code: def test_shape(self, input_param):
      net = LocalNetFeatureExtractorBlock(**input_param)
      input_shape = (
          1,
          input_param["in_channels"],
          *([in_size] * input_param["spatial_dims"]),
      )
      expected_shape = (
          1,
          input_param["out_channels"],
          *([in_size] * input_param["spatial_dims"]),
      )
      with eval_mode(net):
          result = net(torch.randn(input_shape))
          self.assertEqual(result.shape, expected_shape)
  
file_path: MONAI/tests/test_localnet_block.py
imports: from __future__ import annotations
  import unittest
  import torch
  from parameterized import parameterized
  from monai.networks import eval_mode
  from monai.networks.blocks.localnet_block import LocalNetDownSampleBlock, LocalNetFeatureExtractorBlock, LocalNetUpSampleBlock
label_desc: Use image node_id 1 for calling the TestExtractBlock obj's underlying member method code with example usage: obj.test_shape(input_param) without return types