test(torch_provider): guard the d256 aten-op test's backward too (fixes py_test sm80 red since #554)

[egilliam-nv]

Summary

test/python/sdpa/test_torch_provider.py::test_d256_direct_aten_op (added in #554) has been failing on Ampere in py_test:rel:sm80 / py_test:dev:sm80 on every PR since it merged (e.g. job 421380222):

cudnn._compiled_module.cudnnGraphNotSupportedError: Num hidden_dim should be less than or equal to 128 and hidden_dim should be multiple of 8

Two gaps in the test's skip guard:

• It wraps only the forward aten call. On Ampere the forward builds fine; the backward graph is what validate() rejects — Ampere falls into the native backward node's d <= 128 branch (scaled_dot_product_flash_attention.h), and pygraph.validate() runs that C++ validation before any FROST routing, so the d=256 backward never reaches an OSS engine, with or without CUDNN_FRONTEND_ENABLE_FROST_ENGINES=1 (verified both ways on an A100).
• It catches RuntimeError, but the frontend raises cudnnGraphNotSupportedError, which derives from Exception.

Fix: one guard around forward + backward, catching both, with a skip reason naming the arch gate. Verified on A100 (develop 22ed1b1fe): the test now skips in both env modes; the whole test_torch_provider.py file is 16 passed / 1 skipped in the CI-like (no-FROST) env.

Not in this PR

The underlying blind spot — the native support surface gating graphs that a FROST engine could serve (the SM80 backward row advertises d <= 256, so this exact d=256 case is servable) — is architectural (pygraph.validate() exempts only graphs with no native lowering or a caller-registered engine) and is tracked in #704, with #818 as the fix vehicle. Note this guard stays correct after #818: the py_test jobs run FROST-off, where classic C++ validation still applies; in a FROST-on run the test simply executes on the SM80 row.

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Summary by CodeRabbit

• Tests
  • Updated d=256 direct ATen coverage to skip unsupported GPU architectures and cuDNN versions before allocation.
  • Tests continue to skip recognized cuDNN graph and engine-selection limitations while re-raising unrelated runtime failures.

[egilliam-nv]

@cudnn-ci-bot run python_tests

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SHA: c584ca5
Targets: python_tests
Branch: cudnn-gh/pr-863-c584ca5
Pipeline: 65879629
Last updated: 2026-09-02 17:58 UTC

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📝 Walkthrough

Walkthrough

The d=256 direct cuDNN ATen test now skips unsupported GPU and cuDNN environments before allocation. It preserves separate forward and backward support checks and re-raises unrelated runtime errors.

Changes

SDPA support validation

Layer / File(s)	Summary
Environment capability gate test/python/sdpa/test_torch_provider.py	The test skips GPUs below SM80 and cuDNN versions below 9.6 before tensor allocation.
Combined forward and backward support check test/python/sdpa/test_torch_provider.py	The test handles graph-unsupported errors and recognized unsupported-engine messages. It re-raises unrelated runtime errors while requiring both forward and backward support.

Estimated code review effort: 2 (Simple) | ~10 minutes

Merge Risk: ⚪ Minimal · up to 5c138

This change only updates an SDPA test to skip unsupported hardware cases consistently across forward and backward validation; no actionable merge-blocking risk remains after normal checks and review.

Suggested reviewers: vedaanta

🚥 Pre-merge checks | ✅ 5

✅ Passed checks (5 passed)

Check name	Status	Explanation
Docstring Coverage	✅ Passed	Docstring coverage is 100.00% which is sufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 1 functions across 1 files.
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Title check	✅ Passed	The title clearly identifies the main change: extending the d256 ATen test guard to cover backward execution and the SM80 failure context.
Description check	✅ Passed	The description explains the failure, root cause, fix, scope boundaries, related tracking issues, and test results. It is mostly complete, although it does not reproduce all template headings or check…

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Explanation

The description explains the failure, root cause, fix, scope boundaries, related tracking issues, and test results. It is mostly complete, although it does not reproduce all template headings or checklist items.

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Inline comments:
In `@test/python/sdpa/test_torch_provider.py`:
- Around line 266-267: Update the exception handling around the ATen forward and
backward operations so unrelated RuntimeError instances are re-raised rather
than skipped. Catch only the expected unsupported-graph condition for the
relevant operation, while retaining cudnn.cudnnGraphNotSupportedError as its own
pytest.skip path.
- Around line 256-261: Update test_torch_provider.py around
test_d256_direct_aten_op() to gate execution before BF16 tensor allocation:
require an SM80-or-newer GPU and cuDNN backend version 9.12 or newer, skipping
the test when either prerequisite is unavailable. Keep expected
unsupported-configuration handling narrow by catching only the specific cuDNN
graph-not-supported exception rather than every RuntimeError.

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[egilliam-nv]

@cudnn-ci-bot run python_tests

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🏁 Pipeline finished

SHA: 5c13844
Targets: python_tests
Branch: cudnn-gh/pr-863-5c13844
Pipeline: 65881226
Last updated: 2026-09-02 18:05 UTC