7a7ee4b021
* - implementation of cudnn batchnorm_bp op Signed-off-by: Yurii <iuriish@yahoo.com> * - testing and fixing bugs in batchnorm_bp based on cudnn api Signed-off-by: Yurii <iuriish@yahoo.com> * - move pooling mkl code and delete some unnecessary files Signed-off-by: Yurii <iuriish@yahoo.com> * - implementation and testing cudnn pooling2d ops (avg/max, ff/bp) Signed-off-by: Yurii <iuriish@yahoo.com> * - implementation and testing cudnn pooling 3d (ff/bp) ops Signed-off-by: Yurii <iuriish@yahoo.com> * - provide ff step in case of cudnn maxpool3d_bp op Signed-off-by: Yurii <iuriish@yahoo.com> * - remove half type from set of supported types in mkl dpethwise conv op Signed-off-by: Yurii <iuriish@yahoo.com> * - bring back cudaStreamSynchronize in batchnorm and pooling cudnn ops Signed-off-by: Yurii <iuriish@yahoo.com> Co-authored-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/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