code: def test_config(self):
      cat_acc_obj = accuracy_metrics.CategoricalAccuracy(
          name="categorical_accuracy", dtype="float32"
      )
      self.assertEqual(cat_acc_obj.name, "categorical_accuracy")
      self.assertEqual(len(cat_acc_obj.variables), 2)
      self.assertEqual(cat_acc_obj._dtype, "float32")
  
      # Test get_config
      cat_acc_obj_config = cat_acc_obj.get_config()
      self.assertEqual(
          cat_acc_obj_config["name"], "categorical_accuracy"
      )
      self.assertEqual(cat_acc_obj_config["dtype"], "float32")
  
      # Check save and restore config
      cat_acc_obj2 = accuracy_metrics.CategoricalAccuracy.from_config(
          cat_acc_obj_config
      )
      self.assertEqual(cat_acc_obj2.name, "categorical_accuracy")
      self.assertEqual(len(cat_acc_obj2.variables), 2)
      self.assertEqual(cat_acc_obj2._dtype, "float32")
  
imports: import re
  import numpy
  from keras import testing
  from keras.metrics import accuracy_metrics
label_desc: Use image node_id 1 for calling the CategoricalAccuracyTest obj's underlying member method code with example usage: obj.test_config() without return types