code: def testVarianceBroadcast(self):
      scale = [make_pd(1.0, 2), make_pd(1.0, 2)]
      chol_scale = np.float32([chol(s) for s in scale])
      scale = np.float32(scale)
      df = np.array([4.0, 3.0], dtype=np.float32)
      w = wishart.WishartTriL(
          df, scale_tril=chol_scale, validate_args=True
      )
      self.assertAllEqual(
          wishart_var(df, scale), self.evaluate(w.variance())
      )
  
imports: import numpy
  from scipy import linalg
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import categorical
  from tensorflow_probability.python.distributions import mixture_same_family
  from tensorflow_probability.python.distributions import wishart
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 9 for calling the WishartTest obj's underlying member method code with example usage: obj.testVarianceBroadcast() without return types