032b97912e
* working on ALE image pipelines that appear to lose data * transformation pipeline for ALE has been broken for a while and needed some cleanup to make sure that openCV tooling for scene transforms was actually working. * allowing history length to be set and passed through to history merge transforms Signed-off-by: Bam4d <chrisbam4d@gmail.com> * native image loader is not thread-safe so should not be static Signed-off-by: Bam4d <chrisbam4d@gmail.com> * make sure the transformer for encoding observations that are not pixels converts corectly Signed-off-by: Bam4d <chrisbam4d@gmail.com> * Test fixes for ALE pixel observation shape Signed-off-by: Bam4d <chrisbam4d@gmail.com> * Fix compilation errors Signed-off-by: Samuel Audet <samuel.audet@gmail.com> * fixing some post-merge issues, and comments from PR Signed-off-by: Bam4d <chrisbam4d@gmail.com> Co-authored-by: Samuel Audet <samuel.audet@gmail.com>
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