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t/nerl_network.t  view on Meta::CPAN

use Test::More tests=>714;
use Modern::Perl;
use PDL;
use PDL::NiceSlice;
use_ok('AI::Nerl');
use_ok('AI::Nerl::Network');
{
   my $nn = AI::Nerl::Network->new(l1=>2,l2=>2);
   isa_ok($nn,'AI::Nerl::Network');
}

#simplest 3layer: 1 in, i hidden, 1 out
#1->1,0->0
{
   my $x = pdl(0,1);
   my $y = pdl(1,0);
   my $nn = AI::Nerl::Network->new(
      l1=>1,l2=>1,l3=>1,
      alpha=> .7,
      lambda => .01,
   );
   my $prev_cost = 1000;
   for(1..700){
      $nn->train($x,$y,passes=>1);
      my ($cost,$nc) = $nn->cost($x,$y);
      ok($cost < $prev_cost, "round $_: cost < prev cost");
   }
   my $output = $nn->run(pdl(0,.25,.75,1));
   # [0.88530935 0.79459088 0.32803629 0.02482565]
   ok($output(0) > .85, "nn(0) > .85");
   ok($output(1) < .85, "nn(1) < .85");
   ok($output(2) > .15, "nn(2) > .15");
   ok($output(3) < .1, "nn(3) < .1");
}

#build a few really simple nets.
#in: x1,x2
#out: x1 AND|OR|XOR x2
{
   my $id2 = identity(2);
   my $x = pdl([0,0,1,1],[0,1,0,1]);
   my $AND = $id2->range(pdl(0,0,0,1)->transpose);
   my $OR = $id2->range(pdl(0,1,1,1)->transpose);
   my $XOR = $id2->range(pdl(0,1,1,0)->transpose);
   my ($AND_nn,$OR_nn,$XOR_nn) = map {
      AI::Nerl::Network->new(
         l1=>2,
         l2=>4,
         l3=>2,
         alpha=>.5,
         lambda=>0,
      );
   } 1..3;
   isa_ok($XOR_nn, 'AI::Nerl::Network');
   is($XOR_nn->theta1->dim(0), 2, 'theta1 dim1 == 2');
   is($XOR_nn->theta1->dim(1), 4, 'theta1 dim2 == 4');
   is($XOR_nn->theta2->dim(0), 4, 'theta2 dim1 == 4');
   is($XOR_nn->theta2->dim(1), 2, 'theta2 dim2 == 2');

   $XOR_nn->train($x,$XOR, passes=>259);
   $OR_nn->train($x,$OR, passes=>259);
   $AND_nn->train($x,$AND, passes=>259);