code: def testAssertsPositiveConcentration1(self):
      concentration1 = tf.Variable([1.0, 2.0, -3.0])
      self.evaluate(concentration1.initializer)
      with self.assertRaisesOpError(
          "`concentration1` parameter must be positive."
      ):
          d = sigmoid_beta.SigmoidBeta(
              concentration1=concentration1,
              concentration0=[5.0],
              validate_args=True,
          )
          self.evaluate(d.sample(seed=test_util.test_seed()))
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import invert
  from tensorflow_probability.python.bijectors import sigmoid
  from tensorflow_probability.python.distributions import beta
  from tensorflow_probability.python.distributions import sigmoid_beta
  from tensorflow_probability.python.distributions import transformed_distribution
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 15 for calling the SigmoidBetaTest obj's underlying member method code with example usage: obj.testAssertsPositiveConcentration1() without return types