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Description

Eclipse Deeplearning4J is part of the Skymind Intelligence Layer, along with ND4J, DataVec, Arbiter and RL4J. It is an Apache 2.0-licensed, open-source, distributed neural net library written in Java and Scala. By contributing code to this repository, you agree to make your contribution available under an Apache 2.0 license.

Deeplearning4J integrates with Hadoop and Spark and runs on several backends that enable use of CPUs and GPUs. The aim is to create a plug-and-play solution that is more convention than configuration, and which allows for fast prototyping.

The most recent stable release in Maven Central is 0.9.1, and the current master on Github can be built from source.

For more info, see: https://docs.skymind.ai/docs

Code Quality Rank: L1
Programming language: Java
Latest version: v1.0.0

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README

Monorepo of Deeplearning4j

Welcome to the new monorepo of Deeplearning4j that contains the source code for all the following projects, in addition to the original repository of Deeplearning4j moved to [deeplearning4j](deeplearning4j):

To build everything, we can use commands like

./change-cuda-versions.sh x.x
./change-scala-versions.sh 2.xx
./change-spark-versions.sh x
mvn clean install -Dmaven.test.skip -Dlibnd4j.cuda=x.x -Dlibnd4j.compute=xx

or

mvn -B -V -U clean install -pl '!jumpy,!pydatavec,!pydl4j' -Dlibnd4j.platform=linux-x86_64 -Dlibnd4j.chip=cuda -Dlibnd4j.cuda=9.2 -Dlibnd4j.compute=<your GPU CC> -Djavacpp.platform=linux-x86_64 -Dmaven.test.skip=true

An example of GPU "CC" or compute capability is 61 for Titan X Pascal.

Want some examples?

We have separate repository with various examples available: https://github.com/eclipse/deeplearning4j-examples

In the examples repo, you'll also find a tutorial series in Zeppelin: https://github.com/eclipse/deeplearning4j-examples/tree/master/tutorials