Hi all,
I've implemented a time delay neural network module and have been trying to
optimize it now. This function is for propagating the error backwards
through the network.
The deltas.d is just a container for holding the errors so I can do things
in place and don't have to keep initializing arrays. w and d are
collections of weights and errors respectively for different time lags.
This function gets called many many times and according to profiling, there
is a lot of garbage collection being induced by the fourth line,
specifically within multidimensional.jl getindex and setindex! and array.jl
+
function errprop!(w::Array{Float32,3}, d::Array{Float32,3}, deltas)
deltas.d[:] = 0.
for ti=1:size(w,3), ti2 = 1:size(d,3)
deltas.d[:,:,ti+ti2-1] += w[:,:,ti]'*d[:,:,ti2];
end
deltas.d
end
Any advice would be much appreciated!
Best,
Michael
