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Abdelrauf 69d91e272a
- new implementations for Index Reductions (#421) 
* - new implementations for Index Reductions
- small fix in the legacy reduction
- disabled index reduction bench tests inside Playground

Signed-off-by: Abdelrauf <rauf@konduit.ai>

* Allow LIBND4J_TYPES

Signed-off-by: Abdelrauf <rauf@konduit.ai>

* index reduction stuff split into bunch of units

* meh

* IMax switched to new impl

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

* minor fix + test

* minor fix

* index range fix

Signed-off-by: Abdelrauf <rauf@konduit.ai>

* noop on empty outputs

* minor fix

* minor fix

Signed-off-by: Abdelrauf <rauf@konduit.ai>

* ArgMax replaces IMax

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

* argmax/argmin/argamax/argamin shape functions updated

* ArgAmax/ArgAmin/ArgMin replaces IAMax/IAMin/IMin

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

* argmax/argmin/argamax/argamin CUDA

* IMax replaced in dl4j

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

* Codegen output

* imports fixed

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

* fix compilation issue

Signed-off-by: Abdelrauf <rauf@konduit.ai>

* Auto-generate compilation units

Signed-off-by: Abdelrauf <rauf@konduit.ai>

* Should fix NDArray refactored function calls in indexReductions.cu

Signed-off-by: Abdelrauf <rauf@konduit.ai>

Co-authored-by: raver119@gmail.com <raver119@gmail.com>
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
 		2020-05-14 13:41:55 +03:00
..
ci Eclipse Migration Initial Commit 2019-06-06 15:21:15 +03:00
contrib Eclipse Migration Initial Commit 2019-06-06 15:21:15 +03:00
nd4j-backends - new implementations for Index Reductions (#421) 2020-05-14 13:41:55 +03:00
nd4j-common Fix deeplearning4j-util dependency + update remnants still using it (#428) 2020-05-04 15:54:03 +10:00
nd4j-common-tests Refactor packages to fix split package issues (#411) 2020-04-29 11:19:26 +10:00
nd4j-jdbc Refactor packages to fix split package issues (#411) 2020-04-29 11:19:26 +10:00
nd4j-parameter-server-parent Refactor packages to fix split package issues (#411) 2020-04-29 11:19:26 +10:00
nd4j-remote Refactor packages to fix split package issues (#411) 2020-04-29 11:19:26 +10:00
nd4j-serde Refactor packages to fix split package issues (#411) 2020-04-29 11:19:26 +10:00
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 Fix uberjar dependencies (#401) 2020-04-21 10:51:26 +10:00
.appveyor.yml Eclipse Migration Initial Commit 2019-06-06 15:21:15 +03:00
.codeclimate.yml Eclipse Migration Initial Commit 2019-06-06 15:21:15 +03:00
.gitignore Eclipse Migration Initial Commit 2019-06-06 15:21:15 +03:00
.travis.yml Eclipse Migration Initial Commit 2019-06-06 15:21:15 +03:00
LICENSE Eclipse Migration Initial Commit 2019-06-06 15:21:15 +03:00
README.md Various fixes (#43) 2019-11-14 19:38:20 +11:00
RaspberryPi.md Update links to eclipse repos (#252) 2019-09-10 19:09:46 +10:00
VERSION Eclipse Migration Initial Commit 2019-06-06 15:21:15 +03:00
buildAllversions.sh Eclipse Migration Initial Commit 2019-06-06 15:21:15 +03:00
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.