Textattack for cuml models not utilising much GPU resources

[farwashah6]

Hi. I am new to using GPU. I have used the Textattack library earlier for one of my projects using Sklearn and Keras models. For that I created the customModelWrappers according to my models and they worked fine. Now since my data is different and very big, I want to implement it using GPU for the same (sklearn) models.

I have the understanding that sklearn models do not implement on GPU and I have to use CUML instead. But when I use CUML, and pass the cuml model to the CustomModelWrapper I created earlier, it gives me the following error
len() of unsized object
and then stops the execution.

Additional Info: For vectorisation of my data I am using CountVectorizer of cuml, which is the cause of this error. Instead when I use CountVectorizer of sklearn it does the attack but doesn't use much GPU resources (of course). Please help me in this.

I am attaching my modelWrapper here.

class CustomModelWrapper(ta.models.wrappers.ModelWrapper):

    def __init__(self, model, vectorizer):
        super().__init__()
        self.model = model
        self.vectorizer = vectorizer

    def __call__(self, text_input_list, batch=None):
        x_transform = self.vectorizer.transform(pd.Series(text_input_list)).astype(float)
        prediction = self.model.predict_proba(x_transform)
        return prediction