diff options
Diffstat (limited to 'experiments')
| -rwxr-xr-x | experiments/analyze_kp_short.py | 126 | ||||
| -rwxr-xr-x | experiments/kp_short_development.py | 36 |
2 files changed, 162 insertions, 0 deletions
diff --git a/experiments/analyze_kp_short.py b/experiments/analyze_kp_short.py new file mode 100755 index 0000000..76d86e6 --- /dev/null +++ b/experiments/analyze_kp_short.py @@ -0,0 +1,126 @@ +#!/usr/bin/env python3 +"""Audit and gate the frozen KP-1 ResNet-20 development record.""" +import argparse +import json +import math +import os + + +SPLIT_HASH = "8328b206a97c420e49e54e3eca4abe3274c4756b084355784ea3fb8059e4515b" +BP_EPOCH20_ACCURACY = 0.8102 +BP_EPOCH20_MACS = 109_487_808_000_000 + + +def main(): + parser = argparse.ArgumentParser() + parser.add_argument("--input", default="results/kp_short/kp.json") + parser.add_argument( + "--bp", default="results/oral_a_dev/bp_reference_primary.json") + parser.add_argument("--out", default="results/kp_short_gate.json") + args = parser.parse_args() + with open(args.input) as handle: + record = json.load(handle) + run_args = record["args"] + expected = { + "mode": "kp", "depth": 20, "width": 16, "seed": 0, + "loader_seed": 0, "batch_size": 128, "epochs": 20, + "train_limit": 0, "val_examples": 5000, "split_seed": 2027, + "eval_split": "validation", "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, + } + for key, value in expected.items(): + if run_args.get(key) != value: + raise ValueError(f"KP-1 {key} drift") + if record["provenance"]["git_tracked_dirty"]: + raise ValueError("tracked-dirty KP-1 result") + if record["split"]["validation_index_sha256"] != SPLIT_HASH: + raise ValueError("KP-1 split drift") + protocol = record["evaluation_protocol"] + if protocol["test_evaluations"] or protocol["test_used_for_selection"]: + raise ValueError("KP-1 touched test") + if record.get("calibration_metric_space") != ( + "reciprocal_local_activity_products"): + raise ValueError("KP-1 metric-space drift") + + with open(args.bp) as handle: + bp = json.load(handle) + bp_epoch20 = [row for row in bp["epochs"] if row["epoch"] == 20] + if (len(bp_epoch20) != 1 + or float(bp_epoch20[0]["eval_accuracy"]) != BP_EPOCH20_ACCURACY): + raise ValueError("matched BP epoch-20 endpoint drift") + if int(bp["work"]["total_macs_estimate"]) // 10 != BP_EPOCH20_MACS: + raise ValueError("matched BP epoch-20 MAC reference drift") + + epoch_tracking = [row.get("feedback_tracking") for row in record["epochs"]] + if len(epoch_tracking) != 20 or any(value is None for value in epoch_tracking): + raise ValueError("KP-1 tracking trajectory is incomplete") + trajectory_values = [] + for row, tracking in zip(record["epochs"], epoch_tracking): + trajectory_values.extend([ + float(row["train_loss"]), + float(tracking["mean_feedback_forward_cosine"]), + float(tracking["mean_feedback_forward_relative_error"]), + float(tracking["min_feedback_forward_cosine"]), + float(tracking["max_feedback_forward_relative_error"]), + ]) + diagnostics = record["diagnostics"] + accuracy = float(record["final"]["accuracy"]) + loss = float(record["final"]["loss"]) + early = float(diagnostics["early_third_mean"]) + final_cosine = float(diagnostics["mean_feedback_forward_cosine"]) + late_cosine = sum(float(value["mean_feedback_forward_cosine"]) + for value in epoch_tracking[10:]) / 10 + total_macs = int(record["work"]["total_macs_estimate"]) + queries = int(record["work"]["logical_batch_loss_queries"]) + finite = (bool(record["final"]["finite"]) + and all(math.isfinite(value) for value in + trajectory_values + [accuracy, loss, early, final_cosine])) + checks = { + "record_and_trajectory_finite": finite, + "accuracy_at_least_0.70": accuracy >= 0.70, + "within_15_points_of_bp_epoch20": ( + accuracy >= BP_EPOCH20_ACCURACY - 0.15), + "early_alignment_at_least_0.50": early >= 0.50, + "final_feedback_cosine_at_least_0.80": final_cosine >= 0.80, + "epoch11_to20_feedback_cosine_at_least_0.70": late_cosine >= 0.70, + "zero_task_loss_queries": queries == 0, + "macs_at_most_1.40x_bp": total_macs <= 1.40 * BP_EPOCH20_MACS, + } + status = "passed" if all(checks.values()) else "failed" + metrics = { + "accuracy": accuracy, "loss": loss, + "bp_epoch20_accuracy": BP_EPOCH20_ACCURACY, + "early_third_alignment": early, + "final_mean_feedback_forward_cosine": final_cosine, + "epoch11_to20_mean_feedback_forward_cosine": late_cosine, + "final_mean_feedback_forward_relative_error": float( + diagnostics["mean_feedback_forward_relative_error"]), + "total_macs": total_macs, "bp_epoch20_total_macs": BP_EPOCH20_MACS, + "mac_ratio_to_bp": total_macs / BP_EPOCH20_MACS, + "logical_batch_loss_queries": queries, + "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"], + } + output = { + "protocol": "kolen_pollack_short_v1", "status": status, + "checks": checks, "metrics": metrics, + "full_validation_opened": status == "passed", + "confirmation_test_seeds_touched": False, + "review_score_before": 5, "review_score_after": 5, + "score_change_rule": "inherited KP 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/kp_short_development.py b/experiments/kp_short_development.py new file mode 100755 index 0000000..deefb59 --- /dev/null +++ b/experiments/kp_short_development.py @@ -0,0 +1,36 @@ +#!/usr/bin/env python3 +"""Run the single frozen KP-1 ResNet-20 development record.""" +import argparse +import os +import subprocess +import sys + + +def main(): + parser = argparse.ArgumentParser() + parser.add_argument("--device", default="cuda") + parser.add_argument("--dry_run", action="store_true") + args = parser.parse_args() + command = [ + sys.executable, "experiments/conv_run.py", "--mode", "kp", + "--device", args.device, "--depth", "20", "--width", "16", + "--seed", "0", "--loader_seed", "0", "--batch_size", "128", + "--epochs", "20", "--train_limit", "0", + "--val_examples", "5000", "--split_seed", "2027", + "--eval_split", "validation", "--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_short/kp.json", + ] + os.makedirs("results/kp_short", exist_ok=True) + print(" ".join(command), flush=True) + if not args.dry_run: + subprocess.run(command, check=True) + + +if __name__ == "__main__": + main() |