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Add client example of grouped conv2d forward (data type: fp16) (#488)

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* Rename example folder for GroupedConvFwdMultipleD

* Unify example codes

* Change target names

* Add fp16 example for multiple d instance

* Re-format common.hpp

* Add interface 'DeviceGroupedConvFwd'

* Use simpler interface

* Move common conv params out

* Rename conv fwd client example folder

* Add missing include directive

* Update grouped conv instance implementations

* Simplify ckProfiler (grouped conv forward)

* Use GroupedConvFwd to implement client example

* Use greater groupe count in example

* Add custom target to group examples

* Add extra tag param to instance factory function

* Use tag to differentiate factory functions

* Add missing tag argument for factory function

* Remove inheritance relationship

* Remove no-longer used include directive

* Add license in front of file

[ROCm/composable_kernel commit: f49803101e]
This commit is contained in:
Po Yen Chen
2022-11-10 09:01:58 +08:00
committed by GitHub
parent 93f036f2c3
commit d4808347e6
26 changed files with 1078 additions and 2533 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
client_example/07_conv2d_fwd/CMakeLists.txt
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@@ -1,2 +0,0 @@
add_executable(client_conv2d_fwd conv2d_fwd.cpp)
target_link_libraries(client_conv2d_fwd PRIVATE composable_kernel::device_operations)

2
client_example/07_grouped_conv2d_fwd/CMakeLists.txt Normal file
View File

@@ -0,0 +1,2 @@
add_executable(client_grouped_conv2d_fwd grouped_conv2d_fwd.cpp)
target_link_libraries(client_grouped_conv2d_fwd PRIVATE composable_kernel::device_operations)

155
client_example/07_conv2d_fwd/conv2d_fwd.cpp → client_example/07_grouped_conv2d_fwd/grouped_conv2d_fwd.cpp
View File

@@ -1,35 +1,38 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include <iomanip>
#include <iostream>
#include <iterator>
#include <numeric>
#include <vector>
#include "ck/ck.hpp"
#include "ck/library/tensor_operation_instance/gpu/convolution_forward.hpp"
#include "ck/library/tensor_operation_instance/gpu/grouped_convolution_forward.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/device_conv_fwd.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
using InDataType = ck::half_t;
using WeiDataType = ck::half_t;
using OutDataType = ck::half_t;
using InLayout = ck::tensor_layout::convolution::NHWC;
using WeiLayout = ck::tensor_layout::convolution::KYXC;
using OutLayout = ck::tensor_layout::convolution::NHWK;
using InLayout = ck::tensor_layout::convolution::GNHWC;
using WeiLayout = ck::tensor_layout::convolution::GKYXC;
using OutLayout = ck::tensor_layout::convolution::GNHWK;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
static constexpr ck::index_t NumDimSpatial = 2;
static constexpr ck::index_t N = 16;
static constexpr ck::index_t K = 32;
static constexpr ck::index_t C = 3;
static constexpr ck::index_t G = 32;
static constexpr ck::index_t N = 256;
static constexpr ck::index_t K = 192;
static constexpr ck::index_t C = 192;
static constexpr ck::index_t Y = 3;
static constexpr ck::index_t X = 3;
static constexpr ck::index_t Hi = 224;
static constexpr ck::index_t Wi = 224;
static constexpr ck::index_t Ho = 113;
static constexpr ck::index_t Wo = 113;
static constexpr ck::index_t Hi = 28;
static constexpr ck::index_t Wi = 28;
static constexpr ck::index_t Ho = 28;
static constexpr ck::index_t Wo = 28;
struct SimpleDeviceMem
{
@@ -47,30 +50,66 @@ struct SimpleDeviceMem
void* p_mem_;
};
int main(int argc, char* argv[])
int main()
{
std::vector<ck::index_t> in_spatial_lengths{Hi, Wi};
std::vector<ck::index_t> filter_spatial_lengths{Y, X};
std::vector<ck::index_t> out_spatial_lengths{Ho, Wo};
std::vector<ck::index_t> filter_strides{2, 2};
std::vector<ck::index_t> filter_dilations{1, 1};
std::vector<ck::index_t> input_left_pads{2, 2};
std::vector<ck::index_t> input_right_pads{2, 2};
std::array<ck::index_t, NumDimSpatial + 3> in_lengths{G, N, Hi, Wi, C};
std::array<ck::index_t, NumDimSpatial + 3> in_strides{0, 0, 0, 0, 1};
SimpleDeviceMem in(sizeof(InDataType) * N * Hi * Wi * C);
SimpleDeviceMem wei(sizeof(WeiDataType) * K * Y * X * C);
SimpleDeviceMem out(sizeof(OutDataType) * N * Ho * Wo * K);
std::array<ck::index_t, NumDimSpatial + 3> wei_lengths{G, K, Y, X, C};
std::array<ck::index_t, NumDimSpatial + 3> wei_strides{0, 0, 0, 0, 1};
std::array<ck::index_t, NumDimSpatial + 3> out_lengths{G, N, Ho, Wo, K};
std::array<ck::index_t, NumDimSpatial + 3> out_strides{0, 0, 0, 0, 1};
std::partial_sum(rbegin(in_lengths),
std::prev(rend(in_lengths)),
std::next(rbegin(in_strides)),
std::multiplies<>{});
std::partial_sum(rbegin(wei_lengths),
std::prev(rend(wei_lengths)),
std::next(rbegin(wei_strides)),
std::multiplies<>{});
std::partial_sum(rbegin(out_lengths),
std::prev(rend(out_lengths)),
std::next(rbegin(out_strides)),
std::multiplies<>{});
// transpose GNHWC/GKYXC/GNHWK to GNCHW/GKCYX/GNCHW
std::rotate(
rbegin(in_lengths), std::next(rbegin(in_lengths)), std::next(rbegin(in_lengths), 3));
std::rotate(
rbegin(in_strides), std::next(rbegin(in_strides)), std::next(rbegin(in_strides), 3));
std::rotate(
rbegin(wei_lengths), std::next(rbegin(wei_lengths)), std::next(rbegin(wei_lengths), 3));
std::rotate(
rbegin(wei_strides), std::next(rbegin(wei_strides)), std::next(rbegin(wei_strides), 3));
std::rotate(
rbegin(out_lengths), std::next(rbegin(out_lengths)), std::next(rbegin(out_lengths), 3));
std::rotate(
rbegin(out_strides), std::next(rbegin(out_strides)), std::next(rbegin(out_strides), 3));
std::array<ck::index_t, NumDimSpatial> filter_strides{1, 1};
std::array<ck::index_t, NumDimSpatial> filter_dilations{1, 1};
std::array<ck::index_t, NumDimSpatial> input_left_pads{1, 1};
std::array<ck::index_t, NumDimSpatial> input_right_pads{1, 1};
SimpleDeviceMem in(sizeof(InDataType) * G * N * Hi * Wi * C);
SimpleDeviceMem wei(sizeof(WeiDataType) * G * K * Y * X * C);
SimpleDeviceMem out(sizeof(OutDataType) * G * N * Ho * Wo * K);
using DeviceOp = ck::tensor_operation::device::DeviceGroupedConvFwdMultipleD<NumDimSpatial,
InLayout,
WeiLayout,
ck::Tuple<>,
OutLayout,
InDataType,
WeiDataType,
ck::Tuple<>,
OutDataType,
PassThrough,
PassThrough,
PassThrough>;
using DeviceOp = ck::tensor_operation::device::DeviceConvFwd<NumDimSpatial,
InLayout,
WeiLayout,
OutLayout,
InDataType,
WeiDataType,
OutDataType,
PassThrough,
PassThrough,
PassThrough>;
// get device op instances
const auto op_ptrs = ck::tensor_operation::device::instance::DeviceOperationInstanceFactory<
DeviceOp>::GetInstances();
@@ -91,13 +130,16 @@ int main(int argc, char* argv[])
auto& op_ptr = op_ptrs[i];
auto argument_ptr = op_ptr->MakeArgumentPointer(in.GetDeviceBuffer(),
wei.GetDeviceBuffer(),
{},
out.GetDeviceBuffer(),
N,
K,
C,
in_spatial_lengths,
filter_spatial_lengths,
out_spatial_lengths,
in_lengths,
in_strides,
wei_lengths,
wei_strides,
{},
{},
out_lengths,
out_strides,
filter_strides,
filter_dilations,
input_left_pads,
@@ -112,10 +154,10 @@ int main(int argc, char* argv[])
{
float avg_time = invoker_ptr->Run(argument_ptr.get(), StreamConfig{nullptr, true});
std::size_t flop = 2 * N * K * C * Ho * Wo * Y * X;
std::size_t num_bytes = sizeof(InDataType) * N * Hi * Wi * C +
sizeof(WeiDataType) * K * Y * X * C +
sizeof(OutDataType) * N * Ho * Wo * K;
std::size_t flop = std::size_t(2) * G * N * K * C * Ho * Wo * Y * X;
std::size_t num_bytes = sizeof(InDataType) * G * N * Hi * Wi * C +
sizeof(WeiDataType) * G * K * Y * X * C +
sizeof(OutDataType) * G * N * Ho * Wo * K;
float tflops = static_cast<float>(flop) / 1.E9 / avg_time;
float gb_per_sec = num_bytes / 1.E6 / avg_time;
@@ -134,10 +176,16 @@ int main(int argc, char* argv[])
}
else
{
std::cout << op_name << " does not support this problem" << std::endl;
std::cerr << op_name << " does not support this problem" << std::endl;
}
}
if(best_op_id < 0)
{
std::cerr << "no suitable instance" << std::endl;
return EXIT_FAILURE;
}
std::cout << "Best Perf: " << std::setw(10) << best_avg_time << " ms, " << best_tflops
<< " TFlops, " << best_gb_per_sec << " GB/s, " << best_op_name << std::endl;
@@ -148,13 +196,16 @@ int main(int argc, char* argv[])
<< std::endl;
auto argument_ptr = op_ptr->MakeArgumentPointer(in.GetDeviceBuffer(),
wei.GetDeviceBuffer(),
{},
out.GetDeviceBuffer(),
N,
K,
C,
in_spatial_lengths,
filter_spatial_lengths,
out_spatial_lengths,
in_lengths,
in_strides,
wei_lengths,
wei_strides,
{},
{},
out_lengths,
out_strides,
filter_strides,
filter_dilations,
input_left_pads,
@@ -172,6 +223,4 @@ int main(int argc, char* argv[])
std::cout << "Done" << std::endl;
}
return 0;
}
}