forked from pool/onednn
Accepting request 897397 from home:susnux:branches:science:machinelearning
Update to version 2.2.3 OBS-URL: https://build.opensuse.org/request/show/897397 OBS-URL: https://build.opensuse.org/package/show/science:machinelearning/onednn?expand=0&rev=10
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From cfbefd8d744d4cdcdf3dd2f18576f487b36911b6 Mon Sep 17 00:00:00 2001
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From: Denis Samoilov <denis.samoylov@intel.com>
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Date: Fri, 2 Apr 2021 19:46:22 -0700
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Subject: [PATCH] common, gpu: include thread and limit headers to fix GCC 11
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build issues
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---
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src/common/primitive_cache.hpp | 1 +
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src/gpu/jit/ngen/ngen_auto_swsb.hpp | 1 +
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2 files changed, 2 insertions(+)
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diff --git a/src/common/primitive_cache.hpp b/src/common/primitive_cache.hpp
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index 73cb1224f..05a3e53e5 100644
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--- a/src/common/primitive_cache.hpp
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+++ b/src/common/primitive_cache.hpp
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@@ -20,6 +20,7 @@
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#include <future>
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#include <list>
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#include <memory>
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+#include <thread>
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#include <unordered_map>
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#include "c_types_map.hpp"
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diff --git a/src/gpu/jit/ngen/ngen_auto_swsb.hpp b/src/gpu/jit/ngen/ngen_auto_swsb.hpp
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index de3417af3..62ef2a571 100644
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--- a/src/gpu/jit/ngen/ngen_auto_swsb.hpp
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+++ b/src/gpu/jit/ngen/ngen_auto_swsb.hpp
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@@ -33,6 +33,7 @@
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#include <list>
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#include <map>
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+#include <limits>
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namespace ngen {
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namespace autoswsb {
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--
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2.26.2
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3
oneDNN-2.2.3.tar.gz
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3
oneDNN-2.2.3.tar.gz
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version https://git-lfs.github.com/spec/v1
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oid sha256:07e5cc2a30e7bb5a381eba04f8579f427372132ed3d44363f5fd89850a7b50fd
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size 9534138
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@ -1,3 +0,0 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:01e651eb20ca1943bbdf756804fd02d13e5ff3c84b89e3aa5d40abdeb5bb07ee
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size 9533876
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@ -1,3 +1,23 @@
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-------------------------------------------------------------------
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Thu Jun 3 01:38:56 UTC 2021 - Ferdinand Thiessen <rpm@fthiessen.de>
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- Update to version 2.2.3
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* Fixed a bug in int8 depthwise convolution ptimitive with groups
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and 1d spatial size for processors with AVX-512 and AVX2 support
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* Fixed correctness issue for PReLU primitive
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* Fixed corretness issue in reorder for blocked layouts with
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zero padding
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* Improved performance of weights reorders used by BRGEMM-based
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convolution primitive for processors with AVX-512 support
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* Added -fp-model=precise build flag for DPC++ code
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* Fixed potential memory leak in matmul primitive
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* Fixed performance of matmul primitive when fused with bias
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update and sum
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* Fixed a bug in matmul primitive when writing to non-contiguous
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destination buffer
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- Add upstream patch for GCC11 support
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* 0001-common-gpu-include-thread-and-limit-headers-to-fix-G.patch
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-------------------------------------------------------------------
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Thu May 27 08:10:13 UTC 2021 - Jan Engelhardt <jengelh@inai.de>
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15
onednn.spec
15
onednn.spec
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%define libname libdnnl2
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Name: onednn
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Version: 2.2.2
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Version: 2.2.3
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Release: 0
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Summary: Intel Math Kernel Library for Deep Neural Networks
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License: Apache-2.0
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URL: https://01.org/onednn
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Source0: https://github.com/oneapi-src/oneDNN/archive/v%{version}/%{name}-%{version}.tar.gz
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# PATCH-FIX-UPSTREAM - https://github.com/oneapi-src/oneDNN/pull/1045
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Patch1: onednn-1045.patch
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Source0: https://github.com/oneapi-src/oneDNN/archive/v%{version}/oneDNN-%{version}.tar.gz
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# PATCH-FIX-UPSTREAM onednn-1045.patch -- https://github.com/oneapi-src/oneDNN/pull/1045
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Patch0: onednn-1045.patch
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# PATCH-FIX-UPSTREAM 0001-common-gpu-include-thread-and-limit-headers-to-fix-G.patch
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Patch1: 0001-common-gpu-include-thread-and-limit-headers-to-fix-G.patch
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BuildRequires: cmake
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BuildRequires: doxygen
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BuildRequires: fdupes
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@ -114,8 +116,7 @@ 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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%prep
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%setup -q -n oneDNN-%{version}
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%autopatch -p1
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%autosetup -p1 -n oneDNN-%{version}
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%build
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%cmake \
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@ -169,6 +170,7 @@ popd
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%{_datadir}/benchdnn
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%files devel
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%doc README.md
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%{_includedir}/mkl-dnn
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%{_includedir}/mkldnn*.h*
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%{_includedir}/dnnl*.h*
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@ -187,7 +189,6 @@ popd
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%files -n %{libname}
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%license LICENSE
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%doc README.md
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%{_libdir}/libdnnl.so.*
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%{_libdir}/libmkldnn.so.*
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