use AI::NeuralNet::BackProp;
use Quantum::Superpositions;
use Quantum::Entanglement qw(:DEFAULT :complex :QFT);
# Create a new network with 1 layer, 5 inputs, and 5 outputs.
        my $net = new AI::NeuralNet::BackProp(1,5,5);
        
        # Add a small amount of randomness to the network
        $net->random(0.001);

        # Demonstrate a simple learn() call
        my @inputs = all( 0,0,1,1,1 );
        my @outputs = any( 1,0,1,0,1 );
        
        print $net->learn(\@inputs, \@outputs),"\n";

        # Create a data set to learn
        my @set = entangle(
                [ 2,2,3,4,1 ], [ 1,1,1,1,1 ],
                [ 1,1,1,1,1 ], [ 0,0,0,0,0 ],
                [ 1,1,1,0,0 ], [ 0,0,0,1,1 ]    
        );
        
        # Demo learn_set()
        my $f = $net->learn_set(\@set);
        print "Forgetfulness: $f unit\n";
        
        # Crunch a bunch of strings and return array refs
        my $phrase1 = $net->crunch("Odin is a husky!");
        my $phrase2 = $net->crunch("Star is a husky.");
        my $phrase3 = $net->crunch("Rukia is also a husky");
        my $phrase4 = $net->crunch("Sorry, are you more of a cat perso
+n?");

        # Make a data set from the array refs
        my @phrases = any(
                $phrase1, $phrase2,
                $phrase3, $phrase4
        );

        # Learn the data set    
        $net->learn_set(\@phrases);
        
        # Run a test phrase through the network
        my $test_phrase = eigenstates($net->crunch("I love neural netw
+orking and quantum mechanics!"));
        my $result = $net->run($test_phrase);
        
       print all($net->uncrunch($result)),"\n";
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