[DOCS] pre-releasenotes 23.1 Aug port master (#19273)

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@ -30,10 +30,92 @@ Please file a github Issue on these with the label “pre-release” so we can g
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.. dropdown:: OpenVINO Toolkit 2023.1.0.dev20230728
.. dropdown:: OpenVINO Toolkit 2023.1.0.dev20230811
:animate: fade-in-slide-down
:color: primary
:open:
`Check on GitHub <https://github.com/openvinotoolkit/openvino/releases/tag/2023.1.0.dev20230811>`__
**New features:**
* CPU runtime:
* Enabled weights decompression support for Large Language models (LLMs). The implementation
supports avx2 and avx512 HW targets for Intel® Core™ processors and gives up to 2x improvement
in the latency mode (FP32 VS FP32+INT8 weights comparison). For 4th Generation Intel® Xeon®
Scalable Processors (formerly Sapphire Rapids) this INT8 decompression feature gives 10-25%
performance improvement, compared to pure BF16 inference.
* Reduced memory consumption of compile model stage by moving constant folding of Transpose
nodes to the CPU Runtime side.
* Set FP16 inference precision by default for non-convolution networks on ARM. Convolution
network will be executed in FP32.
* GPU runtime: Added paddings for dynamic convolutions to improve performance for models like
Stable-Diffusion v2.1.
* Python API:
* Added the ``torchvision.transforms`` object to OpenVINO preprocessing.
* Moved all python tools related to OpenVINO into a single namespace,
improving user experience with better API readability.
* TensorFlow FE:
* Added support for the TensorFlow 1 Checkpoint format. All native TensorFlow formats are now enabled.
* Added support for 8 new operations:
* MaxPoolWithArgmax
* UnravelIndex
* AdjustContrastv2
* InvertPermutation
* CheckNumerics
* DivNoNan
* EnsureShape
* ShapeN
* PyTorch FE:
* Added support for 6 new operations. To know how to enjoy PyTorch models conversion follow
this `Link <https://docs.openvino.ai/2023.0/openvino_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_PyTorch.html#experimental-converting-a-pytorch-model-with-pytorch-frontend>`__
* aten::concat
* aten::masked_scatter
* aten::linspace
* aten::view_as
* aten::std
* aten::outer
* aten::broadcast_to
**New openvino_notebooks:**
* `245-typo-detector <https://github.com/openvinotoolkit/openvino_notebooks/blob/main/notebooks/245-typo-detector>`__
: English Typo Detection in sentences with OpenVINO™
* `247-code-language-id <https://github.com/openvinotoolkit/openvino_notebooks/blob/main/notebooks/247-code-language-id/247-code-language-id.ipynb>`__
: Identify the programming language used in an arbitrary code snippet
* `121-convert-to-openvino <https://github.com/openvinotoolkit/openvino_notebooks/blob/main/notebooks/121-convert-to-openvino>`__
: Learn OpenVINO model conversion API
* `244-named-entity-recognition <https://github.com/openvinotoolkit/openvino_notebooks/blob/main/notebooks/244-named-entity-recognition>`__
: Named entity recognition with OpenVINO™
* `246-depth-estimation-videpth <https://github.com/openvinotoolkit/openvino_notebooks/blob/main/notebooks/246-depth-estimation-videpth>`__
: Monocular Visual-Inertial Depth Estimation with OpenVINO™
* `248-stable-diffusion-xl <https://github.com/openvinotoolkit/openvino_notebooks/blob/main/notebooks/248-stable-diffusion-xl>`__
: Image generation with Stable Diffusion XL
* `249-oneformer-segmentation <https://github.com/openvinotoolkit/openvino_notebooks/blob/main/notebooks/249-oneformer-segmentation>`__
: Universal segmentation with OneFormer
.. dropdown:: OpenVINO Toolkit 2023.1.0.dev20230728
:animate: fade-in-slide-down
:color: secondary
`Check on GitHub <https://github.com/openvinotoolkit/openvino/releases/tag/2023.1.0.dev20230728>`__
@ -55,7 +137,7 @@ Please file a github Issue on these with the label “pre-release” so we can g
* Frameworks:
- PyTorch Updates: OpenVINO now supportsoriginally quantized PyTorch models, including models produced with the Neural Network Compression Framework (NNCF).
- PyTorch Updates: OpenVINO now supports originally quantized PyTorch models, including models produced with the Neural Network Compression Framework (NNCF).
- TensorFlow FE: Now supports Switch/Merge operations, bringing TensorFlow 1.x control flow support closer to full compatibility and enabling more models.
- Python API: Python Conversion API is now the primary conversion path, making it easier for Python developers to work with OpenVINO.