code: def testInvalidConcentration0(self):
      x = tf.Variable(1.0)
      dist = kumaraswamy.Kumaraswamy(
          concentration0=x, concentration1=1.0, validate_args=True
      )
      self.evaluate(x.initializer)
      self.assertIs(x, dist.concentration0)
      self.assertAllEqual([], self.evaluate(dist.event_shape_tensor()))
      with self.assertRaisesOpError(
          "Argument `concentration0` must be positive."
      ):
          with tf.control_dependencies([x.assign(-1.0)]):
              self.evaluate(dist.event_shape_tensor())
  
imports: import numpy
  from scipy import special
  from scipy import stats
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import kumaraswamy
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 28 for calling the KumaraswamyTest obj's underlying member method code with example usage: obj.testInvalidConcentration0() without return types