GitOrigin-RevId: 93c9b212f4
tags/v1.0.0-rc1
@@ -36,8 +36,9 @@ all: ${PARAM_DEFS} ${ELEMWISE_IMPL} ${CUDA_CONV_IMPL} | |||
../src/cuda/elemwise_multi_type/kimpl: gen_elemwise_multi_type_kern_impls.py | |||
./$^ --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 | |||
./gen_cuda_conv_bias_kern_impls.py --type imma $@ | |||
@@ -91,7 +91,10 @@ ConvBiasForwardImpl::AlgoPack::AlgoPack() { | |||
} | |||
#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); | |||
for (size_t i = all_algo_size; i < all_algos.size(); ++i) { | |||
non_cudnn_algos.push_back(all_algos[i]); | |||
@@ -253,6 +256,20 @@ void ConvBiasForwardImpl::AlgoPack::fill_imma_algos() { | |||
} | |||
#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::AlgoPack::cudnn_conv_from_enum( | |||
@@ -386,18 +386,39 @@ public: | |||
class ConvBiasForwardImpl::AlgoInt8NCHW4DotProdImplicitGemm final | |||
: public AlgoBase { | |||
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; | |||
size_t get_workspace_in_bytes(const SizeArgs& 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; } | |||
private: | |||
WorkspaceBundle get_workspace_bundle(dt_byte* raw_ptr, | |||
const SizeArgs& args) const; | |||
AlgoParam m_algo_param; | |||
std::string m_name; | |||
}; | |||
#if CUDA_VERSION >= 10000 | |||
@@ -578,7 +599,7 @@ public: | |||
AlgoMatmul8x8x32 matmul8x8x32; | |||
AlgoBatchedMatmul batched_matmul; | |||
Algo1x1 a1x1; | |||
AlgoInt8NCHW4DotProdImplicitGemm int8_nchw4_dotprod; | |||
std::vector<AlgoInt8NCHW4DotProdImplicitGemm> int8_nchw4_dotprod; | |||
AlgoInt8CHWN4DotProdImplicitGemm int8_chwn4_dotprod; | |||
#if CUDA_VERSION >= 10000 | |||
AlgoQUInt4x4x32WMMA wmma_quint4x4x32; | |||
@@ -605,6 +626,7 @@ private: | |||
void fill_imma_algos(); | |||
#endif | |||
void fill_cudnn_algos(); | |||
void fill_dp4a_algos(); | |||
}; | |||
} // namespace cuda | |||
@@ -19,7 +19,6 @@ | |||
#endif | |||
#include "src/common/opr_param_defs_enumv.cuh" | |||
#include "src/cuda/conv_bias/cutlass_convolution_wrapper.cuh" | |||
#pragma GCC diagnostic pop | |||
using namespace megdnn; | |||
@@ -149,4 +148,130 @@ INST(true); | |||
INST(false); | |||
#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 |
@@ -37,6 +37,15 @@ void do_conv_bias_int8_implicit_gemm_imma_ncdiv32hw32( | |||
const GemmCoord& threadblock_shape, const GemmCoord& warp_shape, | |||
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 cuda | |||
} // namespace megdnn | |||
@@ -57,30 +57,16 @@ bool ConvBiasForwardImpl::AlgoInt8NCHW32IMMAImplicitGemm::is_available( | |||
// only support sm_75 or later, platform should have tensorcore int8 | |||
// support | |||
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; | |||
} | |||
WorkspaceBundle | |||
ConvBiasForwardImpl::AlgoInt8NCHW32IMMAImplicitGemm::get_workspace_bundle( | |||
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(); | |||
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 | |||
@@ -148,9 +134,9 @@ void ConvBiasForwardImpl::AlgoInt8NCHW32IMMAImplicitGemm::exec( | |||
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, | |||
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}, | |||
@@ -159,14 +145,12 @@ void ConvBiasForwardImpl::AlgoInt8NCHW32IMMAImplicitGemm::exec( | |||
m_algo_param.warp_k}, | |||
stream); | |||
} else { | |||
auto workspace = ws.get(1); | |||
cutlass_wrapper::do_conv_bias_int8_implicit_gemm_imma_ncdiv32hw32<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>(), | |||
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, | |||
m_algo_param.threadblock_n, | |||
m_algo_param.threadblock_k}, | |||
@@ -11,7 +11,8 @@ | |||
#include "./algo.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 cuda; | |||
@@ -53,21 +54,16 @@ bool ConvBiasForwardImpl::AlgoInt8NCHW4DotProdImplicitGemm::is_available( | |||
// only support sm_61 or later, platform should have fast native int8 | |||
// support | |||
available &= is_compute_capability_required(6, 1); | |||
// FIXME: too large filter size is not supported now | |||
available &= fh * fw <= 49; | |||
return available; | |||
} | |||
WorkspaceBundle | |||
ConvBiasForwardImpl::AlgoInt8NCHW4DotProdImplicitGemm::get_workspace_bundle( | |||
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 | |||
@@ -84,27 +80,9 @@ void ConvBiasForwardImpl::AlgoInt8NCHW4DotProdImplicitGemm::exec( | |||
UNPACK_CONV_BIAS_NCHW4_PARAM(*(args.src_layout), fm, *(args.dst_layout), | |||
param); | |||
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()); | |||
// 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 | |||
{ | |||
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; | |||
float alpha = src_scale * filter_scale / dst_scale, | |||
beta = bias_scale / dst_scale; | |||
// process z | |||
int8_t* z_dev_ptr = nullptr; | |||
float gamma = 1.f; | |||
float gamma = 0.0; | |||
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; | |||
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 | |||
* 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") | |||
* | |||
* 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 ignored "-Wunused-parameter" | |||
#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 LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | |||
@@ -4,7 +4,7 @@ | |||
#pragma GCC diagnostic push | |||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||
#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 LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | |||
@@ -4,7 +4,7 @@ | |||
#pragma GCC diagnostic push | |||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||
#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 LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | |||
@@ -4,7 +4,7 @@ | |||
#pragma GCC diagnostic push | |||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||
#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 LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | |||
@@ -4,7 +4,7 @@ | |||
#pragma GCC diagnostic push | |||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||
#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 LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | |||
@@ -4,7 +4,7 @@ | |||
#pragma GCC diagnostic push | |||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||
#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 LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | |||
@@ -4,7 +4,7 @@ | |||
#pragma GCC diagnostic push | |||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||
#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 LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | |||
@@ -4,7 +4,7 @@ | |||
#pragma GCC diagnostic push | |||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||
#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 LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | |||
@@ -4,7 +4,7 @@ | |||
#pragma GCC diagnostic push | |||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||
#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 LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | |||
@@ -4,7 +4,7 @@ | |||
#pragma GCC diagnostic push | |||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||
#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 LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | |||
@@ -4,7 +4,7 @@ | |||
#pragma GCC diagnostic push | |||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||
#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 LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | |||
@@ -4,7 +4,7 @@ | |||
#pragma GCC diagnostic push | |||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||
#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 LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | |||
@@ -4,7 +4,7 @@ | |||
#pragma GCC diagnostic push | |||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||
#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 LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | |||
@@ -4,7 +4,7 @@ | |||
#pragma GCC diagnostic push | |||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||
#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 LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | |||
@@ -4,7 +4,7 @@ | |||
#pragma GCC diagnostic push | |||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||
#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 LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | |||
@@ -4,7 +4,7 @@ | |||
#pragma GCC diagnostic push | |||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||
#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 LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | |||
@@ -4,7 +4,7 @@ | |||
#pragma GCC diagnostic push | |||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||
#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 LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | |||
@@ -4,7 +4,7 @@ | |||
#pragma GCC diagnostic push | |||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||
#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 LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | |||
@@ -4,7 +4,7 @@ | |||
#pragma GCC diagnostic push | |||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||
#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 LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | |||
@@ -4,7 +4,7 @@ | |||
#pragma GCC diagnostic push | |||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||
#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 LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | |||
@@ -4,7 +4,7 @@ | |||
#pragma GCC diagnostic push | |||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||
#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 LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | |||
@@ -4,7 +4,7 @@ | |||
#pragma GCC diagnostic push | |||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||
#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 LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | |||
@@ -4,7 +4,7 @@ | |||
#pragma GCC diagnostic push | |||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||
#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 LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | |||
@@ -4,7 +4,7 @@ | |||
#pragma GCC diagnostic push | |||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||
#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 LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | |||
@@ -4,7 +4,7 @@ | |||
#pragma GCC diagnostic push | |||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||
#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 LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | |||
@@ -4,7 +4,7 @@ | |||
#pragma GCC diagnostic push | |||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||
#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 LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | |||
@@ -4,7 +4,7 @@ | |||
#pragma GCC diagnostic push | |||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||
#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 LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | |||
@@ -4,7 +4,7 @@ | |||
#pragma GCC diagnostic push | |||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||
#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 LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | |||
@@ -4,7 +4,7 @@ | |||
#pragma GCC diagnostic push | |||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||
#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 LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | |||
@@ -4,7 +4,7 @@ | |||
#pragma GCC diagnostic push | |||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||
#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 LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | |||
@@ -4,7 +4,7 @@ | |||
#pragma GCC diagnostic push | |||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||
#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 LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | |||
@@ -4,7 +4,7 @@ | |||
#pragma GCC diagnostic push | |||
#pragma GCC diagnostic ignored "-Wunused-parameter" | |||
#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 LayoutFilter = cutlass::layout::TensorCxRSKx<32>; | |||