tor-browser

tpl_model_test.cc (18617B)

---

/*
* Copyright (c) 2021, 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 <cstdlib>
#include <memory>
#include <new>
#include <vector>

#include "av1/encoder/cost.h"
#include "av1/encoder/tpl_model.h"
#include "av1/encoder/encoder.h"
#include "gtest/gtest.h"

namespace {

#if CONFIG_BITRATE_ACCURACY
constexpr double epsilon = 0.0000001;
#endif

double laplace_prob(double q_step, double b, double zero_bin_ratio,
                   int qcoeff) {
 int abs_qcoeff = abs(qcoeff);
 double z0 = fmax(exp(-zero_bin_ratio / 2 * q_step / b), TPL_EPSILON);
 if (abs_qcoeff == 0) {
   double p0 = 1 - z0;
   return p0;
 } else {
   assert(abs_qcoeff > 0);
   double z = fmax(exp(-q_step / b), TPL_EPSILON);
   double p = z0 / 2 * (1 - z) * pow(z, abs_qcoeff - 1);
   return p;
 }
}
TEST(TplModelTest, ExponentialEntropyBoundaryTest1) {
 double b = 0;
 double q_step = 1;
 double entropy = av1_exponential_entropy(q_step, b);
 EXPECT_NEAR(entropy, 0, 0.00001);
}

TEST(TplModelTest, TransformCoeffEntropyTest1) {
 // Check the consistency between av1_estimate_coeff_entropy() and
 // laplace_prob()
 double b = 1;
 double q_step = 1;
 double zero_bin_ratio = 2;
 for (int qcoeff = -256; qcoeff < 256; ++qcoeff) {
   double rate = av1_estimate_coeff_entropy(q_step, b, zero_bin_ratio, qcoeff);
   double prob = laplace_prob(q_step, b, zero_bin_ratio, qcoeff);
   double ref_rate = -log2(prob);
   EXPECT_DOUBLE_EQ(rate, ref_rate);
 }
}

TEST(TplModelTest, TransformCoeffEntropyTest2) {
 // Check the consistency between av1_estimate_coeff_entropy(), laplace_prob()
 // and av1_laplace_entropy()
 double b = 1;
 double q_step = 1;
 double zero_bin_ratio = 2;
 double est_expected_rate = 0;
 for (int qcoeff = -20; qcoeff < 20; ++qcoeff) {
   double rate = av1_estimate_coeff_entropy(q_step, b, zero_bin_ratio, qcoeff);
   double prob = laplace_prob(q_step, b, zero_bin_ratio, qcoeff);
   est_expected_rate += prob * rate;
 }
 double expected_rate = av1_laplace_entropy(q_step, b, zero_bin_ratio);
 EXPECT_NEAR(expected_rate, est_expected_rate, 0.001);
}

TEST(TplModelTest, InitTplStats1) {
 // We use heap allocation instead of stack allocation here to avoid
 // -Wstack-usage warning.
 std::unique_ptr<TplParams> tpl_data(new (std::nothrow) TplParams);
 ASSERT_NE(tpl_data, nullptr);
 av1_zero(*tpl_data);
 tpl_data->ready = 1;
 EXPECT_EQ(sizeof(tpl_data->tpl_stats_buffer),
           MAX_LENGTH_TPL_FRAME_STATS * sizeof(tpl_data->tpl_stats_buffer[0]));
 for (int i = 0; i < MAX_LENGTH_TPL_FRAME_STATS; ++i) {
   // Set it to a random non-zero number
   tpl_data->tpl_stats_buffer[i].is_valid = i + 1;
 }
 av1_init_tpl_stats(tpl_data.get());
 EXPECT_EQ(tpl_data->ready, 0);
 for (int i = 0; i < MAX_LENGTH_TPL_FRAME_STATS; ++i) {
   EXPECT_EQ(tpl_data->tpl_stats_buffer[i].is_valid, 0);
 }
}

TEST(TplModelTest, DeltaRateCostZeroFlow) {
 // When srcrf_dist equal to recrf_dist, av1_delta_rate_cost should return 0
 int64_t srcrf_dist = 256;
 int64_t recrf_dist = 256;
 int64_t delta_rate = 512;
 int pixel_num = 256;
 int64_t rate_cost =
     av1_delta_rate_cost(delta_rate, recrf_dist, srcrf_dist, pixel_num);
 EXPECT_EQ(rate_cost, 0);
}

// a reference function of av1_delta_rate_cost() with delta_rate using bit as
// basic unit
double ref_delta_rate_cost(int64_t delta_rate, double src_rec_ratio,
                          int pixel_count) {
 assert(src_rec_ratio <= 1 && src_rec_ratio >= 0);
 double bits_per_pixel = (double)delta_rate / pixel_count;
 double p = pow(2, bits_per_pixel);
 double flow_rate_per_pixel =
     sqrt(p * p / (src_rec_ratio * p * p + (1 - src_rec_ratio)));
 double rate_cost = pixel_count * log2(flow_rate_per_pixel);
 return rate_cost;
}

TEST(TplModelTest, DeltaRateCostReference) {
 const int64_t scale = TPL_DEP_COST_SCALE_LOG2 + AV1_PROB_COST_SHIFT;
 std::vector<int64_t> srcrf_dist_arr = { 256, 257, 312 };
 std::vector<int64_t> recrf_dist_arr = { 512, 288, 620 };
 std::vector<int64_t> delta_rate_arr = { 10, 278, 100 };
 for (size_t t = 0; t < srcrf_dist_arr.size(); ++t) {
   int64_t srcrf_dist = srcrf_dist_arr[t];
   int64_t recrf_dist = recrf_dist_arr[t];
   int64_t delta_rate = delta_rate_arr[t];
   int64_t scaled_delta_rate = delta_rate << scale;
   int pixel_count = 256;
   int64_t rate_cost = av1_delta_rate_cost(scaled_delta_rate, recrf_dist,
                                           srcrf_dist, pixel_count);
   rate_cost >>= scale;
   double src_rec_ratio = (double)srcrf_dist / recrf_dist;
   double ref_rate_cost =
       ref_delta_rate_cost(delta_rate, src_rec_ratio, pixel_count);
   EXPECT_NEAR((double)rate_cost, ref_rate_cost, 1);
 }
}

TEST(TplModelTest, GetOverlapAreaHasOverlap) {
 // The block a's area is [10, 17) x [18, 24).
 // The block b's area is [8, 15) x [17, 23).
 // The overlapping area between block a and block b is [10, 15) x [18, 23).
 // Therefore, the size of the area is (15 - 10) * (23 - 18) = 25.
 int row_a = 10;
 int col_a = 18;
 int row_b = 8;
 int col_b = 17;
 int height = 7;
 int width = 6;
 int overlap_area =
     av1_get_overlap_area(row_a, col_a, row_b, col_b, width, height);
 EXPECT_EQ(overlap_area, 25);
}

TEST(TplModelTest, GetOverlapAreaNoOverlap) {
 // The block a's area is [10, 14) x [18, 22).
 // The block b's area is [5, 9) x [5, 9).
 // Threre is no overlapping area between block a and block b.
 // Therefore, the return value should be zero.
 int row_a = 10;
 int col_a = 18;
 int row_b = 5;
 int col_b = 5;
 int height = 4;
 int width = 4;
 int overlap_area =
     av1_get_overlap_area(row_a, col_a, row_b, col_b, width, height);
 EXPECT_EQ(overlap_area, 0);
}

TEST(TplModelTest, GetQIndexFromQstepRatio) {
 const aom_bit_depth_t bit_depth = AOM_BITS_8;
 // When qstep_ratio is 1, the output q_index should be equal to leaf_qindex.
 double qstep_ratio = 1.0;
 for (int leaf_qindex = 1; leaf_qindex <= 255; ++leaf_qindex) {
   const int q_index =
       av1_get_q_index_from_qstep_ratio(leaf_qindex, qstep_ratio, bit_depth);
   EXPECT_EQ(q_index, leaf_qindex);
 }

 // When qstep_ratio is very low, the output q_index should be 1.
 qstep_ratio = 0.0001;
 for (int leaf_qindex = 1; leaf_qindex <= 255; ++leaf_qindex) {
   const int q_index =
       av1_get_q_index_from_qstep_ratio(leaf_qindex, qstep_ratio, bit_depth);
   EXPECT_EQ(q_index, 0);
 }
}

TEST(TplModelTest, TxfmStatsInitTest) {
 TplTxfmStats tpl_txfm_stats;
 av1_init_tpl_txfm_stats(&tpl_txfm_stats);
 EXPECT_EQ(tpl_txfm_stats.coeff_num, 256);
 EXPECT_EQ(tpl_txfm_stats.txfm_block_count, 0);
 for (int i = 0; i < tpl_txfm_stats.coeff_num; ++i) {
   EXPECT_DOUBLE_EQ(tpl_txfm_stats.abs_coeff_sum[i], 0);
 }
}

#if CONFIG_BITRATE_ACCURACY
TEST(TplModelTest, TxfmStatsAccumulateTest) {
 TplTxfmStats sub_stats;
 av1_init_tpl_txfm_stats(&sub_stats);
 sub_stats.txfm_block_count = 17;
 for (int i = 0; i < sub_stats.coeff_num; ++i) {
   sub_stats.abs_coeff_sum[i] = i;
 }

 TplTxfmStats accumulated_stats;
 av1_init_tpl_txfm_stats(&accumulated_stats);
 accumulated_stats.txfm_block_count = 13;
 for (int i = 0; i < accumulated_stats.coeff_num; ++i) {
   accumulated_stats.abs_coeff_sum[i] = 5 * i;
 }

 av1_accumulate_tpl_txfm_stats(&sub_stats, &accumulated_stats);
 EXPECT_DOUBLE_EQ(accumulated_stats.txfm_block_count, 30);
 for (int i = 0; i < accumulated_stats.coeff_num; ++i) {
   EXPECT_DOUBLE_EQ(accumulated_stats.abs_coeff_sum[i], 6 * i);
 }
}

TEST(TplModelTest, TxfmStatsRecordTest) {
 TplTxfmStats stats1;
 TplTxfmStats stats2;
 av1_init_tpl_txfm_stats(&stats1);
 av1_init_tpl_txfm_stats(&stats2);

 tran_low_t coeff[256];
 for (int i = 0; i < 256; ++i) {
   coeff[i] = i;
 }
 av1_record_tpl_txfm_block(&stats1, coeff);
 EXPECT_EQ(stats1.txfm_block_count, 1);

 // we record the same transform block twice for testing purpose
 av1_record_tpl_txfm_block(&stats2, coeff);
 av1_record_tpl_txfm_block(&stats2, coeff);
 EXPECT_EQ(stats2.txfm_block_count, 2);

 EXPECT_EQ(stats1.coeff_num, 256);
 EXPECT_EQ(stats2.coeff_num, 256);
 for (int i = 0; i < 256; ++i) {
   EXPECT_DOUBLE_EQ(stats2.abs_coeff_sum[i], 2 * stats1.abs_coeff_sum[i]);
 }
}
#endif  // CONFIG_BITRATE_ACCURACY

TEST(TplModelTest, ComputeMVDifferenceTest) {
 TplDepFrame tpl_frame_small;
 tpl_frame_small.is_valid = true;
 tpl_frame_small.mi_rows = 4;
 tpl_frame_small.mi_cols = 4;
 tpl_frame_small.stride = 1;
 uint8_t right_shift_small = 1;
 int step_small = 1 << right_shift_small;

 // Test values for motion vectors.
 int mv_vals_small[4] = { 1, 2, 3, 4 };
 int index = 0;

 // 4x4 blocks means we need to allocate a 4 size array.
 // According to av1_tpl_ptr_pos:
 // (row >> right_shift) * stride + (col >> right_shift)
 // (4 >> 1) * 1 + (4 >> 1) = 4
 TplDepStats stats_buf_small[4];
 tpl_frame_small.tpl_stats_ptr = stats_buf_small;

 for (int row = 0; row < tpl_frame_small.mi_rows; row += step_small) {
   for (int col = 0; col < tpl_frame_small.mi_cols; col += step_small) {
     TplDepStats tpl_stats;
     tpl_stats.ref_frame_index[0] = 0;
     int_mv mv;
     mv.as_mv.row = mv_vals_small[index];
     mv.as_mv.col = mv_vals_small[index];
     index++;
     tpl_stats.mv[0] = mv;
     tpl_frame_small.tpl_stats_ptr[av1_tpl_ptr_pos(
         row, col, tpl_frame_small.stride, right_shift_small)] = tpl_stats;
   }
 }

 int_mv result_mv =
     av1_compute_mv_difference(&tpl_frame_small, 1, 1, step_small,
                               tpl_frame_small.stride, right_shift_small);

 // Expect the result to be exactly equal to 1 because this is the difference
 // between neighboring motion vectors in this instance.
 EXPECT_EQ(result_mv.as_mv.row, 1);
 EXPECT_EQ(result_mv.as_mv.col, 1);
}

TEST(TplModelTest, ComputeMVBitsTest) {
 TplDepFrame tpl_frame;
 tpl_frame.is_valid = true;
 tpl_frame.mi_rows = 16;
 tpl_frame.mi_cols = 16;
 tpl_frame.stride = 24;
 uint8_t right_shift = 2;
 int step = 1 << right_shift;
 // Test values for motion vectors.
 int mv_vals_ordered[16] = { 1, 2,  3,  4,  5,  6,  7,  8,
                             9, 10, 11, 12, 13, 14, 15, 16 };
 int mv_vals[16] = { 1, 16, 2, 15, 3, 14, 4, 13, 5, 12, 6, 11, 7, 10, 8, 9 };
 int index = 0;

 // 16x16 blocks means we need to allocate a 100 size array.
 // According to av1_tpl_ptr_pos:
 // (row >> right_shift) * stride + (col >> right_shift)
 // (16 >> 2) * 24 + (16 >> 2) = 100
 TplDepStats stats_buf[100];
 tpl_frame.tpl_stats_ptr = stats_buf;

 for (int row = 0; row < tpl_frame.mi_rows; row += step) {
   for (int col = 0; col < tpl_frame.mi_cols; col += step) {
     TplDepStats tpl_stats;
     tpl_stats.ref_frame_index[0] = 0;
     int_mv mv;
     mv.as_mv.row = mv_vals_ordered[index];
     mv.as_mv.col = mv_vals_ordered[index];
     index++;
     tpl_stats.mv[0] = mv;
     tpl_frame.tpl_stats_ptr[av1_tpl_ptr_pos(row, col, tpl_frame.stride,
                                             right_shift)] = tpl_stats;
   }
 }

 double result = av1_tpl_compute_frame_mv_entropy(&tpl_frame, right_shift);

 // Expect the result to be low because the motion vectors are ordered.
 // The estimation algorithm takes this into account and reduces the cost.
 EXPECT_NEAR(result, 20, 5);

 index = 0;
 for (int row = 0; row < tpl_frame.mi_rows; row += step) {
   for (int col = 0; col < tpl_frame.mi_cols; col += step) {
     TplDepStats tpl_stats;
     tpl_stats.ref_frame_index[0] = 0;
     int_mv mv;
     mv.as_mv.row = mv_vals[index];
     mv.as_mv.col = mv_vals[index];
     index++;
     tpl_stats.mv[0] = mv;
     tpl_frame.tpl_stats_ptr[av1_tpl_ptr_pos(row, col, tpl_frame.stride,
                                             right_shift)] = tpl_stats;
   }
 }

 result = av1_tpl_compute_frame_mv_entropy(&tpl_frame, right_shift);

 // Expect the result to be higher because the vectors are not ordered.
 // Neighboring vectors will have different values, increasing the cost.
 EXPECT_NEAR(result, 70, 5);
}
#if CONFIG_BITRATE_ACCURACY

TEST(TplModelTest, VbrRcInfoSetGopBitBudget) {
 VBR_RATECTRL_INFO vbr_rc_info;
 const double total_bit_budget = 2000;
 const int show_frame_count = 8;
 const int gop_show_frame_count = 4;
 av1_vbr_rc_init(&vbr_rc_info, total_bit_budget, show_frame_count);
 av1_vbr_rc_set_gop_bit_budget(&vbr_rc_info, gop_show_frame_count);
 EXPECT_NEAR(vbr_rc_info.gop_bit_budget, 1000, epsilon);
}

void init_toy_gf_group(GF_GROUP *gf_group) {
 av1_zero(*gf_group);
 gf_group->size = 4;
 const FRAME_UPDATE_TYPE update_type[4] = { KF_UPDATE, ARF_UPDATE,
                                            INTNL_ARF_UPDATE, LF_UPDATE };
 for (int i = 0; i < gf_group->size; ++i) {
   gf_group->update_type[i] = update_type[i];
 }
}

void init_toy_vbr_rc_info(VBR_RATECTRL_INFO *vbr_rc_info, int gop_size) {
 int total_bit_budget = 2000;
 int show_frame_count = 8;
 av1_vbr_rc_init(vbr_rc_info, total_bit_budget, show_frame_count);

 for (int i = 0; i < gop_size; ++i) {
   vbr_rc_info->qstep_ratio_list[i] = 1;
 }
}

void init_toy_tpl_txfm_stats(std::vector<TplTxfmStats> *stats_list) {
 for (size_t i = 0; i < stats_list->size(); i++) {
   TplTxfmStats *txfm_stats = &stats_list->at(i);
   av1_init_tpl_txfm_stats(txfm_stats);
   txfm_stats->txfm_block_count = 8;
   for (int j = 0; j < txfm_stats->coeff_num; j++) {
     txfm_stats->abs_coeff_sum[j] = 1000 + j;
   }
   av1_tpl_txfm_stats_update_abs_coeff_mean(txfm_stats);
 }
}

/*
* Helper method to brute-force search for the closest q_index
* that achieves the specified bit budget.
*/
int find_gop_q_iterative(double bit_budget, aom_bit_depth_t bit_depth,
                        const double *update_type_scale_factors,
                        int frame_count,
                        const FRAME_UPDATE_TYPE *update_type_list,
                        const double *qstep_ratio_list,
                        const TplTxfmStats *stats_list, int *q_index_list,
                        double *estimated_bitrate_byframe) {
 int best_q = 255;
 double curr_estimate = av1_vbr_rc_info_estimate_gop_bitrate(
     best_q, bit_depth, update_type_scale_factors, frame_count,
     update_type_list, qstep_ratio_list, stats_list, q_index_list,
     estimated_bitrate_byframe);
 double min_bits_diff = fabs(curr_estimate - bit_budget);
 // Start at q = 254 because we already have an estimate for q = 255.
 for (int q = 254; q >= 0; q--) {
   curr_estimate = av1_vbr_rc_info_estimate_gop_bitrate(
       q, bit_depth, update_type_scale_factors, frame_count, update_type_list,
       qstep_ratio_list, stats_list, q_index_list, estimated_bitrate_byframe);
   double bits_diff = fabs(curr_estimate - bit_budget);
   if (bits_diff <= min_bits_diff) {
     min_bits_diff = bits_diff;
     best_q = q;
   }
 }
 return best_q;
}

TEST(TplModelTest, EstimateFrameRateTest) {
 GF_GROUP gf_group;
 init_toy_gf_group(&gf_group);

 VBR_RATECTRL_INFO vbr_rc_info;
 init_toy_vbr_rc_info(&vbr_rc_info, gf_group.size);

 std::vector<TplTxfmStats> stats_list(gf_group.size);
 init_toy_tpl_txfm_stats(&stats_list);

 std::vector<double> est_bitrate_list(gf_group.size);
 init_toy_tpl_txfm_stats(&stats_list);
 const aom_bit_depth_t bit_depth = AOM_BITS_8;

 const int q = 125;

 // Case1: all scale factors are 0
 double scale_factors[FRAME_UPDATE_TYPES] = { 0 };
 double estimate = av1_vbr_rc_info_estimate_gop_bitrate(
     q, bit_depth, scale_factors, gf_group.size, gf_group.update_type,
     vbr_rc_info.qstep_ratio_list, stats_list.data(), vbr_rc_info.q_index_list,
     est_bitrate_list.data());
 EXPECT_NEAR(estimate, 0, epsilon);

 // Case2: all scale factors are 1
 for (int i = 0; i < FRAME_UPDATE_TYPES; i++) {
   scale_factors[i] = 1;
 }
 estimate = av1_vbr_rc_info_estimate_gop_bitrate(
     q, bit_depth, scale_factors, gf_group.size, gf_group.update_type,
     vbr_rc_info.qstep_ratio_list, stats_list.data(), vbr_rc_info.q_index_list,
     est_bitrate_list.data());
 double ref_estimate = 0;
 for (int i = 0; i < gf_group.size; i++) {
   ref_estimate += est_bitrate_list[i];
 }
 EXPECT_NEAR(estimate, ref_estimate, epsilon);

 // Case3: Key frame scale factor is 0 and others are 1
 for (int i = 0; i < FRAME_UPDATE_TYPES; i++) {
   if (i == KF_UPDATE) {
     scale_factors[i] = 0;
   } else {
     scale_factors[i] = 1;
   }
 }
 estimate = av1_vbr_rc_info_estimate_gop_bitrate(
     q, bit_depth, scale_factors, gf_group.size, gf_group.update_type,
     vbr_rc_info.qstep_ratio_list, stats_list.data(), vbr_rc_info.q_index_list,
     est_bitrate_list.data());
 ref_estimate = 0;
 for (int i = 0; i < gf_group.size; i++) {
   if (gf_group.update_type[i] != KF_UPDATE) {
     ref_estimate += est_bitrate_list[i];
   }
 }
 EXPECT_NEAR(estimate, ref_estimate, epsilon);
}

TEST(TplModelTest, VbrRcInfoEstimateBaseQTest) {
 GF_GROUP gf_group;
 init_toy_gf_group(&gf_group);

 VBR_RATECTRL_INFO vbr_rc_info;
 init_toy_vbr_rc_info(&vbr_rc_info, gf_group.size);

 std::vector<TplTxfmStats> stats_list(gf_group.size);
 init_toy_tpl_txfm_stats(&stats_list);
 const aom_bit_depth_t bit_depth = AOM_BITS_8;

 // Test multiple bit budgets.
 const std::vector<double> bit_budgets = { 0,     2470,  19200,  30750,
                                           41315, 65017, DBL_MAX };

 for (double bit_budget : bit_budgets) {
   // Binary search method to find the optimal q.
   const int base_q = av1_vbr_rc_info_estimate_base_q(
       bit_budget, bit_depth, vbr_rc_info.scale_factors, gf_group.size,
       gf_group.update_type, vbr_rc_info.qstep_ratio_list, stats_list.data(),
       vbr_rc_info.q_index_list, nullptr);
   const int ref_base_q = find_gop_q_iterative(
       bit_budget, bit_depth, vbr_rc_info.scale_factors, gf_group.size,
       gf_group.update_type, vbr_rc_info.qstep_ratio_list, stats_list.data(),
       vbr_rc_info.q_index_list, nullptr);
   if (bit_budget == 0) {
     EXPECT_EQ(base_q, 255);
   } else if (bit_budget == DBL_MAX) {
     EXPECT_EQ(base_q, 0);
   }
   EXPECT_EQ(base_q, ref_base_q);
 }
}
#endif  // CONFIG_BITRATE_ACCURACY

}  // namespace