code: def test_gradient_penalty_loss_positive(self):
      discriminator = tf.keras.Sequential()
      discriminator.add(tf.keras.layers.Reshape((25,)))
      discriminator.add(tf.keras.layers.Dense(units=1))
      real_data = tf.ones(shape=(1, 5, 5))
      generated_data = tf.ones(shape=(1, 5, 5))
  
      gradient_penalty = losses.gradient_penalty_loss(
          real_data=real_data,
          generated_data=generated_data,
          discriminator=discriminator,
      )
  
      self.assertAllGreaterEqual(gradient_penalty, 0.0)
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow
  from tensorflow_graphics.projects.gan import losses
  from tensorflow_graphics.util import test_case
label_desc: Use image node_id 3 for calling the LossesTest obj's underlying member method code with example usage: obj.test_gradient_penalty_loss_positive() without return types