2b0d7b3b52
* Nd4j pad update Signed-off-by: Ryan Nett <rnett@skymind.io> * switched from guava Immutables to Collections.unmodifiableList/Map Signed-off-by: Ryan Nett <rnett@skymind.io> * javadoc Signed-off-by: Ryan Nett <rnett@skymind.io> * use new pad Signed-off-by: Ryan Nett <rnett@skymind.io> * conv tests use OpValidation Signed-off-by: Ryan Nett <rnett@skymind.io> * deconv3d overrides Signed-off-by: Ryan Nett <rnett@skymind.io> * test fix for the new pad method Signed-off-by: Ryan Nett <rnett@skymind.io> * more test fixes Signed-off-by: Ryan Nett <rnett@skymind.io> * more test fixes Signed-off-by: Ryan Nett <rnett@skymind.io> * rename SameDiff function methods to op (except for the actual SameDiff function ones) Signed-off-by: Ryan Nett <rnett@skymind.io> * more pad overloads, test fix Signed-off-by: Ryan Nett <rnett@skymind.io> * test updates Signed-off-by: Ryan Nett <rnett@skymind.io> * conv1d test Signed-off-by: Ryan Nett <rnett@skymind.io> * remove Conv1D tf import (there isn't a TF conv1d op) Signed-off-by: Ryan Nett <rnett@skymind.io> * remove numThreads from Nd4j Signed-off-by: Ryan Nett <rnett@skymind.io> * replace Old ops with their newer versions, deprecate ones that haven't already been deprecated Signed-off-by: Ryan Nett <rnett@skymind.io> * remove use of setNumThreads Signed-off-by: Ryan Nett <rnett@skymind.io> * fix for Reverse and ATan2 Signed-off-by: Ryan Nett <rnett@skymind.io> * fix test for wrong equals type Signed-off-by: Ryan Nett <rnett@skymind.io> * well it works now Signed-off-by: Ryan Nett <rnett@skymind.io> * better javadocs Signed-off-by: Ryan Nett <rnett@skymind.io> * NonNulls Signed-off-by: Ryan Nett <rnett@skymind.io> * better array literal Signed-off-by: Ryan Nett <rnett@skymind.io> * re-add tf import stuff (will remove later) Signed-off-by: Ryan Nett <rnett@skymind.io> * conv1d config load fix Signed-off-by: Ryan Nett <rnett@skymind.io> * partial config usage changes Signed-off-by: Ryan Nett <rnett@skymind.io> * remove Old op classes Signed-off-by: Ryan Nett <rnett@skymind.io> * config property fixes Signed-off-by: Ryan Nett <rnett@skymind.io> * removed one too many ops Signed-off-by: Ryan Nett <rnett@skymind.io> |
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| .github | ||
| ci | ||
| contrib | ||
| nd4j-backends | ||
| nd4j-buffer | ||
| nd4j-common | ||
| nd4j-context | ||
| nd4j-jdbc | ||
| nd4j-parameter-server-parent | ||
| nd4j-remote | ||
| nd4j-serde | ||
| nd4j-shade | ||
| nd4j-tensorflow | ||
| nd4j-uberjar | ||
| .appveyor.yml | ||
| .codeclimate.yml | ||
| .gitignore | ||
| .travis.yml | ||
| LICENSE | ||
| README.md | ||
| RaspberryPi.md | ||
| VERSION | ||
| buildAllversions.sh | ||
| buildmultiplescalaversions.sh | ||
| pom.xml | ||
README.md
ND4J: Scientific Computing on the JVM
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/deeplearning4j/dl4j-0.4-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
- Search for nd4j in the Maven Central Repository to find the available nd4j jars.
- Include the appropriate dependency in your pom.xml.
Clone from the GitHub Repo
https://deeplearning4j.org/buildinglocally
Contribute
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Check for open issues, or open a new issue to start a discussion around a feature idea or a bug.
-
If you feel uncomfortable or uncertain about an issue or your changes, feel free to contact us on Gitter using the link above.
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Fork the repository on GitHub to start making your changes to the master branch (or branch off of it).
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Write a test, which shows that the bug was fixed or that the feature works as expected.
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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:formatin the subproject you work on, by using thecontrib/formatter.xmlat the root of the repository to configure the Eclipse formatter, or by using the INtellij plugin. -
Send a pull request, and bug us on Gitter until it gets merged and published.