ss_vae_M2.py 文件源码

def classifier(self, xs):
        """
        classify an image (or a batch of images)

        :param xs: a batch of scaled vectors of pixels from an image
        :return: a batch of the corresponding class labels (as one-hots)
        """
        # use the trained model q(y|x) = categorical(alpha(x))
        # compute all class probabilities for the image(s)
        alpha = self.encoder_y.forward(xs)

        # get the index (digit) that corresponds to
        # the maximum predicted class probability
        res, ind = torch.topk(alpha, 1)

        # convert the digit(s) to one-hot tensor(s)
        ys = Variable(torch.zeros(alpha.size()))
        ys = ys.scatter_(1, ind, 1.0)
        return ys