class_docstr: The abstract Model for Bayesian Optimization
docstr: Get the gradients of the predicted mean and variance at X.
docstr_tok: ["Get","the","gradients","of","the","predicted","mean","and","variance","at","X","."]
code: def predict_withGradients(self, X):
      "Get the gradients of the predicted mean and variance at X."
      return
  
imports: import abc
  from six import with_metaclass
label_desc: Use image node_id 3 for calling the BOModel obj's underlying member method code with example usage: obj.predict_withGradients(X) without return types