dddc8a1143
* sync after cublas*gemm Signed-off-by: raver119 <raver119@gmail.com> * mutex for CublasHelper Signed-off-by: raver119 <raver119@gmail.com> * don't store cublasHandle in LaunchContext, it's per-device anyway Signed-off-by: raver119 <raver119@gmail.com> * some printout Signed-off-by: raver119 <raver119@gmail.com> * check for field instead Signed-off-by: raver119 <raver119@gmail.com> * pew-pew Signed-off-by: raver119 <raver119@gmail.com> * don't release ContextBuffers until device changed Signed-off-by: raver119 <raver119@gmail.com> * small tweak Signed-off-by: raver119 <raver119@gmail.com> * some logging in sgemm Signed-off-by: raver119 <raver119@gmail.com> * stream sync Signed-off-by: raver119 <raver119@gmail.com> * some more logging Signed-off-by: raver119 <raver119@gmail.com> * some more error checks Signed-off-by: raver119 <raver119@gmail.com> * one fancy test Signed-off-by: raver119 <raver119@gmail.com> * one fancy test Signed-off-by: raver119 <raver119@gmail.com> * minor AffinityManager fix Signed-off-by: raver119 <raver119@gmail.com> * cudaEvent error logging improvement Signed-off-by: raver119 <raver119@gmail.com> * ConstantHelper thread safety Signed-off-by: raver119 <raver119@gmail.com> * - minor corrections in ConstantTadHelper Signed-off-by: Yurii <yurii@skymind.io> * ConstantShapeHelper thread safety Signed-off-by: raver119 <raver119@gmail.com> * ConstantTadHelper.cu updated Signed-off-by: raver119 <raver119@gmail.com> * logging off Signed-off-by: raver119 <raver119@gmail.com> * logging off 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 | ||
| 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