1d004b542a
* libnd4j first step of mkldnn for xw_plus_b and test of aurora crash in imageHelper * libnd4j sync folders with master * libnd4j merge master, raw implementation of xw_plus_b on mkldnn, clean up, need testing and adding checks for corresponded input shapes * libnd4j corrections and checks added to xw_plus_b mkl * libnd4j corrected dataType description based on mkl operation description, need more investigation * libnd4j fixe xw_blus_b mkl implementation, need testing Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j two unit tests added Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j fixed check input dimensions bug Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libndj4 one more test added to cover different order handling Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j added optional int arg support to define weights format, if arg == 1, mkldnn (do not need transpose in mkldnn implementation), else mmul weights format, corrected check points, added unit test Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j merge master Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j some improvements to avoid NDArray transpose in xw_plus_b operation Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j fixed issues connected with weights rank, also added support of one case based on tf (for mkldnn, cpu, cuda), test case added Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j added proper handling of empty inputs (all implementations) * libnd4j fixed compilation error * libnd4j several more corrections after conflict solve and fixed typos Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j removed unsupported data types Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j merge master and fixed issues Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j added propagation implementation for xw_plus_b, fixed issue connected with mkl weights data format, avoided data copy in transpose mode, test cases added, manually tested with gradCheck Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j one minor fix of double operation declaration Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j code clean up Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j minor tests fixes Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j fixed build problem, integrate helpers changes Signed-off-by: Oleg <oleg.semeniv@gmail.com> Co-authored-by: raver119 <raver119@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