learn()
This commit is contained in:
153
src/learn.jl
153
src/learn.jl
@@ -9,7 +9,7 @@ using ..type, ..snnUtil
|
||||
#------------------------------------------------------------------------------------------------100
|
||||
|
||||
function compute_paramsChange!(kfn::kfn_1, modelError, outputError)
|
||||
#WORKING
|
||||
|
||||
|
||||
lifComputeParamsChange!(kfn.lif_phi,
|
||||
kfn.lif_epsilonRec,
|
||||
@@ -29,36 +29,14 @@ function compute_paramsChange!(kfn::kfn_1, modelError, outputError)
|
||||
kfn.on_wOut,
|
||||
modelError)
|
||||
|
||||
|
||||
|
||||
onComputeParamsChange!(kfn.on_phi,
|
||||
kfn.on_epsilonRec,
|
||||
kfn.on_eta,
|
||||
kfn.on_wOutChange,
|
||||
outputError)
|
||||
|
||||
|
||||
error("debug end -> kfn compute_paramsChange! $(Dates.now())")
|
||||
|
||||
# Threads.@threads for n in kfn.neuronsArray
|
||||
# # for n in kfn.neuronsArray
|
||||
# if typeof(n) <: computeNeuron
|
||||
# wOut = Int64[]
|
||||
# for oN in kfn.outputNeuronsArray
|
||||
# wIndex = findall(isequal.(oN.subscriptionList, n.id))
|
||||
# if length(wIndex) != 0
|
||||
# push!(wOut, wIndex[1])
|
||||
# end
|
||||
# end
|
||||
|
||||
# if length(wOut) != 0
|
||||
# compute_wRecChange!(n, wOut, modelError)
|
||||
# # compute_alphaChange!(n, modelError)
|
||||
# compute_firingRateError!(n, kfn.kfnParams[:neuronFiringRateTarget],
|
||||
# kfn.kfnParams[:totalComputeNeuron])
|
||||
# end
|
||||
# end
|
||||
# end
|
||||
|
||||
# for oN in kfn.outputNeuronsArray
|
||||
# compute_wRecChange!(oN, outputError[oN.id])
|
||||
# # compute_alphaChaZnge!(oN, outputError[oN.id])
|
||||
# end
|
||||
end
|
||||
|
||||
function lifComputeParamsChange!( phi,
|
||||
@@ -77,15 +55,16 @@ function lifComputeParamsChange!( phi,
|
||||
# how much error of this neuron 1-spike causing each output neuron's error
|
||||
|
||||
view(wRecChange, :, :, i, j) .+= (-1 * view(eta, :, :, i, j)[1]) .*
|
||||
# eRec
|
||||
( (view(phi, :, :, i, j)[1] .* view(epsilonRec, :, :, i, j)) .*
|
||||
# nError a.k.a. learning signal
|
||||
(view(modelError, :, j)[1] .*
|
||||
# RSNN neuron's total wOut weight (neuron synaptic subscription .* wOutSum)
|
||||
sum(GeneralUtils.isNotEqual.(view(wRec, :, :, i, j), 0) .*
|
||||
view(wOutSum, :, :, j))
|
||||
)
|
||||
)
|
||||
# eRec
|
||||
(
|
||||
(view(phi, :, :, i, j)[1] .* view(epsilonRec, :, :, i, j)) .*
|
||||
# nError a.k.a. learning signal
|
||||
(
|
||||
view(modelError, :, j)[1] * # dopamine concept, this neuron receive summed error signal
|
||||
# RSNN neuron's total wOut weight (neuron synaptic subscription .* wOutSum)
|
||||
view(wOutSum, :, :, j)[i]
|
||||
)
|
||||
)
|
||||
end
|
||||
end
|
||||
|
||||
@@ -108,30 +87,100 @@ function alifComputeParamsChange!( phi,
|
||||
# how much error of this neuron 1-spike causing each output neuron's error
|
||||
|
||||
view(wRecChange, :, :, i, j) .+= (-1 * view(eta, :, :, i, j)[1]) .*
|
||||
# eRec
|
||||
(
|
||||
# eRec_v
|
||||
(view(phi, :, :, i, j)[1] .* view(epsilonRec, :, :, i, j)) .+
|
||||
# eRec_a
|
||||
((view(phi, :, :, i, j)[1] * view(beta, :, :, i, j)[1]) .*
|
||||
view(epsilonRecA, :, :, i, j))
|
||||
) .*
|
||||
# nError a.k.a. learning signal
|
||||
(
|
||||
view(modelError, :, j)[1] .*
|
||||
# RSNN neuron's total wOut weight (neuron synaptic subscription .* wOutSum)
|
||||
sum(GeneralUtils.isNotEqual.(view(wRec, :, :, i, j), 0) .*
|
||||
view(wOutSum, :, :, j))
|
||||
)
|
||||
# eRec
|
||||
(
|
||||
# eRec_v
|
||||
(view(phi, :, :, i, j)[1] .* view(epsilonRec, :, :, i, j)) .+
|
||||
# eRec_a
|
||||
((view(phi, :, :, i, j)[1] * view(beta, :, :, i, j)[1]) .*
|
||||
view(epsilonRecA, :, :, i, j))
|
||||
) .*
|
||||
# nError a.k.a. learning signal
|
||||
(
|
||||
view(modelError, :, j)[1] *
|
||||
# RSNN neuron's total wOut weight (neuron synaptic subscription .* wOutSum)
|
||||
view(wOutSum, :, :, j)[i]
|
||||
# sum(GeneralUtils.isNotEqual.(view(wRec, :, :, i, j), 0) .*
|
||||
# view(wOutSum, :, :, j))
|
||||
)
|
||||
end
|
||||
end
|
||||
|
||||
|
||||
function onComputeParamsChange!(phi,
|
||||
epsilonRec,
|
||||
eta,
|
||||
wOutChange,
|
||||
outputError)
|
||||
d1, d2, d3, d4 = size(epsilonRec)
|
||||
|
||||
for j in 1:d4, i in 1:d3 # compute along neurons axis of every batch
|
||||
# how much error of this neuron 1-spike causing each output neuron's error
|
||||
|
||||
view(wOutChange, :, :, i, j) .+= (-1 * view(eta, :, :, i, j)[1]) .*
|
||||
# eRec
|
||||
(
|
||||
(view(phi, :, :, i, j)[1] .* view(epsilonRec, :, :, i, j)) .*
|
||||
# nError a.k.a. learning signal, output neuron receives error of its own answer - correct answer.
|
||||
view(outputError, :, j)[i]
|
||||
)
|
||||
end
|
||||
end
|
||||
|
||||
# function onComputeParamsChange!(wOut,
|
||||
# epsilonRec,
|
||||
# eta,
|
||||
# wOutChange,
|
||||
# bChange,
|
||||
# outputError)
|
||||
# d1, d2, d3, d4 = size(epsilonRec)
|
||||
# println(">>> epsilon ", size(epsilonRec))
|
||||
# println(">>> outputError ", size(outputError))
|
||||
|
||||
|
||||
# # Bₖⱼ in paper, sum() to get each neuron's total wOut weight
|
||||
|
||||
# for j in 1:d4, i in 1:d3 # compute along neurons axis of every batch
|
||||
# # how much error of this neuron 1-spike causing each output neuron's error
|
||||
|
||||
# view(wOutChange, :, :, i, j) .+=
|
||||
# (-1 * view(eta, :, :, i, j)[1] * view(outputError, :, j)[i]) .*
|
||||
# view(epsilonRec, :, :, i, j)
|
||||
# end
|
||||
# #TODO add b
|
||||
# error(">>> DEBUG -> onComputeParamsChange!")
|
||||
# end
|
||||
|
||||
|
||||
function learn!(kfn::kfn_1)
|
||||
#WORKING lif learn
|
||||
lifLearn!(kfn.lif_wRec,
|
||||
kfn.lif_wRecChange)
|
||||
|
||||
|
||||
#TODO alif learn
|
||||
|
||||
|
||||
#TODO on learn
|
||||
|
||||
#TODO wOut decay
|
||||
|
||||
# wrap up learning session
|
||||
if kfn.learningStage == [3]
|
||||
kfn.learningStage = [0]
|
||||
end
|
||||
end
|
||||
|
||||
function lifLearn!(wRec,
|
||||
wRecChange)
|
||||
# merge learning weight
|
||||
wRec .+= wRecChange
|
||||
|
||||
#TODO synaptic strength
|
||||
|
||||
#TODO neuroplasticity
|
||||
|
||||
end
|
||||
|
||||
|
||||
|
||||
|
||||
Reference in New Issue
Block a user