Switch branches/tags
Find file History
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Type Name Latest commit message Commit time
Failed to load latest commit information.


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.


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



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 assemble.


will download and unzip the MNIST dataset of 70000 labeled handwritten digits for training and testing a classifier (if not yet done).

Then run

../gradlew runProgram

Alternatively you can run the artifact directly through


You may need to specify LD_LIBRARY_PATH or DYLD_LIBRARY_PATH environment variables to point 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.