docstr: Verifies that ndtri has finite gradients at interesting points.
code: def _baseNdtriFiniteGradientTest(self, dtype):
      """Verifies that ndtri has finite gradients at interesting points."""
      # Tests gradients at 0, 1, and piece-wise boundaries.
      p = constant_op.constant(
          np.array(
              [
                  0.0,
                  np.exp(-32.0),
                  np.exp(-2.0),
                  1.0 - np.exp(-2.0),
                  1.0 - np.exp(-32.0),
                  1.0,
              ]
          ).astype(dtype)
      )
      # Not having the lambda sanitizer means we'd get an `IndexError` whenever
      # the user supplied function has default args.
      _, grads = _value_and_gradient(
          lambda x: special_math.ndtri(x), p
      )  # pylint: disable=unnecessary-lambda
      self.assertAllFinite(self.evaluate(grads[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 4 for calling the NdtriTest obj's underlying member method code with example usage: obj._baseNdtriFiniteGradientTest(dtype) without return types