code: def test_fit_reg_squared_multiple_outputs(train_data):
      X, y = train_data
      reg = CDRegressor(
          C=1.0,
          random_state=0,
          penalty="l2",
          loss="squared",
          max_iter=100,
      )
      Y = np.zeros((len(y), 2))
      Y[:, 0] = y
      Y[:, 1] = y
      reg.fit(X, Y)
      y_pred = reg.predict(X)
      assert y_pred.shape[0] == len(y)
      assert y_pred.shape[1] == 2
  
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 30 for calling a global function with example usage: test_fit_reg_squared_multiple_outputs(train_data) without return types