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Merge commit '3052d7c9e6972d5ea7d2225ab78e45554ba70efd' into develop

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assistant-librarian[bot]
2025-10-29 08:15:15 +00:00
parent e571490afc
commit 6f6c855c0e
13 changed files with 860 additions and 99 deletions
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211
test/ck_tile/pooling/test_pooling.cpp
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@@ -28,7 +28,19 @@ class TestCkTilePooling : public ::testing::Test
using TestPoolShape = ck_tile::PoolShape<BlockWarps_, BlockTile_, WarpTile_, ThreadTile_>;
// 3D pooling configuration
// 2D pooling configuration (NHWC)
struct Config2D
{
ck_tile::index_t N, H, W, C;
ck_tile::index_t Y, X;
ck_tile::index_t Sy, Sx;
ck_tile::index_t Dy, Dx;
ck_tile::index_t LeftPy, LeftPx;
ck_tile::index_t RightPy, RightPx;
std::string name;
};
// 3D pooling configuration (NDHWC)
struct Config3D
{
ck_tile::index_t N, D, H, W, C;
@@ -40,6 +52,117 @@ class TestCkTilePooling : public ::testing::Test
std::string name;
};
bool RunPool2D(const Config2D& config)
{
std::cout << "Testing 2D: " << config.name << " ... ";
const ck_tile::index_t Ys = (config.Y - 1) * config.Dy + 1;
const ck_tile::index_t Xs = (config.X - 1) * config.Dx + 1;
const ck_tile::index_t Ho =
(config.H + config.LeftPy + config.RightPy - Ys) / config.Sy + 1;
const ck_tile::index_t Wo =
(config.W + config.LeftPx + config.RightPx - Xs) / config.Sx + 1;
using IndexDataType = ck_tile::index_t;
// Host tensors
ck_tile::HostTensor<InDataType> h_in({config.N, config.H, config.W, config.C});
ck_tile::HostTensor<OutDataType> h_out({config.N, Ho, Wo, config.C});
ck_tile::HostTensor<OutDataType> h_out_ref({config.N, Ho, Wo, config.C});
ck_tile::HostTensor<IndexDataType> h_out_index({config.N, Ho, Wo, config.C});
ck_tile::HostTensor<IndexDataType> h_out_ref_index({config.N, Ho, Wo, config.C});
// Initialize input with random data
ck_tile::FillUniformDistribution<InDataType>{-5.f, 5.f}(h_in);
// Device memory
ck_tile::DeviceMem d_in_mem(h_in.get_element_space_size_in_bytes());
ck_tile::DeviceMem d_out_mem(h_out.get_element_space_size_in_bytes());
ck_tile::DeviceMem d_out_index_mem(h_out_index.get_element_space_size_in_bytes());
d_in_mem.ToDevice(h_in.data());
d_out_mem.ToDevice(h_out.data());
d_out_index_mem.ToDevice(h_out_index.data());
constexpr ck_tile::index_t kBlockPerCu = 1;
using Problem = ck_tile::PoolProblem<InDataType,
OutDataType,
ComputeDataType,
IndexDataType,
ReduceOpType,
true, // OutputIndex
false, // PropagateNan
TestPoolShape>;
using Kernel = ck_tile::PoolKernel<Problem>;
const ck_tile::index_t kBlockSize = Kernel::BlockSize();
// Shapes and strides (NHWC)
const auto input_shape = ck_tile::make_tuple(config.N, config.H, config.W, config.C);
const auto output_shape = ck_tile::make_tuple(config.N, Ho, Wo, config.C);
const auto input_strides =
ck_tile::make_tuple(config.H * config.W * config.C, config.W * config.C, config.C, 1);
const auto output_strides =
ck_tile::make_tuple(Ho * Wo * config.C, Wo * config.C, config.C, 1);
const auto window_spatial_lengths = ck_tile::make_tuple(config.Y, config.X);
const auto window_strides = ck_tile::make_tuple(config.Sy, config.Sx);
const auto window_dilations = ck_tile::make_tuple(config.Dy, config.Dx);
const auto input_left_pads = ck_tile::make_tuple(config.LeftPy, config.LeftPx);
const auto input_right_pads = ck_tile::make_tuple(config.RightPy, config.RightPx);
auto host_args =
ck_tile::PoolHostArgs<decltype(input_shape), decltype(window_spatial_lengths)>{
static_cast<InDataType*>(d_in_mem.GetDeviceBuffer()),
static_cast<OutDataType*>(d_out_mem.GetDeviceBuffer()),
static_cast<IndexDataType*>(d_out_index_mem.GetDeviceBuffer()),
input_shape,
output_shape,
input_strides,
output_strides,
window_spatial_lengths,
window_strides,
window_dilations,
input_left_pads,
input_right_pads};
auto kernel_args = Kernel::MakeKernelArgs(host_args);
const ck_tile::index_t kGridSize = Kernel::CalculateGridSize(kernel_args);
if(!Kernel::IsSupportedArgument(kernel_args))
{
return true;
}
// Run kernel
ck_tile::launch_kernel(
ck_tile::stream_config{nullptr, false, 0},
ck_tile::make_kernel<kBlockPerCu>(Kernel{}, kGridSize, kBlockSize, 0, kernel_args));
// Run reference
ck_tile::reference_pool2d<InDataType,
ComputeDataType,
OutDataType,
IndexDataType,
ReduceOpType,
decltype(input_shape),
decltype(window_spatial_lengths),
true>(
h_in, h_out_ref, h_out_ref_index, kernel_args, ReduceOpType{});
d_out_mem.FromDevice(h_out.data());
d_out_index_mem.FromDevice(h_out_index.data());
// Validate results
bool pass_value =
ck_tile::check_err(h_out, h_out_ref, "Error: Incorrect values!", 1e-5, 1e-5);
bool pass_index = ck_tile::check_err(
h_out_index, h_out_ref_index, "Error: Incorrect indices!", 1e-5, 1e-5);
std::cout << (pass_value && pass_index ? "PASS" : "FAIL") << std::endl;
return pass_value && pass_index;
}
bool RunPool3D(const Config3D& config)
{
std::cout << "Testing 3D: " << config.name << " ... ";
@@ -72,6 +195,8 @@ class TestCkTilePooling : public ::testing::Test
const auto input_right_pads =
ck_tile::make_tuple(config.RightPz, config.RightPy, config.RightPx);
using IndexDataType = ck_tile::index_t;
ck_tile::HostTensor<InDataType> h_in({config.N, config.D, config.H, config.W, config.C},
{config.D * config.H * config.W * config.C,
config.H * config.W * config.C,
@@ -84,6 +209,12 @@ class TestCkTilePooling : public ::testing::Test
ck_tile::HostTensor<OutDataType> h_out_ref(
{config.N, Do, Ho, Wo, config.C},
{Do * Ho * Wo * config.C, Ho * Wo * config.C, Wo * config.C, config.C, 1});
ck_tile::HostTensor<IndexDataType> h_out_index(
{config.N, Do, Ho, Wo, config.C},
{Do * Ho * Wo * config.C, Ho * Wo * config.C, Wo * config.C, config.C, 1});
ck_tile::HostTensor<IndexDataType> h_out_ref_index(
{config.N, Do, Ho, Wo, config.C},
{Do * Ho * Wo * config.C, Ho * Wo * config.C, Wo * config.C, config.C, 1});
ck_tile::FillUniformDistribution<InDataType>{-5.f, 5.f}(h_in);
h_out.SetZero();
@@ -91,17 +222,19 @@ class TestCkTilePooling : public ::testing::Test
ck_tile::DeviceMem d_in_mem(h_in.get_element_space_size_in_bytes());
ck_tile::DeviceMem d_out_mem(h_out.get_element_space_size_in_bytes());
ck_tile::DeviceMem d_out_index_mem(h_out_index.get_element_space_size_in_bytes());
d_in_mem.ToDevice(h_in.data());
d_out_mem.ToDevice(h_out.data());
d_out_index_mem.ToDevice(h_out_index.data());
using Problem = ck_tile::PoolProblem<InDataType,
OutDataType,
ComputeDataType,
OutDataType,
IndexDataType,
ReduceOpType,
false,
false,
true, // OutputIndex
false, // PropagateNan
TestPoolShape>;
using Kernel = ck_tile::PoolKernel<Problem>;
@@ -112,6 +245,7 @@ class TestCkTilePooling : public ::testing::Test
ck_tile::PoolHostArgs<decltype(input_shape), decltype(window_spatial_lengths)>{
static_cast<InDataType*>(d_in_mem.GetDeviceBuffer()),
static_cast<OutDataType*>(d_out_mem.GetDeviceBuffer()),
static_cast<IndexDataType*>(d_out_index_mem.GetDeviceBuffer()),
input_shape,
output_shape,
input_strides,
@@ -137,16 +271,27 @@ class TestCkTilePooling : public ::testing::Test
ck_tile::make_kernel<kBlockPerCu>(Kernel{}, kGridSize, kBlockSize, 0, kernel_args));
// Run reference implementation
ck_tile::reference_pool3d<InDataType, ComputeDataType, OutDataType>(
h_in, h_out_ref, kernel_args, ReduceOpType{});
ck_tile::reference_pool3d<InDataType,
ComputeDataType,
OutDataType,
IndexDataType,
ReduceOpType,
decltype(input_shape),
decltype(window_spatial_lengths),
true>(
h_in, h_out_ref, h_out_ref_index, kernel_args, ReduceOpType{});
d_out_mem.FromDevice(h_out.data());
d_out_index_mem.FromDevice(h_out_index.data());
// Validate results
bool pass = ck_tile::check_err(h_out, h_out_ref);
std::cout << (pass ? "PASS" : "FAIL") << std::endl;
bool pass_value =
ck_tile::check_err(h_out, h_out_ref, "Error: Incorrect values!", 1e-5, 1e-5);
bool pass_index = ck_tile::check_err(
h_out_index, h_out_ref_index, "Error: Incorrect indices!", 1e-5, 1e-5);
return pass;
std::cout << (pass_value && pass_index ? "PASS" : "FAIL") << std::endl;
return pass_value && pass_index;
}
};
@@ -194,6 +339,50 @@ using TestTypes =
TYPED_TEST_SUITE(TestCkTilePooling, TestTypes);
// 2D Pooling Tests (NHWC)
TYPED_TEST(TestCkTilePooling, Pool2D_2x2)
{
typename TestFixture::Config2D config = {1, // N - batch size
8, // H - height dimension
8, // W - width dimension
32, // C - channel dimension
2, // Y - pooling window height
2, // X - pooling window width
2, // Sy - window stride height
2, // Sx - window stride width
1, // Dy - window dilation height
1, // Dx - window dilation width
0, // LeftPy - left padding height
0, // LeftPx - left padding width
0, // RightPy - right padding height
0, // RightPx - right padding width
"2x2 pooling NHWC"};
bool pass = this->RunPool2D(config);
EXPECT_TRUE(pass);
}
TYPED_TEST(TestCkTilePooling, Pool2D_3x3_WithPadding)
{
typename TestFixture::Config2D config = {2, // N - batch size
16, // H - height dimension
16, // W - width dimension
32, // C - channel dimension
3, // Y - pooling window height
3, // X - pooling window width
2, // Sy - window stride height
2, // Sx - window stride width
1, // Dy - window dilation height
1, // Dx - window dilation width
1, // LeftPy - left padding height
1, // LeftPx - left padding width
1, // RightPy - right padding height
1, // RightPx - right padding width
"3x3 pooling NHWC with padding"};
bool pass = this->RunPool2D(config);
EXPECT_TRUE(pass);
}
// 3D Pooling Tests (NDHWC)
TYPED_TEST(TestCkTilePooling, Pool3D_2x2x2)
{
typename TestFixture::Config3D config = {1, // N - batch size
@@ -216,7 +405,7 @@ TYPED_TEST(TestCkTilePooling, Pool3D_2x2x2)
0, // RightPz - right padding depth
0, // RightPy - right padding height
0, // RightPx - right padding width
"2x2x2 pooling"};
"2x2x2 pooling NDHWC"};
bool pass = this->RunPool3D(config);
EXPECT_TRUE(pass);
}
@@ -243,7 +432,7 @@ TYPED_TEST(TestCkTilePooling, Pool3D_3x3x3)
1, // RightPz - right padding depth
1, // RightPy - right padding height
1, // RightPx - right padding width
"3x3x3 pooling"};
"3x3x3 pooling NDHWC with padding"};
bool pass = this->RunPool3D(config);
EXPECT_TRUE(pass);
}