def METHOD_NAME() -> None:
    X = np.arange(9).astype(np.float32)
    X.shape = (1, 1, 3, 3)
    W = np.ones((1, 1, 2, 2), dtype=np.float32)
    B = np.ones((1,), dtype=np.float32)
    offset = np.zeros((1, 8, 2, 2), dtype=np.float32)
    offset[
        0, 0, 0, 0
    ] = 0.5  # h-coord of [0, 0] element of kernel, at output position [0, 0]
    offset[
        0, 5, 0, 1
    ] = -0.1  # w-coord of [1, 0] element of kernel, at output position [0, 1]
    mask = np.ones((1, 4, 2, 2), dtype=np.float32)
    mask[0, 2, 1, 1] = 0.2  # [1, 0] element of kernel at output position [1, 1]
    node = onnx.helper.make_node(
        "DeformConv",
        inputs=["X", "W", "offset", "B", "mask"],
        outputs=["Y"],
        kernel_shape=[2, 2],
        pads=[0, 0, 0, 0],
    )
    Y = np.array(
        [
            [
                [
                    [10.5, 12.9],  # (1, 1, 2, 2) output tensor
                    [21.0, 19.4],
                ]
            ]
        ]
    ).astype(np.float32)
    expect(
        node,
        inputs=[X, W, offset, B, mask],
        outputs=[Y],
        name="test_deform_conv_with_mask_bias",
    )