## Describe the bug transform_labels() output is not a probability distribution over labels, i.e. does not sum to 1. ### To Reproduce Check following code snippet #### Code sample ``` import ot import numpy as np ot_sinkhorn = ot.da.SinkhornTransport() Xs = np.array([[1, 0], [0, 0]]) ys = np.array([0, 1]) Xt = np.array([[1, 0], [2, 0], [3, 0]]) ot_sinkhorn.fit(Xs=Xs, Xt=Xt) print(ot_sinkhorn.transform_labels(ys)) ``` Output: ``` [[0.07946862 0.58719805] [0.33333333 0.33333333] [0.58719805 0.07946861]] ``` ### Expected behavior Expected the rows of output to sum to 1 (labels being a probability distribution over classes)