Deeplearning4j VS JavaCPP

Have you considered migrating off of Python to just using JVM ML libraries then? I hear good things about Deeplearning4j, but there's quite a few.

I've gone to the linux workflow as directed in the docs and reconstructed the maven command line:

DL4J

Hey folks, just letting you know we see this thread and I appreciate you guys running these benchmarks. I'm not seeing any of your posts on our forums. I think I saw a notification from our examples but we do not actually monitor that. Please use: https://community.konduit.ai/ or at least the main repo dl4j issues: https://github.com/eclipse/deeplearning4j/issues and you'll get a lot more visibility. Thanks!

Also, the website is now redirected to: https://deeplearning4j.konduit.ai/

On top of this several popular projects have been built. This includes tensorflow-java and our project eclipse deeplearning4j: https://github.com/eclipse/deeplearning4j

Nd4j is actively developed. The latest commit was 6 hours ago. Nd4j is part of deeplearning4j which is now owned by eclipse (but the main contributors are from a company) https://github.com/eclipse/deeplearning4j/tree/master/nd4j

JavaCPP and presets for working with JNI

In the meantime you might want to check out JavaCPP: https://github.com/bytedeco/javacpp

Maybe you can use JavaCPP?

Here is the code for JNI, which uses the prebuilt JavaCPP library to call the getpid function. We don't have to write all the manual C binding code and rituals as the JavaCPP library already does it.

Javacpp is the best ffi library of all https://github.com/bytedeco/javacpp

As for our approach, we maintain a library called javacpp: https://github.com/bytedeco/javacpp which proves a python wheel like experience where we distribute natively optimized c/c++ code (and even cuda accelerated code) as jar files on maven central. We also are able to develop with a python like experience by passing pointers around and other low level constructs directly allowing optimizations that you typically only get in c/c++.

https://github.com/bytedeco/javacpp

* it maps naturally and efficiently many common features afforded by the C++ language and often considered problematic, including overloaded operators, class and function templates, callbacks through function pointers, function objects (aka functors), virtual functions and member function pointers, nested struct definitions, variable length arguments, nested namespaces, large data structures containing arbitrary cycles, virtual and multiple inheritance, passing/returning by value/reference/string/vector, anonymous unions, bit fields, exceptions, destructors and shared or unique pointers (via either try-with-resources or garbage collection), and documentation comments*

I did not try myself, but for JNI maybe this could make lives easier? https://github.com/bytedeco/javacpp