[XPU] call empty_cache for dynamo tests #126377
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/126377
Note: Links to docs will display an error until the docs builds have been completed. ✅ You can merge normally! (1 Unrelated Failure)As of commit 56a7d2e with merge base d0dfcd2 ( BROKEN TRUNK - The following job failed but were present on the merge base:👉 Rebase onto the `viable/strict` branch to avoid these failures
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EikanWang
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benchmarks/dynamo/common.py
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| ), "The empty_gpu_cache needs to be called with a non empty device str" | ||
| if device == "cuda": | ||
| torch.cuda.empty_cache() | ||
| if device == "xpu": |
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Thanks for the review! Solved in 56a7d2e
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Summary: When running a batch of models, lacking `empty_cache()` would result in OOM for subsequent models. This PR unifies the `empty_cache` call for both CUDA and XPU. X-link: pytorch/pytorch#126377 Approved by: https://github.com/EikanWang, https://github.com/guangyey, https://github.com/desertfire Reviewed By: huydhn Differential Revision: D57518757 fbshipit-source-id: a42ae31e7fb81bb05217fd672a3427bd68478a50
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When running a batch of models, lacking `empty_cache()` would result in OOM for subsequent models. This PR unifies the `empty_cache` call for both CUDA and XPU. Pull Request resolved: pytorch#126377 Approved by: https://github.com/EikanWang, https://github.com/guangyey, https://github.com/desertfire
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When running a batch of models, lacking
empty_cache()would result in OOM for subsequent models.This PR unifies the
empty_cachecall for both CUDA and XPU.cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang