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[inductor] Limit cpu copies in autotuning to CUDA devices by masnesral · Pull Request #137509 · pytorch/pytorch · GitHub
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[inductor] Limit cpu copies in autotuning to CUDA devices #137509
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Summary: Missed in #136701 (comment): we should perform this optimization only for mutated args on cuda devices Test Plan: `python benchmarks/dynamo/timm_models.py --performance --inductor --device cuda --inference --bfloat16 --print-compilation-time --print-memory --cold-start-latency --only fbnetc_100` [ghstack-poisoned]
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/137509
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 9f297f6 with merge base 9b2e453 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
masnesral
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Summary: Missed in #136701 (comment): we should perform this optimization only for mutated args on cuda devices Test Plan: `python benchmarks/dynamo/timm_models.py --performance --inductor --device cuda --inference --bfloat16 --print-compilation-time --print-memory --cold-start-latency --only fbnetc_100` ghstack-source-id: 3c0c6f2 Pull Request resolved: #137509
int3
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Thank you!
eellison
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Oct 8, 2024
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@pytorchbot merge |
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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Stack from ghstack (oldest at bottom):
Summary: Missed in #136701 (comment): we should perform this optimization only for mutated args on cuda devices
Test Plan:
python benchmarks/dynamo/timm_models.py --performance --inductor --device cuda --inference --bfloat16 --print-compilation-time --print-memory --cold-start-latency --only fbnetc_100cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang