#!/usr/bin/env python3
"""Convert TensorFlow SavedModel to ONNX format."""

import argparse
import logging
import subprocess
import sys
from pathlib import Path


def main():
    """Convert a TensorFlow SavedModel to ONNX format using tf2onnx."""
    logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s")

    parser = argparse.ArgumentParser(
        description="Convert TensorFlow SavedModel to ONNX format"
    )
    parser.add_argument(
        "--saved-model",
        type=Path,
        default=Path("model/saved_model"),
        help="Path to the TensorFlow SavedModel directory",
    )
    parser.add_argument(
        "--output",
        type=Path,
        default=Path("model/model.onnx"),
        help="Path to the output ONNX model file",
    )
    parser.add_argument(
        "--opset",
        type=int,
        default=18,
        help="ONNX opset version to target",
    )

    args = parser.parse_args()

    if not args.saved_model.exists():
        msg = f"SavedModel not found at {args.saved_model}"
        logging.error(msg)
        raise FileNotFoundError(msg)

    args.output.parent.mkdir(parents=True, exist_ok=True)

    cmd = [
        sys.executable,
        "-m",
        "tf2onnx.convert",
        "--saved-model",
        str(args.saved_model),
        "--output",
        str(args.output),
        "--opset",
        str(args.opset),
    ]

    try:
        subprocess.run(cmd, check=True, capture_output=True, text=True)
    except subprocess.CalledProcessError as e:
        logging.error(f"tf2onnx conversion failed with exit code {e.returncode}")
        if e.stderr:
            logging.error(f"stderr: {e.stderr}")
        raise

    logging.info(f"ONNX model saved to {args.output}")


if __name__ == "__main__":
    main()