class_docstr: Try max_constraints_trials random explorations for satisfying constraints.
  The finally chosen point, if it does not satisfy constraints, is penalized as shown in the penalty function,
  using coeffcieints mentioned here.
  
  
  Possibly unstable.
docstr: Parameters
  ----------
      max_trials: int
          number of random tries for satisfying constraints.
      penalty: float
          multiplicative factor on the constraint penalization.
      penalty_exponent: float
          exponent, usually close to 1 and slightly greater than 1.
docstr_tok: ["Parameters","--","--","--","--","--","max_trials",":","int","number","of","random","tries","for","satisfying","constraints",".","penalty",":","float","multiplicative","factor","on","the","constraint","penalization",".","penalty_exponent",":","float","exponent",",","usually","close","to","1","and","slightly","greater","than","1","."]
code: def update(
      self,
      max_trials: tp.Optional[int] = None,
      penalty_factor: tp.Optional[float] = None,
      penalty_exponent: tp.Optional[float] = None,
  ) -> None:
      """
      Parameters
      ----------
          max_trials: int
              number of random tries for satisfying constraints.
          penalty: float
              multiplicative factor on the constraint penalization.
          penalty_exponent: float
              exponent, usually close to 1 and slightly greater than 1.
      """
      for x, y in locals().items():
          if y is not None and x != "self" and not x.startswith("_"):
              setattr(self, x, y)
      if self.penalty_exponent < 1:
          raise ValueError(
              "Penalty exponent needs to be equal or greater than 1"
          )
  
imports: import math
  import operator
  import numpy
  from nevergrad.parametrization import parameter
  from nevergrad.parametrization.utils import float_penalty
  import nevergrad.common.typing
  from nevergrad.common.tools import OrderedSet
label_desc: Use image node_id 3 for calling the ConstraintManager obj's underlying member method code with example usage: obj.update(max_trials, penalty_factor, penalty_exponent) without return types