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

(универсальный)

Ответ агента:

{ "worked": false, "confidence": 9, "verdict": "Implemented exact Hadamard energy-preserving activation normalization in a matched CNN system and ran the full 8-seed vision benchmark with a shared learning-rate union and baseline sweep. The mechanism prediction was confirmed on trained models: exact relative energy RMSE was 5.17e-8 versus random-estimator relative standard deviation 0.3648. Test error was slightly worse for the idea (0.78718749 vs 0.78499998), with paired delta +0.00218751 and permutation p=0.64985, so there was no benchmark win.", "metrics": { "baseline": "vision/cnn_small, best lr=0.001, test error mean 0.78499998; per-seed [0.78750, 0.75000, 0.83500, 0.77250, 0.82750, 0.81750, 0.72500, 0.76500]", "idea": "Exact Hadamard normalization, best lr=0.001, test error mean 0.78718749; per-seed [0.79000, 0.77000, 0.84000, 0.76250, 0.82500, 0.80750, 0.74750, 0.75500]" }, "bench_report": { "bench_version": 1, "track": "vision", "model": "cnn_small", "metric_direction": "lower is better", "n_seeds": 8, "baseline": { "best_cfg": { "lr": 0.001 }, "sweep": [ { "cfg": { "lr": 0.001 }, "mean": 0.78624998 }, { "cfg": { "lr": 0.003 }, "mean": 0.80062498 }, { "cfg": { "lr": 0.006 }, "mean": 0.82375 } ], "full": { "mean": 0.78499998, "std": 0.0366572, "per_seed": [ 0.78749996, 0.75, 0.83499998, 0.77249998, 0.82749999, 0.8175, 0.72499996, 0.76499999 ], "n": 8 } }, "idea": { "lr": 0.001, "mean": 0.78718749, "per_seed": [ 0.78999996, 0.76999998, 0.83999997, 0.76249999, 0.82499999, 0.8075, 0.7475, 0.755 ], "grid": [ { "lr": 0.001, "mean": 0.78718749 }, { "lr": 0.003, "mean": 0.78937498 }, { "lr": 0.006, "mean": 0.82718748 } ] }, "comparison": { "delta_mean": 0.00218751, "idea_wins": 4, "n_pairs": 8, "p_value": 0.64985, "verdict": "no measurable effect", "system_worked": false }, "math_check": { "matrix_frobenius_residual": 0.0, "max_abs_energy_error": 1.42e-14, "relative_energy_rmse": 1.5e-16, "random_relative_rmse": 0.32222905, "random_mean_relative_std": 0.32083649 }, "mechanism_signature": { "predicted_exact_relative_rmse": 0.0, "observed_mean_exact_relative_rmse": 5.17e-08, "observed_mean_random_relative_std": 0.36475653, "confirmed": true } }, "how_to_run": "/home/maxwelhelp/main/bin/python3 bench_experiment.py", "files": [ "bench_experiment.py", "bench_report.json" ], "limitations": "Only the structurally matched vision track was tested, using 1000 training and 400 test CIFAR-10 examples, 8 epochs, and N=16 evaluations rather than the proposed 16-of-256 projection/complement setting. Wall-clock activation-memory savings, importance sampling, learned projections, mixed precision, and larger datasets were not benchmarked.", "system_verdict": "partial", "practical_verdict": "no_effect", "mechanism_ok": 1, "system_judged": true }