public override float InferenceTraining(CudaDeviceVariable <float> input)
{
float error = 0;
switch (_norm)
{
case Norm.L1:
//derivative of cost-function. Hier L1-Norm:
_res.CopyToDevice(input);
_groundTrouthData.Sub(input, _dx);
_dx.Threshold_GTVal(0, 1);
_dx.Threshold_LTVal(0, -1);
_dx.DivC(_batch * _inChannels * _inWidth * _inHeight);
_groundTrouthData.Sub(input, _temp);
_temp.Abs();
_temp.Sum(_summedError, _buffer);
error = _summedError;
error = error / _batch / _inChannels / _inWidth / _inHeight;
break;
case Norm.L2:
//derivative of cost-function. Hier L2-Norm:
_res.CopyToDevice(input);
_groundTrouthData.Sub(input, _dx);
_dx.DivC(_batch * _inChannels * _inWidth * _inHeight);
_groundTrouthData.Sub(input, _temp);
_temp.Sqr();
_temp.Sum(_summedError, _buffer);
error = _summedError;
error = error / _batch / _inChannels / _inWidth / _inHeight;
break;
case Norm.MSSSIM:
_res.CopyToDevice(input);
_kernelMSSSIML1.RunSafe(input, _groundTrouthData, _msssiml1, _dx, _inChannels, _batch, 1.0f);
_msssiml1.Sum(_summedError, _buffer);
error = _summedError;
error = error / _batch / _inChannels;
break;
case Norm.Mix:
_res.CopyToDevice(input);
_kernelMSSSIML1.RunSafe(input, _groundTrouthData, _msssiml1, _dx, _inChannels, _batch, 0.84f);
_msssiml1.Sum(_summedError, _buffer);
error = _summedError;
break;
default:
break;
}
return(error);
}
