老师，我想把resnet的实战代码转成tf2.0下的代码，我改写成了下面的样子，但是运行有错，想请您帮忙看下，该怎么修改，报错在最后粘贴。

def residual_block(x,output_channel):
    """residual connection implementation"""
    input_channel = 32
    if input_channel * 2 == output_channel:
        increase_dim = True
        strides = (2, 2)
    elif input_channel == output_channel:
        increase_dim = False
        strides = (1, 1)
    else:
        raise Exception("input channel can't match output channel")
        
    conv1 = keras.layers.Conv2D(filters=output_channel, kernel_size=3,
                                strides = strides,
                                padding='same',
                                activation='relu')
    conv2 = keras.layers.Conv2D(filters=output_channel, kernel_size=3,
                                strides = (1, 1),
                                padding='same',
                                activation='relu')
    if increase_dim:
        #[None, image_width, image_height, channel] -> [,,,channel*2]
        pooled_x = keras.layers.MaxPool2D(input_shape=train_data_scaled.shape[1:],
                                          pool_size=2)
        
        #做一个padding，padding在通道上
        padded_x = tf.pad(pooled_x,
                          [[0,0],
                           [0,0],
                           [0,0],
                           [input_channel // 2, input_channel // 2]])
    else:
        padded_x = x
    output_x = conv2 + padded_x
    layers.append(output_x)
    return output_x

layers = []
num_residual_blocks = [2,3,2]
num_subsampling = len(num_residual_blocks)

model = keras.models.Sequential()
conv0 = keras.layers.Conv2D(filters=32, kernel_size=3,
                              padding='same',
                              activation='relu',
                              input_shape=train_data_scaled.shape[1:])
model.add(conv0)
layers.append(conv0)
for sample_id in range(num_subsampling):
        for i in range(num_residual_blocks[sample_id]):
            model.add(residual_block(layers[-1],32 * (2 ** sample_id)))
            

TypeError Traceback (most recent call last)
in
49 for sample_id in range(num_subsampling):
50 for i in range(num_residual_blocks[sample_id]):
—> 51 model.add(residual_block(layers[-1],32 * (2 ** sample_id)))
52

in residual_block(x, output_channel)
32 else:
33 padded_x = x
—> 34 output_x = conv2 + padded_x
35 layers.append(output_x)
36 return output_x

TypeError: unsupported operand type(s) for +: ‘Conv2D’ and ‘Conv2D’