shugeo 1e9ff114aa Shugeo atomic tests (#97)
* Added atomic tests for atomicAdd, atomicSub and atomicDiv.

* Fixed atomicAdd for 16bit ints.

* Fixed atomicMul for 16 floats.

* Eliminated waste prints.

* Fixed problems with double type on matrix inverse helepers.

* Eliminated commented wrong code.

* Refactored atomicMul for 16bit types.

* few more minor tweaks

Signed-off-by: raver119 <raver119@gmail.com>

* Fixed fake_quant_with_min_max_vars_per_channel args processing.
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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%