#!/usr/bin/env python3
"""Run a deterministic shard of the frozen A2b short accuracy grid."""
import argparse
import json
import os
import subprocess
import sys


def main():
    parser = argparse.ArgumentParser()
    parser.add_argument("--selection", default="results/oral_a_apical_selection.json")
    parser.add_argument("--device", default="cuda")
    parser.add_argument("--shard_index", type=int, default=0)
    parser.add_argument("--num_shards", type=int, default=1)
    parser.add_argument("--dry_run", action="store_true")
    args = parser.parse_args()
    if not 0 <= args.shard_index < args.num_shards:
        raise ValueError("invalid shard index")
    with open(args.selection) as handle:
        selection = json.load(handle)
    if selection["status"] != "selected":
        raise ValueError("A2a did not select both vectorizer families")

    common = [
        sys.executable, "experiments/conv_run.py", "--device", args.device,
        "--depth", "20", "--width", "16", "--seed", "0", "--loader_seed", "0",
        "--batch_size", "128", "--epochs", "20", "--train_limit", "10000",
        "--val_examples", "5000", "--split_seed", "2027",
        "--eval_split", "validation", "--eval_every", "0", "--augment_train", "1",
        "--lr_schedule", "cosine", "--warmup_epochs", "0", "--momentum", "0.9",
        "--weight_decay", "1e-4", "--normalization", "batchnorm",
    ]
    jobs = []
    jobs.append(("bp_lr0.1", common + [
        "--mode", "bp", "--lr", "0.1",
        "--out", "results/oral_a_short/bp_lr0.1.json"]))
    for rate in (0.01, 0.03, 0.1):
        jobs.append((f"dfa_lr{rate}", common + [
            "--mode", "dfa", "--lr", str(rate), "--output_lr", "0.1",
            "--a_scale", "1", "--vectorizer_mode", "spatial_template",
            "--out", f"results/oral_a_short/dfa_lr{rate}.json"]))
    for mode in ("spatial_template", "channel_gated"):
        chosen = selection["selected"][mode]
        for rate in (0.01, 0.03, 0.1):
            tag = f"sdil_{mode}_lr{rate}"
            jobs.append((tag, common + [
                "--mode", "sdil", "--lr", str(rate), "--output_lr", "0.1",
                "--vectorizer_mode", mode,
                "--a_scale", str(chosen["a_scale"]),
                "--eta_A", str(chosen["eta_A"]), "--a_warmup_steps", "100",
                "--pert_sigma", "0.01", "--pert_directions", "1",
                "--pert_every", "4", "--alignment_probe", "32",
                "--out", f"results/oral_a_short/{tag}.json"]))
    os.makedirs("results/oral_a_short", exist_ok=True)
    selected_jobs = [job for index, job in enumerate(jobs)
                     if index % args.num_shards == args.shard_index]
    for tag, command in selected_jobs:
        print(tag, " ".join(command), flush=True)
        if not args.dry_run:
            subprocess.run(command, check=True)


if __name__ == "__main__":
    main()