code: def test_forward(self):
      inputs = torch.rand(32, 128)
  
      # test
      fc = FcModule(
          in_channels=128,
          out_channels=32,
      )
      fc.init_weights()
      outputs = fc(inputs)
      assert outputs.shape == (32, 32)
  
      # test with norm
      fc = FcModule(
          in_channels=128,
          out_channels=32,
          norm_cfg=dict(type="BN1d"),
      )
      outputs = fc(inputs)
      assert outputs.shape == (32, 32)
  
      # test with norm and act
      fc = FcModule(
          in_channels=128,
          out_channels=32,
          norm_cfg=dict(type="BN1d"),
          act_cfg=dict(type="ReLU"),
      )
      outputs = fc(inputs)
      assert outputs.shape == (32, 32)
  
imports: from unittest import TestCase
  import torch
  from mmdet.models import FcModule
label_desc: Use image node_id 1 for calling the TestFcModule obj's underlying member method code with example usage: obj.test_forward() without return types