AI-LibNeural
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GNU LIBRARY GENERAL PUBLIC LICENSE
Version 2, June 1991
Copyright (C) 1991 Free Software Foundation, Inc.
59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
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[This is the first released version of the library GPL. It is
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That's all there is to it!
LibNeural.pm view on Meta::CPAN
#
# $Header$
#
package AI::LibNeural;
use 5.006;
use strict;
use warnings;
use Carp;
require Exporter;
require DynaLoader;
use AutoLoader;
our @ISA = qw(Exporter DynaLoader);
# This allows declaration use AI::LibNeural ':all';
our %EXPORT_TAGS = ( 'all' => [ qw(
ALL
HIDDEN
INPUT
OUTPUT
) ] );
our @EXPORT_OK = ( @{ $EXPORT_TAGS{'all'} } );
our @EXPORT = qw(
);
our $VERSION = '0.02';
sub AUTOLOAD {
# This AUTOLOAD is used to 'autoload' constants from the constant()
# XS function. If a constant is not found then control is passed
# to the AUTOLOAD in AutoLoader.
my $constname;
our $AUTOLOAD;
($constname = $AUTOLOAD) =~ s/.*:://;
croak "& not defined" if $constname eq 'constant';
my $val = constant($constname, @_ ? $_[0] : 0);
if ($! != 0) {
if ($! =~ /Invalid/ || $!{EINVAL}) {
$AutoLoader::AUTOLOAD = $AUTOLOAD;
goto &AutoLoader::AUTOLOAD;
}
else {
croak "Your vendor has not defined AI::LibNeural macro $constname";
}
}
{
no strict 'refs';
# Fixed between 5.005_53 and 5.005_61
# if ($] >= 5.00561) {
# *$AUTOLOAD = sub () { $val };
# }
# else {
*$AUTOLOAD = sub { $val };
# }
}
goto &$AUTOLOAD;
}
bootstrap AI::LibNeural $VERSION;
# Preloaded methods go here.
# Autoload methods go after =cut, and are processed by the autosplit program.
1;
__END__
=head1 NAME
AI::LibNeural - Perl extension libneural
=head1 SYNOPSIS
use AI::LibNeural;
my $nn = AI::LibNeural->new( 2, 4, 1 );
# teach it the logical AND
$nn->train( [ 0, 0 ], [ 0.05 ], 0.0000000005, 0.2 );
$nn->train( [ 0, 1 ], [ 0.05 ], 0.0000000005, 0.2 );
$nn->train( [ 1, 0 ], [ 0.05 ], 0.0000000005, 0.2 );
$nn->train( [ 1, 1 ], [ 0.95 ], 0.0000000005, 0.2 );
my $result = $nn->run( [ 1, 1 ] );
# result should be ~ 0.95
$result = $nn->run( [ 0, 1 ] );
# result should be ~ 0.05
$nn->save('and.mem');
=head1 ABSTRACT
Perl bindings for the libneural c++ neural netowrk library.
=head1 DESCRIPTION
Provides accessors for the libneural library as a perl object. libneural is a
C++ library that impelements a feed-forward back-proprogation neural network.
The interface is extremely simple and should take no more than a few minutes to
master given a reasonable knowledge of back proprogation neural networks.
=head2 FUNCTIONS
=over
=item $nn = AI:LibNeural->new()
Creates an empty AI::LibNeural object, should only be used when the load method
will be called soon after.
=item $nn = AI::LibNeural->new(FILENAME)
Creates a new AI::LibNeural object from the supplied memory file.
=item $nn = AI::LibNeural->new(INTPUTS,HIDDENS,OUTPUTS)
Creates a new AI::LibNeural object with INPUTS input nodes, HIDDENS hidden
nodes, and OUTPUTS output nodes.
=item $nn->train([I1,I2,...],[O1,O2,...],MINERR,TRAINRATE)
Completes a training cycle for the given inputs I1-IN, with the expected
results of O1-OM, where N is the number of inputs and M is the number of
outputs. MINERR is the mean squared error at the output that you wish to be achieved. TRAINRATE is the learning rate to be used.
=item (O1,O2) = $nn->run([I1,I2,...])
Calculate the corresponding outputs (O1-OM) for the given inputs (I1-ON) based
on the previous training. Should only be called after the network has been
suitably trained.
=item NUM = $nn->get_layersize(WHICH)
Retrieves the number of nodes at the specified layer, WHICH. WHICH should be
one of ALL, INPUT, HIDDEN, OUTPUT. Usefully mainly with a network is loaded
from a file.
=item status = $nn->load(FILENAME)
=item status = $nn->save(FILENAME)
Loads and saves respectively the 'memory,' node configuration and weights,
of the network. FILENAME should be the location of the file in which the
memory is stored/retrieved.
=back
=head2 EXPORT
None by default
=head2 EXPORT TAGS
=over
=item all
=over
=item ALL
The total number of nodes on all three layers
=item INPUT
The number of nodes on the input layer
=item HIDDEN
The number of nodes on the hidden layer
=item OUTPUT
The number of nodes on the output layer
=back
=back
=head1 AUTHOR
Ross McFarland E<lt>rmcfarla at neces dot comE<gt>
=head1 SEE ALSO
L<perl>. libneural documentation
=head1 LICENSE
this is based off of code that i based off of other modules i've found in the
distant past. if you are the original author and you recognize this code let
me know and you'll be credited
Copyright (C) 2003 by Ross McFarland
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Library General Public
License as published by the Free Software Foundation; either
version 2 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Library General Public License for more details.
You should have received a copy of the GNU Library General Public
License along with this library; if not, write to the
Free Software Foundation, Inc., 59 Temple Place - Suite 330,
Boston, MA 02111-1307 USA.
LibNeural.xs view on Meta::CPAN
/*
* $Header$
*
* this is based off of code that i based off of other modules i've found in the
* distant past. if you are the original author and you recognize this code let
* me know and you'll be credited
*
* Copyright (C) 2003 by Ross McFarland
*
* This library is free software; you can redistribute it and/or
* modify it under the terms of the GNU Library General Public
* License as published by the Free Software Foundation; either
* version 2 of the License, or (at your option) any later version.
*
* This library is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* Library General Public License for more details.
*
* You should have received a copy of the GNU Library General Public
* License along with this library; if not, write to the
* Free Software Foundation, Inc., 59 Temple Place - Suite 330,
* Boston, MA 02111-1307 USA.
*
*/
#ifdef __cplusplus
extern "C" {
#endif
#include "EXTERN.h"
#include "perl.h"
#include "XSUB.h"
#ifdef __cplusplus
}
#endif
#include <nnwork.h>
#include <neuron.h>
static int
not_here(char *s)
{
croak("%s not implemented on this architecture", s);
return -1;
}
static double
constant(char *name, int len, int arg)
{
errno = 0;
switch (name[0 + 0]) {
case 'A':
if (strEQ(name + 0, "ALL")) { /* removed */
#ifdef ALL
return ALL;
#else
goto not_there;
#endif
}
case 'H':
if (strEQ(name + 0, "HIDDEN")) { /* removed */
#ifdef HIDDEN
return HIDDEN;
#else
goto not_there;
#endif
}
case 'I':
if (strEQ(name + 0, "INPUT")) { /* removed */
#ifdef INPUT
return INPUT;
#else
goto not_there;
#endif
}
case 'O':
if (strEQ(name + 0, "OUTPUT")) { /* removed */
#ifdef OUTPUT
return OUTPUT;
#else
goto not_there;
#endif
}
}
errno = EINVAL;
return 0;
not_there:
errno = ENOENT;
return 0;
}
/* function that takes an array reference and convert it into an equivelent
* float array. dlen is the number of elements that we want to make sure are in
* the array */
static float *
svpvav_to_float_array (SV * svpvav, int dlen)
{
float * array;
AV * avp;
SV ** svpp;
int i;
/* make sure that svpvav is array reference */
if( !SvROK(svpvav) || (SvTYPE(SvRV(svpvav)) != SVt_PVAV) )
Perl_croak(aTHX_ "parameter should be a valid array reference");
/* get the array pointers out of its sv reference */
avp = (AV*)SvRV(svpvav);
/* make sure that it has the desired number of elements */
if( av_len(avp)+1 != dlen )
Perl_croak(aTHX_ "size of array and desired length do not match");
/* alloc the memory for ains and aouts */
array = (float*)malloc( dlen * sizeof(float) );
if( array == NULL )
Perl_croak(aTHX_ "unable to allocate memory for storing array");
/* copy avins to ains */
for( i = 0; i < dlen; i++ )
{
/* don't need ins anymore use as a tmp */
svpp = av_fetch(avp, i, 0);
if( !svpp || !*svpp || !SvOK(*svpp) )
{
if( array ) free(array);
Perl_croak(aTHX_ "bad array value encountered at index %d", i);
}
array[i] = (float)SvNV(*svpp);
}
return array;
}
MODULE = AI::LibNeural PACKAGE = AI::LibNeural
double
constant(sv,arg)
PREINIT:
STRLEN len;
INPUT:
SV * sv
char * s = SvPV(sv, len);
int arg
CODE:
RETVAL = constant(s,len,arg);
OUTPUT:
RETVAL
nnwork *
nnwork::new (...)
PREINIT:
char * filename;
int inputs;
int hiddens;
int outputs;
CODE:
CLASS = (char*)SvPV_nolen(ST(0));
if( items == 1 )
{
/* blank */
RETVAL = new nnwork();
}
else if( items == 2 )
{
/* given a file to load */
char* filename = (char*)SvPV_nolen(ST(1));
RETVAL = new nnwork(filename);
}
else if( items == 4 )
{
/* given node counts */
int inputs = (int)SvIV(ST(1));
int hiddens = (int)SvIV(ST(2));
int outputs = (int)SvIV(ST(3));
RETVAL = new nnwork(inputs, hiddens, outputs);
}
else
Perl_croak(aTHX_ "Usage: Neural::new([ins, hids, outs])");
OUTPUT:
RETVAL
int
nnwork::get_layersize (which)
int which
void
nnwork::train (ins, outs, minerr, trainrate)
SV * ins
SV * outs
float minerr
float trainrate
PREINIT:
int i;
int nin;
int nout;
float * ains;
float * aouts;
CODE:
nin = THIS->get_layersize(INPUT);
nout = THIS->get_layersize(OUTPUT);
ains = svpvav_to_float_array(ins, nin);
aouts = svpvav_to_float_array(outs, nout);
THIS->train(ains, aouts, minerr, trainrate);
if( ains ) free(ains);
if( aouts ) free(aouts);
void
nnwork::run (ins)
SV * ins
PREINIT:
int i;
int nin;
int nout;
float * ains;
float * aouts;
PPCODE:
nin = THIS->get_layersize(INPUT);
nout = THIS->get_layersize(OUTPUT);
ains = svpvav_to_float_array(ins, nin);
aouts = (float*)malloc(nout * sizeof(float));
if( aouts == NULL )
XSRETURN_UNDEF;
THIS->run(ains, aouts);
EXTEND(SP, nout);
for( i = 0; i < nout; i++ )
{
PUSHs(sv_2mortal(newSVnv(aouts[i])));
}
if( ains ) free(ains);
if( aouts ) free(aouts);
int
nnwork::load (filename)
char * filename
int
nnwork::save (filename)
char * filename
LICENSE
LibNeural.pm
LibNeural.xs
MANIFEST This list of files
MANIFEST.SKIP
Makefile.PL
README
t/00.AILibNeural.t
t/01.AILibNeuralChild.t
typemap
MANIFEST.SKIP view on Meta::CPAN
CVS
blib
pm_to_blib
Makefile$
\.cvsignore$
\.bak$
\.bs$
\.c$
\.o$
~$
\.sw.$
Makefile.PL view on Meta::CPAN
#
# $Header$
#
# this is based off of code that i based off of other modules i've found in the
# distant past. if you are the original author and you recognize this code let
# me know and you'll be credited
#
# Copyright (C) 2003 by Ross McFarland
#
# This library is free software; you can redistribute it and/or
# modify it under the terms of the GNU Library General Public
# License as published by the Free Software Foundation; either
# version 2 of the License, or (at your option) any later version.
#
# This library is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
# Library General Public License for more details.
#
# You should have received a copy of the GNU Library General Public
# License along with this library; if not, write to the
# Free Software Foundation, Inc., 59 Temple Place - Suite 330,
# Boston, MA 02111-1307 USA.
#
use ExtUtils::MakeMaker;
WriteMakefile(
'NAME' => 'AI::LibNeural',
'VERSION_FROM' => 'LibNeural.pm',
'ABSTRACT_FROM' => 'LibNeural.pm',
'LIBS' => [ '-lneural' ],
'TYPEMAPS' => [ './typemap' ],
# this is going to be linked with a c++ lib so special magic is
# required. MakeMaker will complain that it doesn't know anything
# about CC, and LD, but appearently it does
'CC' => 'g++',
'LD' => '$(CC)',
'XSOPT' => '-C++',
);
#
# $Header$
#
AI::LibNeural version 0.02
==========================
This module provides access to the c++ library libneural.
(http://ieee.uow.edu.au/~daniel/software/libneural/ or search for libneural on
freshmeat.net.) libneural is a simple, but useful, backpropagation neural
network. It isn't packed with features or a speed demon, but it works and it's
easy to learn how to use.
INSTALLATION
> perl Makefile.PL
or
> perl Makefile.PL PREFIX=/some/non/system/place
(then setting PERL5LIB as appropriate based on ^ is a good ideal)
ignore the warnings about CC and LD being unknown parameters, then
> make all test install
Provided that everything goes well this should build the module, test it out,
and install it. If you encounter problems try e-mailing the author with as
much detail as possible. System type, os version, perl version, libneural
version, cpp compiler, script of the failing Makefile creation and compile
process.
USE
For information on using this library see the POD within AI::LibNeural.pm by
typing 'perldoc LibNeural.pm' in the same directory as this README or by
typing 'perldoc AI::LibNeural' after installtion.
DEPENDENCIES
libneural v1.0.3 or newer (it may work with older versions, but they have not
been tested.)
COPYRIGHT AND LICENCE
Copyright (C) 2003 by Ross McFarland
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Library General Public
License as published by the Free Software Foundation; either
version 2 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Library General Public License for more details.
You should have received a copy of the GNU Library General Public
License along with this library; if not, write to the
Free Software Foundation, Inc., 59 Temple Place - Suite 330,
Boston, MA 02111-1307 USA.
t/00.AILibNeural.t view on Meta::CPAN
#
# $Header$
#
# this is based off of code that i based off of other modules i've found in the
# distant past. if you are the original author and you recognize this code let
# me know and you'll be credited
#
# Copyright (C) 2003 by Ross McFarland
#
# This library is free software; you can redistribute it and/or
# modify it under the terms of the GNU Library General Public
# License as published by the Free Software Foundation; either
# version 2 of the License, or (at your option) any later version.
#
# This library is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
# Library General Public License for more details.
#
# You should have received a copy of the GNU Library General Public
# License along with this library; if not, write to the
# Free Software Foundation, Inc., 59 Temple Place - Suite 330,
# Boston, MA 02111-1307 USA.
#
#########################
use strict;
use Test::More tests => 31;
BEGIN { use_ok('AI::LibNeural', ':all') };
#########################
my $nn;
ok( $nn = AI::LibNeural->new( 2, 4, 1 ) );
ok( $nn =~ m/AI::LibNeural=SCALAR(.*)/ );
ok( ALL == 0 );
ok( INPUT == 1 );
ok( HIDDEN == 2 );
ok( OUTPUT == 3 );
ok( $nn->get_layersize(ALL) == 7 );
ok( $nn->get_layersize(INPUT) == 2 );
ok( $nn->get_layersize(HIDDEN) == 4 );
ok( $nn->get_layersize(OUTPUT) == 1 );
for( my $i = 0; $i < 20; $i++ )
{
$nn->train( [ 0, 0 ], [ 0.05 ], 0.0000000005, 0.2 );
$nn->train( [ 0, 1 ], [ 0.05 ], 0.0000000005, 0.2 );
$nn->train( [ 1, 0 ], [ 0.05 ], 0.0000000005, 0.2 );
$nn->train( [ 1, 1 ], [ 0.95 ], 0.0000000005, 0.2 );
}
ok(1);
ok( $nn->run( [ 0, 0 ] ) < 0.5 );
ok( $nn->run( [ 0, 1 ] ) < 0.5 );
ok( $nn->run( [ 1, 0 ] ) < 0.5 );
ok( $nn->run( [ 1, 1 ] ) > 0.5 );
ok( $nn->save('test.mem') );
$nn = undef;
ok( $nn = AI::LibNeural->new() );
ok( $nn =~ m/AI::LibNeural=SCALAR(.*)/ );
ok( $nn->load('test.mem') );
ok( $nn->run( [ 0, 0 ] ) < 0.5 );
ok( $nn->run( [ 0, 1 ] ) < 0.5 );
ok( $nn->run( [ 1, 0 ] ) < 0.5 );
ok( $nn->run( [ 1, 1 ] ) > 0.5 );
$nn = undef;
ok( $nn = AI::LibNeural->new('test.mem') );
ok( $nn =~ m/AI::LibNeural=SCALAR(.*)/ );
ok( $nn->run( [ 0, 0 ] ) < 0.5 );
ok( $nn->run( [ 0, 1 ] ) < 0.5 );
ok( $nn->run( [ 1, 0 ] ) < 0.5 );
ok( $nn->run( [ 1, 1 ] ) > 0.5 );
unlink('test.mem') if( -e 'test.mem' );
ok(1);
t/01.AILibNeuralChild.t view on Meta::CPAN
#
# $Header$
#
# this is based off of code that i based off of other modules i've found in the
# distant past. if you are the original author and you recognize this code let
# me know and you'll be credited
#
# Copyright (C) 2003 by Ross McFarland
#
# This library is free software; you can redistribute it and/or
# modify it under the terms of the GNU Library General Public
# License as published by the Free Software Foundation; either
# version 2 of the License, or (at your option) any later version.
#
# This library is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
# Library General Public License for more details.
#
# You should have received a copy of the GNU Library General Public
# License along with this library; if not, write to the
# Free Software Foundation, Inc., 59 Temple Place - Suite 330,
# Boston, MA 02111-1307 USA.
#
#########################
use strict;
use Test::More tests => 31;
BEGIN { use_ok('AI::LibNeural', ':all') };
#########################
package AI::LibNeural::Child;
our @ISA = qw(AI::LibNeural);
package main;
my $nn;
ok( $nn = AI::LibNeural::Child->new( 2, 4, 1 ) );
ok( $nn =~ m/AI::LibNeural::Child=SCALAR(.*)/ );
ok( ALL == 0 );
ok( INPUT == 1 );
ok( HIDDEN == 2 );
ok( OUTPUT == 3 );
ok( $nn->get_layersize(ALL) == 7 );
ok( $nn->get_layersize(INPUT) == 2 );
ok( $nn->get_layersize(HIDDEN) == 4 );
ok( $nn->get_layersize(OUTPUT) == 1 );
for( my $i = 0; $i < 20; $i++ )
{
$nn->train( [ 0, 0 ], [ 0.05 ], 0.0000000005, 0.2 );
$nn->train( [ 0, 1 ], [ 0.05 ], 0.0000000005, 0.2 );
$nn->train( [ 1, 0 ], [ 0.05 ], 0.0000000005, 0.2 );
$nn->train( [ 1, 1 ], [ 0.95 ], 0.0000000005, 0.2 );
}
ok(1);
ok( $nn->run( [ 0, 0 ] ) < 0.5 );
ok( $nn->run( [ 0, 1 ] ) < 0.5 );
ok( $nn->run( [ 1, 0 ] ) < 0.5 );
ok( $nn->run( [ 1, 1 ] ) > 0.5 );
ok( $nn->save('test.mem') );
$nn = undef;
ok( $nn = AI::LibNeural::Child->new() );
ok( $nn =~ m/AI::LibNeural::Child=SCALAR(.*)/ );
ok( $nn->load('test.mem') );
ok( $nn->run( [ 0, 0 ] ) < 0.5 );
ok( $nn->run( [ 0, 1 ] ) < 0.5 );
ok( $nn->run( [ 1, 0 ] ) < 0.5 );
ok( $nn->run( [ 1, 1 ] ) > 0.5 );
$nn = undef;
ok( $nn = AI::LibNeural::Child->new('test.mem') );
ok( $nn =~ m/AI::LibNeural::Child=SCALAR(.*)/ );
ok( $nn->run( [ 0, 0 ] ) < 0.5 );
ok( $nn->run( [ 0, 1 ] ) < 0.5 );
ok( $nn->run( [ 1, 0 ] ) < 0.5 );
ok( $nn->run( [ 1, 1 ] ) > 0.5 );
unlink('test.mem') if( -e 'test.mem' );
ok(1)
#
# $Header$
#
# this is based off of code that i based off of other modules i've found in the
# distant past. if you are the original author and you recognize this code let
# me know and you'll be credited
#
# Copyright (C) 2003 by Ross McFarland
#
# This library is free software; you can redistribute it and/or
# modify it under the terms of the GNU Library General Public
# License as published by the Free Software Foundation; either
# version 2 of the License, or (at your option) any later version.
#
# This library is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
# Library General Public License for more details.
#
# You should have received a copy of the GNU Library General Public
# License along with this library; if not, write to the
# Free Software Foundation, Inc., 59 Temple Place - Suite 330,
# Boston, MA 02111-1307 USA.
#
TYPEMAP
float T_NV
float * T_PV
nnwork * O_OBJECT
OUTPUT
O_OBJECT
sv_setref_pv( $arg, CLASS, (void*)$var );
INPUT
O_OBJECT
if( sv_isobject($arg) && (SvTYPE(SvRV($arg)) == SVt_PVMG) )
$var = ($type)SvIV((SV*)SvRV( $arg ));
else{
warn( \"${Package}::$func_name() -- $var is not a blessed SV reference\" );
XSRETURN_UNDEF;
}
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