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* mmul op instead of cublasSgemm Signed-off-by: raver119 <raver119@gmail.com> * transB Signed-off-by: raver119 <raver119@gmail.com> * jcpp handles Signed-off-by: raver119 <raver119@gmail.com> * bitwise and/or/xor Signed-off-by: raver119 <raver119@gmail.com> * bitwise and/or/xor mapping Signed-off-by: raver119 <raver119@gmail.com> * cuda/cublas version check Signed-off-by: raver119 <raver119@gmail.com> * add expected version Signed-off-by: raver119 <raver119@gmail.com> * cuda/cublas version check in java Signed-off-by: raver119 <raver119@gmail.com> * one more error check Signed-off-by: raver119 <raver119@gmail.com> * build fix Signed-off-by: raver119 <raver119@gmail.com> * build fix Signed-off-by: raver119 <raver119@gmail.com> * build fix Signed-off-by: raver119 <raver119@gmail.com> * one more fix Signed-off-by: raver119 <raver119@gmail.com> * skip CUDA version check for now Signed-off-by: raver119 <raver119@gmail.com> * better wording Signed-off-by: raver119 <raver119@gmail.com> * few more tweaks Signed-off-by: raver119 <raver119@gmail.com> * few more tweaks Signed-off-by: raver119 <raver119@gmail.com>
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