b84b7df8bf23aee3cb98b0390aa69f7ee31fe30a,GPflow/model.py,GPModel,predict_y,#GPModel#Any#,194

Before Change

        
        Compute the mean and variance of held-out data at the points Xnew
        
        tf_Xnew = tf.placeholder("float64")
        with self.tf_mode():
            pred_f_mean, pred_f_var = self.build_predict(tf_Xnew)
            pred_y_mean, pred_y_var = self.likelihood.predict_mean_and_var(pred_f_mean, pred_f_var)
        return self._session.run([pred_y_mean, pred_y_var],
                                 feed_dict={self._free_vars:self.get_free_state(), tf_Xnew:Xnew })

    def predict_density(self, Xnew, Ynew):
        
        Compute the (log) density of the data Ynew at the points Xnew

After Change

        Compute the mean and variance of held-out data at the points Xnew
        
        pred_f_mean, pred_f_var = self.build_predict(Xnew)
        return self.likelihood.predict_mean_and_var(pred_f_mean, pred_f_var)


    @AutoFlow(tf.placeholder(tf.float64), tf.placeholder(tf.float64))
    def predict_density(self, Xnew, Ynew):

Instances