Python scikit-learn：无法克隆对象...作为构造函数似乎没有设置参数 [英] Python scikit-learn: Cannot clone object... as the constructor does not seem to set parameter

问题描述

我修改了 BernoulliRBM 类的scikit学习使用softmax可见单位的组。在这个过程中，我添加了一个额外的Numpy数组 visible_config 作为类属性，在构造函数中初始化如下：

I modified the BernoulliRBM class of scikit-learn to use groups of softmax visible units. In the process, I added an extra Numpy array visible_config as a class attribute which is initialized in the constructor as follows using:

self.visible_config = np.cumsum(np.concatenate((np.asarray([0]),
                                visible_config), axis=0))

其中 visible_config 是一个Numpy数组，构造函数。当我直接使用 fit（）函数来训练模型时，代码运行没有错误。但是，当我使用 GridSearchCV 结构时，会出现以下错误：

where visible_config is a Numpy array passed as an input to the constructor. The code runs without errors when I directly use the fit() function to train the model. However, when I use the GridSearchCV structure, I get the following error

Cannot clone object SoftmaxRBM(batch_size=100, learning_rate=0.01, n_components=100, n_iter=100,
  random_state=0, verbose=True, visible_config=[ 0 21 42 63]), as the constructor does not seem to set parameter visible_config

这似乎是类的实例之间的等式检查中的一个问题，其副本由 sklearn.base.clone 创建因为 visible_config 无法正确复制。我不知道如何解决这个问题。它在文档中说， sklearn.base.clone 使用 deepcopy（），所以不应该 visible_config 也会被复制吗？有人可以解释一下我可以在这里试试吗？非常感谢！

This seems to be a problem in the equality check between the instance of the class and its copy created by sklearn.base.clone because visible_config does not get copied correctly. I'm not sure how to fix this. It says in the documentation that sklearn.base.clone uses a deepcopy(), so shouldn't visible_config also get copied? Can someone please explain what I can try here? Thanks!

推荐答案

没有看到你的代码，很难确定是什么地方出了问题，但是你违反了scikit-learn API约定。估计器中的构造函数应仅将属性设置为用户作为参数传递的值。所有计算都应在 fit 中进行，如果 fit 需要存储计算结果，一个带尾随下划线的属性（ _ ）。这个约定是 clone 和元估计器如 GridSearchCV 工作的原因。

Without seeing your code, it's hard to tell exactly what goes wrong, but you are violating a scikit-learn API convention here. The constructor in an estimator should only set attributes to the values the user passes as arguments. All computation should occur in fit, and if fit needs to store the result of a computation, it should do so in an attribute with a trailing underscore (_). This convention is what makes clone and meta-estimators such as GridSearchCV work.

（*）如果您在主代码库中看到违反此规则的估计值：这将是一个错误，欢迎补丁。

(*) If you ever see an estimator in the main codebase that violates this rule: that would be a bug, and patches are welcome.

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