Package tv.floe.metronome.classification.neuralnetworks.iterativereduce

Examples of tv.floe.metronome.classification.neuralnetworks.iterativereduce.NetworkWeightsUpdateable


 
 
  @Test
  public void testBaseJavaObjectSerialization() {

    NetworkWeightsUpdateable nwu = new NetworkWeightsUpdateable();
   
    Config c = new Config();
    c.parse(null); // default layer: 2-3-2
        c.setConfValue("inputFunction", WeightedSum.class);
    c.setConfValue("transferFunction", Tanh.class);
    c.setConfValue("neuronType", Neuron.class);
    c.setConfValue("networkType", NeuralNetwork.NetworkType.MULTI_LAYER_PERCEPTRON);
    c.setConfValue("layerNeuronCounts", "2,3,1" );
    c.parse(null);
   
    NeuralNetwork nn = new MultiLayerPerceptronNetwork();
   
    try {
      nn.buildFromConf(c);
    } catch (Exception e) {
      // TODO Auto-generated catch block
      e.printStackTrace();
    }
   
    NeuralNetworkWeightsDelta nnwd = new NeuralNetworkWeightsDelta();
    nnwd.network = nn;
   
    nwu.set(nnwd);
   
    nwu.toBytes();
   
   
   
   
   
View Full Code Here


  }
 
  @Test
  public void testMasterNodeObjectSerialization() {

    NetworkWeightsUpdateable nwu = new NetworkWeightsUpdateable();
   
    Config c = new Config();
    c.parse(null); // default layer: 2-3-2
        c.setConfValue("inputFunction", WeightedSum.class);
    c.setConfValue("transferFunction", Tanh.class);
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