code: def export_with_padding() -> None:
      x = (
          np.array([2, 3, 4, 5, 6, 7, 8, 9, 10])
          .astype(np.uint8)
          .reshape((1, 1, 3, 3))
      )
      x_zero_point = np.uint8(1)
      w = np.array([1, 1, 1, 1]).astype(np.uint8).reshape((1, 1, 2, 2))
  
      y = (
          np.array(
              [1, 3, 5, 3, 5, 12, 16, 9, 11, 24, 28, 15, 7, 15, 17, 9]
          )
          .astype(np.int32)
          .reshape((1, 1, 4, 4))
      )
  
      # ConvInteger with padding
      convinteger_node_with_padding = onnx.helper.make_node(
          "ConvInteger",
          inputs=["x", "w", "x_zero_point"],
          outputs=["y"],
          pads=[1, 1, 1, 1],
      )
  
      expect(
          convinteger_node_with_padding,
          inputs=[x, w, x_zero_point],
          outputs=[y],
          name="test_convinteger_with_padding",
      )
  
file_path: onnx/onnx/backend/test/case/node/convinteger.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 ConvInteger obj's underlying member method code with example usage: obj.export_with_padding() without return types