d82877b18b
* MKLDNN LSTM forward implementation (disabled pending #8331) Signed-off-by: AlexDBlack <blacka101@gmail.com> * #8318 add SameDiff.calculateGradientsAndOutputs Signed-off-by: AlexDBlack <blacka101@gmail.com> * Disable mkldnn backprop for now - pending fix, issue #8335 Signed-off-by: AlexDBlack <blacka101@gmail.com> * #8337 Fix CudaExecutioner unnecessary result array allocation/replacement Signed-off-by: AlexDBlack <blacka101@gmail.com> * Small FlatBuffers serde fix, UInt8 Signed-off-by: AlexDBlack <blacka101@gmail.com> * #8135 ImagePreProcessingScaler - add segmentation support Signed-off-by: AlexDBlack <blacka101@gmail.com> * #8319 Ensure listeners are called when they are supposed to be called Signed-off-by: AlexDBlack <blacka101@gmail.com> * #8214 UNet (non-pretrained) last conv layer kernal size fix Signed-off-by: AlexDBlack <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/gym-java-client
- 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