Alex Black 578a5abb68 DNNL/MKLDNN dilated causal conv1d + betainc (#103)
* - add padding calculation in same mode in causal conv1d op for right mkl paddings

Signed-off-by: Yurii <iuriish@yahoo.com>

* - correct causal condition in mkldnnUtils.cpp

Signed-off-by: Yurii <iuriish@yahoo.com>

* - correct some code which caused additional round errors is betainc op

Signed-off-by: Yurii <iuriish@yahoo.com>

* - put float in place of template parameter in nan assign in betainc op

Signed-off-by: Yurii <iuriish@yahoo.com>
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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%