fe47f52896
* Libnd4j: TensorMMul backprop op #8174, raw implementation Signed-off-by: Oleg <oleg.semeniv@gmail.com> * Libnd4j: TensorMMul backprop op #8174 merge master and some corrections Signed-off-by: Oleg <oleg.semeniv@gmail.com> * Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master * Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation Signed-off-by: Oleg <oleg.semeniv@gmail.com> * Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes Signed-off-by: Oleg <oleg.semeniv@gmail.com> * Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing Signed-off-by: Oleg <oleg.semeniv@gmail.com> * Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply Signed-off-by: Oleg <oleg.semeniv@gmail.com> * Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1 Signed-off-by: Oleg <oleg.semeniv@gmail.com> * Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test Signed-off-by: Oleg <oleg.semeniv@gmail.com> * Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs Signed-off-by: Oleg <oleg.semeniv@gmail.com> * Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f Signed-off-by: Oleg <oleg.semeniv@gmail.com> * Libnd4j: TensorMMul backprop op #8174 sync master Signed-off-by: Oleg <oleg.semeniv@gmail.com> * - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC) Signed-off-by: Yurii <iuriish@yahoo.com> * Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring Signed-off-by: Oleg <oleg.semeniv@gmail.com> * - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot Signed-off-by: Yurii <iuriish@yahoo.com> * - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure Signed-off-by: Yurii <iuriish@yahoo.com> * - further work on problem of wrong shape evaluation during permute/reshape procedures Signed-off-by: Yurii <iuriish@yahoo.com> * - still looking for bug reason in reshape/permute stuff Signed-off-by: Yurii <iuriish@yahoo.com> * - correct bug in transform cuda native ops Signed-off-by: Yurii <iuriish@yahoo.com> * - correct bug in NDArray::assign Signed-off-by: Yurii <iuriish@yahoo.com> * - remove old shape::reshape stuff Signed-off-by: Yurii <iuriish@yahoo.com> * - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class Signed-off-by: Yurii <iuriish@yahoo.com> * - correct bug in tensorDot which had to do with wrong pointers assigments Signed-off-by: Yurii <iuriish@yahoo.com> Co-authored-by: Oleh <oleg.semeniv@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