code: def test_shape(self, input_param, input_shape, expected_shape):
      with skip_if_downloading_fails():
          net = MILModel(**input_param).to(device)
      with eval_mode(net):
          result = net(
              torch.randn(input_shape, dtype=torch.float).to(device)
          )
          self.assertEqual(result.shape, expected_shape)
  
file_path: MONAI/tests/test_milmodel.py
imports: from __future__ import annotations
  import unittest
  import torch
  from parameterized import parameterized
  from monai.networks import eval_mode
  from monai.networks.nets import MILModel
  from monai.utils.module import optional_import
  from tests.utils import skip_if_downloading_fails, test_script_save
label_desc: Use image node_id 1 for calling the TestMilModel obj's underlying member method code with example usage: obj.test_shape(input_param, input_shape, expected_shape) without return types