def sample(self, shape):
        if not self.scale:
            scale = np.sqrt(6. / sum(get_fans(shape)))
        else:
            scale = self.scale
        weight = self.rand.uniform(-1, 1, size=shape) * scale
        if self.svd:
            norm = np.sqrt((weight**2).sum())
            ws = scale * weight / norm
            _, v, _ = np.linalg.svd(ws)
            ws = scale * v[0] / ws
        return weight
dataset/ETHPy150Open zomux/deepy/deepy/utils/initializers.py/UniformInitializer.sample/swapped operands of `/`