@smth However there are multiple 3X3 Convolution. If we see figure 4 and use 5X5 the 3X3 convolution should be 1 times. However in implementation is using multiple 3X3 convolution, so I just think that 5X5 should bechange into 3X3.
I just think the code should be like here.
self.branch5x5_2 = BasicConv2d(48, 64, kernel_size=5, padding=2)
change with this
self.branch5x5_2 = BasicConv2d(48, 64, kernel_size=3, padding=1)
Am I right?, sorry I just learn about this and not have so much knowledge about it.

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