code: def test_blur_average_pooling_is_anti_aliased_bilinear_downsampling(
      self, shape=(1, 8, 8, 3)
  ):
      input_tensor = tf.random.normal(shape=shape)
  
      blurred_tensor = keras_layers.Blur2D()(input_tensor)
      average_pooled_tensor = tf.keras.layers.AveragePooling2D()(
          blurred_tensor
      )
  
      height, width = shape[1:3]
      bilinear_interpolated_tensor = tf.image.resize(
          input_tensor,
          (height // 2, width // 2),
          method=tf.image.ResizeMethod.BILINEAR,
          antialias=True,
      )
      self.assertAllClose(
          average_pooled_tensor[:, 1:-1, 1:-1, :],
          bilinear_interpolated_tensor[:, 1:-1, 1:-1, :],
      )
  
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 2 for calling the Blur2DTest obj's underlying member method code with example usage: obj.test_blur_average_pooling_is_anti_aliased_bilinear_downsampling(shape) without return types