cavis/nd4j
Samuel Audet 029b84e2b7
Development updates (#9053)
* 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>
2020-07-26 21:59:27 +09:00
..
ADRs Add SameDiff file format ADR [WIP] (#467) 2020-05-16 22:44:31 +10:00
nd4j-backends Development updates (#9053) 2020-07-26 21:59:27 +09:00
nd4j-common Fix deeplearning4j-util dependency + update remnants still using it (#428) 2020-05-04 15:54:03 +10:00
nd4j-common-tests Assorted fixes (#466) 2020-05-15 15:34:08 +10:00
nd4j-jdbc Development updates (#9053) 2020-07-26 21:59:27 +09:00
nd4j-parameter-server-parent Development updates (#9053) 2020-07-26 21:59:27 +09:00
nd4j-remote Development updates (#9053) 2020-07-26 21:59:27 +09:00
nd4j-serde Development updates (#9053) 2020-07-26 21:59:27 +09:00
nd4j-shade nd4j-jackson: exclude java.xml.stream.XML*Factory from service loader to avoid clashes with other non-shaded jackson etc on classpath 2019-12-13 21:41:28 +11:00
nd4j-tensorflow Refactor packages to fix split package issues (#411) 2020-04-29 11:19:26 +10:00
nd4j-uberjar Development updates (#9053) 2020-07-26 21:59:27 +09:00
.gitignore Eclipse Migration Initial Commit 2019-06-06 15:21:15 +03:00
README.md Improves README (#8973) 2020-07-25 20:33:12 +09:00
RaspberryPi.md Update links to eclipse repos (#252) 2019-09-10 19:09:46 +10:00
buildmultiplescalaversions.sh Eclipse Migration Initial Commit 2019-06-06 15:21:15 +03:00
pom.xml Cleanup of multiple projects (#175) 2020-01-24 22:35:00 +03:00

README.md

ND4J: Scientific Computing on the JVM

Join the chat at https://gitter.im/deeplearning4j/deeplearning4j Maven Central Javadoc

ND4J is an Apache 2.0-licensed scientific computing library for the JVM. By contributing code to this repository, you agree to make your contribution available under an Apache 2.0 license.

It is meant to be used in production environments rather than as a research tool, which means routines are designed to run fast with minimum RAM requirements.

Please search for the latest version on search.maven.org.

Or use the versions displayed in: https://github.com/eclipse/deeplearning4j-examples/blob/master/pom.xml


Main Features

  • Versatile n-dimensional array object
  • Multiplatform functionality including GPUs
  • Linear algebra and signal processing functions

Specifics

  • Supports GPUs via with the CUDA backend nd4j-cuda-7.5 and Native via nd4j-native.
  • All of this is wrapped in a unifying interface.
  • The API mimics the semantics of Numpy, Matlab and scikit-learn.

Documentation

Documentation is available at deeplearning4j.org. Access the JavaDocs for more detail.


Installation

To install ND4J, there are a couple of approaches, and more information can be found on the DL4J website.

Install from Maven Central

  1. Search for nd4j in the Maven Central Repository to find the available nd4j jars.
  2. Include the appropriate dependency in your pom.xml.

Clone from the GitHub Repo

https://deeplearning4j.org/docs/latest/deeplearning4j-build-from-source

Contribute

  1. Check for open issues, or open a new issue to start a discussion around a feature idea or a bug.

  2. If you feel uncomfortable or uncertain about an issue or your changes, feel free to contact us on Gitter using the link above.

  3. Fork the repository on GitHub to start making your changes to the master branch (or branch off of it).

  4. Write a test, which shows that the bug was fixed or that the feature works as expected.

  5. Note the repository follows the Google Java style with two modifications: 120-char column wrap and 4-spaces indentation. You can format your code to this format by typing mvn formatter:format in the subproject you work on, by using the contrib/formatter.xml at the root of the repository to configure the Eclipse formatter, or by using the IntelliJ plugin.

  6. Send a pull request, and bug us on Gitter until it gets merged and published.