[Quant][CPU] Avoid NaN in fp8 output of qlinear and qconv#160957
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Xia-Weiwen wants to merge 2 commits intopytorch:mainfrom
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[Quant][CPU] Avoid NaN in fp8 output of qlinear and qconv#160957Xia-Weiwen wants to merge 2 commits intopytorch:mainfrom
Xia-Weiwen wants to merge 2 commits intopytorch:mainfrom
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/160957
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…0957) **Summary** When output dtype is fp8, oneDNN does not ensure intermediate results in the range of [-448, 448] before converting to fp8. So, we may get NaN in the output, which is a disaster for inference. This PR fixes this issue by clamping the intermediate results by oneDNN's post-op clip. **Test plan** ``` pytest -sv test/quantization/core/test_quantized_op.py -k "q and fp8" ``` Pull Request resolved: pytorch#160957 Approved by: https://github.com/Valentine233, https://github.com/CaoE
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Summary
When output dtype is fp8, oneDNN does not ensure intermediate results in the range of [-448, 448] before converting to fp8. So, we may get NaN in the output, which is a disaster for inference. This PR fixes this issue by clamping the intermediate results by oneDNN's post-op clip.
Test plan
cc @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 @jerryzh168