code: def test_detectorrs_resnet_backbone():
      detectorrs_cfg = dict(
          depth=50,
          num_stages=4,
          out_indices=(0, 1, 2, 3),
          frozen_stages=1,
          norm_cfg=dict(type="BN", requires_grad=True),
          norm_eval=True,
          style="pytorch",
          conv_cfg=dict(type="ConvAWS"),
          sac=dict(type="SAC", use_deform=True),
          stage_with_sac=(False, True, True, True),
          output_img=True,
      )
      """Test init_weights config"""
      with pytest.raises(AssertionError):
          # pretrained and init_cfg cannot be specified at the same time
          DetectoRS_ResNet(
              **detectorrs_cfg,
              pretrained="Pretrained",
              init_cfg="Pretrained",
          )
  
      with pytest.raises(AssertionError):
          # init_cfg must be a dict
          DetectoRS_ResNet(
              **detectorrs_cfg, pretrained=None, init_cfg=["Pretrained"]
          )
  
      with pytest.raises(KeyError):
          # init_cfg must contain the key `type`
          DetectoRS_ResNet(
              **detectorrs_cfg,
              pretrained=None,
              init_cfg=dict(checkpoint="Pretrained"),
          )
  
      with pytest.raises(AssertionError):
          # init_cfg only support initialize pretrained model way
          DetectoRS_ResNet(
              **detectorrs_cfg,
              pretrained=None,
              init_cfg=dict(type="Trained"),
          )
  
      with pytest.raises(TypeError):
          # pretrained mast be a str or None
          model = DetectoRS_ResNet(
              **detectorrs_cfg, pretrained=["Pretrained"], init_cfg=None
          )
          model.init_weights()
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_detectorrs_resnet_backbone() without return types