1.0.0-M2.1

Highlights

Significant changes for views being used within nd4j and samediff via the create_view op allow for users to directly leverage views in combination with graph operations reducing allocations and allowing for increased performance.

Cuda 11.4 and 11.6 added. Add nd4j-cuda-11.4 and nd4j-cuda-11.6 to your dependencies.

New Onnx ops support added (https://github.com/eclipse/deeplearning4j/pull/9663):

1. AliasWithName

2. CumSum

3. GenerateProposals

4. Loop

5. ResizeNearest

6. SequenceAt

7. SequenceConstruct

8. SequenceEmpty

9. SequenceErase

10. SequenceInsert

11. SequenceLength

3D Convolution Pooling serialization fixes for keras

Fix up training gradient propagation: https://github.com/eclipse/deeplearning4j/pull/9664

Significant changes for migration of NEC Aurora backend to VEDA:

1. https://github.com/eclipse/deeplearning4j/pull/9659

2. https://github.com/eclipse/deeplearning4j/pull/9678

3. https://github.com/eclipse/deeplearning4j/pull/9726

4. https://github.com/eclipse/deeplearning4j/pull/9723

5. https://github.com/eclipse/deeplearning4j/pull/9705

More fixes for mac osx arm64, please feel free to report an issue if anything comes up: https://github.com/eclipse/deeplearning4j/pull/9731

Upgrade protobuf to 3.21.2

Migrate project to java 11 and newer: https://github.com/eclipse/deeplearning4j/pull/9738

Enhanced performance for python4j: https://github.com/eclipse/deeplearning4j/pull/9688 (more to be added) thanks to https://github.com/subes for the suggestions for the improvements.

Removes spark 2 support.

Nd4j/Samdiff/Libnd4j

Features and Enhancements

1. Add label serialization for multi

2. Allow using fast path for results as well: https://github.com/eclipse/deeplearning4j/pull/9729

3. Fix up concurrency issue in ticketing framework: https://github.com/eclipse/deeplearning4j/pull/9721 Thanks PZA from: https://github.com/wehowsky

4. Indexing changes: https://github.com/eclipse/deeplearning4j/pull/9690

5. Add graalvm support for onnx/tensorflow import framework annotations: https://github.com/eclipse/deeplearning4j/pull/9718

6. Add more op definitions for sd.linalg: https://github.com/eclipse/deeplearning4j/pull/9681

7. Allow more tolerance for samediff serialization for model import issues: https://github.com/eclipse/deeplearning4j/pull/9745

Bug Fixes

1. Enable Gather Gradient: https://github.com/eclipse/deeplearning4j/pull/9674

2. Fix up tri, samediff training: https://github.com/eclipse/deeplearning4j/pull/9672

3. Fix up SVD: https://github.com/eclipse/deeplearning4j/pull/9673

4. Fix up tri + cuda: https://github.com/eclipse/deeplearning4j/pull/9730

5. Fix up null checks with samediff variable getArr(): https://github.com/eclipse/deeplearning4j/pull/9701

6. Fix up buffer overflow where databufferand length do not match: https://github.com/eclipse/deeplearning4j/pull/9713

Deeplearning4j

Features and Enhancements

1. Add label saving for computation graph, multiayernetwork; https://github.com/eclipse/deeplearning4j/pull/9672

Bug Fixes

1. Fix confusion matrix count increments: https://github.com/eclipse/deeplearning4j/pull/9553

2. Fix Conv3D data format serialization: https://github.com/eclipse/deeplearning4j/pull/9648

3. Add keras import aliases for more recent versions: https://github.com/eclipse/deeplearning4j/pull/9704

4. Misc bug fixes for views in deeplearning4j-nn: https://github.com/eclipse/deeplearning4j/pull/9689

5. Fix up wordvectorserializer: https://github.com/eclipse/deeplearning4j/pull/9728 Thanks to https://github.com/j-d-o!

Datavec

Omnihub

Python4j

1. Significant performance improvements for python4j: https://github.com/eclipse/deeplearning4j/pull/9688