mirror of
https://github.com/ROCm/composable_kernel.git
synced 2026-04-20 06:49:15 +00:00
[CK_TILE] Image to Column kernel (#1532)
* [CK_TILE] Image to Column kernel * Fixes * Vector loads and stores * Fixes * Fixes * change test dir name
This commit is contained in:
Bartłomiej Kocot
3
example/ck_tile/04_img2col/CMakeLists.txt
Normal file
3
example/ck_tile/04_img2col/CMakeLists.txt
Normal file
@@ -0,0 +1,3 @@
|
||||
# not using add_example_executable() to add this target, since we don't want this to have
|
||||
# to be included in "make all/install/check"
|
||||
add_executable(tile_example_img2col EXCLUDE_FROM_ALL image_to_column.cpp)
|
||||
12
example/ck_tile/04_img2col/README.md
Normal file
12
example/ck_tile/04_img2col/README.md
Normal file
@@ -0,0 +1,12 @@
|
||||
# Image to Column
|
||||
|
||||
This folder contains example for Image to Column using ck_tile tile-programming implementation.
|
||||
|
||||
## build
|
||||
```
|
||||
# in the root of ck_tile
|
||||
mkdir build && cd build
|
||||
sh ../script/cmake-ck-dev.sh ../ <arch> # you can replace this <arch> to gfx90a, gfx942...
|
||||
make tile_example_img2col -j
|
||||
```
|
||||
This will result in an executable `build/bin/tile_example_img2col`
|
||||
170
example/ck_tile/04_img2col/image_to_column.cpp
Normal file
170
example/ck_tile/04_img2col/image_to_column.cpp
Normal file
@@ -0,0 +1,170 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include <algorithm>
|
||||
#include <cstring>
|
||||
|
||||
#include "ck_tile/host.hpp"
|
||||
#include "image_to_column.hpp"
|
||||
|
||||
// Host API implementation
|
||||
template <>
|
||||
float image_to_column(const image_to_column_traits& traits,
|
||||
const image_to_column_args<2>& args,
|
||||
const ck_tile::stream_config& stream_conf)
|
||||
{
|
||||
if(traits.data_type.compare("fp16") == 0)
|
||||
{
|
||||
constexpr ck_tile::index_t NDimSpatial = 2;
|
||||
constexpr ck_tile::index_t VectorSize = 8;
|
||||
|
||||
using thread_tile = ck_tile::sequence<8, 8>;
|
||||
using warp_tile = ck_tile::sequence<64, 64>;
|
||||
using block_tile = ck_tile::sequence<128, 128>;
|
||||
|
||||
using Shape = ck_tile::TileImageToColumnShape<thread_tile, warp_tile, block_tile>;
|
||||
|
||||
using InDataType = ck_tile::half_t;
|
||||
using OutDataType = ck_tile::half_t;
|
||||
|
||||
using PipelineProblem = ck_tile::BlockImageToColumnProblem<InDataType,
|
||||
OutDataType,
|
||||
Shape,
|
||||
NDimSpatial,
|
||||
VectorSize,
|
||||
VectorSize>;
|
||||
|
||||
using Kernel = ck_tile::ImageToColumn<PipelineProblem>;
|
||||
|
||||
auto kargs = Kernel::MakeKargs(args.p_in,
|
||||
args.p_out,
|
||||
args.G,
|
||||
args.N,
|
||||
args.C,
|
||||
args.input_spatial_lengths,
|
||||
args.filter_spatial_lengths,
|
||||
args.output_spatial_lengths,
|
||||
args.image_g_n_c_wis_strides,
|
||||
args.gemm_g_m_k_strides,
|
||||
args.conv_filter_strides,
|
||||
args.conv_filter_dilations,
|
||||
args.input_left_pads,
|
||||
args.input_right_pads);
|
||||
|
||||
const dim3 grids = Kernel::GridSize(
|
||||
args.N * args.output_spatial_lengths[0] * args.output_spatial_lengths[1],
|
||||
args.filter_spatial_lengths[0] * args.filter_spatial_lengths[1] * args.C,
|
||||
args.G);
|
||||
constexpr dim3 blocks = Kernel::BlockSize();
|
||||
|
||||
constexpr ck_tile::index_t kBlockPerCu = 2;
|
||||
|
||||
float ave_time = ck_tile::launch_kernel(
|
||||
stream_conf,
|
||||
ck_tile::make_kernel<blocks.x, kBlockPerCu>(Kernel{}, grids, blocks, 0, kargs));
|
||||
|
||||
return ave_time;
|
||||
}
|
||||
|
||||
return 0;
|
||||
}
|
||||
|
||||
int main(int argc, char* argv[])
|
||||
{
|
||||
constexpr ck_tile::index_t NDimSpatial = 2;
|
||||
|
||||
ExecutionConfig config;
|
||||
ck_tile::conv::ConvParam conv_params = DefaultConvParams;
|
||||
|
||||
if(!parse_cmd_args(argc, argv, config, conv_params))
|
||||
{
|
||||
return EXIT_FAILURE;
|
||||
}
|
||||
|
||||
if(conv_params.num_dim_spatial_ != NDimSpatial)
|
||||
{
|
||||
std::cerr << "unsupported # of spatial dimensions" << std::endl;
|
||||
return EXIT_FAILURE;
|
||||
}
|
||||
|
||||
using InDataType = ck_tile::half_t;
|
||||
using OutDataType = ck_tile::half_t;
|
||||
using ImLayout = ck_tile::tensor_layout::convolution::NHWGC;
|
||||
|
||||
const auto G = conv_params.G_;
|
||||
const auto N = conv_params.N_;
|
||||
const auto C = conv_params.C_;
|
||||
|
||||
const ck_tile::long_index_t NHoWo =
|
||||
N * std::accumulate(conv_params.output_spatial_lengths_.begin(),
|
||||
std::next(conv_params.output_spatial_lengths_.begin(), NDimSpatial),
|
||||
1,
|
||||
std::multiplies<>());
|
||||
|
||||
const ck_tile::long_index_t CYX =
|
||||
C * std::accumulate(conv_params.filter_spatial_lengths_.begin(),
|
||||
std::next(conv_params.filter_spatial_lengths_.begin(), NDimSpatial),
|
||||
1,
|
||||
std::multiplies<>());
|
||||
|
||||
const auto in_desc =
|
||||
ck_tile::conv::make_input_host_tensor_descriptor_g_n_c_wis_packed<ImLayout>(conv_params);
|
||||
const auto out_desc = ck_tile::HostTensorDescriptor({G, NHoWo, CYX});
|
||||
|
||||
// host verify
|
||||
ck_tile::HostTensor<InDataType> in(in_desc);
|
||||
ck_tile::HostTensor<OutDataType> out_device(out_desc);
|
||||
ck_tile::HostTensor<OutDataType> out_host(out_desc);
|
||||
|
||||
switch(config.init_method)
|
||||
{
|
||||
case 0: break;
|
||||
case 1: ck_tile::FillUniformDistributionIntegerValue<InDataType>{-5.f, 5.f}(in); break;
|
||||
default: ck_tile::FillUniformDistribution<InDataType>{-0.5, 0.5}(in); break;
|
||||
}
|
||||
|
||||
ck_tile::DeviceMem in_device_buf(in.get_element_space_size_in_bytes());
|
||||
ck_tile::DeviceMem out_device_buf(out_device.get_element_space_size_in_bytes());
|
||||
|
||||
in_device_buf.ToDevice(in.data());
|
||||
|
||||
image_to_column_traits traits{"fp16"};
|
||||
|
||||
image_to_column_args<NDimSpatial> args{
|
||||
in_device_buf.GetDeviceBuffer(),
|
||||
out_device_buf.GetDeviceBuffer(),
|
||||
G,
|
||||
N,
|
||||
C,
|
||||
ck_tile::to_array<ck_tile::long_index_t, NDimSpatial>(conv_params.input_spatial_lengths_),
|
||||
ck_tile::to_array<ck_tile::long_index_t, NDimSpatial>(conv_params.filter_spatial_lengths_),
|
||||
ck_tile::to_array<ck_tile::long_index_t, NDimSpatial>(conv_params.output_spatial_lengths_),
|
||||
ck_tile::to_array<ck_tile::long_index_t, NDimSpatial + 3>(in_desc.get_strides()),
|
||||
ck_tile::to_array<ck_tile::long_index_t, 3>(out_desc.get_strides()),
|
||||
ck_tile::to_array<ck_tile::long_index_t, NDimSpatial>(conv_params.conv_filter_strides_),
|
||||
ck_tile::to_array<ck_tile::long_index_t, NDimSpatial>(conv_params.conv_filter_dilations_),
|
||||
ck_tile::to_array<ck_tile::long_index_t, NDimSpatial>(conv_params.input_left_pads_),
|
||||
ck_tile::to_array<ck_tile::long_index_t, NDimSpatial>(conv_params.input_right_pads_)};
|
||||
|
||||
float ave_time =
|
||||
image_to_column(traits, args, ck_tile::stream_config{nullptr, config.time_kernel});
|
||||
|
||||
std::size_t num_btype = G * NHoWo * CYX * (sizeof(OutDataType) + sizeof(InDataType));
|
||||
float gb_per_sec = num_btype / 1.E6 / ave_time;
|
||||
std::cout << "Perf: " << ave_time << " ms, " << gb_per_sec << " GB/s" << std::endl;
|
||||
|
||||
bool pass = true;
|
||||
|
||||
if(config.do_verification)
|
||||
{
|
||||
// reference
|
||||
ck_tile::reference_im2col<InDataType, OutDataType, NDimSpatial>(in, out_host, conv_params);
|
||||
|
||||
out_device_buf.FromDevice(out_device.data());
|
||||
pass = ck_tile::check_err(out_device, out_host);
|
||||
|
||||
std::cout << "valid:" << (pass ? "y" : "n") << std::endl;
|
||||
}
|
||||
|
||||
return !pass;
|
||||
}
|
||||
105
example/ck_tile/04_img2col/image_to_column.hpp
Normal file
105
example/ck_tile/04_img2col/image_to_column.hpp
Normal file
@@ -0,0 +1,105 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#pragma once
|
||||
|
||||
#include "ck_tile/core.hpp"
|
||||
#include "ck_tile/host/kernel_launch.hpp"
|
||||
#include "ck_tile/ops/image_to_column.hpp"
|
||||
#include <string>
|
||||
|
||||
#define DefaultConvParams \
|
||||
ck_tile::conv::ConvParam \
|
||||
{ \
|
||||
2, 2, 32, 32, 32, {4, 4}, {64, 64}, {1, 1}, {1, 1}, {0, 0}, { 0, 0 } \
|
||||
}
|
||||
|
||||
struct ExecutionConfig final
|
||||
{
|
||||
bool do_verification = true;
|
||||
int init_method = 1;
|
||||
bool time_kernel = false;
|
||||
};
|
||||
|
||||
inline void print_help_msg()
|
||||
{
|
||||
std::cerr << "arg1: verification (0=no, 1=yes)\n"
|
||||
<< "arg2: initialization (0=no init, 1=integer value, 2=decimal value)\n"
|
||||
<< "arg3: time kernel (0=no, 1=yes)\n"
|
||||
<< ck_tile::conv::get_conv_param_parser_helper_msg() << std::endl;
|
||||
}
|
||||
|
||||
inline bool parse_cmd_args(int argc,
|
||||
char* argv[],
|
||||
ExecutionConfig& config,
|
||||
ck_tile::conv::ConvParam& conv_params)
|
||||
{
|
||||
constexpr int num_execution_config_args =
|
||||
3; // arguments for do_verification, init_method, time_kernel
|
||||
constexpr int num_conv_param_leading_args = 5; // arguments for num_dim_spatial_, G_, N_, K_, C_
|
||||
|
||||
constexpr int threshold_to_catch_partial_args = 1 + num_execution_config_args;
|
||||
constexpr int threshold_to_catch_all_args =
|
||||
threshold_to_catch_partial_args + num_conv_param_leading_args;
|
||||
|
||||
if(argc == 1)
|
||||
{
|
||||
// use default
|
||||
config = ExecutionConfig{};
|
||||
}
|
||||
// catch only ExecutionConfig arguments
|
||||
else if(argc == threshold_to_catch_partial_args)
|
||||
{
|
||||
config.do_verification = std::stoi(argv[1]);
|
||||
config.init_method = std::stoi(argv[2]);
|
||||
config.time_kernel = std::stoi(argv[3]);
|
||||
}
|
||||
// catch both ExecutionConfig & ConvParam arguments
|
||||
else if(threshold_to_catch_all_args < argc && ((argc - threshold_to_catch_all_args) % 3 == 0))
|
||||
{
|
||||
config.do_verification = std::stoi(argv[1]);
|
||||
config.init_method = std::stoi(argv[2]);
|
||||
config.time_kernel = std::stoi(argv[3]);
|
||||
|
||||
const ck_tile::index_t num_dim_spatial = std::stoi(argv[4]);
|
||||
conv_params =
|
||||
ck_tile::conv::parse_conv_param(num_dim_spatial, threshold_to_catch_partial_args, argv);
|
||||
}
|
||||
else
|
||||
{
|
||||
print_help_msg();
|
||||
return false;
|
||||
}
|
||||
|
||||
return true;
|
||||
}
|
||||
|
||||
struct image_to_column_traits
|
||||
{
|
||||
std::string data_type;
|
||||
};
|
||||
|
||||
template <ck_tile::index_t NDimSpatial>
|
||||
struct image_to_column_args
|
||||
{
|
||||
const void* p_in;
|
||||
void* p_out;
|
||||
const ck_tile::long_index_t G;
|
||||
const ck_tile::long_index_t N;
|
||||
const ck_tile::long_index_t C;
|
||||
const ck_tile::array<ck_tile::long_index_t, NDimSpatial> input_spatial_lengths;
|
||||
const ck_tile::array<ck_tile::long_index_t, NDimSpatial> filter_spatial_lengths;
|
||||
const ck_tile::array<ck_tile::long_index_t, NDimSpatial> output_spatial_lengths;
|
||||
const ck_tile::array<ck_tile::long_index_t, NDimSpatial + 3> image_g_n_c_wis_strides;
|
||||
const ck_tile::array<ck_tile::long_index_t, 3> gemm_g_m_k_strides;
|
||||
const ck_tile::array<ck_tile::long_index_t, NDimSpatial> conv_filter_strides;
|
||||
const ck_tile::array<ck_tile::long_index_t, NDimSpatial> conv_filter_dilations;
|
||||
const ck_tile::array<ck_tile::long_index_t, NDimSpatial> input_left_pads;
|
||||
const ck_tile::array<ck_tile::long_index_t, NDimSpatial> input_right_pads;
|
||||
};
|
||||
|
||||
// host API
|
||||
template <ck_tile::index_t NDimSpatial>
|
||||
float image_to_column(const image_to_column_traits&,
|
||||
const image_to_column_args<NDimSpatial>&,
|
||||
const ck_tile::stream_config&);
|
||||
Reference in New Issue
Block a user