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Included review availability: Your plan provides up to 12 included reviews per hour; 11 remain after this review. WalkthroughRubin NVFP4 fused FC12 now supports SwiGLU and SiTU activation modes. Activation parameters flow through the public operator, runner, tactic keys, autotuner, and generated kernel. Backend selection and tests cover FC12 SiTU execution and degradation rules. ChangesRubin FC12 activation support
Priority: ➖ Normal Estimated code review effort: 4 (Complex) | ~45 minutes Change: Feature Sequence Diagram(s)sequenceDiagram
participant TorchOperator
participant FC12Runner
participant Autotuner
participant RubinKernel
participant ActivationEpilogue
TorchOperator->>FC12Runner: pass activation type and beta values
FC12Runner->>Autotuner: identify configured workload
FC12Runner->>RubinKernel: execute fused FC12
RubinKernel->>ActivationEpilogue: dispatch SiTU or SwiGLU
ActivationEpilogue-->>TorchOperator: return fused output
Merge Risk: 🔵 Low · up to The FC12 SiTU validation tests do not cover nonuniform linear softcaps, so a regression could go undetected. This is a bounded follow-up risk. 🚥 Pre-merge checks | ✅ 4 | ❌ 1❌ Failed checks (1 warning)
✅ Passed checks (4 passed)
✨ Finishing Touches🧪 Generate unit tests (beta)
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In `@tests/unittest/_torch/moe/test_kimi_k3_situ_moe.py`:
- Around line 1723-1726: Update the FC12 test’s skip condition to also require
the explicit MoED.CUTEDSL_RUBIN capability, while preserving the existing CUDA
and SM107 checks and skip reason.
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Blocked for Rubin 1.3 on two mechanical items. Please update the FC12 SiTU test skip condition to require explicit |
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One correctness guard must be fixed before re-review.
The FC12 SiTU test currently gates on CUDA and SM107 but not on the explicit MoED.CUTEDSL_RUBIN capability it exercises. Please add that capability requirement while preserving the existing architecture checks, then resolve the main conflict and rerun the focused Rubin backend/shape and real-kernel tests. This is required for this PR; otherwise unsupported configurations can enter a capability-specific test path.
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Approved on functionality; the bot’s remaining test-guard item is non-blocking.
The Rubin FC12 SiTU implementation has focused backend/shape coverage and reported real-kernel plus CUDA-graph validation. Adding MoED.CUTEDSL_RUBIN to the test skip condition is worthwhile test hygiene, but it does not invalidate the supported SM107 path. The branch still must resolve its main conflict before merge.
…u-main Signed-off-by: Xin Guan <294044352+xguannv@users.noreply.github.com> # Conflicts: # tests/unittest/_torch/moe/test_kimi_k3_situ_moe.py
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Inline comments:
In `@tests/unittest/_torch/moe/test_moe_backend.py`:
- Line 1307: Update the SiTuActivation validation test to parameterize separate
cases where gate_softcap and linear_softcap are each nonuniform, ensuring both
nonuniform inputs are rejected. Preserve the existing expected error-path
assertion and use scalar values for the other softcap in each case.
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In `@tensorrt_llm/_torch/models/modeling_kimi_linear.py`:
- Line 1406: Add "CUTEDSL_FC12" to the non-degradable set used by create_moe so
unavailable FC12 raises instead of selecting the Cutlass fallback. Preserve the
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No attention change, approve to unblock it
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The reported Rubin numerics contradict the test at head, and CI cannot catch it. The description says the real CUTEDSL_FC12 SiTU test passed with relative L2 0.232667 against the SiTU reference, but _SITU_NVFP4_REL_L2_MAX in test_kimi_k3_situ_moe.py is 0.20 (from #19003, which landed in this branch via the merge from main, after the Slurm run on 51ec5e46). At the current head that number fails the assertion. Since the test skips on every SM except 107, the manual Rubin run is the only merge gate for this path, and it is stale. Please rerun test_nvfp4_kernel_actually_applies_situ[CUTEDSL_FC12] at head and post cosine, rel_l2 and |k|/|ref|.
Beyond pass/fail, the number itself is suspicious. The bound's comment derives it as sqrt(stages)×0.095; the other three NVFP4 backends measure 0.161–0.166 (sqrt(3)×eps). 0.2327/0.095 ≈ 2.45 ≈ sqrt(6), i.e. roughly three extra quantization-stage-equivalents, and it also exceeds the measured plain-SwiGLU distance (≥0.205). The SiTU epilogue math is copied verbatim from the Blackwell act-fusion kernel that scores 0.16, so the excess is more likely in the FC12-specific path (in-kernel requant/SFC generation, alpha application) than in the activation formula. Comparing FC12 SwiGLU vs two-op CUTEDSL SwiGLU on the same shape would tell whether this is SiTU-specific or an FC12-wide precision characteristic. Please do not loosen the bound without that analysis; the comment above it says why.
Smaller items:
- The description is truncated mid-sentence ("Incorrect SwiGLU ref") — that number is exactly what is needed for the analysis above.
[None]on a feature PR that adds a new kernel epilogue and backend capability: please attach a JIRA.- The
CuteDslFc12FusedMoENvfp4Runner.forward/do_preparationoverride is a behavior change (FC12 preparation went from a no-op to priming both tiles) that the description does not mention. CUTEDSL_FC12is not mentioned anywhere underdocs/source(pre-existing since #18357). A line in the MoE backend docs listing it and its SwiGLU/SiTU support would help.
| "ActivationType.SiTu requires both situ_beta and " | ||
| f"situ_linear_beta, got {situ_beta} and {situ_linear_beta}." | ||
| ) | ||
| if situ_beta <= 0 or situ_linear_beta <= 0: |
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<= 0 admits inf and nan (every comparison with nan is False). Both are then folded into the epilogue constants: with beta=inf, 2.0/beta, 2.0*beta, -beta become 0, inf, -inf and every output element is inf*sigmoid(0) - inf = NaN. The Blackwell act-fusion kernel checks 0 < situ_beta < _INF and 0 < situ_linear_beta < _INF for exactly this reason; please use the same bounded check here (or math.isfinite) so a bad softcap raises at construction instead of producing NaNs at runtime.
| ) | ||
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| @cute.jit | ||
| def _apply_situ_epilogue( |
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This method and the nested _sigmoid are byte-for-byte copies of _apply_situ_epilogue in blackwell/blockscaled_contiguous_gather_grouped_gemm_act_fusion.py:2836-2924. Copying is defensible if the Rubin kernel must stay self-contained, but a numerics fix in one will not reach the other. Consider lifting the packed-f32x2 sigmoid/tanh helpers into cute_dsl_kernels/utils (next to silu_f32/sigmoid_f32) and calling them from both kernels, or at minimum add a cross-reference comment in both places so the drift risk is visible.
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| router_logits = gate.compute_logits(x) | ||
| actual = moe.forward(x, router_logits, all_rank_num_tokens=None).float() | ||
| assert torch.isfinite(actual).all() |
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This test asserts situ_l2 < _SITU_NVFP4_REL_L2_MAX (0.20, line 1836) further down, but the PR description reports rel_l2 0.232667 for CUTEDSL_FC12. That run predates the merge of #19003, which introduced the calibrated bound. Because the FC12 parametrization skips on every SM except 107, no CI lane will exercise this; please rerun at head on Rubin and report cosine, rel_l2 and |k|/|ref|. If it fails, follow the comment above the bound: 0.233 ≈ sqrt(6)*0.095 vs the other backends' sqrt(3)*0.095, which points at extra quantization stages in the FC12 path rather than at the bound.
| - unittest/_torch/moe/test_moe_backend.py::test_trtllm_gen_nvfp4_situ_selects_padded_quant_method | ||
| - unittest/_torch/moe/test_moe_backend.py::test_trtllm_gen_nvfp4_situ_fc31_scale_c_drops_dequant_scale | ||
| - unittest/_torch/moe/test_moe_backend.py::test_megamoe_bakes_situ_softcaps_as_uniform_scalars | ||
| - unittest/_torch/moe/test_moe_backend.py::test_codegen_baked_situ_softcaps_are_uniform_scalars |
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The rename is complete (only this list had the old name), but the four new GPU-free tests in test_moe_backend.py (test_fc12_rejects_nonuniform_situ_softcaps, test_fc12_swiglu_keeps_clamp_without_situ_constants, test_fc12_outer_tuning_separates_activation_and_softcaps, test_fc12_preparation_primes_fused_tiles_without_two_op_memset_knob) and test_moe_impl.py::test_fc12_pinned_activation_support are not registered here or in any other l0 list, so CI never runs them. This file lists test_moe_backend.py per-function, and test_moe_impl.py is not in any list at all. Please add the new functions here alongside this entry.
| tactic: Optional[int], | ||
| do_preparation: bool = False, | ||
| ) -> torch.Tensor: | ||
| if do_preparation: |
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Worth stating in the docstring that this override exists because setting workload_identity (new in this PR) turns on the parent's priming loop, which passes overlap_moe_output_memset=False, a kwarg run_moe_nvfp4_impl does not accept. Before this PR FC12 preparation was effectively a no-op (identity was None), so this is a behavior change for the SwiGLU path too, not just SiTU; the PR description should mention it.
Signed-off-by: Xin Guan <294044352+xguannv@users.noreply.github.com>
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ActivationType.SiTuwhile preservingSwigluand clamp behavior.CUTEDSL_FC12as a strict Kimi K3 SiTU backend.main, and focused Rubin test reruns.QA Engineer Review
test_codegen_baked_situ_softcaps_are_uniform_scalars.Per-File QA Perspective
tensorrt_llm/_torch/custom_ops/cute_dsl_custom_ops.py: Verify activation and SiTU beta defaults, schema changes, and forwarding.tensorrt_llm/_torch/cute_dsl_kernels/rubin/moe/rubin_contiguous_grouped_blockscaled_gemm_fused_fc12.py: Verify SiTU epilogues, validation, clamp rejection, and SwiGLU behavior.tensorrt_llm/_torch/moe/fused_moe/fused_moe_cute_dsl_fc12.py: Verify capability reporting, autotuner-key separation, and FC12 preparation.tensorrt_llm/_torch/models/modeling_kimi_linear.py: Verify strict Kimi K3 routing toCUTEDSL_FC12.tests/integration/test_lists/test-db/l0_b200.yml: Renames the SiTU softcap test entry in the CI test database.tests/unittest/_torch/moe/test_kimi_k3_situ_moe.py: Covers Rubin FC12 execution, capability gating, CUDA Graph replay, and backend preservation. CI-list coverage is not established.tests/unittest/_torch/moe/test_moe_backend.py: Covers softcaps, cache identities, clamp behavior, and FC12 preparation. CI-list coverage is not established.tests/unittest/_torch/moe/test_moe_impl.py: Covers SiTU acceptance andRelu2rejection. CI-list coverage is not established.Description
PR #18357 added the Rubin FC12 MoE backend, but its fused epilogue supports only SwiGLU. Kimi K3 uses SiTU, so the resolver cannot select FC12 for those MoE layers.
This change:
Existing SwiGLU and clamp behavior remains supported.
Test Coverage
Added tests cover:
Validation:
python3 -m py_compilepassed for all six modified Python files.51ec5e46b792ef64fd9e5db96dc49edb09bc7ba8, Slurm job621253: the TensorRT-LLM build withCMAKE_CUDA_ARCHITECTURES=107-realpassed. The three implementation-file blobs are unchanged in the current rebased commit666fc3a35459369f9bf23463d99a3f4fa4ecd4d6.CUTEDSL_FC12SiTU kernel and CUDA Graph test: passed. SiTU reference: cosine0.972989, relative L20.232667. Incorrect SwiGLU reference: cosine0.065067, relative L20.998031.PR Checklist
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