toy-conv.jl

# this is actually cross-correlation
function toyconv(x::AbstractArray{T,3}, w::AbstractArray{T,4}, pad::Integer, _stride::Integer) where T<:Real
   xSpatialDims = size(x, 1, 2)
   kernelSpatialDims = size(w, 1, 2)
   channelNum, kernelNum = size(w, 3, 4)
   ySpatialDims = 1 .+ (xSpatialDims .+ 2pad .- kernelSpatialDims) .÷ _stride
   δ = kernelSpatialDims[1] ÷ 2
   padSpatialDims = xSpatialDims .+ 2pad
   xOffset = OffsetArray(x, pad, pad, 0)
   xPadded = PaddedView(zero(T), xOffset, (padSpatialDims..., channelNum))
   y = zeros(T, ySpatialDims..., kernelNum)
   for kn = 1:kernelNum, cn = 1:channelNum
       for j = 1:ySpatialDims[2], i = 1:ySpatialDims[1]
           iPad = _stride*(i-1) + pad - δ
           jPad = _stride*(j-1) + pad - δ
           for m = 1:kernelSpatialDims[2], n = 1:kernelSpatialDims[1]
              y[i,j,kn] += xPadded[iPad+n,jPad+m,cn] * w[n,m,cn,kn]
           end
       end
   end
   y
end