code: def export_convtranspose_autopad_same() -> None:
      x = np.array(
          [
              [[[0.0, 1.0, 2.0], [3.0, 4.0, 5.0], [6.0, 7.0, 8.0]]]
          ]  # (1, 1, 3, 3)
      ).astype(np.float32)
  
      W = np.array(
          [
              [
                  [
                      [1.0, 1.0, 1.0],
                      [1.0, 1.0, 1.0],
                      [1.0, 1.0, 1.0],
                  ],  # (1, 2, 3, 3)
                  [[1.0, 1.0, 1.0], [1.0, 1.0, 1.0], [1.0, 1.0, 1.0]],
              ]
          ]
      ).astype(np.float32)
  
      node = onnx.helper.make_node(
          "ConvTranspose",
          ["X", "W"],
          ["Y"],
          auto_pad="SAME_UPPER",
          strides=[2, 2],
      )
  
      y = np.array(
          [
              [
                  [
                      [0.0, 0.0, 1.0, 1.0, 3.0, 2.0],
                      [0.0, 0.0, 1.0, 1.0, 3.0, 2.0],
                      [3.0, 3.0, 8.0, 5.0, 12.0, 7.0],
                      [3.0, 3.0, 7.0, 4.0, 9.0, 5.0],
                      [9.0, 9.0, 20.0, 11.0, 24.0, 13.0],
                      [6.0, 6.0, 13.0, 7.0, 15.0, 8.0],
                  ],
                  [
                      [0.0, 0.0, 1.0, 1.0, 3.0, 2.0],
                      [0.0, 0.0, 1.0, 1.0, 3.0, 2.0],
                      [3.0, 3.0, 8.0, 5.0, 12.0, 7.0],
                      [3.0, 3.0, 7.0, 4.0, 9.0, 5.0],
                      [9.0, 9.0, 20.0, 11.0, 24.0, 13.0],
                      [6.0, 6.0, 13.0, 7.0, 15.0, 8.0],
                  ],
              ]
          ]
      ).astype(np.float32)
  
      expect(
          node,
          inputs=[x, W],
          outputs=[y],
          name="test_convtranspose_autopad_same",
      )
  
file_path: onnx/onnx/backend/test/case/node/convtranspose.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 7 for calling the ConvTranspose obj's underlying member method code with example usage: obj.export_convtranspose_autopad_same() without return types