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我有这样的代码:

def new_predict(y):
    _text_data = pad_sequences(y, 350, padding="post", truncating="post")
    return np.array([[float(1-m), float(m)] for m in model.predict(_text_data)])


if __name__ == '__main__':

    model = tf.keras.models.load_model(path)

    doc = 'sample Text'

    x, len_vocab = preprocess_data(path)

    test_padded = pad_sequences(x, 350, padding="post", truncating="post")
    model.predict(test_padded[-1].reshape(1, -1))
    explainer = LimeTextExplainer()
    exp = explainer.explain_instance(doc, new_predict(x), 350, top_labels=1)
    print(exp)
    print(exp.show_in_notebook(text=False))

我有一个错误,例如:

return np.array([[float(1-m), float(m)] for m in model.predict(_text_data)]) TypeError: only size-1 arrays can be convert to Python scalars

我知道问题出在哪里,但我不知道如何解决。问题是,在我的模型中,所有键都是二维数组 [1,0](好)或 [0,1](坏),但解释器需要一个 int。

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