(self, theta)
Computes the gradient of the prior with
        respect to theta.

        Parameters
        ----------
        theta : (D,) numpy array
            Hyperparameter configuration in log space

        Returns
        -------
        (D) np.array
            The gradient of the prior at theta.
Computes the gradient of the prior with
        respect to theta.
Computes the gradient of the prior with respect to theta .
def gradient(self, theta):
        """
        Computes the gradient of the prior with
        respect to theta.

        Parameters
        ----------
        theta : (D,) numpy array
            Hyperparameter configuration in log space

        Returns
        -------
        (D) np.array
            The gradient of the prior at theta.
        """
        pass
def gradient ( self , theta ) : pass