#!/usr/bin/env python3

import argparse
from dataclasses import dataclass

import jinja2


def get_args():
    parser = argparse.ArgumentParser()
    parser.add_argument(
        "--total",
        type=int,
        default=1,
        help="Number of runners",
    )
    parser.add_argument(
        "--index",
        type=int,
        default=0,
        help="Index of the current runner",
    )
    return parser.parse_args()


@dataclass
class SlidModel:
    model_name: str
    idx: int
    short_name: str = ""


def get_models():
    # see https://k2-fsa.github.io/sherpa/onnx/spolken-language-identification/pretrained_models.html#pre-trained-models
    whisper_models = [
        SlidModel(
            model_name="sherpa-onnx-whisper-tiny",
            idx=0,
            short_name="whisper_tiny",
        ),
    ]

    return whisper_models


def main():
    args = get_args()
    index = args.index
    total = args.total
    assert 0 <= index < total, (index, total)

    all_model_list = get_models()

    num_models = len(all_model_list)

    num_per_runner = num_models // total
    if num_per_runner <= 0:
        raise ValueError(f"num_models: {num_models}, num_runners: {total}")

    start = index * num_per_runner
    end = start + num_per_runner

    remaining = num_models - args.total * num_per_runner

    print(f"{index}/{total}: {start}-{end}/{num_models}")

    d = dict()
    d["model_list"] = all_model_list[start:end]
    if index < remaining:
        s = args.total * num_per_runner + index
        d["model_list"].append(all_model_list[s])
        print(f"{s}/{num_models}")

    filename_list = [
        "./build-apk-slid.sh",
    ]
    for filename in filename_list:
        environment = jinja2.Environment()
        with open(f"{filename}.in") as f:
            s = f.read()
        template = environment.from_string(s)

        s = template.render(**d)
        with open(filename, "w") as f:
            print(s, file=f)


if __name__ == "__main__":
    main()