trying to break BaggingClassifier on sparse input

sparse_input_test.py

from sklearn.datasets import load_iris
from scipy.sparse import csr_matrix, csc_matrix
from sklearn.neighbors import KNeighborsClassifier
from sklearn.ensemble import BaggingClassifier

iris = load_iris()
data = iris['data']
labels = iris['target']
csc = csc_matrix(data)

knn = KNeighborsClassifier()
csc_knn = KNeighborsClassifier()

bag = BaggingClassifier(KNeighborsClassifier())
sparse_bag = BaggingClassifier(KNeighborsClassifier())

knn.fit(data, labels)
csc_knn.fit(csc, labels)
bag.fit(data, labels)
sparse_bag.fit(csc, labels)

print(knn.predict(data[50]))
print(csc_knn.predict(data[50]))
print(sparse_bag.predict([data[50]]))
print(labels[50])