def _param_grad_helper(self, dL_dK, X, X2, target):
self._K_computations(X, X2)<EOL>self._dK_computations(dL_dK)<EOL>if X2==None:<EOL><INDENT>gmapping = self.mapping.df_dtheta(<NUM_LIT:2>*self._dL_dl[:, None], X)<EOL><DEDENT>else:<EOL><INDENT>gmapping = self.mapping.df_dtheta(self._dL_dl[:, None], X)<EOL>gmapping += self.mapping.df_dtheta(self._dL_dl_two[:, None], X2)<EOL><DEDENT>target+= np.hstack([(dL_dK*self._K_dvar).sum(), gmapping])<EOL>
Derivative of the covariance with respect to the parameters.