code: def test_config_contains_both_base_classes(self):
      conv2d_layer = keras_layers.FanInScaledConv2D(
          filters=3,
          kernel_size=1,
          kernel_multiplier=2.0,
          multiplier=1.0,
      )
  
      config_dict = conv2d_layer.get_config()
  
      with self.subTest(name="_FanInScaler"):
          self.assertIn("kernel_multiplier", config_dict)
          self.assertIn("multiplier", config_dict)
          self.assertIn("bias_multiplier", config_dict)
          self.assertEqual(config_dict["kernel_multiplier"], 2.0)
          self.assertEqual(config_dict["multiplier"], 1.0)
          self.assertIsNone(config_dict["bias_multiplier"])
  
      with self.subTest(name="Conv2D"):
          self.assertIn("filters", config_dict)
          self.assertEqual(config_dict["filters"], 3)
  
imports: import math
  from absl.testing import parameterized
  import tensorflow
  from tensorflow_graphics.projects.gan import keras_layers
  from tensorflow_graphics.util import test_case
label_desc: Use image node_id 4 for calling the FanInScaledConv2DTest obj's underlying member method code with example usage: obj.test_config_contains_both_base_classes() without return types