[inductor][test] Check if mkl dnn bf16 is supported when using bf16 #136290
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Differential Revision: D62984129
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/136290
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This pull request was exported from Phabricator. Differential Revision: D62984129 |
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@jgong5 @XuehaiPan can I get a stamp? |
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@pytorchbot merge |
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Merge failedReason: Approvers from one of the following sets are needed:
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@pytorchbot merge |
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Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
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…ytorch#136290) Sometimes the test is run with older cpu, e.g. Intel(R) Xeon(R) CPU E5-2680 v4. If we inspect its `lscpu`, in the flags, we don't see a `avx512_bf16`. So that probably means bf16 is not supported for those hardwares, and hence the unit test can fail. So we add the check in the code. Context: pytorch#135038 Differential Revision: D62984129 Pull Request resolved: pytorch#136290 Approved by: https://github.com/XuehaiPan, https://github.com/chenyang78
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Sometimes the test is run with older cpu, e.g. Intel(R) Xeon(R) CPU E5-2680 v4. If we inspect its
lscpu, in the flags, we don't see aavx512_bf16. So that probably means bf16 is not supported for those hardwares, and hence the unit test can fail. So we add the check in the code.Context: #135038
Differential Revision: D62984129
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang