class_docstr: Differential evolution.
  
  Default pop size equal to 30
  We return the mean of the individuals with fitness better than median, which might be stupid sometimes.
  CR =.5, F1=.8, F2=.8, curr-to-best.
  Initial population: pure random.
class_docstr_tok: ["Differential","evolution",".","Default","pop","size","equal","to","30","We","return","the","mean","of","the","individuals","with","fitness","better","than","median",",","which","might","be","stupid","sometimes",".","CR","=.5",",","F1=.8",",","F2=.8",",","curr-to-best",".","Initial","population",":","pure","random","."]
code: def set_objective_weights(self, weights: tp.Any) -> None:
      self.objective_weights = weights
  
imports: import warnings
  import numpy
  import nevergrad.common.typing
  from nevergrad.parametrization import parameter
  from .None import metamodel
  from .None import base
  from .None import oneshot
label_desc: Use image node_id 2 for calling the _DE obj's underlying member method code with example usage: obj.set_objective_weights(weights) without return types