3e2dbc65dd
* libnd4j added optional alpha and beta support to matmul Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j typos fixes Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j add optional alpha and beta to matmul_bp Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j one more typo fix Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j added optional alpha and beta to mkl implementation Signed-off-by: Oleg <oleg.semeniv@gmail.com> * MatMul alpha/beta on java side Signed-off-by: raver119 <raver119@gmail.com> * alpha/beta fix in libnd4j Signed-off-by: raver119 <raver119@gmail.com> * alpha/beta fix in matmul_bp Signed-off-by: raver119 <raver119@gmail.com> * restored view validation Signed-off-by: raver119 <raver119@gmail.com> * gemv/gemm now use MatMul op Signed-off-by: raver119 <raver119@gmail.com> * few tests fixed Signed-off-by: raver119 <raver119@gmail.com> * additional INDArray.mmul signature Signed-off-by: raver119 <raver119@gmail.com> * make C order default for INDArray.mmul, unless both A/B have F order Signed-off-by: raver119 <raver119@gmail.com> * Nd4j.gemm validation fix Signed-off-by: raver119 <raver119@gmail.com> * disable mkldnn matmul for xxf with beta != 0 case Signed-off-by: raver119 <raver119@gmail.com> * SimpleRnn workspace fix + timeouts Signed-off-by: Alex Black <blacka101@gmail.com> * two more tests + minor fix in matmul platform check Signed-off-by: raver119 <raver119@gmail.com> * Flaky test fixes Signed-off-by: Alex Black <blacka101@gmail.com> * propagate testresources profile Signed-off-by: raver119 <raver119@gmail.com> * Resources fix + flaky test fix Signed-off-by: Alex Black <blacka101@gmail.com> Co-authored-by: Oleg <oleg.semeniv@gmail.com> Co-authored-by: Alex Black <blacka101@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/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