public override InternalArray Forward(InternalArray ar)
{
#if PROFILER
LogItem = new CalcLogItem(this, "batchNorm2d");
var sw = Stopwatch.StartNew();
#endif
InternalArray ret = new InternalArray(ar.Shape);
var n = ar.Shape[0];
var c = ar.Shape[1];
List <float> data = new List <float>();
for (int i = 0; i < ar.Data.Length; i++)
{
var tt = (float)(((ar.Data[i] - RunningMean.Data[i]) / Math.Sqrt(RunningVar.Data[i] + eps)) * Weight.Data[i] + Bias.Data[i]);
data.Add(tt);
}
ret.Data = data.ToArray();
#if PROFILER
sw.Stop();
if (Parent != null)
{
Profiler.AddLog(Parent.LogItem, LogItem);
}
#endif
return(ret);
}
public override InternalArray Forward(InternalArray ar)
{
#if PROFILER
LogItem = new CalcLogItem(this, "avgPool2D");
var sw = Stopwatch.StartNew();
#endif
var hin = ar.Shape[2];
var win = ar.Shape[3];
var n = ar.Shape[0];
var c = ar.Shape[1];
var hout = ((hin + 2 * padding[0] - kernelSize[0]) / stride[0]) + 1;
var wout = ((win + 2 * padding[1] - kernelSize[1]) / stride[1]) + 1;
InternalArray ret = new InternalArray(new int[] { n, c, hout, wout });
//get all 2d images
//append them together to [n,c]
if (ar.QIntData != null)
{
List <short> data = new List <short>();
ret.QIntData = new short[ret.Data.Length];
ret.Data = null;
for (int i = 0; i < n; i++)
{
for (int j = 0; j < c; j++)
{
var img = Helpers.Get2DImageFrom4DArray(ar, i, j);
var img2 = Process2DImage(img);
data.AddRange(img2.QIntData);
}
}
ret.QIntData = data.ToArray();
}
else
{
List <float> data = new List <float>();
for (int i = 0; i < n; i++)
{
for (int j = 0; j < c; j++)
{
var img = Helpers.Get2DImageFrom4DArray(ar, i, j);
var img2 = Process2DImage(img);
data.AddRange(img2.Data);
}
}
ret.Data = data.ToArray();
}
#if PROFILER
sw.Stop();
Profiler.AddLog(LogItem, this, "exec", sw.ElapsedMilliseconds, true);
#endif
return(ret);
}
public override InternalArray Forward(InternalArray ar)
{
#if PROFILER
LogItem = new CalcLogItem(this, "batchNorm2d");
var sw = Stopwatch.StartNew();
#endif
InternalArray ret = new InternalArray(ar.Shape);
var n = ar.Shape[0];
var c = ar.Shape[1];
List <float> data = new List <float>();
for (int i = 0; i < n; i++)
{
for (int j = 0; j < c; j++)
{
var img = Helpers.Get2DImageFrom4DArray(ar, i, j);
for (int zi = 0; zi < img.Data.Length; zi++)
{
img.Data[zi] = (float)(((img.Data[zi] - RunningMean.Data[j]) / Math.Sqrt(RunningVar.Data[j] + eps)) * Weight.Data[j] + Bias.Data[j]);;
}
data.AddRange(img.Data);
}
}
ret.Data = data.ToArray();
#if PROFILER
sw.Stop();
if (Parent != null)
{
Profiler.AddLog(Parent.LogItem, LogItem);
}
#endif
return(ret);
}
public override InternalArray Forward(InternalArray ar)
{
//Profiler.PushCurrent(new CalcLogItem(this, "conv2d"));
#if PROFILER
LogItem = new CalcLogItem(this, "conv2d");
Profiler.AddLog(LogItem);
var sw = Stopwatch.StartNew();
#endif
var hin = ar.Shape[2];
var win = ar.Shape[3];
var n = ar.Shape[0];
var c = ar.Shape[1];
var hout = ((hin + 2 * padding[0] - dilation[0] * (kernelSize[0] - 1) - 1) / stride[0]) + 1;
var wout = ((win + 2 * padding[1] - dilation[1] * (kernelSize[1] - 1) - 1) / stride[1]) + 1;
var cout = Weight.Shape[0];
InternalArray ret = new InternalArray(new int[] { n, cout, hout, wout });
//get all 3d images
int pos = 0;
int pos0 = 0;
for (int i = 0; i < n; i++)
{
var img = ar.GetNext3DImageFrom4DArray(ref pos0);
InternalArray img2 = null;
if (AllowOptimized)
{
if (AllowOptimizedViaDot)
{
img2 = ProcessImageViaDot(img);
#if PROFILER
method = "dot";
#endif
}
else
{
/*if (dilation[0] == 1 && kernelSize[0] == 3 && padding[0] > 0)
* {
#if PROFILER
*
* method = "+pad";
#endif
* img2 = ProcessImageOptimized2(img, hout, wout, c, hin, win);
* var img4 = Helpers.Pad3d(img, padding[0]);
* var img3 = ProcessImageOptimizedNoPadding(img4, hout + padding[0] * 2, wout + padding[0] * 2, c, img.Shape[1], img.Shape[2]);
* var img5 = Helpers.Unpad3d(img, padding[0]);
*
* }
* else*/
{
if (padding[0] == 0 && dilation[1] == 1 && kernelSize[0] == 1 && stride[0] == 1)
{
#if PROFILER
method = "nopad.k1";
#endif
img2 = ProcessImageOptimizedNoPaddingKernel1(img, hout, wout, c, hin, win);
/*var img3 = ProcessImageOptimized2(img, hout, wout, c, hin, win);
* if (!img2.IsEqual(img3))
* {
* throw new Exception("11");
* }*/
}
else
if (padding[0] == 0 && dilation[0] == 1 && kernelSize[0] == 3)
{
#if PROFILER
method = "no pad";
//Helpers.Pad2d()
#endif
img2 = ProcessImageOptimizedNoPadding(img, hout, wout, c, hin, win);
/*var img3 = ProcessImageOptimized2(img, hout, wout, c, hin, win);
* if (!img2.IsEqual(img3))
* {
* throw new Exception("11");
* }
*/
}
else
{
#if PROFILER
method = "opt2";
#endif
img2 = ProcessImageOptimized2(img, hout, wout, c, hin, win);
}
}
}
}
else
{
#if PROFILER
method = "native";
#endif
//img2 = ProcessImage(img);
img2 = ProcessImageBySubRegions(img);
/*var res1 = ProcessImageBySubRegions(img);
* if (!img2.IsEqual(res1))
* {
* throw new Exception("11");
* }*/
}
Array.Copy(img2.Data, 0, ret.Data, pos, img2.Data.Length);
pos += img2.Data.Length;
}
//sw.Stop();
// LastMs = sw.ElapsedMilliseconds;
#if PROFILER
Profiler.AddLog(LogItem, this, method + "; hin: " + hin + "; win: ;" + win + "; padding: " + padding[0] + "; dilation: " + dilation[0] + "; ksize: " + kernelSize[0] + "; stride: " + stride[0] + "; nIn: " + inChannels + "; nOut: " + outChannels, LastMs);
Profiler.AddLog(LogItem, this, $"ar: {ar}; w: {Weight}");
Profiler.AddLog(LogItem, this, "out shape: " + ret.Shape.Aggregate("", (x, y) => x + y + "; "));
//Profiler.PopCurrent();
if (Parent != null)
{
Profiler.AddLog(Parent.LogItem, LogItem);
}
#endif
return(ret);
}
