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*implementation of class Base::SynetConvolution16bNchwGemm methods: S…
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…etWeight and Forward.
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@ermig1979
ermig1979 committed Jul 23, 2024
1 parent d4e49b1 commit 253654a
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Showing 2 changed files with 46 additions and 65 deletions.
109 changes: 45 additions & 64 deletions src/Simd/SimdBaseSynetConvolution16bNchwGemm.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -98,35 +98,31 @@ namespace Simd
{
const ConvParam& p = _param;
const AlgParam& a = _alg;
//size_t D = DivHi(p.dstC, _alg.F);
//_weight.Resize(a.bufK * a.bufD, true);
//uint16_t* dst = _weight.data;
//for (size_t d = 0; d < D; d++)
//{
// for (size_t k = 0; k < a.bufK; k += 2)
// {
// const float* src = weight + k * p.dstC + d * _alg.F;
// for (size_t f = 0; f < _alg.F; ++f)
// {
// for (size_t i = 0; i < 2; ++i)
// {
// if (d * _alg.F + f < p.dstC && k + i < a.K)
// *(dst++) = Float32ToBFloat16(src[i * p.dstC]);
// else
// *(dst++) = 0;
// }
// src++;
// }
// }
//}
_weight.Resize(a.bufK * a.bufD, true);
uint16_t* dst = _weight.data;
for (size_t mak = 0; mak < a.bufK; mak += a.macroK)
{
size_t macroK = Simd::Min(a.bufK, mak + a.macroK) - mak;
for (size_t d = 0; d < a.bufD; d += 1)
{
const float* src = weight + d * p.dstC + mak;
for (size_t k = 0; k < macroK; k += 1)
{
if (d < p.dstC && mak + k < a.K)
*(dst++) = Float32ToBFloat16(src[k]);
else
*(dst++) = 0;
}
}
}
}

void SynetConvolution16bNchwGemm::Forward(const uint8_t* src, uint8_t* buf8, uint8_t* dst)
{
const ConvParam& p = _param;
const AlgParam& a = _alg;
buf8 = Buffer(buf8);
uint16_t* bufB = _convert ? Allocate<uint16_t>(buf8, a.bufN * a.bufK) : NULL;
uint16_t* bufB = Allocate<uint16_t>(buf8, a.bufN * a.bufK);
float* bufS = a.sumBuf ? Allocate<float>(buf8, a.macroD * a.bufN) : NULL;
for (size_t b = 0; b < p.batch; b += 1)
{
Expand All @@ -143,48 +139,33 @@ namespace Simd
const ConvParam& p = _param;
const AlgParam& a = _alg;
const float* bias = _bias.data, * params = _params.data;

//for (size_t dc = 0; dc < p.dstC; dc += a.macroD)
//{
// size_t macroD = Simd::Min(p.dstC, dc + a.macroD) - dc;
// const uint16_t* weight = _weight.data + dc * a.bufK;
// for (size_t mak = 0; mak < a.K; mak += a.macroK)
// {
// size_t macroK = Simd::Min(a.bufK, mak + a.macroK) - mak;
// for (size_t yBeg = 0; yBeg < dstH;)
// {
// size_t yEnd = Simd::Min(yBeg + a.macroH, dstH);
// size_t bufOffs = (a.macroK < a.bufK || _convert == NULL) ?
// yBeg * (_convert ? AlignHi(p.dstW, a.F) : p.dstW) * a.bufK + (a.reorderType ? mak * a.F : mak) : 0;
// size_t sumOffs = a.macroK < a.bufK ? yBeg * p.dstW * a.macroD : 0;
// size_t dstOffs = yBeg * p.dstW * p.dstC * _elemD;
// if (dc == 0 && mak == 0 && _convert)
// {
// if (a.batch > 1)
// {
// size_t dS = p.srcH * p.srcW * p.srcC * _elemS;
// size_t dB = p.dstH * p.dstW * a.bufK;
// for (size_t b = 0; b < a.batch; ++b)
// _convert(src + b * dS, p, a, 0, p.dstH, buf + b * dB);
// }
// else
// _convert(src, p, a, yBeg, yEnd, buf + bufOffs);
// }
// if (mak + macroK == a.bufK)
// _convolutions[1](buf + bufOffs, p, a, macroD, yEnd - yBeg, macroK, macroK == a.bufK ? 1 : 0,
// weight, bias, params, sum + sumOffs, dst + dstOffs);
// else
// _convolutions[0](buf + bufOffs, p, a, macroD, yEnd - yBeg, macroK, mak == 0 ? 1 : 0,
// weight, bias, params, sum + sumOffs, dst + dstOffs);
// yBeg = yEnd;
// }
// weight += macroK * a.F;
// }
// bias += macroD;
// if (p.activation == ::SimdConvolutionActivationPrelu)
// params += macroD;
// dst += macroD * _elemD;
//}
for (size_t yBeg = 0; yBeg < p.dstH;)
{
size_t yEnd = Simd::Min(yBeg + a.macroH, p.dstH);
if(!_is1x1)
_convert(src, p, a, yBeg, yEnd, 0, p.srcC, buf);
for (size_t mak = 0; mak < a.K; mak += a.macroK)
{
size_t macroK = Simd::Min(a.bufK, mak + a.macroK) - mak;
if (_is1x1)
_convert(src, p, a, yBeg, yEnd, mak, mak + macroK, buf);
size_t bufOffs = _is1x1 ? mak * a.F : 0;
for (size_t dc = 0; dc < p.dstC; dc += a.macroD)
{
size_t macroD = Simd::Min(p.dstC, dc + a.macroD) - dc;
size_t sumOffs = a.macroK < a.bufK ? yBeg * p.dstW * a.macroD : 0;
size_t dstOffs = (dc * p.dstH + yBeg) * p.dstW * _elemD;
const uint16_t* weight = _weight.data + a.bufD * mak + dc * macroK;
if (mak + macroK == a.bufK)
_convolutions[1](weight, p, a, macroD, yEnd - yBeg, macroK, macroK == a.bufK ? 1 : 0,
buf + bufOffs, bias, params, sum + sumOffs, dst + dstOffs);
else
_convolutions[0](weight, p, a, macroD, yEnd - yBeg, macroK, mak == 0 ? 1 : 0,
buf + bufOffs, bias, params, sum + sumOffs, dst + dstOffs);
}
}
yBeg = yEnd;
}
}

bool SynetConvolution16bNchwGemm::Preferable(const ConvParam& p)
Expand Down
2 changes: 1 addition & 1 deletion src/Simd/SimdSynetConvolution16b.h
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Original file line number Diff line number Diff line change
Expand Up @@ -221,7 +221,7 @@ namespace Simd
int reorderType, sumBuf;
};

typedef void(*ConvertPtr)(const uint8_t* src, const ConvParam& p, const AlgParam& a, size_t yBeg, size_t yEnd, uint16_t* dst);
typedef void(*ConvertPtr)(const uint8_t* src, const ConvParam& p, const AlgParam& a, size_t yBeg, size_t yEnd, size_t cBeg, size_t cEnd, uint16_t* dst);

typedef void(*ConvolutionPtr)(const uint16_t* weight, const ConvParam& p, const AlgParam& a, size_t dstC, size_t dstH,
size_t srcC, int zero, const uint16_t* src, const float* bias, const float* params, float* sum, uint8_t* dst);
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