* one noop test Signed-off-by: raver119 <raver119@gmail.com> * skip input validation for no-input ops Signed-off-by: raver119 <raver119@gmail.com> * - one more noop empty test - one more validation before sync Signed-off-by: raver119 <raver119@gmail.com> * typo Signed-off-by: raver119 <raver119@gmail.com> * one more validation fix Signed-off-by: raver119 <raver119@gmail.com> * CUDA empty reductions java side Signed-off-by: raver119 <raver119@gmail.com> * one svd test Signed-off-by: raver119 <raver119@gmail.com> * Corrected segment_mean helpers and added another test. * Refactored segment_mean kernels to avoid race_condition. |
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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