generic_wrapper.py 文件源码

def get_preds_true_for_task(self,train_tasks, test_tasks, param_dict):
        t = param_dict['task_num']
        X = train_tasks[t]['X']
        y = train_tasks[t]['Y']

        test_X = test_tasks[t]['X']
        true_y = list(test_tasks[t]['Y'].flatten())

        if len(y)==0 or len(X)==0 or len(test_X) == 0 or len(true_y)==0:
            return None, None

        if self.cant_train_with_one_class and len(np.unique(y))==1:
            preds = list(np.unique(y)[0]*np.ones(len(true_y)))
        else:
            preds = self.train_and_predict_task(t, X, y, test_X, param_dict)

        return preds, true_y