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Add NEWS and README #10545
Add NEWS and README #10545
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@nswamy @spidydev @anirudhacharya @reminisce @zheng-da @rahul003 @cjolivier01 @eric-haibin-lin @aaronmarkham @piiswrong Can you please help review ? |
NEWS.md
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- Implemented new [Scala Inference APIs](https://cwiki.apache.org/confluence/display/MXNET/MXNetScalaInferenceAPI) which offer an easy-to-use, and Scala Idiomatic and thread-safe high level APIs for performing predictions with deep learning models trained with MXNet (#9678). Implemented new ImageClassifier class provides APIs for classification tasks on a Java BufferedImage using a pre-trained model you provide (#10054). Implemented new ObjectDetector class provides APIs for object and boundary detections on a Java BufferedImage using a pre-trained model you provide (#10229). | ||
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### New Features - Added module to import ONNX models into MXNet | ||
- Implemented new ONNX module in MXNet offers an easy to use API to import ONNX models into MXNet's symbolic interface (#9963). Checkout the example on how you could use this API to import ONNX models and perform inference on MXNet. |
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grammar mistake. It should be - "Implemented new ONNX module in MXNet. It offers an easy ...".
NEWS.md
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- Implemented new [Scala Inference APIs](https://cwiki.apache.org/confluence/display/MXNET/MXNetScalaInferenceAPI) which offer an easy-to-use, and Scala Idiomatic and thread-safe high level APIs for performing predictions with deep learning models trained with MXNet (#9678). Implemented new ImageClassifier class provides APIs for classification tasks on a Java BufferedImage using a pre-trained model you provide (#10054). Implemented new ObjectDetector class provides APIs for object and boundary detections on a Java BufferedImage using a pre-trained model you provide (#10229). | ||
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### New Features - Added module to import ONNX models into MXNet | ||
- Implemented new ONNX module in MXNet offers an easy to use API to import ONNX models into MXNet's symbolic interface (#9963). Checkout the example on how you could use this API to import ONNX models and perform inference on MXNet. |
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And in "Checkout the example ..." part. The example should link to one of these two - https://github.com/apache/incubator-mxnet/blob/master/example/onnx/super_resolution.py or https://github.com/apache/incubator-mxnet/blob/master/docs/tutorials/onnx/super_resolution.md
NEWS.md
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- Implemented new [Scala Inference APIs](https://cwiki.apache.org/confluence/display/MXNET/MXNetScalaInferenceAPI) which offer an easy-to-use, and Scala Idiomatic and thread-safe high level APIs for performing predictions with deep learning models trained with MXNet (#9678). Implemented new ImageClassifier class provides APIs for classification tasks on a Java BufferedImage using a pre-trained model you provide (#10054). Implemented new ObjectDetector class provides APIs for object and boundary detections on a Java BufferedImage using a pre-trained model you provide (#10229). | ||
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### New Features - Added module to import ONNX models into MXNet | ||
- Implemented new ONNX module in MXNet offers an easy to use API to import ONNX models into MXNet's symbolic interface (#9963). Checkout the example on how you could use this API to import ONNX models and perform inference on MXNet. |
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link the API to this - https://cwiki.apache.org/confluence/display/MXNET/ONNX-MXNet+API+Design
@KellenSunderland @larroy shall we mention that there's now a new way to build ARM and Jetson and that we output wheels? |
NEWS.md
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### New Features - Added Scala Inference APIs | ||
- Implemented new [Scala Inference APIs](https://cwiki.apache.org/confluence/display/MXNET/MXNetScalaInferenceAPI) which offer an easy-to-use, Scala Idiomatic and thread-safe high level APIs for performing predictions with deep learning models trained with MXNet (#9678). Implemented a new ImageClassifier class which provides APIs for classification tasks on a Java BufferedImage using a pre-trained model you provide (#10054). Implemented a new ObjectDetector class which provides APIs for object and boundary detections on a Java BufferedImage using a pre-trained model you provide (#10229). | ||
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### New Features - Added module to import ONNX models into MXNet |
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Added a Module to Import ONNX Models into MXNet
NEWS.md
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### New Features - Added module to import ONNX models into MXNet | ||
- Implemented a new ONNX module in MXNet which offers an easy to use API to import ONNX models into MXNet's symbolic interface (#9963). Checkout the [example](https://github.com/apache/incubator-mxnet/blob/master/example/onnx/super_resolution.py) on how you could use this [API](https://cwiki.apache.org/confluence/display/MXNET/ONNX-MXNet+API+Design) to import ONNX models and perform inference on MXNet. | ||
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### New Features - Added support for Model Quantization with Calibration |
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support -> Support
NEWS.md
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- Added support for multi-GPU training with `row_sparse` weights using `device` KVStore (#9987). | ||
- Added `Module.prepare` API for multi-GPU and multi-machine training with row_sparse weight (#10285) | ||
- Added `deterministic` option for `contrib.SparseEmbedding` operator | ||
- Added `sparse.broadcast_mul` and `sparse.broadcast_div` with CSRNDArray and 1-D dense NDArray |
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.. on CPU (#10208)
NEWS.md
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### Sparse Support | ||
- Added support for multi-GPU training with `row_sparse` weights using `device` KVStore (#9987). | ||
- Added `Module.prepare` API for multi-GPU and multi-machine training with row_sparse weight (#10285) | ||
- Added `deterministic` option for `contrib.SparseEmbedding` operator |
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(#9846)
### New Features - Added Profiling Enhancements | ||
- Enhanced built-in profiler to support native Intel:registered: VTune:tm: Amplifier objects such as Task, Frame, Event, Counter and Marker from both C++ and Python -- which is also visible in the Chrome tracing view(#8972). Added Runtime tracking of symbolic and imperative operators as well as memory and API calls. Added Tracking and dumping of aggregate profiling data. Profiler also no longer affects runtime performance when not in use. | ||
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### Breaking Changes |
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We have breaking changes?!
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Yes. The first one was discussed on the dev list and there was a vote on it. The second one is likely to be a low impact change, assuming that Pooling
operator is used more with kwargs rather than args.
Also cherry-picked #10554 |
@eric-haibin-lin @piiswrong is this good to merge ? @marcoabreu do you have other stuff to add to the NEWS.md ? |
@anirudh2290 Would it be possible to format the PR a bit before merging. I think it would make sense to either have 1 PR with two commits (merged without squashing), or two PRs (one for news, one with a fix). |
I'd be in favour of the second approach. The news get squashed and merged and the backports get rebased and merged. |
@KellenSunderland You raised a good point! Thanks. I have squashed all the README related changes into a single commit. I think this PR should now be merged without squashing. |
* Update data.md Change strategy to get im2rec_path * Update test_utils.py * Update data.md * Update test_utils.py * Update test_utils.py
* Addng a dummy space * Changing the static references to 1.1.0 to 1.2.0 * Removed the extra space * In the new page add new two new text sections for for Improved ONNX Support and Introducing Scala * Updating the text to ensure that Apache goes along with Incubating * Add rc0 to the release version in the home page * updated the link to be : https://github.com/apache/incubator-mxnet/releases/tag/1.2.0.rc0. * Changing the Github 1.2.0.rc0 link in the home page to Confluence
…ge (apache#10477) * Adding the Download page and linking it to the Install page * Removing the extra 'Download Source Package' section header * Minor fixes to the download page and the reference to it * Adding the GitHub repository link to the download page content * Minor text fix in install/index * Adding the download page in Step 4 for install
All required commits have been cherry-picked. This PR is ready to be merged (without squashing). |
Description
Added NEWS and README for 1.2.0 release.
@mbaijal Let me know on the decision with legal-discuss@ so we can update the release notes with known issues for the license.
Please see previews here: https://github.com/anirudh2290/mxnet/blob/v1.2.0/NEWS.md and https://github.com/anirudh2290/mxnet/blob/v1.2.0/README.md