"""
Generate resized ImageNet-100 dataset.
"""

from argparse import ArgumentParser
from functools import partial
from pathlib import Path

from datasets import load_dataset
from torchvision.transforms import InterpolationMode
from torchvision.transforms.functional import resize

SCRIPT = str(Path(__file__).parent / "imagenet-100.py")


def transforms(examples, size: int = 160):
    examples["image"] = [
        resize(image, size, interpolation=InterpolationMode.BICUBIC)
        for image in examples["image"]
    ]
    return examples


if __name__ == "__main__":
    parser = ArgumentParser()
    parser.add_argument("--outdir", "-o", type=str, default="cache")
    parser.add_argument("--size", "-s", type=int, default=160)
    parser.add_argument("--num-proc", "-n", type=int, default=8)
    args = parser.parse_args()

    dataset = load_dataset(SCRIPT)
    dataset = dataset.map(
        partial(transforms, size=args.size),
        batched=True,
        batch_size=256,
        num_proc=args.num_proc,
    )
    print(dataset)
    print(dataset["validation"][0])

    outdir = Path(args.outdir) / f"imagenet-100_{args.size}"
    dataset.save_to_disk(outdir, num_proc=args.num_proc)