This keras implementation has different order of bn and activation

[pgr2015]

Hi, thank you for your work. One thing I want to point out here is that you have some tiny difference compared with original implementaion, which may lead to more latency. Your implementation here is conv + activation + bn as shown below:

y = Conv2D(32, 3, strides=2, padding='same', activation='relu', name='conv1_1_3x3_s2')(y)
y = BatchNormalization(name='conv1_1_3x3_s2_bn')(y)

But the original caffe implementaion is conv + bn + activation, which normally won't have much differnce, but this kind of order make it possible to merge bn into conv, thus leads to smaller latency.