| 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() | |