model.py 文件源码

def batched_gram(self, fmap):
        # (batch, featuremaps, height*width)
        fmap=fmap.flatten(ndim=3)

        # The T.prod term can't be taken outside as a T.mean in style_loss(), since the width and height of the image might vary
        if self.net_type == 0:
            return T.batched_dot(fmap, fmap.dimshuffle(0,2,1))/T.prod(fmap.shape[-2:])
        elif self.net_type == 1:
            return T.batched_dot(fmap, fmap.dimshuffle(0,2,1))/T.prod(fmap.shape[-1])