code: def testAssertionsProbsMutation(self):
      probs = tf.Variable([0.5])
  
      d = binomial_lib.Binomial(
          total_count=10, probs=probs, validate_args=True
      )
      self.evaluate([v.initializer for v in d.variables])
      self.evaluate(d.probs_parameter())
  
      self.evaluate(probs.assign([1.25]))
      with self.assertRaisesOpError(
          "probs has components greater than 1"
      ):
          self.evaluate(d.probs_parameter())
  
      self.evaluate(probs.assign([-0.5]))
      with self.assertRaisesOpError("x >= 0 did not hold"):
          self.evaluate(d.probs_parameter())
  
      self.evaluate(probs.assign([0.75]))
      self.evaluate(d.probs_parameter())
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import binomial
  from tensorflow_probability.python.internal import implementation_selection
  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 BinomialFromVariableTest obj's underlying member method code with example usage: obj.testAssertionsProbsMutation() without return types