code: def testLogProbGradientThroughConcentration1(self):
      concentration1 = tf.Variable(3.0)
      d = beta_binomial.BetaBinomial(
          total_count=10,
          concentration1=concentration1,
          concentration0=5.0,
          validate_args=True,
      )
      with tf.GradientTape() as tape:
          loss = -d.log_prob([3.0, 4.0, 5.0])
      grad = tape.gradient(loss, d.trainable_variables)
      self.assertLen(grad, 1)
      self.assertAllNotNone(grad)
  
imports: import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import bernoulli
  from tensorflow_probability.python.distributions import beta_binomial
  from tensorflow_probability.python.distributions import dirichlet_multinomial
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 5 for calling the BetaBinomialFromVariableTest obj's underlying member method code with example usage: obj.testLogProbGradientThroughConcentration1() without return types