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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/18663
Note: Links to docs will display an error until the docs builds have been completed. ✅ You can merge normally! (2 Unrelated Failures)As of commit 1041db3 with merge base 15b268f ( FLAKY - The following job failed but was likely due to flakiness present on trunk:
BROKEN TRUNK - The following job failed but was present on the merge base:👉 Rebase onto the `viable/strict` branch to avoid these failures
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Summary
Most XNNPACK parameter / constant data is packed and XNNPACK takes ownership of it. This means that we can free the buffer after load. However, PreLU doesn't pack and thus expects the buffer to stay alive. There is a reproable segfault when running PreLU on ET XNNPACK when running from a file (vs. in-memory buffer data). This PR fixes this by only freeing buffers for ops we know take ownership of the data. Practically speaking this should be a no-op for most cases (linear, conv, etc.) but plays it safe for other constant tensors.
Fixes #17559.
cc @digantdesai @cbilgin