Unverified Commit 0077eeb3 authored by Bartłomiej Kocot's avatar Bartłomiej Kocot Committed by GitHub
Browse files

Add image to column kernel (#867)

* Add image to column kernel

* Add instances, tests, profiler, example

* Add client example

* Several fixes of image to column

* Fix variable name in device_image_to_column_impl

* Several fixes of image to column profiler

* Fix num_btype calculation

* Make new mesaurements for correct bytes calculation
parent 0c9a1d25
add_gtest_executable(test_image_to_column test_image_to_column.cpp)
target_link_libraries(test_image_to_column PRIVATE utility device_image_to_column_instance)
add_gtest_executable(test_image_to_column_interface test_image_to_column_interface.cpp)
target_link_libraries(test_image_to_column_interface PRIVATE utility)
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include <iostream>
#include <initializer_list>
#include <tuple>
#include <vector>
#include <gtest/gtest.h>
#include "profiler/profile_image_to_column_impl.hpp"
template <typename Tuple>
class TestImageToColumn : public ::testing::Test
{
protected:
using InDataType = std::tuple_element_t<0, Tuple>;
using OutDataType = std::tuple_element_t<1, Tuple>;
using InLayout = std::tuple_element_t<2, Tuple>;
std::vector<ck::utils::conv::ConvParam> conv_params;
template <ck::index_t NDimSpatial>
void Run()
{
EXPECT_FALSE(conv_params.empty());
bool pass = true;
for(auto& param : conv_params)
{
pass = pass && ck::profiler::profile_image_to_column_impl<NDimSpatial,
InLayout,
InDataType,
OutDataType>(
true, // do_verification
1, // init_method: integer value
false, // do_log
false, // time_kernel
param);
}
EXPECT_TRUE(pass);
}
};
using namespace ck::tensor_layout::convolution;
using KernelTypes1d = ::testing::Types<std::tuple<float, float, GNWC>,
std::tuple<ck::bhalf_t, ck::bhalf_t, GNWC>,
std::tuple<ck::half_t, ck::half_t, GNWC>,
std::tuple<int8_t, int8_t, GNWC>>;
using KernelTypes2d = ::testing::Types<std::tuple<float, float, GNHWC>,
std::tuple<ck::bhalf_t, ck::bhalf_t, GNHWC>,
std::tuple<ck::half_t, ck::half_t, GNHWC>,
std::tuple<int8_t, int8_t, GNHWC>>;
using KernelTypes3d = ::testing::Types<std::tuple<float, float, GNDHWC>,
std::tuple<ck::bhalf_t, ck::bhalf_t, GNDHWC>,
std::tuple<ck::half_t, ck::half_t, GNDHWC>,
std::tuple<int8_t, int8_t, GNDHWC>>;
template <typename Tuple>
class TestImageToColumn1d : public TestImageToColumn<Tuple>
{
};
template <typename Tuple>
class TestImageToColumn2d : public TestImageToColumn<Tuple>
{
};
template <typename Tuple>
class TestImageToColumn3d : public TestImageToColumn<Tuple>
{
};
TYPED_TEST_SUITE(TestImageToColumn1d, KernelTypes1d);
TYPED_TEST_SUITE(TestImageToColumn2d, KernelTypes2d);
TYPED_TEST_SUITE(TestImageToColumn3d, KernelTypes3d);
TYPED_TEST(TestImageToColumn1d, Test1D)
{
this->conv_params.clear();
this->conv_params.push_back({1, 1, 4, 1, 192, {3}, {28}, {1}, {1}, {1}, {1}});
this->conv_params.push_back({1, 1, 64, 1, 64, {3}, {14}, {1}, {1}, {1}, {1}});
this->conv_params.push_back({1, 1, 64, 1, 64, {1}, {7}, {2}, {1}, {0}, {0}});
this->conv_params.push_back({1, 1, 64, 1, 64, {1}, {3}, {1}, {1}, {0}, {0}});
// ScalarPerVector should be 1
this->conv_params.push_back({1, 1, 4, 1, 1, {3}, {28}, {1}, {1}, {1}, {1}});
// stride != 1
this->conv_params.push_back({1, 1, 1, 1, 4, {3}, {28}, {2}, {1}, {1}, {1}});
// dilation != 1
this->conv_params.push_back({1, 1, 1, 1, 4, {3}, {28}, {1}, {2}, {1}, {1}});
this->template Run<1>();
}
TYPED_TEST(TestImageToColumn2d, Test2D)
{
this->conv_params.clear();
this->conv_params.push_back(
{2, 1, 4, 1, 192, {3, 3}, {28, 28}, {1, 1}, {1, 1}, {1, 1}, {1, 1}});
this->conv_params.push_back(
{2, 1, 64, 1, 64, {3, 3}, {14, 14}, {1, 1}, {1, 1}, {1, 1}, {1, 1}});
this->conv_params.push_back({2, 1, 64, 1, 64, {1, 1}, {7, 7}, {2, 2}, {1, 1}, {0, 0}, {0, 0}});
this->conv_params.push_back({2, 1, 64, 1, 64, {1, 1}, {3, 3}, {1, 1}, {1, 1}, {0, 0}, {0, 0}});
this->template Run<2>();
}
TYPED_TEST(TestImageToColumn3d, Test3D)
{
this->conv_params.clear();
this->conv_params.push_back(
{3, 1, 16, 1, 64, {1, 1, 1}, {7, 7, 7}, {2, 2, 2}, {1, 1, 1}, {0, 0, 0}, {0, 0, 0}});
this->conv_params.push_back(
{3, 1, 2, 1, 64, {3, 3, 3}, {14, 14, 3}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}});
this->conv_params.push_back(
{3, 1, 32, 1, 64, {1, 1, 1}, {3, 3, 3}, {1, 1, 1}, {1, 1, 1}, {0, 0, 0}, {0, 0, 0}});
this->template Run<3>();
}
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include <iostream>
#include <initializer_list>
#include <tuple>
#include <vector>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/impl/device_image_to_column_impl.hpp"
#include "ck/library/utility/convolution_parameter.hpp"
#include "ck/library/utility/algorithm.hpp"
#include "ck/library/utility/convolution_host_tensor_descriptor_helper.hpp"
#include <gtest/gtest.h>
using DataType = float;
using InLayout = ck::tensor_layout::convolution::GNWC;
template <ck::index_t... Is>
using S = ck::Sequence<Is...>;
template <ck::index_t ScalarPerVector, bool IsCPacked>
class TestImageToColumnInterface : public ::testing::Test
{
protected:
static constexpr ck::index_t NDimSpatial = 1;
// clang-format off
using DeviceImgToColInstance = ck::tensor_operation::device::DeviceImageToColumnImpl
//#####################| Num| InLayout| InDataType| OutDataType| Block| MPer| KPer| Thread| Scalar|
//#####################| Dim| | | | Size| Block| Block| Cluster| Per|
//#####################| Spatial| | | | | | | Lengths| Vector|
//#####################| | | | | | | | | |
< NDimSpatial, InLayout, DataType, DataType, 256, 128, 128, S<16, 16>,ScalarPerVector>;
// clang-format on
ck::utils::conv::ConvParam conv_param;
bool Run()
{
const auto N = conv_param.N_;
const auto C = conv_param.C_;
const auto FakeC =
conv_param.C_ / 2; // Fake C to simulate the behavior that C is not packed
const ck::index_t NDoHoWo =
N *
ck::accumulate_n<ck::index_t>(
conv_param.output_spatial_lengths_.begin(), NDimSpatial, 1, std::multiplies<>());
const ck::index_t CZYX =
C *
ck::accumulate_n<ck::index_t>(
conv_param.filter_spatial_lengths_.begin(), NDimSpatial, 1, std::multiplies<>());
const auto in_desc =
ck::utils::conv::make_input_host_tensor_descriptor_g_n_c_wis_packed<InLayout>(
conv_param);
const auto out_desc = HostTensorDescriptor({NDoHoWo, CZYX});
std::array<ck::index_t, NDimSpatial> input_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 + 3> input_g_n_c_wis_strides{};
std::array<ck::index_t, 2> output_m_k_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> input_left_pads{};
std::array<ck::index_t, NDimSpatial> input_right_pads{};
auto copy = [](const auto& x, auto& y) { std::copy(x.begin(), x.end(), y.begin()); };
copy(conv_param.input_spatial_lengths_, input_spatial_lengths);
copy(conv_param.filter_spatial_lengths_, filter_spatial_lengths);
copy(conv_param.output_spatial_lengths_, output_spatial_lengths);
copy(in_desc.GetStrides(), input_g_n_c_wis_strides);
copy(out_desc.GetStrides(), output_m_k_strides);
copy(conv_param.conv_filter_strides_, conv_filter_strides);
copy(conv_param.conv_filter_dilations_, conv_filter_dilations);
copy(conv_param.input_left_pads_, input_left_pads);
copy(conv_param.input_right_pads_, input_right_pads);
auto img2col = DeviceImgToColInstance{};
auto argument = img2col.MakeArgument(nullptr,
nullptr,
N,
IsCPacked ? C : FakeC,
input_spatial_lengths,
filter_spatial_lengths,
output_spatial_lengths,
input_g_n_c_wis_strides,
output_m_k_strides,
conv_filter_strides,
conv_filter_dilations,
input_left_pads,
input_right_pads);
return img2col.IsSupportedArgument(argument);
}
};
class TestImageToColumnInterface1ScalarPerVector : public TestImageToColumnInterface<1, true>
{
};
class TestImageToColumnInterface4ScalarPerVector : public TestImageToColumnInterface<4, true>
{
};
class TestImageToColumnInterface4ScalarPerVectorFakeC : public TestImageToColumnInterface<4, false>
{
};
TEST_F(TestImageToColumnInterface1ScalarPerVector, X1ScalarPerVector)
{
// vector load C * X % ScalarPerVector
this->conv_param = {1, 1, 1, 1, 1, {3}, {3}, {1}, {1}, {0}, {0}};
bool is_supported = this->Run();
EXPECT_TRUE(is_supported);
// vector load C * left_pad_x % ScalarPerVector
this->conv_param = {1, 1, 1, 1, 1, {4}, {3}, {1}, {1}, {3}, {0}};
is_supported = this->Run();
EXPECT_TRUE(is_supported);
// vector load C * right_pad_x % ScalarPerVector
this->conv_param = {1, 1, 1, 1, 1, {4}, {3}, {1}, {1}, {0}, {3}};
is_supported = this->Run();
EXPECT_TRUE(is_supported);
// vector load C % ScalarPerVector, right_pad and stride
this->conv_param = {1, 1, 1, 1, 1, {4}, {3}, {2}, {1}, {0}, {3}};
is_supported = this->Run();
EXPECT_TRUE(is_supported);
// vector load C % ScalarPerVector, left_pad and stride
this->conv_param = {1, 1, 1, 1, 1, {4}, {3}, {2}, {1}, {3}, {0}};
is_supported = this->Run();
EXPECT_TRUE(is_supported);
// vector load C % ScalarPerVector, dilation
this->conv_param = {1, 1, 1, 1, 1, {4}, {3}, {1}, {2}, {0}, {0}};
is_supported = this->Run();
EXPECT_TRUE(is_supported);
// C = 4
this->conv_param = {1, 1, 1, 1, 4, {3}, {3}, {1}, {1}, {3}, {3}};
is_supported = this->Run();
EXPECT_TRUE(is_supported);
}
TEST_F(TestImageToColumnInterface4ScalarPerVector, X4ScalarPerVector)
{
// vector load C * X % ScalarPerVector
this->conv_param = {1, 1, 1, 1, 1, {3}, {3}, {1}, {1}, {0}, {0}};
bool is_supported = this->Run();
EXPECT_FALSE(is_supported);
// vector load C * left_pad_x % ScalarPerVector
this->conv_param = {1, 1, 1, 1, 1, {4}, {3}, {1}, {1}, {3}, {0}};
is_supported = this->Run();
EXPECT_FALSE(is_supported);
// vector load C * right_pad_x % ScalarPerVector
this->conv_param = {1, 1, 1, 1, 1, {4}, {3}, {1}, {1}, {0}, {3}};
is_supported = this->Run();
EXPECT_FALSE(is_supported);
// vector load C % ScalarPerVector, right_pad and stride
this->conv_param = {1, 1, 1, 1, 1, {4}, {3}, {2}, {1}, {0}, {3}};
is_supported = this->Run();
EXPECT_FALSE(is_supported);
// vector load C % ScalarPerVector, left_pad and stride
this->conv_param = {1, 1, 1, 1, 1, {4}, {3}, {2}, {1}, {3}, {0}};
is_supported = this->Run();
EXPECT_FALSE(is_supported);
// vector load C % ScalarPerVector, dilation
this->conv_param = {1, 1, 1, 1, 1, {4}, {3}, {1}, {2}, {0}, {0}};
is_supported = this->Run();
EXPECT_FALSE(is_supported);
// C = 4
this->conv_param = {1, 1, 1, 1, 4, {3}, {3}, {1}, {1}, {3}, {3}};
is_supported = this->Run();
EXPECT_TRUE(is_supported);
}
TEST_F(TestImageToColumnInterface4ScalarPerVectorFakeC, X4ScalarPerVectorFakeC)
{
// C = 3
this->conv_param = {1, 1, 1, 1, 3, {4}, {3}, {1}, {1}, {0}, {0}};
bool is_supported = this->Run();
EXPECT_FALSE(is_supported);
// C = 4
this->conv_param = {1, 1, 1, 1, 8, {4}, {3}, {1}, {1}, {0}, {0}};
is_supported = this->Run();
EXPECT_TRUE(is_supported);
}
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment