예제 #1
0
        public ProtoNet(int[] topology)
        {
            // Validate the input.
            if (topology == null || topology.Length < 1) return;
            this.topology = topology;

            // NOTE: I seed my random for consistency when
            // testing the network.
            rand = new Random(424242);

            // And now I'm cheating with a flattened
            // list of nodes. This makes training easier.
            flattened = new List<Neuron>();

            // Create the neuron array.
            inputs = new Neuron[topology[0]];

            // Generate the input nodes and recursively construct the graph.
            for (var i = 0; i < topology[0]; i++)
            {
                // The first layer of the topology arg will be
                // representative of the inputs.
                inputs[i] = new Neuron(topology[0], rand);
                flattened.Add(inputs[i]);
            }

            // Recursively construct the graph.
            recurse(inputs, topology, 1);
        }
예제 #2
0
        private void recurse(Neuron[] parents, int[] topology, int index)
        {
            if (parents == null || parents.Length == 0) return;
            if (topology == null || topology.Length == 0) return;
            if (index >= topology.Length) return;

            // Construct the next layer.
            Neuron[] layer = new Neuron[topology[index]];
            for (var i = 0; i < layer.Length; i++)
            {
                // Create each node in this layer.
                layer[i] = new Neuron(parents.Length, rand);
                flattened.Add(layer[i]);
            }

            // "Wire up" the parents.
            for (var i = 0; i < parents.Length; i++)
            {
                parents[i].Children = layer;
            }

            // Recurse.
            recurse(layer, topology, ++index);
        }