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Alex Black 29104083cc
Various fixes (#143) 
* #8568 ArrayUtil optimization

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

* #6171 Keras ReLU and ELU support

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

* Keras softmax layer import

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

* #8549 Webjars dependency management

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

* Fix for TF import names ':0' suffix issue / NPE

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

* BiasAdd: fix default data format for TF import

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

* Update zoo test ignores

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

* #8509 SameDiff Listener API - provide frame + iteration

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

* #8520 ND4J Environment

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

* Deconv3d

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

* Deconv3d fixes + gradient check

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

* Conv3d fixes + deconv3d DType test

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

* Fix issue with deconv3d gradinet check weight init

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

* #8579 Fix BaseCudaDataBuffer constructor fix for UINT16

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

* DataType.isNumerical() returns false for BOOL type

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

* #8504 Reduce Spark log spam for tests

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

* Clean up DL4J gradient check test spam

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

* More Gradient check spam reduction

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

* SameDiff test spam reduction

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

* Fixes for FlatBuffers mapping

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

* SameDiff log spam cleanup

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

* Tests should extend BaseNd4jTest

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

* Remove debug line in c++ op

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

* ND4J test spam cleanup

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

* DL4J test spam reduction

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

* More Dl4J and datavec test spam cleanup

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

* Fix for bad conv3d test

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

* Additional test

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

* Embedding layers: don't inherit global default activation function

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

* Trigger CI

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

* Consolidate all BaseDL4JTest classes to single class used everywhere; make timeout configurable per class

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

* Test fixes and timeout increases

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

* Timeouts and PReLU fixes

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

* Restore libnd4j build threads arg for CUDA build

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

* Increase timeouts on a few tests to avoid spurious failures on some CI machines

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

* More timeout fixes

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

* More test timeout fixes

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

* Tweak timeout for one more test

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

* Final tweaks

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

* One more ignore

Signed-off-by: AlexDBlack <blacka101@gmail.com>
 		2020-01-04 13:45:07 +11:00
..
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 Various fixes (#143) 2020-01-04 13:45:07 +11:00
nd4j-buffer Various fixes (#143) 2020-01-04 13:45:07 +11:00
nd4j-common Various fixes (#143) 2020-01-04 13:45:07 +11:00
nd4j-context Various fixes (#143) 2020-01-04 13:45:07 +11:00
nd4j-jdbc Eclipse Migration Initial Commit 2019-06-06 15:21:15 +03:00
nd4j-parameter-server-parent Various fixes (#43) 2019-11-14 19:38:20 +11:00
nd4j-remote Add support for CUDA 10.2 (#89) 2019-11-29 16:31:03 +11:00
nd4j-serde J9+ -> J8 ByteBuffer fix (#59) 2019-11-20 07:43:17 +03:00
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 Updates (#87) 2019-12-04 17:11:03 +11:00
nd4j-uberjar Add support for CUDA 10.2 (#89) 2019-11-29 16:31:03 +11:00
.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 Version upgrades (#199) 2019-08-30 14:35:27 +10:00

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.