Accepting request 1235691 from science:machinelearning
OBS-URL: https://build.opensuse.org/request/show/1235691 OBS-URL: https://build.opensuse.org/package/show/openSUSE:Factory/onednn?expand=0&rev=17
This commit is contained in:
Ana Guerrero
Git OBS Bridge
commit
03ed886f24
3
_service
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3
_service
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<services>
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<service name="download_files" mode="manual" />
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</services>
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BIN
oneDNN-3.6.2.tar.gz
(Stored with Git LFS)
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BIN
oneDNN-3.6.2.tar.gz
(Stored with Git LFS)
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version https://git-lfs.github.com/spec/v1
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oid sha256:20c4a92cc0ae0dc19d3d2beca0e357b1d13a5a3af9890a2cc3e41a880e4a0302
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size 13782760
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@ -1,3 +1,9 @@
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-------------------------------------------------------------------
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Fri Jan 3 23:23:08 UTC 2025 - Eyad Issa <eyadlorenzo@gmail.com>
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- Update to 3.6.2:
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* https://github.com/oneapi-src/oneDNN/releases/tag/v3.6.2
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-------------------------------------------------------------------
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Thu Oct 17 11:42:58 UTC 2024 - Guillaume GARDET <guillaume.gardet@opensuse.org>
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@ -24,27 +30,27 @@ Mon Sep 23 10:04:43 UTC 2024 - Guillaume GARDET <guillaume.gardet@opensuse.org>
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Fri Apr 19 17:27:48 UTC 2024 - Alessandro de Oliveira Faria <cabelo@opensuse.org>
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- Update to 3.4.1:
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* Fixed an issue with caching and serialization of primitives in
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* Fixed an issue with caching and serialization of primitives in
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deterministic mode (7ed604a)
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* Introduced memory descriptor serialization API
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* Introduced memory descriptor serialization API
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(4cad420, 929a27a, 9b848c8)
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* Fixed incorrect results in fp64 convolution and deconvolution
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on Intel GPUs based on Xe-LPG architecture (ebe77b5, 0b399ac,
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* Fixed incorrect results in fp64 convolution and deconvolution
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on Intel GPUs based on Xe-LPG architecture (ebe77b5, 0b399ac,
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d748d64, 9f4f3d5, 21a8cae)
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* Fixed incorrect results in reorder with large sizes on
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* Fixed incorrect results in reorder with large sizes on
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Intel CPUs and GPUs (69a111e, 4b72361, 74a343b)
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* Reduced creation time for deconvolution primitive on
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* Reduced creation time for deconvolution primitive on
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Intel CPUs (bec487e, 1eab005)
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* Fixed performance regression in deconvolution on
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* Fixed performance regression in deconvolution on
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Intel CPUs (fbe5b97, 1dd3c6a)
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* Removed dangling symblols from static builds
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* Removed dangling symblols from static builds
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(e92c404, 6f5621a)
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* Fixed crash during platform detection on some
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* Fixed crash during platform detection on some
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AArch64-based systems (406a079)
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* Fixed performance regression in int8 deconvolution on
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* Fixed performance regression in int8 deconvolution on
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Intel CPUs (7e50e15)
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* Fixed handling of zero points for matmul in verbose
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logs converter (15c7916)
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* Fixed handling of zero points for matmul in verbose
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logs converter (15c7916)
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-------------------------------------------------------------------
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Fri Dec 1 04:33:49 UTC 2023 - Alessandro de Oliveira Faria <cabelo@opensuse.org>
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@ -279,38 +285,38 @@ Wed Feb 26 10:36:26 UTC 2020 - Tomáš Chvátal <tchvatal@suse.com>
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-------------------------------------------------------------------
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Thu Feb 20 10:26:52 UTC 2020 - Christian Goll <cgoll@suse.com>
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- enabled tests
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- enabled tests
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-------------------------------------------------------------------
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Thu Jan 30 14:20:22 UTC 2020 - Christian Goll <cgoll@suse.com>
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- packaged separate benchnn packae with its input files
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- updated to v1.1.3 which includes
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* Fixed the mean and variance memory descriptors in layer
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* Fixed the mean and variance memory descriptors in layer
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normalization (65f1908)
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* Fixed the layer normalization formula (c176ceb)
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-------------------------------------------------------------------
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Wed Jan 8 15:21:54 UTC 2020 - Christian Goll <cgoll@suse.com>
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- updated to v1.1.2
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- updated to v1.1.2
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* Fixed threading over the spatial in bfloat16 batched
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normalization (017b6c9)
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* Fixed read past end-of-buffer error for int8 convolution (7d6f45e)
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* Fixed condition for dispatching optimized channel blocking in
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* Fixed condition for dispatching optimized channel blocking in
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fp32 backward convolution on Intel Xeon Phi(TM) processor (846eba1)
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* Fixed fp32 backward convolution for shapes with spatial strides
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* Fixed fp32 backward convolution for shapes with spatial strides
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over the depth dimension (002e3ab)
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* Fixed softmax with zero sizes on GPU (936bff4)
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* Fixed int8 deconvolution with dilation when ih <= dh (3e3bacb)
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* Enabled back fp32 -> u8 reorder for RNN (a2c2507)
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* Fixed segmentation fault in bfloat16 backward convolution from
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* Fixed segmentation fault in bfloat16 backward convolution from
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kd_padding=0 computation (52d476c)
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* Fixed segmentation fault in bfloat16 forward convolution due
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* Fixed segmentation fault in bfloat16 forward convolution due
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to push/pop imbalance (4f6e3d5)
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* Fixed library version for OS X build (0d85005)
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* Fixed padding by channels in concat (a265c7d)
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* Added full text of third party licenses and
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* Added full text of third party licenses and
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copyright notices to LICENSE file (79f204c)
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* Added separate README for binary packages (28f4c96)
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* Fixed computing per-oc mask in RNN (ff3ffab)
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@ -324,7 +330,7 @@ Mon Feb 11 16:35:48 UTC 2019 - cgoll@suse.com
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-------------------------------------------------------------------
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Tue Feb 5 07:45:53 UTC 2019 - Christian Goll <cgoll@suse.com>
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- Initial checking of the Intel(R) Math Kernel Library for
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- Initial checking of the Intel(R) Math Kernel Library for
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Deep Neural Networks which can be used by:
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* tensorflow
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* Caffee
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40
onednn.spec
40
onednn.spec
@ -1,7 +1,7 @@
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#
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# spec file for package onednn
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#
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# Copyright (c) 2024 SUSE LLC
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# Copyright (c) 2025 SUSE LLC
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#
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# All modifications and additions to the file contributed by third parties
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# remain the property of their copyright owners, unless otherwise agreed
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@ -16,27 +16,25 @@
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#
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%define libname libdnnl3
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%ifarch x86_64
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%bcond_without opencl
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%else
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# Build broken on non-x86, with openCL
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%bcond_with opencl
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%endif
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%ifarch aarch64
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# Disable ACL until fixed upstream - https://github.com/oneapi-src/oneDNN/issues/2137
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%bcond_with acl
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%else
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%bcond_with acl
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%endif
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%define libname libdnnl3
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Name: onednn
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Version: 3.6
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Version: 3.6.2
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Release: 0
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Summary: Intel Math Kernel Library for Deep Neural Networks
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Summary: oneAPI Deep Neural Network Library (oneDNN)
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License: Apache-2.0
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URL: https://01.org/onednn
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URL: https://github.com/oneapi-src/oneDNN
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Source0: https://github.com/oneapi-src/oneDNN/archive/v%{version}/oneDNN-%{version}.tar.gz
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BuildRequires: chrpath
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BuildRequires: cmake
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@ -44,7 +42,12 @@ BuildRequires: doxygen
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BuildRequires: fdupes
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BuildRequires: gcc-c++
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BuildRequires: graphviz
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BuildRequires: ninja
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BuildRequires: texlive-dvips-bin
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Provides: mkl-dnn = %{version}
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Obsoletes: mkl-dnn <= %{version}
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Provides: oneDNN = %{version}
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ExclusiveArch: x86_64 aarch64 ppc64le
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%if %{with acl}
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BuildRequires: ComputeLibrary-devel >= 24.08.1
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%endif
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@ -53,17 +56,13 @@ BuildRequires: opencl-headers
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BuildRequires: pkgconfig
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BuildRequires: pkgconfig(OpenCL)
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%endif
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ExclusiveArch: x86_64 aarch64 ppc64le
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Provides: mkl-dnn = %{version}
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Obsoletes: mkl-dnn <= %{version}
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Provides: oneDNN = %{version}
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%description
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Intel Math Kernel Library for Deep Neural Networks (Intel MKL-DNN) is an
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open-source performance library for deep-learning applications. The library
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accelerates deep-learning applications and frameworks on Intel architecture.
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Intel MKL-DNN contains vectorized and threaded building blocks that you can use
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to implement deep neural networks (DNN) with C and C++ interfaces.
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oneAPI Deep Neural Network Library (oneDNN) is an open-source cross-platform
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performance library of basic building blocks for deep learning applications.
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oneDNN project is part of the UXL Foundation and is an implementation of the
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oneAPI specification for oneDNN component.
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%package -n benchdnn
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Summary: Header files of Intel Math Kernel Library
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@ -81,13 +80,13 @@ This package only includes the benchmark utility including its input files.
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%package devel
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Summary: Header files of Intel Math Kernel Library
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Requires: %{libname} = %{version}
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Provides: mkl-dnn-devel = %{version}
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Obsoletes: mkl-dnn-devel <= %{version}
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Provides: oneDNN-devel = %{version}
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%if %{with opencl}
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Requires: opencl-headers
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Requires: pkgconfig(OpenCL)
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%endif
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Provides: mkl-dnn-devel = %{version}
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Obsoletes: mkl-dnn-devel <= %{version}
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Provides: oneDNN-devel = %{version}
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%description devel
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Intel Math Kernel Library for Deep Neural Networks (Intel MKL-DNN) is an
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@ -121,6 +120,7 @@ to implement deep neural networks (DNN) with C and C++ interfaces.
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%autosetup -p1 -n oneDNN-%{version}
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%build
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%define __builder ninja
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%cmake \
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-DCMAKE_INSTALL_LIBDIR=%{_lib} \
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-DMKLDNN_ARCH_OPT_FLAGS="" \
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@ -164,7 +164,7 @@ chrpath -d %{buildroot}/%{_bindir}/benchdnn
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# do not use macro so we can exclude all gpu and cross (gpu and cpu) tests (they need gpu set up)
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pushd build
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export LD_LIBRARY_PATH=%{buildroot}%{_libdir}
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ctest --output-on-failure --force-new-ctest-process %{_smp_mflags} -E '(gpu|cross)'
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ctest --output-on-failure --force-new-ctest-process %{?_smp_mflags} -E '(gpu|cross)'
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popd
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%post -n %{libname} -p /sbin/ldconfig
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