OneVsRestCalibrator + IsotonicCalibration output probabilities have a wrong shape

[perellonieto]

from sklearn.naive_bayes import GaussianNB
from pycalib.models import CalibratedModel, OneVsRestCalibrator, IsotonicCalibration
from sklearn import datasets

X, y = datasets.make_classification(n_classes=3, n_clusters_per_class=1)

cal = CalibratedModel(GaussianNB(), method=OneVsRestCalibrator(IsotonicCalibration()))
cal.fit(X, y)
cal.predict_proba(X).shape

returns the following shape

(2, 100, 3)

While other calibrators (eg. BinningCalibration, SigmoidCalibration) return the correct shape

(100, 3)