1a35ebec2e
* Starting to switch configs of RL algorithms to use more fluent builder patterns. Many parameter choices in different algorithms default to SOTA and only be changed in specific cases Signed-off-by: Bam4d <chris.bam4d@gmail.com> * remove personal gpu-build file Signed-off-by: Bam4d <chrisbam4d@gmail.com> * refactored out configurations so they are heirarchical and re-usable, this is a step towards having a plug-and-play framework for different algorithms * backwardly compatible configurations * adding documentation to new configuration classes Signed-off-by: Bam4d <chrisbam4d@gmail.com> * private access modifiers are better suited here Signed-off-by: Bam4d <chrisbam4d@gmail.com> * RL4j does not compile without java 8 due to previous updates fixing null pointers when listener arrays are empty Signed-off-by: Bam4d <chrisbam4d@gmail.com> * fixing copyright headers Signed-off-by: Bam4d <chrisbam4d@gmail.com> * uncomment logging line Signed-off-by: Bam4d <chrisbam4d@gmail.com> * fixing default value for learningUpdateFrequency fixing test failure due to #352 Signed-off-by: Bam4d <chrisbam4d@gmail.com> Co-authored-by: Bam4d <chris.bam4d@gmail.com> |
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| .github | ||
| arbiter | ||
| datavec | ||
| deeplearning4j | ||
| docs | ||
| jumpy | ||
| libnd4j | ||
| nd4j | ||
| nd4s | ||
| pydatavec | ||
| pydl4j | ||
| rl4j | ||
| scalnet | ||
| .gitignore | ||
| CONTRIBUTING.md | ||
| Jenkinsfile | ||
| LICENSE | ||
| README.md | ||
| change-cuda-versions.sh | ||
| change-scala-versions.sh | ||
| perform-release.sh | ||
| pom.xml | ||
README.md
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:
- https://github.com/eclipse/deeplearning4j/tree/master/libnd4j
- https://github.com/eclipse/deeplearning4j/tree/master/nd4j
- https://github.com/eclipse/deeplearning4j/tree/master/datavec
- https://github.com/eclipse/deeplearning4j/tree/master/arbiter
- https://github.com/eclipse/deeplearning4j/tree/master/nd4s
- https://github.com/eclipse/deeplearning4j/tree/master/rl4j
- https://github.com/eclipse/deeplearning4j/tree/master/scalnet
- https://github.com/eclipse/deeplearning4j/tree/master/pydl4j
- https://github.com/eclipse/deeplearning4j/tree/master/jumpy
- https://github.com/eclipse/deeplearning4j/tree/master/pydatavec
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