import numpy as np

from preprocessor.feature_extractor import HapticFeatureExtractor


def main():
    extractor = HapticFeatureExtractor.from_pretrained(".")
    sample = np.random.randn(1024, 12).astype(np.float32)
    features = extractor(sample)

    print("input_values:", features["input_values"].shape)
    print("attention_mask:", features["attention_mask"].shape)
    print("This scaffold does not include a runnable model checkpoint.")


if __name__ == "__main__":
    main()