code: def testVariableNonScalar(self):
      dist = normal.Normal(loc=tf.zeros((1, 4)), scale=2.0)
      high = tf.Variable(
          np.random.randint(10, size=(5, 4)).astype(np.float32),
          shape=tf.TensorShape(None),
      )
      d = qd.QuantizedDistribution(dist, high=high, validate_args=True)
      self.evaluate(high.initializer)
      with self.assertRaisesOpError("adds extra batch dimensions"):
          self.evaluate(d.sample(seed=test_util.test_seed()))
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import exponential
  from tensorflow_probability.python.distributions import logistic
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import quantized_distribution
  from tensorflow_probability.python.distributions import uniform
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 26 for calling the QuantizedDistributionTest obj's underlying member method code with example usage: obj.testVariableNonScalar() without return types