79f3de05f7
modified: checkpoints_final/task1_final/task1_final_model.pkl new file: checkpoints_final/task1_final/task1_tmd_adapter.pkl new file: scripts_4/README.md new file: scripts_4/__init__.py new file: scripts_4/__pycache__/adapter.cpython-314.pyc new file: scripts_4/adapter.py new file: scripts_4/predict_tmd_single.py new file: scripts_4/train_tmd_adapter.py
79 lines
2.9 KiB
Python
79 lines
2.9 KiB
Python
from __future__ import annotations
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import argparse
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import importlib.util
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import pickle
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from pathlib import Path
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import sys
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PROJECT_ROOT = Path(__file__).resolve().parents[1]
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try:
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from .adapter import load_adapter
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except ImportError:
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from adapter import load_adapter
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def _load_module(module_name: str, file_path: Path):
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spec = importlib.util.spec_from_file_location(module_name, file_path)
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if spec is None or spec.loader is None:
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raise ImportError(f"Cannot load module from {file_path}")
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module = importlib.util.module_from_spec(spec)
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sys.modules[module_name] = module
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spec.loader.exec_module(module)
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return module
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def parse_args() -> argparse.Namespace:
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parser = argparse.ArgumentParser(description="Predict TMD RMS using baseline model + frequency adapter.")
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parser.add_argument("--file", type=str, required=True)
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parser.add_argument("--checkpoint", type=str, default="checkpoints_final/task1_final/task1_final_model.pkl")
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parser.add_argument("--adapter", type=str, default="checkpoints_final/task1_final/task1_tmd_adapter.pkl")
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parser.add_argument("--data-dir", type=str, default="downloads/TMD")
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return parser.parse_args()
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def main() -> None:
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args = parse_args()
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config_module = _load_module("config", PROJECT_ROOT / "scripts" / "config.py")
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dataset_module = _load_module("task1_dataset", PROJECT_ROOT / "scripts" / "dataset.py")
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make_experiment_config = getattr(config_module, "make_experiment_config")
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build_record_from_file = getattr(dataset_module, "build_record_from_file")
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config = make_experiment_config()
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config.data.data_dir = args.data_dir
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config.data.__post_init__()
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ckpt_path = (PROJECT_ROOT / args.checkpoint).resolve()
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adapter_path = (PROJECT_ROOT / args.adapter).resolve()
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with ckpt_path.open("rb") as handle:
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payload = pickle.load(handle)
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model = payload["model"]
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adapter, extra = load_adapter(adapter_path)
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file_path = Path(args.file).resolve()
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record = build_record_from_file(file_path, config.data)
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pred_tr = max(float(model.predict([record.features.tolist()])[0]), config.data.normalization_eps)
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pred_base = pred_tr * record.x_rms
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pred_tmd = adapter.predict(pred_base, record.frequency_hz)
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true_rms = float(record.y_rms)
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base_err = abs(pred_base - true_rms) / max(abs(true_rms), 1e-12) * 100.0
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tmd_err = abs(pred_tmd - true_rms) / max(abs(true_rms), 1e-12) * 100.0
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print(f"Checkpoint: {ckpt_path}")
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print(f"Adapter: {adapter_path}")
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print(f"Adapter extra: {extra}")
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print(f"Input file: {file_path}")
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print(f"Frequency (Hz): {record.frequency_hz:.6f}")
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print(f"x_rms: {record.x_rms:.6f}")
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print(f"True y_rms: {true_rms:.6f}")
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print(f"Base pred y_rms: {pred_base:.6f} | error={base_err:.4f}%")
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print(f"Adapted pred y_rms: {pred_tmd:.6f} | error={tmd_err:.4f}%")
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print(f"Applied scale k(f): {adapter.scale_at(record.frequency_hz):.6f}")
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if __name__ == "__main__":
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main()
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