code: def testGradientThroughConcentration(self):
      concentration = tf.Variable(3.0)
      d = gp.GeneralizedPareto(
          loc=0,
          scale=1,
          concentration=concentration,
          validate_args=True,
      )
      with tf.GradientTape() as tape:
          loss = -d.log_prob([1.0, 2.0, 4.0])
      grad = tape.gradient(loss, d.trainable_variables)
      self.assertLen(grad, 1)
      self.assertAllNotNone(grad)
  
imports: import hypothesis
  import hypothesis.strategies
  import numpy
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import generalized_pareto
  from tensorflow_probability.python.internal import hypothesis_testlib
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 17 for calling the GeneralizedParetoTest obj's underlying member method code with example usage: obj.testGradientThroughConcentration() without return types