code: def __call__(self, clf):
      clf._finalize_coef()
      y_pred = clf.decision_function(self.X).ravel()
      loss = (np.maximum(1 - self.y * y_pred, 0) ** 2).mean()
      coef = clf.coef_.ravel()
      regul = 0.5 * clf.alpha * np.dot(coef, coef)
      self.obj.append(loss + regul)
  
imports: import numpy
  import pytest
  from scipy import sparse
  from sklearn.datasets import make_classification
  from lightning.impl.base import BaseClassifier
  from lightning.impl.dataset_fast import get_dataset
  from lightning.classification import SAGClassifier, SAGAClassifier
  from lightning.regression import SAGRegressor, SAGARegressor
  from lightning.impl.sgd_fast import ModifiedHuber
  from lightning.impl.sgd_fast import SmoothHinge
  from lightning.impl.sgd_fast import SquaredHinge
  from lightning.impl.sgd_fast import Log
  from lightning.impl.sgd_fast import SquaredLoss
  from lightning.impl.sag import get_auto_step_size
  from lightning.impl.tests.utils import check_predict_proba
label_desc: Use image node_id 2 for calling the Callback obj's underlying member method code with example usage: obj.__call__(clf) without return types