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

_service

@@ -1,9 +1,9 @@
 <services>
-  <service name="obs_scm" mode="manual">
+  <service name="obs_scm">
     <param name="url">https://github.com/openvinotoolkit/openvino.git</param>
     <param name="scm">git</param>
-    <param name="revision">2024.0.0</param>
+    <param name="revision">2024.1.0</param>
-    <param name="version">2024.0.0</param>
+    <param name="version">2024.1.0</param>
     <param name="submodules">enable</param>
     <param name="filename">openvino</param>
     <param name="exclude">.git</param>

_service:obs_scm:openvino-2024.1.0.obscpio

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7a62674d7f3b6ddf8a7e32a8344922b9968101d01963e037ebf2142bc48cfb9f
+size 865282063

_service:obs_scm:openvino.obsinfo

@@ -0,0 +1,4 @@
+name: openvino
+version: 2024.1.0
+mtime: 1713778234
+commit: f4afc983258bcb2592d999ed6700043fdb58ad78

openvino-2024.0.0.obscpio

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:df436c6a42a84424f4a3c2249298d40b89a6046568ea7b38088f1d7bde3b011e
-size 825923087

openvino-2024.1.0.obscpio

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:556da89cbc03dd30dad270a1c1796598932c488a696a87056399e74a4d688680
+size 865282063

openvino-fix-build-sample-path.patch

@@ -0,0 +1,12 @@
+diff -uNr openvino.orig/samples/cpp/build_samples.sh openvino/samples/cpp/build_samples.sh
+--- openvino.orig/samples/cpp/build_samples.sh	2024-04-25 01:04:42.451868881 -0300
++++ openvino/samples/cpp/build_samples.sh	2024-04-25 01:05:04.678342617 -0300
+@@ -59,7 +59,7 @@
+ printf "\nSetting environment variables for building samples...\n"
+ 
+ if [ -z "$INTEL_OPENVINO_DIR" ]; then
+-    if [[ "$SAMPLES_SOURCE_DIR" = "/usr/share/openvino"* ]]; then
++    if [[ "$SAMPLES_SOURCE_DIR" = "/usr/share/OpenVINO"* ]]; then
+         true
+     elif [ -e "$SAMPLES_SOURCE_DIR/../../setupvars.sh" ]; then
+         setupvars_path="$SAMPLES_SOURCE_DIR/../../setupvars.sh"

openvino.changes

@@ -1,3 +1,92 @@
+-------------------------------------------------------------------
+Thu May  9 22:56:53 UTC 2024 - Alessandro de Oliveira Faria <cabelo@opensuse.org>
+
+- 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.
+
 -------------------------------------------------------------------
 Tue Apr 23 18:57:17 UTC 2024 - Atri Bhattacharya <badshah400@gmail.com>
 

openvino.obsinfo

@@ -1,4 +1,4 @@
 name: openvino
-version: 2024.0.0
+version: 2024.1.0
-mtime: 1708605048
+mtime: 1713778234
-commit: 34caeefd07800b59065345d651949efbe8ab6649
+commit: f4afc983258bcb2592d999ed6700043fdb58ad78

openvino.spec

@@ -21,12 +21,12 @@
 # Compilation takes ~1 hr on OBS for a single python, don't try all supported flavours
 %define pythons python3
 %define __builder ninja
-%define so_ver 2400
+%define so_ver 2410
 %define shlib lib%{name}%{so_ver}
 %define shlib_c lib%{name}_c%{so_ver}
 %define prj_name OpenVINO
 Name:           openvino
-Version:        2024.0.0
+Version:        2024.1.0
 Release:        0
 Summary:        A toolkit for optimizing and deploying AI inference
 # Let's be safe and put all third party licenses here, no matter that we use specific thirdparty libs or not
@@ -40,6 +40,8 @@ Patch0:         openvino-onnx-ml-defines.patch
 Patch2:         openvino-fix-install-paths.patch
 # PATCH-FIX-UPSTREAM openvino-ComputeLibrary-include-string.patch badshah400@gmail.com -- Include header for std::string
 Patch3:         openvino-ComputeLibrary-include-string.patch
+# PATCH-FIX-UPSTREAM openvino-fix-build-sample-path.patch cabelo@opensuse.org -- Fix sample source path in build script
+Patch4:         openvino-fix-build-sample-path.patch
 BuildRequires:  ade-devel
 BuildRequires:  cmake
 BuildRequires:  fdupes
@@ -51,6 +53,12 @@ BuildRequires:  opencl-cpp-headers
 # headers. Please regenerate this file with a newer version of protoc.
 #BuildRequires:  cmake(ONNX)
 BuildRequires:  pkgconfig
+BuildRequires:  %{python_module devel}
+BuildRequires:  %{python_module pip}
+BuildRequires:  %{python_module pybind11-devel}
+BuildRequires:  %{python_module setuptools}
+BuildRequires:  %{python_module wheel}
+BuildRequires:  python-rpm-macros
 BuildRequires:  zstd
 BuildRequires:  pkgconfig(OpenCL-Headers)
 BuildRequires:  pkgconfig(flatbuffers)
@@ -62,12 +70,6 @@ BuildRequires:  pkgconfig(pugixml)
 BuildRequires:  pkgconfig(snappy)
 BuildRequires:  pkgconfig(tbb)
 BuildRequires:  pkgconfig(zlib)
-BuildRequires:  python-rpm-macros
-BuildRequires:  %{python_module devel}
-BuildRequires:  %{python_module pip}
-BuildRequires:  %{python_module pybind11-devel}
-BuildRequires:  %{python_module setuptools}
-BuildRequires:  %{python_module wheel}
 %ifarch %{arm64}
 BuildRequires:  scons
 %endif
@@ -79,8 +81,11 @@ ExcludeArch:    %{ix86} %{arm32} ppc
 %description
 OpenVINO is an open-source toolkit for optimizing and deploying AI inference.
 
+
+
 ## Main shared libs and devel pkg ##
 #
+
 %package -n %{shlib}
 Summary:        Shared library for OpenVINO toolkit
 
@@ -89,14 +94,20 @@ OpenVINO is an open-source toolkit for optimizing and deploying AI inference.
 
 This package provides the shared library for OpenVINO.
 
+
+
 #
+
 %package -n %{shlib_c}
 Summary:        Shared C library for OpenVINO toolkit
 
 %description -n %{shlib_c}
 This package provides the C library for OpenVINO.
 
+
+
 #
+
 %package  -n %{name}-devel
 Summary:        Headers and sources for OpenVINO toolkit
 Requires:       %{shlib_c} = %{version}
@@ -127,8 +138,11 @@ OpenVINO is an open-source toolkit for optimizing and deploying AI inference.
 This package provides the headers and sources for developing applications with
 OpenVINO.
 
+
+
 ## Plugins ##
 #
+
 %package -n %{name}-arm-cpu-plugin
 Summary:        Intel CPU plugin for OpenVINO toolkit
 
@@ -137,7 +151,10 @@ OpenVINO is an open-source toolkit for optimizing and deploying AI inference.
 
 This package provides the ARM CPU plugin for OpenVINO on %{arm64} archs.
 
+
+
 #
+
 %package -n %{name}-auto-plugin
 Summary:        Auto / Multi software plugin for OpenVINO toolkit
 
@@ -146,7 +163,10 @@ OpenVINO is an open-source toolkit for optimizing and deploying AI inference.
 
 This package provides the Auto / Multi software plugin for OpenVINO.
 
+
+
 #
+
 %package -n %{name}-auto-batch-plugin
 Summary:        Automatic batch software plugin for OpenVINO toolkit
 
@@ -155,7 +175,10 @@ OpenVINO is an open-source toolkit for optimizing and deploying AI inference.
 
 This package provides the automatic batch software plugin for OpenVINO.
 
+
+
 #
+
 %package -n %{name}-hetero-plugin
 Summary:        Hetero frontend for Intel OpenVINO toolkit
 
@@ -164,7 +187,10 @@ OpenVINO is an open-source toolkit for optimizing and deploying AI inference.
 
 This package provides the hetero frontend for OpenVINO.
 
+
+
 #
+
 %package -n %{name}-intel-cpu-plugin
 Summary:        Intel CPU plugin for OpenVINO toolkit
 
@@ -173,8 +199,23 @@ OpenVINO is an open-source toolkit for optimizing and deploying AI inference.
 
 This package provides the intel CPU plugin for OpenVINO for %{x86_64} archs.
 
+
+
+#
+
+%package -n %{name}-intel-npu-plugin
+Summary:        Intel NPU plugin for OpenVINO toolkit
+
+%description -n %{name}-intel-npu-plugin
+OpenVINO is an open-source toolkit for optimizing and deploying AI inference.
+
+This package provides the intel NPU plugin for OpenVINO for %{x86_64} archs.
+
+
+
 ## Frontend shared libs ##
 #
+
 %package -n lib%{name}_ir_frontend%{so_ver}
 Summary:        Paddle frontend for Intel OpenVINO toolkit
 
@@ -183,7 +224,10 @@ OpenVINO is an open-source toolkit for optimizing and deploying AI inference.
 
 This package provides the ir frontend for OpenVINO.
 
+
+
 #
+
 %package -n lib%{name}_onnx_frontend%{so_ver}
 Summary:        Onnx frontend for OpenVINO toolkit
 
@@ -192,7 +236,10 @@ OpenVINO is an open-source toolkit for optimizing and deploying AI inference.
 
 This package provides the onnx frontend for OpenVINO.
 
+
+
 #
+
 %package -n lib%{name}_paddle_frontend%{so_ver}
 Summary:        Paddle frontend for Intel OpenVINO toolkit
 
@@ -201,7 +248,10 @@ OpenVINO is an open-source toolkit for optimizing and deploying AI inference.
 
 This package provides the paddle frontend for OpenVINO.
 
+
+
 #
+
 %package -n lib%{name}_pytorch_frontend%{so_ver}
 Summary:        PyTorch frontend for OpenVINO toolkit
 
@@ -210,7 +260,10 @@ OpenVINO is an open-source toolkit for optimizing and deploying AI inference.
 
 This package provides the pytorch frontend for OpenVINO.
 
+
+
 #
+
 %package -n lib%{name}_tensorflow_frontend%{so_ver}
 Summary:        TensorFlow frontend for OpenVINO toolkit
 
@@ -219,7 +272,10 @@ OpenVINO is an open-source toolkit for optimizing and deploying AI inference.
 
 This package provides the tensorflow frontend for OpenVINO.
 
+
+
 #
+
 %package -n lib%{name}_tensorflow_lite_frontend%{so_ver}
 Summary:        TensorFlow Lite frontend for OpenVINO toolkit
 
@@ -228,8 +284,11 @@ OpenVINO is an open-source toolkit for optimizing and deploying AI inference.
 
 This package provides the tensorflow-lite frontend for OpenVINO.
 
+
+
 ## Python module ##
 #
+
 %package -n python-openvino
 Summary:        Python module for openVINO toolkit
 Requires:       python-numpy < 2
@@ -241,8 +300,11 @@ OpenVINO is an open-source toolkit for optimizing and deploying AI inference.
 This package provides a Python module for interfacing with openVINO toolkit.
 
 
+
+
 ## Samples/examples ##
 #
+
 %package -n %{name}-sample
 Summary:        Samples for use with OpenVINO toolkit
 BuildArch:      noarch
@@ -251,8 +313,10 @@ BuildArch:      noarch
 OpenVINO is an open-source toolkit for optimizing and deploying AI inference.
 
 This package provides some samples for use with openVINO.
-#
 
+
+
+#
 %prep
 %autosetup -p1
 
@@ -352,6 +416,10 @@ rm -fr %{buildroot}%{_datadir}/licenses/*
 %files -n %{name}-intel-cpu-plugin
 %dir %{_libdir}/%{prj_name}
 %{_libdir}/%{prj_name}/libopenvino_intel_cpu_plugin.so
+
+%files -n %{name}-intel-npu-plugin
+%dir %{_libdir}/%{prj_name}
+%{_libdir}/%{prj_name}/libopenvino_intel_npu_plugin.so
 %endif
 
 %ifarch %{arm64}