lif forward
This commit is contained in:
141
src/forward.jl
141
src/forward.jl
@@ -17,91 +17,114 @@ function (kfn::kfn_1)(input::AbstractArray)
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end
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println(">>> input ", size(input))
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# pass input_data into input neuron.
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GeneralUtils.cartesianAssign!(kfn.z_i_t, input)
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kfn.lif_z_i_t = GeneralUtils.matMul_3Dto4D_batchwise(kfn.z_i_t,
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ones(size(kfn.z_i_t)[1], size(kfn.z_i_t)[2], size(kfn.lif_w)[3], size(kfn.z_i_t)[3]))
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println(">>> z_i_t ", size(kfn.z_i_t))
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println(">>> lif_z_i_t ", size(kfn.lif_z_i_t))
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println(">>> lif_recSignal ", size(kfn.lif_recSignal))
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println(">>> lif_w ", size(kfn.lif_w))
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println(">>> lif_refractoryActive ", size(kfn.lif_refractoryCounter))
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println(">>> zit ", size(kfn.zit))
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# println(">>> lif_zit ", size(kfn.lif_zit))
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# println(">>> lif_recSignal ", size(kfn.lif_recSignal))
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println(">>> lif_wRec ", size(kfn.lif_wRec))
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println(">>> lif_refractoryCounter ", size(kfn.lif_refractoryCounter))
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println(">>> lif_alpha ", size(kfn.lif_alpha))
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println(">>> lif_vt0 ", size(kfn.lif_vt0))
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println(">>> lif_vt0 sum ", sum(kfn.lif_vt0))
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# check active/inactive neurons
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refractoryStatus!(kfn.lif_refractoryCounter, kfn.lif_refractoryActive, kfn.lif_refractoryInactive)
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refractoryStatus!(kfn.alif_refractoryCounter, kfn.alif_refractoryActive, kfn.alif_refractoryInactive)
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# pass input_data into input neuron.
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s1, s2, s3 = size(input)
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GeneralUtils.cartesianAssign!(kfn.zit, reshape(input, (s1, s2, 1, s3)))
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#WORKING LIF forward active neurons
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# a = kfn.lif_refractoryActive .* kfn.lif_w
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# lifForward.(kfn.lif_refractoryCounter, kfn.z_i_t0, kfn.z_i_t1,
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lifForward( kfn.zit,
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kfn.lif_zit,
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kfn.lif_wRec,
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kfn.lif_vt0,
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kfn.lif_vt1,
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kfn.lif_vth,
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kfn.lif_vRest,
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kfn.lif_zt1,
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kfn.lif_alpha,
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kfn.lif_phi,
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kfn.lif_epsilonRec,
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kfn.lif_refractoryCounter,
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kfn.lif_refractoryDuration,)
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error("debug end kfn forward")
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# kfn.lif_zit = GeneralUtils.matMul_3Dto4D_batchwise(kfn.zit,
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# ones(size(kfn.zit)[1], size(kfn.zit)[2], size(kfn.lif_wRec)[3], size(kfn.zit)[3]))
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# check active/inactive neurons
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# refractoryStatus!(kfn.lif_refractoryCounter, kfn.lif_refractoryActive, kfn.lif_refractoryInactive)
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# refractoryStatus!(kfn.alif_refractoryCounter, kfn.alif_refractoryActive, kfn.alif_refractoryInactive)
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# a = kfn.lif_refractoryActive .* kfn.lif_wRec
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# lifForward.(kfn.lif_refractoryCounter, kfn.zit0, kfn.zit1,
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# kfn.lif_vt0, kfn.lif_vt1, kfn.lif_alpha, kfn.lif_recSignal)
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# kfn.lif_recSignal .= GeneralUtils.sumAlongDim3(
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# GeneralUtils.matMul_3Dto4D_batchwise(kfn.z_i_t1, kfn.lif_refractoryActive .* kfn.lif_w))
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# GeneralUtils.matMul_3Dto4D_batchwise(kfn.zit1, kfn.lif_refractoryActive .* kfn.lif_wRec))
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# kfn.lif_vt1 = (kfn.lif_alpha .* kfn.lif_vt0) .+ kfn.lif_recSignal
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# GeneralUtils.batchMatEleMul(kfn.z_i_t1, kfn.alif_w, resultStorage=kfn.alif_recSignal)
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# GeneralUtils.batchMatEleMul(kfn.zit1, kfn.alif_wRec, resultStorage=kfn.alif_recSignal)
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error("debug end kfn forward")
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end
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function lifForward(lif_refractoryCounter, z_i_t0, z_i_t1, lif_w, lif_vt0, lif_vt1, lif_alpha,
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lif_recSignal)
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error("debug end LIF forward")
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# if n.refractoryCounter != 0
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# n.refractoryCounter -= 1
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function lifForward(zit,
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lif_zit,
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lif_wRec,
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lif_vt0,
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lif_vt1,
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lif_vth,
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lif_vRest,
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lif_zt1,
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lif_alpha,
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lif_phi,
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lif_epsilonRec,
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lif_refractoryCounter,
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lif_refractoryDuration,)
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_, _, d3, d4 = size(lif_wRec)
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lif_zit .= zit .* ones(size(lif_wRec)...) # project zit into lif_zit
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# # neuron is in refractory state, skip all calculation
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# n.z_t1 = false # used by timestep_forward() in kfn. Set to zero because neuron spike
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# # last only 1 timestep follow by a period of refractory.
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# n.recSignal = n.recSignal * 0.0
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# # decay of v_t1
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# n.v_t1 = n.alpha * n.v_t
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for j in 1:d4, i in 1:d3 # compute along neurons axis of every batch
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if view(lif_refractoryCounter, :, :, i, j)[1] > 0 # refractory period is active
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view(lif_refractoryCounter, :, :, i, j)[1] -= 1
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view(lif_zt1, :, :, i, j)[1] = 0
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view(lif_vt1, :, :, i, j)[1] = view(lif_alpha, :, :, i, j)[1] * view(lif_vt0, :, :, i, j)[1]
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view(lif_phi, :, :, i, j)[1] = 0.0
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view(lif_epsilonRec, :, :, i, j) .= view(lif_alpha, :, :, i, j)[1] .*
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view(lif_epsilonRec, :, :, i, j)
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else # refractory period is inactive
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view(lif_vt1, :, :, i, j)[1] =
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(view(lif_alpha, :, :, i, j)[1] * view(lif_vt0,:, :, i, j)[1]) +
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sum(view(lif_zit, :, :, i, j) .* view(lif_wRec, :, :, i, j))
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if view(lif_vt1, :, :, i, j)[1] > view(lif_vth, :, :, i, j)[1]
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view(lif_zt1, :, :, i, j)[1] = 1
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view(lif_refractoryCounter, :, :, i, j)[1] = view(lif_refractoryDuration, :, :, i, j)[1]
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view(lif_firingCounter, :, :, i, j)[1] += 1
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view(lif_vt1, :, :, i, j)[1] = view(lif_vRest, :, :, i, j)[1]
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else
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view(lif_zt1, :, :, i, j)[1] = 0
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end
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end
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end
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# n.phi = 0.0
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# n.decayedEpsilonRec = n.alpha * n.epsilonRec
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# n.epsilonRec = n.decayedEpsilonRec
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# else
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# n.recSignal = sum(n.wRec .* n.z_i_t) # signal from other neuron that this neuron subscribed
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# # computeAlpha!(n)
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# n.alpha_v_t = n.alpha * n.v_t
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# n.v_t1 = n.alpha_v_t + n.recSignal
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# # n.v_t1 = no_negative!(n.v_t1)
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# if n.v_t1 > n.v_th
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# n.z_t1 = true
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# n.refractoryCounter = n.refractoryDuration
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# n.firingCounter += 1
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# n.v_t1 = n.vRest
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# else
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# n.z_t1 = false
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# end
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# # there is a difference from alif formula
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# n.phi = (n.gammaPd / n.v_th) * max(0, 1 - (n.v_t1 - n.v_th) / n.v_th)
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# n.decayedEpsilonRec = n.alpha * n.epsilonRec
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# n.epsilonRec = n.decayedEpsilonRec + n.z_i_t
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# end
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error("debug end -> LIF forward")
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end
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@@ -72,7 +72,6 @@ end
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end # module
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56
src/type.jl
56
src/type.jl
@@ -21,40 +21,44 @@ Base.@kwdef mutable struct kfn_1 <: knowledgeFn
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timeStep::AbstractArray = [0]
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learningStage::AbstractArray = [0] # 0 inference, 1 start, 2 during, 3 end learning
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z_i_t::Union{AbstractArray, Nothing} = nothing # 3D activation matrix
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zit::Union{AbstractArray, Nothing} = nothing # 3D activation matrix
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# ---------------------------------------------------------------------------- #
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# LIF #
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# ---------------------------------------------------------------------------- #
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# a projection of kfn.z_i_t into lif dimension for broadcasting later)
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lif_z_i_t::Union{AbstractArray, Nothing} = nothing
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# a projection of kfn.zit into lif dimension for broadcasting later)
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lif_zit::Union{AbstractArray, Nothing} = nothing
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lif_w::Union{AbstractArray, Nothing} = nothing
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lif_recSignal::Union{AbstractArray, Nothing} = nothing
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lif_wRec::Union{AbstractArray, Nothing} = nothing
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# lif_recSignal::Union{AbstractArray, Nothing} = nothing
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lif_vt0::Union{AbstractArray, Nothing} = nothing
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lif_vt1::Union{AbstractArray, Nothing} = nothing
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lif_vth::Union{AbstractArray, Nothing} = nothing
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lif_vRest::Union{AbstractArray, Nothing} = nothing
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lif_zt0::Union{AbstractArray, Nothing} = nothing
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lif_zt1::Union{AbstractArray, Nothing} = nothing
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lif_refractoryCounter::Union{AbstractArray, Nothing} = nothing
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lif_refractoryActive::Union{AbstractArray, Nothing} = nothing
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lif_refractoryInactive::Union{AbstractArray, Nothing} = nothing
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lif_refractoryDuration::Union{AbstractArray, Nothing} = nothing
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# lif_refractoryActive::Union{AbstractArray, Nothing} = nothing
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# lif_refractoryInactive::Union{AbstractArray, Nothing} = nothing
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lif_alpha::Union{AbstractArray, Nothing} = nothing
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lif_delta::AbstractFloat = 1.0
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lif_tau_m::AbstractFloat = 20.0
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lif_phi::Union{AbstractArray, Nothing} = nothing
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lif_epsilonRec::Union{AbstractArray, Nothing} = nothing
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lif_firingCounter::Union{AbstractArray, Nothing} = nothing
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# ---------------------------------------------------------------------------- #
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# ALIF #
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# ---------------------------------------------------------------------------- #
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alif_w::Union{AbstractArray, Nothing} = nothing
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alif_wRec::Union{AbstractArray, Nothing} = nothing
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alif_recSignal::Union{AbstractArray, Nothing} = nothing
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alif_zt0::Union{AbstractArray, Nothing} = nothing
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alif_zt1::Union{AbstractArray, Nothing} = nothing
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alif_refractoryCounter::Union{AbstractArray, Nothing} = nothing
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alif_refractoryActive::Union{AbstractArray, Nothing} = nothing
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alif_refractoryInactive::Union{AbstractArray, Nothing} = nothing
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end
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# outer constructor
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@@ -70,23 +74,27 @@ function kfn_1(params::Dict)
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col += kfn.params[:computeNeuron][:alif][:numbers][2]
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# activation matrix
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kfn.z_i_t = zeros(row, col, batch)
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kfn.zit = zeros(row, col, 1, batch)
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# -------------------------------- LIF config -------------------------------- #
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# In 3D LIF matrix, z-axis represent each neuron while each 2D slice represent that neuron's
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# synaptic subscription to other neurons (via activation matrix)
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z = kfn.params[:computeNeuron][:lif][:numbers][1] * kfn.params[:computeNeuron][:lif][:numbers][2]
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kfn.lif_recSignal = zeros(1, 1, z, batch)
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kfn.lif_zit = zeros(row, col, z, batch)
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# kfn.lif_recSignal = zeros(1, 1, z, batch)
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kfn.lif_vt0 = zeros(1, 1, z, batch)
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kfn.lif_vt1 = zeros(1, 1, z, batch)
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kfn.lif_vth = ones(1, 1, z, batch)
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kfn.lif_vRest = zeros(1, 1, z, batch)
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kfn.lif_zt0 = zeros(1, 1, z, batch)
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kfn.lif_zt1 = zeros(1, 1, z, batch)
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kfn.lif_refractoryCounter = zeros(1, 1, z, batch)
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kfn.lif_refractoryActive = zeros(1, 1, z, batch)
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kfn.lif_refractoryInactive = zeros(1, 1, z, batch)
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kfn.lif_refractoryDuration = ones(1, 1, z, batch) .* 3
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# kfn.lif_refractoryActive = zeros(1, 1, z, batch)
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# kfn.lif_refractoryInactive = zeros(1, 1, z, batch)
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kfn.lif_alpha = ones(1, 1, z, batch) .* (exp(-kfn.lif_delta / kfn.lif_tau_m))
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kfn.lif_phi = zeros(1, 1, z, batch)
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kfn.lif_epsilonRec = zeros(row, col, z, batch)
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# subscription
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w = zeros(row, col, z)
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@@ -98,14 +106,13 @@ function kfn_1(params::Dict)
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slice[i] = randn()/10 # assign weight to synaptic connection
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end
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end
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#WORKING project 3D w into 4D kfn.lif_w
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kfn.lif_w = reshape(w, (row, col, z, 1)) .* ones(row, col, z, batch)
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println(">>> lif_w ", size(kfn.lif_w))
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error("end WORKING")
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# project 3D w into 4D kfn.lif_wRec
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kfn.lif_wRec = reshape(w, (row, col, z, 1)) .* ones(row, col, z, batch)
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# ALIF
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kfn.lif_firingCounter = zeros(1, 1, z, batch)
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# -------------------------------- ALIF config ------------------------------- #
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z = kfn.params[:computeNeuron][:alif][:numbers][1] * kfn.params[:computeNeuron][:alif][:numbers][2]
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kfn.alif_w = zeros(row, col, z) # matrix z-axis represent each neurons
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kfn.alif_recSignal = zeros(1, 1, z, batch)
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kfn.alif_zt0 = zeros(1, 1, z, batch)
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kfn.alif_zt1 = zeros(1, 1, z, batch)
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@@ -114,16 +121,17 @@ function kfn_1(params::Dict)
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kfn.alif_refractoryInactive = zeros(1, 1, z, batch)
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# subscription
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row, col, _ = size(kfn.alif_w) # row*col is synaptic subscribe weight for each neuron in z-axis
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w = zeros(row, col, z)
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synapticConnectionPercent = kfn.params[:computeNeuron][:alif][:params][:synapticConnectionPercent]
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synapticConnection = Int(floor(row*col * synapticConnectionPercent/100))
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for slice in eachslice(kfn.alif_w, dims=3)
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for slice in eachslice(w, dims=3)
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pool = shuffle!([1:row*col...])[1:synapticConnection]
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for i in pool
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slice[i] = randn()/10
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end
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end
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# project 3D w into 4D kfn.lif_wRec
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kfn.alif_wRec = reshape(w, (row, col, z, 1)) .* ones(row, col, z, batch)
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