483c3d7b8c
* #8565 Normalizer toString/hashcode Signed-off-by: Alex Black <blacka101@gmail.com> * #8731 ImagePreProcessingScaler lables/segmentation fix Signed-off-by: Alex Black <blacka101@gmail.com> * #8691 Fix SameDiffLayer/Vertx finetuning and parameter setting support Signed-off-by: Alex Black <blacka101@gmail.com> * #8663 DL4J embedding layer weight init - don't depend on vocab size Signed-off-by: Alex Black <blacka101@gmail.com> * EmbeddingLayer test tweak Signed-off-by: Alex Black <blacka101@gmail.com> |
||
---|---|---|
.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