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Commit d0b9a467 authored by Chao Liu's avatar Chao Liu
Browse files

Merge remote-tracking branch 'origin/develop' into improve_pipeline

parents c8f6d5d1 8eca05a6
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Showing with 801 additions and 872 deletions
profiler/include/profile_batched_gemm_reduce_impl.hpp
View file @ d0b9a467
...@@ -8,7 +8,7 @@ ...@@ -8,7 +8,7 @@
#include "tensor_layout.hpp" #include "tensor_layout.hpp"
#include "device_tensor.hpp" #include "device_tensor.hpp"
#include "element_wise_operation.hpp" #include "element_wise_operation.hpp"
#include "element_wise_reduce_operation.hpp" #include "reduction_operator.hpp"
#include "device_gemm_reduce.hpp" #include "device_gemm_reduce.hpp"
#include "reference_batched_gemm.hpp" #include "reference_batched_gemm.hpp"
...@@ -21,8 +21,7 @@ using DeviceGemmReduceNoOpPtr = ck::tensor_operation::device::DeviceGemmReducePt ...@@ -21,8 +21,7 @@ using DeviceGemmReduceNoOpPtr = ck::tensor_operation::device::DeviceGemmReducePt
ck::tensor_operation::element_wise::PassThrough, ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough, ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough, ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::ReduceSum, ck::tensor_operation::element_wise::UnarySquare<float, float, false>>;
ck::tensor_operation::element_wise::ReduceSquareSum>;
void add_device_batched_gemm_reduce_xdl_cshuffle_f16_f16_f16_f32_f32_gmk_gkn_gmn_instances( void add_device_batched_gemm_reduce_xdl_cshuffle_f16_f16_f16_f32_f32_gmk_gkn_gmn_instances(
std::vector<DeviceGemmReduceNoOpPtr>&); std::vector<DeviceGemmReduceNoOpPtr>&);
...@@ -123,14 +122,16 @@ bool profile_batched_gemm_reduce_impl(int do_verification, ...@@ -123,14 +122,16 @@ bool profile_batched_gemm_reduce_impl(int do_verification,
using AElementOp = ck::tensor_operation::element_wise::PassThrough; using AElementOp = ck::tensor_operation::element_wise::PassThrough;
using BElementOp = ck::tensor_operation::element_wise::PassThrough; using BElementOp = ck::tensor_operation::element_wise::PassThrough;
using CElementOp = ck::tensor_operation::element_wise::PassThrough; using CElementOp = ck::tensor_operation::element_wise::PassThrough;
using D0ReduceOp = ck::tensor_operation::element_wise::ReduceSum; using D0ReduceOp = ck::reduce::Add<float>;
using D1ReduceOp = ck::tensor_operation::element_wise::ReduceSquareSum; using D1ReduceOp = ck::reduce::Add<float>;
using D1ElementOp = ck::tensor_operation::element_wise::UnarySquare<float, float, false>;
const auto a_element_op = AElementOp{}; const auto a_element_op = AElementOp{};
const auto b_element_op = BElementOp{}; const auto b_element_op = BElementOp{};
const auto c_element_op = CElementOp{}; const auto c_element_op = CElementOp{};
const auto d0_reduce_op = D0ReduceOp{}; const auto d0_reduce_op = D0ReduceOp{};
const auto d1_reduce_op = D1ReduceOp{}; const auto d1_reduce_op = D1ReduceOp{};
const auto d1_element_op = D1ElementOp{};
if(do_verification) if(do_verification)
{ {
...@@ -154,17 +155,21 @@ bool profile_batched_gemm_reduce_impl(int do_verification, ...@@ -154,17 +155,21 @@ bool profile_batched_gemm_reduce_impl(int do_verification,
{ {
for(int m = 0; m < M; ++m) for(int m = 0; m < M; ++m)
{ {
float d0_acc = d0_reduce_op.GetReduceZeroValue(); float d0_acc = d0_reduce_op.GetReductionZeroVal();
float d1_acc = d1_reduce_op.GetReduceZeroValue(); float d1_acc = d1_reduce_op.GetReductionZeroVal();
for(int n = 0; n < N; ++n) for(int n = 0; n < N; ++n)
{ {
d0_reduce_op.Reduce(d0_acc, c_g_m_n_host_result(batch, m, n)); float d0_val = ck::type_convert<float>(c_g_m_n_host_result(batch, m, n));
d1_reduce_op.Reduce(d1_acc, c_g_m_n_host_result(batch, m, n)); float d1_val;
d1_element_op(d1_val, d0_val);
d0_reduce_op(d0_acc, d0_val);
d1_reduce_op(d1_acc, d1_val);
} }
d0_g_m_host_result(batch, m) = d0_acc; d0_g_m_host_result(batch, m) = ck::type_convert<DDataType>(d0_acc);
d1_g_m_host_result(batch, m) = d1_acc; d1_g_m_host_result(batch, m) = ck::type_convert<DDataType>(d1_acc);
} }
} }
} }
...@@ -247,8 +252,7 @@ bool profile_batched_gemm_reduce_impl(int do_verification, ...@@ -247,8 +252,7 @@ bool profile_batched_gemm_reduce_impl(int do_verification,
a_element_op, a_element_op,
b_element_op, b_element_op,
c_element_op, c_element_op,
d0_reduce_op, d1_element_op,
d1_reduce_op,
BatchCount); BatchCount);
auto invoker_ptr = gemm_ptr->MakeInvokerPointer(); auto invoker_ptr = gemm_ptr->MakeInvokerPointer();
......
profiler/include/profile_gemm_reduce_impl.hpp
View file @ d0b9a467
...@@ -7,7 +7,7 @@ ...@@ -7,7 +7,7 @@
#include "tensor_layout.hpp" #include "tensor_layout.hpp"
#include "device_tensor.hpp" #include "device_tensor.hpp"
#include "element_wise_operation.hpp" #include "element_wise_operation.hpp"
#include "element_wise_reduce_operation.hpp" #include "reduction_operator.hpp"
#include "device_gemm_reduce.hpp" #include "device_gemm_reduce.hpp"
#include "reference_gemm.hpp" #include "reference_gemm.hpp"
...@@ -20,8 +20,7 @@ using DeviceGemmReduceNoOpPtr = ck::tensor_operation::device::DeviceGemmReducePt ...@@ -20,8 +20,7 @@ using DeviceGemmReduceNoOpPtr = ck::tensor_operation::device::DeviceGemmReducePt
ck::tensor_operation::element_wise::PassThrough, ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough, ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough, ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::ReduceSum, ck::tensor_operation::element_wise::UnarySquare<float, float, false>>;
ck::tensor_operation::element_wise::ReduceSquareSum>;
void add_device_gemm_reduce_xdl_cshuffle_f16_f16_f16_f32_f32_mk_kn_mn_instances( void add_device_gemm_reduce_xdl_cshuffle_f16_f16_f16_f32_f32_mk_kn_mn_instances(
std::vector<DeviceGemmReduceNoOpPtr>&); std::vector<DeviceGemmReduceNoOpPtr>&);
...@@ -116,14 +115,16 @@ bool profile_gemm_reduce_impl(int do_verification, ...@@ -116,14 +115,16 @@ bool profile_gemm_reduce_impl(int do_verification,
using AElementOp = ck::tensor_operation::element_wise::PassThrough; using AElementOp = ck::tensor_operation::element_wise::PassThrough;
using BElementOp = ck::tensor_operation::element_wise::PassThrough; using BElementOp = ck::tensor_operation::element_wise::PassThrough;
using CElementOp = ck::tensor_operation::element_wise::PassThrough; using CElementOp = ck::tensor_operation::element_wise::PassThrough;
using D0ReduceOp = ck::tensor_operation::element_wise::ReduceSum; using D0ReduceOp = ck::reduce::Add<float>;
using D1ReduceOp = ck::tensor_operation::element_wise::ReduceSquareSum; using D1ReduceOp = ck::reduce::Add<float>;
using D1ElementOp = ck::tensor_operation::element_wise::UnarySquare<float, float, false>;
const auto a_element_op = AElementOp{}; const auto a_element_op = AElementOp{};
const auto b_element_op = BElementOp{}; const auto b_element_op = BElementOp{};
const auto c_element_op = CElementOp{}; const auto c_element_op = CElementOp{};
const auto d0_reduce_op = D0ReduceOp{}; const auto d0_reduce_op = D0ReduceOp{};
const auto d1_reduce_op = D1ReduceOp{}; const auto d1_reduce_op = D1ReduceOp{};
const auto d1_element_op = D1ElementOp{};
if(do_verification) if(do_verification)
{ {
...@@ -140,17 +141,21 @@ bool profile_gemm_reduce_impl(int do_verification, ...@@ -140,17 +141,21 @@ bool profile_gemm_reduce_impl(int do_verification,
for(int m = 0; m < M; ++m) for(int m = 0; m < M; ++m)
{ {
float d0_acc = d0_reduce_op.GetReduceZeroValue(); float d0_acc = d0_reduce_op.GetReductionZeroVal();
float d1_acc = d1_reduce_op.GetReduceZeroValue(); float d1_acc = d1_reduce_op.GetReductionZeroVal();
for(int n = 0; n < N; ++n) for(int n = 0; n < N; ++n)
{ {
d0_reduce_op.Reduce(d0_acc, c_m_n_host_result(m, n)); float d0_val = ck::type_convert<float>(c_m_n_host_result(m, n));
d1_reduce_op.Reduce(d1_acc, c_m_n_host_result(m, n)); float d1_val;
d1_element_op(d1_val, d0_val);
d0_reduce_op(d0_acc, d0_val);
d1_reduce_op(d1_acc, d1_val);
} }
d0_m_host_result(m) = d0_acc; d0_m_host_result(m) = ck::type_convert<DDataType>(d0_acc);
d1_m_host_result(m) = d1_acc; d1_m_host_result(m) = ck::type_convert<DDataType>(d1_acc);
} }
} }
...@@ -232,8 +237,7 @@ bool profile_gemm_reduce_impl(int do_verification, ...@@ -232,8 +237,7 @@ bool profile_gemm_reduce_impl(int do_verification,
a_element_op, a_element_op,
b_element_op, b_element_op,
c_element_op, c_element_op,
d0_reduce_op, d1_element_op);
d1_reduce_op);
auto invoker_ptr = gemm_ptr->MakeInvokerPointer(); auto invoker_ptr = gemm_ptr->MakeInvokerPointer();
......
script/clang-format-overwrite.sh
View file @ d0b9a467
find . -name deps -prune -o -name build -prune -o -iname '*.h' -o -iname '*.hpp' -o -iname '*.cpp' -o -iname '*.h.in' -o -iname '*.hpp.in' -o -iname '*.cpp.in' -o -iname '*.cl' -o -iname '*.cuh' -o -iname '*.cu' | xargs -n 1 -P 16 -I{} -t sh -c 'clang-format-10 -i -style=file {}' #find . -name deps -prune -o -name build -prune -o -iname '*.h' -o -iname '*.hpp' -o -iname '*.cpp' -o -iname '*.h.in' -o -iname '*.hpp.in' -o -iname '*.cpp.in' -o -iname '*.cl' -o -iname '*.cuh' -o -iname '*.cu' | xargs -n 1 -P 16 -I{} -t sh -c 'clang-format-10 -i -style=file {}'
git status --porcelain | awk '$1 != "D" && (match($2, "\\.cpp|hpp")) {print $2}' | xargs -n 1 -P 16 -I{} -t sh -c 'clang-format-10 -i -style=file {}'
test/CMakeLists.txt
View file @ d0b9a467
...@@ -24,6 +24,7 @@ include_directories(BEFORE ...@@ -24,6 +24,7 @@ include_directories(BEFORE
add_custom_target(check COMMAND ${CMAKE_CTEST_COMMAND} --output-on-failure -C ${CMAKE_CFG_INTDIR}) add_custom_target(check COMMAND ${CMAKE_CTEST_COMMAND} --output-on-failure -C ${CMAKE_CFG_INTDIR})
add_custom_target(tests) add_custom_target(tests)
function(add_test_executable TEST_NAME) function(add_test_executable TEST_NAME)
message("adding test ${TEST_NAME}") message("adding test ${TEST_NAME}")
add_executable(${TEST_NAME} ${ARGN}) add_executable(${TEST_NAME} ${ARGN})
...@@ -32,6 +33,20 @@ function(add_test_executable TEST_NAME) ...@@ -32,6 +33,20 @@ function(add_test_executable TEST_NAME)
add_dependencies(check ${TEST_NAME}) add_dependencies(check ${TEST_NAME})
endfunction(add_test_executable TEST_NAME) endfunction(add_test_executable TEST_NAME)
include(GoogleTest)
function(add_gtest_executable TEST_NAME)
message("adding gtest ${TEST_NAME}")
add_executable(${TEST_NAME} ${ARGN})
add_dependencies(tests ${TEST_NAME})
add_dependencies(check ${TEST_NAME})
# suppress gtest warnings
target_compile_options(${TEST_NAME} PRIVATE -Wno-global-constructors)
target_link_libraries(${TEST_NAME} PRIVATE gtest_main)
gtest_discover_tests(${TEST_NAME})
endfunction(add_gtest_executable TEST_NAME)
add_subdirectory(magic_number_division) add_subdirectory(magic_number_division)
add_subdirectory(space_filling_curve) add_subdirectory(space_filling_curve)
add_subdirectory(conv_util) add_subdirectory(conv_util)
......
test/conv_util/CMakeLists.txt
View file @ d0b9a467
add_test_executable(test_conv_util conv_util.cpp) add_gtest_executable(test_conv_util conv_util.cpp)
target_link_libraries(test_conv_util PRIVATE host_tensor conv_fwd_util) target_link_libraries(test_conv_util PRIVATE host_tensor conv_fwd_util)
test/conv_util/conv_util.cpp
View file @ d0b9a467
#include <iostream> #include <iostream>
#include <string> #include <string>
#include <vector> #include <vector>
#include "gtest/gtest.h"
#include "config.hpp" #include "config.hpp"
#include "conv_fwd_util.hpp" #include "conv_fwd_util.hpp"
...@@ -9,196 +10,194 @@ ...@@ -9,196 +10,194 @@
namespace { namespace {
bool test_conv_params_get_output_spatial_lengths() class TestConvUtil : public ::testing::Test
{ {
bool res{true}; public:
// -------------------------- default 2D ------------------------------------ void SetNDParams(std::size_t ndims)
{
conv_params.num_dim_spatial = ndims;
conv_params.filter_spatial_lengths = std::vector<ck::index_t>(ndims, 3);
conv_params.input_spatial_lengths = std::vector<ck::index_t>(ndims, 71);
conv_params.conv_filter_strides = std::vector<ck::index_t>(ndims, 2);
conv_params.conv_filter_dilations = std::vector<ck::index_t>(ndims, 1);
conv_params.input_left_pads = std::vector<ck::index_t>(ndims, 1);
conv_params.input_right_pads = std::vector<ck::index_t>(ndims, 1);
}
protected:
// ------- default 2D -------
// input NCHW {128,192,71,71}, // input NCHW {128,192,71,71},
// weights KCYX {256,192,3,3}, // weights KCYX {256,192,3,3},
// stride {2,2}, // stride {2,2},
// dilations {1,1}, // dilations {1,1},
// padding {{1,1}, {1,1}} // padding {{1,1}, {1,1}}
ck::utils::conv::ConvParams conv_params; ck::utils::conv::ConvParams conv_params;
};
} // namespace
TEST_F(TestConvUtil, ConvParamsGetOutputSpatialLengths2D)
{
ck::utils::conv::ConvParams conv_params;
std::vector<ck::index_t> out_spatial_len = conv_params.GetOutputSpatialLengths(); std::vector<ck::index_t> out_spatial_len = conv_params.GetOutputSpatialLengths();
res = ck::utils::check_err(out_spatial_len, EXPECT_TRUE(ck::utils::check_err(out_spatial_len,
std::vector<ck::index_t>{36, 36}, std::vector<ck::index_t>{36, 36},
"Error: ConvParams 2D default constructor."); "Error: ConvParams 2D default constructor."));
conv_params.conv_filter_strides = std::vector<ck::index_t>{1, 1}; conv_params.conv_filter_strides = std::vector<ck::index_t>{1, 1};
out_spatial_len = conv_params.GetOutputSpatialLengths(); out_spatial_len = conv_params.GetOutputSpatialLengths();
res = ck::utils::check_err( EXPECT_TRUE(ck::utils::check_err(
out_spatial_len, std::vector<ck::index_t>{71, 71}, "Error: ConvParams 2D stride {1,1}."); out_spatial_len, std::vector<ck::index_t>{71, 71}, "Error: ConvParams 2D stride {1,1}."));
conv_params.conv_filter_strides = std::vector<ck::index_t>{2, 2}; conv_params.conv_filter_strides = std::vector<ck::index_t>{2, 2};
conv_params.input_left_pads = std::vector<ck::index_t>{2, 2}; conv_params.input_left_pads = std::vector<ck::index_t>{2, 2};
conv_params.input_right_pads = std::vector<ck::index_t>{2, 2}; conv_params.input_right_pads = std::vector<ck::index_t>{2, 2};
out_spatial_len = conv_params.GetOutputSpatialLengths(); out_spatial_len = conv_params.GetOutputSpatialLengths();
res = ck::utils::check_err(out_spatial_len, EXPECT_TRUE(ck::utils::check_err(out_spatial_len,
std::vector<ck::index_t>{37, 37}, std::vector<ck::index_t>{37, 37},
"Error: ConvParams 2D padding left/right {2,2}."); "Error: ConvParams 2D padding left/right {2,2}."));
conv_params.conv_filter_dilations = std::vector<ck::index_t>{2, 2}; conv_params.conv_filter_dilations = std::vector<ck::index_t>{2, 2};
out_spatial_len = conv_params.GetOutputSpatialLengths(); out_spatial_len = conv_params.GetOutputSpatialLengths();
res = ck::utils::check_err( EXPECT_TRUE(ck::utils::check_err(
out_spatial_len, std::vector<ck::index_t>{36, 36}, "Error: ConvParams 2D dilation {2,2}."); out_spatial_len, std::vector<ck::index_t>{36, 36}, "Error: ConvParams 2D dilation {2,2}."));
conv_params.conv_filter_strides = std::vector<ck::index_t>{3, 3}; conv_params.conv_filter_strides = std::vector<ck::index_t>{3, 3};
conv_params.input_left_pads = std::vector<ck::index_t>{1, 1}; conv_params.input_left_pads = std::vector<ck::index_t>{1, 1};
conv_params.input_right_pads = std::vector<ck::index_t>{1, 1}; conv_params.input_right_pads = std::vector<ck::index_t>{1, 1};
conv_params.conv_filter_dilations = std::vector<ck::index_t>{2, 2}; conv_params.conv_filter_dilations = std::vector<ck::index_t>{2, 2};
out_spatial_len = conv_params.GetOutputSpatialLengths(); out_spatial_len = conv_params.GetOutputSpatialLengths();
res = EXPECT_TRUE(
ck::utils::check_err(out_spatial_len, ck::utils::check_err(out_spatial_len,
std::vector<ck::index_t>{23, 23}, std::vector<ck::index_t>{23, 23},
"Error: ConvParams 2D strides{3,3}, padding {1,1}, dilations {2,2}."); "Error: ConvParams 2D strides{3,3}, padding {1,1}, dilations {2,2}."));
}
// -------------------------- 1D ------------------------------------ TEST_F(TestConvUtil, ConvParamsGetOutputSpatialLengths1D)
conv_params.num_dim_spatial = 1; {
conv_params.filter_spatial_lengths = std::vector<ck::index_t>{3}; SetNDParams(1);
conv_params.input_spatial_lengths = std::vector<ck::index_t>{71};
conv_params.conv_filter_strides = std::vector<ck::index_t>{2};
conv_params.conv_filter_dilations = std::vector<ck::index_t>{1};
conv_params.input_left_pads = std::vector<ck::index_t>{1};
conv_params.input_right_pads = std::vector<ck::index_t>{1};
out_spatial_len = conv_params.GetOutputSpatialLengths(); std::vector<ck::index_t> out_spatial_len = conv_params.GetOutputSpatialLengths();
res = ck::utils::check_err( EXPECT_TRUE(ck::utils::check_err(
out_spatial_len, std::vector<ck::index_t>{36}, "Error: ConvParams 1D."); out_spatial_len, std::vector<ck::index_t>{36}, "Error: ConvParams 1D."));
conv_params.conv_filter_strides = std::vector<ck::index_t>{1}; conv_params.conv_filter_strides = std::vector<ck::index_t>{1};
out_spatial_len = conv_params.GetOutputSpatialLengths(); out_spatial_len = conv_params.GetOutputSpatialLengths();
res = ck::utils::check_err( EXPECT_TRUE(ck::utils::check_err(
out_spatial_len, std::vector<ck::index_t>{71}, "Error: ConvParams 1D stride {1}."); out_spatial_len, std::vector<ck::index_t>{71}, "Error: ConvParams 1D stride {1}."));
conv_params.conv_filter_strides = std::vector<ck::index_t>{2}; conv_params.conv_filter_strides = std::vector<ck::index_t>{2};
conv_params.input_left_pads = std::vector<ck::index_t>{2}; conv_params.input_left_pads = std::vector<ck::index_t>{2};
conv_params.input_right_pads = std::vector<ck::index_t>{2}; conv_params.input_right_pads = std::vector<ck::index_t>{2};
out_spatial_len = conv_params.GetOutputSpatialLengths(); out_spatial_len = conv_params.GetOutputSpatialLengths();
res = ck::utils::check_err(out_spatial_len, EXPECT_TRUE(ck::utils::check_err(out_spatial_len,
std::vector<ck::index_t>{37}, std::vector<ck::index_t>{37},
"Error: ConvParams 1D padding left/right {2}."); "Error: ConvParams 1D padding left/right {2}."));
conv_params.conv_filter_dilations = std::vector<ck::index_t>{2}; conv_params.conv_filter_dilations = std::vector<ck::index_t>{2};
out_spatial_len = conv_params.GetOutputSpatialLengths(); out_spatial_len = conv_params.GetOutputSpatialLengths();
res = ck::utils::check_err( EXPECT_TRUE(ck::utils::check_err(
out_spatial_len, std::vector<ck::index_t>{36}, "Error: ConvParams 1D dilation {2}."); out_spatial_len, std::vector<ck::index_t>{36}, "Error: ConvParams 1D dilation {2}."));
conv_params.conv_filter_strides = std::vector<ck::index_t>{3}; conv_params.conv_filter_strides = std::vector<ck::index_t>{3};
conv_params.input_left_pads = std::vector<ck::index_t>{1}; conv_params.input_left_pads = std::vector<ck::index_t>{1};
conv_params.input_right_pads = std::vector<ck::index_t>{1}; conv_params.input_right_pads = std::vector<ck::index_t>{1};
conv_params.conv_filter_dilations = std::vector<ck::index_t>{2}; conv_params.conv_filter_dilations = std::vector<ck::index_t>{2};
out_spatial_len = conv_params.GetOutputSpatialLengths(); out_spatial_len = conv_params.GetOutputSpatialLengths();
res = ck::utils::check_err(out_spatial_len, EXPECT_TRUE(
ck::utils::check_err(out_spatial_len,
std::vector<ck::index_t>{23}, std::vector<ck::index_t>{23},
"Error: ConvParams 1D strides{3}, padding {1}, dilations {2}."); "Error: ConvParams 1D strides{3}, padding {1}, dilations {2}."));
}
// -------------------------- 3D ------------------------------------ TEST_F(TestConvUtil, ConvParamsGetOutputSpatialLengths3D)
conv_params.num_dim_spatial = 3; {
conv_params.filter_spatial_lengths = std::vector<ck::index_t>{3, 3, 3}; SetNDParams(3);
conv_params.input_spatial_lengths = std::vector<ck::index_t>{71, 71, 71};
conv_params.conv_filter_strides = std::vector<ck::index_t>{2, 2, 2};
conv_params.conv_filter_dilations = std::vector<ck::index_t>{1, 1, 1};
conv_params.input_left_pads = std::vector<ck::index_t>{1, 1, 1};
conv_params.input_right_pads = std::vector<ck::index_t>{1, 1, 1};
out_spatial_len = conv_params.GetOutputSpatialLengths(); std::vector<ck::index_t> out_spatial_len = conv_params.GetOutputSpatialLengths();
res = ck::utils::check_err( EXPECT_TRUE(ck::utils::check_err(
out_spatial_len, std::vector<ck::index_t>{36, 36, 36}, "Error: ConvParams 3D."); out_spatial_len, std::vector<ck::index_t>{36, 36, 36}, "Error: ConvParams 3D."));
conv_params.conv_filter_strides = std::vector<ck::index_t>{1, 1, 1}; conv_params.conv_filter_strides = std::vector<ck::index_t>{1, 1, 1};
out_spatial_len = conv_params.GetOutputSpatialLengths(); out_spatial_len = conv_params.GetOutputSpatialLengths();
res = ck::utils::check_err(out_spatial_len, EXPECT_TRUE(ck::utils::check_err(out_spatial_len,
std::vector<ck::index_t>{71, 71, 71}, std::vector<ck::index_t>{71, 71, 71},
"Error: ConvParams 3D stride {1, 1, 1}."); "Error: ConvParams 3D stride {1, 1, 1}."));
conv_params.conv_filter_strides = std::vector<ck::index_t>{2, 2, 2}; conv_params.conv_filter_strides = std::vector<ck::index_t>{2, 2, 2};
conv_params.input_left_pads = std::vector<ck::index_t>{2, 2, 2}; conv_params.input_left_pads = std::vector<ck::index_t>{2, 2, 2};
conv_params.input_right_pads = std::vector<ck::index_t>{2, 2, 2}; conv_params.input_right_pads = std::vector<ck::index_t>{2, 2, 2};
out_spatial_len = conv_params.GetOutputSpatialLengths(); out_spatial_len = conv_params.GetOutputSpatialLengths();
res = ck::utils::check_err(out_spatial_len, EXPECT_TRUE(ck::utils::check_err(out_spatial_len,
std::vector<ck::index_t>{37, 37, 37}, std::vector<ck::index_t>{37, 37, 37},
"Error: ConvParams 3D padding left/right {2, 2, 2}."); "Error: ConvParams 3D padding left/right {2, 2, 2}."));
conv_params.conv_filter_dilations = std::vector<ck::index_t>{2, 2, 2}; conv_params.conv_filter_dilations = std::vector<ck::index_t>{2, 2, 2};
out_spatial_len = conv_params.GetOutputSpatialLengths(); out_spatial_len = conv_params.GetOutputSpatialLengths();
res = ck::utils::check_err(out_spatial_len, EXPECT_TRUE(ck::utils::check_err(out_spatial_len,
std::vector<ck::index_t>{36, 36, 36}, std::vector<ck::index_t>{36, 36, 36},
"Error: ConvParams 3D dilation {2, 2, 2}."); "Error: ConvParams 3D dilation {2, 2, 2}."));
conv_params.conv_filter_strides = std::vector<ck::index_t>{3, 3, 3}; conv_params.conv_filter_strides = std::vector<ck::index_t>{3, 3, 3};
conv_params.input_left_pads = std::vector<ck::index_t>{1, 1, 1}; conv_params.input_left_pads = std::vector<ck::index_t>{1, 1, 1};
conv_params.input_right_pads = std::vector<ck::index_t>{1, 1, 1}; conv_params.input_right_pads = std::vector<ck::index_t>{1, 1, 1};
conv_params.conv_filter_dilations = std::vector<ck::index_t>{2, 2, 2}; conv_params.conv_filter_dilations = std::vector<ck::index_t>{2, 2, 2};
out_spatial_len = conv_params.GetOutputSpatialLengths(); out_spatial_len = conv_params.GetOutputSpatialLengths();
res = ck::utils::check_err( EXPECT_TRUE(ck::utils::check_err(
out_spatial_len, out_spatial_len,
std::vector<ck::index_t>{23, 23, 23}, std::vector<ck::index_t>{23, 23, 23},
"Error: ConvParams 3D strides{3, 3, 3}, padding {1, 1, 1}, dilations {2, 2, 2}."); "Error: ConvParams 3D strides{3, 3, 3}, padding {1, 1, 1}, dilations {2, 2, 2}."));
return res;
} }
bool test_get_host_tensor_descriptor() TEST(ConvUtil, GetHostTensorDescriptor)
{ {
bool res{true};
namespace tl = ck::tensor_layout::convolution; namespace tl = ck::tensor_layout::convolution;
std::vector<std::size_t> dims{2, 3, 4, 5}; std::vector<std::size_t> dims{2, 3, 4, 5};
HostTensorDescriptor h = ck::utils::conv::get_host_tensor_descriptor(dims, tl::NHWC{}); HostTensorDescriptor h = ck::utils::conv::get_host_tensor_descriptor(dims, tl::NHWC{});
res = EXPECT_TRUE(ck::utils::check_err(
ck::utils::check_err(h.GetLengths(), {2, 3, 4, 5}, "Error: wrong NHWC dimensions lengths!"); h.GetLengths(), {2, 3, 4, 5}, "Error: wrong NHWC dimensions lengths!"));
res = ck::utils::check_err( EXPECT_TRUE(ck::utils::check_err(
h.GetStrides(), {3 * 4 * 5, 1, 3 * 5, 3}, "Error: wrong NHWC dimensions strides!"); h.GetStrides(), {3 * 4 * 5, 1, 3 * 5, 3}, "Error: wrong NHWC dimensions strides!"));
h = ck::utils::conv::get_host_tensor_descriptor(dims, tl::NCHW{}); h = ck::utils::conv::get_host_tensor_descriptor(dims, tl::NCHW{});
res = EXPECT_TRUE(ck::utils::check_err(
ck::utils::check_err(h.GetLengths(), {2, 3, 4, 5}, "Error: wrong NCHW dimensions lengths!"); h.GetLengths(), {2, 3, 4, 5}, "Error: wrong NCHW dimensions lengths!"));
res = ck::utils::check_err( EXPECT_TRUE(ck::utils::check_err(
h.GetStrides(), {3 * 4 * 5, 4 * 5, 5, 1}, "Error: wrong NCHW dimensions strides!"); h.GetStrides(), {3 * 4 * 5, 4 * 5, 5, 1}, "Error: wrong NCHW dimensions strides!"));
dims = std::vector<std::size_t>{2, 3, 4}; dims = std::vector<std::size_t>{2, 3, 4};
h = ck::utils::conv::get_host_tensor_descriptor(dims, tl::NWC{}); h = ck::utils::conv::get_host_tensor_descriptor(dims, tl::NWC{});
res = ck::utils::check_err(h.GetLengths(), {2, 3, 4}, "Error: wrong NWC dimensions lengths!"); EXPECT_TRUE(
res = ck::utils::check_err(h.GetLengths(), {2, 3, 4}, "Error: wrong NWC dimensions lengths!"));
ck::utils::check_err(h.GetStrides(), {3 * 4, 1, 3}, "Error: wrong NWC dimensions strides!"); EXPECT_TRUE(ck::utils::check_err(
h.GetStrides(), {3 * 4, 1, 3}, "Error: wrong NWC dimensions strides!"));
h = ck::utils::conv::get_host_tensor_descriptor(dims, tl::NCW{}); h = ck::utils::conv::get_host_tensor_descriptor(dims, tl::NCW{});
res = ck::utils::check_err(h.GetLengths(), {2, 3, 4}, "Error: wrong NCW dimensions lengths!"); EXPECT_TRUE(
res = ck::utils::check_err(h.GetLengths(), {2, 3, 4}, "Error: wrong NCW dimensions lengths!"));
ck::utils::check_err(h.GetStrides(), {3 * 4, 4, 1}, "Error: wrong NCW dimensions strides!"); EXPECT_TRUE(ck::utils::check_err(
h.GetStrides(), {3 * 4, 4, 1}, "Error: wrong NCW dimensions strides!"));
dims = std::vector<std::size_t>{2, 3, 4, 5, 6}; dims = std::vector<std::size_t>{2, 3, 4, 5, 6};
h = ck::utils::conv::get_host_tensor_descriptor(dims, tl::NDHWC{}); h = ck::utils::conv::get_host_tensor_descriptor(dims, tl::NDHWC{});
res = ck::utils::check_err(h.GetLengths(), dims, "Error: wrong NDHWC dimensions lengths!"); EXPECT_TRUE(
res = ck::utils::check_err(h.GetStrides(), ck::utils::check_err(h.GetLengths(), dims, "Error: wrong NDHWC dimensions lengths!"));
EXPECT_TRUE(ck::utils::check_err(h.GetStrides(),
{3 * 4 * 5 * 6, // N {3 * 4 * 5 * 6, // N
1, // C 1, // C
3 * 5 * 6, // D 3 * 5 * 6, // D
3 * 6, // H 3 * 6, // H
3}, // W 3}, // W
"Error: wrong NDHWC dimensions strides!"); "Error: wrong NDHWC dimensions strides!"));
h = ck::utils::conv::get_host_tensor_descriptor(dims, tl::NCDHW{}); h = ck::utils::conv::get_host_tensor_descriptor(dims, tl::NCDHW{});
res = ck::utils::check_err(h.GetLengths(), dims, "Error: wrong NCDHW dimensions lengths!"); EXPECT_TRUE(
res = ck::utils::check_err(h.GetStrides(), ck::utils::check_err(h.GetLengths(), dims, "Error: wrong NCDHW dimensions lengths!"));
EXPECT_TRUE(ck::utils::check_err(h.GetStrides(),
{3 * 4 * 5 * 6, // N {3 * 4 * 5 * 6, // N
4 * 5 * 6, // C 4 * 5 * 6, // C
5 * 6, // D 5 * 6, // D
6, // H 6, // H
1}, // W 1}, // W
"Error: wrong NCDHW dimensions strides!"); "Error: wrong NCDHW dimensions strides!"));
return res;
}
} // namespace
int main(void)
{
bool res = test_conv_params_get_output_spatial_lengths();
std::cout << "test_conv_params_get_output_spatial_lengths ..... "
<< (res ? "SUCCESS" : "FAILURE") << std::endl;
res = test_get_host_tensor_descriptor();
std::cout << "test_get_host_tensor_descriptor ..... " << (res ? "SUCCESS" : "FAILURE")
<< std::endl;
return res ? 0 : 1;
} }
test/convnd_fwd/CMakeLists.txt
View file @ d0b9a467
add_custom_target(test_convnd_fwd) add_custom_target(test_convnd_fwd)
add_test_executable(test_conv1d_fwd conv1d_fwd.cpp) add_gtest_executable(test_conv1d_fwd conv1d_fwd.cpp)
target_link_libraries(test_conv1d_fwd PRIVATE host_tensor device_conv1d_fwd_instance conv_fwd_util) target_link_libraries(test_conv1d_fwd PRIVATE host_tensor device_conv1d_fwd_instance conv_fwd_util)
target_link_libraries(test_conv1d_fwd PRIVATE )
add_dependencies(test_convnd_fwd test_conv1d_fwd) add_dependencies(test_convnd_fwd test_conv1d_fwd)
add_test_executable(test_conv2d_fwd conv2d_fwd.cpp) add_gtest_executable(test_conv2d_fwd conv2d_fwd.cpp)
target_link_libraries(test_conv2d_fwd PRIVATE host_tensor device_conv2d_fwd_instance conv_fwd_util) target_link_libraries(test_conv2d_fwd PRIVATE host_tensor device_conv2d_fwd_instance conv_fwd_util)
add_dependencies(test_convnd_fwd test_conv2d_fwd) add_dependencies(test_convnd_fwd test_conv2d_fwd)
add_test_executable(test_conv3d_fwd conv3d_fwd.cpp) add_gtest_executable(test_conv3d_fwd conv3d_fwd.cpp)
target_link_libraries(test_conv3d_fwd PRIVATE host_tensor device_conv3d_fwd_instance conv_fwd_util) target_link_libraries(test_conv3d_fwd PRIVATE host_tensor device_conv3d_fwd_instance conv_fwd_util)
add_dependencies(test_convnd_fwd test_conv3d_fwd) add_dependencies(test_convnd_fwd test_conv3d_fwd)
test/convnd_fwd/conv1d_fwd.cpp
View file @ d0b9a467
...@@ -2,6 +2,7 @@ ...@@ -2,6 +2,7 @@
#include <stdexcept> #include <stdexcept>
#include <tuple> #include <tuple>
#include <vector> #include <vector>
#include "gtest/gtest.h"
#include "data_type.hpp" #include "data_type.hpp"
#include "element_wise_operation.hpp" #include "element_wise_operation.hpp"
...@@ -10,7 +11,8 @@ ...@@ -10,7 +11,8 @@
namespace { namespace {
bool test_conv1D_nwc() template <typename T>
bool test_conv1d_nwc_instances(const std::vector<test::conv::DeviceConvFwdNoOpPtr>& conv_ptrs)
{ {
using namespace std::placeholders; using namespace std::placeholders;
using namespace ck::utils; using namespace ck::utils;
...@@ -18,31 +20,24 @@ bool test_conv1D_nwc() ...@@ -18,31 +20,24 @@ bool test_conv1D_nwc()
ck::utils::conv::ConvParams params; ck::utils::conv::ConvParams params;
params.num_dim_spatial = 1; params.num_dim_spatial = 1;
params.N = 2;
params.K = 16;
params.C = 4;
params.filter_spatial_lengths = std::vector<ck::index_t>{3}; params.filter_spatial_lengths = std::vector<ck::index_t>{3};
params.input_spatial_lengths = std::vector<ck::index_t>{16}; params.input_spatial_lengths = std::vector<ck::index_t>{71};
params.conv_filter_strides = std::vector<ck::index_t>{1}; params.conv_filter_strides = std::vector<ck::index_t>{2};
params.conv_filter_dilations = std::vector<ck::index_t>{1}; params.conv_filter_dilations = std::vector<ck::index_t>{1};
params.input_left_pads = std::vector<ck::index_t>{1}; params.input_left_pads = std::vector<ck::index_t>{1};
params.input_right_pads = std::vector<ck::index_t>{1}; params.input_right_pads = std::vector<ck::index_t>{1};
std::vector<test::conv::DeviceConvFwdNoOpPtr> conv_ptrs; conv::ConvFwdOpInstance<T, T, T, ctl::NWC, ctl::KCX, ctl::NWK> conv_instance(params);
test::conv::get_test_convolution_fwd_instance<1>(conv_ptrs);
conv::ConvFwdOpInstance<float, float, float, ctl::NWC, ctl::KCX, ctl::NWK> conv_instance(
params);
auto reference_conv_fwd_fun = std::bind( auto reference_conv_fwd_fun =
conv::run_reference_convolution_forward<1, float, float, float>, params, _1, _2, _3); std::bind(conv::run_reference_convolution_forward<1, T, T, T>, params, _1, _2, _3);
OpInstanceRunEngine<float, float, float> run_engine(conv_instance, reference_conv_fwd_fun); OpInstanceRunEngine<T, T, T> run_engine(conv_instance, reference_conv_fwd_fun);
run_engine.SetAtol(1e-5);
run_engine.SetRtol(1e-4);
return run_engine.Test(conv_ptrs); return run_engine.Test(conv_ptrs);
} }
template <typename T> } // anonymous namespace
bool test_conv1d_nwc_instances(const std::vector<test::conv::DeviceConvFwdNoOpPtr>& conv_ptrs)
TEST(Conv1DFwdNWC, TestConv1D)
{ {
using namespace std::placeholders; using namespace std::placeholders;
using namespace ck::utils; using namespace ck::utils;
...@@ -50,65 +45,49 @@ bool test_conv1d_nwc_instances(const std::vector<test::conv::DeviceConvFwdNoOpPt ...@@ -50,65 +45,49 @@ bool test_conv1d_nwc_instances(const std::vector<test::conv::DeviceConvFwdNoOpPt
ck::utils::conv::ConvParams params; ck::utils::conv::ConvParams params;
params.num_dim_spatial = 1; params.num_dim_spatial = 1;
params.N = 2;
params.K = 16;
params.C = 4;
params.filter_spatial_lengths = std::vector<ck::index_t>{3}; params.filter_spatial_lengths = std::vector<ck::index_t>{3};
params.input_spatial_lengths = std::vector<ck::index_t>{71}; params.input_spatial_lengths = std::vector<ck::index_t>{16};
params.conv_filter_strides = std::vector<ck::index_t>{2}; params.conv_filter_strides = std::vector<ck::index_t>{1};
params.conv_filter_dilations = std::vector<ck::index_t>{1}; params.conv_filter_dilations = std::vector<ck::index_t>{1};
params.input_left_pads = std::vector<ck::index_t>{1}; params.input_left_pads = std::vector<ck::index_t>{1};
params.input_right_pads = std::vector<ck::index_t>{1}; params.input_right_pads = std::vector<ck::index_t>{1};
conv::ConvFwdOpInstance<T, T, T, ctl::NWC, ctl::KCX, ctl::NWK> conv_instance(params); std::vector<test::conv::DeviceConvFwdNoOpPtr> conv_ptrs;
test::conv::get_test_convolution_fwd_instance<1>(conv_ptrs);
auto reference_conv_fwd_fun = conv::ConvFwdOpInstance<float, float, float, ctl::NWC, ctl::KCX, ctl::NWK> conv_instance(
std::bind(conv::run_reference_convolution_forward<1, T, T, T>, params, _1, _2, _3); params);
OpInstanceRunEngine<T, T, T> run_engine(conv_instance, reference_conv_fwd_fun);
return run_engine.Test(conv_ptrs);
}
bool test_conv1d_nwc_bf16_instances() auto reference_conv_fwd_fun = std::bind(
{ conv::run_reference_convolution_forward<1, float, float, float>, params, _1, _2, _3);
return test_conv1d_nwc_instances<ck::bhalf_t>( OpInstanceRunEngine<float, float, float> run_engine(conv_instance, reference_conv_fwd_fun);
ck::utils::conv::ConvolutionFwdInstances<ck::bhalf_t, ck::bhalf_t, ck::bhalf_t>::Get<1>()); run_engine.SetAtol(1e-5);
run_engine.SetRtol(1e-4);
EXPECT_TRUE(run_engine.Test(conv_ptrs));
} }
bool test_conv1d_nwc_f16_instances() TEST(Conv1DFwdNWC, Bf16Iinstances)
{ {
return test_conv1d_nwc_instances<ck::half_t>( EXPECT_TRUE(test_conv1d_nwc_instances<ck::bhalf_t>(
ck::utils::conv::ConvolutionFwdInstances<ck::half_t, ck::half_t, ck::half_t>::Get<1>()); ck::utils::conv::ConvolutionFwdInstances<ck::bhalf_t, ck::bhalf_t, ck::bhalf_t>::Get<1>()));
} }
bool test_conv1d_nwc_f32_instances() TEST(Conv1DFwdNWC, F16Instances)
{ {
return test_conv1d_nwc_instances<float>( EXPECT_TRUE(test_conv1d_nwc_instances<ck::half_t>(
ck::utils::conv::ConvolutionFwdInstances<float, float, float>::Get<1>()); ck::utils::conv::ConvolutionFwdInstances<ck::half_t, ck::half_t, ck::half_t>::Get<1>()));
} }
bool test_conv1d_nwc_int8_instances() TEST(Conv1DFwdNWC, F32Instances)
{ {
return test_conv1d_nwc_instances<int8_t>( EXPECT_TRUE(test_conv1d_nwc_instances<float>(
ck::utils::conv::ConvolutionFwdInstances<int8_t, int8_t, int8_t>::Get<1>()); ck::utils::conv::ConvolutionFwdInstances<float, float, float>::Get<1>()));
} }
} // anonymous namespace TEST(Conv1DFwdNWC, Int8Instances)
int main()
{ {
bool res{true}; EXPECT_TRUE(test_conv1d_nwc_instances<int8_t>(
res = test_conv1D_nwc(); ck::utils::conv::ConvolutionFwdInstances<int8_t, int8_t, int8_t>::Get<1>()));
std::cout << "test_conv1D_nwc ..... " << (res ? "SUCCESS" : "FAILURE") << std::endl;
res = test_conv1d_nwc_bf16_instances();
std::cout << "\nTestConv1DNWCBF16Instances ..... " << (res ? "SUCCESS" : "FAILURE")
<< std::endl;
res = test_conv1d_nwc_f16_instances();
std::cout << "\ntest_conv1d_nwc_f16_instances ..... " << (res ? "SUCCESS" : "FAILURE")
<< std::endl;
res = test_conv1d_nwc_f32_instances();
std::cout << "\ntest_conv1d_nwc_f32_instances ..... " << (res ? "SUCCESS" : "FAILURE")
<< std::endl;
res = test_conv1d_nwc_int8_instances();
std::cout << "\ntest_conv1d_nwc_int8_instances ..... " << (res ? "SUCCESS" : "FAILURE")
<< std::endl;
return res ? 0 : 1;
} }
test/convnd_fwd/conv2d_fwd.cpp
View file @ d0b9a467
...@@ -2,6 +2,7 @@ ...@@ -2,6 +2,7 @@
#include <iostream> #include <iostream>
#include <tuple> #include <tuple>
#include <vector> #include <vector>
#include "gtest/gtest.h"
#include "data_type.hpp" #include "data_type.hpp"
#include "element_wise_operation.hpp" #include "element_wise_operation.hpp"
...@@ -10,30 +11,6 @@ ...@@ -10,30 +11,6 @@
namespace { namespace {
bool test_conv2d_nhwc()
{
using namespace std::placeholders;
using namespace ck::utils;
ck::utils::conv::ConvParams params;
params.N = 2;
params.K = 16;
params.C = 4;
params.input_spatial_lengths = std::vector<ck::index_t>{16, 16};
params.conv_filter_strides = std::vector<ck::index_t>{1, 1};
std::vector<test::conv::DeviceConvFwdNoOpPtr> conv_ptrs;
test::conv::get_test_convolution_fwd_instance<2>(conv_ptrs);
conv::ConvFwdOpInstance<float, float, float> conv_instance(params);
auto reference_conv_fwd_fun = std::bind(
conv::run_reference_convolution_forward<2, float, float, float>, params, _1, _2, _3);
OpInstanceRunEngine<float, float, float> run_engine(conv_instance, reference_conv_fwd_fun);
run_engine.SetAtol(1e-5);
run_engine.SetRtol(1e-4);
return run_engine.Test(conv_ptrs);
}
template <typename T> template <typename T>
bool test_conv2d_nhwc_instances(const std::vector<test::conv::DeviceConvFwdNoOpPtr>& conv_ptrs) bool test_conv2d_nhwc_instances(const std::vector<test::conv::DeviceConvFwdNoOpPtr>& conv_ptrs)
{ {
...@@ -57,50 +34,58 @@ bool test_conv2d_nhwc_instances(const std::vector<test::conv::DeviceConvFwdNoOpP ...@@ -57,50 +34,58 @@ bool test_conv2d_nhwc_instances(const std::vector<test::conv::DeviceConvFwdNoOpP
return run_engine.Test(conv_ptrs); return run_engine.Test(conv_ptrs);
} }
bool test_conv2d_nhwc_bf16_instances() } // anonymous namespace
TEST(Conv2DFwdNHWC, TestConv2D)
{ {
return test_conv2d_nhwc_instances<ck::bhalf_t>( using namespace std::placeholders;
ck::utils::conv::ConvolutionFwdInstances<ck::bhalf_t, ck::bhalf_t, ck::bhalf_t>::Get<2>()); using namespace ck::utils;
ck::utils::conv::ConvParams params;
params.N = 2;
params.K = 16;
params.C = 4;
params.input_spatial_lengths = std::vector<ck::index_t>{16, 16};
params.conv_filter_strides = std::vector<ck::index_t>{1, 1};
std::vector<test::conv::DeviceConvFwdNoOpPtr> conv_ptrs;
test::conv::get_test_convolution_fwd_instance<2>(conv_ptrs);
conv::ConvFwdOpInstance<float, float, float> conv_instance(params);
auto reference_conv_fwd_fun = std::bind(
conv::run_reference_convolution_forward<2, float, float, float>, params, _1, _2, _3);
OpInstanceRunEngine<float, float, float> 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));
} }
bool test_conv2d_nhwc_f16_instances() TEST(Conv2DFwdNHWC, Bf16Instances)
{ {
return test_conv2d_nhwc_instances<ck::half_t>( EXPECT_TRUE(test_conv2d_nhwc_instances<ck::bhalf_t>(
ck::utils::conv::ConvolutionFwdInstances<ck::half_t, ck::half_t, ck::half_t>::Get<2>()); ck::utils::conv::ConvolutionFwdInstances<ck::bhalf_t, ck::bhalf_t, ck::bhalf_t>::Get<2>()));
} }
bool test_conv2d_nhwc_f32_instances() TEST(Conv2DFwdNHWC, F16Instances)
{ {
return test_conv2d_nhwc_instances<float>( EXPECT_TRUE(test_conv2d_nhwc_instances<ck::half_t>(
ck::utils::conv::ConvolutionFwdInstances<float, float, float>::Get<2>()); ck::utils::conv::ConvolutionFwdInstances<ck::half_t, ck::half_t, ck::half_t>::Get<2>()));
} }
bool test_conv2d_nhwc_int8_instances() TEST(Conv2DFwdNHWC, BF32Instances)
{ {
return test_conv2d_nhwc_instances<int8_t>( EXPECT_TRUE(test_conv2d_nhwc_instances<float>(
ck::utils::conv::ConvolutionFwdInstances<int8_t, int8_t, int8_t>::Get<2>()); ck::utils::conv::ConvolutionFwdInstances<float, float, float>::Get<2>()));
} }
} // anonymous namespace TEST(Conv2DFwdNHWC, F32Instances)
{
EXPECT_TRUE(test_conv2d_nhwc_instances<float>(
ck::utils::conv::ConvolutionFwdInstances<float, float, float>::Get<2>()));
}
int main() TEST(Conv2DFwdNHWC, Int8Instances)
{ {
bool res{true}; EXPECT_TRUE(test_conv2d_nhwc_instances<int8_t>(
res = test_conv2d_nhwc(); ck::utils::conv::ConvolutionFwdInstances<int8_t, int8_t, int8_t>::Get<2>()));
std::cout << "test_conv2d_nhwc ..... " << (res ? "SUCCESS" : "FAILURE") << std::endl;
res = test_conv2d_nhwc_bf16_instances();
std::cout << "\ntest_conv2d_nhwc_bf16_instances ..... " << (res ? "SUCCESS" : "FAILURE")
<< std::endl;
res = test_conv2d_nhwc_f16_instances();
std::cout << "\ntest_conv2d_nhwc_f16_instances ....." << (res ? "SUCCESS" : "FAILURE")
<< std::endl;
res = test_conv2d_nhwc_f32_instances();
std::cout << "\ntest_conv2d_nhwc_f32_instances ..... " << (res ? "SUCCESS" : "FAILURE")
<< std::endl;
res = test_conv2d_nhwc_int8_instances();
std::cout << "\ntest_conv2d_nhwc_int8_instances ..... " << (res ? "SUCCESS" : "FAILURE")
<< std::endl;
return res ? 0 : 1;
} }
test/convnd_fwd/conv3d_fwd.cpp
View file @ d0b9a467
...@@ -3,6 +3,7 @@ ...@@ -3,6 +3,7 @@
#include <stdexcept> #include <stdexcept>
#include <tuple> #include <tuple>
#include <vector> #include <vector>
#include "gtest/gtest.h"
#include "data_type.hpp" #include "data_type.hpp"
#include "element_wise_operation.hpp" #include "element_wise_operation.hpp"
...@@ -11,7 +12,34 @@ ...@@ -11,7 +12,34 @@
namespace { namespace {
bool test_conv3d_ndhwc() template <typename T>
bool test_conv3d_ndhwc_instances(const std::vector<test::conv::DeviceConvFwdNoOpPtr>& conv_ptrs)
{
using namespace std::placeholders;
using namespace ck::utils;
namespace ctl = ck::tensor_layout::convolution;
conv::ConvParams params;
params.N = 64;
params.num_dim_spatial = 3;
params.filter_spatial_lengths = std::vector<ck::index_t>{3, 3, 2};
params.input_spatial_lengths = std::vector<ck::index_t>{32, 32, 2};
params.conv_filter_strides = std::vector<ck::index_t>{2, 2, 2};
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};
conv::ConvFwdOpInstance<T, T, T, ctl::NDHWC, ctl::KZYXC, ctl::NDHWK> conv_instance(params);
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);
return run_engine.Test(conv_ptrs);
}
} // anonymous namespace
TEST(Conv3DFwdNDHWC, TestConv3D)
{ {
using namespace std::placeholders; using namespace std::placeholders;
using namespace ck::utils; using namespace ck::utils;
...@@ -39,10 +67,10 @@ bool test_conv3d_ndhwc() ...@@ -39,10 +67,10 @@ bool test_conv3d_ndhwc()
OpInstanceRunEngine<float, float, float> run_engine(conv_instance, reference_conv_fwd_fun); OpInstanceRunEngine<float, float, float> run_engine(conv_instance, reference_conv_fwd_fun);
run_engine.SetAtol(1e-5); run_engine.SetAtol(1e-5);
run_engine.SetRtol(1e-4); run_engine.SetRtol(1e-4);
return run_engine.Test(conv_ptrs); EXPECT_TRUE(run_engine.Test(conv_ptrs));
} }
bool test_conv3d_ndhwc_2gb_input() TEST(Conv3DFwdNDHWC, InputOver2GB)
{ {
using PassThrough = ck::tensor_operation::element_wise::PassThrough; using PassThrough = ck::tensor_operation::element_wise::PassThrough;
using namespace ck::utils; using namespace ck::utils;
...@@ -79,10 +107,10 @@ bool test_conv3d_ndhwc_2gb_input() ...@@ -79,10 +107,10 @@ bool test_conv3d_ndhwc_2gb_input()
PassThrough{}, PassThrough{},
PassThrough{}, PassThrough{},
PassThrough{}); PassThrough{});
return !(conv_ptrs.back()->IsSupportedArgument(arg.get())); EXPECT_FALSE(conv_ptrs.back()->IsSupportedArgument(arg.get()));
} }
bool test_conv3d_ndhwc_2gb_filters() TEST(Conv3DFwdNDHWC, FiltersOver2GB)
{ {
using PassThrough = ck::tensor_operation::element_wise::PassThrough; using PassThrough = ck::tensor_operation::element_wise::PassThrough;
using namespace ck::utils; using namespace ck::utils;
...@@ -119,10 +147,10 @@ bool test_conv3d_ndhwc_2gb_filters() ...@@ -119,10 +147,10 @@ bool test_conv3d_ndhwc_2gb_filters()
PassThrough{}, PassThrough{},
PassThrough{}, PassThrough{},
PassThrough{}); PassThrough{});
return !(conv_ptrs.back()->IsSupportedArgument(arg.get())); EXPECT_FALSE(conv_ptrs.back()->IsSupportedArgument(arg.get()));
} }
bool test_conv3d_ndhwc_2gb_output() TEST(Conv3DFwdNDHWC, OutputOver2GB)
{ {
using PassThrough = ck::tensor_operation::element_wise::PassThrough; using PassThrough = ck::tensor_operation::element_wise::PassThrough;
using namespace ck::utils; using namespace ck::utils;
...@@ -158,88 +186,29 @@ bool test_conv3d_ndhwc_2gb_output() ...@@ -158,88 +186,29 @@ bool test_conv3d_ndhwc_2gb_output()
PassThrough{}, PassThrough{},
PassThrough{}, PassThrough{},
PassThrough{}); PassThrough{});
return !(conv_ptrs.back()->IsSupportedArgument(arg.get())); EXPECT_FALSE(conv_ptrs.back()->IsSupportedArgument(arg.get()));
}
template <typename T>
bool test_conv3d_ndhwc_instances(const std::vector<test::conv::DeviceConvFwdNoOpPtr>& conv_ptrs)
{
using namespace std::placeholders;
using namespace ck::utils;
namespace ctl = ck::tensor_layout::convolution;
conv::ConvParams params;
params.N = 64;
params.num_dim_spatial = 3;
params.filter_spatial_lengths = std::vector<ck::index_t>{3, 3, 2};
params.input_spatial_lengths = std::vector<ck::index_t>{32, 32, 2};
params.conv_filter_strides = std::vector<ck::index_t>{2, 2, 2};
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};
conv::ConvFwdOpInstance<T, T, T, ctl::NDHWC, ctl::KZYXC, ctl::NDHWK> conv_instance(params);
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);
return run_engine.Test(conv_ptrs);
} }
bool test_conv3d_ndhwc_bf16_instances() TEST(Conv3DFwdNDHWC, Bf16Instances)
{ {
return test_conv3d_ndhwc_instances<ck::bhalf_t>( EXPECT_TRUE(test_conv3d_ndhwc_instances<ck::bhalf_t>(
ck::utils::conv::ConvolutionFwdInstances<ck::bhalf_t, ck::bhalf_t, ck::bhalf_t>::Get<3>()); ck::utils::conv::ConvolutionFwdInstances<ck::bhalf_t, ck::bhalf_t, ck::bhalf_t>::Get<3>()));
} }
bool test_conv3d_ndhwc_f16_instances() TEST(Conv3DFwdNDHWC, F16Instances)
{ {
return test_conv3d_ndhwc_instances<ck::half_t>( EXPECT_TRUE(test_conv3d_ndhwc_instances<ck::half_t>(
ck::utils::conv::ConvolutionFwdInstances<ck::half_t, ck::half_t, ck::half_t>::Get<3>()); ck::utils::conv::ConvolutionFwdInstances<ck::half_t, ck::half_t, ck::half_t>::Get<3>()));
} }
bool test_conv3d_ndhwc_f32_instances() TEST(Conv3DFwdNDHWC, F32Instances)
{ {
return test_conv3d_ndhwc_instances<float>( EXPECT_TRUE(test_conv3d_ndhwc_instances<float>(
ck::utils::conv::ConvolutionFwdInstances<float, float, float>::Get<3>()); ck::utils::conv::ConvolutionFwdInstances<float, float, float>::Get<3>()));
} }
bool test_conv3d_ndhwc_int8_instances() TEST(Conv3DFwdNDHWC, Int8Instances)
{
return test_conv3d_ndhwc_instances<int8_t>(
ck::utils::conv::ConvolutionFwdInstances<int8_t, int8_t, int8_t>::Get<3>());
}
} // anonymous namespace
int main()
{ {
bool res{true}; EXPECT_TRUE(test_conv3d_ndhwc_instances<int8_t>(
res = test_conv3d_ndhwc(); ck::utils::conv::ConvolutionFwdInstances<int8_t, int8_t, int8_t>::Get<3>()));
std::cout << "test_conv3d_ndhwc ..... " << (res ? "SUCCESS" : "FAILURE") << std::endl;
res = test_conv3d_ndhwc_2gb_input();
std::cout << "\ntest_conv3d_ndhwc_2gb_input ..... " << (res ? "SUCCESS" : "FAILURE")
<< std::endl;
res = test_conv3d_ndhwc_2gb_filters();
std::cout << "\ntest_conv3d_ndhwc_2gb_filters ..... " << (res ? "SUCCESS" : "FAILURE")
<< std::endl;
res = test_conv3d_ndhwc_2gb_output();
std::cout << "\ntest_conv3d_ndhwc_2gb_output ..... " << (res ? "SUCCESS" : "FAILURE")
<< std::endl;
res = test_conv3d_ndhwc_bf16_instances();
std::cout << "\ntest_conv3d_ndhwc_bf16_instances ..... " << (res ? "SUCCESS" : "FAILURE")
<< std::endl;
res = test_conv3d_ndhwc_f16_instances();
std::cout << "\ntest_conv3d_ndhwc_f16_instances ..... " << (res ? "SUCCESS" : "FAILURE")
<< std::endl;
res = test_conv3d_ndhwc_f32_instances();
std::cout << "\ntest_conv3d_ndhwc_f32_instances ..... " << (res ? "SUCCESS" : "FAILURE")
<< std::endl;
res = test_conv3d_ndhwc_int8_instances();
std::cout << "\ntest_conv3d_ndhwc_int8_instances ..... " << (res ? "SUCCESS" : "FAILURE")
<< std::endl;
return res ? 0 : 1;
} }
test/gemm/gemm_util.hpp
View file @ d0b9a467
...@@ -139,17 +139,10 @@ struct TestGemm ...@@ -139,17 +139,10 @@ struct TestGemm
Tensor<CDataType> c_m_n_device_result( Tensor<CDataType> c_m_n_device_result(
f_host_tensor_descriptor(params.M, params.N, params.StrideC, CLayout{})); f_host_tensor_descriptor(params.M, params.N, params.StrideC, CLayout{}));
auto f_generate_tensor_value = [](auto desc, auto type) { auto f_generate_tensor_value = [](auto& tensor, auto type) {
using dataType = decltype(type); using dataType = decltype(type);
if(std::is_same<dataType, int8_t>::value) tensor.GenerateTensorValue(GeneratorTensor_2<dataType>{-5, 5});
{
desc.GenerateTensorValue(GeneratorTensor_2<int8_t>{-5, 5});
}
else
{
desc.GenerateTensorValue(GeneratorTensor_3<dataType>{-0.5, 0.5});
}
}; };
f_generate_tensor_value(a_m_k, ADataType{}); f_generate_tensor_value(a_m_k, ADataType{});
......
test/reference_conv_fwd/CMakeLists.txt
View file @ d0b9a467
add_test_executable(test_reference_conv_fwd reference_conv_fwd.cpp) add_gtest_executable(test_reference_conv_fwd reference_conv_fwd.cpp)
target_link_libraries(test_reference_conv_fwd PRIVATE host_tensor conv_fwd_util) target_link_libraries(test_reference_conv_fwd PRIVATE host_tensor conv_fwd_util)
test/reference_conv_fwd/reference_conv_fwd.cpp
View file @ d0b9a467
...@@ -4,6 +4,7 @@ ...@@ -4,6 +4,7 @@
#include <numeric> #include <numeric>
#include <type_traits> #include <type_traits>
#include <vector> #include <vector>
#include "gtest/gtest.h"
#include "check_err.hpp" #include "check_err.hpp"
#include "config.hpp" #include "config.hpp"
...@@ -82,13 +83,13 @@ run_reference_convolution_forward(const ck::utils::conv::ConvParams& params, ...@@ -82,13 +83,13 @@ run_reference_convolution_forward(const ck::utils::conv::ConvParams& params,
OutElementOp{}); OutElementOp{});
ref_invoker.Run(ref_argument); ref_invoker.Run(ref_argument);
// std::cout <<"output: " << host_output.mDesc << std::endl << host_output.mData << std::endl;
return host_output; return host_output;
} }
bool test_conv2d_nhwc() } // anonymous namespace
TEST(ReferenceConvolutionFWD, Conv2DNHWC)
{ {
bool res{true};
ck::utils::conv::ConvParams params; ck::utils::conv::ConvParams params;
params.N = 1; params.N = 1;
params.K = 1; params.K = 1;
...@@ -118,11 +119,14 @@ bool test_conv2d_nhwc() ...@@ -118,11 +119,14 @@ bool test_conv2d_nhwc()
472.5, 472.5,
490.5, 490.5,
508.5}; 508.5};
res = res && ck::utils::check_err(out_tensor.mDesc.GetLengths(), EXPECT_TRUE(ck::utils::check_err(
ref_dims, out_tensor.mDesc.GetLengths(), ref_dims, "Error: wrong output tensor dimensions!"));
"Error: wrong output tensor dimensions!"); EXPECT_TRUE(ck::utils::check_err(out_tensor.mData, ref_data, "Error: incorrect results!"));
res = res && ck::utils::check_err(out_tensor.mData, ref_data, "Error: incorrect results!"); }
TEST(ReferenceConvolutionFWD, Conv2DNHWCStridesDilationsPadding)
{
ck::utils::conv::ConvParams params;
params.N = 1; params.N = 1;
params.K = 2; params.K = 2;
params.C = 2; params.C = 2;
...@@ -133,25 +137,21 @@ bool test_conv2d_nhwc() ...@@ -133,25 +137,21 @@ bool test_conv2d_nhwc()
params.input_left_pads = std::vector<ck::index_t>{1, 1}; params.input_left_pads = std::vector<ck::index_t>{1, 1};
params.input_right_pads = std::vector<ck::index_t>{1, 1}; params.input_right_pads = std::vector<ck::index_t>{1, 1};
out_tensor = run_reference_convolution_forward<2>(params); auto out_tensor = run_reference_convolution_forward<2>(params);
ref_dims = std::vector<std::size_t>{1, 2, 5, 5}; std::vector<std::size_t> ref_dims = std::vector<std::size_t>{1, 2, 5, 5};
ref_data = std::vector<float>{ std::vector<float> ref_data{
210., 210., 327., 327., 351., 351., 375., 375., 399., 399., 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, 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, 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, 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}; 1323., 1323., 2002.5, 2002.5, 2038.5, 2038.5, 2074.5, 2074.5, 2110.5, 2110.5};
res = res && ck::utils::check_err(out_tensor.mDesc.GetLengths(), EXPECT_TRUE(ck::utils::check_err(
ref_dims, out_tensor.mDesc.GetLengths(), ref_dims, "Error: wrong output tensor dimensions!"));
"Error: wrong output tensor dimensions!"); EXPECT_TRUE(ck::utils::check_err(out_tensor.mData, ref_data, "Error: incorrect results!"));
res = res && ck::utils::check_err(out_tensor.mData, ref_data, "Error: incorrect results!");
return res;
} }
bool test_conv1d_nwc() TEST(ReferenceConvolutionFWD, Conv1DNWC)
{ {
bool res{true};
ck::utils::conv::ConvParams params; ck::utils::conv::ConvParams params;
params.num_dim_spatial = 1; params.num_dim_spatial = 1;
params.N = 1; params.N = 1;
...@@ -174,11 +174,14 @@ bool test_conv1d_nwc() ...@@ -174,11 +174,14 @@ bool test_conv1d_nwc()
ck::tensor_layout::convolution::NWK>(params); ck::tensor_layout::convolution::NWK>(params);
std::vector<std::size_t> ref_dims{1, 1, 4}; std::vector<std::size_t> ref_dims{1, 1, 4};
std::vector<float> ref_data{7.5, 13.5, 19.5, 25.5}; std::vector<float> ref_data{7.5, 13.5, 19.5, 25.5};
res = res && ck::utils::check_err(out_tensor.mDesc.GetLengths(), EXPECT_TRUE(ck::utils::check_err(
ref_dims, out_tensor.mDesc.GetLengths(), ref_dims, "Error: wrong output tensor dimensions!"));
"Error: wrong output tensor dimensions!"); EXPECT_TRUE(ck::utils::check_err(out_tensor.mData, ref_data, "Error: incorrect results!"));
res = res && ck::utils::check_err(out_tensor.mData, ref_data, "Error: incorrect results!"); }
TEST(ReferenceConvolutionFWD, Conv1DNWCStridesDilationsPadding)
{
ck::utils::conv::ConvParams params;
params.num_dim_spatial = 1; params.num_dim_spatial = 1;
params.N = 1; params.N = 1;
params.K = 2; params.K = 2;
...@@ -190,20 +193,24 @@ bool test_conv1d_nwc() ...@@ -190,20 +193,24 @@ bool test_conv1d_nwc()
params.input_left_pads = std::vector<ck::index_t>{1}; params.input_left_pads = std::vector<ck::index_t>{1};
params.input_right_pads = std::vector<ck::index_t>{1}; params.input_right_pads = std::vector<ck::index_t>{1};
out_tensor = run_reference_convolution_forward<1, auto out_tensor =
run_reference_convolution_forward<1,
float, float,
float, float,
float, float,
ck::tensor_layout::convolution::NWC, ck::tensor_layout::convolution::NWC,
ck::tensor_layout::convolution::KXC, ck::tensor_layout::convolution::KXC,
ck::tensor_layout::convolution::NWK>(params); ck::tensor_layout::convolution::NWK>(params);
ref_dims = std::vector<std::size_t>{1, 2, 5}; std::vector<std::size_t> ref_dims{1, 2, 5};
ref_data = std::vector<float>{9., 9., 19.5, 19.5, 31.5, 31.5, 43.5, 43.5, 55.5, 55.5}; std::vector<float> ref_data{9., 9., 19.5, 19.5, 31.5, 31.5, 43.5, 43.5, 55.5, 55.5};
res = res && ck::utils::check_err(out_tensor.mDesc.GetLengths(), EXPECT_TRUE(ck::utils::check_err(
ref_dims, out_tensor.mDesc.GetLengths(), ref_dims, "Error: wrong output tensor dimensions!"));
"Error: wrong output tensor dimensions!"); EXPECT_TRUE(ck::utils::check_err(out_tensor.mData, ref_data, "Error: incorrect results!"));
res = res && ck::utils::check_err(out_tensor.mData, ref_data, "Error: incorrect results!"); }
TEST(ReferenceConvolutionFWD, Conv1DNWCSameOutputSize)
{
ck::utils::conv::ConvParams params;
params.num_dim_spatial = 1; params.num_dim_spatial = 1;
params.N = 2; params.N = 2;
params.K = 16; params.K = 16;
...@@ -224,8 +231,8 @@ bool test_conv1d_nwc() ...@@ -224,8 +231,8 @@ bool test_conv1d_nwc()
ck::tensor_layout::convolution::NWK>( ck::tensor_layout::convolution::NWK>(
params, ck::utils::FillMonotonicSeq<float>{0.f, 0.1f}); params, ck::utils::FillMonotonicSeq<float>{0.f, 0.1f});
ref_dims = std::vector<std::size_t>{2, 16, 16}; std::vector<std::size_t> ref_dims{2, 16, 16};
ref_data = std::vector<float>{ 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,
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,
...@@ -290,17 +297,13 @@ bool test_conv1d_nwc() ...@@ -290,17 +297,13 @@ bool test_conv1d_nwc()
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,
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};
res = res && ck::utils::check_err(out_tensor2.mDesc.GetLengths(), EXPECT_TRUE(ck::utils::check_err(
ref_dims, out_tensor2.mDesc.GetLengths(), ref_dims, "Error: wrong output tensor dimensions!"));
"Error: wrong output tensor dimensions!"); EXPECT_TRUE(ck::utils::check_err(out_tensor2.mData, ref_data, "Error: incorrect results!"));
res = res && ck::utils::check_err(out_tensor2.mData, ref_data, "Error: incorrect results!");
return res;
} }
bool test_conv3d_ncdhw() TEST(ReferenceConvolutionFWD, Conv3DNCDHW)
{ {
bool res{true};
ck::utils::conv::ConvParams params; ck::utils::conv::ConvParams params;
params.num_dim_spatial = 3; params.num_dim_spatial = 3;
params.N = 1; params.N = 1;
...@@ -331,12 +334,17 @@ bool test_conv3d_ncdhw() ...@@ -331,12 +334,17 @@ bool test_conv3d_ncdhw()
634.5, 637.2, 639.9, 642.60004, 650.7, 653.4, 656.10004, 658.8, 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, 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.}; 731.7, 734.4001, 737.10004, 739.8, 747.9001, 750.60004, 753.3, 756.};
res = res && ck::utils::check_err(out_tensor.mDesc.GetLengths(), EXPECT_TRUE(ck::utils::check_err(out_tensor.mDesc.GetLengths(),
ref_dims, ref_dims,
"Error [case 1]: wrong output tensor dimensions!"); "Error [case 1]: wrong output tensor dimensions!"));
res = res && EXPECT_TRUE(
ck::utils::check_err(out_tensor.mData, ref_data, "Error [case 1]: incorrect results!"); ck::utils::check_err(out_tensor.mData, ref_data, "Error [case 1]: incorrect results!"));
}
TEST(ReferenceConvolutionFWD, Conv3DNCDHWStridesDilations)
{
ck::utils::conv::ConvParams params;
params.num_dim_spatial = 3;
params.N = 1; params.N = 1;
params.K = 2; params.K = 2;
params.C = 2; params.C = 2;
...@@ -347,7 +355,7 @@ bool test_conv3d_ncdhw() ...@@ -347,7 +355,7 @@ bool test_conv3d_ncdhw()
params.input_left_pads = std::vector<ck::index_t>{0, 0, 0}; params.input_left_pads = std::vector<ck::index_t>{0, 0, 0};
params.input_right_pads = std::vector<ck::index_t>{0, 0, 0}; params.input_right_pads = std::vector<ck::index_t>{0, 0, 0};
out_tensor = run_reference_convolution_forward<3, auto out_tensor = run_reference_convolution_forward<3,
float, float,
float, float,
float, float,
...@@ -355,8 +363,8 @@ bool test_conv3d_ncdhw() ...@@ -355,8 +363,8 @@ bool test_conv3d_ncdhw()
ck::tensor_layout::convolution::KCZYX, ck::tensor_layout::convolution::KCZYX,
ck::tensor_layout::convolution::NKDHW>( ck::tensor_layout::convolution::NKDHW>(
params, ck::utils::FillMonotonicSeq<float>{0.f, 0.1f}); params, ck::utils::FillMonotonicSeq<float>{0.f, 0.1f});
ref_dims = std::vector<std::size_t>{1, 2, 4, 4, 4}; std::vector<std::size_t> ref_dims{1, 2, 4, 4, 4};
ref_data = std::vector<float>{ std::vector<float> ref_data{
2756.7002, 2764.7998, 2772.9001, 2781., 2853.9001, 2862., 2870.1, 2878.2002, 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, 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, 3923.1, 3931.2, 3939.2998, 3947.4, 4020.2998, 4028.4001, 4036.5002, 4044.5999,
...@@ -373,26 +381,9 @@ bool test_conv3d_ncdhw() ...@@ -373,26 +381,9 @@ bool test_conv3d_ncdhw()
5283.9004, 5292., 5300.0996, 5308.2, 5381.0996, 5389.2, 5397.3, 5405.4004, 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, 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}; 6450.301, 6458.4, 6466.5, 6474.6, 6547.5, 6555.6, 6563.699, 6571.801};
res = res && ck::utils::check_err(out_tensor.mDesc.GetLengths(), EXPECT_TRUE(ck::utils::check_err(out_tensor.mDesc.GetLengths(),
ref_dims, ref_dims,
"Error [case 2]: wrong output tensor dimensions!"); "Error [case 2]: wrong output tensor dimensions!"));
res = EXPECT_TRUE(ck::utils::check_err(
res && ck::utils::check_err( out_tensor.mData, ref_data, "Error [case 2]: incorrect results!", 1e-4f, 1e-6f));
out_tensor.mData, ref_data, "Error [case 2]: incorrect results!", 1e-4f, 1e-6f);
return res;
}
} // anonymous namespace
int main(void)
{
bool res{true};
res = test_conv2d_nhwc();
std::cout << "test_conv2d_nhwc ..... " << (res ? "SUCCESS" : "FAILURE") << std::endl;
res = test_conv1d_nwc();
std::cout << "TestConv1DNHWC ..... " << (res ? "SUCCESS" : "FAILURE") << std::endl;
res = test_conv3d_ncdhw();
std::cout << "test_conv3d_ncdhw ..... " << (res ? "SUCCESS" : "FAILURE") << std::endl;
return res ? 0 : 1;
} }
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