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lib/AI/Nerl/Network.pm  view on Meta::CPAN

sub append_l2{
   my ($self,$x) = @_;
   $x->sever();
   if ($self->scale_input){
      $x *= $self->scale_input;
   }
   $x = $x->transpose if $self->l1 != $x->dim(1);
   my $l2 = $self->theta1 x $x;
   $l2 += $self->b1->transpose;
   $l2->inplace()->tanh;
#   warn join ',',$x->dims;
#   warn join ',',$l2->dims;
   return $x->glue(1,$l2);
}

sub cost{
   my ($self,$x,$y) = @_;
   $x->sever();# = $x->copy();
   my $n = $x->dim(0);
   if ($self->scale_input){
      $x *= $self->scale_input;
   }
   my $num_correct = 0;
   #die join(',',$x->dims) .',,,'. join(',',$y->dims);
   my $total_cost = 0; 
   for my $i (0..$n-1){
      my $a1 = $x(($i));
      my $z2 = ($self->theta1 x $a1->transpose)->squeeze;
      $z2 += $self->b1;
      my $a2 = $z2->tanh();
      my $z3 = ($self->theta2 x $a2->transpose)->squeeze;
      $z3 += $self->b2;
      my $a3 = $z3->tanh;
      $total_cost += ($y(($i))-$a3)->abs()->power(2,0)->sum()/2;
      #warn $a3->maximum_ind . '    ' . $y(($i))->maximum_ind;;
      $num_correct++ if $a3->maximum_ind == $y(($i))->maximum_ind;
   }
   $total_cost /= $n;
   $total_cost += $self->theta1->flat->power(2,0)->sum * $self->lambda;
   $total_cost += $self->theta2->flat->power(2,0)->sum * $self->lambda;
   return ($total_cost, $num_correct);
}

sub tanhx{ #don't use this. pdl has $pdl->tanh which can be used in place.
   my $foo = shift;
   my $p = E**$foo;
   my $n = E**-$foo;
   return (($p-$n)/($p+$n));
}
sub tanhxderivative{ #use: tanhxderivative($pdl->tanh()). save time by finding tanh first.
   my $tanhx = shift;
   return (1 - $tanhx**2);
}

sub sigmoid{
   my $foo = shift;
   return 1/(1+E**-$foo);
}

sub logistic{
   #find sigmoid before calling this.
   #grad=logistic(sigmoid(foo))
   my $foo = shift;
   return $foo * (1-$foo);
}

my $g2d_tried = 0;
my $g2d_failed = '';
sub USE_G2D{
   return 0 if $g2d_tried and $g2d_failed;
   return 1 if $g2d_tried;
   eval{
      require PDL::Graphics2D;
      PDL::Graphics2d->import('imag2d');
      1;
   } or do {
      $g2d_failed = $@;
      warn "PDL::Graphics2d failed to load. perhaps $g2d_failed";
   };
   $g2d_tried = 1;
   return USE_G2D();
}
#display 28x28 grayscale pdl.
sub show784{
   return unless USE_G2D();
   my $w = shift;
   $w = $w->copy;
   #warn join',', $w->dims;
   $w = $w->squeeze;
   my $min = $w->minimum;
   $w -= $min;
   my $max = $w->maximum;
   $w /= $max;
   $w = $w->reshape(28,28);
   imag2d $w;
}

sub show_neuron{
   unless (USE_G2D()){
      warn 'Can\'t display neuron. Get OpenGL?';
      return;
   }
   my $self = shift;
   my $n = shift // 0;
   my $x = shift || 28;
   my $y = shift || 28;
   my $w = $self->theta1->slice(":,$n")->copy;
   $w = $w->squeeze;
   my $min = $w->minimum;
   $w -= $min;
   my $max = $w->maximum;
   $w /= $max;
   $w = $w->reshape($x,$y);
   PDL::Graphics2D::imag2d $w;
}

'$nn->train($sovietRussian)';