330a69d4e2
* lstsq op. Initial commit. Signed-off-by: shugeo <sgazeos@gmail.com> * Least squares linear problem solve op (lstsq). Cpu draft implementation. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed shape routine and tests. Signed-off-by: shugeo <sgazeos@gmail.com> * Added test for lstsq op. Signed-off-by: shugeo <sgazeos@gmail.com> * Rectification for lstsq op implementation. Signed-off-by: shugeo <sgazeos@gmail.com> * Corrected test to avoid numerical inconsistensy. Signed-off-by: shugeo <sgazeos@gmail.com> * Added prints for check computing. Signed-off-by: shugeo <sgazeos@gmail.com> * Corrected tests to use evalueate facility instead. Signed-off-by: shugeo <sgazeos@gmail.com> * CPU implementation of MatrixSolveLs op and tests. Signed-off-by: shugeo <sgazeos@gmail.com> * Added cuda implementation for helpers with lstsq op. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored tests for lstsq op. Signed-off-by: shugeo <sgazeos@gmail.com> * Added processing for empty inputs. Signed-off-by: shugeo <sgazeos@gmail.com> * Merged tests. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored lstsq op for fast case. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed test. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored lstsq op. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed some issues with solve. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed lstsq op to avoid erros. Signed-off-by: shugeo <sgazeos@gmail.com> * Added kernel for giagonal factor Signed-off-by: shugeo <sgazeos@gmail.com> * lstsq wrapper and triangular_solve fixed * Added proper processing empty inputs and test. Signed-off-by: shugeo <sgazeos@gmail.com> * SequenceMask test * Build fixed * Added proper processing of empty inputs with solve op. Signed-off-by: shugeo <sgazeos@gmail.com> * Mapping added * Added check of input shapes with solve op. Signed-off-by: shugeo <sgazeos@gmail.com> * Added a couple of tests for lstsq op and minor changes with cuda helper for one.' Signed-off-by: shugeo <sgazeos@gmail.com> * Tests on * Refactored test for lstsq op. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed test * Added another approach for lstsq op aka solve_ls. Signed-off-by: shugeo <sgazeos@gmail.com> * Finished cpu part for solve_ls op helpers. * Added helper for low triangular matrix inversion. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored alternate solve_ls cpu implementation. Signed-off-by: shugeo <sgazeos@gmail.com> * Removed alternate approach for solve_ls op. Added multithreading with matrix inversion. Signed-off-by: shugeo <sgazeos@gmail.com> * Assert fixed * Refactored multithreading for inverse matricies. Signed-off-by: shugeo <sgazeos@gmail.com> Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com> |
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| .github | ||
| arbiter | ||
| datavec | ||
| deeplearning4j | ||
| docs | ||
| jumpy | ||
| libnd4j | ||
| nd4j | ||
| nd4s | ||
| pydatavec | ||
| pydl4j | ||
| rl4j | ||
| scalnet | ||
| .gitignore | ||
| CONTRIBUTING.md | ||
| Jenkinsfile | ||
| LICENSE | ||
| README.md | ||
| change-cuda-versions.sh | ||
| change-scala-versions.sh | ||
| perform-release.sh | ||
| pom.xml | ||
README.md
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