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"...en/git@developer.sourcefind.cn:OpenDAS/mmdetection3d.git" did not exist on "e943e84d51ac4208084326f6dc13bade42b049ec"
Commit ad2fddf4 authored by Jing Zhang's avatar Jing Zhang
Browse files

Merge remote-tracking branch 'origin/develop' into grouped_gemm_args_simplify

parents fa649421 1ee99dca
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Showing with 240 additions and 43 deletions
.pre-commit-config.yaml 0 → 100644
View file @ ad2fddf4
repos:
- repo: local
hooks:
- id: clang-format
name: clang-format
entry: clang-format-10 -i --style=file
language: system
types_or: [c++, inc]
- id: copyright-year-checker
name: copyright-year-checker
entry: script/check_copyright_year.sh
verbose: false
language: script
types: [c++]
Jenkinsfile
View file @ ad2fddf4
...@@ -11,6 +11,20 @@ def show_node_info() { ...@@ -11,6 +11,20 @@ def show_node_info() {
""" """
} }
def nthreads() {
def nproc = sh(returnStdout: true, script: 'nproc')
echo "Number of cores: ${nproc}"
def n = nproc.toInteger()
if (n > 32){
n /= 2
}
if (n > 64){
n = 64
}
echo "Number of threads used for building: ${n}"
return n
}
def runShell(String command){ def runShell(String command){
def responseCode = sh returnStatus: true, script: "${command} > tmp.txt" def responseCode = sh returnStatus: true, script: "${command} > tmp.txt"
def output = readFile(file: "tmp.txt") def output = readFile(file: "tmp.txt")
...@@ -219,7 +233,8 @@ def cmake_build(Map conf=[:]){ ...@@ -219,7 +233,8 @@ def cmake_build(Map conf=[:]){
""" """
def setup_cmd = conf.get("setup_cmd", "${cmake_envs} cmake ${setup_args} .. ") def setup_cmd = conf.get("setup_cmd", "${cmake_envs} cmake ${setup_args} .. ")
// reduce parallelism when compiling, clang uses too much memory // reduce parallelism when compiling, clang uses too much memory
def build_cmd = conf.get("build_cmd", "${build_envs} dumb-init make -j\$(( \$(nproc) / 2 )) ${config_targets}") def nt = nthreads()
def build_cmd = conf.get("build_cmd", "${build_envs} dumb-init make -j${nt} ${config_targets}")
def execute_cmd = conf.get("execute_cmd", "") def execute_cmd = conf.get("execute_cmd", "")
def cmd = conf.get("cmd", """ def cmd = conf.get("cmd", """
...@@ -461,7 +476,7 @@ def Build_CK(Map conf=[:]){ ...@@ -461,7 +476,7 @@ def Build_CK(Map conf=[:]){
else{ else{
echo "GPU is OK" echo "GPU is OK"
} }
if ( runShell('grep -n "gfx1030" clinfo.log') ){ if ( runShell('grep -n "gfx1030" clinfo.log') || runShell('grep -n "gfx1101" clinfo.log') ){
navi_node = 1 navi_node = 1
} }
} }
...@@ -482,7 +497,7 @@ def Build_CK(Map conf=[:]){ ...@@ -482,7 +497,7 @@ def Build_CK(Map conf=[:]){
else{ else{
echo "GPU is OK" echo "GPU is OK"
} }
if ( runShell('grep -n "gfx1030" clinfo.log') ){ if ( runShell('grep -n "gfx1030" clinfo.log') || runShell('grep -n "gfx1101" clinfo.log') ){
navi_node = 1 navi_node = 1
} }
} }
...@@ -493,8 +508,9 @@ def Build_CK(Map conf=[:]){ ...@@ -493,8 +508,9 @@ def Build_CK(Map conf=[:]){
{ {
cmake_build(conf) cmake_build(conf)
dir("build"){ dir("build"){
//run tests and examples //run tests and examples
sh 'make -j\$(( \$(nproc) / 2 )) check' def nt = nthreads()
sh 'make -j${nt} check'
if (navi_node == 0 ){ if (navi_node == 0 ){
//we only need the ckProfiler to run the performance tests, so we pack and stash it //we only need the ckProfiler to run the performance tests, so we pack and stash it
//do not stash profiler on Navi nodes //do not stash profiler on Navi nodes
...@@ -717,7 +733,7 @@ pipeline { ...@@ -717,7 +733,7 @@ pipeline {
Build_CK_and_Reboot(setup_args: setup_args, config_targets: "install", no_reboot:true, build_type: 'Release', execute_cmd: execute_args, prefixpath: '/usr/local') Build_CK_and_Reboot(setup_args: setup_args, config_targets: "install", no_reboot:true, build_type: 'Release', execute_cmd: execute_args, prefixpath: '/usr/local')
} }
} }
stage("Build CK and run Tests on Navi") stage("Build CK and run Tests on Navi21")
{ {
when { when {
beforeAgent true beforeAgent true
......
README.md
View file @ ad2fddf4
...@@ -109,6 +109,24 @@ make install ...@@ -109,6 +109,24 @@ make install
Instructions for using CK as a pre-built kernel library are under [client_example](/client_example) Instructions for using CK as a pre-built kernel library are under [client_example](/client_example)
## Contributing
When you contribute to Composable Kernel, make sure to run `clang-format` on all the changed files. We highly recommend using git hooks that are managed by the `pre-commit` framework. To install hooks, run:
```bash
sudo script/install_precommit.sh
```
This way, `pre-commit` will add the appropriate hooks to your local repository and automatically run `clang-format` (and possibly additional checks) before any commit is created.
If you need to uninstall hooks from the repository, you can do so by running the following command:
```bash
script/uninstall_precommit.sh
```
If for any reason, you need to temporarily disable precommit hooks, you can add the `--no-verify` option to the `git commit` command.
## Caveat ## Caveat
### Kernel Timing and Verification ### Kernel Timing and Verification
......
client_example/11_grouped_conv_bwd_weight/common.hpp
View file @ ad2fddf4
...@@ -101,13 +101,15 @@ template <ck::index_t NumDimSpatial, ...@@ -101,13 +101,15 @@ template <ck::index_t NumDimSpatial,
typename WeiLayout, typename WeiLayout,
typename OutLayout> typename OutLayout>
bool run_grouped_conv_bwd_weight( bool run_grouped_conv_bwd_weight(
ck::index_t G, const ck::index_t G,
ck::index_t N, const ck::index_t N,
ck::index_t K, const ck::index_t K,
ck::index_t C, const ck::index_t C,
const std::array<ck::index_t, NumDimSpatial>& input_spatial_lengths, const std::array<ck::index_t, NumDimSpatial>& input_spatial_lengths,
const std::array<ck::index_t, NumDimSpatial>& filter_spatial_lengths, const std::array<ck::index_t, NumDimSpatial>& filter_spatial_lengths,
const std::array<ck::index_t, NumDimSpatial>& output_spatial_lengths, const std::array<ck::index_t, NumDimSpatial>& output_spatial_lengths,
const std::array<ck::index_t, NumDimSpatial + 3>& input_strides,
const std::array<ck::index_t, NumDimSpatial + 3>& output_strides,
const std::array<ck::index_t, NumDimSpatial>& conv_filter_strides, const std::array<ck::index_t, NumDimSpatial>& conv_filter_strides,
const std::array<ck::index_t, NumDimSpatial>& conv_filter_dilations, const std::array<ck::index_t, NumDimSpatial>& conv_filter_dilations,
const std::array<ck::index_t, NumDimSpatial>& input_left_pads, const std::array<ck::index_t, NumDimSpatial>& input_left_pads,
...@@ -157,6 +159,8 @@ bool run_grouped_conv_bwd_weight( ...@@ -157,6 +159,8 @@ bool run_grouped_conv_bwd_weight(
input_spatial_lengths, input_spatial_lengths,
filter_spatial_lengths, filter_spatial_lengths,
output_spatial_lengths, output_spatial_lengths,
input_strides,
output_strides,
conv_filter_strides, conv_filter_strides,
conv_filter_dilations, conv_filter_dilations,
input_left_pads, input_left_pads,
...@@ -224,6 +228,8 @@ bool run_grouped_conv_bwd_weight( ...@@ -224,6 +228,8 @@ bool run_grouped_conv_bwd_weight(
input_spatial_lengths, input_spatial_lengths,
filter_spatial_lengths, filter_spatial_lengths,
output_spatial_lengths, output_spatial_lengths,
input_strides,
output_strides,
conv_filter_strides, conv_filter_strides,
conv_filter_dilations, conv_filter_dilations,
input_left_pads, input_left_pads,
......
client_example/11_grouped_conv_bwd_weight/grouped_conv1d_bwd_weight_fp16.cpp
View file @ ad2fddf4
...@@ -22,6 +22,15 @@ static constexpr ck::index_t C = 192; ...@@ -22,6 +22,15 @@ static constexpr ck::index_t C = 192;
static constexpr ck::index_t X = 3; static constexpr ck::index_t X = 3;
static constexpr ck::index_t Wi = 28; static constexpr ck::index_t Wi = 28;
static constexpr ck::index_t Wo = 28; static constexpr ck::index_t Wo = 28;
static constexpr std::array<ck::index_t, NumDimSpatial> input_spatial_lengths{Wi};
static constexpr std::array<ck::index_t, NumDimSpatial> filter_spatial_lengths{X};
static constexpr std::array<ck::index_t, NumDimSpatial> output_spatial_lengths{Wo};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> input_strides{N * Wi * C, Wi* C, C, 1};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> output_strides{N * Wo * K, Wo* K, K, 1};
static constexpr std::array<ck::index_t, NumDimSpatial> conv_filter_strides{1};
static constexpr std::array<ck::index_t, NumDimSpatial> conv_filter_dilations{1};
static constexpr std::array<ck::index_t, NumDimSpatial> input_left_pads{1};
static constexpr std::array<ck::index_t, NumDimSpatial> input_right_pads{1};
int main() int main()
{ {
...@@ -31,7 +40,19 @@ int main() ...@@ -31,7 +40,19 @@ int main()
OutDataType, OutDataType,
InLayout, InLayout,
WeiLayout, WeiLayout,
OutLayout>(G, N, K, C, {Wi}, {X}, {Wo}, {1}, {1}, {1}, {1}) OutLayout>(G,
N,
K,
C,
input_spatial_lengths,
filter_spatial_lengths,
output_spatial_lengths,
input_strides,
output_strides,
conv_filter_strides,
conv_filter_dilations,
input_left_pads,
input_right_pads)
? EXIT_SUCCESS ? EXIT_SUCCESS
: EXIT_FAILURE; : EXIT_FAILURE;
} }
client_example/11_grouped_conv_bwd_weight/grouped_conv2d_bwd_weight_fp16.cpp
View file @ ad2fddf4
...@@ -25,6 +25,17 @@ static constexpr ck::index_t Hi = 28; ...@@ -25,6 +25,17 @@ static constexpr ck::index_t Hi = 28;
static constexpr ck::index_t Wi = 28; static constexpr ck::index_t Wi = 28;
static constexpr ck::index_t Ho = 28; static constexpr ck::index_t Ho = 28;
static constexpr ck::index_t Wo = 28; static constexpr ck::index_t Wo = 28;
static constexpr std::array<ck::index_t, NumDimSpatial> input_spatial_lengths{Hi, Wi};
static constexpr std::array<ck::index_t, NumDimSpatial> filter_spatial_lengths{Y, X};
static constexpr std::array<ck::index_t, NumDimSpatial> output_spatial_lengths{Ho, Wo};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> input_strides{
N * Hi * Wi * C, Hi* Wi* C, Wi* C, C, 1};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> output_strides{
N * Ho * Wo * K, Ho* Wo* K, Wo* K, K, 1};
static constexpr std::array<ck::index_t, NumDimSpatial> conv_filter_strides{1, 1};
static constexpr std::array<ck::index_t, NumDimSpatial> conv_filter_dilations{1, 1};
static constexpr std::array<ck::index_t, NumDimSpatial> input_left_pads{1, 1};
static constexpr std::array<ck::index_t, NumDimSpatial> input_right_pads{1, 1};
int main() int main()
{ {
...@@ -34,8 +45,19 @@ int main() ...@@ -34,8 +45,19 @@ int main()
OutDataType, OutDataType,
InLayout, InLayout,
WeiLayout, WeiLayout,
OutLayout>( OutLayout>(G,
G, N, K, C, {Hi, Wi}, {Y, X}, {Ho, Wo}, {1, 1}, {1, 1}, {1, 1}, {1, 1}) N,
K,
C,
input_spatial_lengths,
filter_spatial_lengths,
output_spatial_lengths,
input_strides,
output_strides,
conv_filter_strides,
conv_filter_dilations,
input_left_pads,
input_right_pads)
? EXIT_SUCCESS ? EXIT_SUCCESS
: EXIT_FAILURE; : EXIT_FAILURE;
} }
client_example/11_grouped_conv_bwd_weight/grouped_conv3d_bwd_weight_fp16.cpp
View file @ ad2fddf4
...@@ -28,6 +28,17 @@ static constexpr ck::index_t Wi = 3; ...@@ -28,6 +28,17 @@ static constexpr ck::index_t Wi = 3;
static constexpr ck::index_t Do = 28; static constexpr ck::index_t Do = 28;
static constexpr ck::index_t Ho = 28; static constexpr ck::index_t Ho = 28;
static constexpr ck::index_t Wo = 3; static constexpr ck::index_t Wo = 3;
static constexpr std::array<ck::index_t, NumDimSpatial> input_spatial_lengths{Di, Hi, Wi};
static constexpr std::array<ck::index_t, NumDimSpatial> filter_spatial_lengths{Z, Y, X};
static constexpr std::array<ck::index_t, NumDimSpatial> output_spatial_lengths{Do, Ho, Wo};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> input_strides{
N * Di * Hi * Wi * C, Di* Hi* Wi* C, Hi* Wi* C, Wi* C, C, 1};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> output_strides{
N * Do * Ho * Wo * K, Do* Ho* Wo* K, Ho* Wo* K, Wo* K, K, 1};
static constexpr std::array<ck::index_t, NumDimSpatial> conv_filter_strides{1, 1, 1};
static constexpr std::array<ck::index_t, NumDimSpatial> conv_filter_dilations{1, 1, 1};
static constexpr std::array<ck::index_t, NumDimSpatial> input_left_pads{1, 1, 1};
static constexpr std::array<ck::index_t, NumDimSpatial> input_right_pads{1, 1, 1};
int main() int main()
{ {
...@@ -41,13 +52,15 @@ int main() ...@@ -41,13 +52,15 @@ int main()
N, N,
K, K,
C, C,
{Di, Hi, Wi}, input_spatial_lengths,
{Z, Y, X}, filter_spatial_lengths,
{Do, Ho, Wo}, output_spatial_lengths,
{1, 1, 1}, input_strides,
{1, 1, 1}, output_strides,
{1, 1, 1}, conv_filter_strides,
{1, 1, 1}) conv_filter_dilations,
input_left_pads,
input_right_pads)
? EXIT_SUCCESS ? EXIT_SUCCESS
: EXIT_FAILURE; : EXIT_FAILURE;
} }
client_example/11_grouped_conv_bwd_weight/grouped_conv3d_bwd_weight_fp32.cpp
View file @ ad2fddf4
...@@ -28,6 +28,17 @@ static constexpr ck::index_t Wi = 3; ...@@ -28,6 +28,17 @@ static constexpr ck::index_t Wi = 3;
static constexpr ck::index_t Do = 28; static constexpr ck::index_t Do = 28;
static constexpr ck::index_t Ho = 28; static constexpr ck::index_t Ho = 28;
static constexpr ck::index_t Wo = 3; static constexpr ck::index_t Wo = 3;
static constexpr std::array<ck::index_t, NumDimSpatial> input_spatial_lengths{Di, Hi, Wi};
static constexpr std::array<ck::index_t, NumDimSpatial> filter_spatial_lengths{Z, Y, X};
static constexpr std::array<ck::index_t, NumDimSpatial> output_spatial_lengths{Do, Ho, Wo};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> input_strides{
N * Di * Hi * Wi * C, Di* Hi* Wi* C, Hi* Wi* C, Wi* C, C, 1};
static constexpr std::array<ck::index_t, NumDimSpatial + 3> output_strides{
N * Do * Ho * Wo * K, Do* Ho* Wo* K, Ho* Wo* K, Wo* K, K, 1};
static constexpr std::array<ck::index_t, NumDimSpatial> conv_filter_strides{1, 1, 1};
static constexpr std::array<ck::index_t, NumDimSpatial> conv_filter_dilations{1, 1, 1};
static constexpr std::array<ck::index_t, NumDimSpatial> input_left_pads{1, 1, 1};
static constexpr std::array<ck::index_t, NumDimSpatial> input_right_pads{1, 1, 1};
int main() int main()
{ {
...@@ -37,17 +48,20 @@ int main() ...@@ -37,17 +48,20 @@ int main()
OutDataType, OutDataType,
InLayout, InLayout,
WeiLayout, WeiLayout,
OutLayout>(G, OutLayout>(
N, G,
K, N,
C, K,
{Di, Hi, Wi}, C,
{Z, Y, X}, {Di, Hi, Wi},
{Do, Ho, Wo}, {Z, Y, X},
{1, 1, 1}, {Do, Ho, Wo},
{1, 1, 1}, {N * Di * Hi * Wi * C, Di * Hi * Wi * C, Hi * Wi * C, Wi * C, C, 1},
{1, 1, 1}, {N * Do * Ho * Wo * K, Do * Ho * Wo * K, Ho * Wo * K, Wo * K, K, 1},
{1, 1, 1}) {1, 1, 1},
{1, 1, 1},
{1, 1, 1},
{1, 1, 1})
? EXIT_SUCCESS ? EXIT_SUCCESS
: EXIT_FAILURE; : EXIT_FAILURE;
} }
example/01_gemm/CMakeLists.txt
View file @ ad2fddf4
...@@ -44,3 +44,7 @@ if(GPU_TARGETS MATCHES "gfx1100" OR GPU_TARGETS MATCHES "gfx1101" OR GPU_TARGETS ...@@ -44,3 +44,7 @@ if(GPU_TARGETS MATCHES "gfx1100" OR GPU_TARGETS MATCHES "gfx1101" OR GPU_TARGETS
add_dependencies(example_gemm_wmma example_gemm_wmma_fp16) add_dependencies(example_gemm_wmma example_gemm_wmma_fp16)
endif() endif()
if(GPU_TARGETS MATCHES "gfx940" OR GPU_TARGETS MATCHES "gfx941" OR GPU_TARGETS MATCHES "gfx942")
add_example_executable(example_gemm_xdl_f8 gemm_xdl_f8.cpp)
add_dependencies(example_gemm_xdl example_gemm_xdl_f8)
endif()
example/01_gemm/gemm_xdl_f8.cpp 0 → 100644
View file @ ad2fddf4
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
#include "common.hpp"
#include "ck/tensor_operation/gpu/device/impl/device_gemm_xdl_cshuffle.hpp"
using ADataType = ck::f8_t;
using BDataType = ck::f8_t;
using CDataType = ck::f8_t;
using AccDataType = float;
using CShuffleDataType = ck::f8_t;
using ALayout = Row;
using BLayout = Col;
using CLayout = Row;
using AElementOp = PassThrough;
using BElementOp = PassThrough;
using CElementOp = PassThrough;
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
// clang-format off
using DeviceGemmInstance = ck::tensor_operation::device::DeviceGemm_Xdl_CShuffle
// ######| ALayout| BLayout| CLayout| AData| BData| CData| AccData| CShuffle| A| B| C| GEMM| NumGemmK| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CBlockTransfer|
// ######| | | | Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| Spacialization| Prefetch| Size| Block| Block| Block| | | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MWaveMPerXdl| ScalarPerVector|
// ######| | | | | | | | | Operation| Operation| Operation| | Stage| | | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NWaveNPerXdl| _NWaveNPerXdl|
// ######| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
< ALayout, BLayout, CLayout, ADataType, BDataType, CDataType, AccDataType, CShuffleDataType, AElementOp, BElementOp, CElementOp, GemmDefault, 1, 256, 256, 128, 64, 16, 16, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 64, 1, 4>, 16>;
// clang-format on
using ReferenceGemmInstance = ck::tensor_operation::host::
ReferenceGemm<ADataType, BDataType, CDataType, AccDataType, AElementOp, BElementOp, CElementOp>;
#include "run_gemm_example.inc"
int main(int argc, char* argv[]) { return !run_gemm_example(argc, argv); }
example/01_gemm/gemm_xdl_wavelet_fp16.cpp
View file @ ad2fddf4
...@@ -3,7 +3,7 @@ ...@@ -3,7 +3,7 @@
#include "common.hpp" #include "common.hpp"
#include "ck/tensor_operation/gpu/device/device_gemm_xdl_waveletmodel_cshuffle.hpp" #include "ck/tensor_operation/gpu/device/impl/device_gemm_xdl_waveletmodel_cshuffle.hpp"
using ADataType = ck::half_t; using ADataType = ck::half_t;
using BDataType = ck::half_t; using BDataType = ck::half_t;
......
example/09_convnd_fwd/convnd_fwd_dl_fp16.cpp
View file @ ad2fddf4
...@@ -3,7 +3,7 @@ ...@@ -3,7 +3,7 @@
#include "convnd_fwd_dl_common.hpp" #include "convnd_fwd_dl_common.hpp"
#include "ck/tensor_operation/gpu/device/device_grouped_conv_fwd_dl_multiple_d_nhwc_kyxc_nhwk.hpp" #include "ck/tensor_operation/gpu/device/impl/device_grouped_conv_fwd_dl_multiple_d_nhwc_kyxc_nhwk.hpp"
#include "ck/library/utility/convolution_host_tensor_descriptor_helper.hpp" #include "ck/library/utility/convolution_host_tensor_descriptor_helper.hpp"
......
example/09_convnd_fwd/convnd_fwd_dl_fp32.cpp
View file @ ad2fddf4
...@@ -3,7 +3,7 @@ ...@@ -3,7 +3,7 @@
#include "convnd_fwd_dl_common.hpp" #include "convnd_fwd_dl_common.hpp"
#include "ck/tensor_operation/gpu/device/device_grouped_conv_fwd_dl_multiple_d_nhwc_kyxc_nhwk.hpp" #include "ck/tensor_operation/gpu/device/impl/device_grouped_conv_fwd_dl_multiple_d_nhwc_kyxc_nhwk.hpp"
#include "ck/library/utility/convolution_host_tensor_descriptor_helper.hpp" #include "ck/library/utility/convolution_host_tensor_descriptor_helper.hpp"
......
example/09_convnd_fwd/convnd_fwd_dl_int8.cpp
View file @ ad2fddf4
...@@ -3,7 +3,7 @@ ...@@ -3,7 +3,7 @@
#include "convnd_fwd_dl_common.hpp" #include "convnd_fwd_dl_common.hpp"
#include "ck/tensor_operation/gpu/device/device_grouped_conv_fwd_dl_multiple_d_nhwc_kyxc_nhwk.hpp" #include "ck/tensor_operation/gpu/device/impl/device_grouped_conv_fwd_dl_multiple_d_nhwc_kyxc_nhwk.hpp"
#include "ck/library/utility/convolution_host_tensor_descriptor_helper.hpp" #include "ck/library/utility/convolution_host_tensor_descriptor_helper.hpp"
......
example/20_grouped_conv_bwd_weight/grouped_conv_bwd_weight_xdl_bf16.cpp
View file @ ad2fddf4
...@@ -3,7 +3,7 @@ ...@@ -3,7 +3,7 @@
#include "common.hpp" #include "common.hpp"
#include "ck/tensor_operation/gpu/device/impl/device_grouped_conv_bwd_weight_gnwc_gkxc_gnwk_xdl_cshuffle.hpp" #include "ck/tensor_operation/gpu/device/impl/device_grouped_conv_bwd_weight_xdl_cshuffle.hpp"
using InDataType = BF16; using InDataType = BF16;
// bf16 kernel use fp32 atomic add to accumulate Weight tensor into global memory // bf16 kernel use fp32 atomic add to accumulate Weight tensor into global memory
...@@ -17,8 +17,20 @@ using OutElementOp = PassThrough; ...@@ -17,8 +17,20 @@ using OutElementOp = PassThrough;
template <ck::index_t NDimSpatial> template <ck::index_t NDimSpatial>
using DeviceConvBwdWeightInstance = using DeviceConvBwdWeightInstance =
ck::tensor_operation::device::DeviceGroupedConvBwdWeightGnwcGkxcGnwk_Xdl_CShuffle< ck::tensor_operation::device::DeviceGroupedConvBwdWeight_Xdl_CShuffle<
NDimSpatial, // NDimSpatial NDimSpatial,
ck::tuple_element_t<NDimSpatial - 1,
ck::Tuple<ck::tensor_layout::convolution::GNWC,
ck::tensor_layout::convolution::GNHWC,
ck::tensor_layout::convolution::GNDHWC>>,
ck::tuple_element_t<NDimSpatial - 1,
ck::Tuple<ck::tensor_layout::convolution::GKXC,
ck::tensor_layout::convolution::GKYXC,
ck::tensor_layout::convolution::GKZYXC>>,
ck::tuple_element_t<NDimSpatial - 1,
ck::Tuple<ck::tensor_layout::convolution::GNWK,
ck::tensor_layout::convolution::GNHWK,
ck::tensor_layout::convolution::GNDHWK>>,
InDataType, // InDataType InDataType, // InDataType
WeiDataType, // WeiDataType WeiDataType, // WeiDataType
OutDataType, // OutDataType OutDataType, // OutDataType
......
example/20_grouped_conv_bwd_weight/grouped_conv_bwd_weight_xdl_fp16.cpp
View file @ ad2fddf4
...@@ -3,7 +3,7 @@ ...@@ -3,7 +3,7 @@
#include "common.hpp" #include "common.hpp"
#include "ck/tensor_operation/gpu/device/impl/device_grouped_conv_bwd_weight_gnwc_gkxc_gnwk_xdl_cshuffle.hpp" #include "ck/tensor_operation/gpu/device/impl/device_grouped_conv_bwd_weight_xdl_cshuffle.hpp"
using InDataType = F16; using InDataType = F16;
using WeiDataType = F16; using WeiDataType = F16;
...@@ -16,8 +16,20 @@ using OutElementOp = PassThrough; ...@@ -16,8 +16,20 @@ using OutElementOp = PassThrough;
template <ck::index_t NDimSpatial> template <ck::index_t NDimSpatial>
using DeviceConvBwdWeightInstance = using DeviceConvBwdWeightInstance =
ck::tensor_operation::device::DeviceGroupedConvBwdWeightGnwcGkxcGnwk_Xdl_CShuffle< ck::tensor_operation::device::DeviceGroupedConvBwdWeight_Xdl_CShuffle<
NDimSpatial, // NDimSpatial NDimSpatial,
ck::tuple_element_t<NDimSpatial - 1,
ck::Tuple<ck::tensor_layout::convolution::GNWC,
ck::tensor_layout::convolution::GNHWC,
ck::tensor_layout::convolution::GNDHWC>>,
ck::tuple_element_t<NDimSpatial - 1,
ck::Tuple<ck::tensor_layout::convolution::GKXC,
ck::tensor_layout::convolution::GKYXC,
ck::tensor_layout::convolution::GKZYXC>>,
ck::tuple_element_t<NDimSpatial - 1,
ck::Tuple<ck::tensor_layout::convolution::GNWK,
ck::tensor_layout::convolution::GNHWK,
ck::tensor_layout::convolution::GNDHWK>>,
InDataType, // InDataType InDataType, // InDataType
WeiDataType, // WeiDataType WeiDataType, // WeiDataType
OutDataType, // OutDataType OutDataType, // OutDataType
......
example/20_grouped_conv_bwd_weight/run_grouped_conv_bwd_weight_example.inc
View file @ ad2fddf4
...@@ -75,6 +75,8 @@ bool run_grouped_conv_bwd_weight(const ExecutionConfig& config, ...@@ -75,6 +75,8 @@ bool run_grouped_conv_bwd_weight(const ExecutionConfig& config,
std::array<ck::index_t, NDimSpatial> input_spatial_lengths{}; std::array<ck::index_t, NDimSpatial> input_spatial_lengths{};
std::array<ck::index_t, NDimSpatial> filter_spatial_lengths{}; std::array<ck::index_t, NDimSpatial> filter_spatial_lengths{};
std::array<ck::index_t, NDimSpatial> output_spatial_lengths{}; std::array<ck::index_t, NDimSpatial> output_spatial_lengths{};
std::array<ck::index_t, NDimSpatial + 3> input_strides{};
std::array<ck::index_t, NDimSpatial + 3> output_strides{};
std::array<ck::index_t, NDimSpatial> conv_filter_strides{}; std::array<ck::index_t, NDimSpatial> conv_filter_strides{};
std::array<ck::index_t, NDimSpatial> conv_filter_dilations{}; std::array<ck::index_t, NDimSpatial> conv_filter_dilations{};
std::array<ck::index_t, NDimSpatial> input_left_pads{}; std::array<ck::index_t, NDimSpatial> input_left_pads{};
...@@ -85,6 +87,8 @@ bool run_grouped_conv_bwd_weight(const ExecutionConfig& config, ...@@ -85,6 +87,8 @@ bool run_grouped_conv_bwd_weight(const ExecutionConfig& config,
range_copy(conv_param.input_spatial_lengths_, begin(input_spatial_lengths)); range_copy(conv_param.input_spatial_lengths_, begin(input_spatial_lengths));
range_copy(conv_param.filter_spatial_lengths_, begin(filter_spatial_lengths)); range_copy(conv_param.filter_spatial_lengths_, begin(filter_spatial_lengths));
range_copy(conv_param.output_spatial_lengths_, begin(output_spatial_lengths)); range_copy(conv_param.output_spatial_lengths_, begin(output_spatial_lengths));
range_copy(in_g_n_c_wis_desc.GetStrides(), begin(input_strides));
range_copy(out_g_n_k_wos_desc.GetStrides(), begin(output_strides));
range_copy(conv_param.conv_filter_strides_, begin(conv_filter_strides)); range_copy(conv_param.conv_filter_strides_, begin(conv_filter_strides));
range_copy(conv_param.conv_filter_dilations_, begin(conv_filter_dilations)); range_copy(conv_param.conv_filter_dilations_, begin(conv_filter_dilations));
range_copy(conv_param.input_left_pads_, begin(input_left_pads)); range_copy(conv_param.input_left_pads_, begin(input_left_pads));
...@@ -103,6 +107,8 @@ bool run_grouped_conv_bwd_weight(const ExecutionConfig& config, ...@@ -103,6 +107,8 @@ bool run_grouped_conv_bwd_weight(const ExecutionConfig& config,
input_spatial_lengths, input_spatial_lengths,
filter_spatial_lengths, filter_spatial_lengths,
output_spatial_lengths, output_spatial_lengths,
input_strides,
output_strides,
conv_filter_strides, conv_filter_strides,
conv_filter_dilations, conv_filter_dilations,
input_left_pads, input_left_pads,
......
example/32_batched_gemm_scale_softmax_gemm/grouped_gemm_lower_triangle_scale_softmax_gemm_permute_xdl_fp16.cpp
View file @ ad2fddf4
...@@ -17,7 +17,7 @@ Gemm + Softmax + Gemm fused operation. Computes C_g_m_o = Softmax(A_g_m_k * B0_g ...@@ -17,7 +17,7 @@ Gemm + Softmax + Gemm fused operation. Computes C_g_m_o = Softmax(A_g_m_k * B0_g
#include "ck/ck.hpp" #include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp" #include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/tensor_specialization.hpp" #include "ck/tensor_operation/gpu/device/tensor_specialization.hpp"
#include "ck/tensor_operation/gpu/device/device_grouped_gemm_softmax_gemm_permute_xdl_cshuffle.hpp" #include "ck/tensor_operation/gpu/device/impl/device_grouped_gemm_softmax_gemm_permute_xdl_cshuffle.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp" #include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/utility/check_err.hpp" #include "ck/library/utility/check_err.hpp"
......
example/32_batched_gemm_scale_softmax_gemm/grouped_gemm_scale_softmax_gemm_permute_xdl_fp16.cpp
View file @ ad2fddf4
...@@ -17,7 +17,7 @@ Gemm + Softmax + Gemm fused operation. Computes C_g_m_o = Softmax(A_g_m_k * B0_g ...@@ -17,7 +17,7 @@ Gemm + Softmax + Gemm fused operation. Computes C_g_m_o = Softmax(A_g_m_k * B0_g
#include "ck/ck.hpp" #include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp" #include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/tensor_specialization.hpp" #include "ck/tensor_operation/gpu/device/tensor_specialization.hpp"
#include "ck/tensor_operation/gpu/device/device_grouped_gemm_softmax_gemm_permute_xdl_cshuffle.hpp" #include "ck/tensor_operation/gpu/device/impl/device_grouped_gemm_softmax_gemm_permute_xdl_cshuffle.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp" #include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/utility/check_err.hpp" #include "ck/library/utility/check_err.hpp"
......
example/34_batchnorm/CMakeLists.txt
View file @ ad2fddf4
add_example_executable(example_batchnorm_forward_training batchnorm_forward_training_nhwc.cpp) add_example_executable(example_batchnorm_forward_training batchnorm_forward_training_nhwc.cpp)
add_example_executable(example_batchnorm_forward_training_obsolete batchnorm_forward_training_nhwc_obsolete.cpp)
add_example_executable(example_batchnorm_forward_inferring batchnorm_forward_inferring_nhwc.cpp) add_example_executable(example_batchnorm_forward_inferring batchnorm_forward_inferring_nhwc.cpp)
add_example_executable(example_batchnorm_backward batchnorm_backward_nhwc.cpp) add_example_executable(example_batchnorm_backward batchnorm_backward_nhwc.cpp)
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