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* Binary deser Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com> * Binary mode for servlet Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com> * Added test Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com> * -sRandom image generation copied from datavec * -sRandom image generation copied from datavec * Remove serialization constraints * Fix: Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com> * Removed unused code Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com> * Resources usage Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com> * Async inference Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com> * Cleanup Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com> * -sTest corrected * Cleanup Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com> * Mutually eclusive serializers/deserializers Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com> * Binary output supported Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com> * Binary out test Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com> * - types hardcoded - increased payload size limit Signed-off-by: raver119 <raver119@gmail.com> * change types constant 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