class_docstr: Bounds all real values into [0, 1] using a gaussian cumulative density function (cdf)
  Beware, cdf goes very fast to its limits.
  
  Parameters
  ----------
  lower: float
      lower bound
  upper: float
      upper bound
  eps: float
      small values to avoid hitting the bounds
  scale: float
      scaling factor of the density
  density: str
      either gaussian, or cauchy distributions
class_docstr_tok: ["Bounds","all","real","values","into","[","0",",","1","]","using","a","gaussian","cumulative","density","function","(","cdf",")","Beware",",","cdf","goes","very","fast","to","its","limits",".","Parameters","--","--","--","--","--","lower",":","float","lower","bound","upper",":","float","upper","bound","eps",":","float","small","values","to","avoid","hitting","the","bounds","scale",":","float","scaling","factor","of","the","density","density",":","str","either","gaussian",",","or","cauchy","distributions"]
code: def forward(self, x: np.ndarray) -> np.ndarray:
      return self._a * self._forw(x / self._scale) + self._b
  
imports: import uuid
  import itertools
  import numpy
  from scipy import stats
  import nevergrad.common.typing
  from .None import utils
label_desc: Use image node_id 2 for calling the CumulativeDensity obj's underlying member method code with example usage: obj.forward(x) and returns: unknown