0316d552fa6005aaf0f6231eb9ca20441d5a2532,ot/da.py,OTDA_sinkhorn,fit,#OTDA_sinkhorn#Any#Any#Any#Any#Any#Any#,775

Before Change

        self.wt = wt

        self.M = dist(xs, xt, metric=self.metric)
        self.normalizeM(norm)
        self.G = sinkhorn(ws, wt, self.M, reg, **kwargs)
        self.computed = True

After Change

    

    def fit(self, xs, xt, reg=1, ws=None, wt=None, norm=None, **kwargs):
        Fit regularized domain adaptation between samples is xs and xt
        (with optional weights)
        self.xs = xs
        self.xt = xt

        if wt is None:
            wt = unif(xt.shape[0])
        if ws is None:
            ws = unif(xs.shape[0])

        self.ws = ws
        self.wt = wt

        self.M = dist(xs, xt, metric=self.metric)
        self.M = cost_normalization(self.M, norm)
        self.G = sinkhorn(ws, wt, self.M, reg, **kwargs)
        self.computed = True

Instances