code: def predict_proba(self, L):
          
          n = L.shape[0]
          Y_p = np.random.rand(n, self.k)
          Y_p /= Y_p.sum(axis=1).reshape(-1, 1)
          return Y_p
docs: Args:
              L: An [n, m] scipy.sparse matrix of labels
          Returns:
              output: A [n, k] np.ndarray of probabilistic labels