* Refactored usage of std::map to std::unordered_map instead. Signed-off-by: shugeo <sgazeos@gmail.com> * Eliminated crash with wrong ShapeDescriptor hash. Signed-off-by: shugeo <sgazeos@gmail.com> * Eliminated crash with TadDescriptor hash. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored Stash hash. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored hashes. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored TadDescriptor hash and top_k mapping. * Refactored hashes for ShapeDescriptor and TadDescriptor classes. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored hash for ConstantDescriptor and ShapeDescriptor classes. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed map using with cuda platform. Signed-off-by: shugeo <sgazeos@gmail.com> * - few rearrangements for hash functions - shared openblas allowed Signed-off-by: raver119 <raver119@gmail.com> * exports Signed-off-by: raver119 <raver119@gmail.com> * exports Signed-off-by: raver119 <raver119@gmail.com> * Stash reverted to std::map Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Added additional test. Signed-off-by: shugeo <sgazeos@gmail.com> * different maps for different compilers Signed-off-by: raver119 <raver119@gmail.com> * missing include Signed-off-by: raver119 <raver119@gmail.com> * fix the leak Signed-off-by: raver119 <raver119@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