#!/usr/bin/env python3
"""Run the single frozen HFA-S2 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/oral_a_hfa_short_selection.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") != "convolutional_hfa_S1_v1":
        raise ValueError("unexpected HFA-S1 selection protocol")
    if selection.get("status") != "selected_full_open":
        raise ValueError("HFA-S1 full-validation gate did not pass")
    rate = float(selection["selected"]["lr"])
    if rate not in (0.01, 0.03, 0.1):
        raise ValueError("selected HFA learning rate left the frozen grid")

    command = [
        sys.executable, "experiments/conv_run.py", "--mode", "hfa",
        "--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",
        "--out", "results/oral_a_hfa_full/hfa.json",
    ]
    os.makedirs("results/oral_a_hfa_full", exist_ok=True)
    print(" ".join(command), flush=True)
    if not args.dry_run:
        subprocess.run(command, check=True)


if __name__ == "__main__":
    main()