Стенд-проверка (stage-2) · промт оператора:

(универсальный)

Ответ агента:

{ "worked": false, "confidence": 10, "verdict": "Implemented a local custom long-1D convolution classification track and an end-to-end matched baseline/implicit-FFT CNN comparison using the required benchmark utilities. Across 8 paired seeds, the implicit system was significantly worse: test error 0.4850 versus 0.3525, paired delta +0.1325, permutation p=0.0081. The trained-model mechanism signature also failed, with observed relative operator error 1.0826 versus predicted 0, so the claimed transfer was not demonstrated.", "metrics": { "baseline": "Best explicit-padding FFT baseline: mean test error 0.35250, std 0.02773, lr=0.01. Sweep means: lr=0.001 -> 0.43125, lr=0.003 -> 0.43875, lr=0.01 -> 0.35875.", "idea": "Best implicit-padding system: mean test error 0.48500, std 0.03382, lr=0.01, m=8. Idea sweep means: lr=0.001 -> 0.48500, lr=0.003 -> 0.48625, lr=0.01 -> 0.47875.", "paired_comparison": "delta_mean=+0.13250, idea_wins=0/8, permutation_p=0.0081, verdict=idea worse (significant).", "mechanism_signature": "Predicted relative operator error 0; observed relative operator error 1.08260; predicted storage ratio 2.0; trained-system output gap 1.05474; confirmed=false." }, "how_to_run": "/home/maxwelhelp/main/bin/python3 stage2_bench.py", "files": [ "stage2_bench.py", "bench_report.json" ], "limitations": "The built-in vision track uses Conv2d and does not directly exercise long 1D FFT convolution, so a local custom track was used as required. Wall-clock and peak allocator memory were not measured in this stage-2 run. The failed mechanism signature indicates that the current torch mixed-radix implementation needs correction before interpreting storage or training results.", "bench_report": { "bench_version": 1, "track": "long_1d_convolution", "model": "cnn_small", "metric_direction": "lower is better", "n_seeds": 8, "baseline": { "best_cfg": { "lr": 0.01, "m": 8 }, "sweep": [ { "cfg": { "lr": 0.001, "m": 8 }, "mean": 0.4312499911 }, { "cfg": { "lr": 0.003, "m": 8 }, "mean": 0.4387499914 }, { "cfg": { "lr": 0.01, "m": 8 }, "mean": 0.3587499857 } ], "full": { "mean": 0.3524999917, "std": 0.0277263437, "per_seed": [ 0.4149999917, 0.3599999845, 0.3299999833, 0.3299999833, 0.3449999988, 0.3700000048, 0.3449999988, 0.3249999881 ], "n": 8 } }, "idea": { "mean": 0.4849999845, "std": 0.0338193695, "per_seed": [ 0.4299999774, 0.4399999976, 0.5299999714, 0.5149999857, 0.4899999797, 0.4699999988, 0.5149999857, 0.4899999797 ], "n": 8 }, "comparison": { "delta_mean": 0.1324999928, "idea_wins": 0, "n_pairs": 8, "p_value": 0.0081, "mde": 0.0524563327, "mde_rel_pct": 14.88122949, "verdict": "idea worse (significant)", "system_worked": false }, "mechanism_signature": { "prediction": "implicit convolution equals explicit convolution; tile storage ratio M/(ceil(L/m)*m)", "predicted_relative_operator_error": 0.0, "observed_relative_operator_error": 1.0825973749, "predicted_storage_ratio": 2.0, "trained_system_output_gap": 1.0547434092, "confirmed": false, "custom_track": { "name": "long_1d_convolution", "file": "stage2_bench.py", "domain": "cnn" } } }, "system_verdict": "failed", "practical_verdict": "harms", "mechanism_ok": 0, "system_judged": true }