blob: acc147342a35e2c434b90243c6f6b12e954cc788 [file] [log] [blame]
/*
* Copyright (c) 2019, Alliance for Open Media. All rights reserved
*
* This source code is subject to the terms of the BSD 2 Clause License and
* the Alliance for Open Media Patent License 1.0. If the BSD 2 Clause License
* was not distributed with this source code in the LICENSE file, you can
* obtain it at www.aomedia.org/license/software. If the Alliance for Open
* Media Patent License 1.0 was not distributed with this source code in the
* PATENTS file, you can obtain it at www.aomedia.org/license/patent.
*/
#include <cmath>
#include <cstdlib>
#include <memory>
#include <new>
#include <string>
#include <tuple>
#include "third_party/googletest/src/googletest/include/gtest/gtest.h"
#include "config/aom_config.h"
#include "config/aom_dsp_rtcd.h"
#include "config/av1_rtcd.h"
#include "aom_ports/mem.h"
#include "av1/encoder/encoder.h"
#include "av1/encoder/temporal_filter.h"
#include "test/acm_random.h"
#include "test/register_state_check.h"
#include "test/util.h"
#include "test/function_equivalence_test.h"
using libaom_test::ACMRandom;
using ::testing::Combine;
using ::testing::Values;
using ::testing::ValuesIn;
#if !CONFIG_REALTIME_ONLY
namespace {
typedef enum {
I400, // Monochrome
I420, // 4:2:0
I422, // 4:2:2
I444, // 4:4:4
} ColorFormat;
static const char *color_fmt_str[] = { "I400", "I420", "I422", "I444" };
typedef void (*TemporalFilterFunc)(
const YV12_BUFFER_CONFIG *frame_to_filter, const MACROBLOCKD *mbd,
const BLOCK_SIZE block_size, const int mb_row, const int mb_col,
const int num_planes, const double *noise_level, const MV *subblock_mvs,
const int *subblock_mses, const int q_factor, const int filter_strength,
int tf_wgt_calc_lvl, const uint8_t *pred, uint32_t *accum, uint16_t *count);
typedef libaom_test::FuncParam<TemporalFilterFunc> TemporalFilterFuncParam;
typedef std::tuple<TemporalFilterFuncParam, int> TemporalFilterWithParam;
class TemporalFilterTest
: public ::testing::TestWithParam<TemporalFilterWithParam> {
public:
virtual ~TemporalFilterTest() {}
virtual void SetUp() {
params_ = GET_PARAM(0);
tf_wgt_calc_lvl_ = GET_PARAM(1);
rnd_.Reset(ACMRandom::DeterministicSeed());
src1_ = reinterpret_cast<uint8_t *>(
aom_memalign(8, sizeof(uint8_t) * MAX_MB_PLANE * BH * BW));
src2_ = reinterpret_cast<uint8_t *>(
aom_memalign(8, sizeof(uint8_t) * MAX_MB_PLANE * BH * BW));
ASSERT_NE(src1_, nullptr);
ASSERT_NE(src2_, nullptr);
}
virtual void TearDown() {
aom_free(src1_);
aom_free(src2_);
}
void RunTest(int isRandom, int run_times, ColorFormat color_fmt);
void GenRandomData(int width, int height, int stride, int stride2,
int num_planes, int subsampling_x, int subsampling_y) {
uint8_t *src1p = src1_;
uint8_t *src2p = src2_;
for (int plane = 0; plane < num_planes; plane++) {
int plane_w = plane ? width >> subsampling_x : width;
int plane_h = plane ? height >> subsampling_y : height;
int plane_stride = plane ? stride >> subsampling_x : stride;
int plane_stride2 = plane ? stride2 >> subsampling_x : stride2;
for (int ii = 0; ii < plane_h; ii++) {
for (int jj = 0; jj < plane_w; jj++) {
src1p[jj] = rnd_.Rand8();
src2p[jj] = rnd_.Rand8();
}
src1p += plane_stride;
src2p += plane_stride2;
}
}
}
void GenExtremeData(int width, int height, int stride, int stride2,
int num_planes, int subsampling_x, int subsampling_y,
uint8_t val) {
uint8_t *src1p = src1_;
uint8_t *src2p = src2_;
for (int plane = 0; plane < num_planes; plane++) {
int plane_w = plane ? width >> subsampling_x : width;
int plane_h = plane ? height >> subsampling_y : height;
int plane_stride = plane ? stride >> subsampling_x : stride;
int plane_stride2 = plane ? stride2 >> subsampling_x : stride2;
for (int ii = 0; ii < plane_h; ii++) {
for (int jj = 0; jj < plane_w; jj++) {
src1p[jj] = val;
src2p[jj] = (255 - val);
}
src1p += plane_stride;
src2p += plane_stride2;
}
}
}
protected:
TemporalFilterFuncParam params_;
int32_t tf_wgt_calc_lvl_;
uint8_t *src1_;
uint8_t *src2_;
ACMRandom rnd_;
};
GTEST_ALLOW_UNINSTANTIATED_PARAMETERIZED_TEST(TemporalFilterTest);
void TemporalFilterTest::RunTest(int isRandom, int run_times,
ColorFormat color_fmt) {
aom_usec_timer ref_timer, test_timer;
const BLOCK_SIZE block_size = TF_BLOCK_SIZE;
static_assert(block_size == BLOCK_32X32, "");
const int width = 32;
const int height = 32;
int num_planes = MAX_MB_PLANE;
int subsampling_x = 0;
int subsampling_y = 0;
if (color_fmt == I420) {
subsampling_x = 1;
subsampling_y = 1;
} else if (color_fmt == I422) {
subsampling_x = 1;
subsampling_y = 0;
} else if (color_fmt == I400) {
num_planes = 1;
}
for (int k = 0; k < 3; k++) {
const int stride = width;
const int stride2 = width;
if (isRandom) {
GenRandomData(width, height, stride, stride2, num_planes, subsampling_x,
subsampling_y);
} else {
const int msb = 8; // Up to 8 bit input
const int limit = (1 << msb) - 1;
if (k == 0) {
GenExtremeData(width, height, stride, stride2, num_planes,
subsampling_x, subsampling_y, limit);
} else {
GenExtremeData(width, height, stride, stride2, num_planes,
subsampling_x, subsampling_y, 0);
}
}
double sigma[MAX_MB_PLANE] = { 2.1002103677063437, 2.1002103677063437,
2.1002103677063437 };
DECLARE_ALIGNED(16, unsigned int, accumulator_ref[1024 * 3]);
DECLARE_ALIGNED(16, uint16_t, count_ref[1024 * 3]);
memset(accumulator_ref, 0, 1024 * 3 * sizeof(accumulator_ref[0]));
memset(count_ref, 0, 1024 * 3 * sizeof(count_ref[0]));
DECLARE_ALIGNED(16, unsigned int, accumulator_mod[1024 * 3]);
DECLARE_ALIGNED(16, uint16_t, count_mod[1024 * 3]);
memset(accumulator_mod, 0, 1024 * 3 * sizeof(accumulator_mod[0]));
memset(count_mod, 0, 1024 * 3 * sizeof(count_mod[0]));
static_assert(width == 32 && height == 32, "");
const MV subblock_mvs[4] = { { 0, 0 }, { 5, 5 }, { 7, 8 }, { 2, 10 } };
const int subblock_mses[4] = { 15, 16, 17, 18 };
const int q_factor = 12;
const int filter_strength = 5;
const int mb_row = 0;
const int mb_col = 0;
std::unique_ptr<YV12_BUFFER_CONFIG> frame_to_filter(new (std::nothrow)
YV12_BUFFER_CONFIG);
ASSERT_NE(frame_to_filter, nullptr);
frame_to_filter->y_crop_height = 360;
frame_to_filter->y_crop_width = 540;
frame_to_filter->heights[PLANE_TYPE_Y] = height;
frame_to_filter->heights[PLANE_TYPE_UV] = height >> subsampling_y;
frame_to_filter->strides[PLANE_TYPE_Y] = stride;
frame_to_filter->strides[PLANE_TYPE_UV] = stride >> subsampling_x;
DECLARE_ALIGNED(16, uint8_t, src[1024 * 3]);
frame_to_filter->buffer_alloc = src;
frame_to_filter->flags = 0; // Only support low bit-depth test.
memcpy(src, src1_, 1024 * 3 * sizeof(uint8_t));
std::unique_ptr<MACROBLOCKD> mbd(new (std::nothrow) MACROBLOCKD);
ASSERT_NE(mbd, nullptr);
mbd->bd = 8;
for (int plane = AOM_PLANE_Y; plane < num_planes; plane++) {
int plane_height = plane ? height >> subsampling_y : height;
int plane_stride = plane ? stride >> subsampling_x : stride;
frame_to_filter->buffers[plane] =
frame_to_filter->buffer_alloc + plane * plane_stride * plane_height;
mbd->plane[plane].subsampling_x = plane ? subsampling_x : 0;
mbd->plane[plane].subsampling_y = plane ? subsampling_y : 0;
}
params_.ref_func(frame_to_filter.get(), mbd.get(), block_size, mb_row,
mb_col, num_planes, sigma, subblock_mvs, subblock_mses,
q_factor, filter_strength, tf_wgt_calc_lvl_, src2_,
accumulator_ref, count_ref);
params_.tst_func(frame_to_filter.get(), mbd.get(), block_size, mb_row,
mb_col, num_planes, sigma, subblock_mvs, subblock_mses,
q_factor, filter_strength, tf_wgt_calc_lvl_, src2_,
accumulator_mod, count_mod);
if (run_times > 1) {
aom_usec_timer_start(&ref_timer);
for (int j = 0; j < run_times; j++) {
params_.ref_func(frame_to_filter.get(), mbd.get(), block_size, mb_row,
mb_col, num_planes, sigma, subblock_mvs, subblock_mses,
q_factor, filter_strength, tf_wgt_calc_lvl_, src2_,
accumulator_ref, count_ref);
}
aom_usec_timer_mark(&ref_timer);
const int elapsed_time_c =
static_cast<int>(aom_usec_timer_elapsed(&ref_timer));
aom_usec_timer_start(&test_timer);
for (int j = 0; j < run_times; j++) {
params_.tst_func(frame_to_filter.get(), mbd.get(), block_size, mb_row,
mb_col, num_planes, sigma, subblock_mvs, subblock_mses,
q_factor, filter_strength, tf_wgt_calc_lvl_, src2_,
accumulator_mod, count_mod);
}
aom_usec_timer_mark(&test_timer);
const int elapsed_time_simd =
static_cast<int>(aom_usec_timer_elapsed(&test_timer));
printf(
"c_time=%d \t simd_time=%d \t "
"gain=%f\t width=%d\t height=%d\t color_format=%s\n",
elapsed_time_c, elapsed_time_simd,
(float)((float)elapsed_time_c / (float)elapsed_time_simd), width,
height, color_fmt_str[color_fmt]);
} else {
for (int i = 0, l = 0; i < height; i++) {
for (int j = 0; j < width; j++, l++) {
EXPECT_EQ(accumulator_ref[l], accumulator_mod[l])
<< "Error:" << k << " SSE Sum Test [" << width << "x" << height
<< "] " << color_fmt_str[color_fmt]
<< " C accumulator does not match optimized accumulator.";
EXPECT_EQ(count_ref[l], count_mod[l])
<< "Error:" << k << " SSE Sum Test [" << width << "x" << height
<< "] " << color_fmt_str[color_fmt]
<< " count does not match optimized count.";
}
}
}
}
}
TEST_P(TemporalFilterTest, OperationCheck) {
RunTest(1, 1, I400);
RunTest(1, 1, I420);
RunTest(1, 1, I422);
RunTest(1, 1, I444);
}
TEST_P(TemporalFilterTest, ExtremeValues) {
RunTest(0, 1, I400);
RunTest(0, 1, I420);
RunTest(0, 1, I422);
RunTest(0, 1, I444);
}
TEST_P(TemporalFilterTest, DISABLED_Speed) {
RunTest(1, 100000, I400);
RunTest(1, 100000, I420);
RunTest(1, 100000, I422);
RunTest(1, 100000, I444);
}
#if HAVE_AVX2
TemporalFilterFuncParam temporal_filter_test_avx2[] = { TemporalFilterFuncParam(
&av1_apply_temporal_filter_c, &av1_apply_temporal_filter_avx2) };
INSTANTIATE_TEST_SUITE_P(AVX2, TemporalFilterTest,
Combine(ValuesIn(temporal_filter_test_avx2),
Values(0, 1)));
#endif // HAVE_AVX2
#if HAVE_SSE2
TemporalFilterFuncParam temporal_filter_test_sse2[] = { TemporalFilterFuncParam(
&av1_apply_temporal_filter_c, &av1_apply_temporal_filter_sse2) };
INSTANTIATE_TEST_SUITE_P(SSE2, TemporalFilterTest,
Combine(ValuesIn(temporal_filter_test_sse2),
Values(0, 1)));
#endif // HAVE_SSE2
#if HAVE_NEON
TemporalFilterFuncParam temporal_filter_test_neon[] = { TemporalFilterFuncParam(
&av1_apply_temporal_filter_c, &av1_apply_temporal_filter_neon) };
INSTANTIATE_TEST_SUITE_P(NEON, TemporalFilterTest,
Combine(ValuesIn(temporal_filter_test_neon),
Values(0, 1)));
#endif // HAVE_NEON
typedef double (*EstimateNoiseFunc)(const uint8_t *src, int height, int width,
int stride, int edge_thresh);
typedef std::tuple<EstimateNoiseFunc, EstimateNoiseFunc, int, int>
EstimateNoiseWithParam;
class EstimateNoiseTest
: public ::testing::TestWithParam<EstimateNoiseWithParam> {
public:
virtual ~EstimateNoiseTest() {}
virtual void SetUp() {
ref_func = GET_PARAM(0);
tst_func = GET_PARAM(1);
width_ = GET_PARAM(2);
height_ = GET_PARAM(3);
rnd_.Reset(ACMRandom::DeterministicSeed());
src1_ = reinterpret_cast<uint8_t *>(
aom_memalign(8, sizeof(uint8_t) * width_ * height_));
GenRandomData(width_ * height_);
ASSERT_NE(src1_, nullptr);
}
virtual void TearDown() { aom_free(src1_); }
void RunTest(int run_times) {
stride_ = width_;
for (int i = 0; i < run_times; i++) {
double ref_out = ref_func(src1_, height_, width_, stride_,
NOISE_ESTIMATION_EDGE_THRESHOLD);
double tst_out = tst_func(src1_, height_, width_, stride_,
NOISE_ESTIMATION_EDGE_THRESHOLD);
EXPECT_EQ(ref_out, tst_out);
}
}
void SpeedTest(int run_times) {
stride_ = width_;
aom_usec_timer timer;
aom_usec_timer_start(&timer);
for (int i = 0; i < run_times; i++) {
ref_func(src1_, height_, width_, stride_,
NOISE_ESTIMATION_EDGE_THRESHOLD);
}
aom_usec_timer_mark(&timer);
const double time1 = static_cast<double>(aom_usec_timer_elapsed(&timer));
aom_usec_timer_start(&timer);
for (int i = 0; i < run_times; i++) {
tst_func(src1_, height_, width_, stride_,
NOISE_ESTIMATION_EDGE_THRESHOLD);
}
aom_usec_timer_mark(&timer);
const double time2 = static_cast<double>(aom_usec_timer_elapsed(&timer));
printf("(%3.2f)\n", time1 / time2);
}
void GenRandomData(int size) {
for (int ii = 0; ii < size; ii++) src1_[ii] = rnd_.Rand8();
}
protected:
EstimateNoiseFunc ref_func;
EstimateNoiseFunc tst_func;
ACMRandom rnd_;
uint8_t *src1_;
int width_;
int height_;
int stride_;
};
GTEST_ALLOW_UNINSTANTIATED_PARAMETERIZED_TEST(EstimateNoiseTest);
TEST_P(EstimateNoiseTest, RandomValues) { RunTest(1); }
TEST_P(EstimateNoiseTest, DISABLED_Speed) { SpeedTest(2000); }
#if HAVE_AVX2
// Width and height for which av1_estimate_noise_from_single_plane() will be
// tested.
int width[] = { 3840, 1920, 1280, 800, 640, 360, 357 };
int height[] = { 2160, 1080, 720, 600, 480, 240, 237 };
INSTANTIATE_TEST_SUITE_P(
AVX2, EstimateNoiseTest,
::testing::Combine(
::testing::Values(av1_estimate_noise_from_single_plane_c),
::testing::Values(av1_estimate_noise_from_single_plane_avx2),
::testing::ValuesIn(width), ::testing::ValuesIn(height)));
#endif // HAVE_AVX2
#if CONFIG_AV1_HIGHBITDEPTH
typedef void (*HBDTemporalFilterFunc)(
const YV12_BUFFER_CONFIG *frame_to_filter, const MACROBLOCKD *mbd,
const BLOCK_SIZE block_size, const int mb_row, const int mb_col,
const int num_planes, const double *noise_level, const MV *subblock_mvs,
const int *subblock_mses, const int q_factor, const int filter_strength,
int tf_wgt_calc_lvl, const uint8_t *pred, uint32_t *accum, uint16_t *count);
typedef libaom_test::FuncParam<HBDTemporalFilterFunc>
HBDTemporalFilterFuncParam;
typedef std::tuple<HBDTemporalFilterFuncParam, int> HBDTemporalFilterWithParam;
class HBDTemporalFilterTest
: public ::testing::TestWithParam<HBDTemporalFilterWithParam> {
public:
virtual ~HBDTemporalFilterTest() {}
virtual void SetUp() {
params_ = GET_PARAM(0);
tf_wgt_calc_lvl_ = GET_PARAM(1);
rnd_.Reset(ACMRandom::DeterministicSeed());
src1_ = reinterpret_cast<uint16_t *>(
aom_memalign(16, sizeof(uint16_t) * MAX_MB_PLANE * BH * BW));
src2_ = reinterpret_cast<uint16_t *>(
aom_memalign(16, sizeof(uint16_t) * MAX_MB_PLANE * BH * BW));
ASSERT_NE(src1_, nullptr);
ASSERT_NE(src2_, nullptr);
}
virtual void TearDown() {
aom_free(src1_);
aom_free(src2_);
}
void RunTest(int isRandom, int run_times, int bd, ColorFormat color_fmt);
void GenRandomData(int width, int height, int stride, int stride2, int bd,
int subsampling_x, int subsampling_y, int num_planes) {
uint16_t *src1p = src1_;
uint16_t *src2p = src2_;
for (int plane = AOM_PLANE_Y; plane < num_planes; plane++) {
int plane_w = plane ? width >> subsampling_x : width;
int plane_h = plane ? height >> subsampling_y : height;
int plane_stride = plane ? stride >> subsampling_x : stride;
int plane_stride2 = plane ? stride2 >> subsampling_x : stride2;
const uint16_t max_val = (1 << bd) - 1;
for (int ii = 0; ii < plane_h; ii++) {
for (int jj = 0; jj < plane_w; jj++) {
src1p[jj] = rnd_.Rand16() & max_val;
src2p[jj] = rnd_.Rand16() & max_val;
}
src1p += plane_stride;
src2p += plane_stride2;
}
}
}
void GenExtremeData(int width, int height, int stride, int stride2, int bd,
int subsampling_x, int subsampling_y, int num_planes,
uint16_t val) {
uint16_t *src1p = src1_;
uint16_t *src2p = src2_;
for (int plane = AOM_PLANE_Y; plane < num_planes; plane++) {
int plane_w = plane ? width >> subsampling_x : width;
int plane_h = plane ? height >> subsampling_y : height;
int plane_stride = plane ? stride >> subsampling_x : stride;
int plane_stride2 = plane ? stride2 >> subsampling_x : stride2;
uint16_t max_val = (1 << bd) - 1;
for (int ii = 0; ii < plane_h; ii++) {
for (int jj = 0; jj < plane_w; jj++) {
src1p[jj] = val;
src2p[jj] = (max_val - val);
}
src1p += plane_stride;
src2p += plane_stride2;
}
}
}
protected:
HBDTemporalFilterFuncParam params_;
int tf_wgt_calc_lvl_;
uint16_t *src1_;
uint16_t *src2_;
ACMRandom rnd_;
};
GTEST_ALLOW_UNINSTANTIATED_PARAMETERIZED_TEST(HBDTemporalFilterTest);
void HBDTemporalFilterTest::RunTest(int isRandom, int run_times, int BD,
ColorFormat color_fmt) {
aom_usec_timer ref_timer, test_timer;
const BLOCK_SIZE block_size = TF_BLOCK_SIZE;
static_assert(block_size == BLOCK_32X32, "");
const int width = 32;
const int height = 32;
int num_planes = MAX_MB_PLANE;
int subsampling_x = 0;
int subsampling_y = 0;
if (color_fmt == I420) {
subsampling_x = 1;
subsampling_y = 1;
} else if (color_fmt == I422) {
subsampling_x = 1;
subsampling_y = 0;
} else if (color_fmt == I400) {
num_planes = 1;
}
for (int k = 0; k < 3; k++) {
const int stride = width;
const int stride2 = width;
if (isRandom) {
GenRandomData(width, height, stride, stride2, BD, subsampling_x,
subsampling_y, num_planes);
} else {
const int msb = BD;
const uint16_t limit = (1 << msb) - 1;
if (k == 0) {
GenExtremeData(width, height, stride, stride2, BD, subsampling_x,
subsampling_y, num_planes, limit);
} else {
GenExtremeData(width, height, stride, stride2, BD, subsampling_x,
subsampling_y, num_planes, 0);
}
}
double sigma[MAX_MB_PLANE] = { 2.1002103677063437, 2.1002103677063437,
2.1002103677063437 };
DECLARE_ALIGNED(16, unsigned int, accumulator_ref[1024 * 3]);
DECLARE_ALIGNED(16, uint16_t, count_ref[1024 * 3]);
memset(accumulator_ref, 0, 1024 * 3 * sizeof(accumulator_ref[0]));
memset(count_ref, 0, 1024 * 3 * sizeof(count_ref[0]));
DECLARE_ALIGNED(16, unsigned int, accumulator_mod[1024 * 3]);
DECLARE_ALIGNED(16, uint16_t, count_mod[1024 * 3]);
memset(accumulator_mod, 0, 1024 * 3 * sizeof(accumulator_mod[0]));
memset(count_mod, 0, 1024 * 3 * sizeof(count_mod[0]));
static_assert(width == 32 && height == 32, "");
const MV subblock_mvs[4] = { { 0, 0 }, { 5, 5 }, { 7, 8 }, { 2, 10 } };
const int subblock_mses[4] = { 15, 16, 17, 18 };
const int q_factor = 12;
const int filter_strength = 5;
const int mb_row = 0;
const int mb_col = 0;
std::unique_ptr<YV12_BUFFER_CONFIG> frame_to_filter(new (std::nothrow)
YV12_BUFFER_CONFIG);
ASSERT_NE(frame_to_filter, nullptr);
frame_to_filter->y_crop_height = 360;
frame_to_filter->y_crop_width = 540;
frame_to_filter->heights[PLANE_TYPE_Y] = height;
frame_to_filter->heights[PLANE_TYPE_UV] = height >> subsampling_y;
frame_to_filter->strides[PLANE_TYPE_Y] = stride;
frame_to_filter->strides[PLANE_TYPE_UV] = stride >> subsampling_x;
DECLARE_ALIGNED(16, uint16_t, src[1024 * 3]);
frame_to_filter->buffer_alloc = CONVERT_TO_BYTEPTR(src);
frame_to_filter->flags =
YV12_FLAG_HIGHBITDEPTH; // Only Hihgbd bit-depth test.
memcpy(src, src1_, 1024 * 3 * sizeof(uint16_t));
std::unique_ptr<MACROBLOCKD> mbd(new (std::nothrow) MACROBLOCKD);
ASSERT_NE(mbd, nullptr);
mbd->bd = BD;
for (int plane = AOM_PLANE_Y; plane < num_planes; plane++) {
int plane_height = plane ? height >> subsampling_y : height;
int plane_stride = plane ? stride >> subsampling_x : stride;
frame_to_filter->buffers[plane] =
frame_to_filter->buffer_alloc + plane * plane_stride * plane_height;
mbd->plane[plane].subsampling_x = plane ? subsampling_x : 0;
mbd->plane[plane].subsampling_y = plane ? subsampling_y : 0;
}
params_.ref_func(frame_to_filter.get(), mbd.get(), block_size, mb_row,
mb_col, num_planes, sigma, subblock_mvs, subblock_mses,
q_factor, filter_strength, tf_wgt_calc_lvl_,
CONVERT_TO_BYTEPTR(src2_), accumulator_ref, count_ref);
params_.tst_func(frame_to_filter.get(), mbd.get(), block_size, mb_row,
mb_col, num_planes, sigma, subblock_mvs, subblock_mses,
q_factor, filter_strength, tf_wgt_calc_lvl_,
CONVERT_TO_BYTEPTR(src2_), accumulator_mod, count_mod);
if (run_times > 1) {
aom_usec_timer_start(&ref_timer);
for (int j = 0; j < run_times; j++) {
params_.ref_func(frame_to_filter.get(), mbd.get(), block_size, mb_row,
mb_col, num_planes, sigma, subblock_mvs, subblock_mses,
q_factor, filter_strength, tf_wgt_calc_lvl_,
CONVERT_TO_BYTEPTR(src2_), accumulator_ref, count_ref);
}
aom_usec_timer_mark(&ref_timer);
const int elapsed_time_c =
static_cast<int>(aom_usec_timer_elapsed(&ref_timer));
aom_usec_timer_start(&test_timer);
for (int j = 0; j < run_times; j++) {
params_.tst_func(frame_to_filter.get(), mbd.get(), block_size, mb_row,
mb_col, num_planes, sigma, subblock_mvs, subblock_mses,
q_factor, filter_strength, tf_wgt_calc_lvl_,
CONVERT_TO_BYTEPTR(src2_), accumulator_mod, count_mod);
}
aom_usec_timer_mark(&test_timer);
const int elapsed_time_simd =
static_cast<int>(aom_usec_timer_elapsed(&test_timer));
printf(
"c_time=%d \t simd_time=%d \t "
"gain=%f\t width=%d\t height=%d\t color_format=%s\n",
elapsed_time_c, elapsed_time_simd,
(float)((float)elapsed_time_c / (float)elapsed_time_simd), width,
height, color_fmt_str[color_fmt]);
} else {
for (int i = 0, l = 0; i < height; i++) {
for (int j = 0; j < width; j++, l++) {
EXPECT_EQ(accumulator_ref[l], accumulator_mod[l])
<< "Error:" << k << " SSE Sum Test [" << width << "x" << height
<< "] " << color_fmt_str[color_fmt]
<< " C accumulator does not match optimized accumulator.";
EXPECT_EQ(count_ref[l], count_mod[l])
<< "Error:" << k << " SSE Sum Test [" << width << "x" << height
<< "] " << color_fmt_str[color_fmt]
<< " C count does not match optimized count.";
}
}
}
}
}
TEST_P(HBDTemporalFilterTest, OperationCheck) {
RunTest(1, 1, 10, I400);
RunTest(1, 1, 10, I420);
RunTest(1, 1, 10, I422);
RunTest(1, 1, 10, I444);
}
TEST_P(HBDTemporalFilterTest, ExtremeValues) {
RunTest(0, 1, 10, I400);
RunTest(0, 1, 10, I420);
RunTest(0, 1, 10, I422);
RunTest(0, 1, 10, I444);
}
TEST_P(HBDTemporalFilterTest, DISABLED_Speed) {
RunTest(1, 100000, 10, I400);
RunTest(1, 100000, 10, I420);
RunTest(1, 100000, 10, I422);
RunTest(1, 100000, 10, I444);
}
#if HAVE_SSE2
HBDTemporalFilterFuncParam HBDtemporal_filter_test_sse2[] = {
HBDTemporalFilterFuncParam(&av1_highbd_apply_temporal_filter_c,
&av1_highbd_apply_temporal_filter_sse2)
};
INSTANTIATE_TEST_SUITE_P(SSE2, HBDTemporalFilterTest,
Combine(ValuesIn(HBDtemporal_filter_test_sse2),
Values(0, 1)));
#endif // HAVE_SSE2
#if HAVE_AVX2
HBDTemporalFilterFuncParam HBDtemporal_filter_test_avx2[] = {
HBDTemporalFilterFuncParam(&av1_highbd_apply_temporal_filter_c,
&av1_highbd_apply_temporal_filter_avx2)
};
INSTANTIATE_TEST_SUITE_P(AVX2, HBDTemporalFilterTest,
Combine(ValuesIn(HBDtemporal_filter_test_avx2),
Values(0, 1)));
#endif // HAVE_AVX2
#endif // CONFIG_AV1_HIGHBITDEPTH
} // namespace
#endif