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dnnl: init at 1.1.1 #74893

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bhipple commented Dec 3, 2019

This commit continues the work proposed in #68014, but fixes the issue with the
proprietary mkl defaults. Since mkl is a heavyweight proprietary package, we
only want to enable it when the user explicitly requests it.

By default, dnnl will be built with all FOSS packages on Hydra. The
proprietary mkl variant can be enabled easily via an overlay for users who
wish to use it.

Fixes #67982, closes #68014

Co-authored-by: Alex Rice alexrice999@hotmail.co.uk

Motivation for this change
Things done
  • Tested using sandboxing (nix.useSandbox on NixOS, or option sandbox in nix.conf on non-NixOS linux)
  • Built on platform(s)
    • NixOS
    • macOS
    • other Linux distributions
  • Tested via one or more NixOS test(s) if existing and applicable for the change (look inside nixos/tests)
  • Tested compilation of all pkgs that depend on this change using nix-shell -p nix-review --run "nix-review wip"
  • Tested execution of all binary files (usually in ./result/bin/)
  • Determined the impact on package closure size (by running nix path-info -S before and after)
  • Ensured that relevant documentation is up to date
  • Fits CONTRIBUTING.md.
Notify maintainers

cc @alexarice @jonringer @stites @Ericson2314

This commit continues the work proposed in #68014, but fixes the issue with the
proprietary `mkl` defaults. Since `mkl` is a heavyweight proprietary package, we
only want to enable it when the user explicitly requests it.

By default, `dnnl` will be built with all FOSS packages on Hydra. The
proprietary `mkl` variant can be enabled easily via an overlay for users who
wish to use it.

Fixes #67982, closes #68014

Co-authored-by: Alex Rice <alexrice999@hotmail.co.uk>
@bhipple bhipple mentioned this pull request Dec 3, 2019
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bhipple commented Dec 3, 2019

Interestingly, the FOSS variant as built by ofborg builds just fine . . . but the MKL variant is failing some test cases. I'll take a look tomorrow.

The mklSupport attribute was chosen specifically because that's what pytorch happens to use; in #74894 I'm working on generalizing this across the stack so it can be consistently overlaid.

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