code: def export_deformconv_with_mask_bias() -> 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",
      )
  
file_path: onnx/onnx/backend/test/case/node/deformconv.py
imports: import numpy
  import onnx
  from onnx.backend.test.case.base import Base
  from onnx.backend.test.case.node import expect
label_desc: Use image node_id 2 for calling the DeformConv obj's underlying member method code with example usage: obj.export_deformconv_with_mask_bias() without return types