code: def testAssertionsProbs(self):
      x = tf.Variable([0.1, 0.7, 0.0])
      with self.assertRaisesOpError("Argument `probs` must sum to 1."):
          d = multinomial.Multinomial(
              total_count=2.0, probs=x, validate_args=True
          )
          self.evaluate([v.initializer for v in d.variables])
          self.evaluate(d.mean())
  
imports: import unittest
  from absl.testing import parameterized
  import hypothesis
  from hypothesis import strategies
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import identity
  from tensorflow_probability.python.distributions import binomial
  from tensorflow_probability.python.distributions import hypothesis_testlib
  from tensorflow_probability.python.distributions import multinomial
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import hypothesis_testlib
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
  from tensorflow_probability.python.util import deferred_tensor
label_desc: Use image node_id 3 for calling the MultinomialFromVariableTest obj's underlying member method code with example usage: obj.testAssertionsProbs() without return types