public void ReferenceTest()
{
int inchannels = 9, outchannels = 12, batch = 3;
float[] xval = (new float[batch * inchannels]).Select((_, idx) => idx * 1e-2f).ToArray();
float[] wval = (new float[outchannels * inchannels / 9 * 4]).Select((_, idx) => idx * 1e-2f).Reverse().ToArray();
Trivector[] xcval = (new Trivector[xval.Length / 3])
.Select((_, idx) => new Trivector(xval[idx * 3], xval[idx * 3 + 1], xval[idx * 3 + 2])).ToArray();
Quaternion.Quaternion[] wcval = (new Quaternion.Quaternion[wval.Length / 4])
.Select((_, idx) => new Quaternion.Quaternion(wval[idx * 4], wval[idx * 4 + 1], wval[idx * 4 + 2], wval[idx * 4 + 3])).ToArray();
TrivectorMap0D x = new TrivectorMap0D(inchannels / 3, batch, xcval);
Quaternion.QuaternionFilter0D w = new Quaternion.QuaternionFilter0D(inchannels / 3, outchannels / 3, wcval);
TrivectorMap0D y = Reference(x, w);
float[] y_expect =
{
9.880600000e-02f, 5.148000000e-02f, 7.391000000e-02f, 4.912600000e-02f, 2.397600000e-02f, 3.575000000e-02f,
1.672600000e-02f, 6.840000000e-03f, 1.141400000e-02f, 1.606000000e-03f, 7.200000000e-05f, 9.020000000e-04f,
2.949520000e-01f, 2.340180000e-01f, 2.567720000e-01f, 1.506640000e-01f, 1.157940000e-01f, 1.278920000e-01f,
5.476000000e-02f, 3.904200000e-02f, 4.394000000e-02f, 7.240000000e-03f, 3.762000000e-03f, 4.916000000e-03f,
4.910980000e-01f, 4.165560000e-01f, 4.396340000e-01f, 2.522020000e-01f, 2.076120000e-01f, 2.200340000e-01f,
9.279400000e-02f, 7.124400000e-02f, 7.646600000e-02f, 1.287400000e-02f, 7.452000000e-03f, 8.930000000e-03f,
};
float[] y_actual = y.ToArray();
AssertError.Tolerance(y_expect, y_actual, 1e-7f, 1e-5f, $"mismatch value {inchannels},{outchannels},{batch}");
}
public void ReferenceTest()
{
int inchannels = 9, outchannels = 12, batch = 3;
float[] yval = (new float[outchannels * batch]).Select((_, idx) => idx * 1e-2f).ToArray();
float[] wval = (new float[outchannels * inchannels / 9 * 4]).Select((_, idx) => idx * 1e-2f).Reverse().ToArray();
Trivector[] ycval = (new Trivector[yval.Length / 3])
.Select((_, idx) => new Trivector(yval[idx * 3], yval[idx * 3 + 1], yval[idx * 3 + 2])).ToArray();
Quaternion.Quaternion[] wcval = (new Quaternion.Quaternion[wval.Length / 4])
.Select((_, idx) => new Quaternion.Quaternion(wval[idx * 4], wval[idx * 4 + 1], wval[idx * 4 + 2], wval[idx * 4 + 3])).ToArray();
TrivectorMap0D y = new TrivectorMap0D(outchannels / 3, batch, ycval);
Quaternion.QuaternionFilter0D w = new Quaternion.QuaternionFilter0D(inchannels / 3, outchannels / 3, wcval);
TrivectorMap0D x = Reference(y, w);
float[] x_expect =
{
6.030000000e-02f, 2.514000000e-02f, 4.170000000e-02f, 4.426800000e-02f, 1.669200000e-02f, 2.979600000e-02f,
3.156400000e-02f, 1.054800000e-02f, 2.070800000e-02f, 2.506680000e-01f, 1.993800000e-01f, 2.165160000e-01f,
1.939320000e-01f, 1.525320000e-01f, 1.662120000e-01f, 1.466680000e-01f, 1.141320000e-01f, 1.248680000e-01f,
4.410360000e-01f, 3.736200000e-01f, 3.913320000e-01f, 3.435960000e-01f, 2.883720000e-01f, 3.026280000e-01f,
2.617720000e-01f, 2.177160000e-01f, 2.290280000e-01f
};
float[] x_actual = x.ToArray();
AssertError.Tolerance(x_expect, x_actual, 1e-7f, 1e-5f, $"mismatch value {inchannels},{outchannels},{batch}");
}
public void ExecuteTest()
{
float max_err = 0;
foreach (int batch in new int[] { 1, 2, 3 })
{
foreach (int inchannels in new int[] { 3, 6, 9, 12 })
{
foreach (int outchannels in new int[] { 3, 6, 9, 12 })
{
float[] xval = (new float[inchannels * batch]).Select((_, idx) => idx * 1e-3f).ToArray();
float[] wval = (new float[inchannels * outchannels / 9 * 4]).Select((_, idx) => idx * 1e-3f).Reverse().ToArray();
Trivector[] xcval = (new Trivector[xval.Length / 3])
.Select((_, idx) => new Trivector(xval[idx * 3], xval[idx * 3 + 1], xval[idx * 3 + 2])).ToArray();
Quaternion.Quaternion[] wcval = (new Quaternion.Quaternion[wval.Length / 4])
.Select((_, idx) => new Quaternion.Quaternion(wval[idx * 4], wval[idx * 4 + 1], wval[idx * 4 + 2], wval[idx * 4 + 3])).ToArray();
TrivectorMap0D x = new TrivectorMap0D(inchannels / 3, batch, xcval);
Quaternion.QuaternionFilter0D w = new Quaternion.QuaternionFilter0D(inchannels / 3, outchannels / 3, wcval);
TrivectorMap0D y = Reference(x, w);
OverflowCheckedTensor x_tensor = new OverflowCheckedTensor(Shape.Map0D(inchannels, batch), xval);
OverflowCheckedTensor w_tensor = new OverflowCheckedTensor(Shape.Kernel0D(inchannels / 3 * 4, outchannels / 3), wval);
OverflowCheckedTensor y_tensor = new OverflowCheckedTensor(Shape.Map0D(outchannels, batch));
TrivectorDense ope = new TrivectorDense(inchannels, outchannels, gradmode: false, 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}");
}