From c62c3ab2fccb6e40219e0b5fbfe85312fd642970 Mon Sep 17 00:00:00 2001 From: Nikita Malinin Date: Mon, 29 Jul 2024 13:15:10 +0200 Subject: [PATCH] Update ReleaseNotes.md (#2837) ### Changes - Added v2.12.0 template; ### Reason for changes - Upcoming release; ### Related tickets - 142565; #### For the contributors: Please add your changes (as the commit to the branch) to the list according to the template and previous notes; Do not add tests-related notes; Provide the list of the PRs (for all your notes) in the comment for the discussion; --------- Co-authored-by: Liubov Talamanova Co-authored-by: Nikita Savelyev Co-authored-by: Aleksei Kashapov Co-authored-by: Alexander Kozlov --- ReleaseNotes.md | 42 ++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 42 insertions(+) diff --git a/ReleaseNotes.md b/ReleaseNotes.md index bc6108d349c..b43c17627de 100644 --- a/ReleaseNotes.md +++ b/ReleaseNotes.md @@ -1,5 +1,47 @@ # Release Notes +## New in Release 2.12.0 + +Post-training Quantization: + +- Features: + - (OpenVINO, PyTorch, ONNX) Excluded comparison operators from the quantization scope for `nncf.ModelType.TRANSFORMER`. + - (OpenVINO, PyTorch) Changed the representation of symmetrically quantized weights from an unsigned integer with a fixed zero-point to a signed data type without a zero-point in the `nncf.compress_weights()` method. + - (OpenVINO) Extended patterns support of the AWQ algorithm as part of `nncf.compress_weights()`. This allows apply AWQ for the wider scope of the models. + - (OpenVINO) Introduced `nncf.CompressWeightsMode.E2M1` `mode` option of `nncf.compress_weights()` as the new MXFP4 precision (Experimental). + - (OpenVINO) Added support for models with BF16 precision in the `nncf.quantize()` method. + - (PyTorch) Added quantization support for the `torch.addmm`. + - (PyTorch) Added quantization support for the `torch.nn.functional.scaled_dot_product_attention`. +- Fixes: + - (OpenVINO, PyTorch, ONNX) Fixed Fast-/BiasCorrection algorithms with correct support of transposed MatMul layers. + - (OpenVINO) Fixed `nncf.IgnoredScope()` functionality for models with If operation. + - (OpenVINO) Fixed patterns with PReLU operations. + - Fixed runtime error while importing NNCF without Matplotlib package. +- Improvements: + - Reduced the amount of memory required for applying `nncf.compress_weights()` to OpenVINO models. + - Improved logging in case of the not empty `nncf.IgnoredScope()`. +- Tutorials: + - [Post-Training Optimization of Stable Audio Open Model](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/stable-audio/stable-audio.ipynb) + - [Post-Training Optimization of Phi3-Vision Model](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/phi-3-vision/phi-3-vision.ipynb) + - [Post-Training Optimization of MiniCPM-V2 Model](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/minicpm-v-multimodal-chatbot/minicpm-v-multimodal-chatbot.ipynb) + - [Post-Training Optimization of Jina CLIP Model](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/jina-clip/jina-clip.ipynb) + - [Post-Training Optimization of Stable Diffusion v3 Model](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/stable-diffusion-v3/stable-diffusion-v3.ipynb) + - [Post-Training Optimization of HunyuanDIT Model](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/hunyuan-dit-image-generation/hunyuan-dit-image-generation.ipynb) + - [Post-Training Optimization of DDColor Model](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/ddcolor-image-colorization/ddcolor-image-colorization.ipynb) + - [Post-Training Optimization of DynamiCrafter Model](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/dynamicrafter-animating-images/dynamicrafter-animating-images.ipynb) + - [Post-Training Optimization of DepthAnythingV2 Model](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/depth-anything/depth-anything-v2.ipynb) + - [Post-Training Optimization of Kosmos-2 Model](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/kosmos2-multimodal-large-language-model/kosmos2-multimodal-large-language-model.ipynb) + +Compression-aware training: + +- Fixes: + - (PyTorch) Fixed issue with wrapping for operator without patched state. + +Requirements: + +- Updated Tensorflow (2.15) version. This version requires Python 3.9-3.11. +- Added NumPy 2.0 support. + ## New in Release 2.11.0 Post-training Quantization: