Lower Conv1d atomically through TOSA Conv2d (#22282)

[mcremon-meta]

Summary:

Lower one-dimensional convolutions atomically during convolution rewriting instead of expanding them to rank four in an earlier pass. Emit rank-three layout boundaries around the operation and introduce the singleton spatial dimension only after converting the input to the backend layout.

Rewrite regular and depthwise weights directly into their TOSA Conv2d layouts, and retain the earlier expansion path only for transposed one-dimensional convolutions. This exposes rank-three transforms to the existing layout propagation and cancellation passes while keeping the generated convolution representation valid.

Differential Revision: D116686805

[pytorch-bot]

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❌ 2 New Failures, 45 Pending, 1 Unrelated Failure

As of commit dd3785c with merge base 80f7005 ():

NEW FAILURES - The following jobs have failed:

• Lint / lintrunner-mypy (gh)
  >>> Lint for backends/arm/_passes/rewrite_conv_pass.py:
• pull / test-arm-backend-no-driver (test_pytest_ops_tosa) / linux-job (gh)
  RuntimeError: Command docker exec -t a04dd07b6d821df88219d01a18793413fddd4ba238e0df7ffbf0792dc2832841 /exec failed with exit code 1

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

• pull / test-qnn-testsuite-linux / test-backend-linux (qnn, models) / linux-job (gh) (matched linux rule in flaky-rules.json)
  The runner has received a shutdown signal. This can happen when the runner service is stopped, or a manually started runner is canceled.

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[meta-codesync]

@mcremon-meta has exported this pull request. If you are a Meta employee, you can view the originating Diff in D116686805.

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[rascani]

FYI, you'll probably want to rebase and test with #22212 and #22213. The latter is not yet landed. CC @zingo