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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def fit(self, train_events, test_events, n_epoch=1):
 """Train a model using the first 30% positive events to avoid cold-start. Evaluation of this batch training is done by using the next 20% positive events. After the batch SGD training, the models are incrementally updated by using the 20% test events. Args: train_events (list of Event):
 Positive training events (0-30%). test_events (list of Event):
 Test events (30-50%). n_epoch (int):
 Number of epochs for the batch training. """

        # make initial status for batch training
        for e in train_events:
            self.__validate(e)
            self.rec.users[e.user.index]['known_items'].add(e.item.index)
            self.item_buffer.append(e.item.index)

        # for batch evaluation, temporarily save new users info
        for e in test_events:
            self.__validate(e)
            self.item_buffer.append(e.item.index)

        self.__batch_update(train_events, test_events, n_epoch)

        # batch test events are considered as a new observations;
        # the model is incrementally updated based on them before the incremental evaluation step
        for e in test_events:
            self.rec.users[e.user.index]['known_items'].add(e.item.index)
            self.rec.update(e)