pityka / aten-scala   0.0.0+117-ef358cb2


jni bindings to aten from libtorch

Scala versions: 3.x 2.13 2.12


Build documentation

The JNI bindings are built with clang++ for Mac (x86 and arm64) and for Linux (x86). The build runs on a Mac and uses Docker for cross compilation. The docker image used for building (and possible at runtime) is defined in docker-runtime/Dockerfile. This image is pushed to the Docker Hub (https://hub.docker.com/r/pityka/base-ubuntu-libtorch/tags?page=1&ordering=last_updated), and by default the build will pull it.



  1. make prepare - this creates bloop build definitions from sbt the sbt build definition
  2. Copy from one to the other
  3. make test
  4. make test-linux - builds for linux and runs tests in a linux container (needs docker for mac, will pull pityka/base-ubuntu-libtorch from docker hub)
  5. make test-cuda - runs tests in a cuda enabled remote docker context


  • make publishLocal - publishes artifacts locally
  • make publish - publishes artifacts to github packages.
  • bash publish.sh - publishes the artifacts to Maven Central

How this works

The Makefile will generate Java and C++ sources and create a JNI native library.

parser/ holds a parser for parseable.h which is a subset of the libtorch/include/ATen/Functions.h. This parser generates cpp (./wrapper.cpp) and java JNI code (./aten-scala/core/src/main/java/ATen.java). The cpp code is compiled to ./aten-scala/jni-osx/src/main/resources/libatenscalajni.dylib.

aten-scala/ holds an sbt project with two subprojects. aten-scala/core is the Java counterpart of the binding. It depends on Scala because std::tuple is translated into Scala tuples. aten-scala/jni-osx contains no source code but its Maven artifact contains the native library.

Libtorch runtime dependency

Libtorch is linked dynamically during runtime.


On OSX the jni shared library always looks for libtorch in /usr/local/lib/. You can get the libtorch libraries with pip3 install torch then copy the necessary files to /usr/local/lib/. E.g. cp /usr/local/lib/python3.9/site-packages/torch/lib/* /usr/local/lib/. However one needs to copy /usr/local/lib/python3.9/site-packages/torch/.dylibs/libomp.dylib as well to /usr/local/.dylibs/ (depends on the libtorch version).


On Linux there is no @rpath baked in the jni shared library. Use LD_LIBRARY_PATH to make sure the linker finds libtorch. See the docker-runtime/Dockerfiles on how to do this.

Docker image for Linux with libtorch and CUDA

See docker-runtime/Dockerfile. This image is pushed to the Docker Hub (https://hub.docker.com/r/pityka/base-ubuntu-libtorch/tags?page=1&ordering=last_updated).

The image also has Java 8 and sbt. It is ready to make use of this library on Linux.


See LICENSE file.