11bddb3825
* example api Signed-off-by: Ryan Nett <rnett@skymind.io> * Lambda based evaluation Signed-off-by: Ryan Nett <rnett@skymind.io> * lambda test Signed-off-by: Ryan Nett <rnett@skymind.io> * fixes Signed-off-by: Ryan Nett <rnett@skymind.io> * partial fixes, use get-variable listener framework, example EvaluationListener Signed-off-by: Ryan Nett <rnett@skymind.io> * javadoc fix and newInstance implementations Signed-off-by: Ryan Nett <rnett@skymind.io> * fit and evaluate methods with validation data (for fit) and listeners Signed-off-by: Ryan Nett <rnett@skymind.io> * output method overloads + listener args Signed-off-by: Ryan Nett <rnett@skymind.io> * history and evaluation helpers Signed-off-by: Ryan Nett <rnett@skymind.io> * fixes Signed-off-by: Ryan Nett <rnett@skymind.io> * more fixes Signed-off-by: Ryan Nett <rnett@skymind.io> * FitConfig and added getters and setters Signed-off-by: Ryan Nett <rnett@skymind.io> * javadocs Signed-off-by: Ryan Nett <rnett@skymind.io> * fixes, javadoc, added activations to history, added latest activation listener Signed-off-by: Ryan Nett <rnett@skymind.io> * fixes, start of tests Signed-off-by: Ryan Nett <rnett@skymind.io> * fixes and updates Signed-off-by: Ryan Nett <rnett@skymind.io> * newInstance fixes, tests Signed-off-by: Ryan Nett <rnett@skymind.io> * test fixes Signed-off-by: Ryan Nett <rnett@skymind.io> * javadocs, getters with SDVariable overrides, CustomEvaluation fix Signed-off-by: Ryan Nett <rnett@skymind.io> * more operation config classes (evaluation, output, exec/single batch output), fix custom eval tests Signed-off-by: Ryan Nett <rnett@skymind.io> * merge fixes Signed-off-by: Ryan Nett <rnett@skymind.io> * fix Signed-off-by: Ryan Nett <rnett@skymind.io> * fixes, most old fit/evaluate/output methods use the builders Signed-off-by: Ryan Nett <rnett@skymind.io> * fixes Signed-off-by: Ryan Nett <rnett@skymind.io> * numerous fixes/cleanup Signed-off-by: Ryan Nett <rnett@skymind.io> * fixes Signed-off-by: Ryan Nett <rnett@skymind.io> * javadoc Signed-off-by: Ryan Nett <rnett@skymind.io> * Polish round 1 Signed-off-by: AlexDBlack <blacka101@gmail.com> * Round 2 Signed-off-by: AlexDBlack <blacka101@gmail.com> * Formatting + round 3 Signed-off-by: AlexDBlack <blacka101@gmail.com> * Round 4 Signed-off-by: AlexDBlack <blacka101@gmail.com> |
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| .github | ||
| arbiter | ||
| datavec | ||
| deeplearning4j | ||
| docs | ||
| gym-java-client | ||
| jumpy | ||
| libnd4j | ||
| nd4j | ||
| nd4s | ||
| pydatavec | ||
| pydl4j | ||
| rl4j | ||
| scalnet | ||
| .gitignore | ||
| CONTRIBUTING.md | ||
| Jenkinsfile | ||
| LICENSE | ||
| README.md | ||
| change-cuda-versions.sh | ||
| change-scala-versions.sh | ||
| change-spark-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/deeplearning4j/libnd4j
- https://github.com/deeplearning4j/nd4j
- https://github.com/deeplearning4j/datavec
- https://github.com/deeplearning4j/arbiter
- https://github.com/deeplearning4j/nd4s
- https://github.com/deeplearning4j/gym-java-client
- https://github.com/deeplearning4j/rl4j
- https://github.com/deeplearning4j/scalnet
- https://github.com/deeplearning4j/pydl4j
- https://github.com/deeplearning4j/jumpy
- https://github.com/deeplearning4j/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/deeplearning4j/dl4j-examples
In the examples repo, you'll also find a tutorial series in Zeppelin: https://github.com/deeplearning4j/dl4j-examples/tree/master/tutorials