code: def export_resize_downsample_sizes_linear_antialias() -> None:
      node = onnx.helper.make_node(
          "Resize",
          inputs=["X", "", "", "sizes"],
          outputs=["Y"],
          mode="linear",
          antialias=1,
      )
  
      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, 3, 3], dtype=np.int64)
  
      # [[[[ 2.3636363  3.590909   4.818182 ]
      #    [ 7.2727275  8.5        9.727273 ]
      #    [12.181818  13.409091  14.636364 ]]]]
      output = interpolate_nd(
          data, linear_coeffs_antialias, output_size=sizes
      ).astype(np.float32)
  
      expect(
          node,
          inputs=[data, sizes],
          outputs=[output],
          name="test_resize_downsample_sizes_linear_antialias",
      )
  
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 25 for calling the Resize obj's underlying member method code with example usage: obj.export_resize_downsample_sizes_linear_antialias() without return types