Examples of ValuesProvider

com.github.neuralnetworks.calculation.ValuesProvider
Provides Matrix instances for the layers of the network. It ensures that the instances are reused.
com.github.neuralnetworks.calculation.memory.ValuesProvider
Something similar to tensor factory

Examples of com.github.neuralnetworks.calculation.memory.ValuesProvider

  FullyConnected cb1 = (FullyConnected) c.get(1);
  Matrix cgb1 = cb1.getWeights();
  cgb1.set(0.1f, 0, 0);
  cgb1.set(0.2f, 1, 0);


  ValuesProvider results = TensorFactory.tensorProvider(nn, 2, true);
  Matrix in = results.get(nn.getInputLayer());
  in.set(8, 0, 0);
  in.set(2, 1, 0);
  in.set(1, 0, 1);
  in.set(7, 1, 1);


  Set<Layer> calculated = new HashSet<>();
  calculated.add(nn.getInputLayer());
  nn.getLayerCalculator().calculate(nn, nn.getOutputLayer(), calculated, results);


  Matrix out = results.get(nn.getOutputLayer());
  assertEquals(1.1f, out.get(0, 0), 0f);
  assertEquals(1.2f, out.get(1, 0), 0f);
  assertEquals(3.6f, out.get(0, 1), 0f);
  assertEquals(3.7f, out.get(1, 1), 0f);

View Full Code Here

Examples of com.github.neuralnetworks.calculation.memory.ValuesProvider

  FullyConnected cb1 = (FullyConnected) c.get(1);
  Matrix cgb1 = cb1.getWeights();
  cgb1.set(0.1f, 0, 0);
  cgb1.set(0.2f, 1, 0);


  ValuesProvider results = TensorFactory.tensorProvider(nn, 2, true);
  Matrix in = results.get(nn.getInputLayer());
  in.set(8, 0, 0);
  in.set(2, 1, 0);
  in.set(1, 0, 1);
  in.set(7, 1, 1);

View Full Code Here

Examples of com.github.neuralnetworks.calculation.memory.ValuesProvider

      ip.reset();


      triggerEvent(new TestingStartedEvent(this));


      Set<Layer> calculatedLayers = new UniqueList<>();
      ValuesProvider results = TensorFactory.tensorProvider(n, getTestBatchSize(), Environment.getInstance().getUseDataSharedMemory());


      OutputError oe = getOutputError();
      if (oe != null) {
    oe.reset();
    results.add(oe, results.get(n.getOutputLayer()).getDimensions());
      }


      TrainingInputData input = new TrainingInputDataImpl(results.get(n.getInputLayer()), results.get(oe));
      for (int i = 0; i < ip.getInputSize(); i += getTestBatchSize()) {
    ip.populateNext(input);
    calculatedLayers.clear();
    calculatedLayers.add(n.getInputLayer());
    n.getLayerCalculator().calculate(n, n.getOutputLayer(), calculatedLayers, results);
    
    if (oe != null) {
        oe.addItem(results.get(n.getOutputLayer()), input.getTarget());
    }
    
    triggerEvent(new MiniBatchFinishedEvent(this, input, results, null));
      }

View Full Code Here

Examples of com.github.neuralnetworks.calculation.memory.ValuesProvider

  mlp.setLayerCalculator(NNFactory.lcWeightedSum(mlp, null));


  Set<Layer> calculated = new HashSet<>();
  calculated.add(mlp.getInputLayer());


  ValuesProvider results = TensorFactory.tensorProvider(mlp, 1, true);
  results.get(mlp.getInputLayer()).set(2, 0, 0);
  results.get(mlp.getInputLayer()).set(2, 1, 0);


  mlp.getLayerCalculator().calculate(mlp, output, calculated, results);


  assertEquals(1.32, results.get(output).get(0, 0), 0.000001);
    }

View Full Code Here

Examples of com.github.neuralnetworks.calculation.memory.ValuesProvider

    if (n.getLayerCalculator() != null) {
        OutputError outputError = t.getOutputError();
        outputError.reset();
        inputProvider.reset();


        ValuesProvider vp = mbe.getResults();
        if (vp == null) {
      vp = TensorFactory.tensorProvider(n, 1, Environment.getInstance().getUseDataSharedMemory());
        }
        if (vp.get(outputError) == null) {
      vp.add(outputError, vp.get(n.getOutputLayer()).getDimensions());
        }
        TrainingInputData input = new TrainingInputDataImpl(vp.get(n.getInputLayer()), vp.get(outputError));


        Set<Layer> calculatedLayers = new UniqueList<>();
        for (int i = 0; i < inputProvider.getInputSize(); i++) {
      inputProvider.populateNext(input);
      calculatedLayers.clear();
      calculatedLayers.add(n.getInputLayer());


      n.getLayerCalculator().calculate(n, n.getOutputLayer(), calculatedLayers, vp);


      outputError.addItem(vp.get(n.getOutputLayer()), input.getTarget());
        }


        float e = outputError.getTotalNetworkError();
        if (e <= acceptanceError) {
      System.out.println("Stopping at error " + e + " (" + (e * 100) + "%) for " + mbe.getBatchCount() + " minibatches");

View Full Code Here

Examples of com.github.neuralnetworks.calculation.memory.ValuesProvider

  t.forEach(i -> e6[i] = 0.5f);


  Set<Layer> calculatedLayers = new HashSet<>();
  calculatedLayers.add(dbn.getInputLayer());


  ValuesProvider results = TensorFactory.tensorProvider(dbn, 1, true);
  results.get(dbn.getInputLayer()).set(1, 0, 0);
  results.get(dbn.getInputLayer()).set(0, 1, 0);
  results.get(dbn.getInputLayer()).set(1, 2, 0);
  dbn.getLayerCalculator().calculate(dbn, dbn.getOutputLayer(), calculatedLayers, results);


  assertEquals(1.06, results.get(dbn.getOutputLayer()).get(0, 0), 0.00001);
  assertEquals(1.06, results.get(dbn.getOutputLayer()).get(1, 0), 0.00001);
    }

View Full Code Here

Examples of com.github.neuralnetworks.calculation.memory.ValuesProvider

  t.forEach(i -> e8[i] = 0.9f);


  Set<Layer> calculatedLayers = new HashSet<>();
  calculatedLayers.add(sae.getInputLayer());


  ValuesProvider results = TensorFactory.tensorProvider(sae, 1, true);
  results.get(sae.getInputLayer()).set(1, 0, 0);
  results.get(sae.getInputLayer()).set(0, 1, 0);
  results.get(sae.getInputLayer()).set(1, 2, 0);


  sae.getLayerCalculator().calculate(sae, sae.getOutputLayer(), calculatedLayers, results);


  assertEquals(1.06, results.get(sae.getOutputLayer()).get(0, 0), 0.00001);
  assertEquals(1.06, results.get(sae.getOutputLayer()).get(1, 0), 0.00001);
    }

View Full Code Here

Examples of com.github.neuralnetworks.calculation.memory.ValuesProvider


public class GeneralTest {


    @Test
    public void testTensorProvider() {
  ValuesProvider tp = new ValuesProvider(true);
  String s1 = "1";
  tp.add(s1, 2, 3);
  String s2 = "2";
  tp.add(s2, 2, 3);


  assertTrue(tp.get(s1).getElements() == tp.get(s2).getElements());
  assertEquals(12, tp.get(s1).getElements().length, 0);
  assertEquals(0, tp.get(s1).getStartIndex(), 0);
  assertEquals(12, tp.get(s2).getElements().length, 0);
  assertEquals(6, tp.get(s2).getStartIndex(), 0);


  ValuesProvider tp2 = new ValuesProvider(tp);
  tp2.add(s1, 2, 3);
  tp2.add(s2, 2, 3);


  assertTrue(tp2.get(s1).getElements() == tp.get(s2).getElements());
  assertEquals(24, tp2.get(s1).getElements().length, 0);
  assertEquals(12, tp2.get(s1).getStartIndex(), 0);
  assertEquals(18, tp2.get(s2).getStartIndex(), 0);
    }

View Full Code Here

Examples of com.github.neuralnetworks.calculation.memory.ValuesProvider

  Environment.getInstance().setUseWeightsSharedMemory(true);
  ConnectionFactory cf = new ConnectionFactory();
  NNFactory.addFullyConnectedLayer(nn, h, cf, 2, 3, true);
  NNFactory.addFullyConnectedLayer(nn, o, cf, 4, 1, true);


  ValuesProvider tp = TensorFactory.tensorProvider(nn, 2, true);


  Matrix im = tp.get(nn.getInputLayer());
  Matrix hm1 = tp.get(h, 3, 2);
  Matrix hm2 = tp.get(h, 4, 2);


  Tensor om = tp.get(o);


  assertTrue(im == tp.get(i, 2, 2));
  assertTrue(im == tp.get(i));
  assertTrue(hm1 == tp.get(h, 3, 2));
  assertTrue(hm2 == tp.get(h, 4, 2));
  assertTrue(hm1 == TensorFactory.tensor(h, nn.getConnection(i, h), tp));
  assertTrue(hm2 == TensorFactory.tensor(h, nn.getConnection(h, o), tp));
  assertTrue(om == tp.get(o, 1, 2));
  assertTrue(om == tp.get(o));
    }

View Full Code Here

Examples of com.github.neuralnetworks.calculation.memory.ValuesProvider

    @Test
    public void testTensorProvider3() {
  // simple mlp test
  Environment.getInstance().setUseWeightsSharedMemory(true);
  NeuralNetworkImpl nn = NNFactory.mlp(new int[] { 3, 4, 2 }, true);
  ValuesProvider tp = TensorFactory.tensorProvider(nn, 2, false);


  Matrix in = tp.get(nn.getInputLayer());
  Matrix hidden = tp.get(nn.getLayers().stream().filter(l -> l != nn.getInputLayer() && l != nn.getOutputLayer() && !Util.isBias(l)).findFirst().get());
  Matrix out = tp.get(nn.getOutputLayer());


  assertEquals(6, in.getElements().length, 0);
  assertEquals(3, in.getRows(), 0);
  assertEquals(2, in.getColumns(), 0);
  assertEquals(8, hidden.getElements().length, 0);

View Full Code Here

0 1 2 3 4

TOP

All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.