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Unverified Commit 9f8ab221 authored by zjing14's avatar zjing14 Committed by GitHub
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Merge branch 'develop' into add_int8_wmma_example_instance

parents 755ace59 b4fc4d0b
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test/grouped_convnd_fwd/grouped_convnd_fwd.cpp deleted 100644 → 0
View file @ 755ace59
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include <iostream>
#include <initializer_list>
#include <vector>
#include <gtest/gtest.h>
#include "profiler/profile_grouped_conv_fwd_impl.hpp"
class TestGroupedConvNdFwd : public ::testing::Test
{
protected:
std::vector<ck::utils::conv::ConvParam> conv_params;
};
// 1d GNWC/GKXC/GNWK
TEST_F(TestGroupedConvNdFwd, GroupedConv1dFwdGNWC)
{
conv_params.clear();
conv_params.push_back({1, 2, 128, 128, 256, {1}, {14}, {2}, {1}, {0}, {0}});
conv_params.push_back({1, 2, 128, 128, 256, {3}, {28}, {1}, {1}, {1}, {1}});
conv_params.push_back({1, 2, 128, 128, 256, {1}, {3}, {1}, {1}, {0}, {0}});
conv_params.push_back({1, 1, 1, 1, 32, {3}, {32}, {1}, {1}, {1}, {1}});
conv_params.push_back({1, 1, 1, 64, 3, {3}, {32}, {1}, {1}, {1}, {1}});
for(auto& param : conv_params)
{
bool pass;
// fp32
pass = ck::profiler::profile_grouped_conv_fwd_impl<1,
ck::tensor_layout::convolution::GNWC,
ck::tensor_layout::convolution::GKXC,
ck::tensor_layout::convolution::GNWK,
float,
float,
float>(true, // do_verification
1, // init_method
false, // do_log
false, // time_kernel
param);
EXPECT_TRUE(pass);
// fp16
pass = ck::profiler::profile_grouped_conv_fwd_impl<1,
ck::tensor_layout::convolution::GNWC,
ck::tensor_layout::convolution::GKXC,
ck::tensor_layout::convolution::GNWK,
ck::half_t,
ck::half_t,
ck::half_t>(true, // do_verification
1, // init_method
false, // do_log
false, // time_kernel
param);
EXPECT_TRUE(pass);
// bf16
pass = ck::profiler::profile_grouped_conv_fwd_impl<1,
ck::tensor_layout::convolution::GNWC,
ck::tensor_layout::convolution::GKXC,
ck::tensor_layout::convolution::GNWK,
ck::bhalf_t,
ck::bhalf_t,
ck::bhalf_t>(true, // do_verification
1, // init_method
false, // do_log
false, // time_kernel
param);
EXPECT_TRUE(pass);
// int8
pass = ck::profiler::profile_grouped_conv_fwd_impl<1,
ck::tensor_layout::convolution::GNWC,
ck::tensor_layout::convolution::GKXC,
ck::tensor_layout::convolution::GNWK,
int8_t,
int8_t,
int8_t>(true, // do_verification
1, // init_method
false, // do_log
false, // time_kernel
param);
EXPECT_TRUE(pass);
}
}
// 2d GNHWC/GKYXC/GNHWK
TEST_F(TestGroupedConvNdFwd, GroupedConv2dFwdGNHWC)
{
conv_params.clear();
conv_params.push_back({2, 2, 128, 128, 256, {1, 1}, {7, 7}, {2, 2}, {1, 1}, {0, 0}, {0, 0}});
conv_params.push_back({2, 2, 128, 128, 256, {3, 3}, {14, 14}, {1, 1}, {1, 1}, {1, 1}, {1, 1}});
conv_params.push_back({2, 2, 128, 128, 256, {1, 1}, {3, 3}, {1, 1}, {1, 1}, {0, 0}, {0, 0}});
conv_params.push_back({2, 1, 1, 1, 32, {3, 3}, {32, 32}, {1, 1}, {1, 1}, {1, 1}, {1, 1}});
conv_params.push_back({2, 1, 1, 64, 3, {3, 3}, {32, 32}, {1, 1}, {1, 1}, {1, 1}, {1, 1}});
conv_params.push_back({2, 1, 1, 1, 1, {3, 3}, {32, 32}, {1, 1}, {1, 1}, {1, 1}, {1, 1}});
for(auto& param : conv_params)
{
bool pass;
// fp32
pass = ck::profiler::profile_grouped_conv_fwd_impl<2,
ck::tensor_layout::convolution::GNHWC,
ck::tensor_layout::convolution::GKYXC,
ck::tensor_layout::convolution::GNHWK,
float,
float,
float>(true, // do_verification
1, // init_method
false, // do_log
false, // time_kernel
param);
EXPECT_TRUE(pass);
// fp16
pass = ck::profiler::profile_grouped_conv_fwd_impl<2,
ck::tensor_layout::convolution::GNHWC,
ck::tensor_layout::convolution::GKYXC,
ck::tensor_layout::convolution::GNHWK,
ck::half_t,
ck::half_t,
ck::half_t>(true, // do_verification
1, // init_method
false, // do_log
false, // time_kernel
param);
EXPECT_TRUE(pass);
// bf16
pass = ck::profiler::profile_grouped_conv_fwd_impl<2,
ck::tensor_layout::convolution::GNHWC,
ck::tensor_layout::convolution::GKYXC,
ck::tensor_layout::convolution::GNHWK,
ck::bhalf_t,
ck::bhalf_t,
ck::bhalf_t>(true, // do_verification
1, // init_method
false, // do_log
false, // time_kernel
param);
EXPECT_TRUE(pass);
// int8
pass = ck::profiler::profile_grouped_conv_fwd_impl<2,
ck::tensor_layout::convolution::GNHWC,
ck::tensor_layout::convolution::GKYXC,
ck::tensor_layout::convolution::GNHWK,
int8_t,
int8_t,
int8_t>(true, // do_verification
1, // init_method
false, // do_log
false, // time_kernel
param);
EXPECT_TRUE(pass);
}
}
// 3d GNDHWC/GKZYXC/GNDHWK
TEST_F(TestGroupedConvNdFwd, GroupedConv3dFwdGNDHWC)
{
conv_params.clear();
conv_params.push_back(
{3, 2, 128, 128, 256, {1, 1, 1}, {7, 7, 7}, {2, 2, 2}, {1, 1, 1}, {0, 0, 0}, {0, 0, 0}});
conv_params.push_back(
{3, 2, 128, 128, 256, {3, 3, 3}, {14, 14, 3}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}});
conv_params.push_back(
{3, 2, 128, 128, 256, {1, 1, 1}, {3, 3, 3}, {1, 1, 1}, {1, 1, 1}, {0, 0, 0}, {0, 0, 0}});
conv_params.push_back(
{3, 1, 1, 1, 32, {3, 3, 3}, {32, 32, 32}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}});
this->conv_params.push_back(
{3, 1, 1, 64, 3, {3, 3, 3}, {32, 32, 32}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}});
conv_params.push_back(
{3, 1, 1, 1, 1, {3, 3, 3}, {32, 32, 32}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}});
for(auto& param : conv_params)
{
bool pass;
// fp32
pass = ck::profiler::profile_grouped_conv_fwd_impl<3,
ck::tensor_layout::convolution::GNDHWC,
ck::tensor_layout::convolution::GKZYXC,
ck::tensor_layout::convolution::GNDHWK,
float,
float,
float>(true, // do_verification
1, // init_method
false, // do_log
false, // time_kernel
param);
EXPECT_TRUE(pass);
// fp16
pass = ck::profiler::profile_grouped_conv_fwd_impl<3,
ck::tensor_layout::convolution::GNDHWC,
ck::tensor_layout::convolution::GKZYXC,
ck::tensor_layout::convolution::GNDHWK,
ck::half_t,
ck::half_t,
ck::half_t>(true, // do_verification
1, // init_method
false, // do_log
false, // time_kernel
param);
EXPECT_TRUE(pass);
// bf16
pass = ck::profiler::profile_grouped_conv_fwd_impl<3,
ck::tensor_layout::convolution::GNDHWC,
ck::tensor_layout::convolution::GKZYXC,
ck::tensor_layout::convolution::GNDHWK,
ck::bhalf_t,
ck::bhalf_t,
ck::bhalf_t>(true, // do_verification
1, // init_method
false, // do_log
false, // time_kernel
param);
EXPECT_TRUE(pass);
// int8
pass = ck::profiler::profile_grouped_conv_fwd_impl<3,
ck::tensor_layout::convolution::GNDHWC,
ck::tensor_layout::convolution::GKZYXC,
ck::tensor_layout::convolution::GNDHWK,
int8_t,
int8_t,
int8_t>(true, // do_verification
1, // init_method
false, // do_log
false, // time_kernel
param);
EXPECT_TRUE(pass);
}
}
// 2d NHWGC/KYXGC/NHWGK
TEST_F(TestGroupedConvNdFwd, GroupedConv2dFwdNHWGC)
{
conv_params.clear();
conv_params.push_back({2, 2, 128, 128, 256, {1, 1}, {7, 7}, {2, 2}, {1, 1}, {0, 0}, {0, 0}});
conv_params.push_back({2, 2, 128, 128, 256, {3, 3}, {14, 14}, {1, 1}, {1, 1}, {1, 1}, {1, 1}});
conv_params.push_back({2, 2, 128, 128, 256, {1, 1}, {3, 3}, {1, 1}, {1, 1}, {0, 0}, {0, 0}});
conv_params.push_back({2, 1, 1, 1, 32, {3, 3}, {32, 32}, {1, 1}, {1, 1}, {1, 1}, {1, 1}});
conv_params.push_back({2, 1, 1, 64, 3, {3, 3}, {32, 32}, {1, 1}, {1, 1}, {1, 1}, {1, 1}});
conv_params.push_back({2, 1, 1, 1, 1, {3, 3}, {32, 32}, {1, 1}, {1, 1}, {1, 1}, {1, 1}});
for(auto& param : conv_params)
{
bool pass;
// fp16
pass = ck::profiler::profile_grouped_conv_fwd_impl<2,
ck::tensor_layout::convolution::NHWGC,
ck::tensor_layout::convolution::GKYXC,
ck::tensor_layout::convolution::NHWGK,
ck::half_t,
ck::half_t,
ck::half_t>(true, // do_verification
1, // init_method
false, // do_log
false, // time_kernel
param);
EXPECT_TRUE(pass);
}
}
test/grouped_convnd_fwd/test_grouped_convnd_fwd.cpp 0 → 100644
View file @ 9f8ab221
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include <iostream>
#include <initializer_list>
#include <vector>
#include <gtest/gtest.h>
#include "profiler/profile_grouped_conv_fwd_impl.hpp"
template <typename Tuple>
class TestGroupedConvndFwd : public ::testing::Test
{
protected:
using DataType = std::tuple_element_t<0, Tuple>;
using InLayout = std::tuple_element_t<1, Tuple>;
using WeiLayout = std::tuple_element_t<2, Tuple>;
using OutLayout = std::tuple_element_t<3, 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_grouped_conv_fwd_impl<NDimSpatial,
InLayout,
WeiLayout,
OutLayout,
DataType,
DataType,
DataType>(
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, GNWC, GKXC, GNWK>,
std::tuple<ck::half_t, GNWC, GKXC, GNWK>,
std::tuple<ck::bhalf_t, GNWC, GKXC, GNWK>,
std::tuple<int8_t, GNWC, GKXC, GNWK>>;
using KernelTypes2d = ::testing::Types<std::tuple<float, GNHWC, GKYXC, GNHWK>,
std::tuple<ck::half_t, GNHWC, GKYXC, GNHWK>,
std::tuple<ck::bhalf_t, GNHWC, GKYXC, GNHWK>,
std::tuple<int8_t, GNHWC, GKYXC, GNHWK>,
std::tuple<float, NHWGC, GKYXC, NHWGK>,
std::tuple<ck::half_t, NHWGC, GKYXC, NHWGK>,
std::tuple<ck::bhalf_t, NHWGC, GKYXC, NHWGK>,
std::tuple<int8_t, NHWGC, GKYXC, NHWGK>>;
using KernelTypes3d = ::testing::Types<std::tuple<float, GNDHWC, GKZYXC, GNDHWK>,
std::tuple<ck::half_t, GNDHWC, GKZYXC, GNDHWK>,
std::tuple<ck::bhalf_t, GNDHWC, GKZYXC, GNDHWK>,
std::tuple<int8_t, GNDHWC, GKZYXC, GNDHWK>,
std::tuple<float, NDHWGC, GKZYXC, NDHWGK>,
std::tuple<ck::half_t, NDHWGC, GKZYXC, NDHWGK>,
std::tuple<ck::bhalf_t, NDHWGC, GKZYXC, NDHWGK>,
std::tuple<int8_t, NDHWGC, GKZYXC, NDHWGK>>;
template <typename Tuple>
class TestGroupedConvndFwd1d : public TestGroupedConvndFwd<Tuple>
{
};
template <typename Tuple>
class TestGroupedConvndFwd2d : public TestGroupedConvndFwd<Tuple>
{
};
template <typename Tuple>
class TestGroupedConvndFwd3d : public TestGroupedConvndFwd<Tuple>
{
};
TYPED_TEST_SUITE(TestGroupedConvndFwd1d, KernelTypes1d);
TYPED_TEST_SUITE(TestGroupedConvndFwd2d, KernelTypes2d);
TYPED_TEST_SUITE(TestGroupedConvndFwd3d, KernelTypes3d);
TYPED_TEST(TestGroupedConvndFwd1d, Test1D)
{
this->conv_params.clear();
this->conv_params.push_back({1, 2, 32, 128, 256, {1}, {14}, {2}, {1}, {0}, {0}});
this->conv_params.push_back({1, 2, 32, 128, 256, {3}, {28}, {1}, {1}, {1}, {1}});
this->conv_params.push_back({1, 2, 32, 128, 256, {1}, {3}, {1}, {1}, {0}, {0}});
this->conv_params.push_back({1, 1, 1, 1, 32, {3}, {32}, {1}, {1}, {1}, {1}});
this->conv_params.push_back({1, 1, 1, 64, 3, {3}, {32}, {1}, {1}, {1}, {1}});
this->template Run<1>();
}
TYPED_TEST(TestGroupedConvndFwd2d, Test2D)
{
this->conv_params.clear();
this->conv_params.push_back(
{2, 2, 32, 128, 256, {1, 1}, {7, 7}, {2, 2}, {1, 1}, {0, 0}, {0, 0}});
this->conv_params.push_back(
{2, 2, 32, 128, 256, {3, 3}, {14, 14}, {1, 1}, {1, 1}, {1, 1}, {1, 1}});
this->conv_params.push_back(
{2, 2, 32, 128, 256, {1, 1}, {3, 3}, {1, 1}, {1, 1}, {0, 0}, {0, 0}});
this->conv_params.push_back({2, 1, 1, 1, 32, {3, 3}, {32, 32}, {1, 1}, {1, 1}, {1, 1}, {1, 1}});
this->conv_params.push_back({2, 1, 1, 64, 3, {3, 3}, {32, 32}, {1, 1}, {1, 1}, {1, 1}, {1, 1}});
this->conv_params.push_back({2, 1, 1, 1, 1, {3, 3}, {32, 32}, {1, 1}, {1, 1}, {1, 1}, {1, 1}});
this->template Run<2>();
}
TYPED_TEST(TestGroupedConvndFwd3d, Test3D)
{
this->conv_params.clear();
this->conv_params.push_back(
{3, 2, 32, 128, 256, {1, 1, 1}, {7, 7, 7}, {2, 2, 2}, {1, 1, 1}, {0, 0, 0}, {0, 0, 0}});
this->conv_params.push_back(
{3, 2, 32, 128, 256, {3, 3, 3}, {14, 14, 3}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}});
this->conv_params.push_back(
{3, 2, 32, 128, 256, {1, 1, 1}, {3, 3, 3}, {1, 1, 1}, {1, 1, 1}, {0, 0, 0}, {0, 0, 0}});
this->conv_params.push_back(
{3, 1, 1, 1, 32, {3, 3, 3}, {32, 32, 32}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}});
this->conv_params.push_back(
{3, 1, 1, 64, 3, {3, 3, 3}, {32, 32, 32}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}});
this->conv_params.push_back(
{3, 1, 1, 1, 1, {3, 3, 3}, {32, 32, 32}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}});
this->template Run<3>();
}
test/grouped_gemm/CMakeLists.txt
View file @ 9f8ab221
if(DTYPES MATCHES "fp16" OR NOT DEFINED DTYPES)
list(APPEND gpu_list gfx908 gfx90a gfx940 gfx941 gfx942)
set(target 0)
foreach(gpu IN LISTS GPU_TARGETS)
......@@ -13,4 +12,3 @@ foreach(gpu IN LISTS GPU_TARGETS)
set(target 1)
endif()
endforeach()
endif()
test/image_to_column/CMakeLists.txt deleted 100644 → 0
View file @ 755ace59
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)
test/normalization/CMakeLists.txt
View file @ 9f8ab221
if(DTYPES MATCHES "fp16" OR DTYPES MATCHES "fp32" OR NOT DEFINED DTYPES)
add_custom_target(test_normalization)
endif()
if(DTYPES MATCHES "fp32" OR NOT DEFINED DTYPES)
add_gtest_executable(test_layernorm2d_fp32 test_layernorm2d_fp32.cpp)
add_gtest_executable(test_groupnorm_fp32 test_groupnorm_fp32.cpp)
add_custom_target(test_normalization)
add_gtest_executable(test_layernorm2d_fp32 test_layernorm2d_fp32.cpp)
if(result EQUAL 0)
target_link_libraries(test_layernorm2d_fp32 PRIVATE utility device_normalization_instance)
target_link_libraries(test_groupnorm_fp32 PRIVATE utility device_normalization_instance)
add_dependencies(test_normalization test_layernorm2d_fp32)
endif()
add_gtest_executable(test_groupnorm_fp32 test_groupnorm_fp32.cpp)
if(result EQUAL 0)
target_link_libraries(test_groupnorm_fp32 PRIVATE utility device_normalization_instance)
add_dependencies(test_normalization test_groupnorm_fp32)
endif()
if(DTYPES MATCHES "fp16" OR NOT DEFINED DTYPES)
add_gtest_executable(test_layernorm2d_fp16 test_layernorm2d_fp16.cpp)
add_gtest_executable(test_groupnorm_fp16 test_groupnorm_fp16.cpp)
add_gtest_executable(test_layernorm2d_fp16 test_layernorm2d_fp16.cpp)
if(result EQUAL 0)
target_link_libraries(test_layernorm2d_fp16 PRIVATE utility device_normalization_instance)
target_link_libraries(test_groupnorm_fp16 PRIVATE utility device_normalization_instance)
add_dependencies(test_normalization test_layernorm2d_fp16)
endif()
add_gtest_executable(test_groupnorm_fp16 test_groupnorm_fp16.cpp)
if(result EQUAL 0)
target_link_libraries(test_groupnorm_fp16 PRIVATE utility device_normalization_instance)
add_dependencies(test_normalization test_groupnorm_fp16)
endif()
test/normalization/test_groupnorm_fp16.cpp
View file @ 9f8ab221
......@@ -12,11 +12,12 @@ template <typename Tuple>
class TestGroupnorm : public ::testing::Test
{
protected:
using XDataType = std::tuple_element_t<0, Tuple>;
using GammaDataType = std::tuple_element_t<1, Tuple>;
using BetaDataType = std::tuple_element_t<2, Tuple>;
using ComputeDataType = std::tuple_element_t<3, Tuple>;
using YDataType = std::tuple_element_t<4, Tuple>;
using XDataType = std::tuple_element_t<0, Tuple>;
using GammaDataType = std::tuple_element_t<1, Tuple>;
using BetaDataType = std::tuple_element_t<2, Tuple>;
using ComputeDataType = std::tuple_element_t<3, Tuple>;
using YDataType = std::tuple_element_t<4, Tuple>;
using SaveMeanInvStdDataType = std::tuple_element_t<5, Tuple>;
void Run()
{
......@@ -37,7 +38,9 @@ class TestGroupnorm : public ::testing::Test
GammaDataType,
BetaDataType,
ComputeDataType,
YDataType>(true, 2, false, false, length);
YDataType,
SaveMeanInvStdDataType,
true>(true, 2, false, false, length);
EXPECT_TRUE(success);
}
}
......@@ -45,7 +48,7 @@ class TestGroupnorm : public ::testing::Test
using KernelTypes = ::testing::Types<
// XDataType, GammaDataType, BetaDataType, ComputeDataType, YDataType>
std::tuple<F16, F16, F16, F32, F16>>;
std::tuple<F16, F16, F16, F32, F16, F32>>;
TYPED_TEST_SUITE(TestGroupnorm, KernelTypes);
TYPED_TEST(TestGroupnorm, Test_FP16) { this->Run(); }
test/normalization/test_groupnorm_fp32.cpp
View file @ 9f8ab221
......@@ -12,11 +12,12 @@ template <typename Tuple>
class TestGroupnorm : public ::testing::Test
{
protected:
using XDataType = std::tuple_element_t<0, Tuple>;
using GammaDataType = std::tuple_element_t<1, Tuple>;
using BetaDataType = std::tuple_element_t<2, Tuple>;
using ComputeDataType = std::tuple_element_t<3, Tuple>;
using YDataType = std::tuple_element_t<4, Tuple>;
using XDataType = std::tuple_element_t<0, Tuple>;
using GammaDataType = std::tuple_element_t<1, Tuple>;
using BetaDataType = std::tuple_element_t<2, Tuple>;
using ComputeDataType = std::tuple_element_t<3, Tuple>;
using YDataType = std::tuple_element_t<4, Tuple>;
using SaveMeanInvStdDataType = std::tuple_element_t<5, Tuple>;
void Run()
{
......@@ -35,7 +36,9 @@ class TestGroupnorm : public ::testing::Test
GammaDataType,
BetaDataType,
ComputeDataType,
YDataType>(true, 2, false, false, length);
YDataType,
SaveMeanInvStdDataType,
true>(true, 2, false, false, length);
EXPECT_TRUE(success);
}
}
......@@ -43,7 +46,7 @@ class TestGroupnorm : public ::testing::Test
using KernelTypes = ::testing::Types<
// XDataType, GammaDataType, BetaDataType, ComputeDataType, YDataType>
std::tuple<F32, F32, F32, F32, F32>>;
std::tuple<F32, F32, F32, F32, F32, F32>>;
TYPED_TEST_SUITE(TestGroupnorm, KernelTypes);
TYPED_TEST(TestGroupnorm, Test_FP32) { this->Run(); }
test/normalization/test_layernorm2d_fp16.cpp
View file @ 9f8ab221
......@@ -12,11 +12,12 @@ template <typename Tuple>
class TestLayernorm2d : public ::testing::Test
{
protected:
using XDataType = std::tuple_element_t<0, Tuple>;
using GammaDataType = std::tuple_element_t<1, Tuple>;
using BetaDataType = std::tuple_element_t<2, Tuple>;
using ComputeDataType = std::tuple_element_t<3, Tuple>;
using YDataType = std::tuple_element_t<4, Tuple>;
using XDataType = std::tuple_element_t<0, Tuple>;
using GammaDataType = std::tuple_element_t<1, Tuple>;
using BetaDataType = std::tuple_element_t<2, Tuple>;
using ComputeDataType = std::tuple_element_t<3, Tuple>;
using YDataType = std::tuple_element_t<4, Tuple>;
using SaveMeanInvStdDataType = std::tuple_element_t<5, Tuple>;
void Run()
{
......@@ -31,6 +32,8 @@ class TestLayernorm2d : public ::testing::Test
BetaDataType,
ComputeDataType,
YDataType,
SaveMeanInvStdDataType,
true,
2>(true, 2, false, false, length);
EXPECT_TRUE(success);
}
......@@ -39,7 +42,7 @@ class TestLayernorm2d : public ::testing::Test
using KernelTypes = ::testing::Types<
// XDataType, GammaDataType, BetaDataType, ComputeDataType, YDataType>
std::tuple<F16, F16, F16, F32, F16>>;
std::tuple<F16, F16, F16, F32, F16, F32>>;
TYPED_TEST_SUITE(TestLayernorm2d, KernelTypes);
TYPED_TEST(TestLayernorm2d, Test_FP16) { this->Run(); }
test/normalization/test_layernorm2d_fp32.cpp
View file @ 9f8ab221
......@@ -12,11 +12,12 @@ template <typename Tuple>
class TestLayernorm2d : public ::testing::Test
{
protected:
using XDataType = std::tuple_element_t<0, Tuple>;
using GammaDataType = std::tuple_element_t<1, Tuple>;
using BetaDataType = std::tuple_element_t<2, Tuple>;
using ComputeDataType = std::tuple_element_t<3, Tuple>;
using YDataType = std::tuple_element_t<4, Tuple>;
using XDataType = std::tuple_element_t<0, Tuple>;
using GammaDataType = std::tuple_element_t<1, Tuple>;
using BetaDataType = std::tuple_element_t<2, Tuple>;
using ComputeDataType = std::tuple_element_t<3, Tuple>;
using YDataType = std::tuple_element_t<4, Tuple>;
using SaveMeanInvStdDataType = std::tuple_element_t<5, Tuple>;
void Run()
{
......@@ -31,6 +32,8 @@ class TestLayernorm2d : public ::testing::Test
BetaDataType,
ComputeDataType,
YDataType,
SaveMeanInvStdDataType,
true,
2>(true, 2, false, false, length);
EXPECT_TRUE(success);
}
......@@ -39,7 +42,7 @@ class TestLayernorm2d : public ::testing::Test
using KernelTypes = ::testing::Types<
// XDataType, GammaDataType, BetaDataType, ComputeDataType, YDataType>
std::tuple<F32, F32, F32, F32, F32>>;
std::tuple<F32, F32, F32, F32, F32, F32>>;
TYPED_TEST_SUITE(TestLayernorm2d, KernelTypes);
TYPED_TEST(TestLayernorm2d, Test_FP32) { this->Run(); }
test/reduce/CMakeLists.txt
View file @ 9f8ab221
add_test_executable(test_reduce_no_index reduce_no_index.cpp)
add_test_executable(test_reduce_with_index reduce_with_index.cpp)
target_link_libraries(test_reduce_no_index PRIVATE utility)
target_link_libraries(test_reduce_no_index PRIVATE device_reduce_instance)
target_link_libraries(test_reduce_with_index PRIVATE utility)
target_link_libraries(test_reduce_with_index PRIVATE device_reduce_instance)
target_link_libraries(test_reduce_no_index PRIVATE utility device_reduce_instance)
target_link_libraries(test_reduce_with_index PRIVATE utility device_reduce_instance)
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