code: def export_softmaxcrossentropy_mean_no_weights_ii_4d() -> None:
      # Define operator attributes.
      reduction = "mean"
      ignore_index = np.int64(2)
  
      # Create operator.
      node = onnx.helper.make_node(
          "SoftmaxCrossEntropyLoss",
          inputs=["x", "y"],
          outputs=["z"],
          reduction=reduction,
          ignore_index=ignore_index,
      )
  
      # Define operator inputs.
      np.random.seed(0)
      x = np.random.rand(3, 5, 2, 7).astype(np.float32)
      labels = np.random.randint(0, high=5, size=(3, 2, 7)).astype(
          np.int64
      )
      labels[0][0][0] = np.int64(2)
  
      # Compute SoftmaxCrossEntropyLoss
      sce = softmaxcrossentropy(
          x, labels, reduction=reduction, ignore_index=ignore_index
      )
  
      # Check results
      expect(
          node,
          inputs=[x, labels],
          outputs=[sce],
          name="test_sce_mean_no_weight_ii_4d",
      )
  
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 23 for calling the SoftmaxCrossEntropyLoss obj's underlying member method code with example usage: obj.export_softmaxcrossentropy_mean_no_weights_ii_4d() without return types