code: def generate_random_test_lbs_blend():
      """Generates random test for the linear blend skinning blend function."""
      tensor_dimensions = np.random.randint(3)
      tensor_shape = np.random.randint(
          1, 10, size=(tensor_dimensions)
      ).tolist()
      random_points = np.random.uniform(size=tensor_shape + [3])
      num_weights = np.random.randint(2, 10)
      random_weights = np.random.uniform(
          size=tensor_shape + [num_weights]
      )
      random_weights /= np.sum(random_weights, axis=-1, keepdims=True)
  
      random_rotations = np.array(
          [stats.special_ortho_group.rvs(3) for _ in range(num_weights)]
      )
      random_rotations = np.reshape(
          random_rotations, [num_weights, 3, 3]
      )
      random_translations = np.random.uniform(size=[num_weights, 3])
      return (
          random_points,
          random_weights,
          random_rotations,
          random_translations,
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import itertools
  import math
  import numpy
  from scipy import stats
  from six.moves import range
  import tensorflow.compat.v2
  from tensorflow_graphics.geometry.transformation import axis_angle
  from tensorflow_graphics.geometry.transformation import quaternion
  from tensorflow_graphics.geometry.transformation import rotation_matrix_2d
  from tensorflow_graphics.geometry.transformation import rotation_matrix_3d
label_desc: Use image node_id 15 for calling a global function with example usage: generate_random_test_lbs_blend() and returns: random_points,  random_weights,  random_rotations,  random_translations