Alex Black ce02b6fae7
Small fixes (#140)
* Allow scalar op result array auto allocation

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* Don't swallow underlying exception for calculateOutputShape execution failures

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* Ignore for known keras failure

Signed-off-by: AlexDBlack <blacka101@gmail.com>
2019-12-21 17:00:46 +11:00
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2019-12-21 17:00:46 +11:00
2019-11-29 16:31:03 +11:00
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2019-11-14 19:38:20 +11:00
2019-06-06 15:21:15 +03:00
2019-06-06 15:21:15 +03:00
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2019-09-10 19:09:46 +10:00

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:

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
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Readme 108 MiB
Languages
Java 62.6%
C++ 25.3%
Cuda 4.6%
Kotlin 3.2%
PureBasic 1.8%
Other 2.3%