text_sentiment_CNN.py 文件源码

def fit(self, X_train, y_train, X_test, y_test,
            batch_size=50, nb_epoch=3):
        """

        :param X_train: each instance is a list of word index
        :param y_train:
        :return:
        """
        print(len(X_train), 'train sequences')
        print(len(X_test), 'test sequences')
        print("Pad sequences (samples x time)")
        X_train = sequence.pad_sequences(X_train, maxlen=self.maxlen)
        X_test = sequence.pad_sequences(X_test, maxlen=self.maxlen)
        print('X_train shape:', X_train.shape)
        print('X_test shape:', X_test.shape)
        y_train = expand_label(y_train)
        y_test = expand_label(y_test)

        #early stopping
        early_stop = EarlyStopping(monitor='val_loss', patience=2)

        self.model.fit({'input': X_train, 'output': y_train}, batch_size=batch_size, nb_epoch=nb_epoch,
          verbose=1, validation_data=({'input': X_test, 'output': y_test}), callbacks=[early_stop])