code: def testGradientThroughConcentration0(self):
      concentration0 = tf.Variable(3.0)
      d = beta.Beta(
          concentration0=concentration0,
          concentration1=5.0,
          validate_args=True,
      )
      with tf.GradientTape() as tape:
          loss = -d.log_prob([0.25, 0.5, 0.9])
      grad = tape.gradient(loss, d.trainable_variables)
      self.assertLen(grad, 1)
      self.assertAllNotNone(grad)
  
imports: from absl.testing import parameterized
  import numpy
  from scipy import special
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import beta
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 34 for calling the BetaTest obj's underlying member method code with example usage: obj.testGradientThroughConcentration0() without return types