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ad57f6ef0bcaeef7988bfd3954aac06554f12afb
composable_kernel/test/reference_conv_fwd/reference_conv_fwd.cpp
John Shumway ad57f6ef0b [CK_BUILDER] Put global CK functions in an the CK namespace (#3232) 
* Wrap ck host utitlies in CK namespace.

The CK and CK-Tile source code bases are incompatible because CK is not properly using namespaces everywhere. In particular, we need to put hip_check_error in the ck namespace.

Move all functions in include/ck_/host_utility that were in global namespace into the ck namespace.

There may be additional namespace problems like this, and it's possible we'll have namespace clashes. But it is good design to properly guard our to code bases (CK and CKTile) so that they can both coexist. Moreover, estabilishing this compatiblity is essential if we are going to allow the builder to instantiate  kernels from either template library.

* Add using declarations to test code.

After moving some of the untils into the ck namespace, most examples and a few tests had to be updated to recognize the new namespace declarations. We add using declarations to individual compute units for functions that were previously in the global namespace.

* Add using declarations to client examples.
2025-11-19 11:23:02 +01:00

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// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
#include <cmath>
#include <cstdlib>
#include <numeric>
#include <type_traits>
#include <vector>
#include <gtest/gtest.h>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/library/utility/algorithm.hpp"
#include "ck/library/utility/check_err.hpp"
#include "ck/library/utility/fill.hpp"
#include "ck/library/utility/host_tensor.hpp"
#include "ck/library/utility/convolution_parameter.hpp"
#include "ck/library/utility/convolution_host_tensor_descriptor_helper.hpp"
#include "ck/library/reference_tensor_operation/cpu/reference_conv_fwd.hpp"
namespace {
using ::ck::Tensor;
using InElementOp = ck::tensor_operation::element_wise::PassThrough;
using WeiElementOp = ck::tensor_operation::element_wise::PassThrough;
using OutElementOp = ck::tensor_operation::element_wise::PassThrough;
template <ck::index_t NDimSpatial,
typename InDataType = float,
typename WeiDataType = float,
typename OutDataType = float,
typename InLayout = ck::tensor_layout::convolution::GNHWC,
typename WeiLayout = ck::tensor_layout::convolution::GKYXC,
typename OutLayout = ck::tensor_layout::convolution::GNHWK,
typename FillInputOp = ck::utils::FillMonotonicSeq<InDataType>,
typename FillWeightsOp = ck::utils::FillConstant<WeiDataType>>
Tensor<OutDataType>
run_reference_convolution_forward(const ck::utils::conv::ConvParam& conv_param,
const FillInputOp& fill_input_op = FillInputOp{},
const FillWeightsOp& fill_weights_op = FillWeightsOp{0.5f})
{
const auto in_g_n_c_wis_desc =
ck::utils::conv::make_input_host_tensor_descriptor_g_n_c_wis_packed<InLayout>(conv_param);
const auto wei_g_k_c_xs_desc =
ck::utils::conv::make_weight_host_tensor_descriptor_g_k_c_xs_packed<WeiLayout>(conv_param);
const auto out_g_n_k_wos_desc =
ck::utils::conv::make_output_host_tensor_descriptor_g_n_k_wos_packed<OutLayout>(conv_param);
Tensor<InDataType> input(in_g_n_c_wis_desc);
Tensor<WeiDataType> weights(wei_g_k_c_xs_desc);
Tensor<OutDataType> host_output(out_g_n_k_wos_desc);
fill_input_op(input.begin(), input.end());
fill_weights_op(weights.begin(), weights.end());
ck::ranges::fill<OutDataType>(host_output, 0.f);
auto ref_conv = ck::tensor_operation::host::ReferenceConvFwd<NDimSpatial,
InDataType,
WeiDataType,
OutDataType,
InElementOp,
WeiElementOp,
OutElementOp>();
auto ref_invoker = ref_conv.MakeInvoker();
auto ref_argument = ref_conv.MakeArgument(input,
weights,
host_output,
conv_param.conv_filter_strides_,
conv_param.conv_filter_dilations_,
conv_param.input_left_pads_,
conv_param.input_right_pads_,
InElementOp{},
WeiElementOp{},
OutElementOp{});
ref_invoker.Run(ref_argument);
return host_output;
}
} // anonymous namespace
// Eeference convolution assume dimensions of tensor descriptors are in GNCDHW/GKCZYX/GNKDHW order,
// regardless of physical tensor layouts in memory.
// Some tests below assume dimensions of tensor descriptors can be in other order, and therefore
// are disabled
// TODO: add more tests, which comply with assumption about dimension order of reference convolution
// and add tests for more physical layout
#if 0
TEST(ReferenceConvolutionFWD, Conv2DGNHWC)
{
ck::utils::conv::ConvParam conv_param(2,
1,
1,
1,
2,
std::vector<ck::index_t>{3, 3},
std::vector<ck::index_t>{6, 6},
std::vector<ck::index_t>{1, 1},
std::vector<ck::index_t>{1, 1},
std::vector<ck::index_t>{0, 0},
std::vector<ck::index_t>{0, 0});
auto out_tensor = run_reference_convolution_forward<2>(conv_param);
std::vector<std::size_t> ref_dims{1, 1, 4, 4, 1};
std::vector<float> ref_data{130.5,
148.5,
166.5,
184.5,
238.5,
256.5,
274.5,
292.5,
346.5,
364.5,
382.5,
400.5,
454.5,
472.5,
490.5,
508.5};
EXPECT_TRUE(ck::utils::check_err(
out_tensor.mDesc.GetLengths(), ref_dims, "Error: wrong output tensor dimensions!"));
EXPECT_TRUE(ck::utils::check_err(out_tensor, ref_data, "Error: incorrect results!"));
}
TEST(ReferenceConvolutionFWD, Conv2DGNHWCStridesDilationsPadding)
{
ck::utils::conv::ConvParam conv_param(2,
1,
1,
2,
2,
std::vector<ck::index_t>{3, 3},
std::vector<ck::index_t>{12, 12},
std::vector<ck::index_t>{2, 2},
std::vector<ck::index_t>{2, 2},
std::vector<ck::index_t>{1, 1},
std::vector<ck::index_t>{1, 1});
auto out_tensor = run_reference_convolution_forward<2>(conv_param);
std::vector<std::size_t> ref_dims = std::vector<std::size_t>{1, 5, 5, 2};
std::vector<float> ref_data{
210., 210., 327., 327., 351., 351., 375., 375., 399., 399.,
459., 459., 706.5, 706.5, 742.5, 742.5, 778.5, 778.5, 814.5, 814.5,
747., 747., 1138.5, 1138.5, 1174.5, 1174.5, 1210.5, 1210.5, 1246.5, 1246.5,
1035., 1035., 1570.5, 1570.5, 1606.5, 1606.5, 1642.5, 1642.5, 1678.5, 1678.5,
1323., 1323., 2002.5, 2002.5, 2038.5, 2038.5, 2074.5, 2074.5, 2110.5, 2110.5};
EXPECT_TRUE(ck::utils::check_err(
out_tensor.mDesc.GetLengths(), ref_dims, "Error: wrong output tensor dimensions!"));
EXPECT_TRUE(ck::utils::check_err(out_tensor, ref_data, "Error: incorrect results!"));
}
TEST(ReferenceConvolutionFWD, Conv1DGNWC)
{
ck::utils::conv::ConvParam conv_param(1,
1,
1,
1,
2,
std::vector<ck::index_t>{3},
std::vector<ck::index_t>{6},
std::vector<ck::index_t>{1},
std::vector<ck::index_t>{1},
std::vector<ck::index_t>{0},
std::vector<ck::index_t>{0});
auto out_tensor =
run_reference_convolution_forward<1,
float,
float,
float,
ck::tensor_layout::convolution::GNWC,
ck::tensor_layout::convolution::GKXC,
ck::tensor_layout::convolution::GNWK>(conv_param);
std::vector<std::size_t> ref_dims{1, 1, 4, 1};
std::vector<float> ref_data{7.5, 13.5, 19.5, 25.5};
EXPECT_TRUE(ck::utils::check_err(
out_tensor.mDesc.GetLengths(), ref_dims, "Error: wrong output tensor dimensions!"));
EXPECT_TRUE(ck::utils::check_err(out_tensor, ref_data, "Error: incorrect results!"));
}
TEST(ReferenceConvolutionFWD, Conv1DGNWCStridesDilationsPadding)
{
ck::utils::conv::ConvParam conv_param(1,
1,
1,
2,
2,
std::vector<ck::index_t>{3},
std::vector<ck::index_t>{12},
std::vector<ck::index_t>{2},
std::vector<ck::index_t>{2},
std::vector<ck::index_t>{1},
std::vector<ck::index_t>{1});
auto out_tensor =
run_reference_convolution_forward<1,
float,
float,
float,
ck::tensor_layout::convolution::GNWC,
ck::tensor_layout::convolution::GKXC,
ck::tensor_layout::convolution::GNWK>(conv_param);
std::vector<std::size_t> ref_dims{1, 1, 5, 2};
std::vector<float> ref_data{9., 9., 19.5, 19.5, 31.5, 31.5, 43.5, 43.5, 55.5, 55.5};
EXPECT_TRUE(ck::utils::check_err(
out_tensor.mDesc.GetLengths(), ref_dims, "Error: wrong output tensor dimensions!"));
EXPECT_TRUE(ck::utils::check_err(out_tensor, ref_data, "Error: incorrect results!"));
}
TEST(ReferenceConvolutionFWD, Conv1DGNWCSameOutputSize)
{
ck::utils::conv::ConvParam conv_param(1,
1,
2,
16,
4,
std::vector<ck::index_t>{3},
std::vector<ck::index_t>{16},
std::vector<ck::index_t>{1},
std::vector<ck::index_t>{1},
std::vector<ck::index_t>{1},
std::vector<ck::index_t>{1});
auto out_tensor2 = run_reference_convolution_forward<1,
float,
float,
float,
ck::tensor_layout::convolution::GNWC,
ck::tensor_layout::convolution::GKXC,
ck::tensor_layout::convolution::GNWK>(
conv_param, ck::utils::FillMonotonicSeq<float>{0.f, 0.1f});
std::vector<std::size_t> ref_dims{1, 2, 16, 16};
std::vector<float> ref_data{
1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4,
1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4,
3.3, 3.3, 3.3, 3.3, 3.3, 3.3, 3.3, 3.3,
3.3, 3.3, 3.3, 3.3, 3.3, 3.3, 3.3, 3.3,
5.7, 5.7, 5.7, 5.7, 5.7, 5.7, 5.7, 5.7,
5.7, 5.7, 5.7, 5.7, 5.7, 5.7, 5.7, 5.7,
8.1, 8.1, 8.1, 8.1, 8.1, 8.1, 8.1, 8.1,
8.1, 8.1, 8.1, 8.1, 8.1, 8.1, 8.1, 8.1,
10.5, 10.5, 10.5, 10.5, 10.5, 10.5, 10.5, 10.5,
10.5, 10.5, 10.5, 10.5, 10.5, 10.5, 10.5, 10.5,
12.900001, 12.900001, 12.900001, 12.900001, 12.900001, 12.900001, 12.900001, 12.900001,
12.900001, 12.900001, 12.900001, 12.900001, 12.900001, 12.900001, 12.900001, 12.900001,
15.3, 15.3, 15.3, 15.3, 15.3, 15.3, 15.3, 15.3,
15.3, 15.3, 15.3, 15.3, 15.3, 15.3, 15.3, 15.3,
17.7, 17.7, 17.7, 17.7, 17.7, 17.7, 17.7, 17.7,
17.7, 17.7, 17.7, 17.7, 17.7, 17.7, 17.7, 17.7,
20.1, 20.1, 20.1, 20.1, 20.1, 20.1, 20.1, 20.1,
20.1, 20.1, 20.1, 20.1, 20.1, 20.1, 20.1, 20.1,
22.5, 22.5, 22.5, 22.5, 22.5, 22.5, 22.5, 22.5,
22.5, 22.5, 22.5, 22.5, 22.5, 22.5, 22.5, 22.5,
24.900002, 24.900002, 24.900002, 24.900002, 24.900002, 24.900002, 24.900002, 24.900002,
24.900002, 24.900002, 24.900002, 24.900002, 24.900002, 24.900002, 24.900002, 24.900002,
27.300001, 27.300001, 27.300001, 27.300001, 27.300001, 27.300001, 27.300001, 27.300001,
27.300001, 27.300001, 27.300001, 27.300001, 27.300001, 27.300001, 27.300001, 27.300001,
29.7, 29.7, 29.7, 29.7, 29.7, 29.7, 29.7, 29.7,
29.7, 29.7, 29.7, 29.7, 29.7, 29.7, 29.7, 29.7,
32.100002, 32.100002, 32.100002, 32.100002, 32.100002, 32.100002, 32.100002, 32.100002,
32.100002, 32.100002, 32.100002, 32.100002, 32.100002, 32.100002, 32.100002, 32.100002,
34.5, 34.5, 34.5, 34.5, 34.5, 34.5, 34.5, 34.5,
34.5, 34.5, 34.5, 34.5, 34.5, 34.5, 34.5, 34.5,
23.8, 23.8, 23.8, 23.8, 23.8, 23.8, 23.8, 23.8,
23.8, 23.8, 23.8, 23.8, 23.8, 23.8, 23.8, 23.8,
27., 27., 27., 27., 27., 27., 27., 27.,
27., 27., 27., 27., 27., 27., 27., 27.,
41.7, 41.7, 41.7, 41.7, 41.7, 41.7, 41.7, 41.7,
41.7, 41.7, 41.7, 41.7, 41.7, 41.7, 41.7, 41.7,
44.100002, 44.100002, 44.100002, 44.100002, 44.100002, 44.100002, 44.100002, 44.100002,
44.100002, 44.100002, 44.100002, 44.100002, 44.100002, 44.100002, 44.100002, 44.100002,
46.5, 46.5, 46.5, 46.5, 46.5, 46.5, 46.5, 46.5,
46.5, 46.5, 46.5, 46.5, 46.5, 46.5, 46.5, 46.5,
48.899998, 48.899998, 48.899998, 48.899998, 48.899998, 48.899998, 48.899998, 48.899998,
48.899998, 48.899998, 48.899998, 48.899998, 48.899998, 48.899998, 48.899998, 48.899998,
51.3, 51.3, 51.3, 51.3, 51.3, 51.3, 51.3, 51.3,
51.3, 51.3, 51.3, 51.3, 51.3, 51.3, 51.3, 51.3,
53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7,
53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7,
56.100002, 56.100002, 56.100002, 56.100002, 56.100002, 56.100002, 56.100002, 56.100002,
56.100002, 56.100002, 56.100002, 56.100002, 56.100002, 56.100002, 56.100002, 56.100002,
58.5, 58.5, 58.5, 58.5, 58.5, 58.5, 58.5, 58.5,
58.5, 58.5, 58.5, 58.5, 58.5, 58.5, 58.5, 58.5,
60.899998, 60.899998, 60.899998, 60.899998, 60.899998, 60.899998, 60.899998, 60.899998,
60.899998, 60.899998, 60.899998, 60.899998, 60.899998, 60.899998, 60.899998, 60.899998,
63.3, 63.3, 63.3, 63.3, 63.3, 63.3, 63.3, 63.3,
63.3, 63.3, 63.3, 63.3, 63.3, 63.3, 63.3, 63.3,
65.7, 65.7, 65.7, 65.7, 65.7, 65.7, 65.7, 65.7,
65.7, 65.7, 65.7, 65.7, 65.7, 65.7, 65.7, 65.7,
68.1, 68.1, 68.1, 68.1, 68.1, 68.1, 68.1, 68.1,
68.1, 68.1, 68.1, 68.1, 68.1, 68.1, 68.1, 68.1,
70.5, 70.5, 70.5, 70.5, 70.5, 70.5, 70.5, 70.5,
70.5, 70.5, 70.5, 70.5, 70.5, 70.5, 70.5, 70.5,
72.9, 72.9, 72.9, 72.9, 72.9, 72.9, 72.9, 72.9,
72.9, 72.9, 72.9, 72.9, 72.9, 72.9, 72.9, 72.9,
49.4, 49.4, 49.4, 49.4, 49.4, 49.4, 49.4, 49.4,
49.4, 49.4, 49.4, 49.4, 49.4, 49.4, 49.4, 49.4};
EXPECT_TRUE(ck::utils::check_err(
out_tensor2.mDesc.GetLengths(), ref_dims, "Error: wrong output tensor dimensions!"));
EXPECT_TRUE(ck::utils::check_err(out_tensor2, ref_data, "Error: incorrect results!"));
}
#endif
TEST(ReferenceConvolutionFWD, Conv3DGNCDHW)
{
ck::utils::conv::ConvParam conv_param(3,
1,
1,
1,
2,
std::vector<ck::index_t>{3, 3, 3},
std::vector<ck::index_t>{6, 6, 6},
std::vector<ck::index_t>{1, 1, 1},
std::vector<ck::index_t>{1, 1, 1},
std::vector<ck::index_t>{0, 0, 0},
std::vector<ck::index_t>{0, 0, 0});
auto out_tensor = run_reference_convolution_forward<3,
float,
float,
float,
ck::tensor_layout::convolution::GNCDHW,
ck::tensor_layout::convolution::GKCZYX,
ck::tensor_layout::convolution::GNKDHW>(
conv_param, ck::utils::FillMonotonicSeq<float>{0.f, 0.1f});
std::vector<std::size_t> ref_dims{1, 1, 1, 4, 4, 4};
std::vector<float> ref_data{
407.7, 410.40002, 413.09998, 415.80002, 423.90002, 426.6, 429.30002, 432.,
440.1, 442.80002, 445.5, 448.2, 456.30002, 459., 461.7, 464.40002,
504.90002, 507.6, 510.30002, 513., 521.1, 523.8, 526.5, 529.2001,
537.3, 540., 542.7001, 545.4, 553.5, 556.2001, 558.9, 561.6,
602.10004, 604.8, 607.5, 610.2, 618.3, 621., 623.7, 626.4,
634.5, 637.2, 639.9, 642.60004, 650.7, 653.4, 656.10004, 658.8,
699.3, 702., 704.7, 707.4, 715.5, 718.2, 720.9, 723.60004,
731.7, 734.4001, 737.10004, 739.8, 747.9001, 750.60004, 753.3, 756.};
EXPECT_TRUE(ck::utils::check_err(out_tensor.mDesc.GetLengths(),
ref_dims,
"Error [case 1]: wrong output tensor dimensions!"));
EXPECT_TRUE(ck::utils::check_err(out_tensor, ref_data, "Error [case 1]: incorrect results!"));
}
TEST(ReferenceConvolutionFWD, Conv3DGNCDHWStridesDilations)
{
ck::utils::conv::ConvParam conv_param(3,
1,
1,
2,
2,
std::vector<ck::index_t>{3, 3, 3},
std::vector<ck::index_t>{12, 12, 12},
std::vector<ck::index_t>{3, 3, 3},
std::vector<ck::index_t>{1, 1, 1},
std::vector<ck::index_t>{0, 0, 0},
std::vector<ck::index_t>{0, 0, 0});
auto out_tensor = run_reference_convolution_forward<3,
float,
float,
float,
ck::tensor_layout::convolution::GNCDHW,
ck::tensor_layout::convolution::GKCZYX,
ck::tensor_layout::convolution::GNKDHW>(
conv_param, ck::utils::FillMonotonicSeq<float>{0.f, 0.1f});
std::vector<std::size_t> ref_dims{1, 1, 2, 4, 4, 4};
std::vector<float> ref_data{
2756.7002, 2764.7998, 2772.9001, 2781., 2853.9001, 2862., 2870.1, 2878.2002,
2951.1, 2959.2002, 2967.2998, 2975.4001, 3048.2998, 3056.4001, 3064.5, 3072.6,
3923.1, 3931.2, 3939.2998, 3947.4, 4020.2998, 4028.4001, 4036.5002, 4044.5999,
4117.5, 4125.6, 4133.7, 4141.8, 4214.7, 4222.8, 4230.9004, 4239.,
5089.5, 5097.5996, 5105.7, 5113.8, 5186.7, 5194.8, 5202.9, 5211.,
5283.9004, 5292., 5300.0996, 5308.2, 5381.0996, 5389.2, 5397.3, 5405.4004,
6255.9004, 6264.0005, 6272.1, 6280.2, 6353.1, 6361.2, 6369.301, 6377.4,
6450.301, 6458.4, 6466.5, 6474.6, 6547.5, 6555.6, 6563.699, 6571.801,
2756.7002, 2764.7998, 2772.9001, 2781., 2853.9001, 2862., 2870.1, 2878.2002,
2951.1, 2959.2002, 2967.2998, 2975.4001, 3048.2998, 3056.4001, 3064.5, 3072.6,
3923.1, 3931.2, 3939.2998, 3947.4, 4020.2998, 4028.4001, 4036.5002, 4044.5999,
4117.5, 4125.6, 4133.7, 4141.8, 4214.7, 4222.8, 4230.9004, 4239.,
5089.5, 5097.5996, 5105.7, 5113.8, 5186.7, 5194.8, 5202.9, 5211.,
5283.9004, 5292., 5300.0996, 5308.2, 5381.0996, 5389.2, 5397.3, 5405.4004,
6255.9004, 6264.0005, 6272.1, 6280.2, 6353.1, 6361.2, 6369.301, 6377.4,
6450.301, 6458.4, 6466.5, 6474.6, 6547.5, 6555.6, 6563.699, 6571.801};
EXPECT_TRUE(ck::utils::check_err(out_tensor.mDesc.GetLengths(),
ref_dims,
"Error [case 2]: wrong output tensor dimensions!"));
EXPECT_TRUE(ck::utils::check_err(
out_tensor, ref_data, "Error [case 2]: incorrect results!", 1e-4f, 1e-6f));
}
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