class_docstr: Compute `Y = g(X) = NormalCDF(x)`.
  
  This bijector maps inputs from `[-inf, inf]` to `[0, 1]`. The inverse of the
  bijector applied to a uniform random variable `X ~ U(0, 1)` gives back a
  random variable with the
  [Normal distribution](https://en.wikipedia.org/wiki/Normal_distribution):
  
  ```none
  Y ~ Normal(0, 1)
  pdf(y; 0., 1.) = 1 / sqrt(2 * pi) * exp(-y ** 2 / 2)
  ```
code: def _inverse(self, y):
      with tf.control_dependencies(self._assertions(y)):
          return tf.math.ndtri(y)
  
file_path: probability/tensorflow_probability/python/bijectors/normal_cdf.py
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import bijector
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import special_math
label_desc: Use image node_id 5 for calling the NormalCDF obj's underlying member method code with example usage: obj._inverse(y) and returns: tf