* Refactor nd4j-common: org.nd4j.* -> org.nd4j.common.*
Signed-off-by: Alex Black <blacka101@gmail.com>
* Fix CUDA (missed nd4j-common package refactoring changes)
Signed-off-by: Alex Black <blacka101@gmail.com>
* nd4j-kryo: org.nd4j -> org.nd4j.kryo
Signed-off-by: Alex Black <blacka101@gmail.com>
* Fix nd4j-common for deeplearning4j-cuda
Signed-off-by: Alex Black <blacka101@gmail.com>
* nd4j-grppc-client: org.nd4j.graph -> org.nd4j.remote.grpc
Signed-off-by: Alex Black <blacka101@gmail.com>
* deeplearning4j-common: org.deeplearning4.* -> org.deeplearning4j.common.*
Signed-off-by: Alex Black <blacka101@gmail.com>
* deeplearning4j-core: org.deeplearning4j.* -> org.deeplearning.core.*
Signed-off-by: Alex Black <blacka101@gmail.com>
* deeplearning4j-cuda: org.deeplearning4j.nn.layers.* -> org.deeplearning4j.cuda.*
Signed-off-by: Alex Black <blacka101@gmail.com>
* Import fixes
Signed-off-by: Alex Black <blacka101@gmail.com>
* deeplearning4j-nlp-*: org.deeplearning4.text.* -> org.deeplearning4j.nlp.(language).*
Signed-off-by: Alex Black <blacka101@gmail.com>
* deeplearning4j-ui-model: org.deeplearning4j.ui -> org.deeplearning4j.ui.model
Signed-off-by: Alex Black <blacka101@gmail.com>
* datavec-spark-inference-{server/model/client}: org.datavec.spark.transform -> org.datavec.spark.inference.{server/model/client}
Signed-off-by: Alex Black <blacka101@gmail.com>
* datavec-jdbc: org.datavec.api -> org.datavec.jdbc
Signed-off-by: Alex Black <blacka101@gmail.com>
* Delete org.deeplearning4j.datasets.iterator.impl.MultiDataSetIteratorAdapter in favor of (essentially identical) org.nd4j.linalg.dataset.adapter.MultiDataSetIteratorAdapter
Signed-off-by: Alex Black <blacka101@gmail.com>
* ND4S fixes
Signed-off-by: Alex Black <blacka101@gmail.com>
* Fixes
Signed-off-by: Alex Black <blacka101@gmail.com>
* nd4j-common-tests: org.nd4j.* -> org.nd4j.common.tests
Signed-off-by: Alex Black <blacka101@gmail.com>
* Trigger CI
Signed-off-by: Alex Black <blacka101@gmail.com>
* Fixes
Signed-off-by: Alex Black <blacka101@gmail.com>
* #8878 Ignore CUDA tests on modules with 'nd4j-native under cuda' issue
Signed-off-by: Alex Black <blacka101@gmail.com>
* Fix bad imports in tests
Signed-off-by: Alex Black <blacka101@gmail.com>
* Add ignore on test (already failing) due to #8882
Signed-off-by: Alex Black <blacka101@gmail.com>
* Import fixes
Signed-off-by: Alex Black <blacka101@gmail.com>
* Additional import fixes
Signed-off-by: Alex Black <blacka101@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
Description
Languages
Java
62.6%
C++
25.3%
Cuda
4.6%
Kotlin
3.2%
PureBasic
1.8%
Other
2.3%