{ "schema": "nodus.affine_ablation_public_projection.v1", "status": "DRAFT_NOT_PUBLISHED", "observed_at_UTC": "2026-11-10T20:49:47.808196+00:00", "credit": { "original_reporter": "zzw4257", "issue": "https://github.com/NVIDIA/SOL-ExecBench/issues/25", "nodus_reproduction_comment": "https://github.com/NVIDIA/SOL-ExecBench/issues/25#issuecomment-6734823293", "previous_result": "https://data.nodus-compute.ai/blog/identity-inputs-hide-normalization-errors" }, "question": "Which affine input dimensions expose six specific altered normalization formulas, and does that pattern persist across this bounded shape/dtype/seed grid?", "finding": "In this fixed18-fixture CPU grid, weight-only perturbations rejected five of six altered formulas but could not expose omitted bias; bias-only perturbations rejected five of six but could not expose omitted weight. Varying both rejected all six in every fixture. All72copied-reference controls passed.", "interpretation": "More shapes and seeds cannot reveal an omitted affine term when that parameter stays at its identity value. The ablation identifies the parameter-specific blind spots left by one-sided variation in this grid.", "environment": { "python": "3.12.14", "platform": "macOS-26.5.1-arm64-arm-64bit", "torch": "2.14.1", "pydantic": "2.12.5", "torch_cuda": null, "backend": "cpu" }, "grid": { "shapes": [ [ 1, 8 ], [ 4, 64 ], [ 4, 127 ] ], "dtypes": [ "float32", "float16" ], "seeds": [ 7, 42, 2026 ], "regimes": [ "identity", "weight_only", "bias_only", "both_varied" ], "variants": [ "copied_reference", "omit_affine", "omit_weight", "omit_bias", "scalar_affine", "apply_affine_twice", "affine_before_norm" ] }, "denominators": { "planned": 504, "accepted": 216, "rejected": 288, "errors": 0, "requested_without_result": 0, "not_requested": 0, "copied_reference_controls": { "planned": 72, "accepted": 72, "rejected": 0, "missing_or_error": 0 }, "altered_formulas": { "planned": 432, "accepted": 144, "rejected": 288, "missing_or_error": 0 }, "fixture_configurations": 18, "task_families": 1 }, "altered_formula_totals_by_regime": { "identity": { "planned": 108, "accepted": 108, "rejected": 0, "missing_or_error": 0 }, "weight_only": { "planned": 108, "accepted": 18, "rejected": 90, "missing_or_error": 0 }, "bias_only": { "planned": 108, "accepted": 18, "rejected": 90, "missing_or_error": 0 }, "both_varied": { "planned": 108, "accepted": 0, "rejected": 108, "missing_or_error": 0 } }, "complete_matrix": [ { "variant": "copied_reference", "control": true, "regimes": { "identity": { "planned": 18, "accepted": 18, "rejected": 0, "error": 0, "requested_without_result": 0, "not_requested": 0 }, "weight_only": { "planned": 18, "accepted": 18, "rejected": 0, "error": 0, "requested_without_result": 0, "not_requested": 0 }, "bias_only": { "planned": 18, "accepted": 18, "rejected": 0, "error": 0, "requested_without_result": 0, "not_requested": 0 }, "both_varied": { "planned": 18, "accepted": 18, "rejected": 0, "error": 0, "requested_without_result": 0, "not_requested": 0 } } }, { 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0 }, "both_varied": { "planned": 18, "accepted": 0, "rejected": 18, "error": 0, "requested_without_result": 0, "not_requested": 0 } } }, { "variant": "omit_bias", "control": false, "regimes": { "identity": { "planned": 18, "accepted": 18, "rejected": 0, "error": 0, "requested_without_result": 0, "not_requested": 0 }, "weight_only": { "planned": 18, "accepted": 18, "rejected": 0, "error": 0, "requested_without_result": 0, "not_requested": 0 }, "bias_only": { "planned": 18, "accepted": 0, "rejected": 18, "error": 0, "requested_without_result": 0, "not_requested": 0 }, "both_varied": { "planned": 18, "accepted": 0, "rejected": 18, "error": 0, "requested_without_result": 0, "not_requested": 0 } } }, { "variant": "scalar_affine", "control": false, "regimes": { "identity": { "planned": 18, "accepted": 18, "rejected": 0, "error": 0, "requested_without_result": 0, "not_requested": 0 }, "weight_only": { "planned": 18, "accepted": 0, "rejected": 18, "error": 0, "requested_without_result": 0, "not_requested": 0 }, "bias_only": { "planned": 18, "accepted": 0, "rejected": 18, "error": 0, "requested_without_result": 0, "not_requested": 0 }, "both_varied": { "planned": 18, "accepted": 0, "rejected": 18, "error": 0, "requested_without_result": 0, "not_requested": 0 } } }, { "variant": "apply_affine_twice", "control": false, "regimes": { "identity": { "planned": 18, "accepted": 18, "rejected": 0, "error": 0, "requested_without_result": 0, "not_requested": 0 }, "weight_only": { "planned": 18, "accepted": 0, "rejected": 18, "error": 0, "requested_without_result": 0, "not_requested": 0 }, "bias_only": { "planned": 18, "accepted": 0, "rejected": 18, "error": 0, "requested_without_result": 0, "not_requested": 0 }, "both_varied": { "planned": 18, "accepted": 0, "rejected": 18, "error": 0, "requested_without_result": 0, "not_requested": 0 } } }, { "variant": "affine_before_norm", "control": false, "regimes": { "identity": { "planned": 18, "accepted": 18, "rejected": 0, "error": 0, "requested_without_result": 0, "not_requested": 0 }, "weight_only": { "planned": 18, "accepted": 0, "rejected": 18, "error": 0, "requested_without_result": 0, "not_requested": 0 }, "bias_only": { "planned": 18, "accepted": 0, "rejected": 18, "error": 0, "requested_without_result": 0, "not_requested": 0 }, "both_varied": { "planned": 18, "accepted": 0, "rejected": 18, "error": 0, "requested_without_result": 0, "not_requested": 0 } } } ], "ground_truth": { "epsilon": 1e-05, "formula": "z = torch.nn.functional.layer_norm(x,(N,),eps=1e-5); reference = z*weight+bias", "arithmetic": "Each tensor has selected dtype. The layer_norm output, multiplication output and addition output round according to those PyTorch eager operations. This decomposed reference exactly defines this experiment; it is not asserted bit-identical to a fused affine layer_norm kernel or an independent real-arithmetic oracle.", "positive_control": "reference.clone(); validates transport/checker consistency only, not independent implementation correctness", "altered_formulas": { "omit_affine": "z", "omit_weight": "z+bias", "omit_bias": "z*weight", "scalar_affine": "z*weight[0]+bias[0]", "apply_affine_twice": "reference*weight+bias", "affine_before_norm": "layer_norm(x*weight+bias,(N,),eps=1e-5)" } }, "checker": { "implementation": "Unmodified public compute_error_stats from pinned SOL-ExecBench commit a9fa0804c793d438e70850c33fe34426e66d53dd; not the full evaluator", "source_sha256": "b4fb0210601cde736348fb4b01cf99031663000b7974c8a1615101448e408d00", "tolerance": { "max_atol": 0.01, "max_rtol": 0.01, "required_matched_ratio": 0.99, "max_error_cap": null, "allow_negative_inf": false }, "interpretation": "Checker converts outputs/reference to float32. Finite element agreement uses abs(output-reference)<=0.01+0.01*abs(reference), with at least99percent matched; nonfinite output/reference and all-zero output against nonzero reference fail. No separate max-error ceiling. This is not ordinary torch.allclose. Tolerances are fixed across dtypes; no after-result tuning." }, "generation": { "location": "CPU, using a fresh explicit torch.Generator(device='cpu') seeded once per shape/dtype/seed fixture", "draw_order": [ "x0 = randn(B,N,float32)", "weight_noise = randn(N,float32)", "bias_noise = randn(N,float32)" ], "conversion": "x=x0 cast to selected dtype; weight_var=(1+0.1*weight_noise) computed in float32 then cast; bias_var=(0.1*bias_noise) computed in float32 then cast. Copy those exact tensors to requested backend. Same x/weight_var/bias_var reused in all four regimes.", "regimes": { "identity": "weight=ones,bias=zeros", "weight_only": "weight=weight_var,bias=zeros", "bias_only": "weight=ones,bias=bias_var", "both_varied": "weight=weight_var,bias=bias_var" }, "scope": "New original fixture generator with the same perturbation scale as the earlier patch; it does not execute SOL gen_inputs or establish behavior of every upstream workload. Backend-independent CPU generation is a deliberate new protocol, not a bitwise replay of prior CUDA RNG." }, "partition": "Exposed development diagnostic only. No training/confirmation source, task bank or held-out result is read, changed or inferred. New seeds do not create independent held-out tasks.", "limitations": [ "One exposed development normalization family, not504independent workloads or a held-out benchmark.", "Six hand-selected altered formulas; no defect-prevalence estimate or exhaustive correctness claim.", "Copied-reference controls are not independent correct kernels.", "Reference is selected-dtype eager layer_norm followed by multiply then add; not asserted bit-identical to fused affine LayerNorm.", "Exact public SOL checker helper and fixed tolerance were used; full SOL evaluator/dataset and generated-kernel judge were not run.", "Local macOSarm64 CPU, Torch2.14.1; this grid has no CUDA confirmation, kernel-performance or training result.", "Constant affine dimensions make some formulas algebraically equivalent on that slice; acceptance there is a lack of test coverage, not evidence of an incorrect value for that specific fixture." ], "execution_scope": { "local_CPU_only": true, "new_provider_resources": 0, 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"sha256": "78f5b26a5911eb422ea873f578c4d89b6ae076fa460f2757bb115a1ad8c3d122" } } ], "publication_note": "Portable original synthetic values and public source pins only. Referenced source-artifact names are provenance, not a claim of public download availability; publication/download packaging still pending." }