Deopen_regression.py 文件源码

def model_initial(X_train,y_train,max_iter = 5):
    global params, val_loss
    params = []
    val_loss = np.zeros(max_iter)
    lr = theano.shared(np.float32(1e-4))
    for iteration in range(max_iter):
        print 'initializing weights (%d/5) ...'%(iteration+1)
        print iteration
        network_init = create_network()
        net_init = NeuralNet(
                network_init,
                max_epochs=3,
                update=adam,
                update_learning_rate=lr,
                train_split=TrainSplit(eval_size=0.1),
                batch_iterator_train=BatchIterator(batch_size=32),
                batch_iterator_test=BatchIterator(batch_size=64),
                regression = True,
                objective_loss_function = squared_error,
                on_training_finished=[SaveTrainHistory(iteration = iteration)],
                verbose=0)
        net_init.initialize()
        net_init.fit(X_train, y_train)


#model training