version 0.0.2

src/IronpenGPU.jl

@@ -25,9 +25,8 @@ using .interface
 
 #------------------------------------------------------------------------------------------------100
 
-""" version 0.0.1
+""" version 0.0.2
     Todo:
-        [*1] knowledgeFn in GPU format
         [] use partial error update for computeNeuron
         [] use integrate_neuron_params synapticConnectionPercent LESS THAN 100%
         [2] implement dormant connection and pruning machanism. the longer the training the longer 
@@ -37,8 +36,8 @@ using .interface
         [] Liquid time constant. training should include adjusting α, neuron membrane potential decay factor
             which defined by neuron.tau_m formula in type.jl
 
-    Change from version:
-        - 
+    Change from version: 0.0.1
+        - knowledgeFn in GPU format
     
     All features
         

src/forward.jl

@@ -18,7 +18,19 @@ function (kfn::kfn_1)(input::AbstractArray)
     #TODO time step forward
     if view(kfn.learningStage, 1)[1] == 1
         # reset learning params
-        # kfn.learningStage = [2]
+        kfn.lif_vt .= 0
+        kfn.lif_wRecChange .= 0
+        kfn.lif_epsilonRec .= 0
+        
+        kfn.alif_vt .= 0
+        kfn.alif_epsilonRec .= 0
+        kfn.alif_wRecChange .= 0
+
+        kfn.on_vt .= 0
+        kfn.on_epsilonRec .= 0
+        kfn.on_wOutChange .= 0
+
+        kfn.learningStage = [2]
     end
     
     # update activation matrix with "lif_zt1" and "alif_zt1" by concatenating
@@ -27,12 +39,6 @@ function (kfn::kfn_1)(input::AbstractArray)
                 reshape(kfn.lif_zt, (size(input, 1), :, 1, size(input, 3))), 
                 reshape(kfn.alif_zt, (size(input, 1), :, 1, size(input, 3))), dims=2)
     kfn.zit .= reshape(_zit, (size(input, 1), :, size(input, 3)))
-    
-    # pass input_data into input neuron.
-#     GeneralUtils.cartesianAssign!(kfn.zit, input)
-
-#     kfn.zit = kfn.zit |> device
-#     input = input |> device
 
     # project 3D kfn zit into 4D lif zit
     i1, i2, i3, i4 = size(kfn.lif_zit)

src/learn.jl

@@ -42,8 +42,6 @@ function compute_paramsChange!(kfn::kfn_1, modelError, outputError)
     # error("DEBUG ->  kfn compute_paramsChange!    $(Dates.now())")
 end
 
-
-
 function lifComputeParamsChange!(   phi::CuArray,
                                     epsilonRec::CuArray,
                                     eta::CuArray,
@@ -197,15 +195,18 @@ end
 function learn!(kfn::kfn_1)
     # lif learn
     lifLearn!(kfn.lif_wRec,
-            kfn.lif_wRecChange)
+            kfn.lif_wRecChange,
+            kfn.lif_arrayProjection4d)
     
     # alif learn
     alifLearn!(kfn.alif_wRec,
-            kfn.alif_wRecChange)
+            kfn.alif_wRecChange,
+            kfn.alif_arrayProjection4d)
 
     # on learn
     onLearn!(kfn.on_wOut,
-            kfn.on_wOutChange)
+            kfn.on_wOutChange,
+            kfn.on_arrayProjection4d)
 
     # wOut decay
     kfn.on_wOut .*= 0.0001
@@ -218,9 +219,11 @@ function learn!(kfn::kfn_1)
 end
 
 function lifLearn!(wRec,
-                    wRecChange)
-    # merge learning weight
-    wRec .+= wRecChange
+                    wRecChange,
+                    arrayProjection4d)
+
+    # merge learning weight with average learning weight
+    wRec .+= (sum(wRecChange) ./ (size(wRec, 4))) .* arrayProjection4d
 
     #TODO synaptic strength 
 
@@ -229,9 +232,10 @@ function lifLearn!(wRec,
 end
 
 function alifLearn!(wRec,
-                    wRecChange)
+                    wRecChange,
+                    arrayProjection4d)
     # merge learning weight
-    wRec .+= wRecChange
+    wRec .+= (sum(wRecChange) ./ (size(wRec, 4))) .* arrayProjection4d
 
     #TODO synaptic strength 
 
@@ -240,9 +244,10 @@ function alifLearn!(wRec,
 end
 
 function onLearn!(wOut,
-                    wOutChange)
+                    wOutChange,
+                    arrayProjection4d)
     # merge learning weight
-    wOut .+= wOutChange
+    wOut .+= (sum(wOutChange) ./ (size(wOut, 4))) .* arrayProjection4d
 
     #TODO synaptic strength