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Commit d84da366 authored by Chao Liu's avatar Chao Liu
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update test for conv fwd

parent 74603261
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Showing with 229 additions and 964 deletions
test/convnd_bwd_data/convnd_bwd_data.cpp
View file @ d84da366
...@@ -22,6 +22,7 @@ int main() ...@@ -22,6 +22,7 @@ int main()
for(auto& param : params) for(auto& param : params)
{ {
// fp32
pass &= ck::profiler::profile_conv_bwd_data_impl<1, pass &= ck::profiler::profile_conv_bwd_data_impl<1,
ck::tensor_layout::convolution::NWC, ck::tensor_layout::convolution::NWC,
ck::tensor_layout::convolution::KXC, ck::tensor_layout::convolution::KXC,
...@@ -34,6 +35,7 @@ int main() ...@@ -34,6 +35,7 @@ int main()
false, // time_kernel false, // time_kernel
param); param);
// fp16
pass &= ck::profiler::profile_conv_bwd_data_impl<1, pass &= ck::profiler::profile_conv_bwd_data_impl<1,
ck::tensor_layout::convolution::NWC, ck::tensor_layout::convolution::NWC,
ck::tensor_layout::convolution::KXC, ck::tensor_layout::convolution::KXC,
...@@ -46,6 +48,7 @@ int main() ...@@ -46,6 +48,7 @@ int main()
false, // time_kernel false, // time_kernel
param); param);
// bf16
pass &= ck::profiler::profile_conv_bwd_data_impl<1, pass &= ck::profiler::profile_conv_bwd_data_impl<1,
ck::tensor_layout::convolution::NWC, ck::tensor_layout::convolution::NWC,
ck::tensor_layout::convolution::KXC, ck::tensor_layout::convolution::KXC,
...@@ -58,6 +61,7 @@ int main() ...@@ -58,6 +61,7 @@ int main()
false, // time_kernel false, // time_kernel
param); param);
// int8
pass &= ck::profiler::profile_conv_bwd_data_impl<1, pass &= ck::profiler::profile_conv_bwd_data_impl<1,
ck::tensor_layout::convolution::NWC, ck::tensor_layout::convolution::NWC,
ck::tensor_layout::convolution::KXC, ck::tensor_layout::convolution::KXC,
...@@ -79,6 +83,7 @@ int main() ...@@ -79,6 +83,7 @@ int main()
for(auto& param : params) for(auto& param : params)
{ {
// fp32
pass &= ck::profiler::profile_conv_bwd_data_impl<2, pass &= ck::profiler::profile_conv_bwd_data_impl<2,
ck::tensor_layout::convolution::NHWC, ck::tensor_layout::convolution::NHWC,
ck::tensor_layout::convolution::KYXC, ck::tensor_layout::convolution::KYXC,
...@@ -91,6 +96,7 @@ int main() ...@@ -91,6 +96,7 @@ int main()
false, // time_kernel false, // time_kernel
param); param);
// fp16
pass &= ck::profiler::profile_conv_bwd_data_impl<2, pass &= ck::profiler::profile_conv_bwd_data_impl<2,
ck::tensor_layout::convolution::NHWC, ck::tensor_layout::convolution::NHWC,
ck::tensor_layout::convolution::KYXC, ck::tensor_layout::convolution::KYXC,
...@@ -103,6 +109,7 @@ int main() ...@@ -103,6 +109,7 @@ int main()
false, // time_kernel false, // time_kernel
param); param);
// bf16
pass &= ck::profiler::profile_conv_bwd_data_impl<2, pass &= ck::profiler::profile_conv_bwd_data_impl<2,
ck::tensor_layout::convolution::NHWC, ck::tensor_layout::convolution::NHWC,
ck::tensor_layout::convolution::KYXC, ck::tensor_layout::convolution::KYXC,
...@@ -115,6 +122,7 @@ int main() ...@@ -115,6 +122,7 @@ int main()
false, // time_kernel false, // time_kernel
param); param);
// int8
pass &= ck::profiler::profile_conv_bwd_data_impl<2, pass &= ck::profiler::profile_conv_bwd_data_impl<2,
ck::tensor_layout::convolution::NHWC, ck::tensor_layout::convolution::NHWC,
ck::tensor_layout::convolution::KYXC, ck::tensor_layout::convolution::KYXC,
...@@ -139,6 +147,7 @@ int main() ...@@ -139,6 +147,7 @@ int main()
for(auto& param : params) for(auto& param : params)
{ {
// fp32
pass &= ck::profiler::profile_conv_bwd_data_impl<3, pass &= ck::profiler::profile_conv_bwd_data_impl<3,
ck::tensor_layout::convolution::NDHWC, ck::tensor_layout::convolution::NDHWC,
ck::tensor_layout::convolution::KZYXC, ck::tensor_layout::convolution::KZYXC,
...@@ -151,6 +160,7 @@ int main() ...@@ -151,6 +160,7 @@ int main()
false, // time_kernel false, // time_kernel
param); param);
// fp16
pass &= ck::profiler::profile_conv_bwd_data_impl<3, pass &= ck::profiler::profile_conv_bwd_data_impl<3,
ck::tensor_layout::convolution::NDHWC, ck::tensor_layout::convolution::NDHWC,
ck::tensor_layout::convolution::KZYXC, ck::tensor_layout::convolution::KZYXC,
...@@ -163,6 +173,7 @@ int main() ...@@ -163,6 +173,7 @@ int main()
false, // time_kernel false, // time_kernel
param); param);
// bf16
pass &= ck::profiler::profile_conv_bwd_data_impl<3, pass &= ck::profiler::profile_conv_bwd_data_impl<3,
ck::tensor_layout::convolution::NDHWC, ck::tensor_layout::convolution::NDHWC,
ck::tensor_layout::convolution::KZYXC, ck::tensor_layout::convolution::KZYXC,
...@@ -175,6 +186,7 @@ int main() ...@@ -175,6 +186,7 @@ int main()
false, // time_kernel false, // time_kernel
param); param);
// int8
pass &= ck::profiler::profile_conv_bwd_data_impl<3, pass &= ck::profiler::profile_conv_bwd_data_impl<3,
ck::tensor_layout::convolution::NDHWC, ck::tensor_layout::convolution::NDHWC,
ck::tensor_layout::convolution::KZYXC, ck::tensor_layout::convolution::KZYXC,
...@@ -190,12 +202,12 @@ int main() ...@@ -190,12 +202,12 @@ int main()
if(pass) if(pass)
{ {
std::cout << "test convnd bwd : Pass" << std::endl; std::cout << "test convnd bwd data: Pass" << std::endl;
return 0; return 0;
} }
else else
{ {
std::cout << "test convnd bwd: Fail " << std::endl; std::cout << "test convnd bwd data: Fail " << std::endl;
return 1; return 1;
} }
} }
test/convnd_fwd/CMakeLists.txt
View file @ d84da366
add_custom_target(test_convnd_fwd) add_test_executable(test_convnd_fwd convnd_fwd.cpp)
target_link_libraries(test_convnd_fwd PRIVATE utility device_conv1d_fwd_instance device_conv2d_fwd_instance device_conv3d_fwd_instance)
add_gtest_executable(test_conv1d_fwd conv1d_fwd.cpp)
target_link_libraries(test_conv1d_fwd PRIVATE utility device_conv1d_fwd_instance)
add_dependencies(test_convnd_fwd test_conv1d_fwd)
add_gtest_executable(test_conv2d_fwd conv2d_fwd.cpp)
target_link_libraries(test_conv2d_fwd PRIVATE utility device_conv2d_fwd_instance)
add_dependencies(test_convnd_fwd test_conv2d_fwd)
add_gtest_executable(test_conv3d_fwd conv3d_fwd.cpp)
target_link_libraries(test_conv3d_fwd PRIVATE utility device_conv3d_fwd_instance)
add_dependencies(test_convnd_fwd test_conv3d_fwd)
test/convnd_fwd/conv1d_fwd.cpp deleted 100644 → 0
View file @ 74603261
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <iostream>
#include <tuple>
#include <vector>
#include <gtest/gtest.h>
#include "ck/utility/data_type.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/utility/convolution_parameter.hpp"
#include "test/convnd_fwd/conv_util.hpp"
namespace {
class Conv1dFwdNWCInstances : public ::testing::Test
{
public:
template <typename T>
bool test_conv1d_nwc_instances(const std::vector<test::conv::DeviceConvFwdNoOpPtr>& conv_ptrs,
const ck::utils::conv::ConvParams& params)
{
using namespace std::placeholders;
using namespace ck::utils;
namespace ctl = ck::tensor_layout::convolution;
conv::ConvFwdOpInstance<T,
T,
T,
ctl::NWC,
ctl::KXC,
ctl::NWK,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough,
FillUniformDistributionIntegerValue<T>,
FillUniformDistributionIntegerValue<T>>
conv_instance(params,
true,
FillUniformDistributionIntegerValue<T>{},
FillUniformDistributionIntegerValue<T>{});
auto reference_conv_fwd_fun =
std::bind(conv::run_reference_convolution_forward<1, T, T, T>, params, _1, _2, _3);
OpInstanceRunEngine<T, T, T> run_engine(conv_instance, reference_conv_fwd_fun);
run_engine.SetAtol(atol_);
run_engine.SetRtol(rtol_);
return run_engine.Test(conv_ptrs);
}
template <typename T>
bool test_default()
{
return test_conv1d_nwc_instances<T>(
ck::utils::conv::ConvolutionFwdInstances<T, T, T>::template Get<1>(), params_default_);
}
template <typename T>
bool test_filter1x1_stride1_pad0()
{
return test_conv1d_nwc_instances<T>(
ck::utils::conv::ConvolutionFwdInstances<T, T, T>::template Get<1>(),
params_filter1x1_stride1_pad0_);
}
template <typename T>
bool test_filter1x1_pad0()
{
return test_conv1d_nwc_instances<T>(
ck::utils::conv::ConvolutionFwdInstances<T, T, T>::template Get<1>(),
params_filter1x1_pad0_);
}
static inline ck::utils::conv::ConvParams params_default_{
1, 4, 256, 64, {3}, {71}, {2}, {2}, {2}, {2}};
static inline ck::utils::conv::ConvParams params_filter1x1_stride1_pad0_{
1, 4, 256, 64, {1}, {28}, {1}, {1}, {0}, {0}};
static inline ck::utils::conv::ConvParams params_filter1x1_pad0_{
1, 4, 256, 64, {1}, {28}, {2}, {1}, {0}, {0}};
private:
double atol_{1e-5};
double rtol_{1e-4};
};
} // anonymous namespace
TEST(Conv1DFwdNWC, IntegerValues)
{
using namespace std::placeholders;
using namespace ck::utils;
namespace ctl = ck::tensor_layout::convolution;
using T = float;
ck::utils::conv::ConvParams params{1, 4, 256, 64, {3}, {36}, {1}, {2}, {2}, {2}};
std::vector<test::conv::DeviceConvFwdNoOpPtr> conv_ptrs;
test::conv::get_test_convolution_fwd_instance<1, T, T, T, T>(conv_ptrs);
conv::ConvFwdOpInstance<T,
T,
T,
ctl::NWC,
ctl::KXC,
ctl::NWK,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough,
FillUniformDistributionIntegerValue<T>,
FillUniformDistributionIntegerValue<T>>
conv_instance(params,
true,
FillUniformDistributionIntegerValue<T>{},
FillUniformDistributionIntegerValue<T>{});
auto reference_conv_fwd_fun =
std::bind(conv::run_reference_convolution_forward<1, T, T, T>, params, _1, _2, _3);
OpInstanceRunEngine<T, T, T> run_engine(conv_instance, reference_conv_fwd_fun);
run_engine.SetAtol(1e-5);
run_engine.SetRtol(1e-4);
EXPECT_TRUE(run_engine.Test(conv_ptrs));
}
TEST(Conv1DFwdNWC, FloatingPointValues)
{
using namespace std::placeholders;
using namespace ck::utils;
namespace ctl = ck::tensor_layout::convolution;
using T = ck::half_t;
ck::utils::conv::ConvParams params{1, 4, 256, 64, {3}, {36}, {1}, {2}, {2}, {2}};
std::vector<test::conv::DeviceConvFwdNoOpPtr> conv_ptrs;
test::conv::get_test_convolution_fwd_instance<1, T, T, T, float>(conv_ptrs);
conv::ConvFwdOpInstance<T,
T,
T,
ctl::NWC,
ctl::KXC,
ctl::NWK,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough,
FillUniformDistribution<T>,
FillUniformDistribution<T>>
conv_instance(params, true, FillUniformDistribution<T>{}, FillUniformDistribution<T>{});
auto reference_conv_fwd_fun =
std::bind(conv::run_reference_convolution_forward<1, T, T, T>, params, _1, _2, _3);
OpInstanceRunEngine<T, T, T> run_engine(conv_instance, reference_conv_fwd_fun);
run_engine.SetAtol(0.1);
run_engine.SetRtol(1e-2);
EXPECT_TRUE(run_engine.Test(conv_ptrs));
}
TEST_F(Conv1dFwdNWCInstances, BF16_default) { EXPECT_TRUE(this->test_default<ck::bhalf_t>()); }
TEST_F(Conv1dFwdNWCInstances, BF16_filter1x1_stride1_pad0)
{
EXPECT_TRUE(this->test_filter1x1_stride1_pad0<ck::bhalf_t>());
}
TEST_F(Conv1dFwdNWCInstances, BF16_filter1x1_pad0)
{
EXPECT_TRUE(this->test_filter1x1_pad0<ck::bhalf_t>());
}
TEST_F(Conv1dFwdNWCInstances, F16_default) { EXPECT_TRUE(this->test_default<ck::half_t>()); }
TEST_F(Conv1dFwdNWCInstances, F16_filter1x1_stride1_pad0)
{
EXPECT_TRUE(this->test_filter1x1_stride1_pad0<ck::half_t>());
}
TEST_F(Conv1dFwdNWCInstances, F16_filter1x1_pad0)
{
EXPECT_TRUE(this->test_filter1x1_pad0<ck::half_t>());
}
TEST_F(Conv1dFwdNWCInstances, F32_default) { EXPECT_TRUE(this->test_default<float>()); }
TEST_F(Conv1dFwdNWCInstances, F32_filter1x1_stride1_pad0)
{
EXPECT_TRUE(this->test_filter1x1_stride1_pad0<float>());
}
TEST_F(Conv1dFwdNWCInstances, F32_filter1x1_pad0)
{
EXPECT_TRUE(this->test_filter1x1_pad0<float>());
}
TEST_F(Conv1dFwdNWCInstances, I8_default) { EXPECT_TRUE(this->test_default<int8_t>()); }
TEST_F(Conv1dFwdNWCInstances, I8_filter1x1_stride1_pad0)
{
EXPECT_TRUE(this->test_filter1x1_stride1_pad0<int8_t>());
}
TEST_F(Conv1dFwdNWCInstances, I8_filter1x1_pad0)
{
EXPECT_TRUE(this->test_filter1x1_pad0<int8_t>());
}
test/convnd_fwd/conv2d_fwd.cpp deleted 100644 → 0
View file @ 74603261
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <tuple>
#include <vector>
#include <gtest/gtest.h>
#include "ck/utility/data_type.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/utility/convolution_parameter.hpp"
#include "test/convnd_fwd/conv_util.hpp"
namespace {
class Conv2dFwdNHWCInstances : public ::testing::Test
{
public:
template <typename T>
bool test_conv2d_nhwc_instances(const std::vector<test::conv::DeviceConvFwdNoOpPtr>& conv_ptrs,
const ck::utils::conv::ConvParams& params)
{
using namespace std::placeholders;
using namespace ck::utils;
conv::ConvFwdOpInstance<T,
T,
T,
ck::tensor_layout::convolution::NHWC,
ck::tensor_layout::convolution::KYXC,
ck::tensor_layout::convolution::NHWK,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough,
FillUniformDistributionIntegerValue<T>,
FillUniformDistributionIntegerValue<T>>
conv_instance(params,
true,
FillUniformDistributionIntegerValue<T>{},
FillUniformDistributionIntegerValue<T>{});
auto reference_conv_fwd_fun =
std::bind(conv::run_reference_convolution_forward<2, T, T, T>, params, _1, _2, _3);
OpInstanceRunEngine<T, T, T> run_engine(conv_instance, reference_conv_fwd_fun);
run_engine.SetAtol(atol_);
run_engine.SetRtol(rtol_);
return run_engine.Test(conv_ptrs);
}
template <typename T>
bool test_default(bool use_convnd = false)
{
if(use_convnd)
{
return test_conv2d_nhwc_instances<T>(
test::conv::ConvolutionNDFwdInstances<T, T, T>::Get(2), params_default_);
}
else
{
return test_conv2d_nhwc_instances<T>(
ck::utils::conv::ConvolutionFwdInstances<T, T, T>::template Get<2>(),
params_default_);
}
}
template <typename T>
bool test_filter1x1_stride1_pad0(bool use_convnd = false)
{
if(use_convnd)
{
return test_conv2d_nhwc_instances<T>(
test::conv::ConvolutionNDFwdInstances<T, T, T>::Get(2),
params_filter1x1_stride1_pad0_);
}
else
{
return test_conv2d_nhwc_instances<T>(
ck::utils::conv::ConvolutionFwdInstances<T, T, T>::template Get<2>(),
params_filter1x1_stride1_pad0_);
}
}
template <typename T>
bool test_filter1x1_pad0(bool use_convnd = false)
{
if(use_convnd)
{
return test_conv2d_nhwc_instances<T>(
test::conv::ConvolutionNDFwdInstances<T, T, T>::Get(2), params_filter1x1_pad0_);
}
else
{
return test_conv2d_nhwc_instances<T>(
ck::utils::conv::ConvolutionFwdInstances<T, T, T>::template Get<2>(),
params_filter1x1_pad0_);
}
}
template <typename T>
bool test_oddC()
{
return test_conv2d_nhwc_instances<T>(
ck::utils::conv::ConvolutionFwdInstances<T, T, T>::template Get<2>(), params_oddC_);
}
static inline ck::utils::conv::ConvParams params_default_{
2, 4, 256, 64, {3, 3}, {36, 36}, {2, 2}, {2, 2}, {2, 2}, {2, 2}};
static inline ck::utils::conv::ConvParams params_filter1x1_stride1_pad0_{
2, 4, 256, 64, {1, 1}, {28, 28}, {1, 1}, {1, 1}, {0, 0}, {0, 0}};
static inline ck::utils::conv::ConvParams params_filter1x1_pad0_{
2, 4, 256, 64, {1, 1}, {28, 28}, {2, 2}, {1, 1}, {0, 0}, {0, 0}};
static inline ck::utils::conv::ConvParams params_oddC_{
2, 4, 256, 3, {3, 3}, {28, 28}, {1, 1}, {1, 1}, {0, 0}, {0, 0}};
private:
double atol_{1e-5};
double rtol_{1e-4};
};
} // anonymous namespace
TEST(Conv2DFwdNHWC, IntegerValues)
{
using namespace std::placeholders;
using namespace ck::utils;
using T = float;
ck::utils::conv::ConvParams params{
2, 4, 256, 64, {3, 3}, {36, 36}, {1, 1}, {2, 2}, {2, 2}, {2, 2}};
std::vector<test::conv::DeviceConvFwdNoOpPtr> conv_ptrs;
test::conv::get_test_convolution_fwd_instance<2, T, T, T, T>(conv_ptrs);
conv::ConvFwdOpInstance<T,
T,
T,
ck::tensor_layout::convolution::NHWC,
ck::tensor_layout::convolution::KYXC,
ck::tensor_layout::convolution::NHWK,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough,
FillUniformDistributionIntegerValue<T>,
FillUniformDistributionIntegerValue<T>>
conv_instance(params,
true,
FillUniformDistributionIntegerValue<T>{},
FillUniformDistributionIntegerValue<T>{});
auto reference_conv_fwd_fun =
std::bind(conv::run_reference_convolution_forward<2, T, T, T>, params, _1, _2, _3);
OpInstanceRunEngine<T, T, T> run_engine(conv_instance, reference_conv_fwd_fun);
run_engine.SetAtol(1e-5);
run_engine.SetRtol(1e-4);
EXPECT_TRUE(run_engine.Test(conv_ptrs));
}
TEST(Conv2DFwdNHWC, FloatingPointValues)
{
using namespace std::placeholders;
using namespace ck::utils;
using T = ck::half_t;
ck::utils::conv::ConvParams params{
2, 4, 256, 64, {3, 3}, {36, 36}, {2, 2}, {2, 2}, {2, 2}, {2, 2}};
std::vector<test::conv::DeviceConvFwdNoOpPtr> conv_ptrs;
test::conv::get_test_convolution_fwd_instance<2, T, T, T, float>(conv_ptrs);
conv::ConvFwdOpInstance<T,
T,
T,
ck::tensor_layout::convolution::NHWC,
ck::tensor_layout::convolution::KYXC,
ck::tensor_layout::convolution::NHWK,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough,
FillUniformDistribution<T>,
FillUniformDistribution<T>>
conv_instance(params, true, FillUniformDistribution<T>{}, FillUniformDistribution<T>{});
auto reference_conv_fwd_fun =
std::bind(conv::run_reference_convolution_forward<2, T, T, T>, params, _1, _2, _3);
OpInstanceRunEngine<T, T, T> run_engine(conv_instance, reference_conv_fwd_fun);
run_engine.SetAtol(2e-4);
run_engine.SetRtol(1e-3);
EXPECT_TRUE(run_engine.Test(conv_ptrs));
}
TEST_F(Conv2dFwdNHWCInstances, BF16_default) { EXPECT_TRUE(this->test_default<ck::bhalf_t>()); }
TEST_F(Conv2dFwdNHWCInstances, BF16_filter1x1_stride1_pad0)
{
EXPECT_TRUE(this->test_filter1x1_stride1_pad0<ck::bhalf_t>());
}
TEST_F(Conv2dFwdNHWCInstances, BF16_filter1x1_pad0)
{
EXPECT_TRUE(this->test_filter1x1_pad0<ck::bhalf_t>());
}
TEST_F(Conv2dFwdNHWCInstances, F16_default) { EXPECT_TRUE(this->test_default<ck::half_t>()); }
TEST_F(Conv2dFwdNHWCInstances, F16_filter1x1_stride1_pad0)
{
EXPECT_TRUE(this->test_filter1x1_stride1_pad0<ck::half_t>());
}
TEST_F(Conv2dFwdNHWCInstances, F16_filter1x1_pad0)
{
EXPECT_TRUE(this->test_filter1x1_pad0<ck::half_t>());
}
TEST_F(Conv2dFwdNHWCInstances, F16_oddC) { EXPECT_TRUE(this->test_oddC<ck::half_t>()); }
TEST_F(Conv2dFwdNHWCInstances, F32_default) { EXPECT_TRUE(this->test_default<float>()); }
TEST_F(Conv2dFwdNHWCInstances, F32_filter1x1_stride1_pad0)
{
EXPECT_TRUE(this->test_filter1x1_stride1_pad0<float>());
}
TEST_F(Conv2dFwdNHWCInstances, F32_filter1x1_pad0)
{
EXPECT_TRUE(this->test_filter1x1_pad0<float>());
}
TEST_F(Conv2dFwdNHWCInstances, I8_default) { EXPECT_TRUE(this->test_default<int8_t>()); }
TEST_F(Conv2dFwdNHWCInstances, I8_filter1x1_stride1_pad0)
{
EXPECT_TRUE(this->test_filter1x1_stride1_pad0<int8_t>());
}
TEST_F(Conv2dFwdNHWCInstances, I8_filter1x1_pad0)
{
EXPECT_TRUE(this->test_filter1x1_pad0<int8_t>());
}
TEST_F(Conv2dFwdNHWCInstances, ND_BF16_default)
{
EXPECT_TRUE(this->test_default<ck::bhalf_t>(true));
}
TEST_F(Conv2dFwdNHWCInstances, ND_BF16_filter1x1_stride1_pad0)
{
EXPECT_TRUE(this->test_filter1x1_stride1_pad0<ck::bhalf_t>(true));
}
TEST_F(Conv2dFwdNHWCInstances, ND_BF16_filter1x1_pad0)
{
EXPECT_TRUE(this->test_filter1x1_pad0<ck::bhalf_t>(true));
}
TEST_F(Conv2dFwdNHWCInstances, ND_F16_default)
{
EXPECT_TRUE(this->test_default<ck::half_t>(true));
}
TEST_F(Conv2dFwdNHWCInstances, ND_F16_filter1x1_stride1_pad0)
{
EXPECT_TRUE(this->test_filter1x1_stride1_pad0<ck::half_t>(true));
}
TEST_F(Conv2dFwdNHWCInstances, ND_F16_filter1x1_pad0)
{
EXPECT_TRUE(this->test_filter1x1_pad0<ck::half_t>(true));
}
TEST_F(Conv2dFwdNHWCInstances, ND_F32_default) { EXPECT_TRUE(this->test_default<float>(true)); }
TEST_F(Conv2dFwdNHWCInstances, ND_F32_filter1x1_stride1_pad0)
{
EXPECT_TRUE(this->test_filter1x1_stride1_pad0<float>(true));
}
TEST_F(Conv2dFwdNHWCInstances, ND_F32_filter1x1_pad0)
{
EXPECT_TRUE(this->test_filter1x1_pad0<float>(true));
}
TEST_F(Conv2dFwdNHWCInstances, ND_I8_default) { EXPECT_TRUE(this->test_default<int8_t>(true)); }
TEST_F(Conv2dFwdNHWCInstances, ND_I8_filter1x1_stride1_pad0)
{
EXPECT_TRUE(this->test_filter1x1_stride1_pad0<int8_t>(true));
}
TEST_F(Conv2dFwdNHWCInstances, ND_I8_filter1x1_pad0)
{
EXPECT_TRUE(this->test_filter1x1_pad0<int8_t>(true));
}
test/convnd_fwd/conv3d_fwd.cpp deleted 100644 → 0
View file @ 74603261
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <iostream>
#include <stdexcept>
#include <tuple>
#include <vector>
#include <gtest/gtest.h>
#include "ck/utility/data_type.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/utility/convolution_parameter.hpp"
#include "test/convnd_fwd/conv_util.hpp"
namespace {
class Conv3dFwdNDHWCInstances : public ::testing::Test
{
public:
template <typename T>
bool test_conv3d_nwc_instances(const std::vector<test::conv::DeviceConvFwdNoOpPtr>& conv_ptrs,
const ck::utils::conv::ConvParams& params)
{
using namespace std::placeholders;
using namespace ck::utils;
namespace ctl = ck::tensor_layout::convolution;
conv::ConvFwdOpInstance<T,
T,
T,
ctl::NDHWC,
ctl::KZYXC,
ctl::NDHWK,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough,
FillUniformDistributionIntegerValue<T>,
FillUniformDistributionIntegerValue<T>>
conv_instance(params,
true,
FillUniformDistributionIntegerValue<T>{},
FillUniformDistributionIntegerValue<T>{});
auto reference_conv_fwd_fun =
std::bind(conv::run_reference_convolution_forward<3, T, T, T>, params, _1, _2, _3);
OpInstanceRunEngine<T, T, T> run_engine(conv_instance, reference_conv_fwd_fun);
run_engine.SetAtol(atol_);
run_engine.SetRtol(rtol_);
return run_engine.Test(conv_ptrs);
}
template <typename T>
bool test_default()
{
return test_conv3d_nwc_instances<T>(
ck::utils::conv::ConvolutionFwdInstances<T, T, T>::template Get<3>(), params_default_);
}
template <typename T>
bool test_filter1x1_stride1_pad0()
{
return test_conv3d_nwc_instances<T>(
ck::utils::conv::ConvolutionFwdInstances<T, T, T>::template Get<3>(),
params_filter1x1_stride1_pad0_);
}
template <typename T>
bool test_filter1x1_pad0()
{
return test_conv3d_nwc_instances<T>(
ck::utils::conv::ConvolutionFwdInstances<T, T, T>::template Get<3>(),
params_filter1x1_pad0_);
}
static inline ck::utils::conv::ConvParams params_default_{
3, 4, 256, 64, {3, 3, 3}, {28, 28, 28}, {2, 2, 2}, {2, 2, 2}, {2, 2, 2}, {2, 2, 2}};
static inline ck::utils::conv::ConvParams params_filter1x1_stride1_pad0_{
3, 4, 256, 64, {1, 1, 1}, {28, 28, 28}, {1, 1, 1}, {1, 1, 1}, {0, 0, 0}, {0, 0, 0}};
static inline ck::utils::conv::ConvParams params_filter1x1_pad0_{
3, 4, 256, 64, {1, 1, 1}, {28, 28, 28}, {2, 2, 2}, {1, 1, 1}, {0, 0, 0}, {0, 0, 0}};
private:
double atol_{1e-5};
double rtol_{1e-4};
};
} // anonymous namespace
TEST(Conv3DFwdNDHWC, IntegerValues)
{
using namespace std::placeholders;
using namespace ck::utils;
namespace ctl = ck::tensor_layout::convolution;
using T = float;
ck::utils::conv::ConvParams params{
3, 4, 256, 64, {3, 3, 3}, {18, 18, 18}, {1, 1, 1}, {2, 2, 2}, {2, 2, 2}, {2, 2, 2}};
std::vector<test::conv::DeviceConvFwdNoOpPtr> conv_ptrs;
test::conv::get_test_convolution_fwd_instance<3, T, T, T, T>(conv_ptrs);
conv::ConvFwdOpInstance<T,
T,
T,
ctl::NDHWC,
ctl::KZYXC,
ctl::NDHWK,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough,
FillUniformDistributionIntegerValue<T>,
FillUniformDistributionIntegerValue<T>>
conv_instance(params,
true,
FillUniformDistributionIntegerValue<T>{},
FillUniformDistributionIntegerValue<T>{});
auto reference_conv_fwd_fun =
std::bind(conv::run_reference_convolution_forward<3, T, T, T>, params, _1, _2, _3);
OpInstanceRunEngine<T, T, T> run_engine(conv_instance, reference_conv_fwd_fun);
run_engine.SetAtol(1e-5);
run_engine.SetRtol(1e-3);
EXPECT_TRUE(run_engine.Test(conv_ptrs));
}
TEST(Conv3DFwdNDHWC, FloatingPointValues)
{
using namespace std::placeholders;
using namespace ck::utils;
namespace ctl = ck::tensor_layout::convolution;
using T = ck::half_t;
ck::utils::conv::ConvParams params{
3, 4, 256, 64, {3, 3, 3}, {18, 18, 18}, {1, 1, 1}, {2, 2, 2}, {2, 2, 2}, {2, 2, 2}};
std::vector<test::conv::DeviceConvFwdNoOpPtr> conv_ptrs;
test::conv::get_test_convolution_fwd_instance<3, T, T, T, float>(conv_ptrs);
conv::ConvFwdOpInstance<T,
T,
T,
ctl::NDHWC,
ctl::KZYXC,
ctl::NDHWK,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough,
FillUniformDistribution<T>,
FillUniformDistribution<T>>
conv_instance(params, true, FillUniformDistribution<T>{}, FillUniformDistribution<T>{});
auto reference_conv_fwd_fun =
std::bind(conv::run_reference_convolution_forward<3, T, T, T>, params, _1, _2, _3);
OpInstanceRunEngine<T, T, T> run_engine(conv_instance, reference_conv_fwd_fun);
run_engine.SetAtol(1e-3);
run_engine.SetRtol(1e-3);
EXPECT_TRUE(run_engine.Test(conv_ptrs));
}
TEST(Conv3DFwdNDHWC, InputOver2GB)
{
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
using namespace ck::utils;
using T = float;
// >2GB Input
conv::ConvParams params;
params.num_dim_spatial_ = 3;
params.N_ = 2;
params.K_ = 16;
params.C_ = 32;
params.filter_spatial_lengths_ = std::vector<ck::index_t>{3, 3, 3};
params.input_spatial_lengths_ = std::vector<ck::index_t>{32, 1000, 1000};
params.conv_filter_strides_ = std::vector<ck::index_t>{1, 1, 1};
params.conv_filter_dilations_ = std::vector<ck::index_t>{1, 1, 1};
params.input_left_pads_ = std::vector<ck::index_t>{1, 1, 1};
params.input_right_pads_ = std::vector<ck::index_t>{1, 1, 1};
std::vector<test::conv::DeviceConvFwdNoOpPtr> conv_ptrs;
test::conv::get_test_convolution_fwd_instance<3, T, T, T, T>(conv_ptrs);
auto arg = conv_ptrs.back()->MakeArgumentPointer(nullptr,
nullptr,
nullptr,
params.N_,
params.K_,
params.C_,
params.input_spatial_lengths_,
params.filter_spatial_lengths_,
params.GetOutputSpatialLengths(),
params.conv_filter_strides_,
params.conv_filter_dilations_,
params.input_left_pads_,
params.input_right_pads_,
PassThrough{},
PassThrough{},
PassThrough{});
EXPECT_FALSE(conv_ptrs.back()->IsSupportedArgument(arg.get()));
}
TEST(Conv3DFwdNDHWC, FiltersOver2GB)
{
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
using namespace ck::utils;
using T = float;
// >2GB Filters
conv::ConvParams params;
params.num_dim_spatial_ = 3;
params.N_ = 2;
params.K_ = 16;
params.C_ = 32;
params.filter_spatial_lengths_ = std::vector<ck::index_t>{4, 1000, 1000};
params.input_spatial_lengths_ = std::vector<ck::index_t>{16, 16, 16};
params.conv_filter_strides_ = std::vector<ck::index_t>{1, 1, 1};
params.conv_filter_dilations_ = std::vector<ck::index_t>{1, 1, 1};
params.input_left_pads_ = std::vector<ck::index_t>{1, 1, 1};
params.input_right_pads_ = std::vector<ck::index_t>{1, 1, 1};
std::vector<test::conv::DeviceConvFwdNoOpPtr> conv_ptrs;
test::conv::get_test_convolution_fwd_instance<3, T, T, T, T>(conv_ptrs);
auto arg = conv_ptrs.back()->MakeArgumentPointer(nullptr,
nullptr,
nullptr,
params.N_,
params.K_,
params.C_,
params.input_spatial_lengths_,
params.filter_spatial_lengths_,
params.GetOutputSpatialLengths(),
params.conv_filter_strides_,
params.conv_filter_dilations_,
params.input_left_pads_,
params.input_right_pads_,
PassThrough{},
PassThrough{},
PassThrough{});
EXPECT_FALSE(conv_ptrs.back()->IsSupportedArgument(arg.get()));
}
TEST(Conv3DFwdNDHWC, OutputOver2GB)
{
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
using namespace ck::utils;
using T = float;
// >2GB Output
conv::ConvParams params;
params.num_dim_spatial_ = 3;
params.N_ = 2;
params.K_ = 16;
params.C_ = 2;
params.filter_spatial_lengths_ = std::vector<ck::index_t>{1, 1, 1};
params.input_spatial_lengths_ = std::vector<ck::index_t>{1000, 1000, 30};
params.conv_filter_strides_ = std::vector<ck::index_t>{1, 1, 1};
params.conv_filter_dilations_ = std::vector<ck::index_t>{1, 1, 1};
params.input_left_pads_ = std::vector<ck::index_t>{2, 2, 2};
params.input_right_pads_ = std::vector<ck::index_t>{2, 2, 2};
std::vector<test::conv::DeviceConvFwdNoOpPtr> conv_ptrs;
test::conv::get_test_convolution_fwd_instance<3, T, T, T, T>(conv_ptrs);
auto arg = conv_ptrs.back()->MakeArgumentPointer(nullptr,
nullptr,
nullptr,
params.N_,
params.K_,
params.C_,
params.input_spatial_lengths_,
params.filter_spatial_lengths_,
params.GetOutputSpatialLengths(),
params.conv_filter_strides_,
params.conv_filter_dilations_,
params.input_left_pads_,
params.input_right_pads_,
PassThrough{},
PassThrough{},
PassThrough{});
EXPECT_FALSE(conv_ptrs.back()->IsSupportedArgument(arg.get()));
}
TEST_F(Conv3dFwdNDHWCInstances, BF16_default) { EXPECT_TRUE(this->test_default<ck::bhalf_t>()); }
TEST_F(Conv3dFwdNDHWCInstances, BF16_filter1x1_stride1_pad0)
{
EXPECT_TRUE(this->test_filter1x1_stride1_pad0<ck::bhalf_t>());
}
TEST_F(Conv3dFwdNDHWCInstances, BF16_filter1x1_pad0)
{
EXPECT_TRUE(this->test_filter1x1_pad0<ck::bhalf_t>());
}
TEST_F(Conv3dFwdNDHWCInstances, F16_default) { EXPECT_TRUE(this->test_default<ck::half_t>()); }
TEST_F(Conv3dFwdNDHWCInstances, F16_filter1x1_stride1_pad0)
{
EXPECT_TRUE(this->test_filter1x1_stride1_pad0<ck::half_t>());
}
TEST_F(Conv3dFwdNDHWCInstances, F16_filter1x1_pad0)
{
EXPECT_TRUE(this->test_filter1x1_pad0<ck::half_t>());
}
TEST_F(Conv3dFwdNDHWCInstances, F32_default) { EXPECT_TRUE(this->test_default<float>()); }
TEST_F(Conv3dFwdNDHWCInstances, F32_filter1x1_stride1_pad0)
{
EXPECT_TRUE(this->test_filter1x1_stride1_pad0<float>());
}
TEST_F(Conv3dFwdNDHWCInstances, F32_filter1x1_pad0)
{
EXPECT_TRUE(this->test_filter1x1_pad0<float>());
}
TEST_F(Conv3dFwdNDHWCInstances, I8_default) { EXPECT_TRUE(this->test_default<int8_t>()); }
TEST_F(Conv3dFwdNDHWCInstances, I8_filter1x1_stride1_pad0)
{
EXPECT_TRUE(this->test_filter1x1_stride1_pad0<int8_t>());
}
TEST_F(Conv3dFwdNDHWCInstances, I8_filter1x1_pad0)
{
EXPECT_TRUE(this->test_filter1x1_pad0<int8_t>());
}
test/convnd_fwd/conv_util.hpp deleted 100644 → 0
View file @ 74603261
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include <tuple>
#include "ck/ck.hpp"
#include "ck/utility/sequence.hpp"
#include "ck/utility/data_type.hpp"
#include "ck/tensor_operation/gpu/device/device_convnd_fwd_xdl_nhwc_kyxc_nhwk.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/utility/host_tensor.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
using DeviceConvFwdNoOpPtr = DeviceConvFwdPtr<element_wise::PassThrough,
element_wise::PassThrough,
element_wise::PassThrough>;
namespace instance {
void add_device_convnd_2d_fwd_xdl_nhwc_kyxc_nhwk_bf16_instances(std::vector<DeviceConvFwdNoOpPtr>&);
void add_device_convnd_2d_fwd_xdl_nhwc_kyxc_nhwk_f16_instances(std::vector<DeviceConvFwdNoOpPtr>&);
void add_device_convnd_2d_fwd_xdl_nhwc_kyxc_nhwk_f32_instances(std::vector<DeviceConvFwdNoOpPtr>&);
void add_device_convnd_2d_fwd_xdl_nhwc_kyxc_nhwk_int8_instances(std::vector<DeviceConvFwdNoOpPtr>&);
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
namespace test {
namespace conv {
template <ck::index_t... Is>
using S = ck::Sequence<Is...>;
using InElementOp = ck::tensor_operation::element_wise::PassThrough;
using WeiElementOp = ck::tensor_operation::element_wise::PassThrough;
using OutElementOp = ck::tensor_operation::element_wise::PassThrough;
using DeviceConvFwdNoOpPtr =
ck::tensor_operation::device::DeviceConvFwdPtr<InElementOp, WeiElementOp, OutElementOp>;
static constexpr auto ConvFwdDefault =
ck::tensor_operation::device::ConvolutionForwardSpecialization::Default;
template <ck::index_t SpatialDims,
typename InDataType,
typename WeiDataType,
typename OutDataType,
typename AccDataType>
using DeviceConvNDFwdInstance = ck::tensor_operation::device::
DeviceConvNDFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<
// clang-format off
InDataType, //
WeiDataType, //
OutDataType, //
AccDataType, // Accumulator data type.
InElementOp, // Input Elementwise Operation
WeiElementOp, // Weights Elementwise Operation
OutElementOp, // Output Elementwise Operation
ConvFwdDefault, // ConvForwardSpecialization
SpatialDims, // SptialDims
256, // BlockSize
128, // MPerBlock
256, // NPerBlock
4, // K0PerBlock
8, // K1
32, // MPerXdl
32, // NPerXdl
2, // MXdlPerWave
4, // NXdlPerWave
S<4, 64, 1>, // ABlockTransferThreadClusterLengths_K0_M_K1
S<1, 0, 2>, // ABlockTransferThreadClusterArrangeOrder
S<1, 0, 2>, // ABlockTransferSrcAccessOrder
2, // ABlockTransferSrcVectorDim
8, // ABlockTransferSrcScalarPerVector
8, // ABlockTransferDstScalarPerVector_K1
true, // ABlockLdsAddExtraM
S<4, 64, 1>, // BBlockTransferThreadClusterLengths_K0_N_K1
S<1, 0, 2>, // BBlockTransferThreadClusterArrangeOrder
S<1, 0, 2>, // BBlockTransferSrcAccessOrder
2, // BBlockTransferSrcVectorDim
8, // BBlockTransferSrcScalarPerVector
8, // BBlockTransferDstScalarPerVector_K1
true, // BBlockLdsAddExtraN
7, // CThreadTransferSrcDstVectorDim
1>; // CThreadTransferDstScalarPerVector
// clang-format on
template <ck::index_t NDim,
typename InDataType,
typename WeiDataType,
typename OutDataType,
typename AccDataType>
void get_test_convolution_fwd_instance(std::vector<DeviceConvFwdNoOpPtr>& instances)
{
using ConvInstanceT =
DeviceConvNDFwdInstance<NDim, InDataType, WeiDataType, OutDataType, AccDataType>;
instances.emplace_back(std::make_unique<ConvInstanceT>());
}
// TODO (aosewski)
// Temporary solution to get all DeviceConvNDFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K
// instances. When switched over to DeviceConvNDFwdXdl for 2D remove ConvolutionNDFwdInstances
// structures.
template <typename InDataType, typename WeiDataType, typename OutDataType>
struct ConvolutionNDFwdInstances;
template <>
struct ConvolutionNDFwdInstances<float, float, float>
{
static std::vector<DeviceConvFwdNoOpPtr> Get(std::size_t num_dim_spatial)
{
std::vector<DeviceConvFwdNoOpPtr> conv_ptrs;
if(num_dim_spatial == 2)
{
ck::tensor_operation::device::instance::
add_device_convnd_2d_fwd_xdl_nhwc_kyxc_nhwk_f32_instances(conv_ptrs);
}
return conv_ptrs;
}
};
template <>
struct ConvolutionNDFwdInstances<ck::half_t, ck::half_t, ck::half_t>
{
static std::vector<DeviceConvFwdNoOpPtr> Get(std::size_t num_dim_spatial)
{
std::vector<DeviceConvFwdNoOpPtr> conv_ptrs;
if(num_dim_spatial == 2)
{
ck::tensor_operation::device::instance::
add_device_convnd_2d_fwd_xdl_nhwc_kyxc_nhwk_f16_instances(conv_ptrs);
}
return conv_ptrs;
}
};
template <>
struct ConvolutionNDFwdInstances<ck::bhalf_t, ck::bhalf_t, ck::bhalf_t>
{
static std::vector<DeviceConvFwdNoOpPtr> Get(std::size_t num_dim_spatial)
{
std::vector<DeviceConvFwdNoOpPtr> conv_ptrs;
if(num_dim_spatial == 2)
{
ck::tensor_operation::device::instance::
add_device_convnd_2d_fwd_xdl_nhwc_kyxc_nhwk_bf16_instances(conv_ptrs);
}
return conv_ptrs;
}
};
template <>
struct ConvolutionNDFwdInstances<int8_t, int8_t, int8_t>
{
static std::vector<DeviceConvFwdNoOpPtr> Get(std::size_t num_dim_spatial)
{
std::vector<DeviceConvFwdNoOpPtr> conv_ptrs;
if(num_dim_spatial == 2)
{
ck::tensor_operation::device::instance::
add_device_convnd_2d_fwd_xdl_nhwc_kyxc_nhwk_int8_instances(conv_ptrs);
}
return conv_ptrs;
}
};
} // namespace conv
} // namespace test
test/convnd_fwd/convnd_fwd.cpp 0 → 100644
View file @ d84da366
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <iostream>
#include <numeric>
#include <initializer_list>
#include <cstdlib>
#include <vector>
#include "profiler/include/profile_conv_fwd_impl.hpp"
int main()
{
bool pass = true;
std::vector<ck::tensor_operation::device::ConvParams> params;
// check 1d
params.push_back({1, 128, 128, 256, {1}, {14}, {2}, {1}, {0}, {0}});
params.push_back({1, 128, 128, 256, {3}, {28}, {1}, {1}, {1}, {1}});
params.push_back({1, 128, 128, 256, {1}, {3}, {1}, {1}, {0}, {0}});
for(auto& param : params)
{
// fp32
pass &= ck::profiler::profile_conv_fwd_impl<1,
ck::tensor_layout::convolution::NWC,
ck::tensor_layout::convolution::KXC,
ck::tensor_layout::convolution::NWK,
float,
float,
float>(true, // do_verification
1, // init_method
false, // do_log
false, // time_kernel
param);
// fp16
pass &= ck::profiler::profile_conv_fwd_impl<1,
ck::tensor_layout::convolution::NWC,
ck::tensor_layout::convolution::KXC,
ck::tensor_layout::convolution::NWK,
ck::half_t,
ck::half_t,
ck::half_t>(true, // do_verification
1, // init_method
false, // do_log
false, // time_kernel
param);
// bf16
pass &= ck::profiler::profile_conv_fwd_impl<1,
ck::tensor_layout::convolution::NWC,
ck::tensor_layout::convolution::KXC,
ck::tensor_layout::convolution::NWK,
ck::bhalf_t,
ck::bhalf_t,
ck::bhalf_t>(true, // do_verification
1, // init_method
false, // do_log
false, // time_kernel
param);
// int8
pass &= ck::profiler::profile_conv_fwd_impl<1,
ck::tensor_layout::convolution::NWC,
ck::tensor_layout::convolution::KXC,
ck::tensor_layout::convolution::NWK,
int8_t,
int8_t,
int8_t>(true, // do_verification
1, // init_method
false, // do_log
false, // time_kernel
param);
}
// check 2d
params.clear();
params.push_back({2, 128, 128, 256, {1, 1}, {7, 7}, {2, 2}, {1, 1}, {0, 0}, {0, 0}});
params.push_back({2, 128, 128, 256, {3, 3}, {14, 14}, {1, 1}, {1, 1}, {1, 1}, {1, 1}});
params.push_back({2, 128, 128, 256, {1, 1}, {3, 3}, {1, 1}, {1, 1}, {0, 0}, {0, 0}});
for(auto& param : params)
{
// fp32
pass &= ck::profiler::profile_conv_fwd_impl<2,
ck::tensor_layout::convolution::NHWC,
ck::tensor_layout::convolution::KYXC,
ck::tensor_layout::convolution::NHWK,
float,
float,
float>(true, // do_verification
1, // init_method
false, // do_log
false, // time_kernel
param);
// fp16
pass &= ck::profiler::profile_conv_fwd_impl<2,
ck::tensor_layout::convolution::NHWC,
ck::tensor_layout::convolution::KYXC,
ck::tensor_layout::convolution::NHWK,
ck::half_t,
ck::half_t,
ck::half_t>(true, // do_verification
1, // init_method
false, // do_log
false, // time_kernel
param);
// bf16
pass &= ck::profiler::profile_conv_fwd_impl<2,
ck::tensor_layout::convolution::NHWC,
ck::tensor_layout::convolution::KYXC,
ck::tensor_layout::convolution::NHWK,
ck::bhalf_t,
ck::bhalf_t,
ck::bhalf_t>(true, // do_verification
1, // init_method
false, // do_log
false, // time_kernel
param);
// int8
pass &= ck::profiler::profile_conv_fwd_impl<2,
ck::tensor_layout::convolution::NHWC,
ck::tensor_layout::convolution::KYXC,
ck::tensor_layout::convolution::NHWK,
int8_t,
int8_t,
int8_t>(true, // do_verification
1, // init_method
false, // do_log
false, // time_kernel
param);
}
// check 3d
params.clear();
params.push_back(
{3, 128, 128, 256, {1, 1, 1}, {7, 7, 7}, {2, 2, 2}, {1, 1, 1}, {0, 0, 0}, {0, 0, 0}});
params.push_back(
{3, 128, 128, 256, {3, 3, 3}, {14, 14, 14}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}});
params.push_back(
{3, 128, 128, 256, {1, 1, 1}, {3, 3, 3}, {1, 1, 1}, {1, 1, 1}, {0, 0, 0}, {0, 0, 0}});
for(auto& param : params)
{
// fp32
pass &= ck::profiler::profile_conv_fwd_impl<3,
ck::tensor_layout::convolution::NDHWC,
ck::tensor_layout::convolution::KZYXC,
ck::tensor_layout::convolution::NDHWK,
float,
float,
float>(true, // do_verification
1, // init_method
false, // do_log
false, // time_kernel
param);
// fp16
pass &= ck::profiler::profile_conv_fwd_impl<3,
ck::tensor_layout::convolution::NDHWC,
ck::tensor_layout::convolution::KZYXC,
ck::tensor_layout::convolution::NDHWK,
ck::half_t,
ck::half_t,
ck::half_t>(true, // do_verification
1, // init_method
false, // do_log
false, // time_kernel
param);
// bf16
pass &= ck::profiler::profile_conv_fwd_impl<3,
ck::tensor_layout::convolution::NDHWC,
ck::tensor_layout::convolution::KZYXC,
ck::tensor_layout::convolution::NDHWK,
ck::bhalf_t,
ck::bhalf_t,
ck::bhalf_t>(true, // do_verification
1, // init_method
false, // do_log
false, // time_kernel
param);
// int8
pass &= ck::profiler::profile_conv_fwd_impl<3,
ck::tensor_layout::convolution::NDHWC,
ck::tensor_layout::convolution::KZYXC,
ck::tensor_layout::convolution::NDHWK,
int8_t,
int8_t,
int8_t>(true, // do_verification
1, // init_method
false, // do_log
false, // time_kernel
param);
}
if(pass)
{
std::cout << "test convnd fwd : Pass" << std::endl;
return 0;
}
else
{
std::cout << "test convnd fwd: Fail " << std::endl;
return 1;
}
}
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