code: def testBetaQuantile(self, dt, rtol):
      shape = (30, 4, 5)
      a = 5.0 * np.random.random(shape).astype(dt)
      b = 5.0 * np.random.random(shape).astype(dt)
      p = np.random.uniform(low=0.0, high=1.0, size=shape).astype(dt)
      quantile = tf.function(beta.Beta(a, b).quantile)
      actual = self.evaluate(quantile(p))
      # Pass f64 values to avoid errors in scipy.
      self.assertAllClose(
          sp_stats.beta.ppf(
              p.astype(np.float64),
              a.astype(np.float64),
              b.astype(np.float64),
          ),
          actual,
          rtol=rtol,
          atol=1e-10,
      )
  
imports: from absl.testing import parameterized
  import numpy
  from scipy import special
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import beta
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 27 for calling the BetaTest obj's underlying member method code with example usage: obj.testBetaQuantile(dt, rtol) without return types