docstr: Verifies that ndtri computation is correct.
code: def testNdtriDynamicShape(self):
      """Verifies that ndtri computation is correct."""
      with self.cached_session() as sess:
          if not special:
              return
  
          p = array_ops.placeholder(np.float32)
          p_ = np.linspace(0.0, 1.0, 50).astype(np.float32)
  
          x = special_math.ndtri(p)
          x_ = sess.run(x, feed_dict={p: p_})
  
          expected_x_ = special.ndtri(p_)
          self.assertAllClose(expected_x_, x_, atol=0.0)
  
imports: import collections
  import importlib
  import numpy
  from tensorflow.python.eager import backprop
  from tensorflow.python.eager import context
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gradient_checker
  from tensorflow.python.ops import gradients_impl
  from tensorflow.python.ops.distributions import special_math
  from tensorflow.python.platform import test
  from tensorflow.python.platform import tf_logging
label_desc: Use image node_id 3 for calling the NdtriTest obj's underlying member method code with example usage: obj.testNdtriDynamicShape() without return types