def METHOD_NAME():
    metadata = {
        "preprocessing": {
            "missing_value_strategy": BFILL,
            "in_memory": True,
            "resize_method": "interpolate",
            "scaling": "pixel_normalization",
            "num_processes": 1,
            "infer_image_num_channels": True,
            "infer_image_dimensions": True,
            "infer_image_max_height": 256,
            "infer_image_max_width": 256,
            "infer_image_sample_size": 100,
            "height": 12,
            "width": 12,
            "num_channels": 2,
        },
        "reshape": (2, 12, 12),
    }
    module = _ImagePreprocessing(metadata)
    with pytest.raises(ValueError):
        module(torch.rand(2, 3, 10, 10))