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* #8777 MultiLayerNetwork.evaluate(MultiDataSetIterator) overload Signed-off-by: Alex Black <blacka101@gmail.com> * #8768 SameDiff.equals Signed-off-by: Alex Black <blacka101@gmail.com> * #8750 shade freemarker library and switch to it in DL4J UI Signed-off-by: Alex Black <blacka101@gmail.com> * #8704 DL4J UI redirect Signed-off-by: Alex Black <blacka101@gmail.com> * #8776 RecordReaderDataSetIterator builder collectMetaData fix Signed-off-by: Alex Black <blacka101@gmail.com> * #8718 Fix DL4J doEvaluation metadata Signed-off-by: Alex Black <blacka101@gmail.com> * #8715 ArchiveUtils - Add option to not log every extracted file Signed-off-by: Alex Black <blacka101@gmail.com> * No exception for evaluations that don't support metadata Signed-off-by: Alex Black <blacka101@gmail.com> * Fixes Signed-off-by: Alex Black <blacka101@gmail.com> * #8765 CompGraph+MDS fix for SharedTrainingMaster Signed-off-by: Alex Black <blacka101@gmail.com> * small fix Signed-off-by: Alex Black <blacka101@gmail.com> * Timeout Signed-off-by: Alex Black <blacka101@gmail.com> * Ignore Signed-off-by: Alex Black <blacka101@gmail.com> * Revert freemarker shading Signed-off-by: Alex Black <blacka101@gmail.com> * Ignore Signed-off-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