The Eclipse Deeplearning4J (DL4J) ecosystem is a set of projects intended to support all the needs of a JVM based deep learning application. This means starting with the raw data, loading and preprocessing it from wherever and whatever format it is in to building and tuning a wide variety of simple and complex deep learning networks.
Because Deeplearning4J runs on the JVM you can use it with a wide variety of JVM based languages other than Java, like Scala, Kotlin, Clojure and many more.
The DL4J stack comprises of:
All projects in the DL4J ecosystem support Windows, Linux and macOS. Hardware support includes CUDA GPUs (10.0, 10.1, 10.2 except OSX), x86 CPU (x86_64, avx2, avx512), ARM CPU (arm, arm64, armhf) and PowerPC (ppc64le).
For support for the project, please go over to https://community.konduit.ai/
Deeplearning4J has quite a few dependencies. For this reason we only support usage with a build tool.
<dependencies> <dependency> <groupId>org.deeplearning4j</groupId> <artifactId>deeplearning4j-core</artifactId> <version>1.0.0-M2.1</version> </dependency> <dependency> <groupId>org.nd4j</groupId> <artifactId>nd4j-native-platform</artifactId> <version>1.0.0-M2.1</version> </dependency> </dependencies>
Add these dependencies to your pom.xml file to use Deeplearning4J with the CPU backend. A full standalone project example is available in the example repository, if you want to start a new Maven project from scratch.
Due to DL4J being a multi faceted project with several modules in the mono repo, we recommend looking at the examples for a taste of different usages of the different modules. Below we'll link to examples for each module.
For users looking for being able to run models from other frameworks, see:
You can find the official documentation for Deeplearning4J and the other libraries of its ecosystem at http://deeplearning4j.konduit.ai/.
We have separate repository with various examples available: https://awesomeopensource.com/project/eclipse/deeplearning4j-examples
It is preferred to use the official pre-compiled releases (see above). But if you want to build from source, first take a look at the prerequisites for building from source here: https://deeplearning4j.konduit.ai/multi-project/how-to-guides/build-from-source. Various instructions for cpu and gpu builds can be found there. Please go to our forums for further help.
In order to run tests, please see the platform-tests module. This module only runs on jdk 11 (mostly due to spark and bugs with older scala versions + JDK 17)
platform-tests allows you to run dl4j for different backends. There are a few properties you can specify on the command line:
More parameters can be found here: https://github.com/deeplearning4j/deeplearning4j/blob/c1bf8717e4839c8930e9c43183bf7b94d0cf84dc/platform-tests/pom.xml#L47
Deeplearning4J is actively developed by the team at Konduit K.K..
[If you need any commercial support feel free to reach out to us. at [email protected]