code: def testQuantile(self):
      batch_size = 6
      concentration = np.linspace(1.0, 12.0, batch_size).astype(
          np.float32
      )[..., np.newaxis]
      rate = np.linspace(3.0, 18.0, batch_size).astype(np.float32)[
          ..., np.newaxis
      ]
      x = np.linspace(0.0, 1.0, 13).astype(np.float32)
      d = exp_gamma_lib.ExpGamma(
          concentration=concentration, rate=rate, validate_args=True
      )
      d_lr = exp_gamma_lib.ExpGamma(
          concentration=concentration,
          log_rate=tf.math.log(rate),
          validate_args=True,
      )
      quantile = d.quantile(x)
      self.assertEqual(quantile.shape, (6, 13))
      expected_quantile = tfb.Log()(
          gamma.Gamma(concentration=concentration, rate=rate)
      ).quantile(x)
      self.assertAllClose(quantile, expected_quantile)
      self.assertAllClose(d_lr.quantile(x), expected_quantile)
  
imports: from absl.testing import parameterized
  import numpy
  from scipy import misc
  from scipy import special
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import exp
  from tensorflow_probability.python.distributions import exp_gamma
  from tensorflow_probability.python.distributions import gamma
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 7 for calling the ExpGammaTest obj's underlying member method code with example usage: obj.testQuantile() without return types