2a488efb1b
* First steps for DL4J NHWC support Signed-off-by: Alex Black <blacka101@gmail.com> * Conv2d NHWC forward pass works Signed-off-by: Alex Black <blacka101@gmail.com> * Conv2d NHWC backprop Signed-off-by: Alex Black <blacka101@gmail.com> * Conv2d backprop + fixes; subsampling fwd/bwd; improve tests Signed-off-by: Alex Black <blacka101@gmail.com> * Zero padding layer NHWC support Signed-off-by: Alex Black <blacka101@gmail.com> * Cropping2D NHWC support Signed-off-by: Alex Black <blacka101@gmail.com> * Deconv2d NHWC + clean up NHWC test framework code duplication Signed-off-by: Alex Black <blacka101@gmail.com> * CnnLossLayer NHWC support Signed-off-by: Alex Black <blacka101@gmail.com> * Upsampling and batchnorm NHWC support Signed-off-by: Alex Black <blacka101@gmail.com> * Space to depth Signed-off-by: Alex Black <blacka101@gmail.com> * Depthwise pt1 Signed-off-by: Alex Black <blacka101@gmail.com> * Depthwise pt2 and LRN Signed-off-by: Alex Black <blacka101@gmail.com> * SpaceToBatch Signed-off-by: Alex Black <blacka101@gmail.com> * LocallyConnected2D Signed-off-by: Alex Black <blacka101@gmail.com> * Fix depthwise nhwc support Signed-off-by: Alex Black <blacka101@gmail.com> * Upsampling NHWC - workaround for #8857 Signed-off-by: Alex Black <blacka101@gmail.com> * Workaround for #8859 - SpaceToDepth Signed-off-by: Alex Black <blacka101@gmail.com> * Batch normalization workaround - #8860 Signed-off-by: Alex Black <blacka101@gmail.com> * cuDNN fixes Signed-off-by: Alex Black <blacka101@gmail.com> * Switch cudnn conv2d to permute based impl due to 'true' NHWC not working Signed-off-by: Alex Black <blacka101@gmail.com> * cuDNN subsampling helper NHWC fix Signed-off-by: Alex Black <blacka101@gmail.com> * Upsampling/batchnorm fixes Signed-off-by: Alex Black <blacka101@gmail.com> * Small fixes Signed-off-by: Alex Black <blacka101@gmail.com> * CNN2D NHWC gradient checks (make CNNGradientCheckTest parameterized) Signed-off-by: Alex Black <blacka101@gmail.com> * Gradient checks, SConv2d, bunch of fixes Signed-off-by: Alex Black <blacka101@gmail.com> * Small fixes Signed-off-by: Alex Black <blacka101@gmail.com> * Global pooling NHWC support Signed-off-by: Alex Black <blacka101@gmail.com> * Also test both float and double for cuDNN NHWC tests Signed-off-by: Alex Black <blacka101@gmail.com> * Javadoc Signed-off-by: Alex Black <blacka101@gmail.com> * Ignore failing keras import test until next PR Signed-off-by: Alex Black <blacka101@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