我试图在sagemaker中使用LinearLearner模型生成record_set。 因此，起初我将train_data作为ndarray传递，并将标签作为1-darray

labels_vector=np.array(train_labels).flatten()
formatted_train_data = estimator.record_set(train=train_features,labels=labels_vector)

但是它给了我TypeError: only size-1 arrays can be converted to Python scalars的错误 因此搜索后，我使用np.vectorize将其作为矢量传递

labels_vector=np.array(train_labels).flatten()
formatted_train_data = estimator.record_set(train=train_features,labels=np.vectorize(labels_vector))

然后提高AttributeError: 'vectorize' object has no attribute 'shape'的Err