code: def test_without_pretrained(
      self, input_param, input_shape, expected_shape
  ):
      net = TorchVisionFCModel(**input_param).to(device)
      with eval_mode(net):
          result = net.forward(torch.randn(input_shape).to(device))
          self.assertEqual(result.shape, expected_shape)
  
file_path: MONAI/tests/test_torchvision_fc_model.py
imports: from __future__ import annotations
  import unittest
  from unittest import skipUnless
  import torch
  from parameterized import parameterized
  from monai.networks import eval_mode
  from monai.networks.nets import TorchVisionFCModel, UNet
  from monai.networks.utils import look_up_named_module, set_named_module
  from monai.utils import min_version, optional_import
  from tests.utils import skip_if_downloading_fails
label_desc: Use image node_id 1 for calling the TestTorchVisionFCModel obj's underlying member method code with example usage: obj.test_without_pretrained(input_param, input_shape, expected_shape) without return types