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Array Not Dimensioned Problem

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Array Not Dimensioned Problem
vspickelen Offline
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Posts: 26
Threads: 5
Joined: Mar 2005
#11
12-29-2005, 11:29 PM
Quote:But how do I do BackPropagation for the hidden layer?

You already got that down, man, it's under 'Calculate HL Error
vspickelen (really likes this)
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Torahteen Offline
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Posts: 684
Threads: 64
Joined: May 2004
#12
12-29-2005, 11:45 PM
Hmm... It's still not giving me correct results. Here is the code, followed by output.

[syntax="qbasic"]DEFINT A-Z

Declare Function sig(x As Double) As Double
Declare Sub DoNet()
Declare Sub TrainNet()
Declare Sub RunNet()
Declare Sub InitNet()

Const MAX_NODES = 20 'Maximum number of nuerons in one layer
Const NUM_IL = MAX_NODES 'Number of Nodes in Input Layer
Const NUM_HL = MAX_NODES 'Number of Nodes in Hidden Layer
Const NUM_OL = 10
Const IMG_WIDTH = 12
Const IMG_HEIGHT = 12
Const IMG_TOTAL = IMG_WIDTH * IMG_HEIGHT
Const LR = 0.05
Const GAIN = 5

Type Node
wt(1 To MAX_NODES) As Double 'Weights
act As Double 'Output of this Node
th As Double 'Threshold
e As Double 'Error
End Type

Dim Shared hl(1 To NUM_HL) As Node 'Hidden Layer
Dim Shared ol(1 To NUM_OL) As Node 'Output Layer

'Digit Images
Dim Shared img(0 To 9,1 To 12, 1 To 12) As Byte
Dim Shared curImg(1 To IMG_TOTAL) As Byte
'Begin Main
'Load the Images
For i = 0 To 9
For y = 1 To 12
For x = 1 To 12
Read img(i,x,y)
Next x
Next y
Next i


InitNet
Print "First, see how the NN performs before training"
RunNet
Sleep
Cls
Print "Now training network"
TrainNet
Cls
Print "Now see how the NN performs after training"
RunNet
Sleep
End

SUB DoNet()
DIM sum AS single

'Run through nodes in HL
FOR i = 1 TO NUM_HL
sum = 0
FOR j = 1 TO IMG_TOTAL
sum = sum + hl(i).wt(j) * curImg(j)
NEXT j
hl(i).act = sig(sum - hl(i).th)
NEXT i

'Run through nodes in OL
FOR i = 1 TO NUM_OL
sum = 0
FOR j = 1 TO NUM_HL
sum = sum + ol(i).wt(j) * hl(j).act
NEXT j
ol(i).act = sig(sum - ol(i).th)
NEXT i
END SUB

Sub InitNet()
Randomize Timer

'Hidden Layer
For i = 1 To NUM_HL
For j = 1 To NUM_IL
hl(i).wt(j) = (Rnd(1)/4)
Next j
Next i

'Output Layer
For i = 1 To NUM_OL
For j = 1 To NUM_HL
ol(i).wt(j) = (Rnd(1)/4)
Next j
Next i
End Sub

Sub TrainNet()
Dim numCycles As Integer
Dim current As Integer
Dim j As Integer
Dim sum As Double

Input "How many training cycles", numCycles
For i = 1 To numCycles
j = 1

current = Int(Rnd(1) * 10)

For y = 1 To IMG_WIDTH
For x = 1 To IMG_HEIGHT
curImg(j) = img(current, x, y)
j = j + 1
Next x
Next y

DoNet

'Calculate OL Error
For j = 1 To NUM_OL
If j = current Then
ol(j).e = (1 - ol(j).act) * ol(j).act * (1 - ol(j).act)
Else
ol(j).e = (0 - ol(j).act) * ol(j).act * (1 - ol(j).act)
End If
Next j

'Calculate HL Error

For j = 1 To NUM_HL
sum = 0
For k = 1 To NUM_OL
sum = sum + ol(k).e * ol(k).wt(j)
hl(j).e = hl(j).act * (1 - hl(j).act) * sum
Next k
Next j

'Adjust Weights
For j = 1 To NUM_OL
For k = 1 To NUM_HL
ol(j).wt(k) = ol(j).wt(k) + LR * ol(j).e * hl(k).act
ol(j).th = ol(j).th - LR * ol(j).e
Next k
Next j

For j = 1 To NUM_HL
For k = 1 To IMG_TOTAL
hl(j).wt(k) = hl(j).wt(k) + LR * hl(j).e * curImg(k)
hl(j).th = hl(j).th - LR * hl(j).e
Next k
Next j

Print ".";
Next i
End Sub

Sub RunNet()
Dim quit As Byte
Dim num As Byte

Input "Which number do you want to test?", num

For y = 1 To IMG_WIDTH
For x = 1 To IMG_HEIGHT
curImg(j) = img(num, x, y)
j = j + 1
Next x
Next y

Print "You chose this number"
For y = 1 To IMG_WIDTH
For x = 1 To IMG_HEIGHT
If img(num, x, y) = 0 Then
Pset(x + 100,y),15
End If
Next x
Next y

DoNet

For i = 1 To NUM_OL
Print "Value of output node ";
Print i - 1
Print ol(i).act
Next i
End Sub

Function sig(x As Double) As Double
sig = 1/(1 + Exp(-GAIN * x))
End Function

0:
Data 0,0,0,0,0,0,0,0,0,0,0,0
Data 0,0,0,0,1,1,1,1,0,0,0,0
Data 0,0,0,1,0,0,0,0,1,0,0,0
Data 0,0,1,0,0,0,0,0,0,1,0,0
Data 0,0,1,0,0,0,0,0,0,1,0,0
Data 0,0,1,0,0,0,0,0,0,1,0,0
Data 0,0,1,0,0,0,0,0,0,1,0,0
Data 0,0,1,0,0,0,0,0,0,1,0,0
Data 0,0,1,0,0,0,0,0,0,1,0,0
Data 0,0,0,1,0,0,0,0,1,0,0,0
Data 0,0,0,0,1,1,1,1,0,0,0,0
Data 0,0,0,0,0,0,0,0,0,0,0,0

1:
Data 0,0,0,0,0,0,0,0,0,0,0,0
Data 0,0,0,0,0,0,1,0,0,0,0,0
Data 0,0,0,0,0,1,1,0,0,0,0,0
Data 0,0,0,0,1,0,1,0,0,0,0,0
Data 0,0,0,0,0,0,1,0,0,0,0,0
Data 0,0,0,0,0,0,1,0,0,0,0,0
Data 0,0,0,0,0,0,1,0,0,0,0,0
Data 0,0,0,0,0,0,1,0,0,0,0,0
Data 0,0,0,0,0,0,1,0,0,0,0,0
Data 0,0,0,0,0,0,1,0,0,0,0,0
Data 0,0,0,0,1,1,1,1,1,0,0,0
Data 0,0,0,0,0,0,0,0,0,0,0,0

2:
Data 0,0,0,0,0,0,0,0,0,0,0,0
Data 0,0,0,0,1,1,1,1,0,0,0,0
Data 0,0,0,1,0,0,0,0,1,0,0,0
Data 0,0,1,0,0,0,0,0,0,1,0,0
Data 0,0,0,0,0,0,0,0,0,1,0,0
Data 0,0,0,0,0,0,0,0,0,1,0,0
Data 0,0,0,0,0,0,0,0,1,0,0,0
Data 0,0,0,0,0,0,0,1,0,0,0,0
Data 0,0,0,0,0,0,1,0,0,0,0,0
Data 0,0,0,0,0,1,0,0,0,0,0,0
Data 0,0,0,1,1,1,1,1,1,1,0,0
Data 0,0,0,0,0,0,0,0,0,0,0,0

3:
Data 0,0,0,0,0,0,0,0,0,0,0,0
Data 0,0,0,0,1,1,1,1,0,0,0,0
Data 0,0,0,1,0,0,0,0,1,0,0,0
Data 0,0,0,0,0,0,0,0,1,0,0,0
Data 0,0,0,0,0,0,0,0,1,0,0,0
Data 0,0,0,0,0,1,1,1,0,0,0,0
Data 0,0,0,0,0,0,0,0,1,0,0,0
Data 0,0,0,0,0,0,0,0,1,0,0,0
Data 0,0,0,1,0,0,0,0,1,0,0,0
Data 0,0,0,0,1,1,1,1,0,0,0,0
Data 0,0,0,0,0,0,0,0,0,0,0,0
Data 0,0,0,0,0,0,0,0,0,0,0,0

4:
Data 0,0,0,0,0,0,0,0,0,0,0,0
Data 0,0,0,0,0,0,0,1,1,0,0,0
Data 0,0,0,0,0,0,1,0,1,0,0,0
Data 0,0,0,0,0,1,0,0,1,0,0,0
Data 0,0,0,0,1,0,0,0,1,0,0,0
Data 0,0,0,1,0,0,0,0,1,0,0,0
Data 0,0,0,1,1,1,1,1,1,1,0,0
Data 0,0,0,0,0,0,0,0,1,0,0,0
Data 0,0,0,0,0,0,0,0,1,0,0,0
Data 0,0,0,0,0,0,0,0,1,0,0,0
Data 0,0,0,0,0,0,0,1,1,1,0,0
Data 0,0,0,0,0,0,0,0,0,0,0,0

5:
Data 0,0,0,0,0,0,0,0,0,0,0,0
Data 0,0,0,1,1,1,1,1,1,0,0,0
Data 0,0,0,1,0,0,0,0,0,0,0,0
Data 0,0,0,1,0,0,0,0,0,0,0,0
Data 0,0,0,1,0,0,0,0,0,0,0,0
Data 0,0,0,1,1,1,1,0,0,0,0,0
Data 0,0,0,0,0,0,0,1,0,0,0,0
Data 0,0,0,0,0,0,0,0,1,0,0,0
Data 0,0,0,0,0,0,0,0,1,0,0,0
Data 0,0,0,0,0,0,0,1,0,0,0,0
Data 0,0,0,1,1,1,1,0,0,0,0,0
Data 0,0,0,0,0,0,0,0,0,0,0,0

6:
Data 0,0,0,0,0,0,0,0,0,0,0,0
Data 0,0,0,0,1,1,1,1,0,0,0,0
Data 0,0,0,1,0,0,0,0,0,0,0,0
Data 0,0,1,0,0,0,0,0,0,0,0,0
Data 0,0,1,0,0,0,0,0,0,0,0,0
Data 0,0,1,0,0,0,0,0,0,0,0,0
Data 0,0,1,0,1,1,1,1,0,0,0,0
Data 0,0,1,1,0,0,0,0,1,0,0,0
Data 0,0,1,0,0,0,0,0,1,0,0,0
Data 0,0,0,1,0,0,0,0,1,0,0,0
Data 0,0,0,0,1,1,1,1,0,0,0,0
Data 0,0,0,0,0,0,0,0,0,0,0,0

7:
Data 0,0,0,0,0,0,0,0,0,0,0,0
Data 0,0,0,1,1,1,1,1,1,1,0,0
Data 0,0,0,0,0,0,0,0,1,0,0,0
Data 0,0,0,0,0,0,0,0,1,0,0,0
Data 0,0,0,0,0,0,0,1,0,0,0,0
Data 0,0,0,0,0,0,0,1,0,0,0,0
Data 0,0,0,0,0,0,1,0,0,0,0,0
Data 0,0,0,0,0,0,1,0,0,0,0,0
Data 0,0,0,0,0,1,0,0,0,0,0,0
Data 0,0,0,0,0,1,0,0,0,0,0,0
Data 0,0,0,0,1,0,0,0,0,0,0,0
Data 0,0,0,0,0,0,0,0,0,0,0,0

8:
Data 0,0,0,0,0,0,0,0,0,0,0,0
Data 0,0,0,0,1,1,1,1,0,0,0,0
Data 0,0,0,1,0,0,0,0,1,0,0,0
Data 0,0,0,1,0,0,0,0,1,0,0,0
Data 0,0,0,1,0,0,0,0,1,0,0,0
Data 0,0,0,0,1,1,1,1,0,0,0,0
Data 0,0,0,1,0,0,0,0,1,0,0,0
Data 0,0,0,1,0,0,0,0,1,0,0,0
Data 0,0,0,1,0,0,0,0,1,0,0,0
Data 0,0,0,1,0,0,0,0,1,0,0,0
Data 0,0,0,0,1,1,1,1,0,0,0,0
Data 0,0,0,0,0,0,0,0,0,0,0,0

9:
Data 0,0,0,0,0,0,0,0,0,0,0,0
Data 0,0,0,0,1,1,1,1,0,0,0,0
Data 0,0,0,1,0,0,0,0,1,0,0,0
Data 0,0,0,1,0,0,0,0,0,1,0,0
Data 0,0,0,1,0,0,0,0,0,1,0,0
Data 0,0,0,1,0,0,0,0,1,1,0,0
Data 0,0,0,0,1,1,1,1,0,1,0,0
Data 0,0,0,0,0,0,0,0,0,1,0,0
Data 0,0,0,0,0,0,0,0,0,1,0,0
Data 0,0,0,1,0,0,0,0,1,0,0,0
Data 0,0,0,0,1,1,1,1,0,0,0,0
Data 0,0,0,0,0,0,0,0,0,0,0,0[/syntax]

Code:
First, see how the NN performs before training
Which number do you want to test? 2
You chose this number
Value of output node  0
0.9999946772066498
Value of output node  1
0.9998794164495293
Value of output node  2
0.9999991414321088
Value of output node  3
0.9999969437467565
Value of output node  4
0.999989835095912
Value of output node  5
0.999954813071024
Value of output node  6
0.9999966488577209
Value of output node  7
0.999993763156863
Value of output node  8
0.9999949938112089
Value of output node  9
0.9999959078217268
------------------------------

Now training network
How many training cycles 5000
--------------------------------

Now see how the NN performs after training
Which number do you want to test? 5
You chose this number
Value of output node  0
0.9999930039506503
Value of output node  1
4.505908216785114e-002
Value of output node  2
0.9999991069143672
Value of output node  3
0.9999964581486549
Value of output node  4
0.9999813061324169
Value of output node  5
7.279828978456202e-002
Value of output node  6
0.9999960467329503
Value of output node  7
0.9999913546369986
Value of output node  8
0.999993535158855
Value of output node  9
0.9999948572862908

Any idea why it is still giving results above 1?
quote="Deleter"]judging gameplay, you can adaquately compare quake 4 with pong[/quote]
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Deleter Offline
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Posts: 1,025
Threads: 44
Joined: May 2005
#13
12-30-2005, 02:14 AM
none of those results are above 1 :???:
[Image: freebasic.png]
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vspickelen Offline
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Posts: 26
Threads: 5
Joined: Mar 2005
#14
12-30-2005, 03:26 AM
O.k, last post for today

Sad to say, your code needs more tidying up still.
Things that will be quite obvious, once you understand
what's goin' on in all those lil'nifty-nested for-loops.

The constants are messed up, this will do
Code:
CONST IMG_WIDTH = 12
CONST IMG_HEIGHT = 12
CONST NUM_IL = IMG_WIDTH * IMG_HEIGHT    'Number of Nodes in Input Layer
CONST NUM_HL = 20                        'Number of Nodes in Hidden Layer
CONST NUM_OL = 10                        'Number of Nodes in Output Layer
CONST LR = 0.1
CONST GAIN = 5
Replace MAX_NODES and IMG_TOTAL accordingly.


Use
Code:
hl(i).wt(j) = (RND - .5) * .1
for small zero mean random weights

While this is fine
Code:
current = INT(RND * NUM_OL)
it can still go wrong
Code:
FOR j = 1 TO NUM_OL
   IF j = current THEN


I've changed the signs before the bias terms here,
guess you can justify the displaced outer-loop exprssions yourself
Code:
'Calculate HL Error
        
        FOR j = 1 TO NUM_HL
            sum = 0
            FOR k = 1 TO NUM_OL
                sum = sum + ol(k).e * ol(k).wt(j)
                hl(j).e = hl(j).act * (1 - hl(j).act) * sum
            NEXT k
        NEXT j
        
        'Adjust Weights
        FOR j = 1 TO NUM_OL
            FOR k = 1 TO NUM_HL
                ol(j).wt(k) = ol(j).wt(k) + LR * ol(j).e * hl(k).act
                ol(j).th = ol(j).th + LR * ol(j).e
            NEXT k
        NEXT j
        
        FOR j = 1 TO NUM_HL
            FOR k = 1 TO IMG_TOTAL
                hl(j).wt(k) = hl(j).wt(k) + LR * hl(j).e * curImg(k)
                hl(j).th = hl(j).th + LR * hl(j).e
            NEXT k
        NEXT j

This innocent one is a classic:
Code:
INPUT "Which number do you want to test?", num

    FOR y = 1 TO IMG_WIDTH
        FOR x = 1 TO IMG_HEIGHT
            curImg(j) = img(num, x, y)
            j = j + 1
        NEXT x
    NEXT y
might drive you nuts.


The only thing left then, is to remember that
Quote:This GAIN also enters the derivatives of the sig-function.

Good night ( snow here )
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Torahteen Offline
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Posts: 684
Threads: 64
Joined: May 2004
#15
12-30-2005, 09:29 AM
Hmm... Maybe I'm just a bad programmer. Do you have a working version of my code? Is it actually presenting the correct results? Could you post the code? I view this as a learning experience, so don't worry about spoiling my fun Wink.
quote="Deleter"]judging gameplay, you can adaquately compare quake 4 with pong[/quote]
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vspickelen Offline
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Posts: 26
Threads: 5
Joined: Mar 2005
#16
12-30-2005, 07:52 PM
C'mon Torahteen,
you certainly don't consider yourself a "bad programmer,"
suspicious perhaps, but probably just running out of patience.

I promise: you're so close to having a working program,
t'would be a pity if I'd finish in your place.
That final satisfaction will be all yours...

(and I wanna see my guidance bear fruit.)

I uploaded an .exe here,
http://home.graffiti.net/vspickelen:graf...orah10.zip
about 200 training cycles will suffice. Looks nice eh?

Now tell me what problems still remain after my previous post.
vspickelen
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Torahteen Offline
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Posts: 684
Threads: 64
Joined: May 2004
#17
12-30-2005, 08:30 PM
Why is it that it keeps returning values above 1? The sigmoid functio should never return a value above 1.
quote="Deleter"]judging gameplay, you can adaquately compare quake 4 with pong[/quote]
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vspickelen Offline
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Posts: 26
Threads: 5
Joined: Mar 2005
#18
12-30-2005, 10:01 PM
Quote:Why is it that it keeps returning values above 1?

Quote:none of those results are above 1 :???:

I didn't notice:
Computer programs use so called exponential notation for expressing large and small numbers, e.g.
0.04305563 = 4.305563 * 10^-2 = 4.305563e-002

see?
vspickelen
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Torahteen Offline
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Posts: 684
Threads: 64
Joined: May 2004
#19
12-31-2005, 03:36 AM
Oh. Silly me :oops:. Anyway, I'm getting an Illegal Operation error when I run my latest version of code. I'm probably not understanding something. It appears to be happening in the DoNet function. Here is my code (I'm making this page really big lol)

[syntax="qbasic"]DEFINT A-Z

Declare Function sig(x As Double) As Double
Declare Sub DoNet()
Declare Sub TrainNet()
Declare Sub RunNet()
Declare Sub InitNet()

Const IMG_WIDTH = 12
Const IMG_HEIGHT = 12
Const NUM_IL = IMG_WIDTH * IMG_HEIGHT 'Number of Nodes in Input Layer
Const NUM_HL = 20 'Number of Nodes in Hidden Layer
Const NUM_OL = 10
Const LR = 0.1
Const GAIN = 5

Type Node
wt(1 To NUM_IL) As Double 'Weights
act As Double 'Output of this Node
th As Double 'Threshold
e As Double 'Error
End Type

Dim Shared hl(1 To NUM_HL) As Node 'Hidden Layer
Dim Shared ol(1 To NUM_OL) As Node 'Output Layer

'Digit Images
Dim Shared img(0 To 9,1 To 12, 1 To 12) As Byte
Dim Shared curImg(1 To IMG_TOTAL) As Byte
'Begin Main
'Load the Images
For i = 0 To 9
For y = 1 To 12
For x = 1 To 12
Read img(i,x,y)
Next x
Next y
Next i


InitNet
Print "First, see how the NN performs before training"
RunNet
Sleep
Cls
Print "Now training network"
TrainNet
Cls
Print "Now see how the NN performs after training"
RunNet
Sleep
End

SUB DoNet()
DIM sum AS single

'Run through nodes in HL
FOR i = 1 TO NUM_HL
sum = 0
FOR j = 1 TO IMG_TOTAL
sum = sum + hl(i).wt(j) * curImg(j)
NEXT j
hl(i).act = sig(sum - hl(i).th)
NEXT i

'Run through nodes in OL
FOR i = 1 TO NUM_OL
sum = 0
FOR j = 1 TO NUM_HL
sum = sum + ol(i).wt(j) * hl(j).act
NEXT j
ol(i).act = sig(sum - ol(i).th)
NEXT i
END SUB

Sub InitNet()
Randomize Timer

'Hidden Layer
For i = 1 To NUM_HL
For j = 1 To NUM_IL
hl(i).wt(j) = (Rnd - .5) * .1
Next j
Next i

'Output Layer
For i = 1 To NUM_OL
For j = 1 To NUM_HL
ol(i).wt(j) = (Rnd - .5) * .1
Next j
Next i
End Sub

Sub TrainNet()
Dim numCycles As Integer
Dim current As Integer
Dim j As Integer
Dim sum As Double

Input "How many training cycles", numCycles
For i = 1 To numCycles
j = 1

current = Int(Rnd(1) * 10)

For y = 1 To IMG_WIDTH
For x = 1 To IMG_HEIGHT
curImg(j) = img(current, x, y)
j = j + 1
Next x
Next y

DoNet

'Calculate OL Error
For j = 1 To NUM_OL
If j = current Then
ol(j).e = (1 - ol(j).act) * ol(j).act * (1 - ol(j).act)
Else
ol(j).e = (0 - ol(j).act) * ol(j).act * (1 - ol(j).act)
End If
Next j

'Calculate HL Error

FOR j = 1 TO NUM_HL
sum = 0
FOR k = 1 TO NUM_OL
sum = sum + ol(k).e * ol(k).wt(j)
hl(j).e = hl(j).act * (1 - hl(j).act) * sum
NEXT k
NEXT j

'Adjust Weights
FOR j = 1 TO NUM_OL
FOR k = 1 TO NUM_HL
ol(j).wt(k) = ol(j).wt(k) + LR * ol(j).e * hl(k).act
ol(j).th = ol(j).th + LR * ol(j).e
NEXT k
NEXT j

FOR j = 1 TO NUM_HL
FOR k = 1 TO IMG_TOTAL
hl(j).wt(k) = hl(j).wt(k) + LR * hl(j).e * curImg(k)
hl(j).th = hl(j).th + LR * hl(j).e
NEXT k
NEXT j


Print ".";
Next i
End Sub

Sub RunNet()
Dim quit As Byte
Dim num As Byte
Dim j As Integer

j = 1

Input "Which number do you want to test?", num

For y = 1 To IMG_WIDTH
For x = 1 To IMG_HEIGHT
curImg(j) = img(num, x, y)
j = j + 1
Next x
Next y

DoNet

For i = 1 To NUM_OL
Print "Value of output node ";
Print i - 1
Print ol(i).act
Next i
End Sub

Function sig(x As Double) As Double
sig = 1/(1 + Exp(-GAIN * x))
End Function[/syntax]

I left out the DATA statements.
quote="Deleter"]judging gameplay, you can adaquately compare quake 4 with pong[/quote]
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speedlemon Offline
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#20
12-31-2005, 04:55 AM
It's throwing that error because IMG_Total has not been declared.:wink: (i think).
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