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#!/usr/bin/env python3
"""Run the frozen D2 short dynamic-projection validation 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(
"--d1_gate", default="results/kp_dynamic_projection_gate.json")
parser.add_argument(
"--out", default="results/kp_dynamic_projection_short/dynamic.json")
args = parser.parse_args()
with open(args.d1_gate) as handle:
gate = json.load(handle)
if (gate.get("protocol") !=
"kp_dynamic_neutral_projection_training_prefix_v1"
or gate.get("status") != "passed"):
raise ValueError("D2 requires the audited D1 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", "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",
"--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()
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