Package tv.floe.metronome.classification.neuralnetworks.learning.adagrad

Examples of tv.floe.metronome.classification.neuralnetworks.learning.adagrad.AdagradLearningRate

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                for (Neuron neuron : this.nn.getLayerByIndex(x).getNeurons()) {
                 
                    for (Connection connection : neuron.getInConnections()) {
                     
                        connection.getWeight().trainingMetaData.put("adagrad", new AdagradLearningRate(this.adagradInitLearningRate));
                       
                    }
                   
                }
                 
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  @Override
    protected void updateNeuronWeights(Neuron neuron) {

      double neuronError = neuron.getError();
        double lrTemp = 0;
        AdagradLearningRate alr = null;
       
        for (Connection connection : neuron.getInConnections()) {

          if (this.adagradLearningOn) {
            alr = (AdagradLearningRate)connection.getWeight().trainingMetaData.get("adagrad");
            lrTemp = alr.compute();
          } else {
            lrTemp = this.learningRate;
          }
         
          double input = connection.getInput();
            //double weightChange = this.learningRate * neuronError * input;
          double weightChange = lrTemp * neuronError * input;

            Weight weight = connection.getWeight();

            if (this.isInBatchMode() == false) {            
                weight.weightChange = weightChange;               
                weight.value += weightChange;
            } else {
                weight.weightChange += weightChange;
            }
           
          if (this.adagradLearningOn) {
            alr = (AdagradLearningRate)connection.getWeight().trainingMetaData.get("adagrad");
            alr.addLastIterationGradient(weightChange);
          }           
           
            if (this.isMetricCollectionOn()) {
              this.metrics.incWeightOpCount();
            }
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        out += "n" + n + "=";
       
            for (Connection connection : neuron.getInConnections()) {

              if (this.adagradLearningOn) {
                AdagradLearningRate alr = (AdagradLearningRate)connection.getWeight().trainingMetaData.get("adagrad");
                //lrTemp = alr.compute();
                out += "" + alr.compute() +",";
              }

            }
           
            n++;
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      Connection c = neuron.getInConnections().get(0);
               
      AdagradLearningRate alr = (AdagradLearningRate)c.getWeight().trainingMetaData.get("adagrad");
                //lrTemp = alr.compute();
       
      out += "[Ada: " + alr.compute() +" ]";

      c = neuron.getInConnections().get(1);
       
      alr = (AdagradLearningRate)c.getWeight().trainingMetaData.get("adagrad");

      out += "[Ada: " + alr.compute() +" ]";
     
    }
   
    return out;
   
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Related Classes of tv.floe.metronome.classification.neuralnetworks.learning.adagrad.AdagradLearningRate

  • tv.floe.metronome.classification.neuralnetworks.learning.BackPropogationLearningAlgorithm
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