When I looked at the source code for vision/AlexNet 27, I’m not sure whether the implementation assumes a 227 or 224 input size, because if you did use 227, the output of the first conv layer should be (227-11+2x2)/4 + 1 = 56 even. This would not have made much sense for the first pooling layer, which would produce an output size of (56 - 3) / 2 + 1 = 27.5.
One possible understanding is that the pool1 output is then floored, but this account differs from this Medium article 12, which suggests that in fact, conv1’s input may in fact be 224, and that the conv1 output is thus floored: (224 - 11 + 2x2) / 4 + 1 = 55.25, so that the pool1 output produces an integer without flooring: (55 - 3) / 2 + 1 = 27. Can someone please comment assertively whether the input should actually be 224 or 227? I believe this may be important for users who need this information to resize their images correctly.