code: def check_common(self, plot_obj, target_type):
      assert plot_obj.plot_type == "target"
      assert isinstance(plot_obj.feature_info, FeatureInfo)
  
      if target_type == "multi-class":
          assert plot_obj.target == [
              f"target_{i}" for i in range(plot_obj.n_classes)
          ]
          assert len(plot_obj.target_lines) == plot_obj.n_classes
          for i in range(plot_obj.n_classes):
              assert set(plot_obj.target_lines[i].columns) == set(
                  ["x", f"target_{i}"]
              )
      else:
          assert plot_obj.target == ["target"]
          assert len(plot_obj.target_lines) == 1
          assert set(plot_obj.target_lines[0].columns) == set(
              ["x", "target"]
          )
  
      assert set(plot_obj.df.columns) == set(
          plot_obj.feature_cols + ["x", "count"] + plot_obj.target
      )
      assert set(plot_obj.count_df.columns) == set(
          ["x", "count", "count_norm"]
      )
  
      summary_cols = ["x", "value", "count"] + plot_obj.target
      if plot_obj.feature_info.percentiles is not None:
          summary_cols.append("percentile")
      assert set(plot_obj.summary_df.columns) == set(summary_cols)
  
imports: import pytest
  import numpy
  from pdpbox.info_plots import TargetPlot, PredictPlot, InteractTargetPlot, InteractPredictPlot
  from pdpbox.utils import FeatureInfo, _make_list
  from conftest import DummyModel, PlotTestBase
label_desc: Use image node_id 2 for calling the TestTargetPlot obj's underlying member method code with example usage: obj.check_common(plot_obj, target_type) without return types