815a2908af
* Added implementation of the triangular_solve op. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed compilation issues. Signed-off-by: shugeo <sgazeos@gmail.com> * Added verification of input data and helpers facilities for triangular_solve op.' Signed-off-by: shugeo <sgazeos@gmail.com> * Added cpu implementation for triangular_solve helpers. * Added tests and implementation for upper triangular equations. Signed-off-by: shugeo <sgazeos@gmail.com> * Added a pair of cases to tests. Signed-off-by: shugeo <sgazeos@gmail.com> * Added multithreading with cpu helpers for triangular_solve op. Signed-off-by: shugeo <sgazeos@gmail.com> * Added cuda implementation of triangular_solve op helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Finished cuda implementation of triangular_solve helpers and tests. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed copyright marks. Signed-off-by: shugeo <sgazeos@gmail.com> * Corrected grammar errors with doc and error messages. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored matricies processing with triangular_solve cuda helper implementation. Signed-off-by: shugeo <sgazeos@gmail.com> * Added triangular_solve wrapper * Fixed mapping * Added processing for adjoint with cpu helpers of triangular_solve op implementation. Signed-off-by: shugeo <sgazeos@gmail.com> * Added implementation for adjoint routine with cuda platform. Signed-off-by: shugeo <sgazeos@gmail.com> * Added multithreading with adjoint routine for cpu platform. Signed-off-by: shugeo <sgazeos@gmail.com> Co-authored-by: Alexander Stoyakin <alexander.stoyakin@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