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[ops] fix: honor sigmoid activation in npu gated rmsnorm - #1223
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Check name Status Explanation Linked Issues check Check skipped because no linked issues were found for this pull request. Out of Scope Changes check Check skipped because no linked issues were found for this pull request. Description Check Check skipped - CodeRabbit’s high-level summary is enabled. Title check The title clearly and concisely describes the main change: making NPU gated RMSNorm honor the sigmoid activation.
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Inline comments:
In `@tests/ops/test_npu_rms_norm_gated.py`:
- Line 23: Add a native-NPU forward-and-gradient parity test alongside the
existing test, using actual torch_npu operators instead of the CPU-backed fake
in the SimpleNamespace patch. Exercise the sigmoid path of the RMS-norm-gated
operation on an NPU tensor, and compare both outputs and gradients against the
established reference behavior while preserving the existing CPU test.
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Review comments at @tests/ops/test_npu_rms_norm_gated.py:
- Around line 68-70: Update the native NPU availability checks around
pytest.importorskip("torch_npu") and torch.npu.is_available() so missing
torch_npu or an unavailable NPU fails clearly when running in Ascend CI, while
retaining skips for local CPU runs. Use the existing CI environment indicator to
distinguish the required-NPU job from local runs.
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Closing as superseded by #1309 and #1142 on
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What does this PR do?
The NPU gated RMSNorm previously ignored activation="sigmoid" and always applied SiLU. Honor the activation, preserve the sigmoid reference cast boundary, and retain the existing default SiLU route. Also honor parameter device/dtype and reject invalid gates.
Test
3 CPU contract tests passed using a mocked torch_npu implementation; these are not native kernel parity tests. make quality passed with Ruff 0.13.1. Native precision/performance validation remains required.
Scope
Extracted from an Ascend training baseline and ported to public main. No dataset paths, deployment credentials, runtime images or private bootstrap hooks. This PR does not claim complete end-to-end checkpoint validation.
Summary by CodeRabbit
New Features
Tests
Review repair receipt (2026-10-09)
2026-10-09 review fixes: added real, unmocked Ascend sigmoid/SiLU forward and x/gate/weight-gradient parity tests for BF16/FP32 with autocast on/off. Explicitly wired the test into NPU CI and corrected the existing SiLU fixture's gate width to match its input. Validation: 3 CPU contract tests passed; 8 native cases skipped on this CPU host; pinned Ruff
make qualitypassed. Native parity awaits NPU CI; it is not claimed as passed.Maintainer repair — 2026-10-16
Merged current upstream and repaired all six legacy extended fixtures to use matching hidden/gate shapes; invalid gates are tested separately for sigmoid/SiLU. 5 portable tests passed; 34 native cases skipped across the targeted files. The Ascend workflow now imports the real
torch_npuruntime and asserts a live NPU immediately before parity tests, so missing hardware cannot produce a green all-skipped parity gate. Native BF16/FP32, sigmoid/SiLU and autocast forward/all-gradient parity remains to be executed.Published revision:
e9119722e6f48417cca7863ca69816a0bea9baa3. No force push or training JobRun modification.Native feedback dependency correction — 2026-10-16
Reconciled upstream 0c1d908 without changing the validated sigmoid unit-weight normalization/cast boundary or SiLU fused arithmetic. Retained upstream generic ACT2FN and swish support, with four additional portable output/all-gradient checks. Unknown activation rejection uses a genuinely unsupported name. Targeted regression: 9 passed,34 native cases skipped; pinned Ruff0.13.2 and independent review pass.
Current exact revision:
0df941853639999845fa3db4bf64bdac1009847e. No forced history rewrite, resource action or new native success claim.Explicit native-test requirement — 2026-10-18
Revision
1256dc0ec3714470644f8bff4ac8e607ca40d250explicitly passesVEOMNI_REQUIRE_NPU=1into the native parity pytest process. In that mode the test directly importstorch_npuand asserts that a live NPU is available, so a missing runtime/device fails rather than skipping. Ordinary CPU invocations retain optional native-case skips.The workflow already had a separate runtime/device preflight; it remains intact. This follow-up makes the requirement explicit inside the test process as well. No kernel arithmetic, numerical tolerances or training configuration changed. As requested, no new pytest/hardware/experiment run; Ruff, whitespace, syntax checks and independent static review passed.