d871eab2e5
* [WIP] maxpool2d_bp fix (#160) * one test for maxpool2d_bp Signed-off-by: raver119 <raver119@gmail.com> * - maxpool2d_bp cuda fix for NaNs - streamSync after each custom op execution Signed-off-by: raver119 <raver119@gmail.com> * MLN/CG: Don't swallow exceptions if a second exception occurs during workspace closing (#161) Signed-off-by: AlexDBlack <blacka101@gmail.com> * Upgrade protobuf version (#162) * First steps for protobuf version upgrade Signed-off-by: AlexDBlack <blacka101@gmail.com> * Phase 2 Signed-off-by: AlexDBlack <blacka101@gmail.com> * Update imports to shaded protobuf Signed-off-by: AlexDBlack <blacka101@gmail.com> * Version fix Signed-off-by: AlexDBlack <blacka101@gmail.com> * Switch to single execution for protobuf codegen to work around plugin bug Signed-off-by: AlexDBlack <blacka101@gmail.com> * Automatically delete old PB generated files after name change Signed-off-by: Alex Black <blacka101@gmail.com> * - string NDArray flat serde impl + tests (#163) - string NDArray equalsTo impl Signed-off-by: raver119 <raver119@gmail.com> * get rid of context variable Signed-off-by: raver119 <raver119@gmail.com> * lup context fix (#164) Signed-off-by: raver119 <raver119@gmail.com> |
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| .github | ||
| arbiter | ||
| datavec | ||
| deeplearning4j | ||
| docs | ||
| gym-java-client | ||
| jumpy | ||
| libnd4j | ||
| nd4j | ||
| nd4s | ||
| pydatavec | ||
| pydl4j | ||
| rl4j | ||
| scalnet | ||
| .gitignore | ||
| CONTRIBUTING.md | ||
| Jenkinsfile | ||
| LICENSE | ||
| README.md | ||
| change-cuda-versions.sh | ||
| change-scala-versions.sh | ||
| change-spark-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/deeplearning4j/libnd4j
- https://github.com/deeplearning4j/nd4j
- https://github.com/deeplearning4j/datavec
- https://github.com/deeplearning4j/arbiter
- https://github.com/deeplearning4j/nd4s
- https://github.com/deeplearning4j/gym-java-client
- https://github.com/deeplearning4j/rl4j
- https://github.com/deeplearning4j/scalnet
- https://github.com/deeplearning4j/pydl4j
- https://github.com/deeplearning4j/jumpy
- https://github.com/deeplearning4j/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/deeplearning4j/dl4j-examples
In the examples repo, you'll also find a tutorial series in Zeppelin: https://github.com/deeplearning4j/dl4j-examples/tree/master/tutorials