class_docstr: Hacky way to sample in the space defined by the parametrization.
  Given an vector of values between 0 and 1,
  the transform method samples in the bounds if provided,
  or using the provided function otherwise.
  This is used for samplers.
  Code of parametrization and/or this helper should definitely be
  updated to make it simpler and more robust
class_docstr_tok: ["Hacky","way","to","sample","in","the","space","defined","by","the","parametrization",".","Given","an","vector","of","values","between","0","and","1",",","the","transform","method","samples","in","the","bounds","if","provided",",","or","using","the","provided","function","otherwise",".","This","is","used","for","samplers",".","Code","of","parametrization","and\/or","this","helper","should","definitely","be","updated","to","make","it","simpler","and","more","robust"]
docstr: Transform from [0, 1] to standardized space
docstr_tok: ["Transform","from","[","0",",","1","]","to","standardized","space"]
code: def backward(self, x: tp.ArrayLike) -> np.ndarray:
      """Transform from [0, 1] to standardized space"""
      return self._apply(x, forward=False)
  
imports: import warnings
  import contextlib
  import itertools
  import numpy
  import nevergrad.common.typing
  from .None import core
  from .None import container
  from .None import _layering
  from .None import _datalayers
  from .None import data
  from .None import choice
  from .None import transforms
label_desc: Use image node_id 3 for calling the Normalizer obj's underlying member method code with example usage: obj.backward(x) and returns: self