Yurii Shyrma 948646b32d
Shyrma mkl test (#211)
* - provide nhwc format in mkl conv ops

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

* - corrections in mkl conv3d

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

* - corrections in mkl batchnorm

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

* - corrections in mkl maxpooling2d

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

* - add format format_tag::any to outputs in mkl conv ops

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

* - complete corrections in mkl conv ops

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

* - add test for comparison of execution speeds of mkl conv2d op with different weights format

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

* - take into account order f in mkl conv ops

Signed-off-by: Yurii <iuriish@yahoo.com>
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2020-02-05 17:07:36 +11:00
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2020-02-05 17:07:36 +11:00
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2020-01-27 16:03:00 +11:00

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%