code: def export() -> None:
      alpha = 2.0
      node = onnx.helper.make_node(
          "Celu",
          inputs=["X"],
          outputs=["Y"],
          alpha=alpha,
      )
  
      input_data = np.array(
          [
              [
                  [[0.8439683], [0.5665144], [0.05836735]],
                  [[0.02916367], [0.12964272], [0.5060197]],
                  [[0.79538304], [0.9411346], [0.9546573]],
              ],
              [
                  [[0.17730942], [0.46192095], [0.26480448]],
                  [[0.6746842], [0.01665257], [0.62473077]],
                  [[0.9240844], [0.9722341], [0.11965699]],
              ],
              [
                  [[0.41356155], [0.9129373], [0.59330076]],
                  [[0.81929934], [0.7862604], [0.11799799]],
                  [[0.69248444], [0.54119414], [0.07513223]],
              ],
          ],
          dtype=np.float32,
      )
  
      # Calculate expected output data
      positive_input = np.maximum(0, input_data)
      negative_input = np.minimum(
          0, alpha * (np.exp(input_data / alpha) - 1)
      )
      expected_output = positive_input + negative_input
  
      expect(
          node,
          inputs=[input_data],
          outputs=[expected_output],
          name="test_celu",
      )
  
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 1 for calling the Celu obj's underlying member method code with example usage: obj.export() without return types