#!/usr/bin/env python3
"""Run deterministic inference with the published t5-smaller checkpoint."""

from __future__ import annotations

import argparse

import torch
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer


def main() -> None:
    parser = argparse.ArgumentParser(description=__doc__)
    parser.add_argument("prompt", nargs="?", default="translate English to German: How old are you?")
    parser.add_argument("--model", default="ShinpacheShimura/t5-smaller")
    parser.add_argument("--subfolder", default="optimized-flan-t5-small")
    parser.add_argument("--max-new-tokens", type=int, default=64)
    args = parser.parse_args()

    common = {"subfolder": args.subfolder} if args.subfolder else {}
    tokenizer = AutoTokenizer.from_pretrained(args.model, **common)
    model = AutoModelForSeq2SeqLM.from_pretrained(args.model, device_map="auto", **common)
    inputs = tokenizer(args.prompt, return_tensors="pt").to(model.device)
    with torch.inference_mode():
        output_ids = model.generate(**inputs, max_new_tokens=args.max_new_tokens, do_sample=False)
    print(tokenizer.decode(output_ids[0], skip_special_tokens=True))


if __name__ == "__main__":
    main()