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refractoring

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This commit is contained in:
tonaerospace
2023-05-16 23:35:56 +07:00
parent fbc40ccef4
commit b9a140372d
2 changed files with 14 additions and 6 deletions
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1
src/learn.jl
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@@ -147,6 +147,7 @@ function learn!(n::alif_neuron, error::Number)
ΔwRecChange = n.eta * error ΔwRecChange = n.eta * error
n.wRecChange = (n.subExInType * n.wRecChange) + ΔwRecChange n.wRecChange = (n.subExInType * n.wRecChange) + ΔwRecChange
reset_epsilonRec!(n) reset_epsilonRec!(n)
reset_epsilonRecA!(n)
end end
""" linear_neuron learn() """ linear_neuron learn()

19
src/snn_utils.jl
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@@ -4,7 +4,7 @@ using Flux.Optimise: apply!
export calculate_α, calculate_ρ, calculate_k, timestep_forward!, init_neuron, no_negative!, export calculate_α, calculate_ρ, calculate_k, timestep_forward!, init_neuron, no_negative!,
precision, calculate_w_change!, store_knowledgefn_error!, interneurons_adjustment!, precision, calculate_w_change!, store_knowledgefn_error!, interneurons_adjustment!,
reset_z_t!, resetLearningParams!, reset_learning_history_params!, reset_epsilonRec!, reset_z_t!, resetLearningParams!, reset_learning_history_params!, reset_epsilonRec!,
cal_v_reg!, calculate_w_change_end!, reset_epsilonRecA!,
firing_rate_error!, firing_rate_regulator!, update_Bn!, cal_firing_reg!, firing_rate_error!, firing_rate_regulator!, update_Bn!, cal_firing_reg!,
neuroplasticity!, shakeup!, reset_learning_no_wchange!, adjust_internal_learning_rate!, neuroplasticity!, shakeup!, reset_learning_no_wchange!, adjust_internal_learning_rate!,
gradient_withloss gradient_withloss
@@ -34,7 +34,7 @@ reset_v_t!(n::neuron) = n.v_t = n.vRest
reset_z_t!(n::compute_neuron) = n.z_t = false reset_z_t!(n::compute_neuron) = n.z_t = false
reset_epsilonRec!(n::compute_neuron) = n.epsilonRec = n.epsilonRec * 0.0 reset_epsilonRec!(n::compute_neuron) = n.epsilonRec = n.epsilonRec * 0.0
reset_epsilonRec!(n::output_neuron) = n.epsilonRec = n.epsilonRec * 0.0 reset_epsilonRec!(n::output_neuron) = n.epsilonRec = n.epsilonRec * 0.0
reset_epsilon_rec_a!(n::alif_neuron) = n.epsilonRecA = n.epsilonRecA * 0.0 reset_epsilonRecA!(n::alif_neuron) = n.epsilonRecA = n.epsilonRecA * 0.0
reset_epsilon_in!(n::compute_neuron) = n.epsilon_in = isnothing(n.epsilon_in) ? nothing : n.epsilon_in * 0.0 reset_epsilon_in!(n::compute_neuron) = n.epsilon_in = isnothing(n.epsilon_in) ? nothing : n.epsilon_in * 0.0
reset_error!(n::Union{compute_neuron, linear_neuron}) = n.error = nothing reset_error!(n::Union{compute_neuron, linear_neuron}) = n.error = nothing
reset_w_in_change!(n::compute_neuron) = n.w_in_change = isnothing(n.w_in_change) ? nothing : n.w_in_change * 0.0 reset_w_in_change!(n::compute_neuron) = n.w_in_change = isnothing(n.w_in_change) ? nothing : n.w_in_change * 0.0
@@ -75,7 +75,7 @@ reset_b_change!(n::linear_neuron) = n.b_change = n.b_change * 0.0
# end # end
# function reset_learning_no_wchange!(n::Union{alif_neuron, elif_neuron}) # function reset_learning_no_wchange!(n::Union{alif_neuron, elif_neuron})
# reset_epsilonRec!(n) # reset_epsilonRec!(n)
# reset_epsilon_rec_a!(n) # reset_epsilonRecA!(n)
# reset_v_t!(n) # reset_v_t!(n)
# reset_z_t!(n) # reset_z_t!(n)
# # reset_a!(n) # # reset_a!(n)
@@ -113,7 +113,7 @@ function resetLearningParams!(n::lif_neuron)
end end
function resetLearningParams!(n::alif_neuron) function resetLearningParams!(n::alif_neuron)
reset_epsilonRec!(n) reset_epsilonRec!(n)
reset_epsilon_rec_a!(n) reset_epsilonRecA!(n)
reset_wRecChange!(n) reset_wRecChange!(n)
# reset_v_t!(n) # reset_v_t!(n)
# reset_z_t!(n) # reset_z_t!(n)
@@ -300,10 +300,17 @@ end
function synapticConnStrength(n::compute_neuron) function synapticConnStrength(n::compute_neuron)
for (i, connStrength) in enumerate(n.synapticStrength) for (i, connStrength) in enumerate(n.synapticStrength)
n. #WORKING
synapticConnStrength # check whether connStrength increase or decrease based on usage from n.epsilonRec
# compute synaptic strength for this conn
# apply conn lowerlimit and upperlimit
# at lowerlimit, mark wRec at this position to 0. for new random synaptic conn
end
end end