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This commit is contained in:
359
src/learn.jl
359
src/learn.jl
@@ -94,7 +94,7 @@ function lifComputeParamsChange!( timeStep::CuArray,
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# some RSNN neuron that has direct connection to output neuron need to get Bjk
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# from output neuron that represent correct answer, the rest of RSNN get random Bjk
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onW = @view(wOut[:, startCol:stopCol, sum(label), 1])
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onW = @view(wOut[:, startCol:stopCol, sum(label+1), 1]) # label+1 because julia is 1-based index
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_bk = @view(bk[:, startCol:stopCol, 1])
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mask = iszero.(onW)
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bk_ = mask .* _bk
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@@ -175,7 +175,7 @@ function alifComputeParamsChange!( timeStep::CuArray,
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# some RSNN neuron that has direct connection to output neuron need to get Bjk
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# from output neuron that represent correct answer, the rest of RSNN get random Bjk
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onW = @view(wOut[:, startCol:stopCol, sum(label), 1])
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onW = @view(wOut[:, startCol:stopCol, sum(label+1), 1]) # label+1 because julia is 1-based index
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_bk = @view(bk[:, startCol:stopCol, 1])
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mask = iszero.(onW)
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bk_ = mask .* _bk
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@@ -423,20 +423,13 @@ function lifLearn(wRec,
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arrayProjection4d_cpu = arrayProjection4d |> cpu
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wRec_cpu = wRec |> cpu
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wRecChange_cpu = wRecChange |> cpu
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wRecChange_cpu = wRecChange_cpu[:,:,:,1]
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eta_cpu = eta |> cpu
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eta_cpu = eta_cpu[:,:,:,1]
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exInType_cpu = exInType |> cpu
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exInType_cpu = exInType_cpu[:,:,:,1]
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neuronInactivityCounter_cpu = neuronInactivityCounter |> cpu
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neuronInactivityCounter_cpu = neuronInactivityCounter_cpu[:,:,:,1] # (row, col, n)
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synapseReconnectDelay_cpu = synapseReconnectDelay |> cpu
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synapseReconnectDelay_cpu = synapseReconnectDelay_cpu[:,:,:,1]
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synapticActivityCounter_cpu = synapticActivityCounter |> cpu
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synapticActivityCounter_cpu = synapticActivityCounter_cpu[:,:,:,1]
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zitCumulative_cpu = zitCumulative |> cpu
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zitCumulative_cpu = zitCumulative_cpu[:,:,1]
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println("synapse 3 ", synapseReconnectDelay_cpu[:,:,1,1])
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# neuroplasticity, work on CPU side
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wRec_cpu, neuronInactivityCounter_cpu, synapseReconnectDelay_cpu =
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neuroplasticity(synapseConnectionNumber,
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@@ -445,44 +438,11 @@ function lifLearn(wRec,
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exInType_cpu,
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wRecChange_cpu,
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vt,
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eta,
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eta_cpu,
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neuronInactivityCounter_cpu,
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synapseReconnectDelay_cpu,
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synapticActivityCounter_cpu,
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progress,)
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# # merge learning weight with average learning weight of all batch
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# wch = sum(wRecChange, dims=4) ./ (size(wRec, 4)) .* arrayProjection4d
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# wRec .= (exInType .* wRec) .+ wch
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# # (row, col)
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# # -W if less than 10% of repeat avg, +W otherwise
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# _, _, i3 = size(wRec_cpu)
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# for i in 1:i3
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# x = 0.1 * (sum(synapseReconnectDelay[:,:,i]) / length(synapseReconnectDelay[:,:,i]))
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# mask = GeneralUtils.replaceLessThan.(wRec_cpu[:,:,i], x, -1, 1)
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# wRec_cpu[:,:,i] .+= mask .* eta_cpu[:,:,i] .* wRec_cpu[:,:,i]
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# end
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# # weak / negative synaptic connection will get randomed in neuroplasticity()
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# wRec_cpu = GeneralUtils.replaceBetween.(wRec_cpu, 0.0, 0.01, -1.0) # mark with -1.0
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# neuroplasticity, work on CPU side
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# wRec_cpu = neuroplasticity(synapseConnectionNumber,
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# zitCumulative_cpu,
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# wRec_cpu,
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# wRecChange_cpu,
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# vt,
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# neuronInactivityCounter_cpu,
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# synapseReconnectDelay_cpu)
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# transfer data backto gpu
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wRec_cpu = wRec_cpu .* arrayProjection4d_cpu
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@@ -491,7 +451,7 @@ function lifLearn(wRec,
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neuronInactivityCounter = neuronInactivityCounter_cpu |> device
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synapseReconnectDelay_cpu = synapseReconnectDelay_cpu .* arrayProjection4d_cpu
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synapseReconnectDelay = synapseReconnectDelay_cpu |> device
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error("DEBUG -> lifLearn! $(Dates.now())")
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return wRec, neuronInactivityCounter, synapseReconnectDelay
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end
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@@ -515,15 +475,10 @@ function alifLearn(wRec,
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arrayProjection4d_cpu = arrayProjection4d |> cpu
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wRec_cpu = wRec |> cpu
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wRec_cpu = wRec_cpu[:,:,:,1] # since every batch has the same neuron wRec, (row, col, n)
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eta_cpu = eta |> cpu
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eta_cpu = eta_cpu[:,:,:,1]
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neuronInactivityCounter_cpu = neuronInactivityCounter |> cpu
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neuronInactivityCounter_cpu = neuronInactivityCounter_cpu[:,:,:,1] # (row, col, n)
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synapseReconnectDelay_cpu = synapseReconnectDelay |> cpu
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synapseReconnectDelay_cpu = synapseReconnectDelay_cpu[:,:,:,1]
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zitCumulative_cpu = zitCumulative |> cpu
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zitCumulative_cpu = zitCumulative_cpu[:,:,1] # (row, col)
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# -W if less than 10% of repeat avg, +W otherwise
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_, _, i3 = size(wRec_cpu)
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@@ -566,10 +521,9 @@ function onLearn!(wOut,
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wOut .-= 0.001 .* wOut
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end
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alltrue(args...) = false ∈ [args...] ? false : true
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isbetween(x, lowerlimit, upperlimit) = lowerlimit < x < upperlimit ? true : false
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GeneralUtils.allTrue(args...) = false ∈ [args...] ? false : true
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#WORKING 1) implement 90% +w, 10% -w 2) rewrite this function
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#WORKING 2) rewrite this function
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function neuroplasticity(synapseConnectionNumber,
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zitCumulative, # (row, col)
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wRec, # (row, col, n)
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@@ -583,196 +537,191 @@ function neuroplasticity(synapseConnectionNumber,
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progress,) # (row, col, n)
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i1,i2,i3 = size(wRec)
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println("eta $(size(eta))")
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println("wRec $(size(wRec))")
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error("DEBUG -> neuroplasticity $(Dates.now())")
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println("wRec 1 $(size(wRec)) ", wRec[:,:,1,1])
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println("zitCumulative $(size(zitCumulative))")
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println("progress $progress")
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if progress == 2 # no need to learn
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# skip neuroplasticity
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#TODO I may need to do something with neuronInactivityCounter and other variables
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wRecChange .= 0
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elseif progress == 1 # progress increase
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error("DEBUG -> neuroplasticity")
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elseif progress != 0 # progress increase
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# ready to reconnect synapse must not have wRecChange
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mask = (!isequal).(wRec, 0)
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wRecChange .*= mask
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# merge learning weight with average learning weight of all batch
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wRec .= abs.((exInType .* wRec) .+ wRecChange) # abs because wRec doesn't carry sign
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# seperate active synapse out of inactive in this signal
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mask_inactiveSynapse = isequal.(synapticActivityCounter, 0)
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mask_activeSynapse = (!isequal).(synapticActivityCounter, 0)
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# adjust weight based on vt progress and repeatition (90% +w, 10% -w) depend on epsilonRec
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avgActivity = sum(synapticActivityCounter) / length(synapticActivityCounter)
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lowerlimit = 0.1 * avgActivity
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# +w, synapse with more than 10% of avg activity get increase weight by eta
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mask_more = (!isless).(synapticActivityCounter, lowerlimit)
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mask_2 = alltrue.(mask_activeSynapse, mask_more)
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mask_2 .*= 1 .+ eta # minor activity synapse weight will be reduced by eta
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wRec .*= mask_2
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# merge learning weight, all resulting negative wRec will get pruned
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mergeLearnWeight!(wRec, exInType, wRecChange, synapticActivityCounter, synapseReconnectDelay)
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# println("wRec 2 $(size(wRec)) ", wRec[:,:,1,1])
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# adjust wRec based on repeatition (90% +w, 10% -w)
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growRepeatedPath!(wRec, synapticActivityCounter, eta)
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# println("wRec 3 $(size(wRec)) ", wRec[:,:,1,1])
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# -w all non-fire connection except mature connection
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weakenNotMatureSynapse!(wRec, synapticActivityCounter, eta)
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# -w, synapse with less than 10% of avg activity get reduced weight by eta
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mask_less = isbetween.(synapticActivityCounter, 0.0, lowerlimit) # 1st criteria
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# prune weak synapse
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pruneSynapse!(wRec, synapticActivityCounter, synapseReconnectDelay)
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mask_3 = alltrue.(mask_activeSynapse, mask_less)
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mask_3 .*= 1 .- eta # minor activity synapse weight will be reduced by eta
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wRec .*= mask_3
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# rewire synapse connection
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rewireSynapse!(wRec, neuronInactivityCounter, synapticActivityCounter,
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synapseReconnectDelay, zitCumulative)
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error("DEBUG -> neuroplasticity")
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# wRec .= (exInType .* wRec) .+ wRecChange
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# mask_negative = isless.(wRec, 0)
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# mask_positive = (!isless).(wRec, 0)
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# GeneralUtils.replaceElements!(mask_negative, 1, wRec, 0.0) # negative synapse get pruned
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# GeneralUtils.replaceElements!(mask_negative, 1, synapticActivityCounter, -0.1)
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# # set pruned synapse to random wait time
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# waittime = rand((1:1000), size(wRec)) .* mask_negative # synapse's random wait time to reconnect
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# # synapseReconnectDelay counting mode when value is negative hence .* -1
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# synapseReconnectDelay .= (synapseReconnectDelay .* mask_positive) .+ (waittime .* -1)
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# # seperate active synapse out of inactive in this signal
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# mask_activeSynapse = (!isequal).(synapticActivityCounter, 0)
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# # adjust weight based on vt progress and repeatition (90% +w, 10% -w) depend on epsilonRec
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# avgActivity = sum(synapticActivityCounter) / length(synapticActivityCounter)
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# lowerlimit = 0.1 * avgActivity
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# # +w, synapse with more than 10% of avg activity get increase weight by eta
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# mask_more = (!isless).(synapticActivityCounter, lowerlimit)
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# mask_2 = GeneralUtils.allTrue.(mask_activeSynapse, mask_more)
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# mask_2 .*= 1 .+ eta # minor activity synapse weight will be reduced by eta
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# wRec .*= mask_2
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# # -w, synapse with less than 10% of avg activity get reduced weight by eta
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# mask_less = GeneralUtils.isBetween.(synapticActivityCounter, 0.0, lowerlimit) # 1st criteria
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# mask_3 = GeneralUtils.allTrue.(mask_activeSynapse, mask_less)
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# mask_3 .*= 1 .- eta # minor activity synapse weight will be reduced by eta
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# wRec .*= mask_3
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# -w all non-fire connection except mature connection
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mask_notmature = isless.(wRec, 0.1) # 2nd criteria, not mature synapse has weight < 0.1
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mask_1 = alltrue.(mask_inactiveSynapse, mask_notmature)
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mask_1 .*= 1 .- eta
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wRec .*= mask_1
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# mask_inactiveSynapse = isequal.(synapticActivityCounter, 0)
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# mask_notmature = GeneralUtils.isBetween.(wRec, 0.0, 0.1) # 2nd criteria, not mature synapse has weight < 0.1
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# mask_1 = GeneralUtils.allTrue.(mask_inactiveSynapse, mask_notmature)
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# mask_1 .*= 1 .- eta
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# wRec .*= mask_1
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# prune synapse
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mask_weak = isbetween.(wRec, 0.0, 0.01)
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mask_notweak = (!isbetween).(wRec, 0.0, 0.01)
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wRec .*= mask_notweak # all marked weak synapse weight need to be 0.0 i.e. pruned
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r = rand((1:1000), size(wRec)) .* mask_weak # synapse random wait time to reconnect
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synapticActivityCounter .*= mask_notweak # all marked weak synapse activity are reset
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synapticActivityCounter .+= (mask_weak .* -1.0)
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synapseReconnectDelay .= (synapseReconnectDelay .* mask_notweak) .+ r # set pruned synapse to random wait time
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# mask_weak = GeneralUtils.isBetween.(wRec, 0.0, 0.01)
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# mask_notweak = (!GeneralUtils.isBetween).(wRec, 0.0, 0.01)
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# wRec .*= mask_notweak # all marked weak synapse weight need to be 0.0 i.e. pruned
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# # all weak synapse activity are reset
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# GeneralUtils.replaceElements!(mask_weak, 1, synapticActivityCounter, -0.1)
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# # set pruned synapse to random wait time
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# r = rand((1:1000), size(wRec)) .* mask_weak # synapse's random wait time to reconnect
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# # synapseReconnectDelay counting mode when value is negative hence .* -1
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# synapseReconnectDelay .= (synapseReconnectDelay .* mask_notweak) .+ (r .* -1)
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#WORKING rewire synapse connection
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synapseReconnectDelay mark timeStep while also counting delay == BUG
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for i in 1:i3 # neuron-by-neuron
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if neuronInactivityCounter[1:1:i][1] < -10000 # neuron die i.e. reset all weight
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println("neuron die")
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neuronInactivityCounter[:,:,i] .= 0 # reset
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w = random_wRec(i1,i2,1,synapseConnectionNumber)
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wRec[:,:,i] .= w
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#WORKING
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a = similar(w) .= -0.99 # synapseConnectionNumber of this neuron
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mask = (!iszero).(w)
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GeneralUtils.replaceElements!(mask, 1, a, 0)
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synapseReconnectDelay[:,:,i] = a
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else
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remaining = 0
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if subToFireNeuron_current[1,1,i] < subToFireNeuron_toBe
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toAddConn = subToFireNeuron_toBe - subToFireNeuron_current[1,1,i]
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totalNewConn[1,1,i] = totalNewConn[1,1,i] - toAddConn
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# add new conn to firing neurons pool
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remaining = addNewSynapticConn!(zitMask[:,:,i], 1,
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@view(wRec[:,:,i]),
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@view(synapseReconnectDelay[:,:,i]),
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toAddConn)
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totalNewConn[1,1,i] += remaining
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end
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# add new conn to non-firing neurons pool
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remaining = addNewSynapticConn!(zitMask[:,:,i], 0,
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@view(wRec[:,:,i]),
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@view(synapseReconnectDelay[:,:,i]),
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totalNewConn[1,1,i])
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if remaining > 0 # final get-all round if somehow non-firing pool has not enough slot
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remaining = addNewSynapticConn!(zitMask[:,:,i], 1,
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@view(wRec[:,:,i]),
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@view(synapseReconnectDelay[:,:,i]),
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remaining)
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end
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end
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end
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# rewire synapse connection
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# for i in 1:i3 # neuron-by-neuron
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# if neuronInactivityCounter[1:1:i][1] < -10000 # neuron die i.e. reset all weight
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# println("neuron $i die")
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# neuronInactivityCounter[:,:,i] .= 0 # reset
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# w = random_wRec(i1,i2,1,synapseConnectionNumber)
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# wRec[:,:,i] .= w
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# a = similar(w) .= -0.1 # synapseConnectionNumber of this neuron
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# mask = (!iszero).(w)
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# GeneralUtils.replaceElements!(mask, 1, a, 0)
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# synapseReconnectDelay[:,:,i] = a
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# else #WORKING
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# for i in eachindex(synapseReconnectDelay[:,:,i])
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# if i > 0 # mark timeStep available
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# # get neuron pool at 10 timeStep earlier
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# earlier = i - 10 > 0 ? i : i - 10
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# pool = sum(zitCumulative[:,:,earlier:i], dims=3)
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# indices = findall(x -> x != 0, pool)
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# pick = rand(indices)
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# wRec[:,:,i][pick] = rand(0.01:0.01:0.5)
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# synapticActivityCounter[:,:,i][pick] = 0
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# synapseReconnectDelay[:,:,i][pick] = -0.1
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# end
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# end
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# end
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# end
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elseif progress == 0 # no progress, no weight update, only rewire
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# -w all non-fire connection except mature connection
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weakenNotMatureSynapse!(wRec, synapticActivityCounter, eta)
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# prune weak connection
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# prune weak synapse
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pruneSynapse!(wRec, synapticActivityCounter, synapseReconnectDelay)
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# rewire synapse connection
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elseif progress == -1 # setback
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# adjust weight based on vt progress and repeatition (90% +w, 10% -w) depend on epsilonRec
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rewireSynapse!(wRec, neuronInactivityCounter, synapticActivityCounter,
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synapseReconnectDelay, zitCumulative)
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# -w all non-fire connection except mature connection
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# prune weak connection
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# rewire synapse connection
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error("DEBUG -> neuroplasticity $(Dates.now())")
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else
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error("undefined condition line $(@__LINE__)")
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end
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# error("DEBUG -> neuroplasticity $(Dates.now())")
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# merge learning weight with average learning weight of all batch
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wRec .= abs.((exInType .* wRec) .+ wRecChange) # abs because wRec doesn't carry sign
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# adjust weight based on vt progress and repeatition (90% +w, 10% -w) depend on epsilonRec
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# -w all non-fire connection except mature connection
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# prune weak connection
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# rewire synapse connection
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# # for each neuron, find total number of synaptic conn that should draw
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# # new connection to firing and non-firing neurons pool
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# subToFireNeuron_toBe = Int(floor(0.7 * synapseConnectionNumber))
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# # for each neuron, count how many synapse already subscribed to firing-neurons
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# zw = zitCumulative .* wRec
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# subToFireNeuron_current = sum(GeneralUtils.GeneralUtils.isBetween.(zw, 0.0, 100.0), dims=(1,2)) # (1, 1, n)
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# zitMask = (!iszero).(zitCumulative) # zitMask of firing neurons = 1, non-firing = 0
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# projection = ones(i1,i2,i3)
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# zitMask = zitMask .* projection # (row, col, n)
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# totalNewConn = sum(isequal.(wRec, -1.0), dims=(1,2)) # count new conn mark (-1.0), (1, 1, n)
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# println("neuroplasticity, from $(synapseConnectionNumber*size(totalNewConn, 3)) conn, $(sum(totalNewConn)) are replaced")
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# for each neuron, find total number of synaptic conn that should draw
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# new connection to firing and non-firing neurons pool
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subToFireNeuron_toBe = Int(floor(0.7 * synapseConnectionNumber))
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# for each neuron, count how many synapse already subscribed to firing-neurons
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zw = zitCumulative .* wRec
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subToFireNeuron_current = sum(GeneralUtils.isBetween.(zw, 0.0, 100.0), dims=(1,2)) # (1, 1, n)
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zitMask = (!iszero).(zitCumulative) # zitMask of firing neurons = 1, non-firing = 0
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projection = ones(i1,i2,i3)
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zitMask = zitMask .* projection # (row, col, n)
|
||||
totalNewConn = sum(isequal.(wRec, -1.0), dims=(1,2)) # count new conn mark (-1.0), (1, 1, n)
|
||||
println("neuroplasticity, from $(synapseConnectionNumber*size(totalNewConn, 3)) conn, $(sum(totalNewConn)) are replaced")
|
||||
|
||||
# clear -1.0 marker
|
||||
GeneralUtils.replaceElements!(wRec, -1.0, synapseReconnectDelay, -0.99)
|
||||
GeneralUtils.replaceElements!(wRec, -1.0, 0.0) # -1.0 marker is no longer required
|
||||
# # clear -1.0 marker
|
||||
# GeneralUtils.replaceElements!(wRec, -1.0, synapseReconnectDelay, -0.99)
|
||||
# GeneralUtils.replaceElements!(wRec, -1.0, 0.0) # -1.0 marker is no longer required
|
||||
|
||||
for i in 1:i3
|
||||
if neuronInactivityCounter[1:1:i][1] < -10000 # neuron die i.e. reset all weight
|
||||
println("neuron die")
|
||||
neuronInactivityCounter[:,:,i] .= 0 # reset
|
||||
w = random_wRec(i1,i2,1,synapseConnectionNumber)
|
||||
wRec[:,:,i] .= w
|
||||
# for i in 1:i3
|
||||
# if neuronInactivityCounter[1:1:i][1] < -10000 # neuron die i.e. reset all weight
|
||||
# println("neuron die")
|
||||
# neuronInactivityCounter[:,:,i] .= 0 # reset
|
||||
# w = random_wRec(i1,i2,1,synapseConnectionNumber)
|
||||
# wRec[:,:,i] .= w
|
||||
|
||||
a = similar(w) .= -0.99 # synapseConnectionNumber of this neuron
|
||||
mask = (!iszero).(w)
|
||||
GeneralUtils.replaceElements!(mask, 1, a, 0)
|
||||
synapseReconnectDelay[:,:,i] = a
|
||||
else
|
||||
remaining = 0
|
||||
if subToFireNeuron_current[1,1,i] < subToFireNeuron_toBe
|
||||
toAddConn = subToFireNeuron_toBe - subToFireNeuron_current[1,1,i]
|
||||
totalNewConn[1,1,i] = totalNewConn[1,1,i] - toAddConn
|
||||
# add new conn to firing neurons pool
|
||||
remaining = addNewSynapticConn!(zitMask[:,:,i], 1,
|
||||
@view(wRec[:,:,i]),
|
||||
@view(synapseReconnectDelay[:,:,i]),
|
||||
toAddConn)
|
||||
totalNewConn[1,1,i] += remaining
|
||||
end
|
||||
# a = similar(w) .= -0.99 # synapseConnectionNumber of this neuron
|
||||
# mask = (!iszero).(w)
|
||||
# GeneralUtils.replaceElements!(mask, 1, a, 0)
|
||||
# synapseReconnectDelay[:,:,i] = a
|
||||
# else
|
||||
# remaining = 0
|
||||
# if subToFireNeuron_current[1,1,i] < subToFireNeuron_toBe
|
||||
# toAddConn = subToFireNeuron_toBe - subToFireNeuron_current[1,1,i]
|
||||
# totalNewConn[1,1,i] = totalNewConn[1,1,i] - toAddConn
|
||||
# # add new conn to firing neurons pool
|
||||
# remaining = addNewSynapticConn!(zitMask[:,:,i], 1,
|
||||
# @view(wRec[:,:,i]),
|
||||
# @view(synapseReconnectDelay[:,:,i]),
|
||||
# toAddConn)
|
||||
# totalNewConn[1,1,i] += remaining
|
||||
# end
|
||||
|
||||
# add new conn to non-firing neurons pool
|
||||
remaining = addNewSynapticConn!(zitMask[:,:,i], 0,
|
||||
@view(wRec[:,:,i]),
|
||||
@view(synapseReconnectDelay[:,:,i]),
|
||||
totalNewConn[1,1,i])
|
||||
if remaining > 0 # final get-all round if somehow non-firing pool has not enough slot
|
||||
remaining = addNewSynapticConn!(zitMask[:,:,i], 1,
|
||||
@view(wRec[:,:,i]),
|
||||
@view(synapseReconnectDelay[:,:,i]),
|
||||
remaining)
|
||||
end
|
||||
end
|
||||
end
|
||||
# # add new conn to non-firing neurons pool
|
||||
# remaining = addNewSynapticConn!(zitMask[:,:,i], 0,
|
||||
# @view(wRec[:,:,i]),
|
||||
# @view(synapseReconnectDelay[:,:,i]),
|
||||
# totalNewConn[1,1,i])
|
||||
# if remaining > 0 # final get-all round if somehow non-firing pool has not enough slot
|
||||
# remaining = addNewSynapticConn!(zitMask[:,:,i], 1,
|
||||
# @view(wRec[:,:,i]),
|
||||
# @view(synapseReconnectDelay[:,:,i]),
|
||||
# remaining)
|
||||
# end
|
||||
# end
|
||||
# end
|
||||
|
||||
# error("DEBUG -> neuroplasticity $(Dates.now())")
|
||||
return wRec
|
||||
@@ -792,7 +741,7 @@ end
|
||||
|
||||
# # for each neuron, count how many synap already subscribed to firing-neurons
|
||||
# zw = zitCumulative .* wRec
|
||||
# subToFireNeuron_current = sum(GeneralUtils.isBetween.(zw, 0.0, 100.0), dims=(1,2)) # (1, 1, n)
|
||||
# subToFireNeuron_current = sum(GeneralUtils.GeneralUtils.isBetween.(zw, 0.0, 100.0), dims=(1,2)) # (1, 1, n)
|
||||
# zitMask = (!iszero).(zitCumulative) # zitMask of firing neurons = 1, non-firing = 0
|
||||
# projection = ones(i1,i2,i3)
|
||||
# zitMask = zitMask .* projection # (row, col, n)
|
||||
|
||||
Reference in New Issue
Block a user