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

(универсальный)

Ответ агента:

{ "worked": false, "confidence": 9, "verdict": "Built a structurally matched vision benchmark for partial re-noising CNN architecture mutation, using the same CNN task, paired seeds, shared learning-rate grid, and equal training budget for baseline and idea. The trained models showed the predicted decrease in parent-operation retention with mutation strength, with maximum observed-vs-predicted error 0.075 and confirmed=true. However, the best idea configuration had higher classification error than the tuned baseline (0.86875 vs 0.86750), with paired delta +0.00125 and permutation p=0.9195; therefore there is no measured benchmark improvement.", "metrics": { "baseline": "Tuned cnn_small, best lr=0.003: mean CIFAR-10 subset classification error 0.86750, std 0.02905, 8 paired seeds.", "idea": "PartialReNoiseCNN, best gamma=0.05 and lr=0.001: mean classification error 0.86875, std 0.03407, 8 paired seeds; paired delta idea-baseline +0.00125, p=0.9195.", "mechanism_signature": "Predicted parent-operation retention [0.9900, 0.9259, 0.7420, 0.0309] for gamma [0.05,0.15,0.30,1.0]; observed trained-model retention [1.0000,1.0000,0.6667,0.0000], maximum absolute error 0.07535, confirmed=true." }, "how_to_run": "/home/maxwelhelp/main/bin/python3 bench_partial_renoise.py", "files": [ "bench_partial_renoise.py", "bench_report.json" ], "limitations": "The benchmark used a fast CIFAR-10 subset of 400 training and 100 test examples and 2 epochs after the larger run exceeded 2400 seconds; it is therefore a limited transfer test rather than a full NAS-Bench-201 search. The reverse diffusion model was represented by a minimal shape-compatible stochastic convolution mutation, not a learned discrete diffusion model, and no architecture archive, latency checker, parameter-budget search, or validation-accuracy NAS loop was tested.", "bench_report": { "bench_version": 1, "track": "vision", "model": "cnn_small", "metric_direction": "lower is better", "n_seeds": 8, "baseline": { "best_cfg": { "lr": 0.003 }, "sweep": [ { "cfg": { "lr": 0.001 }, "mean": 0.8862499818205833 }, { "cfg": { "lr": 0.003 }, "mean": 0.867499977350235 }, { "cfg": { "lr": 0.006 }, "mean": 0.867499977350235 } ], "full": { "mean": 0.867499977350235, "std": 0.029047373044579175, "per_seed": [ 0.9099999666213989, 0.8700000047683716, 0.8899999856948853, 0.8399999737739563, 0.85999995470047, 0.8999999761581421, 0.8499999642372131, 0.8199999928474426 ], "n": 8 } }, "idea": { "mean": 0.8687499910593033, "std": 0.03407253705893027, "per_seed": [ 0.8899999856948853, 0.8299999833106995, 0.8600000143051147, 0.8999999761581421, 0.8199999928474426, 0.8399999737739563, 0.9200000166893005, 0.8899999856948853 ], "n": 8, "config": { "gamma": 0.05, "lr": 0.001, "baseline_best_lr": 0.003 } }, "comparison": { "delta_mean": 0.0012500137090682983, "idea_wins": 5, "n_pairs": 8, "per_seed_diffs": [ -0.019999980926513672, -0.04000002145767212, -0.029999971389770508, 0.06000000238418579, -0.039999961853027344, -0.06000000238418579, 0.0700000524520874, 0.06999999284744263 ], "p_value": 0.9195, "mde": 0.04632656557948158, "mde_rel_pct": 5.340238246574409, "verdict": "no measurable effect", "system_worked": false }, "mechanism_signature": { "prediction": "parent-operation retention decreases monotonically with gamma according to alpha_bar", "trained_model_measurements": [ { "gamma": 0.05, "predicted_retention": 0.99, "observed_retention": 1.0, "absolute_error": 0.010000000000000009 }, { "gamma": 0.15, "predicted_retention": 0.9258820055401662, "observed_retention": 1.0, "absolute_error": 0.0741179944598338 }, { "gamma": 0.3, "predicted_retention": 0.7420133348094462, "observed_retention": 0.6666666666666666, "absolute_error": 0.07534666814277957 }, { "gamma": 1.0, "predicted_retention": 0.030871261192240654, "observed_retention": 0.0, "absolute_error": 0.030871261192240654 } ], "confirmed": true }, "protocol_notes": { "structural_match": "vision CNN architecture mutation", "paired_seeds": [ 0, 1, 2, 3, 4, 5, 6, 7 ], "baseline_grid": [ 0.001, 0.003, 0.006 ], "idea_grid": [ 0.001, 0.003, 0.006 ], "epochs": 2, "metric": "classification error, lower is better" } }, "system_verdict": "partial", "practical_verdict": "no_effect", "mechanism_ok": 1, "system_judged": true }