code: def testInvalidProbabilities(self):
      invalid_probabilities = [1.01, 2.0]
      for p in invalid_probabilities:
          with self.assertRaisesOpError(
              "probs has components greater than 1"
          ):
              dist = binomial_lib.Binomial(
                  total_count=10, probs=p, validate_args=True
              )
              self.evaluate(dist.probs_parameter())
  
      invalid_probabilities = [-0.01, -3.0]
      for p in invalid_probabilities:
          with self.assertRaisesOpError("x >= 0 did not hold"):
              dist = binomial_lib.Binomial(
                  total_count=10, probs=p, validate_args=True
              )
              self.evaluate(dist.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 BinomialTest obj's underlying member method code with example usage: obj.testInvalidProbabilities() without return types