code: def test_unet(self, device, use_trace, use_ort):
      if use_ort:
          _, has_onnxruntime = optional_import("onnxruntime")
          if not has_onnxruntime:
              self.skipTest(
                  "onnxruntime is not installed probably due to python version >= 3.11."
              )
      model = UNet(
          spatial_dims=2,
          in_channels=1,
          out_channels=3,
          channels=(16, 32, 64),
          strides=(2, 2),
          num_res_units=0,
      )
      if pytorch_after(1, 10) or use_trace:
          onnx_model = convert_to_onnx(
              model=model,
              inputs=[
                  torch.randn((16, 1, 32, 32), requires_grad=False)
              ],
              input_names=["x"],
              output_names=["y"],
              verify=True,
              device=device,
              use_ort=use_ort,
              use_trace=use_trace,
              rtol=1e-3,
              atol=1e-4,
          )
      else:
          # https://github.com/pytorch/pytorch/blob/release/1.9/torch/onnx/__init__.py#L182
          # example_outputs is required in scripting mode before PyTorch 3.10
          onnx_model = convert_to_onnx(
              model=model,
              inputs=[
                  torch.randn((16, 1, 32, 32), requires_grad=False)
              ],
              input_names=["x"],
              output_names=["y"],
              example_outputs=[
                  torch.randn((16, 3, 32, 32), requires_grad=False)
              ],
              verify=True,
              device=device,
              use_ort=use_ort,
              use_trace=use_trace,
              rtol=1e-3,
              atol=1e-4,
          )
      self.assertTrue(isinstance(onnx_model, onnx.ModelProto))
  
file_path: MONAI/tests/test_convert_to_onnx.py
imports: from __future__ import annotations
  import itertools
  import unittest
  import torch
  from parameterized import parameterized
  from monai.networks import convert_to_onnx
  from monai.networks.nets import SegResNet, UNet
  from monai.utils.module import pytorch_after
  from tests.utils import SkipIfBeforePyTorchVersion, SkipIfNoModule, optional_import, skip_if_quick
label_desc: Use image node_id 1 for calling the TestConvertToOnnx obj's underlying member method code with example usage: obj.test_unet(device, use_trace, use_ort) without return types