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raver119 3e2dbc65dd
MatMul for gemm/gemv calls (#365) 
* libnd4j added optional alpha and beta support to matmul

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* libnd4j typos fixes

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* libnd4j add optional alpha and beta to matmul_bp

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* libnd4j one more typo fix

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* libnd4j added optional alpha and beta to mkl implementation

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* MatMul alpha/beta on java side

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

* alpha/beta fix in libnd4j

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

* alpha/beta fix in matmul_bp

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

* restored view validation

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

* gemv/gemm now use MatMul op

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

* few tests fixed

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

* additional INDArray.mmul signature

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

* make C order default for INDArray.mmul, unless both A/B have F order

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

* Nd4j.gemm validation fix

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

* disable mkldnn matmul for xxf with beta != 0 case

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

* SimpleRnn workspace fix + timeouts

Signed-off-by: Alex Black <blacka101@gmail.com>

* two more tests + minor fix in matmul platform check

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

* Flaky test fixes

Signed-off-by: Alex Black <blacka101@gmail.com>

* propagate testresources profile

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

* Resources fix + flaky test fix

Signed-off-by: Alex Black <blacka101@gmail.com>

Co-authored-by: Oleg <oleg.semeniv@gmail.com>
Co-authored-by: Alex Black <blacka101@gmail.com>
 		2020-04-10 17:57:02 +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 MatMul for gemm/gemv calls (#365) 2020-04-10 17:57:02 +03:00
nd4j-common DL4J and SameDiff integration tests + LSTMLayer java op class (#353) 2020-04-09 00:20:48 +10:00
nd4j-common-tests Various fixes (#290) 2020-03-06 00:02:32 +11:00
nd4j-jdbc Packages fix (#193) 2020-01-27 23:04:21 +03:00
nd4j-parameter-server-parent Small fixes. (#206) 2020-02-01 18:19:36 +11:00
nd4j-remote Small fixes. (#206) 2020-02-01 18:19:36 +11:00
nd4j-serde Fixes (#213) 2020-02-05 17:07:36 +11:00
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 tf.keras model import (#258) 2020-03-24 20:37:27 +11:00
nd4j-uberjar Cleanup of multiple projects (#175) 2020-01-24 22:35:00 +03:00
.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.