eea3062ccf
* - start working on space_to_batch_nd Signed-off-by: Yurii <yurii@skymind.io> * - provide cpu helper for space_to_batch_nd op Signed-off-by: Yurii <yurii@skymind.io> * few typos fixed Signed-off-by: raver119 <raver119@gmail.com> * - add tests for space_to_batch and correct bugs Signed-off-by: Yurii <yurii@skymind.io> * - write cuda kernel for space_to_batch op Signed-off-by: Yurii <yurii@skymind.io> * - add order argument to shape::index2coords method in convolution cuda ops Signed-off-by: Yurii <yurii@skymind.io> * - restore some previous code Signed-off-by: Yurii <yurii@skymind.io> * old col2im kernel activated Signed-off-by: raver119 <raver119@gmail.com> * - change coords calculation in col2im kernel Signed-off-by: Yurii <yurii@skymind.io> * - restore old col2im kernel Signed-off-by: Yurii <yurii@skymind.io> * - add custom op for batch_to_space Signed-off-by: Yurii <yurii@skymind.io> * - provide cpu version for batch_to_space_nd op Signed-off-by: Yurii <yurii@skymind.io> * - provide cuda kernel for batch_to_space_nd op Signed-off-by: Yurii <yurii@skymind.io> |
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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