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Pool3d fwd (#697)

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* Expand the base class of pool2d, prepare to share base class with pool3d

* Add pool3d device op

* Add pool3d f16 example

* Refactor the base class. implement generic pooling in the future

* clang format

* get original index in max pooling

* Add outputindex to base class

* Fix dimension

* Add pooling instance

* Use indexType instead

* Remove useless header

* Extract IndexDataType to template

* Extract pooling reference code

* clang format

* clang format

* Fix typo

* Add tensor stride

* Add missing header

* Add index stride and output stride

* Refine naming

* Add type to base class

* Rename file

* Use proper size

* Fix typo

* Refine naming

* Modify the argument into vector.

* Add max pool profiler

* Refine naming

* Support f32 pool

* Fix typo

* Add avg pool2d fwd in profiler

* clang format

* Rename AccDatatype to ComputeDatatype

* Fix init

* test pool

* Extract variable

* Add client example

* Check the pooling dim

* clang format

* Connect argv and arg_parser

* Add found check

* Remove useless header

* Refine naming

* Adjust the order of device_pool_fwd
This commit is contained in:
rocking
2023-05-24 22:05:04 +08:00
committed by GitHub
parent d821d1e54f
commit 76ec0089fb
44 changed files with 3226 additions and 241 deletions
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16
test/pool_fwd/CMakeLists.txt Normal file
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add_custom_target(test_pool_fwd)
add_gtest_executable(test_avg_pool2d_fwd test_avg_pool2d_fwd.cpp)
add_gtest_executable(test_avg_pool3d_fwd test_avg_pool3d_fwd.cpp)
add_gtest_executable(test_max_pool2d_fwd test_max_pool2d_fwd.cpp)
add_gtest_executable(test_max_pool3d_fwd test_max_pool3d_fwd.cpp)
target_link_libraries(test_avg_pool2d_fwd PRIVATE utility device_pool_fwd_instance)
target_link_libraries(test_avg_pool3d_fwd PRIVATE utility device_pool_fwd_instance)
target_link_libraries(test_max_pool2d_fwd PRIVATE utility device_pool_fwd_instance)
target_link_libraries(test_max_pool3d_fwd PRIVATE utility device_pool_fwd_instance)
add_dependencies(test_pool_fwd test_avg_pool2d_fwd)
add_dependencies(test_pool_fwd test_avg_pool3d_fwd)
add_dependencies(test_pool_fwd test_max_pool2d_fwd)
add_dependencies(test_pool_fwd test_max_pool3d_fwd)

56
test/pool_fwd/test_avg_pool2d_fwd.cpp Normal file
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// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include "gtest/gtest.h"
#include "profiler/profile_pool2d_fwd_impl.hpp"
#include "test_pool_fwd_common.hpp"
template <typename Tuple>
class TestAvgPool2dFwd : public ::testing::Test
{
protected:
using InDataType = std::tuple_element_t<0, Tuple>;
using OutDataType = std::tuple_element_t<1, Tuple>;
using ComputeDataType = std::tuple_element_t<2, Tuple>;
using IndexDataType = std::tuple_element_t<3, Tuple>;
std::vector<PoolingParam> params;
void Run()
{
for(auto param : params)
{
bool success =
ck::profiler::profile_pool2d_fwd_impl<InDataType,
OutDataType,
ComputeDataType,
IndexDataType,
ck::ReduceTensorOp::AVG,
false,
false>(true,
2,
false,
false,
param.length_,
param.window_spatial_lengths_,
param.window_strides_,
param.input_left_pads_,
param.input_right_pads_);
EXPECT_TRUE(success);
}
}
};
using KernelTypes =
::testing::Types<std::tuple<F16, F16, F32, I32>, std::tuple<F32, F32, F32, I32>>;
TYPED_TEST_SUITE(TestAvgPool2dFwd, KernelTypes);
TYPED_TEST(TestAvgPool2dFwd, Test_Pool)
{
// length, window_length, window_stride, left_pad, right_pad
this->params = {{{1, 1, 1, 1}, {1, 1}, {1, 1}, {0, 0}, {0, 0}},
{{2, 16, 64, 64}, {64, 64}, {1, 1}, {0, 0}, {0, 0}},
{{2, 32, 30, 30}, {2, 2}, {2, 2}, {1, 1}, {1, 1}}};
this->Run();
}

56
test/pool_fwd/test_avg_pool3d_fwd.cpp Normal file
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// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include "gtest/gtest.h"
#include "profiler/profile_pool3d_fwd_impl.hpp"
#include "test_pool_fwd_common.hpp"
template <typename Tuple>
class TestAvgPool3dFwd : public ::testing::Test
{
protected:
using InDataType = std::tuple_element_t<0, Tuple>;
using OutDataType = std::tuple_element_t<1, Tuple>;
using ComputeDataType = std::tuple_element_t<2, Tuple>;
using IndexDataType = std::tuple_element_t<3, Tuple>;
std::vector<PoolingParam> params;
void Run()
{
for(auto param : params)
{
bool success =
ck::profiler::profile_pool3d_fwd_impl<InDataType,
OutDataType,
ComputeDataType,
IndexDataType,
ck::ReduceTensorOp::AVG,
false,
false>(true,
2,
false,
false,
param.length_,
param.window_spatial_lengths_,
param.window_strides_,
param.input_left_pads_,
param.input_right_pads_);
EXPECT_TRUE(success);
}
}
};
using KernelTypes =
::testing::Types<std::tuple<F16, F16, F32, I32>, std::tuple<F32, F32, F32, I32>>;
TYPED_TEST_SUITE(TestAvgPool3dFwd, KernelTypes);
TYPED_TEST(TestAvgPool3dFwd, Test_Pool)
{
// length, window_length, window_stride, left_pad, right_pad
this->params = {{{1, 1, 1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {0, 0, 0}, {0, 0, 0}},
{{2, 16, 64, 64, 64}, {64, 64, 64}, {1, 1, 1}, {0, 0, 0}, {0, 0, 0}},
{{2, 32, 30, 30, 30}, {2, 2, 2}, {2, 2, 2}, {1, 1, 1}, {1, 1, 1}}};
this->Run();
}

75
test/pool_fwd/test_max_pool2d_fwd.cpp Normal file
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// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include "gtest/gtest.h"
#include "profiler/profile_pool2d_fwd_impl.hpp"
#include "test_pool_fwd_common.hpp"
template <typename Tuple>
class TestMaxPool2dFwd : public ::testing::Test
{
protected:
using InDataType = std::tuple_element_t<0, Tuple>;
using OutDataType = std::tuple_element_t<1, Tuple>;
using ComputeDataType = std::tuple_element_t<2, Tuple>;
using IndexDataType = std::tuple_element_t<3, Tuple>;
std::vector<PoolingParam> params;
void Run()
{
for(auto param : params)
{
// max pool
bool success =
ck::profiler::profile_pool2d_fwd_impl<InDataType,
OutDataType,
ComputeDataType,
IndexDataType,
ck::ReduceTensorOp::MAX,
false,
false>(true,
2,
false,
false,
param.length_,
param.window_spatial_lengths_,
param.window_strides_,
param.input_left_pads_,
param.input_right_pads_);
EXPECT_TRUE(success);
// max pool + index
success = ck::profiler::profile_pool2d_fwd_impl<InDataType,
OutDataType,
ComputeDataType,
IndexDataType,
ck::ReduceTensorOp::MAX,
false,
true>(true,
2,
false,
false,
param.length_,
param.window_spatial_lengths_,
param.window_strides_,
param.input_left_pads_,
param.input_right_pads_);
EXPECT_TRUE(success);
}
}
};
using KernelTypes =
::testing::Types<std::tuple<F16, F16, F16, I32>, std::tuple<F32, F32, F32, I32>>;
TYPED_TEST_SUITE(TestMaxPool2dFwd, KernelTypes);
TYPED_TEST(TestMaxPool2dFwd, Test_Pool)
{
// length, window_length, window_stride, left_pad, right_pad
this->params = {{{1, 1, 1, 1}, {1, 1}, {1, 1}, {0, 0}, {0, 0}},
{{2, 16, 64, 64}, {64, 64}, {1, 1}, {0, 0}, {0, 0}},
{{2, 32, 30, 30}, {2, 2}, {2, 2}, {1, 1}, {1, 1}}};
this->Run();
}

75
test/pool_fwd/test_max_pool3d_fwd.cpp Normal file
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// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include "gtest/gtest.h"
#include "profiler/profile_pool3d_fwd_impl.hpp"
#include "test_pool_fwd_common.hpp"
template <typename Tuple>
class TestMaxPool3dFwd : public ::testing::Test
{
protected:
using InDataType = std::tuple_element_t<0, Tuple>;
using OutDataType = std::tuple_element_t<1, Tuple>;
using ComputeDataType = std::tuple_element_t<2, Tuple>;
using IndexDataType = std::tuple_element_t<3, Tuple>;
std::vector<PoolingParam> params;
void Run()
{
for(auto param : params)
{
// max pool
bool success =
ck::profiler::profile_pool3d_fwd_impl<InDataType,
OutDataType,
ComputeDataType,
IndexDataType,
ck::ReduceTensorOp::MAX,
false,
false>(true,
2,
false,
false,
param.length_,
param.window_spatial_lengths_,
param.window_strides_,
param.input_left_pads_,
param.input_right_pads_);
EXPECT_TRUE(success);
// max pool + index
success = ck::profiler::profile_pool3d_fwd_impl<InDataType,
OutDataType,
ComputeDataType,
IndexDataType,
ck::ReduceTensorOp::MAX,
false,
true>(true,
2,
false,
false,
param.length_,
param.window_spatial_lengths_,
param.window_strides_,
param.input_left_pads_,
param.input_right_pads_);
EXPECT_TRUE(success);
}
}
};
using KernelTypes =
::testing::Types<std::tuple<F16, F16, F16, I32>, std::tuple<F32, F32, F32, I32>>;
TYPED_TEST_SUITE(TestMaxPool3dFwd, KernelTypes);
TYPED_TEST(TestMaxPool3dFwd, Test_Pool)
{
// length, window_length, window_stride, left_pad, right_pad
this->params = {{{1, 1, 1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {0, 0, 0}, {0, 0, 0}},
{{2, 16, 64, 64, 64}, {64, 64, 64}, {1, 1, 1}, {0, 0, 0}, {0, 0, 0}},
{{2, 32, 30, 30, 30}, {2, 2, 2}, {2, 2, 2}, {1, 1, 1}, {1, 1, 1}}};
this->Run();
}

31
test/pool_fwd/test_pool_fwd_common.hpp Normal file
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// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include "gtest/gtest.h"
#include "ck/ck.hpp"
using F16 = ck::half_t;
using F32 = float;
using I32 = int32_t;
using ck::index_t;
struct PoolingParam
{
PoolingParam(const std::vector<index_t>& length,
const std::vector<index_t>& window_spatial_lengths,
const std::vector<index_t>& window_strides,
const std::vector<index_t>& input_left_pads,
const std::vector<index_t>& input_right_pads)
: length_(length),
window_spatial_lengths_(window_spatial_lengths),
window_strides_(window_strides),
input_left_pads_(input_left_pads),
input_right_pads_(input_right_pads)
{
}
std::vector<index_t> length_;
std::vector<index_t> window_spatial_lengths_;
std::vector<index_t> window_strides_;
std::vector<index_t> input_left_pads_;
std::vector<index_t> input_right_pads_;
};