67d8199165
* Added infrastructure for implementation op lu for both cuda and cpu platforms. * Added implementation of helpers with lu op. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored LU decomposition to use vector of permutations instead. * Refactored helpers for lu op. * Fixed crash with determinant op. * Refactored cpu LU op heleper. * Added implementation for lu op. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed issue with argmax on column. * Added multithreaded behaviour for lu op helper. * Fixed multithreaded cpu implementation helpers for lu op. * Added cuda implementation for lu op helper. * Finished lu helper implementation for cuda platform. * Eliminated waste prints and comments. * Fixed race condition and multithreading issues. * Fixed memory leak with shape construction. * Corrected test for lu op to avoid near zero elements on the main diagonal." Signed-off-by: shugeo <sgazeos@gmail.com> * Improved test for adjust_constast op. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed issues with cuda implementation of resize_bicubic helpers. Signed-off-by: shugeo <sgazeos@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