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* initial commit Signed-off-by: raver119 <raver119@gmail.com> * bunch of tweaks Signed-off-by: raver119 <raver119@gmail.com> * hamming distance nullification Signed-off-by: raver119 <raver119@gmail.com> * Add output array value assignment for testing/debugging Signed-off-by: Alex Black <blacka101@gmail.com> * don't assign empty arrays Signed-off-by: raver119 <raver119@gmail.com> * conv2d/conv3d/depthwise2d nullified Signed-off-by: raver119 <raver119@gmail.com> * conv2d/conv3d/depthwise2d nullified Signed-off-by: raver119 <raver119@gmail.com> * conv2d/conv3d/depthwise2d nullified Signed-off-by: raver119 <raver119@gmail.com> * few more fixes Signed-off-by: raver119 <raver119@gmail.com> * im2col Signed-off-by: raver119 <raver119@gmail.com> * pooling? Signed-off-by: raver119 <raver119@gmail.com> * more nullified Signed-off-by: raver119 <raver119@gmail.com> * ismax nullified Signed-off-by: raver119 <raver119@gmail.com> * rollback ismax nullification Signed-off-by: raver119 <raver119@gmail.com> * synchronized cublas handle use on per-device basis Signed-off-by: raver119 <raver119@gmail.com> * hiding method from jcpp Signed-off-by: raver119 <raver119@gmail.com> * get rid of test assigns in DeclarableOp Signed-off-by: raver119 <raver119@gmail.com> * get rid of assigns Signed-off-by: raver119 <raver119@gmail.com> * proper deviceId is back Signed-off-by: raver119 <raver119@gmail.com> * include fixed Signed-off-by: raver119 <raver119@gmail.com> Co-authored-by: Alex Black <blacka101@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