code: def ndtri(p, name="ndtri"):
      """The inverse of the CDF of the Normal distribution function.
  
      Returns x such that the area under the pdf from minus infinity to x is equal
      to p.
  
      A piece-wise rational approximation is done for the function.
      This is a port of the implementation in netlib.
  
      Args:
        p: `Tensor` of type `float32`, `float64`.
        name: Python string. A name for the operation (default="ndtri").
  
      Returns:
        x: `Tensor` with `dtype=p.dtype`.
  
      Raises:
        TypeError: if `p` is not floating-type.
      """
  
      with ops.name_scope(name, values=[p]):
          p = ops.convert_to_tensor(p, name="p")
          if p.dtype.as_numpy_dtype not in [np.float32, np.float64]:
              raise TypeError(
                  "p.dtype=%s is not handled, see docstring for supported types."
                  % p.dtype
              )
          return _ndtri(p)
  
file_path: tensorflow/tensorflow/python/ops/distributions/special_math.py
imports: import numpy
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
label_desc: Use image node_id 3 for calling a global function with example usage: ndtri(p, name) and returns: _ndtri