code: def testInverseGammaQuantile(self):
      batch_size = 6
      alpha = np.linspace(2.0, 10.0, batch_size).astype(np.float32)[
          ..., np.newaxis
      ]
      beta = np.linspace(4.0, 17.0, batch_size).astype(np.float32)[
          ..., np.newaxis
      ]
      x = np.linspace(0.0, 1.0, 13).astype(np.float32)
      inv_gamma = inverse_gamma.InverseGamma(
          concentration=alpha, scale=beta, validate_args=True
      )
      expected_quantile = stats.invgamma.ppf(x, alpha, scale=beta)
  
      quantile = inv_gamma.quantile(x)
      self.assertEqual(quantile.shape, (batch_size, 13))
      self.assertAllClose(
          self.evaluate(quantile), expected_quantile, rtol=3e-6
      )
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import inverse_gamma
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 6 for calling the InverseGammaTest obj's underlying member method code with example usage: obj.testInverseGammaQuantile() without return types