code: def test_l2_regularization_sgd():
      lr = LogisticRegression(
          eta=0.01,
          epochs=100,
          minibatches=len(y),
          l2_lambda=1.0,
          random_seed=1,
      )
      lr.fit(X, y)
      y_pred = lr.predict(X)
      expect_weights = np.array([[0.24], [0.35]])
  
      np.testing.assert_almost_equal(lr.w_, expect_weights, 2)
      y_pred = lr.predict(X)
      acc = np.sum(y == y_pred, axis=0) / float(X.shape[0])
      assert acc == 0.97, "Acc: %s" % acc
  
imports: import sys
  import numpy
  from sklearn.base import clone
  from mlxtend.classifier import LogisticRegression
  from mlxtend.data import iris_data
  from mlxtend.utils import assert_raises
label_desc: Use image node_id 12 for calling a global function with example usage: test_l2_regularization_sgd() without return types