Migrate to Graph.materialize_symints; stop passing raw SymInts

[laithsakka]

Summary:
reland plan for pytorch/pytorch#186272 due to executorch dependency have to stage changes !!

Updates the ARM backend passes (convert_full_like_to_full,
decompose_linear, decompose_select, insert_dynamic_padding,
rewrite_conv, size_adjust_input) and the ExportPass base to materialize
SymInt-typed FX-node arguments via Graph.materialize_symints /
create_size_node, so they no longer pass raw SymInts to
Graph.create_node and the new pytorch warning falls silent.

Test assertions in test_decompose_select_pass /
test_insert_dynamic_padding_pass / test_dynamic_shape_propagation are
updated to expect FX Nodes (with the SymInt stored in meta['val']).

This is the second of three diffs split from D107573548.

Differential Revision: D107938874

cc @digantdesai @freddan80 @per @zingo @oscarandersson8218 @mansnils @Sebastian-Larsson @robell @rascani

[pytorch-bot]

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❌ 67 New Failures, 139 Cancelled Jobs, 3 Pending, 1 Unrelated Failure, 26 Unclassified Failures

As of commit 148986d with merge base e0be283 ():

NEW FAILURES - The following jobs have failed:

• Apple / build-benchmark-app / macos-job (gh)
  /Applications/Xcode_15.4.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX.sdk/usr/include/c++/v1/__memory/unique_ptr.h:689:30: error: no matching constructor for initialization of 'libkineto::DeviceInfo'
• Apple / build-demo-ios / macos-job (gh)
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• Apple / build-frameworks-ios / macos-job (gh)
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• check-c10-sync / check-c10-sync (gh)
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• docker-builds / docker-build (linux.4xlarge, executorch-ubuntu-22.04-linter) (gh)
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• Lint / lintrunner-mypy (gh)
  >>> Lint for backends/arm/_passes/size_adjust_input_pass.py:
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• trunk / test-arm-backend-zephyr (zephyr/samples/mv2-ethosu/README.md, ethos-u55) / linux-job (gh)
  AttributeError: DecomposeLinearPass: 'Graph' object has no attribute 'materialize_symints'
• trunk / test-arm-backend-zephyr (zephyr/samples/mv2-ethosu/README.md, ethos-u85) / linux-job (gh)
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• trunk / test-models-linux-aarch64 (add_mul, xnnpack-quantization-delegation, linux.arm64.2xlarge) / linux-job (gh)
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• trunk / test-models-linux-aarch64 (ic3, xnnpack-quantization-delegation, linux.arm64.2xlarge) / linux-job (gh)
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• trunk / unittest-release / macos / macos-job (gh)
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UNCLASSIFIED FAILURES - DrCI could not classify the following jobs because the workflow did not run on the merge base. The failures may be pre-existing on trunk or introduced by this PR:

• Build Windows Wheels / pytorch/executorch / build-wheel-py3_10-cpu (gh) (this job did not run on the merge base, so DrCI cannot tell whether the failure is pre-existing)
• Build Windows Wheels / pytorch/executorch / upload / upload-wheel-py3_10-cpu (gh) (this job did not run on the merge base, so DrCI cannot tell whether the failure is pre-existing)
  Unable to download artifact(s): Artifact not found for name: pytorch_executorch__3.10_cpu_x64
• docker-builds / docker-build (linux.4xlarge, executorch-ubuntu-22.04-arm-sdk) (gh) (this job did not run on the merge base, so DrCI cannot tell whether the failure is pre-existing)
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• docker-builds / docker-build (linux.4xlarge, executorch-ubuntu-22.04-clang12-android) (gh) (this job did not run on the merge base, so DrCI cannot tell whether the failure is pre-existing)
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• docker-builds / docker-build (linux.4xlarge, executorch-ubuntu-22.04-mediatek-sdk) (gh) (this job did not run on the merge base, so DrCI cannot tell whether the failure is pre-existing)
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• docker-builds / docker-build (linux.4xlarge, executorch-ubuntu-22.04-qnn-sdk) (gh) (this job did not run on the merge base, so DrCI cannot tell whether the failure is pre-existing)
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• periodic / test-models-linux (buck2, mv3, portable, linux.2xlarge, 90) / linux-job (gh) (this job did not run on the merge base, so DrCI cannot tell whether the failure is pre-existing)
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• periodic / test-models-linux (cmake, vit, xnnpack-quantization-delegation, linux.2xlarge, 90) / linux-job (gh) (this job did not run on the merge base, so DrCI cannot tell whether the failure is pre-existing)
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• trunk / test-coreml-delegate / macos-job (gh) (this job did not run on the merge base, so DrCI cannot tell whether the failure is pre-existing)
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• trunk / test-models-macos-coreml (edsr) / macos-job (gh) (this job did not run on the merge base, so DrCI cannot tell whether the failure is pre-existing)
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• trunk / test-models-macos-cpu (ic4, xnnpack-quantization-delegation) / macos-job (gh) (this job did not run on the merge base, so DrCI cannot tell whether the failure is pre-existing)
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• Build Presets / linux (linux, linux.2xlarge, executorch-ubuntu-22.04-clang12) / build (gh)
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BROKEN TRUNK - The following job failed but were present on the merge base:

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

• pull / android / build-android (gh) (trunk failure)
  Process completed with exit code 1.

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

[meta-codesync]

@laithsakka has exported this pull request. If you are a Meta employee, you can view the originating Diff in D107938874.

[github-actions]

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[zingo]

Hi @laithsakka thanks for this, do you mind fixing the linting/mypy so this can be approved/merged? 🙏 We have some patches on it way that would look different if this gets merged so we are now planning to do them after. :)

[digantdesai]

@claude review this PR.

[claude]

Claude finished @digantdesai's task in 5m 9s —— View job

---

PR Review: Migrate to Graph.materialize_symints

I reviewed the diff against origin/main, the changed passes, the new pass_base.py helpers, and the failing CI logs.

Summary

The change is well-motivated and the approach is sound: raw SymInts are no longer passed into Graph.create_node call_function args. Two materialization strategies are used, and the split is reasonable:

• Passes that build nodes directly on graph_module.graph use graph.materialize_symints(...) (decompose_linear, decompose_select, rewrite_conv, size_adjust_input).
• Passes that go through call_operator use the new call_size_operator_all helper on _ExportPassBase (convert_full_like, the test_dynamic_shape_propagation test pass).

The comments are thorough and the test updates correctly assert on FX Nodes with the SymInt preserved in meta['val'].

Blocking: lint / mypy (what @zingo asked about)

The Lint / lintrunner-mypy job fails with attr-defined on four sites, because the materialize_symints API does not exist in the torch version mypy resolves against:

• backends/arm/_passes/size_adjust_input_pass.py:244
• backends/arm/_passes/decompose_select.py:63
• backends/arm/_passes/rewrite_conv_pass.py:628
• backends/arm/_passes/decompose_linear_pass.py:69

Each graph.materialize_symints(...) call needs a # type: ignore[attr-defined]. The call_size_operator* helpers don't trip mypy because they route through self.call_operator. Fix this →

Runtime dependency on the pytorch pin

CI also shows real runtime failures, e.g. zephyr:

AttributeError: DecomposeLinearPass: 'Graph' object has no attribute 'materialize_symints'

This is consistent with the PR being the staged reland of pytorch#186272 — .ci/docker/ci_commit_pins/pytorch.txt is bumped release/2.12 → release/2.13, but jobs that don't pick up the new pin (and the locally-installed torch) still lack the API. This PR can't go green until the pinned torch actually exports materialize_symints / create_size_node. Worth confirming the landing order with the reviewers before merge. (The aten.transpose ... 'Dimname' and libkineto::DeviceInfo failures look unrelated to this change.)

Correctness notes (looks good, minor observations)

• rewrite_conv_pass.py:610-631 — Good catch moving the fake-tensor computation before materialization, since target_op(...) expects ints/SymInts, not FX Nodes. conv_args index 4 correctly maps to pad given (x, weight, bias, stride, pad, dilation). ✅
• size_adjust_input_pass.py:243-250 — The flatten → single materialize_symints → regroup via iter/next is correct and preserves per-slice arity. ✅
• decompose_linear_pass.py:64-78 — Slicing all_sizes by n_in / n_w is correct; sharing one call lets repeated symbols hash-cons. ✅
• pass_base.py call_size_operator — Returns plain int for static dims and an aten.sym_size.int proxy for dynamic dims; mirroring example_value only when present matches the surrounding meta convention. ✅
• insert_dynamic_padding.py:39-45 — Now also treats ProxyValue entries in a list/tuple as dynamic, which is the right generalization. ✅

Nits

• call_size_operator / call_size_operator_all are public-looking methods on _ExportPassBase but only emit aten.sym_size.int, which is an aten (not edge) op. Since callers here run on edge graphs, confirm that's intended (it appears to be — sym_size has no edge variant and is left to downstream handling). A one-line note on the helper would help future readers.
• The two materialization paths (helper vs direct graph.materialize_symints) achieve the same goal differently. Not worth unifying, but a short comment pointing out why (call_operator context vs direct graph mutation) would reduce confusion.

Overall the logic is correct; the only true blocker is the mypy # type: ignore and the torch-pin landing dependency.
· branch export-D107938874

[digantdesai]

Too many CI issues, rebase please?

[laithsakka]

started new diff due to export issues https://www.internalfb.com/diff/D109610966