code: def test_multivariate_gradient_descent():
      w_exp = np.array([[0.4], [-0.5]])
      b_exp = np.array([0.0])
      gd_lr = LinearRegression(
          method="sgd",
          eta=0.001,
          epochs=500,
          minibatches=1,
          random_seed=0,
      )
      gd_lr.fit(X_rm_lstat_std, y_std)
      assert_almost_equal(gd_lr.w_, w_exp, decimal=1)
      assert_almost_equal(gd_lr.b_, b_exp, decimal=1)
  
imports: import numpy
  from numpy.testing import assert_almost_equal
  from sklearn.base import clone
  from mlxtend.data import boston_housing_data
  from mlxtend.regressor import LinearRegression
label_desc: Use image node_id 11 for calling a global function with example usage: test_multivariate_gradient_descent() without return types