1.0.0-M2
Highlights
Adds proper support for java 9 modules: https://github.com/eclipse/deeplearning4j/pull/9631 https://github.com/eclipse/deeplearning4j/pull/9626
As part of the same work flatbuffers has been upgraded to 1.12.1. This affects the samediff file format and the user interfaces. Flatbuffers as a file format is forwards and backwards compatible but if you have any issues please do let us know. The relevant files have been updated using the flatc compiler.
Removed rl4j: in continuing to cut unmaintained modules, the 1.0 will focus the framework on a few key use cases. This invites other folks to build external modules for a tightly maintained core that focuses on deployment, framework interop and training models in java.
Added new model zoo module called omnihub for dl4j and new samediff models. These can be found here: https://github.com/KonduitAI/omnihub-zoo See more in the new omnihub section.
Migrated the snapshots to sonatype's new repository https://s01.oss.sonatype.org. More context can be found here: https://twitter.com/Brian_Fox/status/1357414532512104448 https://github.com/eclipse/deeplearning4j/pull/9618
Consolidated tests to platform-tests to allow for easy testing of behavior against different backends.
Adds proper support for jetson nano with curated binaries and an updated cuda 10.2
Adds Spark 3 support: https://github.com/eclipse/deeplearning4j/pull/9444
Reduce binary size using selective compilation: https://github.com/eclipse/deeplearning4j/pull/9443
https://github.com/eclipse/deeplearning4j/pull/9451 Remove scala 11 support. Only supporting scala 2.12: https://github.com/eclipse/deeplearning4j/pull/9440
Extensive enhancements for samediff model training: https://github.com/eclipse/deeplearning4j/pull/9501
Nd4j/Samdiff/Libnd4j
Features and Enhancements
Add beginnings of graph optimization framework: https://github.com/eclipse/deeplearning4j/pull/9402
Many onnx model import improvements (add new ops): https://github.com/eclipse/deeplearning4j/pull/9411 https://github.com/eclipse/deeplearning4j/pull/9489https://github.com/eclipse/deeplearning4j/pull/9475 https://github.com/eclipse/deeplearning4j/pull/9526 https://github.com/eclipse/deeplearning4j/pull/9502https://github.com/eclipse/deeplearning4j/pull/9587 https://github.com/eclipse/deeplearning4j/pull/9599
Add new op subset frameworks: allows selective inclusion of operations to enable users to reduce binary size: https://github.com/eclipse/deeplearning4j/pull/9443 https://github.com/eclipse/deeplearning4j/pull/9451 https://github.com/eclipse/deeplearning4j/pull/9569
Add updated jetson nano support: https://github.com/eclipse/deeplearning4j/pull/9432
Enhance codegen exposing more functions for samediff: https://github.com/eclipse/deeplearning4j/pull/9478 https://github.com/eclipse/deeplearning4j/pull/9503 https://github.com/eclipse/deeplearning4j/pull/9500
Add new samediff eager mode (mainly used for model import use cases): https://github.com/eclipse/deeplearning4j/pull/9538 https://github.com/eclipse/deeplearning4j/pull/9535 https://github.com/eclipse/deeplearning4j/pull/9533
Add dimensions as input variables: https://github.com/eclipse/deeplearning4j/pull/9584
Bug Fixes
Update samediff api to allow dimensions as variables
Fix up conditions/matching: https://github.com/eclipse/deeplearning4j/pull/9551
ImageResize updates to improve compatibility with onnx: https://github.com/eclipse/deeplearning4j/pull/9495
Rewrite compat sparse to dense op: https://github.com/eclipse/deeplearning4j/pull/9566
Fix creation of string scalar ndarrays: https://github.com/eclipse/deeplearning4j/pull/9556
Fix serialization with conv/pooling3d: https://github.com/eclipse/deeplearning4j/pull/9648
Deeplearning4j
Features and Enhancements
Add Spark 3 support: https://github.com/eclipse/deeplearning4j/pull/9553
Added Deconvolution3D for keras import https://github.com/eclipse/deeplearning4j/pull/9399
Add full channels last support for 3d convolutions: https://github.com/eclipse/deeplearning4j/pull/9578
Bug Fixes
Fix confusion matrix count increments: https://github.com/eclipse/deeplearning4j/pull/9553
Fix Conv3D data format serialization: https://github.com/eclipse/deeplearning4j/pull/9648
Datavec
Features and Enhancements
Add LabelsSource to BagOfWordsVectorizer (thanks to XAI!): https://github.com/eclipse/deeplearning4j/pull/9624
Performance enhancement for mnist related datasetiterators: https://github.com/eclipse/deeplearning4j/pull/9612
Bug Fixes
Fix memory leak in datavec-arrow: https://github.com/eclipse/deeplearning4j/pull/9441
Omnihub
Launches new Omnihub module. Allows access to models from: https://github.com/KonduitAI/omnihub-zoo
A pretrained omnihub module will provide access to pretrained samediff and dl4j modules. This will also supplant the old dl4j zoo.
Modules will be made available from a Pretrained class:https://github.com/eclipse/deeplearning4j/blob/feb8eee5eb07239c49a4d14786114dc0394aad4e/omnihub/src/main/java/org/eclipse/deeplearning4j/omnihub/models/Pretrained.java#L30
Python4j
Clean up tests/consolidate tests to platform-tests
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