test/av1_convolve_scale_test.cc - aom - Git at Google

 /*
  * 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/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_.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() {}

   // 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[j][i];
       convolve_params_.bck_offset = quant_dist_lookup_table[j][1 - i];
       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()));

 #if CONFIG_AV1_HIGHBITDEPTH
 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)));
 #endif  // CONFIG_AV1_HIGHBITDEPTH
 }  // namespace
	/*
	* 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/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_.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() {}

	// 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[j][i];
	convolve_params_.bck_offset = quant_dist_lookup_table[j][1 - i];
	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()));

	#if CONFIG_AV1_HIGHBITDEPTH
	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)));
	#endif // CONFIG_AV1_HIGHBITDEPTH
	} // namespace