Examples of BackpropagationAveragePooling2D

com.github.neuralnetworks.training.backpropagation.BackpropagationAveragePooling2D
Backpropagation for average pooling layers

Examples of com.github.neuralnetworks.training.backpropagation.BackpropagationAveragePooling2D

        } else if (ffcc instanceof AparapiReLU) {
      result = new BackPropagationReLU(p);
        } else if (ffcc instanceof AparapiMaxPooling2D || ffcc instanceof AparapiStochasticPooling2D) {
      result = new BackpropagationMaxPooling2D();
        } else if (ffcc instanceof AparapiAveragePooling2D) {
      result = new BackpropagationAveragePooling2D();
        } else if (ffcc instanceof ConnectionCalculatorConv) {
      Layer opposite = Util.getOppositeLayer(chunk.iterator().next(), current);
      if (!convCalculatedLayers.contains(opposite)) {
          convCalculatedLayers.add(opposite);

View Full Code Here

Examples of com.github.neuralnetworks.training.backpropagation.BackpropagationAveragePooling2D

  calc.calculate(connections, vp, c.getOutputLayer());


  ValuesProvider activations = new ValuesProvider();
  activations.addValues(c.getInputLayer(), a1);


  BackpropagationAveragePooling2D bp = new BackpropagationAveragePooling2D();
  bp.setActivations(activations);


  vp = new ValuesProvider();
  vp.addValues(c.getOutputLayer(), o);
  Matrix bpo = new Matrix(32, 2);
  vp.addValues(c.getInputLayer(), bpo);


  bp.calculate(connections, vp, c.getInputLayer());


  assertEquals(true, bpo.get(0, 0) == o.get(0, 0) / c.getSubsamplingRegionLength());
  assertEquals(true, bpo.get(1, 0) == o.get(0, 0) / c.getSubsamplingRegionLength());
  assertEquals(true, bpo.get(4, 0) == o.get(0, 0) / c.getSubsamplingRegionLength());
  assertEquals(true, bpo.get(5, 0) == o.get(0, 0) / c.getSubsamplingRegionLength());

View Full Code Here

Examples of com.github.neuralnetworks.training.backpropagation.BackpropagationAveragePooling2D

  float[] src = new float[] { 0.5f, 1, 1, 2, 1.5f, 3, 2, 4, 2.5f, 5, 3, 6, 3.5f, 7, 4f, 8, 4.5f, 9, 5f, 10, 5.5f, 11, 6f, 12, 6.5f, 13, 7f, 14, 8f, 16, 7.5f, 15, 8.5f, 17, 9f, 18, 9.5f, 19, 10f, 20, 10.5f, 21, 11f, 22, 11.5f, 23, 12f, 24, 12.5f, 25, 13f, 26, 13.5f, 27, 14f, 28, 14.5f, 29, 15f, 30, 16f, 32, 15.5f, 31 };
  System.arraycopy(src, 0, activations.get(c.getInputLayer()).getElements(), activations.get(c.getInputLayer()).getStartIndex(), src.length);


  calc.calculate(connections, activations, c.getOutputLayer());


  BackpropagationAveragePooling2D bp = new BackpropagationAveragePooling2D();
  bp.setActivations(activations);


  ValuesProvider vp = TensorFactory.tensorProvider(c, 2, true);
  TensorFactory.copy(activations.get(c.getOutputLayer()), vp.get(c.getOutputLayer()));


  bp.calculate(connections, vp, c.getInputLayer());


  Tensor o = activations.get(c.getOutputLayer());
  Tensor bpo = vp.get(c.getInputLayer());
  assertEquals(true, bpo.get(0, 0, 0, 0) == o.get(0, 0, 0, 0) / c.getSubsamplingRegionLength());
  assertEquals(true, bpo.get(0, 0, 2, 0) == o.get(0, 0, 1, 0) / c.getSubsamplingRegionLength());

View Full Code Here

Examples of com.github.neuralnetworks.training.backpropagation.BackpropagationAveragePooling2D

        } else if (ffcc instanceof AparapiMaxout) {
      result = new BackpropagationMaxout(p);
        } else if (ffcc instanceof AparapiMaxPooling2D || ffcc instanceof AparapiStochasticPooling2D) {
      result = new BackpropagationMaxPooling2D();
        } else if (ffcc instanceof AparapiAveragePooling2D) {
      result = new BackpropagationAveragePooling2D();
        } else if (ffcc instanceof ConnectionCalculatorConv) {
      Layer opposite = Util.getOppositeLayer(chunk.iterator().next(), current);
      if (!convCalculatedLayers.contains(opposite)) {
          convCalculatedLayers.add(opposite);

View Full Code Here

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.