Package com.github.neuralnetworks.calculation.neuronfunctions

Examples of com.github.neuralnetworks.calculation.neuronfunctions.AparapiConv2D.calculate()

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  Matrix o = new Matrix(4, 1);

  AparapiConv2D conv = new AparapiConv2DFF(c, 1);

  conv.calculate(c, i1, o);

  // most simple case
  assertEquals(164, o.get(0, 0), 0);
  assertEquals(184, o.get(0, 1), 0);
  assertEquals(224, o.get(0, 2), 0);
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  Matrix o = new Matrix(8, 1);

  AparapiConv2D conv = new AparapiConv2DFF(c, 1);

  conv.calculate(c, i1, o);

  assertEquals(164, o.get(0, 0), 0);
  assertEquals(184, o.get(0, 1), 0);
  assertEquals(224, o.get(0, 2), 0);
  assertEquals(244, o.get(0, 3), 0);
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  for (int i = 0; i < vp.get(c.getInputLayer()).getSize(); i++) {
      vp.get(c.getInputLayer()).getElements()[it.next()] = i + 1;
  }

  AparapiConv2D conv = new AparapiConv2DFF(c, vp, c.getOutputLayer());
  conv.calculate(c, vp, c.getOutputLayer());

  // most simple case
  Tensor o = vp.get(c.getOutputLayer());

  assertEquals(164, o.get(0, 0, 0, 0), 0);
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  for (int i = 0; i < vp.get(c.getInputLayer()).getSize(); i++) {
      vp.get(c.getInputLayer()).getElements()[it.next()] = i + 1;
  }

  AparapiConv2D conv = new AparapiConv2DFF(c, vp, c.getOutputLayer());
  conv.calculate(c, vp, c.getOutputLayer());

  Tensor o = vp.get(c.getOutputLayer());

  assertEquals(164, o.get(0, 0, 0, 0), 0);
  assertEquals(184, o.get(0, 0, 1, 0), 0);
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