code: def testGradientThroughConcentration0(self):
      concentration0 = tf.Variable(3.0)
      d = sigmoid_beta.SigmoidBeta(
          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: import numpy
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import invert
  from tensorflow_probability.python.bijectors import sigmoid
  from tensorflow_probability.python.distributions import beta
  from tensorflow_probability.python.distributions import sigmoid_beta
  from tensorflow_probability.python.distributions import transformed_distribution
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 17 for calling the SigmoidBetaTest obj's underlying member method code with example usage: obj.testGradientThroughConcentration0() without return types