Refactor pool fwd (#815)

* Do not hardcode stride

* devicePool2DFwd Inherit devicePool3DFwd

* Move instance declaration out of common

* Add dilation

* use the pool3d rank, because pool2d inherit pooo3d

* calculate Do Ho Wo for the dilation

* Fix header name

* Modify ckProfiler

* Remove pool2d instance

* Remove pool2d in profiler

* Remove pool2d and add dilation

* In to client example, this commit revise following:
1. Add dilation.
2. Use pool3d to implement pool2d

* Refine naming and IsSupportedArgument()

* Add dilation to maxpool bwd example

* clang format

* 1. Remove useless header
2. Fix copyright
3. Refine naming

* Add layout parameter to pool fwd

* clang format

* Fix merge error

* Fix compile error

* Remove layout parameter in derived class

* Refine changlog

* Fix compile error

* Fix compiler error

* Add layout to external api and profiler

[ROCm/composable_kernel commit: f60f0a5e03]
This commit is contained in:
rocking
2023-08-15 02:25:28 +08:00
committed by GitHub
parent 759fb65188
commit 4ee825732f
41 changed files with 824 additions and 1574 deletions

View File

@@ -17,7 +17,6 @@ set(PROFILER_SOURCES
profile_reduce.cpp
profile_groupnorm.cpp
profile_layernorm.cpp
profile_avg_pool2d_fwd.cpp
profile_max_pool3d_fwd.cpp
profile_softmax.cpp
profile_batchnorm_fwd.cpp
@@ -74,7 +73,7 @@ target_link_libraries(${PROFILER_EXECUTABLE} PRIVATE device_reduce_instance)
target_link_libraries(${PROFILER_EXECUTABLE} PRIVATE device_batchnorm_instance)
target_link_libraries(${PROFILER_EXECUTABLE} PRIVATE device_contraction_bilinear_instance)
target_link_libraries(${PROFILER_EXECUTABLE} PRIVATE device_contraction_scale_instance)
target_link_libraries(${PROFILER_EXECUTABLE} PRIVATE device_pool_fwd_instance)
target_link_libraries(${PROFILER_EXECUTABLE} PRIVATE device_pool3d_fwd_instance)
target_link_libraries(${PROFILER_EXECUTABLE} PRIVATE device_grouped_conv2d_bwd_data_instance)
target_link_libraries(${PROFILER_EXECUTABLE} PRIVATE device_grouped_conv3d_bwd_data_instance)
if(DL_KERNELS)

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@@ -1,141 +0,0 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
#include <iostream>
#include <vector>
#include <unordered_map>
#include "profiler/data_type_enum.hpp"
#include "profiler/profile_pool2d_fwd_impl.hpp"
#include "profiler_operation_registry.hpp"
using ck::index_t;
struct avgPoolFwdArgParser
{
std::unordered_map<std::string, std::vector<int>> long_opts = {
{"length", {}}, {"wsize", {}}, {"wstride", {}}, {"pad1", {}}, {"pad2", {}}};
bool parse_opt(int argc, char* argv[], const std::string& key, int i)
{
if(std::string("--") + key == argv[i])
{
int pos = i;
while(++i < argc && argv[i][0] != '-') {}
int end = i;
for(int j = pos + 1; j < end; j++)
{
long_opts[key].push_back(std::stoi(argv[j]));
}
return true;
}
return false;
}
void operator()(int argc, char* argv[])
{
for(auto& kv : long_opts)
{
for(int i = 1; i < argc; i++)
{
if(parse_opt(argc, argv, kv.first, i))
break;
}
}
}
};
void print_help_avg_pool2d_fwd()
{
std::cout << "arg1: data type (0: fp16; 1: fp32)\n"
<< "arg2: verification (0: no; 1: yes)\n"
<< "arg3: initialization (0: no init; 1: integer value; 2: decimal value)\n"
<< "arg4: print tensor value (0: no; 1: yes)\n"
<< "arg5: time kernel (0=no, 1=yes)\n"
<< "--length: input tensor length for NDHW(e.g, --length 2 32 30 30) \n"
<< "--wsize: window size for YX (e.g, --wsize 2 2) \n"
<< "--wstride: window stride for HW (e.g, --wstride 2 2) \n"
<< "--pad1: left side of padding in HW (e.g, --pad1 1 1) \n"
<< "--pad2: right side of padding in HW (e.g, --pad2 1 1) \n"
<< "eg: ckProfiler avg_pool2d_fwd 0 1 2 0 1 0 --length 2 32 30 30 --wsize 2 2 "
"--wstride 2 2 --pad1 1 1 --pad2 1 1"
<< std::endl;
}
int profile_avg_pool2d_fwd(int argc, char* argv[])
{
ck::DataTypeEnum data_type = ck::DataTypeEnum::Half;
bool do_verification = true;
int init_method = 0;
bool do_log = false;
bool time_kernel = true;
std::vector<index_t> in_length = {2, 32, 30, 30};
std::vector<index_t> wsize = {2, 2};
std::vector<index_t> wstride = {2, 2};
std::vector<index_t> pad1 = {1, 1};
std::vector<index_t> pad2 = {1, 1};
if(argc != 2 && argc != 25)
{
print_help_avg_pool2d_fwd();
return 0;
}
else if(argc == 25)
{
data_type = static_cast<ck::DataTypeEnum>(std::stoi(argv[2]));
do_verification = std::stoi(argv[3]);
init_method = std::stoi(argv[4]);
do_log = std::stoi(argv[5]);
time_kernel = std::stoi(argv[6]);
// parse the long options
avgPoolFwdArgParser arg_parser;
arg_parser(argc, argv);
in_length = arg_parser.long_opts["length"];
wsize = arg_parser.long_opts["wsize"];
wstride = arg_parser.long_opts["wstride"];
pad1 = arg_parser.long_opts["pad1"];
pad2 = arg_parser.long_opts["pad2"];
}
using F16 = ck::half_t;
using F32 = float;
using I32 = int32_t;
constexpr auto ReduceOpId = ck::ReduceTensorOp::AVG;
if(data_type == ck::DataTypeEnum::Half)
{
ck::profiler::profile_pool2d_fwd_impl<F16, F16, F32, I32, ReduceOpId, false, false>(
do_verification,
init_method,
do_log,
time_kernel,
in_length,
wsize,
wstride,
pad1,
pad2);
}
else if(data_type == ck::DataTypeEnum::Float)
{
ck::profiler::profile_pool2d_fwd_impl<F32, F32, F32, I32, ReduceOpId, false, false>(
do_verification,
init_method,
do_log,
time_kernel,
in_length,
wsize,
wstride,
pad1,
pad2);
}
else
{
throw std::runtime_error("not implemented yet");
}
return 0;
}
REGISTER_PROFILER_OPERATION("avg_pool2d_fwd", "avg_pool2d fwd", profile_avg_pool2d_fwd);

View File

@@ -13,8 +13,12 @@ using ck::index_t;
struct maxPoolFwdArgParser
{
std::unordered_map<std::string, std::vector<int>> long_opts = {
{"length", {}}, {"wsize", {}}, {"wstride", {}}, {"pad1", {}}, {"pad2", {}}};
std::unordered_map<std::string, std::vector<int>> long_opts = {{"length", {}},
{"wsize", {}},
{"wstride", {}},
{"wdilation", {}},
{"pad1", {}},
{"pad2", {}}};
bool parse_opt(int argc, char* argv[], const std::string& key, int i)
{
@@ -56,10 +60,11 @@ void print_help_max_pool3d_fwd()
<< "--length: input tensor length for NCDHW(e.g, --length 2 32 30 30 30) \n"
<< "--wsize: window size for ZYX (e.g, --wsize 2 2 2) \n"
<< "--wstride: window stride for DHW (e.g, --wstride 2 2 2) \n"
<< "--wdilation: window dilation for DHW (e.g, --wdilation 1 1 1) \n"
<< "--pad1: left side of padding in DHW (e.g, --pad1 1 1 1) \n"
<< "--pad2: right side of padding in DHW (e.g, --pad2 1 1 1) \n"
<< "eg: ckProfiler max_pool3d_fwd 0 1 2 0 1 0 --length 2 32 30 30 30 --wsize 2 2 2 "
"--wstride 2 2 2 --pad1 1 1 1 --pad2 1 1 1"
"--wstride 2 2 2 --wdilation 1 1 1 --pad1 1 1 1 --pad2 1 1 1"
<< std::endl;
}
@@ -75,15 +80,16 @@ int profile_max_pool3d_fwd(int argc, char* argv[])
std::vector<index_t> in_length = {2, 32, 30, 30, 30};
std::vector<index_t> wsize = {2, 2, 2};
std::vector<index_t> wstride = {2, 2, 2};
std::vector<index_t> wdilation = {1, 1, 1};
std::vector<index_t> pad1 = {1, 1, 1};
std::vector<index_t> pad2 = {1, 1, 1};
if(argc != 2 && argc != 30)
if(argc != 2 && argc != 34)
{
print_help_max_pool3d_fwd();
return 0;
}
else if(argc == 30)
else if(argc == 34)
{
data_type = static_cast<ck::DataTypeEnum>(std::stoi(argv[2]));
do_verification = std::stoi(argv[3]);
@@ -98,64 +104,79 @@ int profile_max_pool3d_fwd(int argc, char* argv[])
in_length = arg_parser.long_opts["length"];
wsize = arg_parser.long_opts["wsize"];
wstride = arg_parser.long_opts["wstride"];
wdilation = arg_parser.long_opts["wdilation"];
pad1 = arg_parser.long_opts["pad1"];
pad2 = arg_parser.long_opts["pad2"];
}
using F16 = ck::half_t;
using F32 = float;
using I32 = int32_t;
using F16 = ck::half_t;
using F32 = float;
using I32 = int32_t;
using NDHWC = ck::tensor_layout::convolution::NDHWC;
#if 1
constexpr auto ReduceOpId = ck::ReduceTensorOp::MAX;
#else
constexpr auto ReduceOpId = ck::ReduceTensorOp::AVG;
#endif
if(data_type == ck::DataTypeEnum::Half)
{
if(return_index)
ck::profiler::profile_pool3d_fwd_impl<F16, F16, F16, I32, ReduceOpId, false, true>(
do_verification,
init_method,
do_log,
time_kernel,
in_length,
wsize,
wstride,
pad1,
pad2);
ck::profiler::
profile_pool3d_fwd_impl<F16, F16, F16, I32, NDHWC, NDHWC, ReduceOpId, false, true>(
do_verification,
init_method,
do_log,
time_kernel,
in_length,
wsize,
wstride,
wdilation,
pad1,
pad2);
else
ck::profiler::profile_pool3d_fwd_impl<F16, F16, F16, I32, ReduceOpId, false, false>(
do_verification,
init_method,
do_log,
time_kernel,
in_length,
wsize,
wstride,
pad1,
pad2);
ck::profiler::
profile_pool3d_fwd_impl<F16, F16, F16, I32, NDHWC, NDHWC, ReduceOpId, false, false>(
do_verification,
init_method,
do_log,
time_kernel,
in_length,
wsize,
wstride,
wdilation,
pad1,
pad2);
}
else if(data_type == ck::DataTypeEnum::Float)
{
if(return_index)
ck::profiler::profile_pool3d_fwd_impl<F32, F32, F32, I32, ReduceOpId, false, true>(
do_verification,
init_method,
do_log,
time_kernel,
in_length,
wsize,
wstride,
pad1,
pad2);
ck::profiler::
profile_pool3d_fwd_impl<F32, F32, F32, I32, NDHWC, NDHWC, ReduceOpId, false, true>(
do_verification,
init_method,
do_log,
time_kernel,
in_length,
wsize,
wstride,
wdilation,
pad1,
pad2);
else
ck::profiler::profile_pool3d_fwd_impl<F32, F32, F32, I32, ReduceOpId, false, false>(
do_verification,
init_method,
do_log,
time_kernel,
in_length,
wsize,
wstride,
pad1,
pad2);
ck::profiler::
profile_pool3d_fwd_impl<F32, F32, F32, I32, NDHWC, NDHWC, ReduceOpId, false, false>(
do_verification,
init_method,
do_log,
time_kernel,
in_length,
wsize,
wstride,
wdilation,
pad1,
pad2);
}
else
{