code: def test_fit_squared_loss(bin_dense_train_data):
      bin_dense, bin_target = bin_dense_train_data
      clf = CDClassifier(
          C=1.0,
          random_state=0,
          penalty="l2",
          loss="squared",
          max_iter=100,
      )
      clf.fit(bin_dense, bin_target)
      np.testing.assert_almost_equal(
          clf.score(bin_dense, bin_target), 0.99
      )
      y = bin_target.copy()
      y[y == 0] = -1
      np.testing.assert_array_almost_equal(
          np.dot(bin_dense, clf.coef_.ravel()) - y, clf.errors_.ravel()
      )
  
imports: import numpy
  import pytest
  from sklearn.datasets import load_digits
  from sklearn.preprocessing import LabelBinarizer
  from lightning.impl.primal_cd import CDClassifier, CDRegressor
  from lightning.impl.tests.utils import check_predict_proba
label_desc: Use image node_id 19 for calling a global function with example usage: test_fit_squared_loss(bin_dense_train_data) without return types