code: def test_ill_input_shape(self):
      net = UNet(
          spatial_dims=2,
          in_channels=1,
          out_channels=3,
          channels=(16, 32, 64),
          strides=(2, 2),
      )
      with eval_mode(net):
          with self.assertRaisesRegex(
              RuntimeError, "Sizes of tensors must match"
          ):
              net.forward(torch.randn(2, 1, 16, 5))
  
file_path: MONAI/tests/test_unet.py
imports: from __future__ import annotations
  import unittest
  import torch
  from parameterized import parameterized
  from monai.networks import eval_mode
  from monai.networks.layers import Act, Norm
  from monai.networks.nets import UNet
  from tests.utils import test_script_save
label_desc: Use image node_id 4 for calling the TestUNET obj's underlying member method code with example usage: obj.test_ill_input_shape() without return types