code: def testAssertionsProbs(self):
      x = tf.Variable([0.1, 0.7, 0.0])
      d = probit_bernoulli.ProbitBernoulli(probs=x, validate_args=True)
      self.evaluate(x.initializer)
      self.evaluate(d.entropy())
      with tf.control_dependencies([x.assign([0.1, -0.7, 0.0])]):
          with self.assertRaisesOpError("x >= 0 did not hold"):
              self.evaluate(d.entropy())
  
imports: import numpy
  from scipy import special
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import probit_bernoulli
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 3 for calling the ProbitBernoulliFromVariableTest obj's underlying member method code with example usage: obj.testAssertionsProbs() without return types