code: def export() -> None:
      node = onnx.helper.make_node(
          "Mul",
          inputs=["x", "y"],
          outputs=["z"],
      )
  
      x = np.array([1, 2, 3]).astype(np.float32)
      y = np.array([4, 5, 6]).astype(np.float32)
      z = x * y  # expected output [4., 10., 18.]
      expect(node, inputs=[x, y], outputs=[z], name="test_mul_example")
  
      x = np.random.randn(3, 4, 5).astype(np.float32)
      y = np.random.randn(3, 4, 5).astype(np.float32)
      z = x * y
      expect(node, inputs=[x, y], outputs=[z], name="test_mul")
  
      x = np.random.randint(4, size=(3, 4, 5), dtype=np.uint8)
      y = np.random.randint(24, size=(3, 4, 5), dtype=np.uint8)
      z = x * y
      expect(node, inputs=[x, y], outputs=[z], name="test_mul_uint8")
  
file_path: onnx/onnx/backend/test/case/node/mul.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 1 for calling the Mul obj's underlying member method code with example usage: obj.export() without return types