code: def export_resize_upsample_sizes_cubic() -> None:
      node = onnx.helper.make_node(
          "Resize",
          inputs=["X", "", "", "sizes"],
          outputs=["Y"],
          mode="cubic",
      )
  
      data = np.array(
          [
              [
                  [
                      [1, 2, 3, 4],
                      [5, 6, 7, 8],
                      [9, 10, 11, 12],
                      [13, 14, 15, 16],
                  ]
              ]
          ],
          dtype=np.float32,
      )
  
      sizes = np.array([1, 1, 9, 10], dtype=np.int64)
  
      # [[[[ 0.45507922  0.64057922  0.97157922  1.42257922  1.90732922
      #      2.22332922  2.70807922  3.15907922  3.49007922  3.67557922]
      #    [ 1.39437963  1.57987963  1.91087963  2.36187963  2.84662963
      #      3.16262963  3.64737963  4.09837963  4.42937963  4.61487963]
      #    [ 2.95130693  3.13680693  3.46780693  3.91880693  4.40355693
      #      4.71955693  5.20430693  5.65530693  5.98630693  6.17180693]
      #    [ 5.20525069  5.39075069  5.72175069  6.17275069  6.65750069
      #      6.97350069  7.45825069  7.90925069  8.24025069  8.42575069]
      #    [ 6.88975     7.07525     7.40625     7.85725     8.342
      #      8.658       9.14275     9.59375     9.92475    10.11025   ]
      #    [ 8.57424931  8.75974931  9.09074931  9.54174931 10.02649931
      #     10.34249931 10.82724931 11.27824931 11.60924931 11.79474931]
      #    [10.82819307 11.01369307 11.34469307 11.79569307 12.28044307
      #     12.59644307 13.08119307 13.53219307 13.86319307 14.04869307]
      #    [12.38512037 12.57062037 12.90162037 13.35262037 13.83737037
      #     14.15337037 14.63812037 15.08912037 15.42012037 15.60562037]
      #    [13.32442078 13.50992078 13.84092078 14.29192078 14.77667078
      #     15.09267078 15.57742078 16.02842078 16.35942078 16.54492078]]]]
      output = interpolate_nd(
          data, lambda x, _: cubic_coeffs(x), output_size=sizes
      ).astype(np.float32)
  
      expect(
          node,
          inputs=[data, sizes],
          outputs=[output],
          name="test_resize_upsample_sizes_cubic",
      )
  
imports: import numpy
  import onnx
  from onnx.backend.test.case.base import Base
  from onnx.backend.test.case.node import expect
  from onnx.reference.ops.op_resize import _cubic_coeffs
  from onnx.reference.ops.op_resize import _cubic_coeffs_antialias
  from onnx.reference.ops.op_resize import _interpolate_nd
  from onnx.reference.ops.op_resize import _linear_coeffs
  from onnx.reference.ops.op_resize import _linear_coeffs_antialias
  from onnx.reference.ops.op_resize import _nearest_coeffs
label_desc: Use image node_id 13 for calling the Resize obj's underlying member method code with example usage: obj.export_resize_upsample_sizes_cubic() without return types