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Summary: Add threading support for FBGEMM FP16 routines.
Reviewed By: dskhudia, jacobkahn
Differential Revision: D13792341
fbshipit-source-id: eb31a11340ac9fd0ee9b4f570d161e7c7e6a7602
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Summary:
FP16Benchmark: Allow comparison against fp32
using any local cblas library if MKL not found.
Pull Request resolved: https://github.com/pytorch/FBGEMM/pull/56
Reviewed By: jianyuh
Differential Revision: D13645545
Pulled By: dskhudia
fbshipit-source-id: ca98e84bfb85eb3b0edebad664d211c3af8db309
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Summary:
Pull Request resolved: https://github.com/pytorch/FBGEMM/pull/53
As title
Reviewed By: jianyuh
Differential Revision: D13561724
fbshipit-source-id: 815ab310f2f4862c65ad0e3d61bf221cb8cf679b
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Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/14340
Pull Request resolved: https://github.com/pytorch/FBGEMM/pull/25
Per-group and per-channel quantization in fbgemm
This diff also cleans up explicit template instantiation using macro expansion
This diff also changes randFill interface which was easy to make mistakes of generating integer random numbers for floating point vectors.
Using this in DNNLOWP operators will be done in a separate diff.
Reviewed By: dskhudia
Differential Revision: D13176386
fbshipit-source-id: e46c53e31e21520bded71b8ed86e8b19e010e2dd
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Summary:
Pull Request resolved: https://github.com/pytorch/FBGEMM/pull/11
clang format of fbgemm
Reviewed By: dskhudia
Differential Revision: D13115202
fbshipit-source-id: 6dab29cb8b5f4fabcc165019663351567a2a2952
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