Keras-在模型前面添加图层

我想做的是在导入的VGG16模型前面添加一个Upsampling2D层。但是我不知道该怎么做，从来没有在网上看到过这样的事情

我想做的是：

VGG = VGG16()
model = Sequential()
model.add(UpSampling2D((32,32), input_shape=(7,7,3)))
model.add(VGG)

但是，尝试对任何对象使用此模型都会引发以下错误：

AttributeError:Layer model_1有多个入站节点，因此“Layer output”的概念定义不清。使用

get\u output\u at（节点索引）

---

知道为什么吗？

您可以在

VGG16（）

中提供

input\u tensor

参数

通过运行

VGG.summary（）

，您将看到如下内容：

_________________________________________________________________
Layer (type)                 Output Shape              Param # 
=================================================================
input_1 (InputLayer)         (None, 7, 7, 3)           0
_________________________________________________________________
up_sampling2d_1 (UpSampling2 (None, 224, 224, 3)       0
_________________________________________________________________
block1_conv1 (Conv2D)        (None, 224, 224, 64)      1792
_________________________________________________________________
block1_conv2 (Conv2D)        (None, 224, 224, 64)      36928
_________________________________________________________________
block1_pool (MaxPooling2D)   (None, 112, 112, 64)      0
_________________________________________________________________

...

_________________________________________________________________
Layer (type)                 Output Shape              Param # 
=================================================================
input_1 (InputLayer)         (None, 7, 7, 3)           0
_________________________________________________________________
up_sampling2d_1 (UpSampling2 (None, 224, 224, 3)       0
_________________________________________________________________
block1_conv1 (Conv2D)        (None, 224, 224, 64)      1792
_________________________________________________________________
block1_conv2 (Conv2D)        (None, 224, 224, 64)      36928
_________________________________________________________________
block1_pool (MaxPooling2D)   (None, 112, 112, 64)      0
_________________________________________________________________

...