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"""
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)
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