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openvino/openvino.spec
Christian Goll 3ac7c6a6fe - Update to 2024.3.0 
- Summary of major features and improvements  
  * More Gen AI coverage and framework integrations to minimize 
    code changes
    + OpenVINO pre-optimized models are now available in Hugging 
      Face making it easier for developers to get started with 
      these models.
  * Broader Large Language Model (LLM) support and more model 
    compression techniques.
    + Significant improvement in LLM performance on Intel 
      discrete GPUs with the addition of Multi-Head Attention 
      (MHA) and OneDNN enhancements.
  * More portability and performance to run AI at the edge, in the 
    cloud, or locally.
    + Improved CPU performance when serving LLMs with the 
      inclusion of vLLM and continuous batching in the OpenVINO 
      Model Server (OVMS). vLLM is an easy-to-use open-source 
      library that supports efficient LLM inferencing and model 
      serving.
    + Ubuntu 24.04 long-term support (LTS), 64-bit (Kernel 6.8+) 
      (preview support)
- 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.
    + A number of notebooks have been deprecated. For an 
      up-to-date listing of available notebooks, refer to
      the OpenVINO™ Notebook index (openvinotoolkit.github.io).

OBS-URL: https://build.opensuse.org/package/show/science:machinelearning/openvino?expand=0&rev=13
2024-08-20 13:01:12 +00:00

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#
# spec file for package openvino
#
# Copyright (c) 2024 SUSE LLC
# Copyright (c) 2024 Alessandro de Oliveira Faria (A.K.A. CABELO) <cabelo@opensuse.org> or <alessandro.faria@owasp.org>
#
# All modifications and additions to the file contributed by third parties
# remain the property of their copyright owners, unless otherwise agreed
# upon. The license for this file, and modifications and additions to the
# file, is the same license as for the pristine package itself (unless the
# license for the pristine package is not an Open Source License, in which
# case the license is the MIT License). An "Open Source License" is a
# license that conforms to the Open Source Definition (Version 1.9)
# published by the Open Source Initiative.
# Please submit bugfixes or comments via https://bugs.opensuse.org/
#
# Note: Will not build on Leap:15.X on account of too old TBB
# 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 2430
%define shlib lib%{name}%{so_ver}
%define shlib_c lib%{name}_c%{so_ver}
%define prj_name OpenVINO
Name: openvino
Version: 2024.3.0
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
License: Apache-2.0 AND BSD-2-Clause AND BSD-3-Clause AND HPND AND JSON AND MIT AND OFL-1.1 AND Zlib
URL: https://github.com/openvinotoolkit/openvino
Source0: %{name}-%{version}.tar.zst
Source1: %{name}-rpmlintrc
# PATCH-FEATURE-OPENSUSE openvino-onnx-ml-defines.patch badshah400@gmail.com -- Define ONNX_ML at compile time when using system onnx to allow using 'onnx-ml.pb.h' instead of 'onnx.pb.h', the latter not being shipped with openSUSE's onnx-devel package
Patch0: openvino-onnx-ml-defines.patch
# PATCH-FEATURE-OPENSUSE openvino-fix-install-paths.patch badshah400@gmail.com -- Fix installation paths hardcoded into upstream defined cmake macros
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
# PATCH-FIX-UPSTREAM openvino-remove-npu-compile-tool.patch cabelo@opensuse.org -- Remove NPU Compile Tool
Patch5: openvino-remove-npu-compile-tool.patch
BuildRequires: ade-devel
BuildRequires: cmake
BuildRequires: fdupes
BuildRequires: gcc-c++
BuildRequires: ninja
BuildRequires: opencl-cpp-headers
# FIXME: /usr/include/onnx/onnx-ml.pb.h:17:2: error: This file was generated by
# an older version of protoc which is incompatible with your Protocol Buffer
# 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)
BuildRequires: pkgconfig(libva)
BuildRequires: pkgconfig(nlohmann_json)
BuildRequires: pkgconfig(ocl-icd)
BuildRequires: pkgconfig(protobuf)
BuildRequires: pkgconfig(pugixml)
BuildRequires: pkgconfig(snappy)
BuildRequires: pkgconfig(tbb)
BuildRequires: pkgconfig(zlib)
%ifarch %{arm64}
BuildRequires: scons
%endif
# No 32-bit support
ExcludeArch: %{ix86} %{arm32} ppc
%define python_subpackage_only 1
%python_subpackages
%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
%description -n %{shlib}
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}
Requires: %{shlib} = %{version}
Requires: lib%{name}_ir_frontend%{so_ver} = %{version}
Requires: lib%{name}_onnx_frontend%{so_ver} = %{version}
Requires: lib%{name}_paddle_frontend%{so_ver} = %{version}
Requires: lib%{name}_pytorch_frontend%{so_ver} = %{version}
Requires: lib%{name}_tensorflow_frontend%{so_ver} = %{version}
Requires: lib%{name}_tensorflow_lite_frontend%{so_ver} = %{version}
Requires: pkgconfig(OpenCL-Headers)
Requires: pkgconfig(flatbuffers)
Requires: pkgconfig(libva)
Requires: pkgconfig(nlohmann_json)
Requires: pkgconfig(ocl-icd)
Requires: pkgconfig(protobuf)
Requires: pkgconfig(pugixml)
Requires: pkgconfig(snappy)
Requires: pkgconfig(tbb)
Recommends: %{name}-auto-batch-plugin = %{version}
Recommends: %{name}-auto-plugin = %{version}
Recommends: %{name}-hetero-plugin = %{version}
Recommends: %{name}-intel-cpu-plugin = %{version}
%ifarch riscv64
Recommends: %{name}-riscv-cpu-plugin = %{version}
%endif
%description -n %{name}-devel
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
%description -n %{name}-arm-cpu-plugin
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}-riscv-cpu-plugin
Summary: RISC-V CPU plugin for OpenVINO toolkit
%description -n %{name}-riscv-cpu-plugin
OpenVINO is an open-source toolkit for optimizing and deploying AI inference.
This package provides the RISC-V CPU plugin for OpenVINO on riscv64 archs.
#
%package -n %{name}-auto-plugin
Summary: Auto / Multi software plugin for OpenVINO toolkit
%description -n %{name}-auto-plugin
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
%description -n %{name}-auto-batch-plugin
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
%description -n %{name}-hetero-plugin
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
%description -n %{name}-intel-cpu-plugin
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
%description -n lib%{name}_ir_frontend%{so_ver}
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
%description -n lib%{name}_onnx_frontend%{so_ver}
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
%description -n lib%{name}_paddle_frontend%{so_ver}
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
%description -n lib%{name}_pytorch_frontend%{so_ver}
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
%description -n lib%{name}_tensorflow_frontend%{so_ver}
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
%description -n lib%{name}_tensorflow_lite_frontend%{so_ver}
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
Requires: python-openvino-telemetry
%description -n python-openvino
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
%description -n %{name}-sample
OpenVINO is an open-source toolkit for optimizing and deploying AI inference.
This package provides some samples for use with openVINO.
#
%prep
%autosetup -p1
%build
# Otherwise intel_cpu plugin declares an executable stack
%ifarch %{x86_64}
%define build_ldflags -Wl,-z,noexecstack
%endif
%cmake \
-DCMAKE_CXX_STANDARD=17 \
-DBUILD_SHARED_LIBS=ON \
-DENABLE_OV_ONNX_FRONTEND=ON \
-DENABLE_OV_PADDLE_FRONTEND=ON \
-DENABLE_OV_PYTORCH_FRONTEND=ON \
-DENABLE_OV_IR_FRONTEND=ON \
-DENABLE_OV_TF_FRONTEND=ON \
-DENABLE_OV_TF_LITE_FRONTEND=ON \
-DENABLE_INTEL_GPU=OFF \
-DENABLE_JS=OFF \
-DENABLE_PYTHON=ON \
-DENABLE_WHEEL=OFF \
-DENABLE_SYSTEM_OPENCL=ON \
-DENABLE_SYSTEM_PROTOBUF=ON \
-DENABLE_SYSTEM_PUGIXML=ON \
-DENABLE_SYSTEM_SNAPPY=ON \
-DENABLE_SYSTEM_TBB=ON \
-DONNX_USE_PROTOBUF_SHARED_LIBS=ON \
-DProtobuf_USE_STATIC_LIBS=OFF \
%{nil}
%cmake_build
# Manually generate dist-info dir
export WHEEL_VERSION=%{version} \
BUILD_TYPE=RelWithDebInfo
%ifarch %{power64}
# RelWithDebInfo
# Manual hackery for power64 because it not "officially" supported
sed -i "s/{ARCH}/%{_arch}/" ../src/bindings/python/wheel/setup.py
%endif
%python_exec ../src/bindings/python/wheel/setup.py dist_info -o ../
%install
%cmake_install
rm %{buildroot}%{_datadir}/%{prj_name}/samples/cpp/thirdparty/nlohmann_json/.cirrus.yml
# Hash-bangs in non-exec python sample scripts
sed -Ei "1{\@/usr/bin/env@d}" \
%{buildroot}%{_datadir}/%{prj_name}/samples/python/benchmark/bert_benchmark/bert_benchmark.py \
%{buildroot}%{_datadir}/%{prj_name}/samples/python/benchmark/sync_benchmark/sync_benchmark.py \
%{buildroot}%{_datadir}/%{prj_name}/samples/python/benchmark/throughput_benchmark/throughput_benchmark.py \
%{buildroot}%{_datadir}/%{prj_name}/samples/python/classification_sample_async/classification_sample_async.py \
%{buildroot}%{_datadir}/%{prj_name}/samples/python/hello_classification/hello_classification.py \
%{buildroot}%{_datadir}/%{prj_name}/samples/python/hello_query_device/hello_query_device.py \
%{buildroot}%{_datadir}/%{prj_name}/samples/python/hello_reshape_ssd/hello_reshape_ssd.py \
%{buildroot}%{_datadir}/%{prj_name}/samples/python/model_creation_sample/model_creation_sample.py
# Unnecessary if we get our package dependencies and lib paths right!
rm -fr %{buildroot}%{_prefix}/install_dependencies \
%{buildroot}%{_prefix}/setupvars.sh
%{python_expand rm %{buildroot}%{$python_sitearch}/requirements.txt
chmod -x %{buildroot}%{$python_sitearch}/%{name}/tools/ovc/ovc.py
cp -r %{name}-%{version}.dist-info %{buildroot}%{$python_sitearch}/
%fdupes %{buildroot}%{$python_sitearch}/%{name}/
}
%fdupes %{buildroot}%{_datadir}/
# We do not use bundled thirdparty libs
rm -fr %{buildroot}%{_datadir}/licenses/*
%ldconfig_scriptlets -n %{shlib}
%ldconfig_scriptlets -n %{shlib_c}
%ldconfig_scriptlets -n lib%{name}_ir_frontend%{so_ver}
%ldconfig_scriptlets -n lib%{name}_onnx_frontend%{so_ver}
%ldconfig_scriptlets -n lib%{name}_paddle_frontend%{so_ver}
%ldconfig_scriptlets -n lib%{name}_pytorch_frontend%{so_ver}
%ldconfig_scriptlets -n lib%{name}_tensorflow_lite_frontend%{so_ver}
%ldconfig_scriptlets -n lib%{name}_tensorflow_frontend%{so_ver}
%files -n %{shlib}
%license LICENSE
%{_libdir}/libopenvino.so.*
%files -n %{shlib_c}
%license LICENSE
%{_libdir}/libopenvino_c.so.*
%files -n %{name}-auto-batch-plugin
%dir %{_libdir}/%{prj_name}
%{_libdir}/%{prj_name}/libopenvino_auto_batch_plugin.so
%files -n %{name}-auto-plugin
%dir %{_libdir}/%{prj_name}
%{_libdir}/%{prj_name}/libopenvino_auto_plugin.so
%ifarch %{x86_64}
%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}
%files -n %{name}-arm-cpu-plugin
%dir %{_libdir}/%{prj_name}
%{_libdir}/%{prj_name}/libopenvino_arm_cpu_plugin.so
%endif
%ifarch riscv64
%files -n %{name}-riscv-cpu-plugin
%dir %{_libdir}/%{prj_name}
%{_libdir}/%{prj_name}/libopenvino_riscv_cpu_plugin.so
%endif
%files -n %{name}-hetero-plugin
%dir %{_libdir}/%{prj_name}
%{_libdir}/%{prj_name}/libopenvino_hetero_plugin.so
%files -n lib%{name}_onnx_frontend%{so_ver}
%{_libdir}/libopenvino_onnx_frontend.so.*
%files -n lib%{name}_ir_frontend%{so_ver}
%{_libdir}/libopenvino_ir_frontend.so.*
%files -n lib%{name}_paddle_frontend%{so_ver}
%{_libdir}/libopenvino_paddle_frontend.so.*
%files -n lib%{name}_pytorch_frontend%{so_ver}
%{_libdir}/libopenvino_pytorch_frontend.so.*
%files -n lib%{name}_tensorflow_frontend%{so_ver}
%{_libdir}/libopenvino_tensorflow_frontend.so.*
%files -n lib%{name}_tensorflow_lite_frontend%{so_ver}
%{_libdir}/libopenvino_tensorflow_lite_frontend.so.*
%files -n %{name}-sample
%license LICENSE
%{_datadir}/%{prj_name}/
%files -n %{name}-devel
%license LICENSE
%{_includedir}/%{name}/
%{_libdir}/cmake/%{prj_name}/
%{_libdir}/*.so
%{_libdir}/pkgconfig/openvino.pc
%files %{python_files openvino}
%license LICENSE
%{python_sitearch}/openvino/
%{python_sitearch}/openvino*-info/
%changelog
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