972fae60dc
* cleaned up bert iterator tests (#110) Signed-off-by: eraly <susan.eraly@gmail.com> * Various pre-release fixes (#111) * Various fixes Signed-off-by: AlexDBlack <blacka101@gmail.com> * Fix default dtypes for MaxPoolWithArgmax Signed-off-by: AlexDBlack <blacka101@gmail.com> * Small pre-release tweak (#112) * Log UI address on launch as in previous Play-based UI Signed-off-by: AlexDBlack <blacka101@gmail.com> * Logging level tweak for UI Signed-off-by: AlexDBlack <blacka101@gmail.com> * http not https Signed-off-by: AlexDBlack <blacka101@gmail.com> * datavec python ensure host (#113) * ensure host * one more host ensure * info->debug * [WIP] reverse improvements (#115) * initial commit Signed-off-by: raver119 <raver119@gmail.com> * reverse draft Signed-off-by: raver119 <raver119@gmail.com> * reverse kernel Signed-off-by: raver119 <raver119@gmail.com> * reverse kernel Signed-off-by: raver119 <raver119@gmail.com> * 2 micro fixes Signed-off-by: raver119 <raver119@gmail.com> * Shugeo resize fix5 (#102) * Refactored resize images ops to use TF-like bool args as input. * Refactored helpers for cpu implementation of resize_bilinear and resize_nearest_neighbor ops. * Refactored cuda implementation for image.resize_bilinear and image.resize_nearest_neighbor ops helpers. * Refactored nearest_neighbor resize op. * Added a pair of tests for special case of resize_bilinear algorithm. * Fixed issue with resize_bilinear op. * Refactored cpu implementation for helpers with resize_nearest_neighbor op. * Final fixed for resize ops to conform TF v.1.5 * Refactored cuda helpers for resize_neares_neighbor op. * Fixed resize_bilinear to accept proper data. * Fixed issue with non-float input for resize_bilinear op. * Refactored cuda helper for resize_bilinear to proper process non-float inputs. * Added tests for resize_bilinear to int inputs. * Fixed ResizeBilinear wrapper * Tests fixed * Fixed float and bool constant to avoid overflow for some kind of compilers. * Corrected float constants with float data type. * Added f suffix for float constants. * Corrected float constant to avoid overflow with initializing lists. * Corrected float initializing list with float input. * Corrected bool constant with initalizing list. * Corrected float and bool values with initializing lists. * Fixed wrong constant. * Fixed issue with 1x1 input picture for resize. * ResizeBilinear default values on import fix Signed-off-by: raver119 <raver119@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 | ||
| 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/gym-java-client
- 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