Added benchmarking for new torchao low precision attention api#3865
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howardzhang-cv merged 46 commits intomainfrom Mar 9, 2026
Merged
Added benchmarking for new torchao low precision attention api#3865howardzhang-cv merged 46 commits intomainfrom
howardzhang-cv merged 46 commits intomainfrom
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/3865
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 6065db8 with merge base 42bcdc4 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
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This was referenced Feb 21, 2026
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Summary: Test Plan: Reviewers: Subscribers: Tasks: Tags: ghstack-source-id: 2c5edc7 Pull-Request: pytorch#3865
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Summary: Test Plan: Reviewers: Subscribers: Tasks: Tags: ghstack-source-id: 2c5edc7 Pull-Request: pytorch#3865
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Benchmark script for evaluating FP8 attention on Flux (text-to-image) models. Measures image generation quality and runtime performance with and without low-precision attention applied. ghstack-source-id: 0078782 Pull-Request: pytorch#3865
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Benchmark script for evaluating FP8 attention on Flux (text-to-image) models. Measures image generation quality and runtime performance with and without low-precision attention applied. ghstack-source-id: f287aed Pull-Request: pytorch#3865
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Benchmark script for evaluating FP8 attention on Flux (text-to-image) models. Measures image generation quality and runtime performance with and without low-precision attention applied. ghstack-source-id: f287aed Pull-Request: pytorch#3865
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do you want to eventually compare this with results from quantizing linear, moe, etc? if yes, could just build into existing scripts from the start, if no then separate script seems fine |
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Benchmark script for evaluating FP8 attention on Flux (text-to-image) models. Measures image generation quality and runtime performance with and without low-precision attention applied. ghstack-source-id: f287aed Pull-Request: pytorch#3865
howardzhang-cv
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Benchmark script for evaluating FP8 attention on Flux (text-to-image) models. Measures image generation quality and runtime performance with and without low-precision attention applied. ghstack-source-id: f287aed Pull-Request: pytorch#3865
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Summary
Example Run
python benchmarks/prototype/attention/eval_flux_model.py --baseline fa3 --test fa3_fp8 --compile