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oneDNN/tests/gtests/test_sum.cpp
2025-04-25 11:15:50 -07:00

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C++

/*******************************************************************************
* Copyright 2016-2025 Intel Corporation
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*******************************************************************************/
#include "dnnl_test_common.hpp"
#include "gtest/gtest.h"
#include "oneapi/dnnl/dnnl.hpp"
namespace dnnl {
using tag = memory::format_tag;
/* iface tests */
class iface_sum_test_t : public ::testing::Test {
protected:
engine eng;
stream strm;
void SetUp() override {
eng = get_test_engine();
strm = make_stream(eng);
}
};
TEST_F(iface_sum_test_t, SumTestDstDataTypeCompliance) {
SKIP_IF_HIP(true, "Sum operator is not supported by HIP");
using dt = memory::data_type;
const dt src_dt = dt::s8;
memory::dims shape = {10, 10, 10, 10};
auto src_md = memory::desc(shape, src_dt, tag::abcd);
for_(tag dst_tag : {tag::any, tag::abcd, tag::acdb})
for (dt dst_dt : {dt::undef, dt::s8, dt::s32, dt::f32}) {
sum::primitive_desc sum_pd;
SKIP_FOR_LOOP_CUDA(dst_dt == dt::s32, "Unsupported data_type");
SKIP_FOR_LOOP_GENERIC(dst_dt == dt::s32, "Unsupported data_type");
if (dst_dt != dt::undef) {
memory::desc dst_md(shape, dst_dt, dst_tag);
sum_pd = sum::primitive_desc(
eng, dst_md, {2., 2.}, {src_md, src_md});
} else {
sum_pd = sum::primitive_desc(eng, {2., 2.}, {src_md, src_md});
}
dt expect_dst_dt = dst_dt == dt::undef ? src_dt : dst_dt;
ASSERT_EQ(sum_pd.dst_desc().get_data_type(), expect_dst_dt);
}
}
/* correctness tests */
struct sum_test_params {
std::vector<tag> srcs_format;
tag dst_format;
memory::dims dims;
std::vector<float> scale;
bool is_output_omitted;
bool expect_to_fail;
dnnl_status_t expected_status;
};
template <typename src_data_t, typename acc_t, typename dst_data_t = src_data_t>
class sum_test_t : public ::testing::TestWithParam<sum_test_params> {
private:
memory::data_type src_data_type;
memory::data_type dst_data_type;
void check_data(const std::vector<memory> &srcs,
const std::vector<float> &scale, const memory &dst) {
auto dst_data = map_memory<const dst_data_t>(dst);
const auto &dst_d = dst.get_desc();
const auto dst_dims = dst_d.get_dims();
const dnnl::impl::memory_desc_wrapper dst_mdw(dst_d.get());
std::vector<mapped_ptr_t<const src_data_t>> mapped_srcs;
mapped_srcs.reserve(srcs.size());
for (auto &src : srcs)
mapped_srcs.emplace_back(map_memory<const src_data_t>(src));
dnnl::impl::parallel_nd(dst_dims[0], dst_dims[1], dst_dims[2],
dst_dims[3],
[&](memory::dim n, memory::dim c, memory::dim h,
memory::dim w) {
if (is_current_test_failed()) return;
acc_t src_sum = 0.0;
for (size_t num = 0; num < srcs.size(); num++) {
auto &src_data = mapped_srcs[num];
const auto &src_d = srcs[num].get_desc();
const auto src_dims = src_d.get_dims();
const dnnl::impl::memory_desc_wrapper src_mdw(
src_d.get());
auto src_idx = w + src_dims[3] * h
+ src_dims[2] * src_dims[3] * c
+ src_dims[1] * src_dims[2] * src_dims[3] * n;
if (num == 0) {
src_sum = acc_t(scale[num])
* src_data[src_mdw.off_l(src_idx, false)];
} else {
src_sum += acc_t(scale[num])
* src_data[src_mdw.off_l(src_idx, false)];
}
src_sum = (std::max)(
(std::min)(src_sum,
(std::numeric_limits<acc_t>::max)()),
std::numeric_limits<acc_t>::lowest());
}
auto dst_idx = w + dst_dims[3] * h
+ dst_dims[2] * dst_dims[3] * c
+ dst_dims[1] * dst_dims[2] * dst_dims[3] * n;
acc_t dst_val = dst_data[dst_mdw.off_l(dst_idx, false)];
ASSERT_EQ(src_sum, dst_val);
});
}
protected:
bool cuda_supported_format_tag(memory::format_tag tag) {
return impl::utils::one_of(tag, dnnl_a, dnnl_ab, dnnl_abc, dnnl_abcd,
dnnl_abcde, dnnl_abcdef, dnnl_abdec, dnnl_acb, dnnl_acbde,
dnnl_acbdef, dnnl_acdb, dnnl_acdeb, dnnl_ba, dnnl_bac,
dnnl_bacd, dnnl_bca, dnnl_bcda, dnnl_bcdea, dnnl_cba, dnnl_cdba,
dnnl_cdeba, dnnl_decab, dnnl_defcab, dnnl_aBc4b, dnnl_aBcd4b,
dnnl_aBcde4b);
}
bool generic_supported_format_tag(memory::format_tag tag) {
return impl::utils::one_of(tag, dnnl_a, dnnl_ab, dnnl_abc, dnnl_abcd,
dnnl_abcde, dnnl_abcdef, dnnl_abdec, dnnl_acb, dnnl_acbde,
dnnl_acbdef, dnnl_acdb, dnnl_acdeb, dnnl_ba, dnnl_bac,
dnnl_bacd, dnnl_bca, dnnl_bcda, dnnl_bcdea, dnnl_cba, dnnl_cdba,
dnnl_cdeba, dnnl_decab, dnnl_defcab, dnnl_format_tag_any);
}
bool generic_supported_dt(memory::data_type dt) {
return impl::utils::one_of(
dt, dnnl_f32, dnnl_bf16, dnnl_f16, dnnl_s8, dnnl_u8);
}
void SetUp() override {
SKIP_IF_HIP(true, "Sum operator is not supported by HIP");
src_data_type = data_traits_t<src_data_t>::data_type;
dst_data_type = data_traits_t<dst_data_t>::data_type;
sum_test_params p
= ::testing::TestWithParam<sum_test_params>::GetParam();
SKIP_IF(get_test_engine_kind() == engine::kind::gpu
&& src_data_type == memory::data_type::bf16,
"GPU does not support bfloat16 data type.");
SKIP_IF(unsupported_data_type(src_data_type),
"Engine does not support this data type.");
SKIP_IF(unsupported_data_type(dst_data_type),
"Engine does not support this data type.");
SKIP_IF_CUDA(!cuda_supported_format_tag(p.dst_format),
"Unsupported format tag");
for (size_t i = 0; i < p.srcs_format.size(); i++) {
SKIP_IF_CUDA(!cuda_supported_format_tag(p.srcs_format[i]),
"Unsupported format tag");
}
SKIP_IF_GENERIC(
!generic_supported_dt(src_data_type), "Unsupported data type");
SKIP_IF_GENERIC(
!generic_supported_dt(dst_data_type), "Unsupported data type");
SKIP_IF_GENERIC(!generic_supported_format_tag(p.dst_format),
"Unsupported format tag");
for (size_t i = 0; i < p.srcs_format.size(); i++) {
SKIP_IF_GENERIC(!generic_supported_format_tag(p.srcs_format[i]),
"Unsupported format tag");
}
catch_expected_failures(
[&]() { Test(); }, p.expect_to_fail, p.expected_status);
}
void Test() {
sum_test_params p
= ::testing::TestWithParam<sum_test_params>::GetParam();
// sum specific types and values
using pd_t = sum::primitive_desc;
const auto num_srcs = p.srcs_format.size();
auto eng = get_test_engine();
auto strm = make_stream(eng);
std::vector<memory::desc> srcs_md;
srcs_md.reserve(num_srcs);
std::vector<memory> srcs;
for (size_t i = 0; i < num_srcs; i++)
srcs_md.emplace_back(p.dims, src_data_type, p.srcs_format[i]);
memory dst;
sum::primitive_desc sum_pd;
if (p.is_output_omitted) {
ASSERT_NO_THROW(sum_pd = pd_t(eng, p.scale, srcs_md));
} else {
auto dst_desc = memory::desc(p.dims, dst_data_type, p.dst_format);
sum_pd = pd_t(eng, dst_desc, p.scale, srcs_md);
ASSERT_EQ(sum_pd.dst_desc().get_ndims(), dst_desc.get_ndims());
}
dst = test::make_memory(sum_pd.dst_desc(), eng);
// test all pd ctors
allows_attr_t aa {};
if (p.is_output_omitted)
test_fwd_pd_constructors<pd_t>(sum_pd, aa, p.scale, srcs_md);
else {
auto dst_desc = memory::desc(p.dims, dst_data_type, p.dst_format);
test_fwd_pd_constructors<pd_t>(
sum_pd, aa, dst_desc, p.scale, srcs_md);
}
for (size_t i = 0; i < num_srcs; i++) {
if (p.srcs_format[i] != memory::format_tag::any) {
ASSERT_TRUE(srcs_md[(int)i] == sum_pd.src_desc((int)i));
}
auto src_memory = test::make_memory(sum_pd.src_desc((int)i), eng);
const size_t sz
= src_memory.get_desc().get_size() / sizeof(src_data_t);
fill_data<src_data_t>(sz, src_memory);
// Keep few mantissa digits for fp types to avoid round-off errors
// With proper scalars the computations give exact results
if (!std::is_integral<src_data_t>::value) {
using uint_type = typename data_traits_t<src_data_t>::uint_type;
int mant_digits
= dnnl::impl::nstl::numeric_limits<src_data_t>::digits;
int want_mant_digits = 3;
int digits_shift = mant_digits - want_mant_digits;
uint_type max_val = (uint_type)-1;
// Move left to keep mask value in uint_type range, move left
// to flush all digits but `want_mant_digits`.
uint_type mask = (max_val >> digits_shift) << digits_shift;
auto src_ptr = map_memory<src_data_t>(src_memory);
for (size_t i = 0; i < sz; i++) {
*((uint_type *)&src_ptr[i]) &= mask;
}
}
srcs.push_back(src_memory);
}
ASSERT_TRUE(sum_pd.query_md(query::exec_arg_md, DNNL_ARG_DST)
== sum_pd.dst_desc());
for (int i = 0; i < (int)srcs.size(); i++)
ASSERT_TRUE(sum_pd.query_md(
query::exec_arg_md, DNNL_ARG_MULTIPLE_SRC + i)
== sum_pd.src_desc(i));
{
auto dst_data = map_memory<dst_data_t>(dst);
const size_t sz = dst.get_desc().get_size() / sizeof(dst_data_t);
// overwriting dst to prevent false positives for test cases.
dnnl::impl::parallel_nd(
(ptrdiff_t)sz, [&](ptrdiff_t i) { dst_data[i] = -32; });
}
EXPECT_ANY_THROW(sum(sum_pd, {}));
sum c(sum_pd);
std::unordered_map<int, memory> args = {{DNNL_ARG_DST, dst}};
for (int i = 0; i < (int)num_srcs; i++) {
args.insert({DNNL_ARG_MULTIPLE_SRC + i, srcs[i]});
}
c.execute(strm, args);
strm.wait();
check_data(srcs, p.scale, dst);
}
};
static auto simple_test_cases = [](bool omit_output) {
return ::testing::Values(
sum_test_params {{tag::nchw, tag::nChw8c}, tag::nchw, {0, 7, 4, 4},
{1.0f, 1.0f}, omit_output},
sum_test_params {{tag::nchw, tag::nChw8c}, tag::nchw, {1, 0, 4, 4},
{1.0f, 1.0f}, omit_output},
sum_test_params {{tag::nchw, tag::nChw8c}, tag::nchw, {1, 8, 0, 4},
{1.0f, 1.0f}, omit_output},
sum_test_params {{tag::nchw, tag::nChw8c}, tag::nchw, {-1, 8, 4, 4},
{1.0f, 1.0f}, omit_output, true, dnnl_invalid_arguments},
sum_test_params {{tag::nchw, tag::nChw8c}, tag::nchw,
{1, 1024, 38, 50}, {1.0f, 1.0f}, omit_output},
sum_test_params {{tag::nchw, tag::nchw}, tag::nchw, {2, 8, 2, 2},
{1.0f, 1.0f}, omit_output},
sum_test_params {{tag::nChw8c, tag::nChw8c}, tag::nChw8c,
{2, 16, 3, 4}, {1.0f, 1.0f}, omit_output},
sum_test_params {{tag::nchw, tag::nchw}, tag::nChw8c, {2, 16, 2, 2},
{1.0f, 1.0f}, omit_output},
sum_test_params {{tag::nChw8c, tag::nChw8c}, tag::nchw,
{2, 16, 3, 4}, {1.0f, 1.0f}, omit_output},
sum_test_params {{tag::nchw, tag::nchw}, tag::nchw, {2, 8, 2, 2},
{2.0f, 3.0f}, omit_output},
sum_test_params {{tag::nChw8c, tag::nChw8c}, tag::nChw8c,
{2, 16, 3, 4}, {2.0f, 3.0f}, omit_output},
sum_test_params {{tag::nchw, tag::nchw}, tag::nChw8c, {2, 16, 2, 2},
{2.0f, 3.0f}, omit_output},
sum_test_params {{tag::nChw8c, tag::nChw8c}, tag::nchw,
{2, 16, 3, 4}, {2.0f, 3.0f}, omit_output},
sum_test_params {{tag::nchw, tag::nChw8c}, tag::nchw, {5, 8, 3, 3},
{2.0f, 3.0f}, omit_output},
sum_test_params {{tag::nchw, tag::nChw8c}, tag::nchw,
{32, 32, 13, 14}, {2.0f, 3.0f}, omit_output},
sum_test_params {{tag::nChw16c, tag::nChw8c}, tag::nChw16c,
{2, 16, 3, 3}, {2.0f, 3.0f}, omit_output});
};
static auto simple_test_cases_bf16 = [](bool omit_output) {
return ::testing::Values(
sum_test_params {{tag::nChw16c, tag::nChw16c}, tag::nChw16c,
{1, 16, 1, 1}, {2.0f, 3.0f}, omit_output},
sum_test_params {{tag::nchw, tag::nchw}, tag::nchw, {1, 16, 1, 1},
{2.0f, 3.0f}, omit_output},
sum_test_params {{tag::nchw, tag::nchw}, tag::nchw, {2, 16, 13, 7},
{2.0f, 3.0f}, omit_output},
sum_test_params {{tag::nchw, tag::nchw, tag::nchw, tag::nchw},
tag::nchw, {2, 16, 13, 7}, {2.0f, 3.0f, 4.0f, 5.0f},
omit_output},
sum_test_params {{tag::nchw, tag::nchw, tag::nchw}, tag::nchw,
{2, 16, 13, 7}, {2.0f, 3.0f, 4.0f}, omit_output},
sum_test_params {
{tag::nchw, tag::nchw, tag::nchw, tag::nchw, tag::nchw},
tag::nchw, {2, 16, 13, 7}, {2.0f, 3.0f, 4.0f, 5.0f, 6.0f},
omit_output},
sum_test_params {{tag::nchw, tag::nchw, tag::nchw}, tag::nchw,
{2, 37, 13, 7}, {2.0f, 3.0f, 4.0f}, omit_output},
sum_test_params {{tag::nchw, tag::nchw, tag::nchw}, tag::nchw,
{2, 16, 13, 7}, {2.0f, 3.0f, 4.0f}, omit_output},
sum_test_params {{tag::nChw16c, tag::nChw16c}, tag::nChw16c,
{2, 16, 13, 7}, {2.0f, 3.0f}, omit_output},
sum_test_params {{tag::nChw16c, tag::nChw16c, tag::nChw16c},
tag::nChw16c, {2, 16, 13, 7}, {2.0f, 3.0f, 4.0f},
omit_output},
sum_test_params {{tag::nChw16c, tag::nChw16c, tag::nChw16c,
tag::nChw16c, tag::nChw16c},
tag::nChw16c, {2, 16, 13, 7},
{2.0f, 3.0f, 4.0f, 5.0f, 6.0f}, omit_output},
sum_test_params {{tag::nChw16c, tag::nChw16c}, tag::nChw16c,
{2, 128, 23, 15}, {2.5f, 0.125f}, omit_output});
};
static auto special_test_cases = []() {
return ::testing::Values(
sum_test_params {{tag::nchw, tag::nChw8c}, tag::nchw, {1, 8, 4, 4},
{1.0f}, false, true, dnnl_invalid_arguments},
sum_test_params {{tag::nchw, tag::nChw8c}, tag::nchw, {2, 8, 4, 4},
{0.1f}, false, true, dnnl_invalid_arguments},
sum_test_params {{tag::any, tag::nchw}, tag::nchw, {1, 16, 1, 1},
{2.0f, 3.0f}, false, true, dnnl_invalid_arguments},
sum_test_params {{tag::nchw, tag::any}, tag::nchw, {1, 16, 1, 1},
{2.0f, 3.0f}, false, true, dnnl_invalid_arguments});
};
/* corner cases */
#define CASE_CC(itag0, itag1, otag, dims_, ef, st) \
sum_test_params { \
{tag::itag0, tag::itag1}, tag::otag, memory::dims dims_, {1.0f, 1.0f}, \
0, ef, st \
}
static auto corner_test_cases = []() {
return ::testing::Values(
CASE_CC(nchw, nChw8c, nchw, ({0, 7, 4, 4}), false, dnnl_success),
CASE_CC(nchw, nChw8c, nchw, ({1, 0, 4, 4}), false, dnnl_success),
CASE_CC(nchw, nChw8c, nchw, ({1, 8, 0, 4}), false, dnnl_success),
CASE_CC(nchw, nChw8c, nchw, ({-1, 8, 4, 4}), true,
dnnl_invalid_arguments));
};
#undef CASE_CC
#define CPU_INST_TEST_CASE(test, omit_output) \
CPU_TEST_P(test, TestsSum) {} \
CPU_INSTANTIATE_TEST_SUITE_P( \
TestSum, test, simple_test_cases(omit_output)); \
CPU_INSTANTIATE_TEST_SUITE_P(TestSumEF, test, special_test_cases());
#define INST_TEST_CASE_BF16(test, omit_output) \
CPU_TEST_P(test, TestsSum) {} \
CPU_INSTANTIATE_TEST_SUITE_P( \
TestSum, test, simple_test_cases(omit_output)); \
CPU_INSTANTIATE_TEST_SUITE_P( \
TestSumBf16, test, simple_test_cases_bf16(omit_output)); \
CPU_INSTANTIATE_TEST_SUITE_P(TestSumEF, test, special_test_cases());
#define GPU_INST_TEST_CASE(test, omit_output) \
GPU_TEST_P(test, TestsSum) {} \
GPU_INSTANTIATE_TEST_SUITE_P( \
TestSum, test, simple_test_cases(omit_output)); \
GPU_INSTANTIATE_TEST_SUITE_P(TestSumEF, test, special_test_cases());
#define INST_TEST_CASE(test, omit_output) \
CPU_INST_TEST_CASE(test, omit_output) \
GPU_INST_TEST_CASE(test, omit_output)
using sum_test_float_omit_output = sum_test_t<float, float>;
using sum_test_u8_omit_output = sum_test_t<uint8_t, int32_t>;
using sum_test_s8_omit_output = sum_test_t<int8_t, int32_t>;
using sum_test_s32_omit_output = sum_test_t<int32_t, float>;
using sum_test_f16_omit_output = sum_test_t<float16_t, float>;
using sum_test_bf16bf16_omit_output = sum_test_t<bfloat16_t, float>;
using sum_test_bf16f32_omit_output = sum_test_t<bfloat16_t, float, float>;
using sum_test_float = sum_test_t<float, float>;
using sum_test_u8 = sum_test_t<uint8_t, int32_t>;
using sum_test_s8 = sum_test_t<int8_t, int32_t>;
using sum_test_s32 = sum_test_t<int32_t, float>;
using sum_test_f16 = sum_test_t<float16_t, float>;
using sum_test_bf16bf16 = sum_test_t<bfloat16_t, float>;
using sum_test_bf16f32 = sum_test_t<bfloat16_t, float, float>;
using sum_cc_f32 = sum_test_t<float, float>;
TEST_P(sum_cc_f32, TestSumCornerCases) {}
INSTANTIATE_TEST_SUITE_P(TestSumCornerCases, sum_cc_f32, corner_test_cases());
INST_TEST_CASE(sum_test_float_omit_output, 1)
INST_TEST_CASE(sum_test_u8_omit_output, 1)
INST_TEST_CASE(sum_test_s8_omit_output, 1)
INST_TEST_CASE(sum_test_s32_omit_output, 1)
INST_TEST_CASE_BF16(sum_test_bf16bf16_omit_output, 1)
// Automatically created dst descriptor has bf16 data type so this test is not
// valid: INST_TEST_CASE(sum_test_bf16f32_omit_output, 1)
INST_TEST_CASE(sum_test_f16_omit_output, 1)
INST_TEST_CASE(sum_test_float, 0)
INST_TEST_CASE(sum_test_u8, 0)
INST_TEST_CASE(sum_test_s8, 0)
INST_TEST_CASE(sum_test_s32, 0)
INST_TEST_CASE_BF16(sum_test_bf16bf16, 0)
INST_TEST_CASE_BF16(sum_test_bf16f32, 0)
INST_TEST_CASE(sum_test_f16, 0)
#undef CPU_INST_TEST_CASE
#undef GPU_INST_TEST_CASE
} // namespace dnnl