"""Offline CPU inference. Replace the frequency baseline with your own model."""
import argparse
import json
from pathlib import Path

import pandas as pd
from inputs import prepare_inputs


def predict_file(input_path, output_path):
    root = Path(__file__).parent
    frame = prepare_inputs(pd.read_parquet(input_path))
    weights = json.loads((root / 'weights/baseline.json').read_text())
    # Load your model once. Batch its predictions here.
    with Path(output_path).open('w') as output:
        for key in frame.id:
            output.write(json.dumps({'id':key, 'prediction':weights['prediction']}) + '\n')


if __name__ == '__main__':
    parser = argparse.ArgumentParser(description=__doc__)
    parser.add_argument('--input', required=True)
    parser.add_argument('--output', required=True)
    args = parser.parse_args()
    predict_file(args.input, args.output)