我想在keras中的剩余块之间添加一个跳过连接。这是我当前的实现,因为张量具有不同的形状,因此不起作用。
函数如下:
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
我得到的错误是:ValueError: Operands could not be broadcast together with shapes (None, None, 32) (None, None, 3)
我的问题是,如何将这些张量添加或合并为正确的形状(无,无,32)。如果这不是正确的方法,那么您如何才能达到预期的效果?
编辑:
这是res_block的样子:
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
答案 0 :(得分:2)
您不能添加不同形状的张量。您可以将它们与keras.layers.Concatenate串联在一起,但这会使您的形状为[None, None, 35]
的张量。
或者,看看 Resnet50在Keras中的实现。对于要添加的尺寸不同的情况,它们的残差块在快捷方式中具有1x1xC卷积。