diff options
Diffstat (limited to 'experiments')
| -rw-r--r-- | experiments/analyze_kp_innovation_confirmation.py | 223 | ||||
| -rw-r--r-- | experiments/kp_innovation_confirmation.py | 71 |
2 files changed, 294 insertions, 0 deletions
diff --git a/experiments/analyze_kp_innovation_confirmation.py b/experiments/analyze_kp_innovation_confirmation.py new file mode 100644 index 0000000..adac5dc --- /dev/null +++ b/experiments/analyze_kp_innovation_confirmation.py @@ -0,0 +1,223 @@ +#!/usr/bin/env python3 +"""Audit the untouched MT-3 five-seed mixed-traffic test confirmation.""" +import argparse +import json +import math +import os +import statistics + + +CONDITIONS = ("clean", "raw", "matched", "innovation") +SEEDS = tuple(range(10, 15)) +T_CRITICAL_ONE_SIDED_95_DF4 = 2.131846786 + + +def mean_early(values): + count = max(1, len(values) // 3) + return sum(float(value) for value in values[:count]) / count + + +def lower_confidence_bound(values): + return (statistics.mean(values) + - T_CRITICAL_ONE_SIDED_95_DF4 + * statistics.stdev(values) / math.sqrt(len(values))) + + +def main(): + parser = argparse.ArgumentParser() + parser.add_argument( + "--input_dir", default="results/kp_innovation_confirmation") + parser.add_argument( + "--full_gate", default="results/kp_innovation_full_gate.json") + parser.add_argument( + "--out", default="results/kp_innovation_confirmation_gate.json") + args = parser.parse_args() + with open(args.full_gate) as handle: + full_gate = json.load(handle) + if (full_gate.get("protocol") != "kp_mixed_traffic_full_v1" + or full_gate.get("status") != "passed"): + raise ValueError("MT-2 did not pass") + + common = { + "depth": 20, "width": 16, "batch_size": 128, "epochs": 200, + "train_limit": 0, "val_examples": 0, "split_seed": 2027, + "eval_split": "test", "eval_every": 0, "augment_train": 1, + "lr": 0.1, "output_lr": 0.1, "lr_schedule": "step", + "lr_milestones": "100,150", "lr_gamma": 0.1, + "warmup_epochs": 0, "momentum": 0.9, "weight_decay": 1e-4, + "normalization": "batchnorm", "a_scale": 1.0, + "alignment_probe": 32, + } + traffic = { + "traffic_ratio": 4.0, "traffic_calibration_examples": 64, + "learn_P": 1, "eta_P": 0.1, "predictor_warmup_steps": 20, + "predictor_every": 16, + } + records = {} + source_commits = set() + for seed in SEEDS: + for condition in CONDITIONS: + path = os.path.join( + args.input_dir, f"seed{seed}_{condition}.json") + with open(path) as handle: + record = json.load(handle) + records[(seed, condition)] = record + expected = {**common, "seed": seed, "loader_seed": seed, + "mode": "kp" if condition == "clean" else "kp_traffic"} + if condition != "clean": + expected.update(traffic) + expected.update({"traffic_rule": condition, + "traffic_seed": 5000 + seed}) + for key, value in expected.items(): + if record["args"].get(key) != value: + raise ValueError( + f"MT-3 seed {seed} {condition} {key} drift") + if record["provenance"]["git_tracked_dirty"]: + raise ValueError( + f"tracked-dirty MT-3 seed {seed} {condition}") + source_commits.add(record["provenance"]["git_commit"]) + split = record["split"] + if not (split["validation_examples"] == 0 + and split["validation_index_sha256"] is None + and split["train_examples"] == 50000 + and split["test_examples"] == 10000): + raise ValueError( + f"MT-3 seed {seed} {condition} split drift") + evaluation = record["evaluation_protocol"] + if not (evaluation["validation_evaluations"] == 0 + and evaluation["test_evaluations"] == 1 + and not evaluation["test_used_for_selection"]): + raise ValueError( + f"MT-3 seed {seed} {condition} evaluation drift") + if len(source_commits) != 1: + raise ValueError("all MT-3 runs must share one source revision") + + accuracies = { + condition: [float(records[(seed, condition)]["final"]["accuracy"]) + for seed in SEEDS] + for condition in CONDITIONS + } + raw_gains = [innovation - raw for innovation, raw in zip( + accuracies["innovation"], accuracies["raw"])] + matched_gains = [innovation - matched for innovation, matched in zip( + accuracies["innovation"], accuracies["matched"])] + clean_deficits = [clean - innovation for clean, innovation in zip( + accuracies["clean"], accuracies["innovation"])] + + finite_values = [] + invariant_failures = [] + bp_macs_50k = int( + full_gate["metrics"]["total_macs"]["innovation"] + / full_gate["metrics"]["mac_ratio_to_bp"]["innovation"] + * (50_000 / 45_000)) + for seed in SEEDS: + for condition in CONDITIONS: + record = records[(seed, condition)] + if not record["final"]["finite"]: + invariant_failures.append(f"seed{seed}_{condition}:nonfinite") + finite_values.extend([ + float(record["final"]["accuracy"]), + float(record["final"]["loss"]), + ]) + if int(record["work"]["logical_batch_loss_queries"]) != 0: + invariant_failures.append(f"seed{seed}_{condition}:queries") + if int(record["work"]["total_macs_estimate"]) > 1.40 * bp_macs_50k: + invariant_failures.append(f"seed{seed}_{condition}:cost") + trajectory = record["epochs"] + if len(trajectory) != 200: + invariant_failures.append(f"seed{seed}_{condition}:trajectory") + continue + finite_values.extend(float(row["train_loss"]) for row in trajectory) + tracking = [row.get("feedback_tracking") for row in trajectory] + if any(value is None for value in tracking): + invariant_failures.append(f"seed{seed}_{condition}:tracking") + continue + final_cosine = float( + record["diagnostics"]["mean_feedback_forward_cosine"]) + late_cosine = statistics.mean(float( + value["mean_feedback_forward_cosine"]) for value in tracking[150:]) + if final_cosine < 0.95 or late_cosine < 0.95: + invariant_failures.append(f"seed{seed}_{condition}:kp_tracking") + if condition != "clean": + ratios = record["traffic_calibration"][ + "realized_traffic_instruction_rms_ratio"] + if max(abs(float(value) - 4.0) for value in ratios) > 1e-5: + invariant_failures.append(f"seed{seed}_{condition}:ratio") + diagnostics = record["diagnostics"] + if float(diagnostics[ + "predictor_traffic_residual_rms_ratio"]) > 0.05: + invariant_failures.append(f"seed{seed}_{condition}:predictor") + if condition == "matched" and float(diagnostics[ + "max_norm_match_relative_error"]) > 1e-6: + invariant_failures.append(f"seed{seed}_{condition}:norm") + if int(record["work"][ + "elementwise_operations_estimate"]) <= 0: + invariant_failures.append(f"seed{seed}_{condition}:elementwise") + if condition == "innovation": + diagnostics = record["diagnostics"] + used_early = float(diagnostics["early_third_mean"]) + raw_early = mean_early( + diagnostics["raw_negative_gradient_cosine"]) + if used_early < 0.80 or used_early - raw_early < 0.15: + invariant_failures.append(f"seed{seed}:alignment") + + all_finite = all(math.isfinite(value) for value in finite_values) + checks = { + "all_records_trajectories_and_metrics_finite": all_finite, + "mean_innovation_accuracy_at_least_0.88": ( + statistics.mean(accuracies["innovation"]) >= 0.88), + "mean_paired_deficit_to_clean_at_most_0.03": ( + statistics.mean(clean_deficits) <= 0.03), + "mean_gain_over_raw_at_least_0.05": ( + statistics.mean(raw_gains) >= 0.05), + "mean_gain_over_matched_at_least_0.03": ( + statistics.mean(matched_gains) >= 0.03), + "raw_gain_one_sided_95pct_lower_bound_above_zero": ( + lower_confidence_bound(raw_gains) > 0.0), + "matched_gain_one_sided_95pct_lower_bound_above_zero": ( + lower_confidence_bound(matched_gains) > 0.0), + "at_least_four_positive_raw_gains": ( + sum(value > 0 for value in raw_gains) >= 4), + "at_least_four_positive_matched_gains": ( + sum(value > 0 for value in matched_gains) >= 4), + "all_mechanism_query_tracking_and_cost_invariants": ( + not invariant_failures), + } + status = "passed" if all(checks.values()) else "failed" + output = { + "protocol": "kp_mixed_traffic_confirmation_v1", "status": status, + "checks": checks, + "metrics": { + "accuracy_by_seed": accuracies, + "mean_accuracy": {condition: statistics.mean(values) + for condition, values in accuracies.items()}, + "paired_clean_deficit": clean_deficits, + "paired_gain_over_raw": raw_gains, + "paired_gain_over_matched": matched_gains, + "mean_clean_deficit": statistics.mean(clean_deficits), + "mean_gain_over_raw": statistics.mean(raw_gains), + "mean_gain_over_matched": statistics.mean(matched_gains), + "raw_gain_one_sided_95pct_lower_bound": ( + lower_confidence_bound(raw_gains)), + "matched_gain_one_sided_95pct_lower_bound": ( + lower_confidence_bound(matched_gains)), + "bp_50k_mac_reference": bp_macs_50k, + "invariant_failures": invariant_failures, + "source_commit": next(iter(source_commits)), + }, + "test_evaluations": 20, + "review_score_before": 5, + "review_score_after": 6 if status == "passed" else 5, + "score_change_rule": ( + "only a complete untouched five-seed innovation confirmation " + "establishes the weak-accept bar"), + } + os.makedirs(os.path.dirname(os.path.abspath(args.out)), exist_ok=True) + with open(args.out, "w") as handle: + json.dump(output, handle, indent=2, sort_keys=True) + handle.write("\n") + print(json.dumps(output, indent=2)) + + +if __name__ == "__main__": + main() diff --git a/experiments/kp_innovation_confirmation.py b/experiments/kp_innovation_confirmation.py new file mode 100644 index 0000000..4ba2dd3 --- /dev/null +++ b/experiments/kp_innovation_confirmation.py @@ -0,0 +1,71 @@ +#!/usr/bin/env python3 +"""Run the untouched MT-3 clean/raw/matched/innovation test panel.""" +import argparse +import json +import os +import subprocess +import sys + + +CONDITIONS = ("clean", "raw", "matched", "innovation") +SEEDS = tuple(range(10, 15)) + + +def main(): + parser = argparse.ArgumentParser() + parser.add_argument( + "--full_gate", default="results/kp_innovation_full_gate.json") + parser.add_argument("--condition", choices=("all",) + CONDITIONS, + default="all") + parser.add_argument("--seed", type=int, choices=SEEDS) + parser.add_argument("--device", default="cuda") + parser.add_argument("--dry_run", action="store_true") + args = parser.parse_args() + with open(args.full_gate) as handle: + gate = json.load(handle) + if (gate.get("protocol") != "kp_mixed_traffic_full_v1" + or gate.get("status") != "passed"): + raise ValueError("MT-2 did not open MT-3") + + conditions = CONDITIONS if args.condition == "all" else (args.condition,) + seeds = SEEDS if args.seed is None else (args.seed,) + os.makedirs("results/kp_innovation_confirmation", exist_ok=True) + for seed in seeds: + for condition in conditions: + command = [ + sys.executable, "experiments/conv_run.py", + "--mode", "kp" if condition == "clean" else "kp_traffic", + ] + if condition != "clean": + command.extend([ + "--traffic_rule", condition, + "--traffic_seed", str(5000 + seed), + "--traffic_ratio", "4", + "--traffic_calibration_examples", "64", + "--learn_P", "1", "--eta_P", "0.1", + "--predictor_warmup_steps", "20", + "--predictor_every", "16", + ]) + command.extend([ + "--device", args.device, "--depth", "20", "--width", "16", + "--seed", str(seed), "--loader_seed", str(seed), + "--batch_size", "128", "--epochs", "200", + "--train_limit", "0", "--val_examples", "0", + "--split_seed", "2027", "--eval_split", "test", + "--eval_every", "0", "--augment_train", "1", + "--lr", "0.1", "--output_lr", "0.1", + "--lr_schedule", "step", "--lr_milestones", "100,150", + "--lr_gamma", "0.1", "--warmup_epochs", "0", + "--momentum", "0.9", "--weight_decay", "1e-4", + "--normalization", "batchnorm", "--a_scale", "1", + "--alignment_probe", "32", + "--out", ("results/kp_innovation_confirmation/" + f"seed{seed}_{condition}.json"), + ]) + print(" ".join(command), flush=True) + if not args.dry_run: + subprocess.run(command, check=True) + + +if __name__ == "__main__": + main() |