base_models.py 文件源码

def _forward_prop_deterministic_thru_post(self, x, return_info=False):
        """Propagate deterministic inputs thru posterior

        Args:
            x (float): input values, size K x Din
            return_info (bool, optional): Description

        Returns:
            float, size K x Dout: output means
            float, size K x Dout: output variances
        """
        psi0 = np.exp(2 * self.sf)
        psi1 = compute_kernel(2 * self.ls, 2 * self.sf, x, self.zu)
        mout = np.einsum('nm,dm->nd', psi1, self.A)
        Bpsi2 = np.einsum('dab,na,nb->nd', self.B_det, psi1, psi1)
        vout = psi0 + Bpsi2
        if return_info:
            return mout, vout, psi1
        else:
            return mout, vout