refactor accuracy eval script to be organized by hardware #3472
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/3472
Note: Links to docs will display an error until the docs builds have been completed. This comment was automatically generated by Dr. CI and updates every 15 minutes. |
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Summary: We have a many-to-many mapping of recipe to device it can run on. Reorganizing the accuracy script to reflect this, since we don't have a machine that can run all the workflows. Test Plan: ``` // test on h100 benchmarks/quantization/eval_accuracy_for_readme.sh h100 ``` Reviewers: Subscribers: Tasks: Tags: ghstack-source-id: 3c697ac ghstack-comment-id: 3633684836 Pull-Request: #3472
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| QUANT_RECIPES_ALL=( | ||
| # no quantization (baseline) | ||
| "None" | ||
| "float8_rowwise" |
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Just checking, is this the only float8 recipe we want to showcase?
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this is covering all of the server GPU recipes from https://github.com/pytorch/ao/tree/main?tab=readme-ov-file#stable-workflows, and leaving out all other recipes
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Summary:
We have a many-to-many mapping of recipe to device it can run on.
Reorganizing the accuracy script to reflect this, since we don't have a
machine that can run all the workflows.
Test Plan:
Reviewers:
Subscribers:
Tasks:
Tags: