public void SpeedTest()
{
int inchannels = 1024, outchannels = 512;
OverflowCheckedTensor x_tensor = new OverflowCheckedTensor(Shape.Map0D(inchannels));
OverflowCheckedTensor w_tensor = new OverflowCheckedTensor(Shape.Kernel0D(inchannels, outchannels));
OverflowCheckedTensor y_tensor = new OverflowCheckedTensor(Shape.Map0D(outchannels));
Dense ope = new Dense(inchannels, outchannels);
Stopwatch sw = new Stopwatch();
sw.Start();
ope.Execute(x_tensor, w_tensor, y_tensor);
ope.Execute(x_tensor, w_tensor, y_tensor);
ope.Execute(x_tensor, w_tensor, y_tensor);
ope.Execute(x_tensor, w_tensor, y_tensor);
sw.Stop();
Console.WriteLine($"{sw.ElapsedMilliseconds / 4} msec");
}
public void ExecuteTest()
{
float max_err = 0;
foreach (int batch in new int[] { 1, 2 })
{
foreach (int inchannels in new int[] { 1, 2, 3, 4, 5, 10, 15, 20 })
{
foreach (int outchannels in new int[] { 7, 13 })
{
float[] xval = (new float[inchannels * batch]).Select((_, idx) => idx * 1e-3f).ToArray();
float[] wval = (new float[inchannels * outchannels]).Select((_, idx) => idx * 1e-3f).Reverse().ToArray();
Map0D x = new Map0D(inchannels, batch, xval);
Filter0D w = new Filter0D(inchannels, outchannels, 1, wval);
Map0D y = Reference(x, w);
OverflowCheckedTensor x_tensor = new OverflowCheckedTensor(Shape.Map0D(inchannels, batch), xval);
OverflowCheckedTensor w_tensor = new OverflowCheckedTensor(Shape.Kernel0D(inchannels, outchannels), wval);
OverflowCheckedTensor y_tensor = new OverflowCheckedTensor(Shape.Map0D(outchannels, batch));
Dense ope = new Dense(inchannels, outchannels, batch);
ope.Execute(x_tensor, w_tensor, y_tensor);
float[] y_expect = y.ToArray();
float[] y_actual = y_tensor.State;
CollectionAssert.AreEqual(xval, x_tensor.State);
CollectionAssert.AreEqual(wval, w_tensor.State);
AssertError.Tolerance(y_expect, y_actual, 1e-7f, 1e-5f, ref max_err, $"mismatch value {inchannels},{outchannels},{batch}");
Console.WriteLine($"pass: {inchannels},{outchannels},{batch}");
}
}
}
Console.WriteLine($"maxerr:{max_err}");
}