| /* |
| * 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 |