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/*
* Copyright (c) 2017, 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 <tuple>
#include <vector>
#include "third_party/googletest/src/googletest/include/gtest/gtest.h"
#include "config/av1_rtcd.h"
#include "aom_ports/aom_timer.h"
#include "test/acm_random.h"
#include "test/clear_system_state.h"
#include "test/register_state_check.h"
#include "test/util.h"
#include "av1/common/common_data.h"
namespace {
const int kTestIters = 10;
const int kPerfIters = 1000;
const int kVPad = 32;
const int kHPad = 32;
const int kXStepQn = 16;
const int kYStepQn = 20;
using libaom_test::ACMRandom;
using std::make_tuple;
using std::tuple;
enum NTaps { EIGHT_TAP, TEN_TAP, TWELVE_TAP };
int NTapsToInt(NTaps ntaps) { return 8 + static_cast<int>(ntaps) * 2; }
// A 16-bit filter with a configurable number of taps.
class TestFilter {
public:
void set(NTaps ntaps, bool backwards);
InterpFilterParams params_;
private:
std::vector<int16_t> coeffs_;
};
void TestFilter::set(NTaps ntaps, bool backwards) {
const int n = NTapsToInt(ntaps);
assert(n >= 8 && n <= 12);
// The filter has n * SUBPEL_SHIFTS proper elements and an extra 8 bogus
// elements at the end so that convolutions can read off the end safely.
coeffs_.resize(n * SUBPEL_SHIFTS + 8);
// The coefficients are pretty much arbitrary, but convolutions shouldn't
// over or underflow. For the first filter (subpels = 0), we use an
// increasing or decreasing ramp (depending on the backwards parameter). We
// don't want any zero coefficients, so we make it have an x-intercept at -1
// or n. To ensure absence of under/overflow, we normalise the area under the
// ramp to be I = 1 << FILTER_BITS (so that convolving a constant function
// gives the identity).
//
// When increasing, the function has the form:
//
// f(x) = A * (x + 1)
//
// Summing and rearranging for A gives A = 2 * I / (n * (n + 1)). If the
// filter is reversed, we have the same A but with formula
//
// g(x) = A * (n - x)
const int I = 1 << FILTER_BITS;
const float A = 2.f * I / (n * (n + 1.f));
for (int i = 0; i < n; ++i) {
coeffs_[i] = static_cast<int16_t>(A * (backwards ? (n - i) : (i + 1)));
}
// For the other filters, make them slightly different by swapping two
// columns. Filter k will have the columns (k % n) and (7 * k) % n swapped.
const size_t filter_size = sizeof(coeffs_[0] * n);
int16_t *const filter0 = &coeffs_[0];
for (int k = 1; k < SUBPEL_SHIFTS; ++k) {
int16_t *filterk = &coeffs_[k * n];
memcpy(filterk, filter0, filter_size);
const int idx0 = k % n;
const int idx1 = (7 * k) % n;
const int16_t tmp = filterk[idx0];
filterk[idx0] = filterk[idx1];
filterk[idx1] = tmp;
}
// Finally, write some rubbish at the end to make sure we don't use it.
for (int i = 0; i < 8; ++i) coeffs_[n * SUBPEL_SHIFTS + i] = 123 + i;
// Fill in params
params_.filter_ptr = &coeffs_[0];
params_.taps = n;
// These are ignored by the functions being tested. Set them to whatever.
params_.subpel_shifts = SUBPEL_SHIFTS;
params_.interp_filter = EIGHTTAP_REGULAR;
}
template <typename SrcPixel>
class TestImage {
public:
TestImage(int w, int h, int bd) : w_(w), h_(h), bd_(bd) {
assert(bd < 16);
assert(bd <= 8 * static_cast<int>(sizeof(SrcPixel)));
// Pad width by 2*kHPad and then round up to the next multiple of 16
// to get src_stride_. Add another 16 for dst_stride_ (to make sure
// something goes wrong if we use the wrong one)
src_stride_ = (w_ + 2 * kHPad + 15) & ~15;
dst_stride_ = src_stride_ + 16;
// Allocate image data
src_data_.resize(2 * src_block_size());
dst_data_.resize(2 * dst_block_size());
dst_16_data_.resize(2 * dst_block_size());
}
void Initialize(ACMRandom *rnd);
void Check() const;
int src_stride() const { return src_stride_; }
int dst_stride() const { return dst_stride_; }
int src_block_size() const { return (h_ + 2 * kVPad) * src_stride(); }
int dst_block_size() const { return (h_ + 2 * kVPad) * dst_stride(); }
const SrcPixel *GetSrcData(bool ref, bool borders) const {
const SrcPixel *block = &src_data_[ref ? 0 : src_block_size()];
return borders ? block : block + kHPad + src_stride_ * kVPad;
}
SrcPixel *GetDstData(bool ref, bool borders) {
SrcPixel *block = &dst_data_[ref ? 0 : dst_block_size()];
return borders ? block : block + kHPad + dst_stride_ * kVPad;
}
CONV_BUF_TYPE *GetDst16Data(bool ref, bool borders) {
CONV_BUF_TYPE *block = &dst_16_data_[ref ? 0 : dst_block_size()];
return borders ? block : block + kHPad + dst_stride_ * kVPad;
}
private:
int w_, h_, bd_;
int src_stride_, dst_stride_;
std::vector<SrcPixel> src_data_;
std::vector<SrcPixel> dst_data_;
std::vector<CONV_BUF_TYPE> dst_16_data_;
};
template <typename Pixel>
void FillEdge(ACMRandom *rnd, int num_pixels, int bd, bool trash, Pixel *data) {
if (!trash) {
memset(data, 0, sizeof(*data) * num_pixels);
return;
}
const Pixel mask = (1 << bd) - 1;
for (int i = 0; i < num_pixels; ++i) data[i] = rnd->Rand16() & mask;
}
template <typename Pixel>
void PrepBuffers(ACMRandom *rnd, int w, int h, int stride, int bd,
bool trash_edges, Pixel *data) {
assert(rnd);
const Pixel mask = (1 << bd) - 1;
// Fill in the first buffer with random data
// Top border
FillEdge(rnd, stride * kVPad, bd, trash_edges, data);
for (int r = 0; r < h; ++r) {
Pixel *row_data = data + (kVPad + r) * stride;
// Left border, contents, right border
FillEdge(rnd, kHPad, bd, trash_edges, row_data);
for (int c = 0; c < w; ++c) row_data[kHPad + c] = rnd->Rand16() & mask;
FillEdge(rnd, kHPad, bd, trash_edges, row_data + kHPad + w);
}
// Bottom border
FillEdge(rnd, stride * kVPad, bd, trash_edges, data + stride * (kVPad + h));
const int bpp = sizeof(*data);
const int block_elts = stride * (h + 2 * kVPad);
const int block_size = bpp * block_elts;
// Now copy that to the second buffer
memcpy(data + block_elts, data, block_size);
}
template <typename SrcPixel>
void TestImage<SrcPixel>::Initialize(ACMRandom *rnd) {
PrepBuffers(rnd, w_, h_, src_stride_, bd_, false, &src_data_[0]);
PrepBuffers(rnd, w_, h_, dst_stride_, bd_, true, &dst_data_[0]);
PrepBuffers(rnd, w_, h_, dst_stride_, bd_, true, &dst_16_data_[0]);
}
template <typename SrcPixel>
void TestImage<SrcPixel>::Check() const {
// If memcmp returns 0, there's nothing to do.
const int num_pixels = dst_block_size();
const SrcPixel *ref_dst = &dst_data_[0];
const SrcPixel *tst_dst = &dst_data_[num_pixels];
const CONV_BUF_TYPE *ref_16_dst = &dst_16_data_[0];
const CONV_BUF_TYPE *tst_16_dst = &dst_16_data_[num_pixels];
if (0 == memcmp(ref_dst, tst_dst, sizeof(*ref_dst) * num_pixels)) {
if (0 == memcmp(ref_16_dst, tst_16_dst, sizeof(*ref_16_dst) * num_pixels))
return;
}
// Otherwise, iterate through the buffer looking for differences (including
// the edges)
const int stride = dst_stride_;
for (int r = 0; r < h_ + 2 * kVPad; ++r) {
for (int c = 0; c < w_ + 2 * kHPad; ++c) {
const int32_t ref_value = ref_dst[r * stride + c];
const int32_t tst_value = tst_dst[r * stride + c];
EXPECT_EQ(tst_value, ref_value)
<< "Error at row: " << (r - kVPad) << ", col: " << (c - kHPad);
}
}
for (int r = 0; r < h_ + 2 * kVPad; ++r) {
for (int c = 0; c < w_ + 2 * kHPad; ++c) {
const int32_t ref_value = ref_16_dst[r * stride + c];
const int32_t tst_value = tst_16_dst[r * stride + c];
EXPECT_EQ(tst_value, ref_value)
<< "Error in 16 bit buffer "
<< "Error at row: " << (r - kVPad) << ", col: " << (c - kHPad);
}
}
}
typedef tuple<int, int> BlockDimension;
struct BaseParams {
BaseParams(BlockDimension dims, NTaps ntaps_x, NTaps ntaps_y, bool avg)
: dims(dims), ntaps_x(ntaps_x), ntaps_y(ntaps_y), avg(avg) {}
BlockDimension dims;
NTaps ntaps_x, ntaps_y;
bool avg;
};
template <typename SrcPixel>
class ConvolveScaleTestBase : public ::testing::Test {
public:
ConvolveScaleTestBase() : image_(NULL) {}
virtual ~ConvolveScaleTestBase() { delete image_; }
virtual void TearDown() { libaom_test::ClearSystemState(); }
// Implemented by subclasses (SetUp depends on the parameters passed
// in and RunOne depends on the function to be tested. These can't
// be templated for low/high bit depths because they have different
// numbers of parameters)
virtual void SetUp() = 0;
virtual void RunOne(bool ref) = 0;
protected:
void SetParams(const BaseParams &params, int bd) {
width_ = std::get<0>(params.dims);
height_ = std::get<1>(params.dims);
ntaps_x_ = params.ntaps_x;
ntaps_y_ = params.ntaps_y;
bd_ = bd;
avg_ = params.avg;
filter_x_.set(ntaps_x_, false);
filter_y_.set(ntaps_y_, true);
convolve_params_ =
get_conv_params_no_round(avg_ != false, 0, NULL, 0, 1, bd);
delete image_;
image_ = new TestImage<SrcPixel>(width_, height_, bd_);
}
void SetConvParamOffset(int i, int j, int is_compound, int do_average,
int use_dist_wtd_comp_avg) {
if (i == -1 && j == -1) {
convolve_params_.use_dist_wtd_comp_avg = use_dist_wtd_comp_avg;
convolve_params_.is_compound = is_compound;
convolve_params_.do_average = do_average;
} else {
convolve_params_.use_dist_wtd_comp_avg = use_dist_wtd_comp_avg;
convolve_params_.fwd_offset = quant_dist_lookup_table[i][j][0];
convolve_params_.bck_offset = quant_dist_lookup_table[i][j][1];
convolve_params_.is_compound = is_compound;
convolve_params_.do_average = do_average;
}
}
void Run() {
ACMRandom rnd(ACMRandom::DeterministicSeed());
for (int i = 0; i < kTestIters; ++i) {
int is_compound = 0;
SetConvParamOffset(-1, -1, is_compound, 0, 0);
Prep(&rnd);
RunOne(true);
RunOne(false);
image_->Check();
is_compound = 1;
for (int do_average = 0; do_average < 2; do_average++) {
for (int use_dist_wtd_comp_avg = 0; use_dist_wtd_comp_avg < 2;
use_dist_wtd_comp_avg++) {
for (int j = 0; j < 2; ++j) {
for (int k = 0; k < 4; ++k) {
SetConvParamOffset(j, k, is_compound, do_average,
use_dist_wtd_comp_avg);
Prep(&rnd);
RunOne(true);
RunOne(false);
image_->Check();
}
}
}
}
}
}
void SpeedTest() {
ACMRandom rnd(ACMRandom::DeterministicSeed());
Prep(&rnd);
aom_usec_timer ref_timer;
aom_usec_timer_start(&ref_timer);
for (int i = 0; i < kPerfIters; ++i) RunOne(true);
aom_usec_timer_mark(&ref_timer);
const int64_t ref_time = aom_usec_timer_elapsed(&ref_timer);
aom_usec_timer tst_timer;
aom_usec_timer_start(&tst_timer);
for (int i = 0; i < kPerfIters; ++i) RunOne(false);
aom_usec_timer_mark(&tst_timer);
const int64_t tst_time = aom_usec_timer_elapsed(&tst_timer);
std::cout << "[ ] C time = " << ref_time / 1000
<< " ms, SIMD time = " << tst_time / 1000 << " ms\n";
EXPECT_GT(ref_time, tst_time)
<< "Error: CDEFSpeedTest, SIMD slower than C.\n"
<< "C time: " << ref_time << " us\n"
<< "SIMD time: " << tst_time << " us\n";
}
static int RandomSubpel(ACMRandom *rnd) {
const uint8_t subpel_mode = rnd->Rand8();
if ((subpel_mode & 7) == 0) {
return 0;
} else if ((subpel_mode & 7) == 1) {
return SCALE_SUBPEL_SHIFTS - 1;
} else {
return 1 + rnd->PseudoUniform(SCALE_SUBPEL_SHIFTS - 2);
}
}
void Prep(ACMRandom *rnd) {
assert(rnd);
// Choose subpel_x_ and subpel_y_. They should be less than
// SCALE_SUBPEL_SHIFTS; we also want to add extra weight to "interesting"
// values: 0 and SCALE_SUBPEL_SHIFTS - 1
subpel_x_ = RandomSubpel(rnd);
subpel_y_ = RandomSubpel(rnd);
image_->Initialize(rnd);
}
int width_, height_, bd_;
NTaps ntaps_x_, ntaps_y_;
bool avg_;
int subpel_x_, subpel_y_;
TestFilter filter_x_, filter_y_;
TestImage<SrcPixel> *image_;
ConvolveParams convolve_params_;
};
typedef tuple<int, int> BlockDimension;
typedef void (*LowbdConvolveFunc)(const uint8_t *src, int src_stride,
uint8_t *dst, int dst_stride, int w, int h,
const InterpFilterParams *filter_params_x,
const InterpFilterParams *filter_params_y,
const int subpel_x_qn, const int x_step_qn,
const int subpel_y_qn, const int y_step_qn,
ConvolveParams *conv_params);
// Test parameter list:
// <tst_fun, dims, ntaps_x, ntaps_y, avg>
typedef tuple<LowbdConvolveFunc, BlockDimension, NTaps, NTaps, bool>
LowBDParams;
class LowBDConvolveScaleTest
: public ConvolveScaleTestBase<uint8_t>,
public ::testing::WithParamInterface<LowBDParams> {
public:
virtual ~LowBDConvolveScaleTest() {}
void SetUp() {
tst_fun_ = GET_PARAM(0);
const BlockDimension &block = GET_PARAM(1);
const NTaps ntaps_x = GET_PARAM(2);
const NTaps ntaps_y = GET_PARAM(3);
const int bd = 8;
const bool avg = GET_PARAM(4);
SetParams(BaseParams(block, ntaps_x, ntaps_y, avg), bd);
}
void RunOne(bool ref) {
const uint8_t *src = image_->GetSrcData(ref, false);
uint8_t *dst = image_->GetDstData(ref, false);
convolve_params_.dst = image_->GetDst16Data(ref, false);
const int src_stride = image_->src_stride();
const int dst_stride = image_->dst_stride();
if (ref) {
av1_convolve_2d_scale_c(src, src_stride, dst, dst_stride, width_, height_,
&filter_x_.params_, &filter_y_.params_, subpel_x_,
kXStepQn, subpel_y_, kYStepQn, &convolve_params_);
} else {
tst_fun_(src, src_stride, dst, dst_stride, width_, height_,
&filter_x_.params_, &filter_y_.params_, subpel_x_, kXStepQn,
subpel_y_, kYStepQn, &convolve_params_);
}
}
private:
LowbdConvolveFunc tst_fun_;
};
const BlockDimension kBlockDim[] = {
make_tuple(2, 2), make_tuple(2, 4), make_tuple(4, 4),
make_tuple(4, 8), make_tuple(8, 4), make_tuple(8, 8),
make_tuple(8, 16), make_tuple(16, 8), make_tuple(16, 16),
make_tuple(16, 32), make_tuple(32, 16), make_tuple(32, 32),
make_tuple(32, 64), make_tuple(64, 32), make_tuple(64, 64),
make_tuple(64, 128), make_tuple(128, 64), make_tuple(128, 128),
};
const NTaps kNTaps[] = { EIGHT_TAP };
TEST_P(LowBDConvolveScaleTest, Check) { Run(); }
TEST_P(LowBDConvolveScaleTest, DISABLED_Speed) { SpeedTest(); }
INSTANTIATE_TEST_SUITE_P(
SSE4_1, LowBDConvolveScaleTest,
::testing::Combine(::testing::Values(av1_convolve_2d_scale_sse4_1),
::testing::ValuesIn(kBlockDim),
::testing::ValuesIn(kNTaps), ::testing::ValuesIn(kNTaps),
::testing::Bool()));
typedef void (*HighbdConvolveFunc)(const uint16_t *src, int src_stride,
uint16_t *dst, int dst_stride, int w, int h,
const InterpFilterParams *filter_params_x,
const InterpFilterParams *filter_params_y,
const int subpel_x_qn, const int x_step_qn,
const int subpel_y_qn, const int y_step_qn,
ConvolveParams *conv_params, int bd);
// Test parameter list:
// <tst_fun, dims, ntaps_x, ntaps_y, avg, bd>
typedef tuple<HighbdConvolveFunc, BlockDimension, NTaps, NTaps, bool, int>
HighBDParams;
class HighBDConvolveScaleTest
: public ConvolveScaleTestBase<uint16_t>,
public ::testing::WithParamInterface<HighBDParams> {
public:
virtual ~HighBDConvolveScaleTest() {}
void SetUp() {
tst_fun_ = GET_PARAM(0);
const BlockDimension &block = GET_PARAM(1);
const NTaps ntaps_x = GET_PARAM(2);
const NTaps ntaps_y = GET_PARAM(3);
const bool avg = GET_PARAM(4);
const int bd = GET_PARAM(5);
SetParams(BaseParams(block, ntaps_x, ntaps_y, avg), bd);
}
void RunOne(bool ref) {
const uint16_t *src = image_->GetSrcData(ref, false);
uint16_t *dst = image_->GetDstData(ref, false);
convolve_params_.dst = image_->GetDst16Data(ref, false);
const int src_stride = image_->src_stride();
const int dst_stride = image_->dst_stride();
if (ref) {
av1_highbd_convolve_2d_scale_c(
src, src_stride, dst, dst_stride, width_, height_, &filter_x_.params_,
&filter_y_.params_, subpel_x_, kXStepQn, subpel_y_, kYStepQn,
&convolve_params_, bd_);
} else {
tst_fun_(src, src_stride, dst, dst_stride, width_, height_,
&filter_x_.params_, &filter_y_.params_, subpel_x_, kXStepQn,
subpel_y_, kYStepQn, &convolve_params_, bd_);
}
}
private:
HighbdConvolveFunc tst_fun_;
};
const int kBDs[] = { 8, 10, 12 };
TEST_P(HighBDConvolveScaleTest, Check) { Run(); }
TEST_P(HighBDConvolveScaleTest, DISABLED_Speed) { SpeedTest(); }
INSTANTIATE_TEST_SUITE_P(
SSE4_1, HighBDConvolveScaleTest,
::testing::Combine(::testing::Values(av1_highbd_convolve_2d_scale_sse4_1),
::testing::ValuesIn(kBlockDim),
::testing::ValuesIn(kNTaps), ::testing::ValuesIn(kNTaps),
::testing::Bool(), ::testing::ValuesIn(kBDs)));
} // namespace