code: def testAssertionNonNegativeTotalCount(self):
      total_count = tf.Variable(-1.0)
      concentration = tf.constant([1.0, 1.0, 1.0])
  
      with self.assertRaisesOpError("must be non-negative"):
          d = dm.DirichletMultinomial(
              total_count, concentration, validate_args=True
          )
          self.evaluate([v.initializer for v in d.variables])
          self.evaluate(d.mean())
  
imports: import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import dirichlet_multinomial
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 2 for calling the DirichletMultinomialFromVariableTest obj's underlying member method code with example usage: obj.testAssertionNonNegativeTotalCount() without return types