GPT stands for "Generative Pre Trained". This means that its work is to "generate" the next word, given some words, and that the system has been trained previously in advance.
Seven years ago Google developed and provided a "word2vec" routines that basically help to "vectorize" words. As an example for this, lets consider "colors". Colors can be represented by 3 numbers (red,green,blue) which could be represented as x,y,z coordinates (vectors) in "space". This way we can add "red" and "blue" and obtain "purple". We can see that this vector representation allows to "sum" colors, find "near" colors, "sustract" them, etc.
word2vec https://code.google.com/archive/p/word2vec/ generates these vectors from a given text, and the results are quite impressive. I have managed to build it on Windows in case you may want to test it.
Given those ideas, Rao and I decided to build a simple Harbour and FWH (as the GUI) example to check the basic concepts of a very simple GPT using Harbour. Here you have the code to build it and see how to use it to generate the next word. You can provide your own texts to it. On a next msg we will explain how it works and how you can apply it to your apps already
gpt_2.prg
Code: Select all
#include "FiveWin.ch"
request DBFCDX
field WORDS
static nSize := 3
function Main()
local oFont, oDlg, oBrw, oGet, cScope
local cSearch := Space( 60 )
local aSentences := { "the cat eats mouse","the mouse eats cheese",;
"the cat eats fish","the fish eats fly", "the dog eats meat", ;
"the dog barks at strangers", "the dog bites theives", ;
"this is a really long long text", "this was a stage" }
FErase( "GPT_2.dbf" )
FErase( "GPT_2.cdx" )
if ! File( "GPT_2.dbf" )
DbCreate( "GPT_2.dbf", { { "ID", "+", 10, 0 }, { "WORDS", "C", 30, 0 } }, "DBFCDX" )
USE GPT_2 VIA "DBFCDX"
INDEX ON WORDS TAG GPT_2 CUSTOM
USE
endif
USE GPT_2 VIA "DBFCDX"
SET ORDER TO TAG GPT_2
AEval( aSentences, { |c| RecordSentence( c ) } )
OrdScope( 0, " " )
OrdScope( 1, " " )
GO TOP
SetGetColorFocus()
DEFINE FONT oFont NAME "TAHOMA" SIZE 0,-14
DEFINE DIALOG oDlg SIZE 800, 350 PIXEL TRUEPIXEL FONT oFont
@ 22, 20 SAY "Enter word(s)" SIZE 100, 20 PIXEL OF oDlg
@ 20, 120 GET oGet VAR cSearch SIZE 660,24 PIXEL OF oDlg ;
ON CHANGE ( If( nKey == 32, ResetBrowse( oGet:GetText(), oBrw ), nil ) ) ;
UPDATE
@ 60, 20 XBROWSE oBrw SIZE 760, 250 PIXEL OF oDlg ;
DATASOURCE ReadSuggestions( "" ) ;
COLUMNS 1, 2, 3 ;
HEADERS "RecNo", "Suggestions", "Strength" NOBORDER
WITH OBJECT oBrw
:nStretchCol = 2
:aCols[ 2 ]:bLDClickData := < ||
oGet:cText := PadR( Trim( cSearch ) + " " + Trim( oBrw:aCols[ 2 ]:Value ), 60 )
ResetBrowse( cSearch, oBrw )
return nil
>
:CreateFromCode()
END
ACTIVATE DIALOG oDlg CENTERED
OrdScope( 0, "this " ); OrdScope( 1, "this " )
XBROWSER "GPT_2" COLUMNS "id", "words", "OrdKeyVal()", "OrdKeyCount()"
return nil
function ResetBrowse( cText, oBrw )
local aSuggest := ReadSuggestions( cText )
oBrw:aArrayData := aSuggest
oBrw:GoTop()
oBrw:Refresh()
return nil
function ReadSuggestions( cText )
local aRet := {}
local nTokens, n, nn, cKey
cText := Lower( AllTrim( cText ) )
if Empty( cText )
OrdScope( 0, " " )
OrdScope( 1, " " )
dbGoTop()
DbEVal( { || AAdd( aRet, { RECNO(), WORDS, 1 } ) } )
return aRet
endif
nTokens := NumToken( cText )
SetScope( nil )
if !dbSeek( Token( cText ) )
return aRet
endif
for n := Max( 1, nTokens - nSize + 1 ) to nTokens
cKey := AddTokens( cText, n, nTokens )
nn := NumToken( cKey )
SetScope( cKey + " " )
DbEVal( { || If( AScan( aRet, { |a| a[ 1 ] == RECNO() } ) == 0, AAdd( aRet, { RECNO(), WORDS, nn } ), nil ) }, ;
{ || NumToken( OrdKeyVal() ) == nn + 1 } )
next
return aRet
function SetScope( c )
OrdScope( 0, c ); OrdScope( 1, c ); dbGoTop()
return nil
function RecordSentence( cText )
local nToken, nTokens := NumToken( cText )
local aTokens := Array( nTokens )
local n, cKey
AEval( aTokens, { |u,i| aTokens[ i ] := Token( cText, nil, i ) } )
SET ORDER TO TAG GPT_2
if !dbSeek( " " + aTokens[ 1 ] )
dbAppend()
WORDS := aTokens[ 1 ]
OrdKeyAdd( "GPT_2", nil, " " + Lower( aTokens[ 1 ] ) )
endif
for nToken := 1 to Len( aTokens ) - 1
cKey := Lower( aTokens[ nToken ] + " " + aTokens[ nToken + 1 ] )
if !dbSeek( cKey )
dbAppend()
WORDS := aTokens[ nToken + 1 ]
OrdKeyAdd( "GPT_2", nil, cKey )
if nToken > 1
for n := nToken -1 to Max( 1, nToken - nSize ) step - 1
cKey := Lower( AddTokens( cText, n, nToken + 1 ) )
OrdKeyAdd( "GPT_2", nil, cKey )
next
endif
endif
next
return nil
function LastTokens( cText, nCount )
local nTokens := NumToken( cText )
local n
local nFrom := Max( nTokens - nCount + 1, 1 )
local cRet := Token( cText, , nFrom )
for n := nFrom + 1 to nTokens
cRet += " " + Token( cText, , n )
next
return cRet
function AddTokens( cText, nFrom, nLast )
local n, cRet
DEFAULT nLast := NumToken( cText )
nFrom := Max( 1, nFrom )
cRet := Token( cText, , nFrom )
for n := nFrom + 1 to nLast
cRet += " " + Token( cText, , n )
next
return cRet
