Use -O2 compilation for Autocorrect only (#15425)

[chandanjain999]

Summary:

Apply -02 compiler flag to make FLLM autocorrect faster

Sheet measuring different scopes of applying -02 and the resulting latency
https://docs.google.com/spreadsheets/d/1ZnxoRwCIiMz3hXyhgb6sm_2UThBUyq-mpp8RzksfJMQ/edit?usp=sharing

Latency

Reviewed By: BlakeLucchesi

Differential Revision: D85152814

[pytorch-bot]

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/15583

• 📄 Preview Python docs built from this PR

Note: Links to docs will display an error until the docs builds have been completed.

✅ You can merge normally! (5 Unrelated Failures)

As of commit 7def74c with merge base f4e1bd0 ():

FLAKY - The following job failed but was likely due to flakiness present on trunk:

• pull / test-setup-linux-gcc / linux-job (gh) (similar failure)
  ##[error]The operation was canceled.

BROKEN TRUNK - The following jobs failed but was present on the merge base:

👉 Rebase onto the `viable/strict` branch to avoid these failures

• pull / test-binary-size-linux-gcc / linux-job (gh) (trunk failure)
• pull / test-openvino-linux / linux-job (gh) (trunk failure)
  ##[error]The operation was canceled.
• pull / unittest / windows / windows-job (gh) (trunk failure)
  backends/xnnpack/test/ops/test_conv1d.py::TestConv1d::test_qs8_conv1d_batchnorm_seq
• pull / unittest-editable / windows / windows-job (gh) (trunk failure)
  backends/xnnpack/test/ops/test_conv1d.py::TestConv1d::test_qs8_conv1d_batchnorm_seq

This comment was automatically generated by Dr. CI and updates every 15 minutes.

[meta-codesync]

@chandanjain999 has exported this pull request. If you are a Meta employee, you can view the originating Diff in D85152814.

[github-actions]

This PR needs a release notes: label

If your change should be included in the release notes (i.e. would users of this library care about this change?), please use a label starting with release notes:. This helps us keep track and include your important work in the next release notes.

To add a label, you can comment to pytorchbot, for example
@pytorchbot label "release notes: none"

For more information, see
https://github.com/pytorch/pytorch/wiki/PyTorch-AutoLabel-Bot#why-categorize-for-release-notes-and-how-does-it-work.