code: def export_softmaxcrossentropy_mean_weights() -> None:
      # Define operator attributes.
      reduction = "mean"
  
      # Create operator.
      node = onnx.helper.make_node(
          "SoftmaxCrossEntropyLoss",
          inputs=["x", "y", "w"],
          outputs=["z"],
          reduction=reduction,
      )
  
      # Define operator inputs.
      np.random.seed(0)
      x = np.random.rand(3, 5).astype(np.float32)
      labels = np.random.randint(0, high=5, size=(3,)).astype(np.int64)
      weights = np.array([0.9, 0.7, 0.8, 0.9, 0.9], dtype=np.float32)
  
      # Compute SoftmaxCrossEntropyLoss
      sce = softmaxcrossentropy(x, labels, weight=weights)
  
      # Check results
      expect(
          node,
          inputs=[x, labels, weights],
          outputs=[sce],
          name="test_sce_mean_weight",
      )
  
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 11 for calling the SoftmaxCrossEntropyLoss obj's underlying member method code with example usage: obj.export_softmaxcrossentropy_mean_weights() without return types