code: def test_value(self, precision):
      model = UNet(
          spatial_dims=3,
          in_channels=1,
          out_channels=2,
          channels=(2, 2, 4, 8, 4),
          strides=(2, 2, 2, 2),
          num_res_units=2,
          norm="batch",
      )
      with tempfile.TemporaryDirectory() as _:
          torchscript_model = convert_to_trt(
              model=model,
              precision=precision,
              input_shape=[1, 1, 96, 96, 96],
              dynamic_batchsize=[1, 4, 8],
              use_trace=False,
              verify=True,
              device=0,
              rtol=1e-2,
              atol=1e-2,
          )
          self.assertTrue(
              isinstance(torchscript_model, torch.nn.Module)
          )
  
file_path: MONAI/tests/test_convert_to_trt.py
imports: from __future__ import annotations
  import tempfile
  import unittest
  import torch
  from parameterized import parameterized
  from monai.networks import convert_to_trt
  from monai.networks.nets import UNet
  from monai.utils import optional_import
  from tests.utils import skip_if_no_cuda, skip_if_quick, skip_if_windows
label_desc: Use image node_id 3 for calling the TestConvertToTRT obj's underlying member method code with example usage: obj.test_value(precision) without return types