#!/usr/bin/env python3 """Run the conditionally frozen D3 full dynamic-projection endpoint.""" import argparse import json 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") parser.add_argument( "--d2_gate", default="results/kp_dynamic_projection_short_gate.json") parser.add_argument( "--out", default="results/kp_dynamic_projection_full/dynamic.json") args = parser.parse_args() with open(args.d2_gate) as handle: gate = json.load(handle) if (gate.get("protocol") != "kp_dynamic_neutral_projection_short_v1" or gate.get("status") != "passed" or gate.get("full_validation_opened") is not True): raise ValueError("D3 requires the audited D2 pass") command = [ sys.executable, "experiments/conv_run.py", "--mode", "kp_traffic", "--traffic_rule", "innovation", "--predictor_mode", "closed_form", "--neutral_projection", "1", "--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", "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", "--traffic_seed", "4000", "--traffic_ratio", "4", "--traffic_calibration_examples", "64", "--learn_P", "1", "--eta_P", "0.1", "--predictor_warmup_steps", "1", "--predictor_every", "0", "--alignment_probe", "32", "--out", args.out, ] print(" ".join(command), flush=True) if not args.dry_run: os.makedirs(os.path.dirname(os.path.abspath(args.out)), exist_ok=True) subprocess.run(command, check=True) if __name__ == "__main__": main()