List of encodedArrayLength() Examples

Examples of encodedArrayLength()

org.encog.ml.MLEncodable.encodedArrayLength()
@return The length of an encoded array.
org.encog.neural.networks.BasicNetwork.encodedArrayLength()
{@inheritDoc}

Examples of org.encog.ml.MLEncodable.encodedArrayLength()

      for (int i = 0; i < network.getLayerCount() - 1; i++) {
        randomize(network, i);
      }
    } else if (method instanceof MLEncodable) {
      final MLEncodable encode = (MLEncodable) method;
      final double[] encoded = new double[encode.encodedArrayLength()];
      encode.encodeToArray(encoded);
      randomize(encoded);
      encode.decodeFromArray(encoded);
    }
  }

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Examples of org.encog.ml.MLEncodable.encodedArrayLength()

    }


    if (method instanceof MLEncodable) {
      MLEncodable encode = (MLEncodable)method;
      report.tablePair("Encoded Length",
          Format.formatInteger(encode.encodedArrayLength()));
    }


    report.tablePair("Resettable",
        (method instanceof MLResettable) ? "true" : "false");

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Examples of org.encog.ml.MLEncodable.encodedArrayLength()

      final EncogProgramNode mainClass, final File method) {


    if (this.embedData) {
      final MLEncodable encodable = (MLEncodable) EncogDirectoryPersistence
          .loadObject(method);
      final double[] weights = new double[encodable.encodedArrayLength()];
      encodable.encodeToArray(weights);
      mainClass.createArray("WEIGHTS", weights);
    }


    return mainClass.createNetworkFunction("createNetwork", method);

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Examples of org.encog.ml.MLEncodable.encodedArrayLength()

      for (int i = 0; i < network.getLayerCount() - 1; i++) {
        randomize(network, i);
      }
    } else if (method instanceof MLEncodable) {
      final MLEncodable encode = (MLEncodable) method;
      final double[] encoded = new double[encode.encodedArrayLength()];
      encode.encodeToArray(encoded);
      randomize(encoded);
      encode.decodeFromArray(encoded);
    }
  }

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Examples of org.encog.neural.networks.BasicNetwork.encodedArrayLength()


public class TestAnalyzeNetwork extends TestCase {
  public void testAnalyze()
  {
    BasicNetwork network = EncogUtility.simpleFeedForward(2, 2, 0, 1, false);
    double[] weights = new double[network.encodedArrayLength()];
    EngineArray.fill(weights, 1.0);
    network.decodeFromArray(weights);
    AnalyzeNetwork analyze = new AnalyzeNetwork(network);
    Assert.assertEquals(weights.length, analyze.getWeightsAndBias().getSamples());
    Assert.assertEquals(3,analyze.getBias().getSamples());

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Examples of org.encog.neural.networks.BasicNetwork.encodedArrayLength()

    Assert.assertTrue(network.isLayerBiased(2));
    Assert.assertEquals(3, network.getLayerCount());
    Assert.assertTrue(network.getActivation(0) instanceof ActivationLinear );
    Assert.assertTrue(network.getActivation(1) instanceof ActivationTANH );
    Assert.assertTrue(network.getActivation(2) instanceof ActivationLinear );
    Assert.assertEquals(18,network.encodedArrayLength());
    Assert.assertEquals(1,network.getLayerNeuronCount(0));
    Assert.assertEquals(3,network.getLayerNeuronCount(1));
    Assert.assertEquals(4,network.getLayerNeuronCount(2));
  }

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Examples of org.encog.neural.networks.BasicNetwork.encodedArrayLength()

  {
    BasicNetwork network = obtainNetwork();
    Assert.assertEquals(2, network.getInputCount());
    PruneSelective prune = new PruneSelective(network);
    prune.prune(0, 1);
    Assert.assertEquals(22, network.encodedArrayLength());
    Assert.assertEquals(1,network.getLayerNeuronCount(0));
    Assert.assertEquals("1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,19,20,22,23,25", network.dumpWeights());
    
    BasicNetwork model = EncogUtility.simpleFeedForward(1,3,0,4,false);
    checkWithModel(model.getStructure().getFlat(),network.getStructure().getFlat());

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Examples of org.encog.neural.networks.BasicNetwork.encodedArrayLength()

  public void testPruneNeuronHidden()
  {
    BasicNetwork network = obtainNetwork();
    PruneSelective prune = new PruneSelective(network);
    prune.prune(1, 1);
    Assert.assertEquals(18, network.encodedArrayLength());
    Assert.assertEquals(2,network.getLayerNeuronCount(1));
    Assert.assertEquals("1,3,4,5,7,8,9,11,12,13,15,16,17,18,19,23,24,25", network.dumpWeights());
    
    BasicNetwork model = EncogUtility.simpleFeedForward(2,2,0,4,false);
    checkWithModel(model.getStructure().getFlat(),network.getStructure().getFlat());

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Examples of org.encog.neural.networks.BasicNetwork.encodedArrayLength()

  {
    BasicNetwork network = obtainNetwork();
    Assert.assertEquals(4, network.getOutputCount());
    PruneSelective prune = new PruneSelective(network);
    prune.prune(2, 1);
    Assert.assertEquals(21, network.encodedArrayLength());
    Assert.assertEquals(3,network.getLayerNeuronCount(2));
    Assert.assertEquals("1,2,3,4,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25", network.dumpWeights());
    
    BasicNetwork model = EncogUtility.simpleFeedForward(2,3,0,3,false);
    checkWithModel(model.getStructure().getFlat(),network.getStructure().getFlat());

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Examples of org.encog.neural.networks.BasicNetwork.encodedArrayLength()

  {
    BasicNetwork network = obtainNetwork();
    Assert.assertEquals(2, network.getInputCount());
    PruneSelective prune = new PruneSelective(network);
    prune.prune(0, 1);
    Assert.assertEquals(22, network.encodedArrayLength());
    Assert.assertEquals(1,network.getLayerNeuronCount(0));
    Assert.assertEquals("1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,19,20,22,23,25", network.dumpWeights());
    
    BasicNetwork model = EncogUtility.simpleFeedForward(1,3,0,4,false);
    checkWithModel(model.getStructure().getFlat(),network.getStructure().getFlat());

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