code: def testHalfNormalQuantile(self):
      batch_size = 50
      scale = self._rng.rand(batch_size) + 1.0
      p = np.linspace(0.0, 1.0, batch_size).astype(np.float64)
  
      halfnorm = half_normal.HalfNormal(scale=scale, validate_args=True)
      x = halfnorm.quantile(p)
      self._testBatchShapes(halfnorm, x)
  
      expected_x = sp_stats.halfnorm(scale=scale).ppf(p)
      self.assertAllClose(expected_x, self.evaluate(x), atol=0)
  
imports: from absl.testing import parameterized
  import numpy
  from scipy import stats
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import half_normal
  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 13 for calling the HalfNormalTest obj's underlying member method code with example usage: obj.testHalfNormalQuantile() without return types