diff options
Diffstat (limited to 'experiments')
| -rwxr-xr-x | experiments/analyze_residual_mirror_full.py | 123 | ||||
| -rwxr-xr-x | experiments/residual_mirror_full_development.py | 52 |
2 files changed, 175 insertions, 0 deletions
diff --git a/experiments/analyze_residual_mirror_full.py b/experiments/analyze_residual_mirror_full.py new file mode 100755 index 0000000..3981d68 --- /dev/null +++ b/experiments/analyze_residual_mirror_full.py @@ -0,0 +1,123 @@ +#!/usr/bin/env python3 +"""Audit and gate the frozen RRM-3 full ResNet-20 validation baseline.""" +import argparse +import json +import math +import os + + +SPLIT_HASH = "8328b206a97c420e49e54e3eca4abe3274c4756b084355784ea3fb8059e4515b" + + +def main(): + parser = argparse.ArgumentParser() + parser.add_argument( + "--selection", default="results/residual_mirror_short_gate.json") + parser.add_argument( + "--bp_selection", default="results/oral_a_bp_selection.json") + parser.add_argument("--input", default="results/residual_mirror_full/rrm.json") + parser.add_argument("--out", default="results/residual_mirror_full_gate.json") + args = parser.parse_args() + with open(args.selection) as handle: + selection = json.load(handle) + if selection.get("protocol") != "residual_response_mirror_short_v1": + raise ValueError("unexpected RRM-2 selection protocol") + if selection.get("status") != "passed": + raise ValueError("RRM-2 did not open RRM-3") + with open(args.input) as handle: + record = json.load(handle) + run_args = record["args"] + expected = { + "mode": "rrm", "depth": 20, "width": 16, "seed": 0, + "loader_seed": 0, "batch_size": 128, "epochs": 200, + "train_limit": 0, "val_examples": 5000, "split_seed": 2027, + "eval_split": "validation", "eval_every": 0, + "augment_train": 1, "lr_schedule": "step", + "lr_milestones": "100,150", "lr_gamma": 0.1, + "warmup_epochs": 0, "momentum": 0.9, "weight_decay": 1e-4, + "normalization": "batchnorm", "lr": 0.1, "output_lr": 0.1, + "a_scale": 1.0, "alignment_probe": 32, + "mirror_warmup_steps": 20, "mirror_every": 16, + "mirror_batch_size": 1, "mirror_eta": 0.1, + "mirror_noise_std": 1.0, "mirror_seed": 3000, + } + for key, value in expected.items(): + if run_args.get(key) != value: + raise ValueError(f"RRM-3 {key} drift") + if float(selection["selected_rrm"]["lr"]) != float(run_args["lr"]): + raise ValueError("RRM-3 did not copy the selected hidden rate") + if record["provenance"]["git_tracked_dirty"]: + raise ValueError("tracked-dirty RRM-3 result") + if record["split"]["validation_index_sha256"] != SPLIT_HASH: + raise ValueError("RRM-3 split drift") + protocol = record["evaluation_protocol"] + if protocol["test_evaluations"] or protocol["test_used_for_selection"]: + raise ValueError("RRM-3 touched test") + if record.get("calibration_metric_space") != ( + "local_parent_child_response_residual"): + raise ValueError("RRM-3 metric-space drift") + + with open(args.bp_selection) as handle: + bp_selection = json.load(handle) + if bp_selection.get("status") != "passed_primary": + raise ValueError("matched full BP reference is not frozen") + with open(bp_selection["selected"]["path"]) as handle: + bp = json.load(handle) + bp_macs = int(bp["work"]["total_macs_estimate"]) + bp_accuracy = float(bp["final"]["accuracy"]) + + accuracy = float(record["final"]["accuracy"]) + loss = float(record["final"]["loss"]) + diagnostics = record["diagnostics"] + early = float(diagnostics["early_third_mean"]) + values = diagnostics["teaching_negative_gradient_cosine"] + all_layer = sum(values) / len(values) + feedback_cosines = diagnostics["feedback_forward_cosine"] + norm_ratios = diagnostics["feedback_forward_norm_ratio"] + finite_values = [ + accuracy, loss, early, all_layer, *feedback_cosines, *norm_ratios] + finite = (bool(record["final"]["finite"]) + and all(math.isfinite(value) for value in finite_values)) + total_macs = int(record["work"]["total_macs_estimate"]) + queries = int(record["work"]["logical_batch_loss_queries"]) + metrics = { + "accuracy": accuracy, "loss": loss, + "early_third_alignment": early, "all_layer_alignment": all_layer, + "mean_feedback_forward_cosine": ( + sum(feedback_cosines) / len(feedback_cosines)), + "min_feedback_forward_norm_ratio": min(norm_ratios), + "max_feedback_forward_norm_ratio": max(norm_ratios), + "finite": finite, "total_macs": total_macs, + "bp_total_macs": bp_macs, "mac_ratio_to_bp": total_macs / bp_macs, + "bp_accuracy": bp_accuracy, "logical_batch_loss_queries": queries, + "mirror_events": int(record["counters"]["mirror_events"]), + "peak_memory_allocated_bytes": int( + record["hardware"]["peak_memory_allocated_bytes"]), + "wall_s": float(record["timing"]["total_timed_wall_s"]), + "source_commit": record["provenance"]["git_commit"], + } + checks = { + "finite": finite, + "accuracy_at_least_0.88": accuracy >= 0.88, + "early_alignment_at_least_0.50": early >= 0.50, + "zero_task_loss_queries": queries == 0, + "macs_at_most_1.15x_bp": total_macs <= 1.15 * bp_macs, + } + status = "passed" if all(checks.values()) else "failed" + output = { + "protocol": "residual_response_mirror_full_v1", + "status": status, "checks": checks, "metrics": metrics, + "innovation_experiment_opened": status == "passed", + "confirmation_test_seeds_touched": False, + "review_score_before": 5, "review_score_after": 5, + "score_change_rule": "inherited full baseline cannot raise score", + } + 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/residual_mirror_full_development.py b/experiments/residual_mirror_full_development.py new file mode 100755 index 0000000..adba032 --- /dev/null +++ b/experiments/residual_mirror_full_development.py @@ -0,0 +1,52 @@ +#!/usr/bin/env python3 +"""Run the single frozen RRM-3 full ResNet-20 validation baseline.""" +import argparse +import json +import os +import subprocess +import sys + + +def main(): + parser = argparse.ArgumentParser() + parser.add_argument( + "--selection", default="results/residual_mirror_short_gate.json") + parser.add_argument("--device", default="cuda") + parser.add_argument("--dry_run", action="store_true") + args = parser.parse_args() + with open(args.selection) as handle: + selection = json.load(handle) + if selection.get("protocol") != "residual_response_mirror_short_v1": + raise ValueError("unexpected RRM-2 selection protocol") + if selection.get("status") != "passed": + raise ValueError("RRM-2 did not open RRM-3") + rate = float(selection["selected_rrm"]["lr"]) + if rate != 0.1: + raise ValueError("RRM-2 selected an unexpected hidden rate") + + command = [ + sys.executable, "experiments/conv_run.py", "--mode", "rrm", + "--device", args.device, "--depth", "20", "--width", "16", + "--seed", "0", "--loader_seed", "0", "--batch_size", "128", + "--epochs", "200", "--train_limit", "0", + "--val_examples", "5000", "--split_seed", "2027", + "--eval_split", "validation", "--eval_every", "0", + "--augment_train", "1", "--lr_schedule", "step", + "--lr_milestones", "100,150", "--lr_gamma", "0.1", + "--warmup_epochs", "0", "--momentum", "0.9", + "--weight_decay", "1e-4", "--normalization", "batchnorm", + "--lr", str(rate), "--output_lr", "0.1", "--a_scale", "1", + "--alignment_probe", "32", "--mirror_warmup_steps", "20", + "--mirror_every", "16", "--mirror_batch_size", "1", + "--mirror_eta", "0.1", "--mirror_noise_std", "1", + "--mirror_seed", "3000", + "--out", "results/residual_mirror_full/rrm.json", + ] + os.makedirs("results/residual_mirror_full", exist_ok=True) + print(" ".join(command), flush=True) + if not args.dry_run: + subprocess.run(command, check=True) + + +if __name__ == "__main__": + main() |