import numpy as np
from scipy import sparse
from sklearn import svm
from nose.tools import assert_raises

X = np.array([[-2, -1], [-1, -1], [-1, -2], [1, 1], [1, 2], [2, 1]])
X_sp = sparse.lil_matrix(X)
Y = [1, 1, 1, 2, 2, 2]

sp = svm.sparse.SVC(C=1, kernel=lambda x, y: x * y.T, probability=True)
assert_raises(ValueError, sp.fit, X_sp, Y)