code: def test_discriminator_intermediate_inputs_fit(self, batch_size):
      inputs = tuple(
          tf.ones(shape=(batch_size, 2 ** (i + 2), 2 ** (i + 2), 3))
          for i in range(3)
      )
      discriminator = (
          architectures_progressive_gan.create_discriminator(
              use_layer_normalization=True,
              downsampling_blocks_num_channels=((8, 8), (8, 8)),
              use_intermediate_inputs=True,
          )
      )
  
      output = discriminator(inputs)
      output_value = self.evaluate(output)
  
      with self.subTest(name="static_shape"):
          output.shape.assert_is_fully_defined()
          self.assertSequenceEqual(output.shape, (batch_size, 1))
  
      with self.subTest(name="dynamic_shape"):
          self.assertSequenceEqual(output_value.shape, (batch_size, 1))
  
file_path: graphics/tensorflow_graphics/projects/gan/architectures_progressive_gan_test.py
imports: from absl.testing import parameterized
  import numpy
  import tensorflow
  from tensorflow_graphics.projects.gan import architectures_progressive_gan
label_desc: Use image node_id 5 for calling the ArchitecturesProgressiveGanTest obj's underlying member method code with example usage: obj.test_discriminator_intermediate_inputs_fit(batch_size) without return types