public void SpeedTest() { int inwidth = 512, channels = 32, stride = 2; int outwidth = inwidth / stride; OverflowCheckedTensor x_tensor = new OverflowCheckedTensor(Shape.Map1D(channels, inwidth)); OverflowCheckedTensor y_tensor = new OverflowCheckedTensor(Shape.Map1D(channels, outwidth)); AveragePooling ope = new AveragePooling(inwidth, channels, stride); Stopwatch sw = new Stopwatch(); sw.Start(); ope.Execute(x_tensor, y_tensor); ope.Execute(x_tensor, y_tensor); ope.Execute(x_tensor, y_tensor); ope.Execute(x_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 channels in new int[] { 3, 5 }) { foreach (int stride in new int[] { 2, 3, 4 }) { foreach (int inwidth in new int[] { 5, 7, 11 }) { foreach (int inheight in new int[] { 5, 7, 11 }) { foreach (int indepth in new int[] { 5, 7, 11 }) { int outwidth = inwidth / stride, outheight = inheight / stride, outdepth = indepth / stride; float[] xval = (new float[inwidth * inheight * indepth * channels * batch]).Select((_, idx) => idx * 1e-3f).ToArray(); Map3D x = new Map3D(channels, inwidth, inheight, indepth, batch, xval); Map3D y = Reference(x, stride); OverflowCheckedTensor x_tensor = new OverflowCheckedTensor(Shape.Map3D(channels, inwidth, inheight, indepth, batch), xval); OverflowCheckedTensor y_tensor = new OverflowCheckedTensor(Shape.Map3D(channels, outwidth, outheight, outdepth, batch)); AveragePooling ope = new AveragePooling(inwidth, inheight, indepth, channels, stride, batch); ope.Execute(x_tensor, y_tensor); float[] y_expect = y.ToArray(); float[] y_actual = y_tensor.State; CollectionAssert.AreEqual(xval, x_tensor.State); AssertError.Tolerance(y_expect, y_actual, 1e-7f, 1e-5f, ref max_err, $"mismatch value {channels},{stride},{inwidth},{inheight},{indepth},{batch}"); Console.WriteLine($"pass: {channels},{stride},{inwidth},{inheight},{indepth},{batch}"); } } } } } } Console.WriteLine($"maxerr:{max_err}"); }