code: def test_r1_regularization_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))
  
      r1_regularization = losses.r1_regularization(
          real_data=real_data, discriminator=discriminator
      )
  
      self.assertAllGreaterEqual(r1_regularization, 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 13 for calling the LossesTest obj's underlying member method code with example usage: obj.test_r1_regularization_positive() without return types