def fit(self, X, y, epochs=None):
        if self.check_input:
            X, y = self._check_good_input(X, y)

        if self.use_label_encoder:
            self.enc_ = LabelEncoder()
            y = self.enc_.fit_transform(y).astype(np.int32)
            self.classes_ = self.enc_.classes_
        self.initialize()

        try:
            self.train_loop(X, y, epochs=epochs)
        except __HOLE__:
            pass
        return self
dataset/ETHPy150Open dnouri/nolearn/nolearn/lasagne/base.py/NeuralNet.fit