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4687353 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 | from __future__ import annotations
import argparse
import json
import os
import subprocess
import sys
import time
from pathlib import Path
from typing import Any, Dict, List
import yaml
REPO_ROOT = Path(__file__).resolve().parents[1]
def log(message: str) -> None:
ts = time.strftime("%Y-%m-%d %H:%M:%S")
print(f"[{ts}] [run_baselines] {message}", flush=True)
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser(description="Run Baseline A/B/C experiments.")
parser.add_argument("--mode", choices=["smoke", "full"], default="smoke")
parser.add_argument(
"--experiment-config",
type=Path,
default=REPO_ROOT / "configs" / "experiment.yaml",
)
parser.add_argument("--dataset-config", type=Path, default=REPO_ROOT / "configs" / "dataset.yaml")
parser.add_argument("--model-config", type=Path, default=REPO_ROOT / "configs" / "model.yaml")
parser.add_argument("--train-config", type=Path, default=REPO_ROOT / "configs" / "train.yaml")
parser.add_argument("--eval-config", type=Path, default=REPO_ROOT / "configs" / "eval.yaml")
return parser.parse_args()
def load_yaml(path: Path) -> Dict[str, Any]:
with path.open("r", encoding="utf-8") as handle:
payload = yaml.safe_load(handle)
return payload or {}
def run_train(
mode: str,
run_name: str,
overrides: Dict[str, Any],
dataset_config: Path,
model_config: Path,
train_config: Path,
eval_config: Path,
) -> None:
cmd: List[str] = [
sys.executable,
str(REPO_ROOT / "scripts" / "train_baseline.py"),
"--run-name",
run_name,
"--mode",
mode,
"--dataset-config",
str(dataset_config),
"--model-config",
str(model_config),
"--train-config",
str(train_config),
"--eval-config",
str(eval_config),
"--overrides-json",
json.dumps(overrides),
]
env = dict(**os.environ)
env["PYTHONUNBUFFERED"] = "1"
cmd.insert(1, "-u")
log(f"Launching run '{run_name}' in mode='{mode}'")
log(f"Python executable: {sys.executable}")
log(f"Overrides: {json.dumps(overrides)}")
log(f"Command: {' '.join(cmd)}")
started = time.time()
completed = subprocess.run(cmd, check=False, cwd=REPO_ROOT, env=env)
elapsed = time.time() - started
log(f"Run '{run_name}' exited with code={completed.returncode} after {elapsed:.1f}s")
if completed.returncode != 0:
raise RuntimeError(f"Baseline run failed: {run_name}")
def main() -> None:
args = parse_args()
log("Starting baseline orchestrator")
log(f"Repo root: {REPO_ROOT}")
log(f"Mode: {args.mode}")
log(f"Experiment config: {args.experiment_config}")
experiment_cfg = load_yaml(args.experiment_config)
baseline_runs = experiment_cfg.get("baseline_runs", [])
if not baseline_runs:
raise RuntimeError("No baseline_runs found in experiment config.")
log(f"Discovered {len(baseline_runs)} baseline runs")
output_dir = REPO_ROOT / "outputs"
output_dir.mkdir(parents=True, exist_ok=True)
comparison: Dict[str, Any] = {"mode": args.mode, "runs": []}
for row in baseline_runs:
run_name = f"{row['name']}_{args.mode}"
overrides = row.get("overrides", {})
log(f"Preparing run: {run_name}")
run_train(
mode=args.mode,
run_name=run_name,
overrides=overrides,
dataset_config=args.dataset_config,
model_config=args.model_config,
train_config=args.train_config,
eval_config=args.eval_config,
)
metrics_path = output_dir / run_name / "metrics.json"
log(f"Reading metrics from: {metrics_path}")
with metrics_path.open("r", encoding="utf-8") as handle:
metrics = json.load(handle)
comparison["runs"].append(
{
"run_name": run_name,
"test_map": metrics.get("test_metrics", {}).get("map"),
"test_macro_f1": metrics.get("test_metrics", {}).get("macro_f1"),
"test_micro_f1": metrics.get("test_metrics", {}).get("micro_f1"),
}
)
comparison_path = output_dir / f"baseline_comparison_{args.mode}.json"
with comparison_path.open("w", encoding="utf-8") as handle:
json.dump(comparison, handle, indent=2, ensure_ascii=True)
log(f"Wrote comparison report: {comparison_path}")
if __name__ == "__main__":
main()
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