I am trying to write a CNN from scratch and am wondering if it is possible to vectorize the convolution step.
For example, if I had a dataset of 500 RGB images of size 32x32x3, and wanted the first convolutional layer to have 64 filters, how would I go about the vectorization of this layer?
Currently, I am running through all 500 images in a
for loop, convoluting individually. I do this for all the images up to the flattening stage (where it essentially becomes a normal NN again), at which point I can implement the normal vectorisation approach to get to my output, etc.
A holistic overview of the process would be appreciated, as I am struggling to get my head around it and am struggling to find and information on the matter online.