Accepting request 1173003 from home:cabelo:branches:science:machinelearning
- Fix sample source path in build script.
- Update to 2024.1.0
- More Generative AI coverage and framework integrations to
minimize code changes.
* Mixtral and URLNet models optimized for performance
improvements on Intel® Xeon® processors.
* Stable Diffusion 1.5, ChatGLM3-6B, and Qwen-7B models
optimized for improved inference speed on Intel® Core™
Ultra processors with integrated GPU.
* Support for Falcon-7B-Instruct, a GenAI Large Language Model
(LLM) ready-to-use chat/instruct model with superior
performance metrics.
* New Jupyter Notebooks added: YOLO V9, YOLO V8
Oriented Bounding Boxes Detection (OOB), Stable Diffusion
in Keras, MobileCLIP, RMBG-v1.4 Background Removal, Magika,
TripoSR, AnimateAnyone, LLaVA-Next, and RAG system with
OpenVINO and LangChain.
- Broader Large Language Model (LLM) support and more model
compression techniques.
* LLM compilation time reduced through additional optimizations
with compressed embedding. Improved 1st token performance of
LLMs on 4th and 5th generations of Intel® Xeon® processors
with Intel® Advanced Matrix Extensions (Intel® AMX).
* Better LLM compression and improved performance with oneDNN,
INT4, and INT8 support for Intel® Arc™ GPUs.
* Significant memory reduction for select smaller GenAI
models on Intel® Core™ Ultra processors with integrated GPU.
- More portability and performance to run AI at the edge,
in the cloud, or locally.
* The preview NPU plugin for Intel® Core™ Ultra processors
is now available in the OpenVINO open-source GitHub
repository, in addition to the main OpenVINO package on PyPI.
* The JavaScript API is now more easily accessible through
the npm repository, enabling JavaScript developers’ seamless
access to the OpenVINO API.
* FP16 inference on ARM processors now enabled for the
Convolutional Neural Network (CNN) by default.
- Support Change and Deprecation Notices
* Using deprecated features and components is not advised. They
are available to enable a smooth transition to new solutions
and will be discontinued in the future. To keep using
Discontinued features, you will have to revert to the last
LTS OpenVINO version supporting them.
* For more details, refer to the OpenVINO Legacy Features
and Components page.
* Discontinued in 2024.0:
+ Runtime components:
- Intel® Gaussian & Neural Accelerator (Intel® GNA).
Consider using the Neural Processing Unit (NPU)
for low-powered systems like Intel® Core™ Ultra or
14th generation and beyond.
- OpenVINO C++/C/Python 1.0 APIs (see 2023.3 API
transition guide for reference).
- All ONNX Frontend legacy API (known as
ONNX_IMPORTER_API)
- 'PerfomanceMode.UNDEFINED' property as part of
the OpenVINO Python API
+ Tools:
- Deployment Manager. See installation and deployment
guides for current distribution options.
- Accuracy Checker.
- Post-Training Optimization Tool (POT). Neural Network
Compression Framework (NNCF) should be used instead.
- A Git patch for NNCF integration with
huggingface/transformers. The recommended approach
is to use huggingface/optimum-intel for applying
NNCF optimization on top of models from Hugging
Face.
- Support for Apache MXNet, Caffe, and Kaldi model
formats. Conversion to ONNX may be used as
a solution.
* Deprecated and to be removed in the future:
+ The OpenVINO™ Development Tools package (pip install
openvino-dev) will be removed from installation options
and distribution channels beginning with OpenVINO 2025.0.
+ Model Optimizer will be discontinued with OpenVINO 2025.0.
Consider using the new conversion methods instead. For
more details, see the model conversion transition guide.
+ OpenVINO property Affinity API will be discontinued with
OpenVINO 2025.0. It will be replaced with CPU binding
configurations (ov::hint::enable_cpu_pinning).
+ OpenVINO Model Server components:
- “auto shape” and “auto batch size” (reshaping a model
in runtime) will be removed in the future. OpenVINO’s
dynamic shape models are recommended instead.
OBS-URL: https://build.opensuse.org/request/show/1173003
OBS-URL: https://build.opensuse.org/package/show/science:machinelearning/openvino?expand=0&rev=5
2024-05-13 17:52:35 +00:00
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-------------------------------------------------------------------
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Thu May 9 22:56:53 UTC 2024 - Alessandro de Oliveira Faria <cabelo@opensuse.org>
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2024-05-14 07:36:10 +00:00
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- Fix sample source path in build script:
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* openvino-fix-build-sample-path.patch
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Accepting request 1173003 from home:cabelo:branches:science:machinelearning
- Fix sample source path in build script.
- Update to 2024.1.0
- More Generative AI coverage and framework integrations to
minimize code changes.
* Mixtral and URLNet models optimized for performance
improvements on Intel® Xeon® processors.
* Stable Diffusion 1.5, ChatGLM3-6B, and Qwen-7B models
optimized for improved inference speed on Intel® Core™
Ultra processors with integrated GPU.
* Support for Falcon-7B-Instruct, a GenAI Large Language Model
(LLM) ready-to-use chat/instruct model with superior
performance metrics.
* New Jupyter Notebooks added: YOLO V9, YOLO V8
Oriented Bounding Boxes Detection (OOB), Stable Diffusion
in Keras, MobileCLIP, RMBG-v1.4 Background Removal, Magika,
TripoSR, AnimateAnyone, LLaVA-Next, and RAG system with
OpenVINO and LangChain.
- Broader Large Language Model (LLM) support and more model
compression techniques.
* LLM compilation time reduced through additional optimizations
with compressed embedding. Improved 1st token performance of
LLMs on 4th and 5th generations of Intel® Xeon® processors
with Intel® Advanced Matrix Extensions (Intel® AMX).
* Better LLM compression and improved performance with oneDNN,
INT4, and INT8 support for Intel® Arc™ GPUs.
* Significant memory reduction for select smaller GenAI
models on Intel® Core™ Ultra processors with integrated GPU.
- More portability and performance to run AI at the edge,
in the cloud, or locally.
* The preview NPU plugin for Intel® Core™ Ultra processors
is now available in the OpenVINO open-source GitHub
repository, in addition to the main OpenVINO package on PyPI.
* The JavaScript API is now more easily accessible through
the npm repository, enabling JavaScript developers’ seamless
access to the OpenVINO API.
* FP16 inference on ARM processors now enabled for the
Convolutional Neural Network (CNN) by default.
- Support Change and Deprecation Notices
* Using deprecated features and components is not advised. They
are available to enable a smooth transition to new solutions
and will be discontinued in the future. To keep using
Discontinued features, you will have to revert to the last
LTS OpenVINO version supporting them.
* For more details, refer to the OpenVINO Legacy Features
and Components page.
* Discontinued in 2024.0:
+ Runtime components:
- Intel® Gaussian & Neural Accelerator (Intel® GNA).
Consider using the Neural Processing Unit (NPU)
for low-powered systems like Intel® Core™ Ultra or
14th generation and beyond.
- OpenVINO C++/C/Python 1.0 APIs (see 2023.3 API
transition guide for reference).
- All ONNX Frontend legacy API (known as
ONNX_IMPORTER_API)
- 'PerfomanceMode.UNDEFINED' property as part of
the OpenVINO Python API
+ Tools:
- Deployment Manager. See installation and deployment
guides for current distribution options.
- Accuracy Checker.
- Post-Training Optimization Tool (POT). Neural Network
Compression Framework (NNCF) should be used instead.
- A Git patch for NNCF integration with
huggingface/transformers. The recommended approach
is to use huggingface/optimum-intel for applying
NNCF optimization on top of models from Hugging
Face.
- Support for Apache MXNet, Caffe, and Kaldi model
formats. Conversion to ONNX may be used as
a solution.
* Deprecated and to be removed in the future:
+ The OpenVINO™ Development Tools package (pip install
openvino-dev) will be removed from installation options
and distribution channels beginning with OpenVINO 2025.0.
+ Model Optimizer will be discontinued with OpenVINO 2025.0.
Consider using the new conversion methods instead. For
more details, see the model conversion transition guide.
+ OpenVINO property Affinity API will be discontinued with
OpenVINO 2025.0. It will be replaced with CPU binding
configurations (ov::hint::enable_cpu_pinning).
+ OpenVINO Model Server components:
- “auto shape” and “auto batch size” (reshaping a model
in runtime) will be removed in the future. OpenVINO’s
dynamic shape models are recommended instead.
OBS-URL: https://build.opensuse.org/request/show/1173003
OBS-URL: https://build.opensuse.org/package/show/science:machinelearning/openvino?expand=0&rev=5
2024-05-13 17:52:35 +00:00
|
|
|
|
- Update to 2024.1.0
|
|
|
|
|
- More Generative AI coverage and framework integrations to
|
|
|
|
|
minimize code changes.
|
|
|
|
|
* Mixtral and URLNet models optimized for performance
|
|
|
|
|
improvements on Intel® Xeon® processors.
|
|
|
|
|
* Stable Diffusion 1.5, ChatGLM3-6B, and Qwen-7B models
|
|
|
|
|
optimized for improved inference speed on Intel® Core™
|
|
|
|
|
Ultra processors with integrated GPU.
|
|
|
|
|
* Support for Falcon-7B-Instruct, a GenAI Large Language Model
|
|
|
|
|
(LLM) ready-to-use chat/instruct model with superior
|
|
|
|
|
performance metrics.
|
|
|
|
|
* New Jupyter Notebooks added: YOLO V9, YOLO V8
|
|
|
|
|
Oriented Bounding Boxes Detection (OOB), Stable Diffusion
|
|
|
|
|
in Keras, MobileCLIP, RMBG-v1.4 Background Removal, Magika,
|
|
|
|
|
TripoSR, AnimateAnyone, LLaVA-Next, and RAG system with
|
|
|
|
|
OpenVINO and LangChain.
|
|
|
|
|
- Broader Large Language Model (LLM) support and more model
|
|
|
|
|
compression techniques.
|
|
|
|
|
* LLM compilation time reduced through additional optimizations
|
|
|
|
|
with compressed embedding. Improved 1st token performance of
|
|
|
|
|
LLMs on 4th and 5th generations of Intel® Xeon® processors
|
|
|
|
|
with Intel® Advanced Matrix Extensions (Intel® AMX).
|
|
|
|
|
* Better LLM compression and improved performance with oneDNN,
|
|
|
|
|
INT4, and INT8 support for Intel® Arc™ GPUs.
|
|
|
|
|
* Significant memory reduction for select smaller GenAI
|
|
|
|
|
models on Intel® Core™ Ultra processors with integrated GPU.
|
|
|
|
|
- More portability and performance to run AI at the edge,
|
|
|
|
|
in the cloud, or locally.
|
|
|
|
|
* The preview NPU plugin for Intel® Core™ Ultra processors
|
|
|
|
|
is now available in the OpenVINO open-source GitHub
|
|
|
|
|
repository, in addition to the main OpenVINO package on PyPI.
|
|
|
|
|
* The JavaScript API is now more easily accessible through
|
|
|
|
|
the npm repository, enabling JavaScript developers’ seamless
|
|
|
|
|
access to the OpenVINO API.
|
|
|
|
|
* FP16 inference on ARM processors now enabled for the
|
|
|
|
|
Convolutional Neural Network (CNN) by default.
|
|
|
|
|
- Support Change and Deprecation Notices
|
|
|
|
|
* Using deprecated features and components is not advised. They
|
|
|
|
|
are available to enable a smooth transition to new solutions
|
|
|
|
|
and will be discontinued in the future. To keep using
|
|
|
|
|
Discontinued features, you will have to revert to the last
|
|
|
|
|
LTS OpenVINO version supporting them.
|
|
|
|
|
* For more details, refer to the OpenVINO Legacy Features
|
|
|
|
|
and Components page.
|
|
|
|
|
* Discontinued in 2024.0:
|
|
|
|
|
+ Runtime components:
|
|
|
|
|
- Intel® Gaussian & Neural Accelerator (Intel® GNA).
|
|
|
|
|
Consider using the Neural Processing Unit (NPU)
|
|
|
|
|
for low-powered systems like Intel® Core™ Ultra or
|
|
|
|
|
14th generation and beyond.
|
|
|
|
|
- OpenVINO C++/C/Python 1.0 APIs (see 2023.3 API
|
|
|
|
|
transition guide for reference).
|
|
|
|
|
- All ONNX Frontend legacy API (known as
|
|
|
|
|
ONNX_IMPORTER_API)
|
|
|
|
|
- 'PerfomanceMode.UNDEFINED' property as part of
|
|
|
|
|
the OpenVINO Python API
|
|
|
|
|
+ Tools:
|
|
|
|
|
- Deployment Manager. See installation and deployment
|
|
|
|
|
guides for current distribution options.
|
|
|
|
|
- Accuracy Checker.
|
|
|
|
|
- Post-Training Optimization Tool (POT). Neural Network
|
|
|
|
|
Compression Framework (NNCF) should be used instead.
|
|
|
|
|
- A Git patch for NNCF integration with
|
|
|
|
|
huggingface/transformers. The recommended approach
|
|
|
|
|
is to use huggingface/optimum-intel for applying
|
|
|
|
|
NNCF optimization on top of models from Hugging
|
|
|
|
|
Face.
|
|
|
|
|
- Support for Apache MXNet, Caffe, and Kaldi model
|
|
|
|
|
formats. Conversion to ONNX may be used as
|
|
|
|
|
a solution.
|
|
|
|
|
* Deprecated and to be removed in the future:
|
|
|
|
|
+ The OpenVINO™ Development Tools package (pip install
|
|
|
|
|
openvino-dev) will be removed from installation options
|
|
|
|
|
and distribution channels beginning with OpenVINO 2025.0.
|
|
|
|
|
+ Model Optimizer will be discontinued with OpenVINO 2025.0.
|
|
|
|
|
Consider using the new conversion methods instead. For
|
|
|
|
|
more details, see the model conversion transition guide.
|
|
|
|
|
+ OpenVINO property Affinity API will be discontinued with
|
|
|
|
|
OpenVINO 2025.0. It will be replaced with CPU binding
|
|
|
|
|
configurations (ov::hint::enable_cpu_pinning).
|
|
|
|
|
+ OpenVINO Model Server components:
|
|
|
|
|
- “auto shape” and “auto batch size” (reshaping a model
|
|
|
|
|
in runtime) will be removed in the future. OpenVINO’s
|
|
|
|
|
dynamic shape models are recommended instead.
|
|
|
|
|
|
2024-05-07 14:47:00 +00:00
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-------------------------------------------------------------------
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Tue Apr 23 18:57:17 UTC 2024 - Atri Bhattacharya <badshah400@gmail.com>
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- License update: play safe and list all third party licenses as
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part of the License tag.
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2024-05-06 10:14:29 +00:00
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-------------------------------------------------------------------
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Tue Apr 23 12:42:32 UTC 2024 - Atri Bhattacharya <badshah400@gmail.com>
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- Switch to _service file as tagged Source tarball does not
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include `./thirdparty` submodules.
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- Update openvino-fix-install-paths.patch to fix python module
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install path.
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- Enable python module and split it out into a python subpackage
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(for now default python3 only).
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- Explicitly build python metadata (dist-info) and install it
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(needs simple sed hackery to support "officially" unsupported
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platform ppc64le).
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- Specify ENABLE_JS=OFF to turn off javascript bindings as
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building these requires downloading npm stuff from the network.
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- Build with system pybind11.
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- Bump _constraints for updated disk space requirements.
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- Drop empty %check section, rpmlint was misleading when it
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recommended adding this.
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-------------------------------------------------------------------
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Fri Apr 19 08:08:02 UTC 2024 - Atri Bhattacharya <badshah400@gmail.com>
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- Numerous specfile cleanups:
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* Drop redundant `mv` commands and use `install` where
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appropriate.
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* Build with system protobuf.
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* Fix Summary tags.
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* Trim package descriptions.
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* Drop forcing CMAKE_BUILD_TYPE=Release, let macro default
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RelWithDebInfo be used instead.
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* Correct naming of shared library packages.
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* Separate out libopenvino_c.so.* into own shared lib package.
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* Drop rpmlintrc rule used to hide shlib naming mistakes.
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* Rename Source tarball to %{name}-%{version}.EXT pattern.
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* Use ldconfig_scriptlet macro for post(un).
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- Add openvino-onnx-ml-defines.patch -- Define ONNX_ML at compile
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time when using system onnx to allow using 'onnx-ml.pb.h'
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instead of 'onnx.pb.h', the latter not being shipped with
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openSUSE's onnx-devel package (gh#onnx/onnx#3074).
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- Add openvino-fix-install-paths.patch: Change hard-coded install
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paths in upstream cmake macro to standard Linux dirs.
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- Add openvino-ComputeLibrary-include-string.patch: Include header
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for std::string.
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- Add external devel packages as Requires for openvino-devel.
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- Pass -Wl,-z,noexecstack to %build_ldflags to avoid an exec stack
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issue with intel CPU plugin.
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- Use ninja for build.
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- Adapt _constraits file for correct disk space and memory
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requirements.
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- Add empty %check section.
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-------------------------------------------------------------------
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Mon Apr 15 03:18:33 UTC 2024 - Alessandro de Oliveira Faria <cabelo@opensuse.org>
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- Initial package
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- Version 2024.0.0
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- Add openvino-rpmlintrc.
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