code: def _generate_random_example(self):
      num_cameras = 4
      num_keypoints = 3
      batch_size = 2
      self.points_values = np.random.random_sample(
          (batch_size, num_keypoints, 3)
      )
      points_expanded_values = np.expand_dims(
          self.points_values, axis=-2
      )
      startpoints_values = np.random.random_sample(
          (batch_size, num_keypoints, num_cameras, 3)
      )
  
      difference = points_expanded_values - startpoints_values
      difference_norm = np.sqrt((difference * difference).sum(axis=-1))
      direction = difference / np.expand_dims(difference_norm, axis=-1)
  
      self.startpoints_values = points_expanded_values - 0.5 * direction
      self.endpoints_values = points_expanded_values + 0.5 * direction
      self.weights_values = np.ones(
          (batch_size, num_keypoints, num_cameras)
      )
  
      # Wrap these with identies because some assert_* ops look at the constant
      # tensor values and mark these as unfeedable.
      self.points = tf.identity(
          tf.convert_to_tensor(value=self.points_values)
      )
      self.startpoints = tf.identity(
          tf.convert_to_tensor(value=self.startpoints_values)
      )
      self.endpoints = tf.identity(
          tf.convert_to_tensor(value=self.endpoints_values)
      )
      self.weights = tf.identity(
          tf.convert_to_tensor(value=self.weights_values)
      )
  
imports: import sys
  from absl import flags
  from absl.testing import flagsaver
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tensorflow_graphics.geometry.representation import ray
  from tensorflow_graphics.util import test_case
label_desc: Use image node_id 1 for calling the RayTest obj's underlying member method code with example usage: obj._generate_random_example() without return types