code: def testAssertsPositiveScale(self):
      scale = tf.Variable([1.0, 2.0, -3.0])
      with self.assertRaisesOpError(
          "Argument `scale` must be positive."
      ):
          d = logistic.Logistic(loc=0, scale=scale, validate_args=True)
          self.evaluate([v.initializer for v in d.variables])
          self.evaluate(d.sample(seed=test_util.test_seed()))
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import logistic
  from tensorflow_probability.python.internal import reparameterization
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 14 for calling the LogisticTest obj's underlying member method code with example usage: obj.testAssertsPositiveScale() without return types