code: def export_1d_uneven_split_opset18() -> None:
      node_input = np.array([1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0]).astype(
          np.float32
      )
  
      # If axis is not specified, split is applied on default axis 0
      node = onnx.helper.make_node(
          "Split",
          inputs=["input"],
          outputs=["output_1", "output_2", "output_3", "output_4"],
          num_outputs=4,
      )
  
      expected_outputs = [
          np.array([1.0, 2.0]).astype(np.float32),
          np.array([3.0, 4.0]).astype(np.float32),
          np.array([5.0, 6.0]).astype(np.float32),
          np.array([7.0]).astype(np.float32),
      ]
      expect(
          node,
          inputs=[node_input],
          outputs=expected_outputs,
          name="test_split_1d_uneven_split_opset18",
      )
  
file_path: onnx/onnx/backend/test/case/node/split.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 9 for calling the Split obj's underlying member method code with example usage: obj.export_1d_uneven_split_opset18() without return types