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author | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-04-07 09:22:09 +0000 |
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committer | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-04-07 09:22:09 +0000 |
commit | 43a97878ce14b72f0981164f87f2e35e14151312 (patch) | |
tree | 620249daf56c0258faa40cbdcf9cfba06de2a846 /third_party/aom/test/av1_convolve_scale_test.cc | |
parent | Initial commit. (diff) | |
download | firefox-43a97878ce14b72f0981164f87f2e35e14151312.tar.xz firefox-43a97878ce14b72f0981164f87f2e35e14151312.zip |
Adding upstream version 110.0.1.upstream/110.0.1upstream
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
Diffstat (limited to 'third_party/aom/test/av1_convolve_scale_test.cc')
-rw-r--r-- | third_party/aom/test/av1_convolve_scale_test.cc | 529 |
1 files changed, 529 insertions, 0 deletions
diff --git a/third_party/aom/test/av1_convolve_scale_test.cc b/third_party/aom/test/av1_convolve_scale_test.cc new file mode 100644 index 0000000000..3b1698eeb4 --- /dev/null +++ b/third_party/aom/test/av1_convolve_scale_test.cc @@ -0,0 +1,529 @@ +/* + * 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 <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 ::testing::make_tuple; +using ::testing::tuple; +using libaom_test::ACMRandom; + +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 ¶ms, int bd) { + width_ = ::testing::get<0>(params.dims); + height_ = ::testing::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_jnt_comp_avg) { + if (i == -1 && j == -1) { + convolve_params_.use_jnt_comp_avg = use_jnt_comp_avg; + convolve_params_.is_compound = is_compound; + convolve_params_.do_average = do_average; + } else { + convolve_params_.use_jnt_comp_avg = use_jnt_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_jnt_comp_avg = 0; use_jnt_comp_avg < 2; + use_jnt_comp_avg++) { + for (int j = 0; j < 2; ++j) { + for (int k = 0; k < 4; ++k) { + SetConvParamOffset(j, k, is_compound, do_average, + use_jnt_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_CASE_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_CASE_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 |