code: def testGradientThroughNonVariableParams(self):
      df = tf.convert_to_tensor(13.37)
      d = chi2.Chi2(df, validate_args=True)
      with tf.GradientTape() as tape:
          tape.watch(d.df)
          loss = -d.log_prob([1.0, 2.0, 3.0])
      grad = tape.gradient(loss, [d.df])
      self.assertLen(grad, 1)
      self.assertAllNotNone(grad)
  
imports: import numpy
  from scipy import special
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import chi2
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 11 for calling the Chi2Test obj's underlying member method code with example usage: obj.testGradientThroughNonVariableParams() without return types