code: def testGradientLogits(self):
      x = tf.Variable([-1.0, 1])
      self.evaluate(x.initializer)
      d = relaxed_bernoulli.RelaxedBernoulli(
          0.5, logits=x, validate_args=True
      )
      with tf.GradientTape() as tape:
          loss = -d.log_prob([0, 1])
      g = tape.gradient(loss, d.trainable_variables)
      self.assertLen(g, 1)
      self.assertAllNotNone(g)
  
imports: import numpy
  import scipy.special
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import relaxed_bernoulli
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 1 for calling the RelaxedBernoulliFromVariableTest obj's underlying member method code with example usage: obj.testGradientLogits() without return types