forked from pool/onednn
ade11b5481
- Rename mkl-dnn to onednn to follow upstream
- Obsoletes mkl-dnn* <= %{version}
OBS-URL: https://build.opensuse.org/request/show/839525
OBS-URL: https://build.opensuse.org/package/show/science:machinelearning/onednn?expand=0&rev=1
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Mon Oct 5 06:16:30 UTC 2020 - Guillaume GARDET <guillaume.gardet@opensuse.org>
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- Obsoletes mkl-dnn* <= %{version}
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Fri Oct 2 12:47:08 UTC 2020 - Guillaume GARDET <guillaume.gardet@opensuse.org>
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- Rename mkl-dnn to onednn to follow upstream
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Wed Sep 23 13:36:02 UTC 2020 - Guillaume GARDET <guillaume.gardet@opensuse.org>
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- Update to 1.6.3
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- Drop upstream patch:
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* cmake-no-install-ocl-cmake.patch
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Wed Sep 23 13:16:39 UTC 2020 - Guillaume GARDET <guillaume.gardet@opensuse.org>
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- Build on aarch64 and ppc64le which are now also supported
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- Provide oneDNN and oneDNN-devel as it is the new official name
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Tue May 5 07:38:34 UTC 2020 - Tomáš Chvátal <tchvatal@suse.com>
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- Update to 1.4:
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* Performance improvements all over the board
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- Rebase patch cmake-no-install-ocl-cmake.patch
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Tue Mar 24 10:50:57 UTC 2020 - Tomáš Chvátal <tchvatal@suse.com>
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- Add constraints to not crash during testing on OOM
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Thu Feb 27 12:44:00 UTC 2020 - Tomáš Chvátal <tchvatal@suse.com>
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- Do not disable LTO there is no actual reason for that
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- Export LD_LIBRARY_PATH to fix older releases build
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Wed Feb 26 10:36:26 UTC 2020 - Tomáš Chvátal <tchvatal@suse.com>
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- There is no actual reason to not use github tag for tarball
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fetching -> remove the service
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- Format with spec-cleaner
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- Use proper %cmake macros everywhere
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- Add configure options for cmake to set it up in a way we really
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want
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- Add patch from Debian to not install OpenCL cmake finder:
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* cmake-no-install-ocl-cmake.patch
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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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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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normalization (65f1908)
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* Fixed the layer normalization formula (c176ceb)
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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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* 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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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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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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kd_padding=0 computation (52d476c)
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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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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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* Added workaround for number of cores calculation in Xbyak (301b088)
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-------------------------------------------------------------------
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Mon Feb 11 16:35:48 UTC 2019 - cgoll@suse.com
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- added ARCH_OPT_FLAGS=""
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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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Deep Neural Networks which can be used by:
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* tensorflow
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* Caffee
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* PyTorch
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and other machine learning tools
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