public void AveragePoolingLayer_Forward()
{
var bottom = new Tensor(1, 1, 3, 3);
var filler = new ConstantFiller(2.0d);
filler.Fill(bottom);
var layer = new AveragePoolingLayer(3, 1, 1);
layer.Setup(bottom, top);
Assert.Equal(1, top.Num);
Assert.Equal(1, top.Channels);
Assert.Equal(3, top.Height);
Assert.Equal(3, top.Width);
layer.Forward(bottom, top);
using (var topCpu = top.OnCpu())
{
var topData = topCpu.Data;
AssertInRange(8.0d / 9, topData[0]);
AssertInRange(4.0d / 3, topData[1]);
AssertInRange(8.0d / 9, topData[2]);
AssertInRange(4.0d / 3, topData[3]);
AssertInRange(2.0d, topData[4]);
AssertInRange(4.0d / 3, topData[5]);
AssertInRange(8.0d / 9, topData[6]);
AssertInRange(4.0d / 3, topData[7]);
AssertInRange(8.0d / 9, topData[8]);
}
}
public void AveragePoolingLayer_Forward()
{
var bottom = new Tensor(1, 1, 3, 3);
var filler = new ConstantFiller(2.0d);
filler.Fill(bottom);
var layer = new AveragePoolingLayer(3, 1, 1);
layer.Setup(bottom, top);
Assert.Equal(1, top.Num);
Assert.Equal(1, top.Channels);
Assert.Equal(3, top.Height);
Assert.Equal(3, top.Width);
layer.Forward(bottom, top);
using (var topCpu = top.OnCpu())
{
var topData = topCpu.Data;
AssertInRange(8.0d / 9, topData[0]);
AssertInRange(4.0d / 3, topData[1]);
AssertInRange(8.0d / 9, topData[2]);
AssertInRange(4.0d / 3, topData[3]);
AssertInRange(2.0d, topData[4]);
AssertInRange(4.0d / 3, topData[5]);
AssertInRange(8.0d / 9, topData[6]);
AssertInRange(4.0d / 3, topData[7]);
AssertInRange(8.0d / 9, topData[8]);
}
}
public void ForwardBackwardTest()
{
foreach (string format in new[] { Shape.BWHC, Shape.BHWC, Shape.BCHW })
{
Shape shape = new Shape(format, -1, 13, 11, 2);
foreach (int kw in new[] { 1, 2, 3, 4, 5 })
{
foreach (int kh in new[] { 1, 2, 3, 4, 5 })
{
foreach (int kstridex in new[] { 1, 2, 3 })
{
foreach (int kstridey in new[] { 1, 2, 3 })
{
foreach (int kpaddingx in new[] { 0, 2, -2 })
{
foreach (int kpaddingy in new[] { 0, 2, -2 })
{
Kernel kernel = new Kernel(kw, kh, kstridex, kstridey, kpaddingx, kpaddingy);
AveragePoolingLayer layer = new AveragePoolingLayer(shape, kernel);
for (int mb = 1; mb <= 3; mb++)
{
Session session = new Session(true);
Tensor x = new Tensor(null, shape.Reshape(Axis.B, mb));
x.Randomize(this.random);
Tensor y = layer.Forward(session, new[] { x })[0];
Tensor expected = AveragePoolingLayerTest.CalculateY(x, kernel);
Helpers.AreTensorsEqual(expected, y);
// unroll the graph
y.RandomizeGradient(this.random);
session.Unroll();
Tensor expectedDX = AveragePoolingLayerTest.CalculateDX(x, y, kernel);
Helpers.AreGradientsEqual(expectedDX, x);
}
}
}
}
}
}
}
}
}
