我想在keras中的剩余块之间添加一个skip连接。这是我目前的实现，它不起作用，因为Tensor有不同的形状。
函数如下所示：

def build_res_blocks(net, x_in, num_res_blocks, res_block, num_filters, res_block_expansion, kernel_size, scaling):
    net_next_in = net
    for i in range(num_res_blocks):
        net = res_block(net_next_in, num_filters, res_block_expansion, kernel_size, scaling)
    
        # net tensor shape: (None, None, 32)
        # x_in tensor shape: (None, None, 3)
        # Error here, net_next_in should be in the shape of (None, None, 32) to be fed into next layer
        net_next_in = Add()([net, x_in]) 

    return net

但我得到

ValueError: Operands could not be broadcast together with shapes (None, None, 32) (None, None, 3)

如何添加或合并这些Tensor到正确的形状（无，无，32）？如果这是不正确的方法，你怎么能达到预期的结果？
res_block如下所示：

def res_block(x_in, num_filters, expansion, kernel_size, scaling):
    x = Conv2D(num_filters * expansion, kernel_size, padding='same')(x_in)
    x = Activation('relu')(x)
    x = Conv2D(num_filters, kernel_size, padding='same')(x)
    x = Add()([x_in, x])
return x