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

(универсальный)

Ответ агента:

{
  "worked": false,
  "confidence": 9,
  "verdict": "Implemented a matched sequence-level benchmark: dense learned token mixing versus a trainable orthogonal butterfly mixer with identical encoder structure, optimizer, learning-rate grid, and eight paired seeds. The mechanism signature was confirmed at neural-network scale (norm ratio 1.0 and inverse error 1.19e-6), but the idea had worse test MSE (0.598316 versus 0.476622), paired delta +0.121694, and permutation p=0.1299, so there was no significant win.",
  "metrics": {
    "baseline": "Best dense token mixer, lr=0.001, epochs=6: test MSE mean 0.476622, std 0.099342 over 8 seeds.",
    "idea": "Best isometric butterfly, lr=0.001, epochs=6: test MSE mean 0.598316, std 0.165879 over 8 seeds; paired delta +0.121694, p=0.1299, 2/8 wins.",
    "mechanism_signature": "confirmed=true; predicted norm ratio 1.0, observed trained-model ratio 1.0, observed adjoint inverse max error 1.19e-6; baseline observed norm ratio 0.502587."
  },
  "bench_report": {
    "bench_version": 1,
    "track": "sequence",
    "model": "transformer_tiny",
    "metric_direction": "lower is better",
    "n_seeds": 8,
    "baseline": {
      "best_cfg": {
        "lr": 0.001,
        "epochs": 6,
        "weight_decay": 0.0
      },
      "sweep": [
        {
          "cfg": {
            "lr": 0.001,
            "epochs": 6,
            "weight_decay": 0.0
          },
          "mean": 0.46786613017320633
        },
        {
          "cfg": {
            "lr": 0.003,
            "epochs": 6,
            "weight_decay": 0.0
          },
          "mean": 0.5299046412110329
        },
        {
          "cfg": {
            "lr": 0.006,
            "epochs": 6,
            "weight_decay": 0.0
          },
          "mean": 0.7419369965791702
        }
      ],
      "full": {
        "mean": 0.4766220450401306,
        "std": 0.09934194575564281,
        "per_seed": [
          0.5715442299842834,
          0.39496564865112305,
          0.3930272161960602,
          0.5119274258613586,
          0.4745565354824066,
          0.4187285602092743,
          0.6776894927024841,
          0.37053725123405457
        ],
        "n": 8
      }
    },
    "idea": {
      "mean": 0.5983163416385651,
      "std": 0.16587939812424876,
      "per_seed": [
        0.3822963237762451,
        0.5229498744010925,
        0.8081433773040771,
        0.863442063331604,
        0.6520702838897705,
        0.45361945033073425,
        0.6645830869674683,
        0.4394262731075287
      ],
      "n": 8
    },
    "comparison": {
      "delta_mean": 0.12169429659843445,
      "idea_wins": 2,
      "n_pairs": 8,
      "per_seed_diffs": [
        -0.18924790620803833,
        0.12798422574996948,
        0.41511616110801697,
        0.35151463747024536,
        0.1775137484073639,
        0.03489089012145996,
        -0.01310640573501587,
        0.06888902187347412
      ],
      "p_value": 0.1299,
      "mde": 0.16337849985483555,
      "mde_rel_pct": 34.27841862435872,
      "verdict": "no significant win",
      "system_worked": false
    },
    "mechanism_signature": {
      "prediction": "trained isometric token mixer preserves feature-token Euclidean norm and has exact adjoint inverse",
      "predicted_norm_ratio": 1.0,
      "observed_norm_ratio_seed0": 1.0,
      "observed_inverse_max_error_seed0": 1.1920928955078125e-06,
      "baseline_observed_norm_ratio_seed0": 0.5025865435600281,
      "confirmed": true,
      "trained_model_metric_seed0": 0.3822963237762451
    }
  },
  "how_to_run": "/home/maxwelhelp/main/bin/python3 stage2_bench.py",
  "files": [
    "isometric_mixer.py",
    "stage2_bench.py",
    "bench_report.json"
  ],
  "limitations": "Only the built-in sequence forecast track was tested; CIFAR vision, tabular, and dynamics tracks were not tested. The implementation uses a real orthogonal butterfly specialization rather than full complex U(2) QFT phases, and no reliable wall-clock or FLOP speedup measurement was included.",
  "system_verdict": "partial",
  "practical_verdict": "inconclusive",
  "mechanism_ok": 1,
  "system_judged": true
}