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This commit is contained in:
ton
2023-07-26 15:21:34 +07:00
parent ff9909fd8d
commit a94354efb3
6 changed files with 224 additions and 87 deletions
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135
src/type.jl
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@@ -43,8 +43,10 @@ Base.@kwdef mutable struct kfn_1 <: knowledgeFn
lif_tau_m::AbstractFloat = 20.0
lif_phi::Union{AbstractArray, Nothing} = nothing
lif_epsilonRec::Union{AbstractArray, Nothing} = nothing
# lif_eRec::Union{AbstractArray, Nothing} = nothing
lif_eta::Union{AbstractArray, Nothing} = nothing
lif_gammaPd::Union{AbstractArray, Nothing} = nothing
lif_wRecChange::Union{AbstractArray, Nothing} = nothing
lif_firingCounter::Union{AbstractArray, Nothing} = nothing
@@ -69,8 +71,10 @@ Base.@kwdef mutable struct kfn_1 <: knowledgeFn
alif_phi::Union{AbstractArray, Nothing} = nothing
alif_epsilonRec::Union{AbstractArray, Nothing} = nothing
alif_epsilonRecA::Union{AbstractArray, Nothing} = nothing
# alif_eRec::Union{AbstractArray, Nothing} = nothing
alif_eta::Union{AbstractArray, Nothing} = nothing
alif_gammaPd::Union{AbstractArray, Nothing} = nothing
alif_wRecChange::Union{AbstractArray, Nothing} = nothing
alif_firingCounter::Union{AbstractArray, Nothing} = nothing
@@ -85,7 +89,7 @@ Base.@kwdef mutable struct kfn_1 <: knowledgeFn
# output neuron is based on LIF
on_zit::Union{AbstractArray, Nothing} = nothing
on_wRec::Union{AbstractArray, Nothing} = nothing
on_wOut::Union{AbstractArray, Nothing} = nothing # same as lif_wRec
on_vt0::Union{AbstractArray, Nothing} = nothing
on_vt1::Union{AbstractArray, Nothing} = nothing
on_vth::Union{AbstractArray, Nothing} = nothing
@@ -99,8 +103,10 @@ Base.@kwdef mutable struct kfn_1 <: knowledgeFn
on_tau_m::AbstractFloat = 20.0
on_phi::Union{AbstractArray, Nothing} = nothing
on_epsilonRec::Union{AbstractArray, Nothing} = nothing
on_eRec::Union{AbstractArray, Nothing} = nothing
on_eta::Union{AbstractArray, Nothing} = nothing
on_gammaPd::Union{AbstractArray, Nothing} = nothing
on_wOutChange::Union{AbstractArray, Nothing} = nothing
on_firingCounter::Union{AbstractArray, Nothing} = nothing
end
@@ -128,24 +134,26 @@ function kfn_1(params::Dict)
# ---------------------------------------------------------------------------- #
# In 3D LIF matrix, z-axis represent each neuron while each 2D slice represent that neuron's
# synaptic subscription to other neurons (via activation matrix)
z = kfn.params[:computeNeuron][:lif][:numbers][1] * kfn.params[:computeNeuron][:lif][:numbers][2]
kfn.lif_zit = zeros(row, col, z, batch)
kfn.lif_vt0 = zeros(1, 1, z, batch)
kfn.lif_vt1 = zeros(1, 1, z, batch)
kfn.lif_vth = ones(1, 1, z, batch)
kfn.lif_vRest = zeros(1, 1, z, batch)
kfn.lif_zt0 = zeros(1, 1, z, batch)
kfn.lif_zt1 = zeros(1, 1, z, batch)
kfn.lif_refractoryCounter = zeros(1, 1, z, batch)
kfn.lif_refractoryDuration = ones(1, 1, z, batch) .* 3
kfn.lif_alpha = ones(1, 1, z, batch) .* (exp(-kfn.lif_delta / kfn.lif_tau_m))
kfn.lif_phi = zeros(1, 1, z, batch)
kfn.lif_epsilonRec = zeros(row, col, z, batch)
kfn.lif_eta = zeros(1, 1, z, batch)
kfn.lif_gammaPd = zeros(1, 1, z, batch) .* 0.3
n = kfn.params[:computeNeuron][:lif][:numbers][1] * kfn.params[:computeNeuron][:lif][:numbers][2]
kfn.lif_zit = zeros(row, col, n, batch)
kfn.lif_vt0 = zeros(1, 1, n, batch)
kfn.lif_vt1 = zeros(1, 1, n, batch)
kfn.lif_vth = ones(1, 1, n, batch)
kfn.lif_vRest = zeros(1, 1, n, batch)
kfn.lif_zt0 = zeros(1, 1, n, batch)
kfn.lif_zt1 = zeros(1, 1, n, batch)
kfn.lif_refractoryCounter = zeros(1, 1, n, batch)
kfn.lif_refractoryDuration = ones(1, 1, n, batch) .* 3
kfn.lif_alpha = ones(1, 1, n, batch) .* (exp(-kfn.lif_delta / kfn.lif_tau_m))
kfn.lif_phi = zeros(1, 1, n, batch)
kfn.lif_epsilonRec = zeros(row, col, n, batch)
# kfn.lif_eRec = zeros(row, col, n, batch)
kfn.lif_eta = zeros(1, 1, n, batch)
kfn.lif_gammaPd = zeros(1, 1, n, batch) .* 0.3
kfn.lif_wRecChange = zeros(row, col, n, batch)
# subscription
w = zeros(row, col, z)
w = zeros(row, col, n)
synapticConnectionPercent = kfn.params[:computeNeuron][:lif][:params][:synapticConnectionPercent]
synapticConnection = Int(floor(row*col * synapticConnectionPercent/100))
for slice in eachslice(w, dims=3)
@@ -155,36 +163,38 @@ function kfn_1(params::Dict)
end
end
# project 3D w into 4D kfn.lif_wRec
kfn.lif_wRec = reshape(w, (row, col, z, 1)) .* ones(row, col, z, batch)
kfn.lif_firingCounter = zeros(1, 1, z, batch)
kfn.lif_wRec = reshape(w, (row, col, n, 1)) .* ones(row, col, n, batch)
kfn.lif_firingCounter = zeros(1, 1, n, batch)
# ---------------------------------------------------------------------------- #
# ALIF config #
# ---------------------------------------------------------------------------- #
z = kfn.params[:computeNeuron][:alif][:numbers][1] * kfn.params[:computeNeuron][:alif][:numbers][2]
kfn.alif_zit = zeros(row, col, z, batch)
kfn.alif_vt0 = zeros(1, 1, z, batch)
kfn.alif_vt1 = zeros(1, 1, z, batch)
kfn.alif_vth = ones(1, 1, z, batch)
kfn.alif_avth = ones(1, 1, z, batch)
kfn.alif_vRest = zeros(1, 1, z, batch)
kfn.alif_zt0 = zeros(1, 1, z, batch)
kfn.alif_zt1 = zeros(1, 1, z, batch)
kfn.alif_refractoryCounter = zeros(1, 1, z, batch)
kfn.alif_refractoryDuration = ones(1, 1, z, batch) .* 3
kfn.alif_alpha = ones(1, 1, z, batch) .* (exp(-kfn.alif_delta / kfn.alif_tau_m))
kfn.alif_phi = zeros(1, 1, z, batch)
kfn.alif_epsilonRec = zeros(row, col, z, batch)
kfn.alif_epsilonRecA = zeros(row, col, z, batch)
kfn.alif_eta = zeros(1, 1, z, batch)
kfn.alif_gammaPd = zeros(1, 1, z, batch) .* 0.3
n = kfn.params[:computeNeuron][:alif][:numbers][1] * kfn.params[:computeNeuron][:alif][:numbers][2]
kfn.alif_zit = zeros(row, col, n, batch)
kfn.alif_vt0 = zeros(1, 1, n, batch)
kfn.alif_vt1 = zeros(1, 1, n, batch)
kfn.alif_vth = ones(1, 1, n, batch)
kfn.alif_avth = ones(1, 1, n, batch)
kfn.alif_vRest = zeros(1, 1, n, batch)
kfn.alif_zt0 = zeros(1, 1, n, batch)
kfn.alif_zt1 = zeros(1, 1, n, batch)
kfn.alif_refractoryCounter = zeros(1, 1, n, batch)
kfn.alif_refractoryDuration = ones(1, 1, n, batch) .* 3
kfn.alif_alpha = ones(1, 1, n, batch) .* (exp(-kfn.alif_delta / kfn.alif_tau_m))
kfn.alif_phi = zeros(1, 1, n, batch)
kfn.alif_epsilonRec = zeros(row, col, n, batch)
kfn.alif_epsilonRecA = zeros(row, col, n, batch)
# kfn.alif_eRec = zeros(row, col, n, batch)
kfn.alif_eta = zeros(1, 1, n, batch)
kfn.alif_gammaPd = zeros(1, 1, n, batch) .* 0.3
kfn.alif_wRecChange = zeros(row, col, n, batch)
kfn.alif_a = zeros(1, 1, z, batch)
kfn.alif_beta = zeros(1, 1, z, batch) .* 0.15
kfn.alif_rho = zeros(1, 1, z, batch) .* (exp(-kfn.alif_delta / kfn.alif_tau_a))
kfn.alif_a = zeros(1, 1, n, batch)
kfn.alif_beta = zeros(1, 1, n, batch) .* 0.15
kfn.alif_rho = zeros(1, 1, n, batch) .* (exp(-kfn.alif_delta / kfn.alif_tau_a))
# subscription
w = zeros(row, col, z)
w = zeros(row, col, n)
synapticConnectionPercent = kfn.params[:computeNeuron][:alif][:params][:synapticConnectionPercent]
synapticConnection = Int(floor(row*col * synapticConnectionPercent/100))
for slice in eachslice(w, dims=3)
@@ -194,31 +204,32 @@ function kfn_1(params::Dict)
end
end
# project 3D w into 4D kfn.alif_wRec
kfn.alif_wRec = reshape(w, (row, col, z, 1)) .* ones(row, col, z, batch)
kfn.alif_firingCounter = zeros(1, 1, z, batch)
kfn.alif_wRec = reshape(w, (row, col, n, 1)) .* ones(row, col, n, batch)
kfn.alif_firingCounter = zeros(1, 1, n, batch)
# ---------------------------------------------------------------------------- #
# output config #
# ---------------------------------------------------------------------------- #
#WORKING
z = kfn.params[:outputPort][:numbers][1] * kfn.params[:outputPort][:numbers][2]
kfn.on_zit = zeros(row, col, z, batch)
kfn.on_vt0 = zeros(1, 1, z, batch)
kfn.on_vt1 = zeros(1, 1, z, batch)
kfn.on_vth = ones(1, 1, z, batch)
kfn.on_vRest = zeros(1, 1, z, batch)
kfn.on_zt0 = zeros(1, 1, z, batch)
kfn.on_zt1 = zeros(1, 1, z, batch)
kfn.on_refractoryCounter = zeros(1, 1, z, batch)
kfn.on_refractoryDuration = ones(1, 1, z, batch) .* 1
kfn.on_alpha = ones(1, 1, z, batch) .* (exp(-kfn.on_delta / kfn.on_tau_m))
kfn.on_phi = zeros(1, 1, z, batch)
kfn.on_epsilonRec = zeros(row, col, z, batch)
kfn.on_eta = zeros(1, 1, z, batch)
kfn.on_gammaPd = zeros(1, 1, z, batch) .* 0.3
n = kfn.params[:outputPort][:numbers][1] * kfn.params[:outputPort][:numbers][2]
kfn.on_zit = zeros(row, col, n, batch)
kfn.on_vt0 = zeros(1, 1, n, batch)
kfn.on_vt1 = zeros(1, 1, n, batch)
kfn.on_vth = ones(1, 1, n, batch)
kfn.on_vRest = zeros(1, 1, n, batch)
kfn.on_zt0 = zeros(1, 1, n, batch)
kfn.on_zt1 = zeros(1, 1, n, batch)
kfn.on_refractoryCounter = zeros(1, 1, n, batch)
kfn.on_refractoryDuration = ones(1, 1, n, batch) .* 1
kfn.on_alpha = ones(1, 1, n, batch) .* (exp(-kfn.on_delta / kfn.on_tau_m))
kfn.on_phi = zeros(1, 1, n, batch)
kfn.on_epsilonRec = zeros(row, col, n, batch)
# kfn.on_eRec = zeros(row, col, n, batch)
kfn.on_eta = zeros(1, 1, n, batch)
kfn.on_gammaPd = zeros(1, 1, n, batch) .* 0.3
kfn.on_wOutChange = zeros(row, col, n, batch)
# subscription
w = zeros(row, col, z)
w = zeros(row, col, n)
synapticConnectionPercent = kfn.params[:outputPort][:params][:synapticConnectionPercent]
synapticConnection = Int(floor(row*col * synapticConnectionPercent/100))
for slice in eachslice(w, dims=3)
@@ -227,9 +238,9 @@ function kfn_1(params::Dict)
slice[i] = randn()/10 # assign weight to synaptic connection
end
end
# project 3D w into 4D kfn.on_wRec
kfn.on_wRec = reshape(w, (row, col, z, 1)) .* ones(row, col, z, batch)
kfn.on_firingCounter = zeros(1, 1, z, batch)
# project 3D w into 4D kfn.on_wOut
kfn.on_wOut = reshape(w, (row, col, n, 1)) .* ones(row, col, n, batch)
kfn.on_firingCounter = zeros(1, 1, n, batch)