GitOrigin-RevId: 93c9b212f4
tags/v1.0.0-rc1
@@ -36,8 +36,9 @@ all: ${PARAM_DEFS} ${ELEMWISE_IMPL} ${CUDA_CONV_IMPL} | |||||
../src/cuda/elemwise_multi_type/kimpl: gen_elemwise_multi_type_kern_impls.py | ../src/cuda/elemwise_multi_type/kimpl: gen_elemwise_multi_type_kern_impls.py | ||||
./$^ --type cuda $@ | ./$^ --type cuda $@ | ||||
../src/cuda/conv_bias/int8/kimpl: gen_cuda_conv_bias_kern_impls.py | |||||
./$^ --type dp4a $@ | |||||
../src/cuda/conv_bias/int8/kimpl: gen_cuda_conv_bias_kern_impls.py gen_cutlass_conv_bias_kern_impls.py | |||||
./gen_cuda_conv_bias_kern_impls.py --type dp4a $@ | |||||
./gen_cutlass_conv_bias_kern_impls.py --type dp4a $@ | |||||
../src/cuda/conv_bias/int8_imma/kimpl: gen_cuda_conv_bias_kern_impls.py gen_cutlass_conv_bias_kern_impls.py | ../src/cuda/conv_bias/int8_imma/kimpl: gen_cuda_conv_bias_kern_impls.py gen_cutlass_conv_bias_kern_impls.py | ||||
./gen_cuda_conv_bias_kern_impls.py --type imma $@ | ./gen_cuda_conv_bias_kern_impls.py --type imma $@ | ||||
@@ -91,7 +91,10 @@ ConvBiasForwardImpl::AlgoPack::AlgoPack() { | |||||
} | } | ||||
#endif | #endif | ||||
#endif | #endif | ||||
all_algos.push_back(&int8_nchw4_dotprod); | |||||
fill_dp4a_algos(); | |||||
for (auto&& algo : int8_nchw4_dotprod) { | |||||
all_algos.push_back(&algo); | |||||
} | |||||
all_algos.push_back(&int8_chwn4_dotprod); | all_algos.push_back(&int8_chwn4_dotprod); | ||||
for (size_t i = all_algo_size; i < all_algos.size(); ++i) { | for (size_t i = all_algo_size; i < all_algos.size(); ++i) { | ||||
non_cudnn_algos.push_back(all_algos[i]); | non_cudnn_algos.push_back(all_algos[i]); | ||||
@@ -253,6 +256,20 @@ void ConvBiasForwardImpl::AlgoPack::fill_imma_algos() { | |||||
} | } | ||||
#endif | #endif | ||||
void ConvBiasForwardImpl::AlgoPack::fill_dp4a_algos() { | |||||
using AlgoParam = AlgoInt8NCHW4DotProdImplicitGemm::AlgoParam; | |||||
int8_nchw4_dotprod.emplace_back(AlgoParam{128, 128, 32, 64, 32, 32}); | |||||
int8_nchw4_dotprod.emplace_back(AlgoParam{128, 64, 32, 64, 32, 32}); | |||||
int8_nchw4_dotprod.emplace_back(AlgoParam{64, 128, 32, 64, 32, 32}); | |||||
int8_nchw4_dotprod.emplace_back(AlgoParam{32, 128, 32, 32, 64, 32}); | |||||
int8_nchw4_dotprod.emplace_back(AlgoParam{128, 32, 32, 64, 32, 32}); | |||||
int8_nchw4_dotprod.emplace_back(AlgoParam{64, 64, 32, 64, 32, 32}); | |||||
int8_nchw4_dotprod.emplace_back(AlgoParam{32, 64, 32, 32, 64, 32}); | |||||
int8_nchw4_dotprod.emplace_back(AlgoParam{64, 32, 32, 64, 32, 32}); | |||||
int8_nchw4_dotprod.emplace_back(AlgoParam{32, 32, 32, 32, 32, 32}); | |||||
int8_nchw4_dotprod.emplace_back(AlgoParam{16, 64, 8, 16, 64, 8}); | |||||
} | |||||
ConvBiasForwardImpl::AlgoBase* | ConvBiasForwardImpl::AlgoBase* | ||||
ConvBiasForwardImpl::AlgoPack::cudnn_conv_from_enum( | ConvBiasForwardImpl::AlgoPack::cudnn_conv_from_enum( | ||||
@@ -386,18 +386,39 @@ public: | |||||
class ConvBiasForwardImpl::AlgoInt8NCHW4DotProdImplicitGemm final | class ConvBiasForwardImpl::AlgoInt8NCHW4DotProdImplicitGemm final | ||||
: public AlgoBase { | : public AlgoBase { | ||||
public: | public: | ||||
AlgoInt8NCHW4DotProdImplicitGemm() = default; | |||||
struct AlgoParam { | |||||
int threadblock_m; | |||||
int threadblock_n; | |||||
int threadblock_k; | |||||
int warp_m; | |||||
int warp_n; | |||||
int warp_k; | |||||
std::string to_string() { | |||||
/// default algorithm | |||||
if (threadblock_m == 128 && threadblock_n == 128 && | |||||
threadblock_k == 32 && warp_m == 32 && warp_n == 64 && | |||||
warp_k == 32) { | |||||
return ""; | |||||
} | |||||
return ssprintf("_%dX%dX%d_%dX%dX%d", threadblock_m, threadblock_n, | |||||
threadblock_k, warp_m, warp_n, warp_k); | |||||
} | |||||
}; | |||||
AlgoInt8NCHW4DotProdImplicitGemm(AlgoParam algo_param) | |||||
: m_algo_param{algo_param}, | |||||
m_name{ssprintf("INT8_NCHW4_DOTPROD_IMPLICIT_GEMM%s", | |||||
m_algo_param.to_string().c_str())} {} | |||||
bool is_available(const SizeArgs& args) const override; | bool is_available(const SizeArgs& args) const override; | ||||
size_t get_workspace_in_bytes(const SizeArgs& args) const override; | size_t get_workspace_in_bytes(const SizeArgs& args) const override; | ||||
void exec(const ExecArgs& args) const override; | void exec(const ExecArgs& args) const override; | ||||
const char* name() const override { | |||||
return "INT8_NCHW4_DOTPROD_IMPLICIT_GEMM"; | |||||
} | |||||
const char* name() const override { return m_name.c_str(); } | |||||
bool is_reproducible() const override { return true; } | bool is_reproducible() const override { return true; } | ||||
private: | private: | ||||
WorkspaceBundle get_workspace_bundle(dt_byte* raw_ptr, | WorkspaceBundle get_workspace_bundle(dt_byte* raw_ptr, | ||||
const SizeArgs& args) const; | const SizeArgs& args) const; | ||||
AlgoParam m_algo_param; | |||||
std::string m_name; | |||||
}; | }; | ||||
#if CUDA_VERSION >= 10000 | #if CUDA_VERSION >= 10000 | ||||
@@ -578,7 +599,7 @@ public: | |||||
AlgoMatmul8x8x32 matmul8x8x32; | AlgoMatmul8x8x32 matmul8x8x32; | ||||
AlgoBatchedMatmul batched_matmul; | AlgoBatchedMatmul batched_matmul; | ||||
Algo1x1 a1x1; | Algo1x1 a1x1; | ||||
AlgoInt8NCHW4DotProdImplicitGemm int8_nchw4_dotprod; | |||||
std::vector<AlgoInt8NCHW4DotProdImplicitGemm> int8_nchw4_dotprod; | |||||
AlgoInt8CHWN4DotProdImplicitGemm int8_chwn4_dotprod; | AlgoInt8CHWN4DotProdImplicitGemm int8_chwn4_dotprod; | ||||
#if CUDA_VERSION >= 10000 | #if CUDA_VERSION >= 10000 | ||||
AlgoQUInt4x4x32WMMA wmma_quint4x4x32; | AlgoQUInt4x4x32WMMA wmma_quint4x4x32; | ||||
@@ -605,6 +626,7 @@ private: | |||||
void fill_imma_algos(); | void fill_imma_algos(); | ||||
#endif | #endif | ||||
void fill_cudnn_algos(); | void fill_cudnn_algos(); | ||||
void fill_dp4a_algos(); | |||||
}; | }; | ||||
} // namespace cuda | } // namespace cuda | ||||
@@ -19,7 +19,6 @@ | |||||
#endif | #endif | ||||
#include "src/common/opr_param_defs_enumv.cuh" | #include "src/common/opr_param_defs_enumv.cuh" | ||||
#include "src/cuda/conv_bias/cutlass_convolution_wrapper.cuh" | #include "src/cuda/conv_bias/cutlass_convolution_wrapper.cuh" | ||||
#pragma GCC diagnostic pop | #pragma GCC diagnostic pop | ||||
using namespace megdnn; | using namespace megdnn; | ||||
@@ -149,4 +148,130 @@ INST(true); | |||||
INST(false); | INST(false); | ||||
#undef INST | #undef INST | ||||
#if MEGDNN_TEGRA_X1 | |||||
template <bool NeedLoadFromConstMem> | |||||
void megdnn::cuda::cutlass_wrapper:: | |||||
do_conv_bias_int8_implicit_gemm_dp4a_ncdiv4hw4( | |||||
const int8_t* /* d_src */, const int8_t* /* d_filter */, | |||||
const int32_t* /* d_bias */, const int8_t* /* d_z */, | |||||
int8_t* /* d_dst */, int* /* workspace */, | |||||
const convolution::ConvParam& /* param */, | |||||
uint32_t /* nonlinear_mode */, float /* alpha */, | |||||
float /* beta */, float /* gamma */, float /* scale */, | |||||
const GemmCoord& /* threadblock_shape */, | |||||
const GemmCoord& /* warp_shape */, cudaStream_t /* stream */) {} | |||||
#else | |||||
template <bool NeedLoadFromConstMem> | |||||
void megdnn::cuda::cutlass_wrapper:: | |||||
do_conv_bias_int8_implicit_gemm_dp4a_ncdiv4hw4( | |||||
const int8_t* d_src, const int8_t* d_filter, | |||||
const int32_t* d_bias, const int8_t* d_z, int8_t* d_dst, | |||||
int* workspace, const convolution::ConvParam& param, | |||||
uint32_t nonlinear_mode, float alpha, float beta, float gamma, | |||||
float scale, const GemmCoord& threadblock_shape, | |||||
const GemmCoord& warp_shape, cudaStream_t stream) { | |||||
#define DISPATCH_KERNEL_WITH_TILE_SHAPE(threadblock_m_, threadblock_n_, \ | |||||
threadblock_k_, warp_m_, warp_n_, \ | |||||
warp_k_, aligned_) \ | |||||
if (threadblock_shape.m() == threadblock_m_ && \ | |||||
threadblock_shape.n() == threadblock_n_ && \ | |||||
threadblock_shape.k() == threadblock_k_ && \ | |||||
warp_shape.m() == warp_m_ && warp_shape.n() == warp_n_ && \ | |||||
warp_shape.k() == warp_k_) { \ | |||||
using ThreadBlockShape = \ | |||||
cutlass::gemm::GemmShape<threadblock_m_, threadblock_n_, \ | |||||
threadblock_k_>; \ | |||||
using WarpShape = cutlass::gemm::GemmShape<warp_m_, warp_n_, warp_k_>; \ | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; \ | |||||
using Convolution = cutlass::convolution::device::Convolution< \ | |||||
int8_t, cutlass::layout::TensorNCxHWx<4>, int8_t, \ | |||||
cutlass::layout::TensorCxRSKx<4>, ElementOutput, \ | |||||
cutlass::layout::TensorNCxHWx<4>, int32_t, \ | |||||
cutlass::layout::TensorNCxHWx<4>, int32_t, \ | |||||
cutlass::convolution::ConvType::kConvolution, \ | |||||
cutlass::arch::OpClassSimt, cutlass::arch::Sm61, \ | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, \ | |||||
cutlass::convolution::threadblock:: \ | |||||
ConvolutionNCxHWxThreadblockSwizzle< \ | |||||
cutlass::convolution::ConvType::kConvolution>, \ | |||||
2, 4, aligned_, NeedLoadFromConstMem>; \ | |||||
typename Convolution::ConvolutionParameter conv_param{ \ | |||||
param.n, param.ci, param.co, param.hi, param.wi, \ | |||||
param.fh, param.fw, param.ho, param.wo, param.sh, \ | |||||
param.sw, param.ph, param.pw, 1, 1}; \ | |||||
return cutlass_convolution_wrapper<Convolution>( \ | |||||
d_src, d_filter, d_bias, d_z, d_dst, workspace, conv_param, \ | |||||
epilogue, stream); \ | |||||
} | |||||
#define DISPATCH_KERNEL \ | |||||
DISPATCH_KERNEL_WITH_TILE_SHAPE(128, 128, 32, 64, 32, 32, 16); \ | |||||
DISPATCH_KERNEL_WITH_TILE_SHAPE(128, 64, 32, 64, 32, 32, 16); \ | |||||
DISPATCH_KERNEL_WITH_TILE_SHAPE(64, 128, 32, 64, 32, 32, 16); \ | |||||
DISPATCH_KERNEL_WITH_TILE_SHAPE(128, 32, 32, 64, 32, 32, 16); \ | |||||
DISPATCH_KERNEL_WITH_TILE_SHAPE(32, 128, 32, 32, 64, 32, 16); \ | |||||
DISPATCH_KERNEL_WITH_TILE_SHAPE(64, 64, 32, 64, 32, 32, 16); \ | |||||
DISPATCH_KERNEL_WITH_TILE_SHAPE(32, 64, 32, 32, 64, 32, 16); \ | |||||
DISPATCH_KERNEL_WITH_TILE_SHAPE(64, 32, 32, 64, 32, 32, 16); \ | |||||
DISPATCH_KERNEL_WITH_TILE_SHAPE(32, 32, 32, 32, 32, 32, 16); \ | |||||
DISPATCH_KERNEL_WITH_TILE_SHAPE(16, 64, 8, 16, 64, 8, 4); \ | |||||
megdnn_assert(false, \ | |||||
"unsupported threadblock shape (%dx%dx%d) and warp shape " \ | |||||
"(%dx%dx%d)", \ | |||||
threadblock_shape.m(), threadblock_shape.n(), \ | |||||
threadblock_shape.k(), warp_shape.m(), warp_shape.n(), \ | |||||
warp_shape.k()); | |||||
using ElementOutput = int8_t; | |||||
using ElementAccumulator = int32_t; | |||||
using ElementBias = int32_t; | |||||
using ElementCompute = float; | |||||
using NonlineMode = megdnn::param_enumv::ConvBias::NonlineMode; | |||||
switch (nonlinear_mode) { | |||||
case NonlineMode::IDENTITY: { | |||||
using EpilogueOp = | |||||
cutlass::epilogue::thread::BiasAddLinearCombinationClamp< | |||||
ElementOutput, 4, ElementAccumulator, ElementBias, | |||||
ElementCompute>; | |||||
typename EpilogueOp::Params epilogue{alpha, beta, gamma}; | |||||
DISPATCH_KERNEL; | |||||
} | |||||
case NonlineMode::RELU: { | |||||
using EpilogueOp = cutlass::epilogue::thread:: | |||||
BiasAddLinearCombinationReluClamp< | |||||
ElementOutput, 4, ElementAccumulator, ElementBias, | |||||
ElementCompute>; | |||||
typename EpilogueOp::Params epilogue{alpha, beta, gamma, 0}; | |||||
DISPATCH_KERNEL; | |||||
} | |||||
case NonlineMode::H_SWISH: { | |||||
using EpilogueOp = cutlass::epilogue::thread:: | |||||
BiasAddLinearCombinationHSwishClamp< | |||||
ElementOutput, 4, ElementAccumulator, ElementBias, | |||||
ElementCompute>; | |||||
typename EpilogueOp::Params epilogue{alpha, beta, gamma, scale}; | |||||
DISPATCH_KERNEL; | |||||
} | |||||
default: | |||||
megdnn_assert(false, | |||||
"unsupported nonlinear mode for conv bias operator"); | |||||
} | |||||
#undef DISPATCH_KERNEL_WITH_TILE_SHAPE | |||||
#undef DISPATCH_KERNEL | |||||
} | |||||
#endif | |||||
#define INST(need_load_from_const_mem) \ | |||||
template void megdnn::cuda::cutlass_wrapper:: \ | |||||
do_conv_bias_int8_implicit_gemm_dp4a_ncdiv4hw4< \ | |||||
need_load_from_const_mem>( \ | |||||
const int8_t* d_src, const int8_t* d_filter, \ | |||||
const int32_t* d_bias, const int8_t* d_z, int8_t* d_dst, \ | |||||
int* workspace, const convolution::ConvParam& param, \ | |||||
uint32_t nonlinear_mode, float alpha, float beta, \ | |||||
float gamma, float scale, \ | |||||
const GemmCoord& threadblock_shape, \ | |||||
const GemmCoord& warp_shape, cudaStream_t stream); | |||||
INST(true); | |||||
INST(false); | |||||
#undef INST | |||||
// vim: syntax=cuda.doxygen | // vim: syntax=cuda.doxygen |
@@ -37,6 +37,15 @@ void do_conv_bias_int8_implicit_gemm_imma_ncdiv32hw32( | |||||
const GemmCoord& threadblock_shape, const GemmCoord& warp_shape, | const GemmCoord& threadblock_shape, const GemmCoord& warp_shape, | ||||
cudaStream_t stream); | cudaStream_t stream); | ||||
template <bool NeedLoadFromConstMem> | |||||
void do_conv_bias_int8_implicit_gemm_dp4a_ncdiv4hw4( | |||||
const int8_t* d_src, const int8_t* d_filter, const int32_t* d_bias, | |||||
const int8_t* d_z, int8_t* d_dst, int* workspace, | |||||
const convolution::ConvParam& param, uint32_t nonlinear_mode, | |||||
float alpha, float beta, float gamma, float scale, | |||||
const GemmCoord& threadblock_shape, const GemmCoord& warp_shape, | |||||
cudaStream_t stream); | |||||
} // namespace cutlass_wrapper | } // namespace cutlass_wrapper | ||||
} // namespace cuda | } // namespace cuda | ||||
} // namespace megdnn | } // namespace megdnn | ||||
@@ -57,30 +57,16 @@ bool ConvBiasForwardImpl::AlgoInt8NCHW32IMMAImplicitGemm::is_available( | |||||
// only support sm_75 or later, platform should have tensorcore int8 | // only support sm_75 or later, platform should have tensorcore int8 | ||||
// support | // support | ||||
available &= is_compute_capability_required(7, 5); | available &= is_compute_capability_required(7, 5); | ||||
if (fh == 1 && fw == 1) | |||||
return available; | |||||
// for non 1x1 convolution, we have to check constant memory size | |||||
auto&& device_prop = current_device_prop(); | |||||
// const mem size >= 64K | |||||
available &= device_prop.totalConstMem >= 65536; | |||||
size_t const_mem_usage = get_workspace_in_bytes(args) - | |||||
args.filter_layout->span().dist_byte(); | |||||
available &= const_mem_usage <= device_prop.totalConstMem; | |||||
// FIXME: too large filter size is not supported now | |||||
available &= fh * fw <= 49; | |||||
return available; | return available; | ||||
} | } | ||||
WorkspaceBundle | WorkspaceBundle | ||||
ConvBiasForwardImpl::AlgoInt8NCHW32IMMAImplicitGemm::get_workspace_bundle( | ConvBiasForwardImpl::AlgoInt8NCHW32IMMAImplicitGemm::get_workspace_bundle( | ||||
dt_byte* raw_ptr, const SizeArgs& args) const { | dt_byte* raw_ptr, const SizeArgs& args) const { | ||||
size_t ci = args.filter_layout->operator[](1) * 32; | |||||
size_t fh = args.filter_layout->operator[](2); | |||||
size_t fw = args.filter_layout->operator[](3); | |||||
size_t ws_filter = args.filter_layout->span().dist_byte(); | size_t ws_filter = args.filter_layout->span().dist_byte(); | ||||
if (fh == 1 && fw == 1) { | |||||
return WorkspaceBundle{raw_ptr, {ws_filter}}; | |||||
} | |||||
size_t ws_size = (ci / 32) * fh * fw * sizeof(int32_t) * 2; | |||||
return WorkspaceBundle{raw_ptr, {ws_filter, ws_size}}; | |||||
return WorkspaceBundle{raw_ptr, {ws_filter}}; | |||||
} | } | ||||
size_t | size_t | ||||
@@ -148,9 +134,9 @@ void ConvBiasForwardImpl::AlgoInt8NCHW32IMMAImplicitGemm::exec( | |||||
false>(args.src_tensor->compatible_ptr<int8_t>(), | false>(args.src_tensor->compatible_ptr<int8_t>(), | ||||
reinterpret_cast<int8_t*>(ws_filter), | reinterpret_cast<int8_t*>(ws_filter), | ||||
args.bias_tensor->compatible_ptr<int32_t>(), z_dev_ptr, | args.bias_tensor->compatible_ptr<int32_t>(), z_dev_ptr, | ||||
args.dst_tensor->compatible_ptr<int8_t>(), | |||||
nullptr, kern_param, nonlinear_mode, | |||||
alpha, beta, gamma, dst_scale, | |||||
args.dst_tensor->compatible_ptr<int8_t>(), nullptr, | |||||
kern_param, nonlinear_mode, alpha, beta, gamma, | |||||
dst_scale, | |||||
cutlass_wrapper::GemmCoord{m_algo_param.threadblock_m, | cutlass_wrapper::GemmCoord{m_algo_param.threadblock_m, | ||||
m_algo_param.threadblock_n, | m_algo_param.threadblock_n, | ||||
m_algo_param.threadblock_k}, | m_algo_param.threadblock_k}, | ||||
@@ -159,14 +145,12 @@ void ConvBiasForwardImpl::AlgoInt8NCHW32IMMAImplicitGemm::exec( | |||||
m_algo_param.warp_k}, | m_algo_param.warp_k}, | ||||
stream); | stream); | ||||
} else { | } else { | ||||
auto workspace = ws.get(1); | |||||
cutlass_wrapper::do_conv_bias_int8_implicit_gemm_imma_ncdiv32hw32<true>( | cutlass_wrapper::do_conv_bias_int8_implicit_gemm_imma_ncdiv32hw32<true>( | ||||
args.src_tensor->compatible_ptr<int8_t>(), | args.src_tensor->compatible_ptr<int8_t>(), | ||||
reinterpret_cast<int8_t*>(ws_filter), | reinterpret_cast<int8_t*>(ws_filter), | ||||
args.bias_tensor->compatible_ptr<int32_t>(), z_dev_ptr, | args.bias_tensor->compatible_ptr<int32_t>(), z_dev_ptr, | ||||
args.dst_tensor->compatible_ptr<int8_t>(), | |||||
reinterpret_cast<int*>(workspace), kern_param, nonlinear_mode, | |||||
alpha, beta, gamma, dst_scale, | |||||
args.dst_tensor->compatible_ptr<int8_t>(), nullptr, kern_param, | |||||
nonlinear_mode, alpha, beta, gamma, dst_scale, | |||||
cutlass_wrapper::GemmCoord{m_algo_param.threadblock_m, | cutlass_wrapper::GemmCoord{m_algo_param.threadblock_m, | ||||
m_algo_param.threadblock_n, | m_algo_param.threadblock_n, | ||||
m_algo_param.threadblock_k}, | m_algo_param.threadblock_k}, | ||||
@@ -11,7 +11,8 @@ | |||||
#include "./algo.h" | #include "./algo.h" | ||||
#include "src/cuda/utils.h" | #include "src/cuda/utils.h" | ||||
#include "src/cuda/convolution_helper/bias_visitor.cuh" | |||||
#include "src/cuda/convolution_helper/parameter.cuh" | |||||
#include "src/cuda/conv_bias/cutlass_convolution_wrapper.cuh" | |||||
using namespace megdnn; | using namespace megdnn; | ||||
using namespace cuda; | using namespace cuda; | ||||
@@ -53,21 +54,16 @@ bool ConvBiasForwardImpl::AlgoInt8NCHW4DotProdImplicitGemm::is_available( | |||||
// only support sm_61 or later, platform should have fast native int8 | // only support sm_61 or later, platform should have fast native int8 | ||||
// support | // support | ||||
available &= is_compute_capability_required(6, 1); | available &= is_compute_capability_required(6, 1); | ||||
// FIXME: too large filter size is not supported now | |||||
available &= fh * fw <= 49; | |||||
return available; | return available; | ||||
} | } | ||||
WorkspaceBundle | WorkspaceBundle | ||||
ConvBiasForwardImpl::AlgoInt8NCHW4DotProdImplicitGemm::get_workspace_bundle( | ConvBiasForwardImpl::AlgoInt8NCHW4DotProdImplicitGemm::get_workspace_bundle( | ||||
dt_byte* raw_ptr, const SizeArgs& args) const { | dt_byte* raw_ptr, const SizeArgs& args) const { | ||||
size_t ws_size_src = args.src_layout->span().dist_byte(); | |||||
size_t ws_size_filter = args.filter_layout->span().dist_byte(); | |||||
size_t ws_size_dst = args.dst_layout->span().dist_byte(); | |||||
if (args.z_layout->ndim > 0) { | |||||
size_t ws_size_z = args.z_layout->span().dist_byte(); | |||||
return WorkspaceBundle{ | |||||
raw_ptr, {ws_size_src, ws_size_filter, ws_size_dst, ws_size_z}}; | |||||
} | |||||
return WorkspaceBundle{raw_ptr, {ws_size_src, ws_size_filter, ws_size_dst}}; | |||||
size_t ws_filter = args.filter_layout->span().dist_byte(); | |||||
return WorkspaceBundle{raw_ptr, {ws_filter}}; | |||||
} | } | ||||
size_t | size_t | ||||
@@ -84,27 +80,9 @@ void ConvBiasForwardImpl::AlgoInt8NCHW4DotProdImplicitGemm::exec( | |||||
UNPACK_CONV_BIAS_NCHW4_PARAM(*(args.src_layout), fm, *(args.dst_layout), | UNPACK_CONV_BIAS_NCHW4_PARAM(*(args.src_layout), fm, *(args.dst_layout), | ||||
param); | param); | ||||
auto ws = get_workspace_bundle(args.workspace.raw_ptr, args); | auto ws = get_workspace_bundle(args.workspace.raw_ptr, args); | ||||
auto ws_src = ws.get(0); | |||||
auto ws_filter = ws.get(1); | |||||
auto ws_dst = ws.get(2); | |||||
auto ws_filter = ws.get(0); | |||||
auto&& stream = cuda_stream(args.opr->handle()); | auto&& stream = cuda_stream(args.opr->handle()); | ||||
// reformat src from nchw4 to chwn4 | |||||
{ | |||||
TensorLayout src{{n, ci / 4 * hi * wi}, dtype::Int32()}; | |||||
src.init_contiguous_stride(); | |||||
TensorLayout dst = src; | |||||
dst.stride[0] = 1, dst.stride[1] = dst[0]; | |||||
TensorND ts_src, ts_dst; | |||||
ts_src.raw_ptr = args.src_tensor->raw_ptr; | |||||
ts_src.layout = src; | |||||
ts_dst.raw_ptr = ws_src; | |||||
ts_dst.layout = dst; | |||||
auto&& transpose = | |||||
args.opr->handle()->create_operator<RelayoutForward>(); | |||||
transpose->exec(ts_src, ts_dst); | |||||
} | |||||
// reformat filter from nchw4 to chwn4 | // reformat filter from nchw4 to chwn4 | ||||
{ | { | ||||
TensorLayout src{{co, ci / 4 * fh * fw}, dtype::Int32()}; | TensorLayout src{{co, ci / 4 * fh * fw}, dtype::Int32()}; | ||||
@@ -136,53 +114,42 @@ void ConvBiasForwardImpl::AlgoInt8NCHW4DotProdImplicitGemm::exec( | |||||
dst_scale = args.dst_layout->dtype.param<dtype::QuantizedS8>().scale; | dst_scale = args.dst_layout->dtype.param<dtype::QuantizedS8>().scale; | ||||
float alpha = src_scale * filter_scale / dst_scale, | float alpha = src_scale * filter_scale / dst_scale, | ||||
beta = bias_scale / dst_scale; | beta = bias_scale / dst_scale; | ||||
// process z | |||||
int8_t* z_dev_ptr = nullptr; | int8_t* z_dev_ptr = nullptr; | ||||
float gamma = 1.f; | |||||
float gamma = 0.0; | |||||
if (args.z_layout->ndim > 0) { | if (args.z_layout->ndim > 0) { | ||||
auto ws_z = ws.get(3); | |||||
TensorLayout src{{n, co / 4 * ho * wo}, dtype::Int32()}; | |||||
src.init_contiguous_stride(); | |||||
TensorLayout dst = src; | |||||
dst.stride[0] = 1, dst.stride[1] = dst[0]; | |||||
TensorND ts_src, ts_dst; | |||||
ts_src.raw_ptr = args.z_tensor->raw_ptr; | |||||
ts_src.layout = src; | |||||
ts_dst.raw_ptr = ws_z; | |||||
ts_dst.layout = dst; | |||||
auto&& transpose = | |||||
args.opr->handle()->create_operator<RelayoutForward>(); | |||||
transpose->exec(ts_src, ts_dst); | |||||
z_dev_ptr = reinterpret_cast<int8_t*>(ws_z); | |||||
z_dev_ptr = args.z_tensor->compatible_ptr<int8_t>(); | |||||
float z_scale = args.z_layout->dtype.param<dtype::QuantizedS8>().scale; | float z_scale = args.z_layout->dtype.param<dtype::QuantizedS8>().scale; | ||||
gamma = z_scale / dst_scale; | gamma = z_scale / dst_scale; | ||||
} | } | ||||
convolution::PerChannelBiasVisitor bias_visitor; | |||||
bias_visitor.bias = args.bias_tensor->compatible_ptr<int32_t>(); | |||||
ConvBiasForwardImpl::AlgoInt8CHWN4DotProdImplicitGemm:: | |||||
dispatch_nonlinear_mode<convolution::PerChannelBiasVisitor>( | |||||
reinterpret_cast<int8_t*>(ws_src), | |||||
reinterpret_cast<int8_t*>(ws_filter), bias_visitor, | |||||
z_dev_ptr, reinterpret_cast<int8_t*>(ws_dst), kern_param, | |||||
alpha, beta, gamma, dst_scale, stream, param.nonlineMode); | |||||
// reformat chwn4 to nchw4 | |||||
{ | |||||
TensorLayout src{{co / 4 * ho * wo, n}, dtype::Int32()}; | |||||
src.init_contiguous_stride(); | |||||
TensorLayout dst = src; | |||||
dst.stride[0] = 1, dst.stride[1] = dst[0]; | |||||
TensorND ts_src, ts_dst; | |||||
ts_src.raw_ptr = ws_dst; | |||||
ts_src.layout = src; | |||||
ts_dst.raw_ptr = args.dst_tensor->raw_ptr; | |||||
ts_dst.layout = dst; | |||||
auto&& transpose = | |||||
args.opr->handle()->create_operator<RelayoutForward>(); | |||||
transpose->exec(ts_src, ts_dst); | |||||
uint32_t nonlinear_mode = static_cast<uint32_t>(param.nonlineMode); | |||||
if (fh == 1 && fw == 1) { | |||||
cutlass_wrapper::do_conv_bias_int8_implicit_gemm_dp4a_ncdiv4hw4<false>( | |||||
args.src_tensor->compatible_ptr<int8_t>(), | |||||
reinterpret_cast<int8_t*>(ws_filter), | |||||
args.bias_tensor->compatible_ptr<int32_t>(), z_dev_ptr, | |||||
args.dst_tensor->compatible_ptr<int8_t>(), nullptr, kern_param, | |||||
nonlinear_mode, alpha, beta, gamma, dst_scale, | |||||
cutlass_wrapper::GemmCoord{m_algo_param.threadblock_m, | |||||
m_algo_param.threadblock_n, | |||||
m_algo_param.threadblock_k}, | |||||
cutlass_wrapper::GemmCoord{m_algo_param.warp_m, | |||||
m_algo_param.warp_n, | |||||
m_algo_param.warp_k}, | |||||
stream); | |||||
} else { | |||||
cutlass_wrapper::do_conv_bias_int8_implicit_gemm_dp4a_ncdiv4hw4<true>( | |||||
args.src_tensor->compatible_ptr<int8_t>(), | |||||
reinterpret_cast<int8_t*>(ws_filter), | |||||
args.bias_tensor->compatible_ptr<int32_t>(), z_dev_ptr, | |||||
args.dst_tensor->compatible_ptr<int8_t>(), nullptr, kern_param, | |||||
nonlinear_mode, alpha, beta, gamma, dst_scale, | |||||
cutlass_wrapper::GemmCoord{m_algo_param.threadblock_m, | |||||
m_algo_param.threadblock_n, | |||||
m_algo_param.threadblock_k}, | |||||
cutlass_wrapper::GemmCoord{m_algo_param.warp_m, | |||||
m_algo_param.warp_n, | |||||
m_algo_param.warp_k}, | |||||
stream); | |||||
} | } | ||||
} | } | ||||
@@ -1,6 +1,6 @@ | |||||
/** | /** | ||||
* \file | * \file | ||||
* dnn/src/cuda/conv_bias/int8_imma/conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl | |||||
* dnn/src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl | |||||
* MegEngine is Licensed under the Apache License, Version 2.0 (the "License") | * MegEngine is Licensed under the Apache License, Version 2.0 (the "License") | ||||
* | * | ||||
* Copyright (c) 2014-2020 Megvii Inc. All rights reserved. | * Copyright (c) 2014-2020 Megvii Inc. All rights reserved. |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<128, 128, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationHSwishClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, true>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<128, 128, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, true>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<128, 128, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationReluClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, true>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<128, 32, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationHSwishClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, true>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<128, 32, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, true>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<128, 32, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationReluClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, true>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<128, 64, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationHSwishClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, true>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<128, 64, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, true>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<128, 64, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationReluClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, true>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<16, 64, 8>; | |||||
using WarpShape = cutlass::gemm::GemmShape<16, 64, 8>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationHSwishClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 4, true>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<16, 64, 8>; | |||||
using WarpShape = cutlass::gemm::GemmShape<16, 64, 8>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 4, true>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<16, 64, 8>; | |||||
using WarpShape = cutlass::gemm::GemmShape<16, 64, 8>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationReluClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 4, true>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<128, 128, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationHSwishClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, false>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<128, 128, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, false>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<128, 128, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationReluClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, false>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<128, 32, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationHSwishClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, false>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<128, 32, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, false>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<128, 32, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationReluClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, false>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<128, 64, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationHSwishClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, false>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<128, 64, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, false>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<128, 64, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationReluClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, false>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<16, 64, 8>; | |||||
using WarpShape = cutlass::gemm::GemmShape<16, 64, 8>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationHSwishClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 4, false>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<16, 64, 8>; | |||||
using WarpShape = cutlass::gemm::GemmShape<16, 64, 8>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 4, false>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<16, 64, 8>; | |||||
using WarpShape = cutlass::gemm::GemmShape<16, 64, 8>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationReluClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 4, false>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<32, 128, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<32, 64, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationHSwishClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, false>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<32, 128, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<32, 64, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, false>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<32, 128, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<32, 64, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationReluClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, false>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<32, 32, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<32, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationHSwishClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, false>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<32, 32, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<32, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, false>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<32, 32, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<32, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationReluClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, false>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<32, 64, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<32, 64, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationHSwishClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, false>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<32, 64, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<32, 64, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, false>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<32, 64, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<32, 64, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationReluClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, false>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<64, 128, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationHSwishClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, false>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<64, 128, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, false>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<64, 128, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationReluClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, false>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationHSwishClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, false>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, false>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationReluClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, false>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<64, 64, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationHSwishClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, false>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<64, 64, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, false>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<64, 64, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationReluClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, false>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<32, 128, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<32, 64, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationHSwishClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, true>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<32, 128, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<32, 64, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, true>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<32, 128, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<32, 64, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationReluClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, true>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<32, 32, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<32, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationHSwishClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, true>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<32, 32, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<32, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, true>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<32, 32, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<32, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationReluClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, true>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<32, 64, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<32, 64, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationHSwishClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, true>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<32, 64, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<32, 64, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, true>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<32, 64, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<32, 64, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationReluClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, true>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<64, 128, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationHSwishClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, true>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<64, 128, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, true>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<64, 128, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationReluClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, true>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationHSwishClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, true>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, true>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationReluClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, true>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<64, 64, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationHSwishClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, true>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<64, 64, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, true>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -0,0 +1,35 @@ | |||||
#if !MEGDNN_TEGRA_X1 | |||||
// generated by gen_cuda_conv_bias_kern_impls.py | |||||
// ignore warning of cutlass | |||||
#pragma GCC diagnostic push | |||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<4>; | |||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<4>; | |||||
using ThreadBlockShape = cutlass::gemm::GemmShape<64, 64, 32>; | |||||
using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>; | |||||
using InstructionShape = cutlass::gemm::GemmShape<1, 1, 4>; | |||||
using EpilogueOp = cutlass::epilogue::thread::BiasAddLinearCombinationReluClamp< | |||||
int8_t, 4, int32_t, int32_t, float>; | |||||
using Convolution = cutlass::convolution::device::Convolution< | |||||
int8_t, LayoutSrc, int8_t, LayoutFilter, int8_t, | |||||
LayoutSrc, int32_t, LayoutSrc, int32_t, | |||||
cutlass::convolution::ConvType::kConvolution, cutlass::arch::OpClassSimt, cutlass::arch::Sm61, | |||||
ThreadBlockShape, WarpShape, InstructionShape, EpilogueOp, | |||||
cutlass::convolution::threadblock::ConvolutionNCxHWxThreadblockSwizzle< | |||||
cutlass::convolution::ConvType::kConvolution>, | |||||
2, 4, 16, true>; | |||||
template void megdnn::cuda::cutlass_wrapper::cutlass_convolution_wrapper<Convolution>( | |||||
const int8_t* d_src, | |||||
const int8_t* d_filter, | |||||
const int32_t* d_bias, | |||||
const int8_t* d_z, | |||||
int8_t* d_dst, | |||||
int* workspace, | |||||
typename Convolution::ConvolutionParameter const& conv_param, | |||||
typename Convolution::EpilogueOutputOp::Params const& epilogue, | |||||
cudaStream_t stream); | |||||
#pragma GCC diagnostic pop | |||||
#endif |
@@ -4,7 +4,7 @@ | |||||
#pragma GCC diagnostic push | #pragma GCC diagnostic push | ||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | #pragma GCC diagnostic ignored "-Wunused-parameter" | ||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | #pragma GCC diagnostic ignored "-Wstrict-aliasing" | ||||
#include "../conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | ||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | ||||
@@ -4,7 +4,7 @@ | |||||
#pragma GCC diagnostic push | #pragma GCC diagnostic push | ||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | #pragma GCC diagnostic ignored "-Wunused-parameter" | ||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | #pragma GCC diagnostic ignored "-Wstrict-aliasing" | ||||
#include "../conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | ||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | ||||
@@ -4,7 +4,7 @@ | |||||
#pragma GCC diagnostic push | #pragma GCC diagnostic push | ||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | #pragma GCC diagnostic ignored "-Wunused-parameter" | ||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | #pragma GCC diagnostic ignored "-Wstrict-aliasing" | ||||
#include "../conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | ||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | ||||
@@ -4,7 +4,7 @@ | |||||
#pragma GCC diagnostic push | #pragma GCC diagnostic push | ||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | #pragma GCC diagnostic ignored "-Wunused-parameter" | ||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | #pragma GCC diagnostic ignored "-Wstrict-aliasing" | ||||
#include "../conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | ||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | ||||
@@ -4,7 +4,7 @@ | |||||
#pragma GCC diagnostic push | #pragma GCC diagnostic push | ||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | #pragma GCC diagnostic ignored "-Wunused-parameter" | ||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | #pragma GCC diagnostic ignored "-Wstrict-aliasing" | ||||
#include "../conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | ||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | ||||
@@ -4,7 +4,7 @@ | |||||
#pragma GCC diagnostic push | #pragma GCC diagnostic push | ||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | #pragma GCC diagnostic ignored "-Wunused-parameter" | ||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | #pragma GCC diagnostic ignored "-Wstrict-aliasing" | ||||
#include "../conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | ||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | ||||
@@ -4,7 +4,7 @@ | |||||
#pragma GCC diagnostic push | #pragma GCC diagnostic push | ||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | #pragma GCC diagnostic ignored "-Wunused-parameter" | ||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | #pragma GCC diagnostic ignored "-Wstrict-aliasing" | ||||
#include "../conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | ||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | ||||
@@ -4,7 +4,7 @@ | |||||
#pragma GCC diagnostic push | #pragma GCC diagnostic push | ||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | #pragma GCC diagnostic ignored "-Wunused-parameter" | ||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | #pragma GCC diagnostic ignored "-Wstrict-aliasing" | ||||
#include "../conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | ||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | ||||
@@ -4,7 +4,7 @@ | |||||
#pragma GCC diagnostic push | #pragma GCC diagnostic push | ||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | #pragma GCC diagnostic ignored "-Wunused-parameter" | ||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | #pragma GCC diagnostic ignored "-Wstrict-aliasing" | ||||
#include "../conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | ||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | ||||
@@ -4,7 +4,7 @@ | |||||
#pragma GCC diagnostic push | #pragma GCC diagnostic push | ||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | #pragma GCC diagnostic ignored "-Wunused-parameter" | ||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | #pragma GCC diagnostic ignored "-Wstrict-aliasing" | ||||
#include "../conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | ||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | ||||
@@ -4,7 +4,7 @@ | |||||
#pragma GCC diagnostic push | #pragma GCC diagnostic push | ||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | #pragma GCC diagnostic ignored "-Wunused-parameter" | ||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | #pragma GCC diagnostic ignored "-Wstrict-aliasing" | ||||
#include "../conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | ||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | ||||
@@ -4,7 +4,7 @@ | |||||
#pragma GCC diagnostic push | #pragma GCC diagnostic push | ||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | #pragma GCC diagnostic ignored "-Wunused-parameter" | ||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | #pragma GCC diagnostic ignored "-Wstrict-aliasing" | ||||
#include "../conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | ||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | ||||
@@ -4,7 +4,7 @@ | |||||
#pragma GCC diagnostic push | #pragma GCC diagnostic push | ||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | #pragma GCC diagnostic ignored "-Wunused-parameter" | ||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | #pragma GCC diagnostic ignored "-Wstrict-aliasing" | ||||
#include "../conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | ||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | ||||
@@ -4,7 +4,7 @@ | |||||
#pragma GCC diagnostic push | #pragma GCC diagnostic push | ||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | #pragma GCC diagnostic ignored "-Wunused-parameter" | ||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | #pragma GCC diagnostic ignored "-Wstrict-aliasing" | ||||
#include "../conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | ||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | ||||
@@ -4,7 +4,7 @@ | |||||
#pragma GCC diagnostic push | #pragma GCC diagnostic push | ||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | #pragma GCC diagnostic ignored "-Wunused-parameter" | ||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | #pragma GCC diagnostic ignored "-Wstrict-aliasing" | ||||
#include "../conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | ||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | ||||
@@ -4,7 +4,7 @@ | |||||
#pragma GCC diagnostic push | #pragma GCC diagnostic push | ||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | #pragma GCC diagnostic ignored "-Wunused-parameter" | ||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | #pragma GCC diagnostic ignored "-Wstrict-aliasing" | ||||
#include "../conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | ||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | ||||
@@ -4,7 +4,7 @@ | |||||
#pragma GCC diagnostic push | #pragma GCC diagnostic push | ||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | #pragma GCC diagnostic ignored "-Wunused-parameter" | ||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | #pragma GCC diagnostic ignored "-Wstrict-aliasing" | ||||
#include "../conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | ||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | ||||
@@ -4,7 +4,7 @@ | |||||
#pragma GCC diagnostic push | #pragma GCC diagnostic push | ||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | #pragma GCC diagnostic ignored "-Wunused-parameter" | ||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | #pragma GCC diagnostic ignored "-Wstrict-aliasing" | ||||
#include "../conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | ||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | ||||
@@ -4,7 +4,7 @@ | |||||
#pragma GCC diagnostic push | #pragma GCC diagnostic push | ||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | #pragma GCC diagnostic ignored "-Wunused-parameter" | ||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | #pragma GCC diagnostic ignored "-Wstrict-aliasing" | ||||
#include "../conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | ||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | ||||
@@ -4,7 +4,7 @@ | |||||
#pragma GCC diagnostic push | #pragma GCC diagnostic push | ||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | #pragma GCC diagnostic ignored "-Wunused-parameter" | ||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | #pragma GCC diagnostic ignored "-Wstrict-aliasing" | ||||
#include "../conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | ||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | ||||
@@ -4,7 +4,7 @@ | |||||
#pragma GCC diagnostic push | #pragma GCC diagnostic push | ||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | #pragma GCC diagnostic ignored "-Wunused-parameter" | ||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | #pragma GCC diagnostic ignored "-Wstrict-aliasing" | ||||
#include "../conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | ||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | ||||
@@ -4,7 +4,7 @@ | |||||
#pragma GCC diagnostic push | #pragma GCC diagnostic push | ||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | #pragma GCC diagnostic ignored "-Wunused-parameter" | ||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | #pragma GCC diagnostic ignored "-Wstrict-aliasing" | ||||
#include "../conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | ||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | ||||
@@ -4,7 +4,7 @@ | |||||
#pragma GCC diagnostic push | #pragma GCC diagnostic push | ||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | #pragma GCC diagnostic ignored "-Wunused-parameter" | ||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | #pragma GCC diagnostic ignored "-Wstrict-aliasing" | ||||
#include "../conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | ||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | ||||
@@ -4,7 +4,7 @@ | |||||
#pragma GCC diagnostic push | #pragma GCC diagnostic push | ||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | #pragma GCC diagnostic ignored "-Wunused-parameter" | ||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | #pragma GCC diagnostic ignored "-Wstrict-aliasing" | ||||
#include "../conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | ||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | ||||
@@ -4,7 +4,7 @@ | |||||
#pragma GCC diagnostic push | #pragma GCC diagnostic push | ||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | #pragma GCC diagnostic ignored "-Wunused-parameter" | ||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | #pragma GCC diagnostic ignored "-Wstrict-aliasing" | ||||
#include "../conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | ||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | ||||
@@ -4,7 +4,7 @@ | |||||
#pragma GCC diagnostic push | #pragma GCC diagnostic push | ||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | #pragma GCC diagnostic ignored "-Wunused-parameter" | ||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | #pragma GCC diagnostic ignored "-Wstrict-aliasing" | ||||
#include "../conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | ||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | ||||
@@ -4,7 +4,7 @@ | |||||
#pragma GCC diagnostic push | #pragma GCC diagnostic push | ||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | #pragma GCC diagnostic ignored "-Wunused-parameter" | ||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | #pragma GCC diagnostic ignored "-Wstrict-aliasing" | ||||
#include "../conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | ||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | ||||
@@ -4,7 +4,7 @@ | |||||
#pragma GCC diagnostic push | #pragma GCC diagnostic push | ||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | #pragma GCC diagnostic ignored "-Wunused-parameter" | ||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | #pragma GCC diagnostic ignored "-Wstrict-aliasing" | ||||
#include "../conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | ||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | ||||
@@ -4,7 +4,7 @@ | |||||
#pragma GCC diagnostic push | #pragma GCC diagnostic push | ||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | #pragma GCC diagnostic ignored "-Wunused-parameter" | ||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | #pragma GCC diagnostic ignored "-Wstrict-aliasing" | ||||
#include "../conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | ||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | ||||
@@ -4,7 +4,7 @@ | |||||
#pragma GCC diagnostic push | #pragma GCC diagnostic push | ||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | #pragma GCC diagnostic ignored "-Wunused-parameter" | ||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | #pragma GCC diagnostic ignored "-Wstrict-aliasing" | ||||
#include "../conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | ||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | ||||
@@ -4,7 +4,7 @@ | |||||
#pragma GCC diagnostic push | #pragma GCC diagnostic push | ||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | #pragma GCC diagnostic ignored "-Wunused-parameter" | ||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | #pragma GCC diagnostic ignored "-Wstrict-aliasing" | ||||
#include "../conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | ||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | ||||
@@ -4,7 +4,7 @@ | |||||
#pragma GCC diagnostic push | #pragma GCC diagnostic push | ||||
#pragma GCC diagnostic ignored "-Wunused-parameter" | #pragma GCC diagnostic ignored "-Wunused-parameter" | ||||
#pragma GCC diagnostic ignored "-Wstrict-aliasing" | #pragma GCC diagnostic ignored "-Wstrict-aliasing" | ||||
#include "../conv_bias_int8_implicit_gemm_imma_ncdiv32hw32.cuinl" | |||||
#include "src/cuda/conv_bias/int8/conv_bias_int8_implicit_gemm_cutlass_wrapper.cuinl" | |||||
using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | using LayoutSrc = cutlass::layout::TensorNCxHWx<32>; | ||||
using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | using LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | ||||