def test_gradient_checking(): nn3 = NeuralNetMLP(n_output=len(np.unique(y)), n_features=X_std.shape[1], n_hidden=25, l2=0.0, l1=0.0, epochs=1, eta=0.01, alpha=0.0, decrease_const=0.0, minibatches=1, shuffle_init=False, shuffle_epoch=False, random_seed=1) for epoch in range(10): eucldist = nn3._gradient_checking(X=X_std, y=y) assert eucldist < 1e-07, 'Gradient difference is %s' % eucldist