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composable_kernel/driver/include/host_conv.hpp
Chao Liu 625838def0 added tuple
2019-09-06 18:07:56 -05:00

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#pragma once
#include "tensor.hpp"
#include "common_header.hpp"
#include "ConstantTensorDescriptor.hpp"
// this is ugly, only for 4d
template <class TConstTensorDesc>
void ostream_ConstantTensorDescriptor(TConstTensorDesc, std::ostream& os = std::cout)
{
using namespace ck;
static_assert(TConstTensorDesc::nDim == 4, "nDim is not 4");
constexpr auto I0 = Number<0>{};
constexpr auto I1 = Number<1>{};
constexpr auto I2 = Number<2>{};
constexpr auto I3 = Number<3>{};
constexpr auto desc = TConstTensorDesc{};
os << "Lengths: {" << desc.GetLength(I0) << ", " << desc.GetLength(I1) << ", "
<< desc.GetLength(I2) << ", " << desc.GetLength(I3) << "}, "
<< "Strides: {" << desc.GetStride(I0) << ", " << desc.GetStride(I1) << ", "
<< desc.GetStride(I2) << ", " << desc.GetStride(I3) << "}" << std::endl;
}
// this is ugly, only for 4d
template <class TConstTensorDesc>
auto make_TensorDescriptor(TConstTensorDesc)
{
using namespace ck;
static_assert(TConstTensorDesc::nDim == 4, "nDim is not 4");
constexpr auto I0 = Number<0>{};
constexpr auto I1 = Number<1>{};
constexpr auto I2 = Number<2>{};
constexpr auto I3 = Number<3>{};
constexpr auto desc = TConstTensorDesc{};
std::initializer_list<index_t> lengths = {
desc.GetLength(I0), desc.GetLength(I1), desc.GetLength(I2), desc.GetLength(I3)};
std::initializer_list<index_t> strides = {
desc.GetStride(I0), desc.GetStride(I1), desc.GetStride(I2), desc.GetStride(I3)};
return TensorDescriptor(lengths, strides);
}
template <class TIn,
class TWei,
class TOut,
class ConvStrides,
class ConvDilations,
class LowerPads,
class UpperPads>
void host_direct_convolution(const Tensor<TIn>& in_nchw,
const Tensor<TWei>& wei_kcyx,
Tensor<TOut>& out_nkhw,
ConvStrides,
ConvDilations,
LowerPads,
UpperPads)
{
using namespace ck;
index_t h_pad_low = LowerPads{}.Get(Number<0>{});
index_t w_pad_low = LowerPads{}.Get(Number<1>{});
auto f = [&](auto n, auto k, auto ho, auto wo) {
double v = 0;
for(int c = 0; c < wei_kcyx.mDesc.GetLengths()[1]; ++c)
{
for(int y = 0; y < wei_kcyx.mDesc.GetLengths()[2]; ++y)
{
int hi = ho * ConvStrides{}[0] + y * ConvDilations{}[0] - h_pad_low;
for(int x = 0; x < wei_kcyx.mDesc.GetLengths()[3]; ++x)
{
int wi = wo * ConvStrides{}[1] + x * ConvDilations{}[1] - w_pad_low;
if(hi >= 0 && hi < in_nchw.mDesc.GetLengths()[2] && wi >= 0 &&
wi < in_nchw.mDesc.GetLengths()[3])
{
v += double(in_nchw(n, c, hi, wi)) * double(wei_kcyx(k, c, y, x));
}
}
}
}
out_nkhw(n, k, ho, wo) = v;
};
auto f_par = make_ParallelTensorFunctor(f,
out_nkhw.mDesc.GetLengths()[0],
out_nkhw.mDesc.GetLengths()[1],
out_nkhw.mDesc.GetLengths()[2],
out_nkhw.mDesc.GetLengths()[3]);
f_par(std::thread::hardware_concurrency());
}
template <class TIn, class TWei, class TOut, class LowerPads, class UpperPads>
void host_winograd_3x3_convolution(const Tensor<TIn>& in_nchw,
const Tensor<TWei>& wei_kcyx,
Tensor<TOut>& out_nkhw,
LowerPads,
UpperPads)
{
using namespace ck;
constexpr std::size_t HoPerTile = 2;
constexpr std::size_t WoPerTile = 2;
std::size_t N = in_nchw.mDesc.GetLengths()[0];
std::size_t C = in_nchw.mDesc.GetLengths()[1];
std::size_t HI = in_nchw.mDesc.GetLengths()[2];
std::size_t WI = in_nchw.mDesc.GetLengths()[3];
std::size_t K = wei_kcyx.mDesc.GetLengths()[0];
std::size_t Y = wei_kcyx.mDesc.GetLengths()[2];
std::size_t X = wei_kcyx.mDesc.GetLengths()[3];
std::size_t HO = out_nkhw.mDesc.GetLengths()[2];
std::size_t WO = out_nkhw.mDesc.GetLengths()[3];
index_t h_pad_low = LowerPads{}.Get(Number<0>{});
index_t w_pad_low = LowerPads{}.Get(Number<1>{});
std::size_t HiPerTile = HoPerTile + Y - 1;
std::size_t WiPerTile = WoPerTile + X - 1;
std::size_t HTile = (HO + HoPerTile - 1) / HoPerTile;
std::size_t WTile = (WO + WoPerTile - 1) / WoPerTile;
Tensor<double> in_hold({N, C, HTile, WTile, HiPerTile, WiPerTile});
Tensor<double> in_transform({N, C, HTile, WTile, HiPerTile, WiPerTile});
Tensor<double> wei_transform({K, C, HiPerTile, WiPerTile});
Tensor<double> out_transform({N, K, HTile, WTile, HiPerTile, HiPerTile});
Tensor<double> out_hold({N, K, HTile, WTile, HoPerTile, WoPerTile});
auto f_in_hold = [&](auto n, auto c, auto htile, auto wtile) {
for(int j = 0; j < HiPerTile; ++j)
{
int hi = HoPerTile * htile + j - h_pad_low;
for(int i = 0; i < WiPerTile; ++i)
{
int wi = WoPerTile * wtile + i - w_pad_low;
if(hi >= 0 && hi < in_nchw.mDesc.GetLengths()[2] && wi >= 0 &&
wi < in_nchw.mDesc.GetLengths()[3])
{
in_hold(n, c, htile, wtile, j, i) = in_nchw(n, c, hi, wi);
}
else
{
in_hold(n, c, htile, wtile, j, i) = TIn(0);
}
}
}
};
auto f_in_transform = [&](auto n, auto c, auto htile, auto wtile) {
in_transform(n, c, htile, wtile, 0, 0) =
in_hold(n, c, htile, wtile, 0, 0) - in_hold(n, c, htile, wtile, 0, 2) -
in_hold(n, c, htile, wtile, 2, 0) + in_hold(n, c, htile, wtile, 2, 2);
in_transform(n, c, htile, wtile, 0, 1) =
in_hold(n, c, htile, wtile, 0, 1) + in_hold(n, c, htile, wtile, 0, 2) -
in_hold(n, c, htile, wtile, 2, 1) - in_hold(n, c, htile, wtile, 2, 2);
in_transform(n, c, htile, wtile, 0, 2) =
-in_hold(n, c, htile, wtile, 0, 1) + in_hold(n, c, htile, wtile, 0, 2) +
in_hold(n, c, htile, wtile, 2, 1) - in_hold(n, c, htile, wtile, 2, 2);
in_transform(n, c, htile, wtile, 0, 3) =
in_hold(n, c, htile, wtile, 0, 1) - in_hold(n, c, htile, wtile, 0, 3) -
in_hold(n, c, htile, wtile, 2, 1) + in_hold(n, c, htile, wtile, 2, 3);
in_transform(n, c, htile, wtile, 1, 0) =
in_hold(n, c, htile, wtile, 1, 0) - in_hold(n, c, htile, wtile, 1, 2) +
in_hold(n, c, htile, wtile, 2, 0) - in_hold(n, c, htile, wtile, 2, 2);
in_transform(n, c, htile, wtile, 1, 1) =
in_hold(n, c, htile, wtile, 1, 1) + in_hold(n, c, htile, wtile, 1, 2) +
in_hold(n, c, htile, wtile, 2, 1) + in_hold(n, c, htile, wtile, 2, 2);
in_transform(n, c, htile, wtile, 1, 2) =
-in_hold(n, c, htile, wtile, 1, 1) + in_hold(n, c, htile, wtile, 1, 2) -
in_hold(n, c, htile, wtile, 2, 1) + in_hold(n, c, htile, wtile, 2, 2);
in_transform(n, c, htile, wtile, 1, 3) =
in_hold(n, c, htile, wtile, 1, 1) - in_hold(n, c, htile, wtile, 1, 3) +
in_hold(n, c, htile, wtile, 2, 1) - in_hold(n, c, htile, wtile, 2, 3);
in_transform(n, c, htile, wtile, 2, 0) =
-in_hold(n, c, htile, wtile, 1, 0) + in_hold(n, c, htile, wtile, 1, 2) +
in_hold(n, c, htile, wtile, 2, 0) - in_hold(n, c, htile, wtile, 2, 2);
in_transform(n, c, htile, wtile, 2, 1) =
-in_hold(n, c, htile, wtile, 1, 1) - in_hold(n, c, htile, wtile, 1, 2) +
in_hold(n, c, htile, wtile, 2, 1) + in_hold(n, c, htile, wtile, 2, 2);
in_transform(n, c, htile, wtile, 2, 2) =
in_hold(n, c, htile, wtile, 1, 1) - in_hold(n, c, htile, wtile, 1, 2) -
in_hold(n, c, htile, wtile, 2, 1) + in_hold(n, c, htile, wtile, 2, 2);
in_transform(n, c, htile, wtile, 2, 3) =
-in_hold(n, c, htile, wtile, 1, 1) + in_hold(n, c, htile, wtile, 1, 3) +
in_hold(n, c, htile, wtile, 2, 1) - in_hold(n, c, htile, wtile, 2, 3);
in_transform(n, c, htile, wtile, 3, 0) =
in_hold(n, c, htile, wtile, 1, 0) - in_hold(n, c, htile, wtile, 1, 2) -
in_hold(n, c, htile, wtile, 3, 0) + in_hold(n, c, htile, wtile, 3, 2);
in_transform(n, c, htile, wtile, 3, 1) =
in_hold(n, c, htile, wtile, 1, 1) + in_hold(n, c, htile, wtile, 1, 2) -
in_hold(n, c, htile, wtile, 3, 1) - in_hold(n, c, htile, wtile, 3, 2);
in_transform(n, c, htile, wtile, 3, 2) =
-in_hold(n, c, htile, wtile, 1, 1) + in_hold(n, c, htile, wtile, 1, 2) +
in_hold(n, c, htile, wtile, 3, 1) - in_hold(n, c, htile, wtile, 3, 2);
in_transform(n, c, htile, wtile, 3, 3) =
in_hold(n, c, htile, wtile, 1, 1) - in_hold(n, c, htile, wtile, 1, 3) -
in_hold(n, c, htile, wtile, 3, 1) + in_hold(n, c, htile, wtile, 3, 3);
};
auto f_wei_transform = [&](auto k, auto c) {
wei_transform(k, c, 0, 0) = double(wei_kcyx(k, c, 0, 0));
wei_transform(k, c, 0, 1) = 0.5 * double(wei_kcyx(k, c, 0, 0)) +
0.5 * double(wei_kcyx(k, c, 0, 1)) +
0.5 * double(wei_kcyx(k, c, 0, 2));
wei_transform(k, c, 0, 2) = 0.5 * double(wei_kcyx(k, c, 0, 0)) -
0.5 * double(wei_kcyx(k, c, 0, 1)) +
0.5 * double(wei_kcyx(k, c, 0, 2));
wei_transform(k, c, 0, 3) = double(wei_kcyx(k, c, 0, 2));
wei_transform(k, c, 1, 0) = 0.5 * double(wei_kcyx(k, c, 0, 0)) +
0.5 * double(wei_kcyx(k, c, 1, 0)) +
0.5 * double(wei_kcyx(k, c, 2, 0));
wei_transform(k, c, 1, 1) =
0.25 * double(wei_kcyx(k, c, 0, 0)) + 0.25 * double(wei_kcyx(k, c, 0, 1)) +
0.25 * double(wei_kcyx(k, c, 0, 2)) + 0.25 * double(wei_kcyx(k, c, 1, 0)) +
0.25 * double(wei_kcyx(k, c, 1, 1)) + 0.25 * double(wei_kcyx(k, c, 1, 2)) +
0.25 * double(wei_kcyx(k, c, 2, 0)) + 0.25 * double(wei_kcyx(k, c, 2, 1)) +
0.25 * double(wei_kcyx(k, c, 2, 2));
wei_transform(k, c, 1, 2) =
0.25 * double(wei_kcyx(k, c, 0, 0)) - 0.25 * double(wei_kcyx(k, c, 0, 1)) +
0.25 * double(wei_kcyx(k, c, 0, 2)) + 0.25 * double(wei_kcyx(k, c, 1, 0)) -
0.25 * double(wei_kcyx(k, c, 1, 1)) + 0.25 * double(wei_kcyx(k, c, 1, 2)) +
0.25 * double(wei_kcyx(k, c, 2, 0)) - 0.25 * double(wei_kcyx(k, c, 2, 1)) +
0.25 * double(wei_kcyx(k, c, 2, 2));
wei_transform(k, c, 1, 3) = 0.5 * double(wei_kcyx(k, c, 0, 2)) +
0.5 * double(wei_kcyx(k, c, 1, 2)) +
0.5 * double(wei_kcyx(k, c, 2, 2));
wei_transform(k, c, 2, 0) = 0.5 * double(wei_kcyx(k, c, 0, 0)) -
0.5 * double(wei_kcyx(k, c, 1, 0)) +
0.5 * double(wei_kcyx(k, c, 2, 0));
wei_transform(k, c, 2, 1) =
0.25 * double(wei_kcyx(k, c, 0, 0)) + 0.25 * double(wei_kcyx(k, c, 0, 1)) +
0.25 * double(wei_kcyx(k, c, 0, 2)) - 0.25 * double(wei_kcyx(k, c, 1, 0)) -
0.25 * double(wei_kcyx(k, c, 1, 1)) - 0.25 * double(wei_kcyx(k, c, 1, 2)) +
0.25 * double(wei_kcyx(k, c, 2, 0)) + 0.25 * double(wei_kcyx(k, c, 2, 1)) +
0.25 * double(wei_kcyx(k, c, 2, 2));
wei_transform(k, c, 2, 2) =
0.25 * double(wei_kcyx(k, c, 0, 0)) - 0.25 * double(wei_kcyx(k, c, 0, 1)) +
0.25 * double(wei_kcyx(k, c, 0, 2)) - 0.25 * double(wei_kcyx(k, c, 1, 0)) +
0.25 * double(wei_kcyx(k, c, 1, 1)) - 0.25 * double(wei_kcyx(k, c, 1, 2)) +
0.25 * double(wei_kcyx(k, c, 2, 0)) - 0.25 * double(wei_kcyx(k, c, 2, 1)) +
0.25 * double(wei_kcyx(k, c, 2, 2));
wei_transform(k, c, 2, 3) = 0.5 * double(wei_kcyx(k, c, 0, 2)) -
0.5 * double(wei_kcyx(k, c, 1, 2)) +
0.5 * double(wei_kcyx(k, c, 2, 2));
wei_transform(k, c, 3, 0) = double(wei_kcyx(k, c, 2, 0));
wei_transform(k, c, 3, 1) = 0.5 * double(wei_kcyx(k, c, 2, 0)) +
0.5 * double(wei_kcyx(k, c, 2, 1)) +
0.5 * double(wei_kcyx(k, c, 2, 2));
wei_transform(k, c, 3, 2) = 0.5 * double(wei_kcyx(k, c, 2, 0)) -
0.5 * double(wei_kcyx(k, c, 2, 1)) +
0.5 * double(wei_kcyx(k, c, 2, 2));
wei_transform(k, c, 3, 3) = double(wei_kcyx(k, c, 2, 2));
};
auto f_out_transform = [&](auto n, auto k, auto htile, auto wtile) {
for(int j = 0; j < HiPerTile; ++j)
{
for(int i = 0; i < WiPerTile; ++i)
{
double v = 0;
for(int c = 0; c < C; ++c)
{
v += in_transform(n, c, htile, wtile, j, i) * wei_transform(k, c, j, i);
}
out_transform(n, k, htile, wtile, j, i) = v;
}
}
};
auto f_out_hold = [&](auto n, auto k, auto htile, auto wtile) {
out_hold(n, k, htile, wtile, 0, 0) =
out_transform(n, k, htile, wtile, 0, 0) + out_transform(n, k, htile, wtile, 0, 1) +
out_transform(n, k, htile, wtile, 0, 2) + out_transform(n, k, htile, wtile, 1, 0) +
out_transform(n, k, htile, wtile, 1, 1) + out_transform(n, k, htile, wtile, 1, 2) +
out_transform(n, k, htile, wtile, 2, 0) + out_transform(n, k, htile, wtile, 2, 1) +
out_transform(n, k, htile, wtile, 2, 2);
out_hold(n, k, htile, wtile, 0, 1) =
out_transform(n, k, htile, wtile, 0, 1) - out_transform(n, k, htile, wtile, 0, 2) -
out_transform(n, k, htile, wtile, 0, 3) + out_transform(n, k, htile, wtile, 1, 1) -
out_transform(n, k, htile, wtile, 1, 2) - out_transform(n, k, htile, wtile, 1, 3) +
out_transform(n, k, htile, wtile, 2, 1) - out_transform(n, k, htile, wtile, 2, 2) -
out_transform(n, k, htile, wtile, 2, 3);
out_hold(n, k, htile, wtile, 1, 0) =
out_transform(n, k, htile, wtile, 1, 0) + out_transform(n, k, htile, wtile, 1, 1) +
out_transform(n, k, htile, wtile, 1, 2) - out_transform(n, k, htile, wtile, 2, 0) -
out_transform(n, k, htile, wtile, 2, 1) - out_transform(n, k, htile, wtile, 2, 2) -
out_transform(n, k, htile, wtile, 3, 0) - out_transform(n, k, htile, wtile, 3, 1) -
out_transform(n, k, htile, wtile, 3, 2);
out_hold(n, k, htile, wtile, 1, 1) =
out_transform(n, k, htile, wtile, 1, 1) - out_transform(n, k, htile, wtile, 1, 2) -
out_transform(n, k, htile, wtile, 1, 3) - out_transform(n, k, htile, wtile, 2, 1) +
out_transform(n, k, htile, wtile, 2, 2) + out_transform(n, k, htile, wtile, 2, 3) -
out_transform(n, k, htile, wtile, 3, 1) + out_transform(n, k, htile, wtile, 3, 2) +
out_transform(n, k, htile, wtile, 3, 3);
};
auto f_out = [&](auto n, auto k, auto htile, auto wtile) {
for(int j = 0; j < HoPerTile; ++j)
{
std::size_t ho = HoPerTile * htile + j;
for(int i = 0; i < WoPerTile; ++i)
{
std::size_t wo = WoPerTile * wtile + i;
out_nkhw(n, k, ho, wo) = out_hold(n, k, htile, wtile, j, i);
}
}
};
std::size_t num_thread = std::thread::hardware_concurrency();
make_ParallelTensorFunctor(f_in_hold, N, C, HTile, WTile)(num_thread);
make_ParallelTensorFunctor(f_in_transform, N, C, HTile, WTile)(num_thread);
make_ParallelTensorFunctor(f_wei_transform, K, C)(num_thread);
make_ParallelTensorFunctor(f_out_transform, N, K, HTile, WTile)(num_thread);
make_ParallelTensorFunctor(f_out_hold, N, K, HTile, WTile)(num_thread);
make_ParallelTensorFunctor(f_out, N, K, HTile, WTile)(num_thread);
}
template <class T>
void check_error(const Tensor<T>& ref, const Tensor<T>& result)
{
float error = 0;
float max_diff = -1;
float ref_value = 0, result_value = 0;
for(int i = 0; i < ref.mData.size(); ++i)
{
error += std::abs(double(ref.mData[i]) - double(result.mData[i]));
float diff = std::abs(double(ref.mData[i]) - double(result.mData[i]));
if(max_diff < diff)
{
max_diff = diff;
ref_value = ref.mData[i];
result_value = result.mData[i];
}
}
std::cout << "error: " << error << std::endl;
std::cout << "max_diff: " << max_diff << ", " << ref_value << ", " << result_value << std::endl;
}
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