataset of 70000 labeled handwritten digits for training and testing a classifier.
Then run
../gradlew run
Alternatively you can run the artifact directly through
./build/konan/bin/macbook/HelloTorch.kexe
You may need to specify LD_LIBRARY_PATH or DYLD_LIBRARY_PATH to $HOME/.konan/third-party/torch/lib
if the ATen dynamic library cannot be found.
Even on a CPU, training should only take some minutes, and you should observe a classification accuracy of about 95% on the test dataset.