Liren Large Software Subsidy 9/09.iso/e/e065/1.ddi/SAMPLE.INS

Text File | 1991-08-28 | 3.2 KB | 111 lines

inst4.0 ! 02-Jun-88  (Sample.ins)  Sample 2-input Xor (backprop)
!****************************************************************
!*                                *
!*    "Sample" Back-Propagation Network Builder        *
!*                                *
!****************************************************************
!
!    This script builds a back-propagation network designed
!    to solve the exclusive "OR" problem with two inputs.

!    *** Load the Control Strategy and LRS if needed

@LdCS    "backprop"        !control strategy
@LdLR    "backprop"        !L/R schedule

=netn "InstaNet (tm) 'Sample' Back-Propagation Network version 1.00 20-Jun-88"
!=DLnF    1            !learn  re-display on
=DLnN    53            !learn, re-display every 53
=DRcF    1            !recall re-display on
=DRcN    1            !show each recall

!    *** Build the Input Layer ***

@LLdf                !load default layer to mi_layer structure
=LDln    "In"            !layer name
=Lpes    2            !2 PEs for XOR
=Ltrn    "Linear"        !buffer
=LDsp    6            !spacing
=x    100            !place to put layer on screen
=y     80
#Incl    "stdnwgtf.iif"        !standard # weight fields
@LAdd                !add the input layer
=x    130            !position hidden & output over center

!    *** Build the first hidden Layer ***

@LLdf                !start with default layer again
=LDln    "H"            !layer name
=Lpes    1            !One Hidden PE
=Ltrn    "Sigmoid"        !transfer function
=Llrn    "Delta-Rule"        !Generalized Delta learning rule
+y    60            !up higher on display
#Incl    "stdnwgtf.iif"        !standard # weight fields
@LAdd

!    *** Connect Hidden Layer to Bias & Input Layers ***

=SPEl    1            !current layer
@SlPE                !select it as destination (sb already)
=NPEl    -1            !near to bias term (source)
@NrPE
=cnwt    1.0            !connection weight
=cnty    WVar            !variable
=cnsc    WAbs            !absolute
@LCFl                !fully connect to bias element
=NPEl    0            !input layer
@NrPE
@LCFl                !fully connect to input layer

!    *** Build the output layer & connect it to prior, input & bias term ***

@LLdf                !load default layer to mi_layer structure
=LDln    "Out"            !layer name
=Lpes    1            !copy # of input PEs from menu
=Ltrn    "Sigmoid"        !transfer function
=Llrn    "Delta-Rule"        !Generalized Delta learning rule
+y    60
#Incl    "stdnwgtf.iif"        !standard # weight fields
@LAdd                !add the output layer
=n7    LayN            !save for stdprobe

=SPEl    2            !current layer
@SlPE                !select it as destination (sb already)
=NPEl    -1            !near to bias term (source)
@NrPE
@LCFl                !fully connect to bias element
=NPEl    1            !previous layer
@NrPE
@LCFl                !fully connect to input layer
=NPEl    0            !input layer
@NrPE
@LCFl                !fully connect to input layer

!    *** Select Control Strategy & L/R Schedule ***

=LrnN    2000            !learn counter for LearnN
@LLsl                !load super layer
=Lctl    "backprop"        !backprop control strategy
=Llrs    "backprop"        !backprop L/R Schedule
=Llnn    "sample"        !name of learn input
=Lrcn    "sample"        !name of recall output
=Llio    321            !binary,sequential,load (0x0141)
=Lrio    1137            !binary,seq,inp, des out, header (0x0471)
=Lscl     0            !input  low-value
=Loff     1            !input  high-value
=Llow     0            !output low-value
=Lhgh     1            !output high-value
@SVsl                !save it back
!
=n5    0.0
=n6    1.0
=n4    1
#Incl    "stdprobe.iif"        !Standard probe include file
!
=jogl    -.1            !lower limit for jog
=jogh    +.1            !upper limit for jog
=seed    257            !starting seed number
@seed                !set the seed
@Nini                !randomize the network
@EOF