ff_mnist.py 文件源码

def run_network(data=None, model=None, epochs=20, batch=256):
    try:
        start_time = time.time()
        if data is None:
            X_train, X_test, y_train, y_test = load_data()
        else:
            X_train, X_test, y_train, y_test = data

        if model is None:
            model = init_model()

        history = LossHistory()

        print 'Training model...'
        model.fit(X_train, y_train, nb_epoch=epochs, batch_size=batch,
                  callbacks=[history],
                  validation_data=(X_test, y_test), verbose=2)

        print "Training duration : {0}".format(time.time() - start_time)
        score = model.evaluate(X_test, y_test, batch_size=16)

        print "Network's test score [loss, accuracy]: {0}".format(score)
        return model, history.losses
    except KeyboardInterrupt:
        print ' KeyboardInterrupt'
        return model, history.losses