Hello, am trying to recreate the model from (https://arxiv.org/pdf/1207.0580.pdf appendix G - Models for Cifar10). So I should construct a CNN with 3 convolutional layers each followed by a subsam-
pling/pooling layer. The convolutional layers should consist of 64 5x5 filters and the subsampling layers implement the max-pooling function over a window of size 3x3 using a stride of 2. In the end, I must connect the 3rd pooling layer to a 10-way softmax output layer. But when am trying to create this model, am having technical difficulties.
So output shape for each layer would look like this:
Layer (type) Output Shape
Conv2d-1 [64, 28, 28]
MaxPool2d-2 [64, 13, 13]
Conv2d-3 [64, 9, 9]
MaxPool2d-4 [64, 4, 4]
///////////////////////////////////////////////////////// I can’t add another Conv2vd with kernal_size = 5 x 5,
///////////////////////////////////////////////////////// because it would lead to
Conv2d-5 [64, 4 - 5 , 4 - 5 ] - > error.
So this model can’t be created? Or am doing something wrong?