Package com.github.neuralnetworks.calculation

Examples of com.github.neuralnetworks.calculation.ValuesProvider.addValues()

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  ConnectionCalculator calc = new AparapiMaxPooling2D();
  Matrix o = new Matrix(8, 2);

  ValuesProvider vp = new ValuesProvider();
  vp.addValues(c.getInputLayer(), i1);
  vp.addValues(c.getOutputLayer(), o);

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

  assertEquals(3, o.get(0, 0), 0);
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  ConnectionCalculator calc = new AparapiMaxPooling2D();
  Matrix o = new Matrix(8, 2);

  ValuesProvider vp = new ValuesProvider();
  vp.addValues(c.getInputLayer(), i1);
  vp.addValues(c.getOutputLayer(), o);

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

  assertEquals(3, o.get(0, 0), 0);
  assertEquals(4, o.get(1, 0), 0);
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  AparapiAveragePooling2D calc = new AparapiAveragePooling2D();
  Matrix o = new Matrix(8, 2);

  ValuesProvider vp = new ValuesProvider();
  vp.addValues(c.getInputLayer(), i1);
  vp.addValues(c.getOutputLayer(), o);

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

  assertEquals(1.75, o.get(0, 0), 0);
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  AparapiAveragePooling2D calc = new AparapiAveragePooling2D();
  Matrix o = new Matrix(8, 2);

  ValuesProvider vp = new ValuesProvider();
  vp.addValues(c.getInputLayer(), i1);
  vp.addValues(c.getOutputLayer(), o);

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

  assertEquals(1.75, o.get(0, 0), 0);
  assertEquals(2.75, o.get(1, 0), 0);
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  connections.add(c);

  Matrix o = new Matrix(1, 2);

  ValuesProvider vp = new ValuesProvider();
  vp.addValues(c.getInputLayer(), i1);
  vp.addValues(c.getOutputLayer(), o);

  AparapiStochasticPooling2D calc = new AparapiStochasticPooling2D();
  calc.calculate(connections, vp, c.getOutputLayer());
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  Matrix o = new Matrix(1, 2);

  ValuesProvider vp = new ValuesProvider();
  vp.addValues(c.getInputLayer(), i1);
  vp.addValues(c.getOutputLayer(), o);

  AparapiStochasticPooling2D calc = new AparapiStochasticPooling2D();
  calc.calculate(connections, vp, c.getOutputLayer());

  assertEquals(2.08, o.get(0, 0), 0.01);
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  List<Connections> connections = new ArrayList<Connections>();
  connections.add(c);

  // max pooling
  ValuesProvider vp = new ValuesProvider();
  vp.addValues(c.getInputLayer(), a1);
  vp.addValues(c.getOutputLayer(), o);

  ConnectionCalculator calc = new AparapiMaxPooling2D();
  calc.calculate(connections, vp, c.getOutputLayer());
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  connections.add(c);

  // max pooling
  ValuesProvider vp = new ValuesProvider();
  vp.addValues(c.getInputLayer(), a1);
  vp.addValues(c.getOutputLayer(), o);

  ConnectionCalculator calc = new AparapiMaxPooling2D();
  calc.calculate(connections, vp, c.getOutputLayer());

  ValuesProvider activations = new ValuesProvider();
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  ConnectionCalculator calc = new AparapiMaxPooling2D();
  calc.calculate(connections, vp, c.getOutputLayer());

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

  Matrix bpo = new Matrix(32, 2);

  vp = new ValuesProvider();
  vp.addValues(c.getOutputLayer(), o);
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  List<Connections> connections = new ArrayList<Connections>();
  connections.add(c);

  ValuesProvider vp = new ValuesProvider();
  vp.addValues(c.getInputLayer(), a1);
  Matrix o = new Matrix(8, 2);
  vp.addValues(c.getOutputLayer(), o);

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