refractoring

src/forward.jl

@@ -31,6 +31,29 @@ function (kfn::kfn_1)(m::model, input_data::AbstractVector)
 
     kfn.learningStage = m.learningStage
 
+    if kfn.learningStage == "start_learning"
+        # reset params here instead of at the end_learning so that neuron's parameter data
+        # don't gets wiped and can be logged for visualization later
+        for n in kfn.neuronsArray
+            # epsilonRec need to be reset because it counting how many each synaptic fires and 
+            # use this info to calculate how much synaptic weight should be adjust
+            resetLearningParams!(n)
+        end
+
+        for n in kfn.output_neuron
+            # epsilonRec need to be reset because it counting how many each synaptic fires and 
+            # use this info to calculate how much synaptic weight should be adjust
+            resetLearningParams!(n)
+        end
+
+        # clear variables
+        kfn.firedNeurons = Vector{Int64}()   
+        kfn.firedNeurons_t0 = Vector{Bool}()
+        kfn.firedNeurons_t1 = Vector{Bool}()
+
+        kfn.learningStage = "learning"
+    end
+
     # generate noise
     noise = [GeneralUtils.randomChoiceWithProb([true, false],[0.5,0.5])
                 for i in 1:length(input_data)]
@@ -41,6 +64,9 @@ function (kfn::kfn_1)(m::model, input_data::AbstractVector)
     for n in kfn.neuronsArray
         timestep_forward!(n)
     end
+    for n in kfn.outputNeuronsArray
+        timestep_forward!(n)
+    end
 
     # pass input_data into input neuron.
     # number of data point equals to number of input neuron starting from id 1
@@ -89,7 +115,6 @@ function (n::lif_neuron)(kfn::knowledgeFn)
 
     # pulling other neuron's firing status at time t
     n.z_i_t = getindex(kfn.firedNeurons_t0, n.subscriptionList)
-    n.z_i_t .*= n.subExInType
 
     if n.refractoryCounter != 0
         n.refractoryCounter -= 1
@@ -102,7 +127,7 @@ function (n::lif_neuron)(kfn::knowledgeFn)
         # decay of v_t1
         n.v_t1 = n.alpha * n.v_t
     else
-        n.recSignal = sum(n.wRec .* n.z_i_t)  # signal from other neuron that this neuron subscribed
+        n.recSignal = sum(n.wRec .* n.z_i_t .* n.subExInType)  # signal from other neuron that this neuron subscribed
     
         n.alpha_v_t = n.alpha * n.v_t
         n.v_t1 = n.alpha_v_t + n.recSignal
@@ -132,7 +157,6 @@ function (n::alif_neuron)(kfn::knowledgeFn)
     n.timeStep = kfn.timeStep
 
     n.z_i_t = getindex(kfn.firedNeurons_t0, n.subscriptionList)
-    n.z_i_t .*= n.subExInType
 
     if n.refractoryCounter != 0
         n.refractoryCounter -= 1
@@ -149,7 +173,7 @@ function (n::alif_neuron)(kfn::knowledgeFn)
         n.z_t = isnothing(n.z_t) ? false : n.z_t
         n.a = (n.rho * n.a) + ((1 - n.rho) * n.z_t)
         n.av_th = n.v_th + (n.beta * n.a)
-        n.recSignal = sum(n.wRec .* n.z_i_t)  # signal from other neuron that this neuron subscribed
+        n.recSignal = sum(n.wRec .* n.z_i_t .* n.subExInType)  # signal from other neuron that this neuron subscribed
         n.alpha_v_t = n.alpha * n.v_t
         n.v_t1 = n.alpha_v_t + n.recSignal
         n.v_t1 = no_negative!.(n.v_t1)
@@ -181,7 +205,6 @@ function (n::linear_neuron)(kfn::T) where T<:knowledgeFn
 
     # pulling other neuron's firing status at time t
     n.z_i_t = getindex(kfn.firedNeurons_t0, n.subscriptionList)
-    n.z_i_t .*= n.subExInType
 
     if n.refractoryCounter != 0
         n.refractoryCounter -= 1
@@ -194,7 +217,7 @@ function (n::linear_neuron)(kfn::T) where T<:knowledgeFn
         # decay of v_t1
         n.v_t1 = n.alpha * n.v_t
     else
-        n.recSignal = sum(n.wRec .* n.z_i_t)  # signal from other neuron that this neuron subscribed
+        n.recSignal = sum(n.wRec .* n.z_i_t .* n.subExInType)  # signal from other neuron that this neuron subscribed
     
         n.alpha_v_t = n.alpha * n.v_t
         n.v_t1 = n.alpha_v_t + n.recSignal