029b84e2b7
* RL4J: Add generic update rule (#502) Signed-off-by: Alexandre Boulanger <aboulang2002@yahoo.com> * Shyrma reduce (#481) * - start working on improving of cpu legacy code for reduce ops Signed-off-by: Yurii <iuriish@yahoo.com> * - further work on improving legacy loops Signed-off-by: Yurii <iuriish@yahoo.com> * - still working on improving reduce ops Signed-off-by: Yurii <iuriish@yahoo.com> * - further work on improving reduce ops Signed-off-by: Yurii <iuriish@yahoo.com> * - testing speed run of new reduce op Signed-off-by: Yurii <iuriish@yahoo.com> * - working on improvement of default loop for reduce op Signed-off-by: Yurii <iuriish@yahoo.com> * - update signatures of stuff which calls reduce ops Signed-off-by: Yurii <iuriish@yahoo.com> * - make corrections in cuda reduce kernels Signed-off-by: Yurii <iuriish@yahoo.com> * - change loop for default case in broadcast legacy ops Signed-off-by: Yurii <iuriish@yahoo.com> * - comment some shape stuff Signed-off-by: Yurii <iuriish@yahoo.com> * - comment unnecessary prints in RNGtests Signed-off-by: Yurii <iuriish@yahoo.com> * - finish to resolve conflicts after master has been merged Signed-off-by: Yurii <iuriish@yahoo.com> * - get rid of some compilation mistakes of cuda stuff Signed-off-by: Yurii <iuriish@yahoo.com> * - minor changes Signed-off-by: Yurii <iuriish@yahoo.com> * - further search for bug causing crash on java test Signed-off-by: Yurii <iuriish@yahoo.com> * - add scalar case in reduce_ ... exec stuff Signed-off-by: Yurii <iuriish@yahoo.com> * - minor corrections in NAtiveOps.cu Signed-off-by: Yurii <iuriish@yahoo.com> * - add switch to scalar case execReduceXD functions Signed-off-by: Yurii <iuriish@yahoo.com> * - add support for vectors old shape in ConstantShapeHelper::createShapeInfoWithNoUnitiesForReduce Signed-off-by: Yurii <iuriish@yahoo.com> * - correct cuda mirrorPad Signed-off-by: Yurii <iuriish@yahoo.com> * - add support for vectors old shape in cuda createShapeInfoWithNoUnitiesForReduce Signed-off-by: Yurii <iuriish@yahoo.com> Co-authored-by: raver119 <raver119@gmail.com> * Add support for CUDA 11.0 (#492) * Add support for CUDA 11.0 * libnd4j tweaks for CUDA 11 Signed-off-by: raver119@gmail.com <raver119@gmail.com> * bindings update, again? Signed-off-by: raver119@gmail.com <raver119@gmail.com> * * Update versions of JavaCPP Presets for FFmpeg, OpenBLAS, and NumPy * update API to match CUDA 8 Signed-off-by: raver119@gmail.com <raver119@gmail.com> * * Update version of JavaCPP Presets for CPython * C++ updated for cuDNN 8.0 Signed-off-by: raver119@gmail.com <raver119@gmail.com> * one more test Signed-off-by: raver119@gmail.com <raver119@gmail.com> * one more test Signed-off-by: raver119@gmail.com <raver119@gmail.com> * one more test Signed-off-by: raver119@gmail.com <raver119@gmail.com> * 128-bit alignment for workspaces Signed-off-by: raver119@gmail.com <raver119@gmail.com> * change seed in 1 test Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Fix dependecy duplication in python4j-parent pom * Fix group id for in python4j-numpy * few tests tweaked Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Remove macosx-x86_64-gpu from nd4j-tests-tensorflow * few minor tweaks for IndexReduce Signed-off-by: raver119@gmail.com <raver119@gmail.com> * one test removed Signed-off-by: raver119@gmail.com <raver119@gmail.com> Co-authored-by: raver119@gmail.com <raver119@gmail.com> Co-authored-by: Serhii Shepel <9946053+sshepel@users.noreply.github.com> * RL4J: Add SyncTrainer and AgentLearnerBuilder for a few algorithms (#504) Signed-off-by: Alexandre Boulanger <aboulang2002@yahoo.com> Co-authored-by: Alexandre Boulanger <44292157+aboulang2002@users.noreply.github.com> Co-authored-by: Yurii Shyrma <iuriish@yahoo.com> Co-authored-by: raver119 <raver119@gmail.com> Co-authored-by: Serhii Shepel <9946053+sshepel@users.noreply.github.com> |
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| pom.xml | ||
| sbt-pom.xml | ||
README.md
ScalNet
ScalNet is a wrapper around Deeplearning4J emulating a Keras like API for deep learning.
ScalNet is released under an Apache 2.0 license. By contributing code to this repository, you agree to make your contribution available under an Apache 2.0 license.
ScalNet is STILL ALPHA and we are open sourcing this in an attempt to get feedback.
Come in to gitter if you are interested in learning more.
Prerequisites
- JDK 8
- Scala 2.11.+ or 2.10.x
- SBT and Maven
How to build
ScalNet depends on Deeplearning4j and ND4J
sbt
ScalNet uses sbt, but due to resolving issues, you must have Maven available to copy some nd4j-native dependencies in your classpath, in order to run the examples.
This is automatically done in build.sbt and you don't need to do anything besides having maven installed.
If you use sbt in your own project, you will probably have to proceed the same way. When ScalNet will be using releases instead of snapshots, this won't be necessary anymore.
To build, use:
$ sbt package
Alternatively, for some quick testing or usage in Jupyter for example, run:
$ sbt assembly
To obtain a JAR file with all needed dependencies.
See the official sbt documentation for more on how to use sbt.
Maven
Althought Maven is mainly used for release management, you can use the provided pom.xml to import ScalNet as a Maven project.
Target for scala 2.11
$ change-scala-versions.sh "2.11"
$ mvn package
Target for scala 2.10
$ change-scala-versions.sh "2.10"
$ mvn package
How to use
sbt
libraryDependencies ++= "org.deeplearning4j" % "scalnet_2.11" % "0.9.2-SNAPSHOT"
Maven
<dependency>
<groupId>org.deeplearning4j</groupId>
<artifactId>scalnet_2.11</artifactId>
<version>0.9.2-SNAPSHOT</version>
</dependency>
Getting started
ScalNet uses a Keras like API, wrapping deeplearning4j to make it more easier to start with.
Also, since you can call Java code from Scala, you can still use everything from deeplearning4j.
To see what ScalNet has to offer, run one of the [examples] (https://github.com/eclipse/deeplearning4j/tree/master/scalnet/src/test/scala/org/deeplearning4j/scalnet/examples) it ships with.
Please note that those examples are not state-of-the-art in any way, they're just enough to get you started.