code: def erfinv(x: np.ndarray) -> np.ndarray:
      zeros = np.zeros_like(x)
  
      w = -np.log((1.0 - x) * (1.0 + x))
      mask_lesser = w < (zeros + 5.0)
  
      w = np.where(mask_lesser, w - 2.5, np.sqrt(w) - 3.0)
  
      coefficients_lesser = [
          2.81022636e-08,
          3.43273939e-07,
          -3.5233877e-06,
          -4.39150654e-06,
          0.00021858087,
          -0.00125372503,
          -0.00417768164,
          0.246640727,
          1.50140941,
      ]
  
      coefficients_greater_equal = [
          -0.000200214257,
          0.000100950558,
          0.00134934322,
          -0.00367342844,
          0.00573950773,
          -0.0076224613,
          0.00943887047,
          1.00167406,
          2.83297682,
      ]
  
      p = np.where(
          mask_lesser,
          coefficients_lesser[0] + zeros,
          coefficients_greater_equal[0] + zeros,
      )
  
      for c_l, c_ge in zip(
          coefficients_lesser[1:], coefficients_greater_equal[1:]
      ):
          c = np.where(mask_lesser, c_l + zeros, c_ge + zeros)
          p = c + p * w
  
      return p * x
  
imports: from typing import Callable, Iterator, List, Optional, Tuple, Type
  import numpy
  from toolz import valmap
  from gluonts.core.component import validated, tensor_to_numpy
  from gluonts.dataset.common import DataEntry
  from gluonts.exceptions import assert_data_error
  from ._base import FlatMapTransformation, MapTransformation, SimpleTransformation
label_desc: Use image node_id 2 for calling a global function with example usage: erfinv(x) and returns: unknown