1 /*
2 * Copyright (c) 2021, Alliance for Open Media. All rights reserved
3 *
4 * This source code is subject to the terms of the BSD 2 Clause License and
5 * the Alliance for Open Media Patent License 1.0. If the BSD 2 Clause License
6 * was not distributed with this source code in the LICENSE file, you can
7 * obtain it at www.aomedia.org/license/software. If the Alliance for Open
8 * Media Patent License 1.0 was not distributed with this source code in the
9 * PATENTS file, you can obtain it at www.aomedia.org/license/patent.
10 */
11
12 #include <cstdlib>
13 #include <memory>
14 #include <new>
15 #include <vector>
16
17 #include "av1/encoder/cost.h"
18 #include "av1/encoder/tpl_model.h"
19 #include "av1/encoder/encoder.h"
20 #include "third_party/googletest/src/googletest/include/gtest/gtest.h"
21
22 namespace {
23
24 #if CONFIG_BITRATE_ACCURACY
25 constexpr double epsilon = 0.0000001;
26 #endif
27
laplace_prob(double q_step,double b,double zero_bin_ratio,int qcoeff)28 double laplace_prob(double q_step, double b, double zero_bin_ratio,
29 int qcoeff) {
30 int abs_qcoeff = abs(qcoeff);
31 double z0 = fmax(exp(-zero_bin_ratio / 2 * q_step / b), TPL_EPSILON);
32 if (abs_qcoeff == 0) {
33 double p0 = 1 - z0;
34 return p0;
35 } else {
36 assert(abs_qcoeff > 0);
37 double z = fmax(exp(-q_step / b), TPL_EPSILON);
38 double p = z0 / 2 * (1 - z) * pow(z, abs_qcoeff - 1);
39 return p;
40 }
41 }
TEST(TplModelTest,ExponentialEntropyBoundaryTest1)42 TEST(TplModelTest, ExponentialEntropyBoundaryTest1) {
43 double b = 0;
44 double q_step = 1;
45 double entropy = av1_exponential_entropy(q_step, b);
46 EXPECT_NEAR(entropy, 0, 0.00001);
47 }
48
TEST(TplModelTest,TransformCoeffEntropyTest1)49 TEST(TplModelTest, TransformCoeffEntropyTest1) {
50 // Check the consistency between av1_estimate_coeff_entropy() and
51 // laplace_prob()
52 double b = 1;
53 double q_step = 1;
54 double zero_bin_ratio = 2;
55 for (int qcoeff = -256; qcoeff < 256; ++qcoeff) {
56 double rate = av1_estimate_coeff_entropy(q_step, b, zero_bin_ratio, qcoeff);
57 double prob = laplace_prob(q_step, b, zero_bin_ratio, qcoeff);
58 double ref_rate = -log2(prob);
59 EXPECT_DOUBLE_EQ(rate, ref_rate);
60 }
61 }
62
TEST(TplModelTest,TransformCoeffEntropyTest2)63 TEST(TplModelTest, TransformCoeffEntropyTest2) {
64 // Check the consistency between av1_estimate_coeff_entropy(), laplace_prob()
65 // and av1_laplace_entropy()
66 double b = 1;
67 double q_step = 1;
68 double zero_bin_ratio = 2;
69 double est_expected_rate = 0;
70 for (int qcoeff = -20; qcoeff < 20; ++qcoeff) {
71 double rate = av1_estimate_coeff_entropy(q_step, b, zero_bin_ratio, qcoeff);
72 double prob = laplace_prob(q_step, b, zero_bin_ratio, qcoeff);
73 est_expected_rate += prob * rate;
74 }
75 double expected_rate = av1_laplace_entropy(q_step, b, zero_bin_ratio);
76 EXPECT_NEAR(expected_rate, est_expected_rate, 0.001);
77 }
78
TEST(TplModelTest,InitTplStats1)79 TEST(TplModelTest, InitTplStats1) {
80 // We use heap allocation instead of stack allocation here to avoid
81 // -Wstack-usage warning.
82 std::unique_ptr<TplParams> tpl_data(new (std::nothrow) TplParams);
83 ASSERT_NE(tpl_data, nullptr);
84 av1_zero(*tpl_data);
85 tpl_data->ready = 1;
86 EXPECT_EQ(sizeof(tpl_data->tpl_stats_buffer),
87 MAX_LENGTH_TPL_FRAME_STATS * sizeof(tpl_data->tpl_stats_buffer[0]));
88 for (int i = 0; i < MAX_LENGTH_TPL_FRAME_STATS; ++i) {
89 // Set it to a random non-zero number
90 tpl_data->tpl_stats_buffer[i].is_valid = i + 1;
91 }
92 av1_init_tpl_stats(tpl_data.get());
93 EXPECT_EQ(tpl_data->ready, 0);
94 for (int i = 0; i < MAX_LENGTH_TPL_FRAME_STATS; ++i) {
95 EXPECT_EQ(tpl_data->tpl_stats_buffer[i].is_valid, 0);
96 }
97 }
98
TEST(TplModelTest,DeltaRateCostZeroFlow)99 TEST(TplModelTest, DeltaRateCostZeroFlow) {
100 // When srcrf_dist equal to recrf_dist, av1_delta_rate_cost should return 0
101 int64_t srcrf_dist = 256;
102 int64_t recrf_dist = 256;
103 int64_t delta_rate = 512;
104 int pixel_num = 256;
105 int64_t rate_cost =
106 av1_delta_rate_cost(delta_rate, recrf_dist, srcrf_dist, pixel_num);
107 EXPECT_EQ(rate_cost, 0);
108 }
109
110 // a reference function of av1_delta_rate_cost() with delta_rate using bit as
111 // basic unit
ref_delta_rate_cost(int64_t delta_rate,double src_rec_ratio,int pixel_count)112 double ref_delta_rate_cost(int64_t delta_rate, double src_rec_ratio,
113 int pixel_count) {
114 assert(src_rec_ratio <= 1 && src_rec_ratio >= 0);
115 double bits_per_pixel = (double)delta_rate / pixel_count;
116 double p = pow(2, bits_per_pixel);
117 double flow_rate_per_pixel =
118 sqrt(p * p / (src_rec_ratio * p * p + (1 - src_rec_ratio)));
119 double rate_cost = pixel_count * log2(flow_rate_per_pixel);
120 return rate_cost;
121 }
122
TEST(TplModelTest,DeltaRateCostReference)123 TEST(TplModelTest, DeltaRateCostReference) {
124 const int64_t scale = TPL_DEP_COST_SCALE_LOG2 + AV1_PROB_COST_SHIFT;
125 std::vector<int64_t> srcrf_dist_arr = { 256, 257, 312 };
126 std::vector<int64_t> recrf_dist_arr = { 512, 288, 620 };
127 std::vector<int64_t> delta_rate_arr = { 10, 278, 100 };
128 for (size_t t = 0; t < srcrf_dist_arr.size(); ++t) {
129 int64_t srcrf_dist = srcrf_dist_arr[t];
130 int64_t recrf_dist = recrf_dist_arr[t];
131 int64_t delta_rate = delta_rate_arr[t];
132 int64_t scaled_delta_rate = delta_rate << scale;
133 int pixel_count = 256;
134 int64_t rate_cost = av1_delta_rate_cost(scaled_delta_rate, recrf_dist,
135 srcrf_dist, pixel_count);
136 rate_cost >>= scale;
137 double src_rec_ratio = (double)srcrf_dist / recrf_dist;
138 double ref_rate_cost =
139 ref_delta_rate_cost(delta_rate, src_rec_ratio, pixel_count);
140 EXPECT_NEAR((double)rate_cost, ref_rate_cost, 1);
141 }
142 }
143
TEST(TplModelTest,GetOverlapAreaHasOverlap)144 TEST(TplModelTest, GetOverlapAreaHasOverlap) {
145 // The block a's area is [10, 17) x [18, 24).
146 // The block b's area is [8, 15) x [17, 23).
147 // The overlapping area between block a and block b is [10, 15) x [18, 23).
148 // Therefore, the size of the area is (15 - 10) * (23 - 18) = 25.
149 int row_a = 10;
150 int col_a = 18;
151 int row_b = 8;
152 int col_b = 17;
153 int height = 7;
154 int width = 6;
155 int overlap_area =
156 av1_get_overlap_area(row_a, col_a, row_b, col_b, width, height);
157 EXPECT_EQ(overlap_area, 25);
158 }
159
TEST(TplModelTest,GetOverlapAreaNoOverlap)160 TEST(TplModelTest, GetOverlapAreaNoOverlap) {
161 // The block a's area is [10, 14) x [18, 22).
162 // The block b's area is [5, 9) x [5, 9).
163 // Threre is no overlapping area between block a and block b.
164 // Therefore, the return value should be zero.
165 int row_a = 10;
166 int col_a = 18;
167 int row_b = 5;
168 int col_b = 5;
169 int height = 4;
170 int width = 4;
171 int overlap_area =
172 av1_get_overlap_area(row_a, col_a, row_b, col_b, width, height);
173 EXPECT_EQ(overlap_area, 0);
174 }
175
TEST(TplModelTest,GetQIndexFromQstepRatio)176 TEST(TplModelTest, GetQIndexFromQstepRatio) {
177 const aom_bit_depth_t bit_depth = AOM_BITS_8;
178 // When qstep_ratio is 1, the output q_index should be equal to leaf_qindex.
179 double qstep_ratio = 1.0;
180 for (int leaf_qindex = 1; leaf_qindex <= 255; ++leaf_qindex) {
181 const int q_index =
182 av1_get_q_index_from_qstep_ratio(leaf_qindex, qstep_ratio, bit_depth);
183 EXPECT_EQ(q_index, leaf_qindex);
184 }
185
186 // When qstep_ratio is very low, the output q_index should be 1.
187 qstep_ratio = 0.0001;
188 for (int leaf_qindex = 1; leaf_qindex <= 255; ++leaf_qindex) {
189 const int q_index =
190 av1_get_q_index_from_qstep_ratio(leaf_qindex, qstep_ratio, bit_depth);
191 EXPECT_EQ(q_index, 0);
192 }
193 }
194
TEST(TplModelTest,TxfmStatsInitTest)195 TEST(TplModelTest, TxfmStatsInitTest) {
196 TplTxfmStats tpl_txfm_stats;
197 av1_init_tpl_txfm_stats(&tpl_txfm_stats);
198 EXPECT_EQ(tpl_txfm_stats.coeff_num, 256);
199 EXPECT_EQ(tpl_txfm_stats.txfm_block_count, 0);
200 for (int i = 0; i < tpl_txfm_stats.coeff_num; ++i) {
201 EXPECT_DOUBLE_EQ(tpl_txfm_stats.abs_coeff_sum[i], 0);
202 }
203 }
204
TEST(TplModelTest,TxfmStatsAccumulateTest)205 TEST(TplModelTest, TxfmStatsAccumulateTest) {
206 TplTxfmStats sub_stats;
207 av1_init_tpl_txfm_stats(&sub_stats);
208 sub_stats.txfm_block_count = 17;
209 for (int i = 0; i < sub_stats.coeff_num; ++i) {
210 sub_stats.abs_coeff_sum[i] = i;
211 }
212
213 TplTxfmStats accumulated_stats;
214 av1_init_tpl_txfm_stats(&accumulated_stats);
215 accumulated_stats.txfm_block_count = 13;
216 for (int i = 0; i < accumulated_stats.coeff_num; ++i) {
217 accumulated_stats.abs_coeff_sum[i] = 5 * i;
218 }
219
220 av1_accumulate_tpl_txfm_stats(&sub_stats, &accumulated_stats);
221 EXPECT_DOUBLE_EQ(accumulated_stats.txfm_block_count, 30);
222 for (int i = 0; i < accumulated_stats.coeff_num; ++i) {
223 EXPECT_DOUBLE_EQ(accumulated_stats.abs_coeff_sum[i], 6 * i);
224 }
225 }
226
TEST(TplModelTest,TxfmStatsRecordTest)227 TEST(TplModelTest, TxfmStatsRecordTest) {
228 TplTxfmStats stats1;
229 TplTxfmStats stats2;
230 av1_init_tpl_txfm_stats(&stats1);
231 av1_init_tpl_txfm_stats(&stats2);
232
233 tran_low_t coeff[256];
234 for (int i = 0; i < 256; ++i) {
235 coeff[i] = i;
236 }
237 av1_record_tpl_txfm_block(&stats1, coeff);
238 EXPECT_EQ(stats1.txfm_block_count, 1);
239
240 // we record the same transform block twice for testing purpose
241 av1_record_tpl_txfm_block(&stats2, coeff);
242 av1_record_tpl_txfm_block(&stats2, coeff);
243 EXPECT_EQ(stats2.txfm_block_count, 2);
244
245 EXPECT_EQ(stats1.coeff_num, 256);
246 EXPECT_EQ(stats2.coeff_num, 256);
247 for (int i = 0; i < 256; ++i) {
248 EXPECT_DOUBLE_EQ(stats2.abs_coeff_sum[i], 2 * stats1.abs_coeff_sum[i]);
249 }
250 }
251
TEST(TplModelTest,ComputeMVDifferenceTest)252 TEST(TplModelTest, ComputeMVDifferenceTest) {
253 TplDepFrame tpl_frame_small;
254 tpl_frame_small.is_valid = true;
255 tpl_frame_small.mi_rows = 4;
256 tpl_frame_small.mi_cols = 4;
257 tpl_frame_small.stride = 1;
258 uint8_t right_shift_small = 1;
259 int step_small = 1 << right_shift_small;
260
261 // Test values for motion vectors.
262 int mv_vals_small[4] = { 1, 2, 3, 4 };
263 int index = 0;
264
265 // 4x4 blocks means we need to allocate a 4 size array.
266 // According to av1_tpl_ptr_pos:
267 // (row >> right_shift) * stride + (col >> right_shift)
268 // (4 >> 1) * 1 + (4 >> 1) = 4
269 TplDepStats stats_buf_small[4];
270 tpl_frame_small.tpl_stats_ptr = stats_buf_small;
271
272 for (int row = 0; row < tpl_frame_small.mi_rows; row += step_small) {
273 for (int col = 0; col < tpl_frame_small.mi_cols; col += step_small) {
274 TplDepStats tpl_stats;
275 tpl_stats.ref_frame_index[0] = 0;
276 int_mv mv;
277 mv.as_mv.row = mv_vals_small[index];
278 mv.as_mv.col = mv_vals_small[index];
279 index++;
280 tpl_stats.mv[0] = mv;
281 tpl_frame_small.tpl_stats_ptr[av1_tpl_ptr_pos(
282 row, col, tpl_frame_small.stride, right_shift_small)] = tpl_stats;
283 }
284 }
285
286 int_mv result_mv =
287 av1_compute_mv_difference(&tpl_frame_small, 1, 1, step_small,
288 tpl_frame_small.stride, right_shift_small);
289
290 // Expect the result to be exactly equal to 1 because this is the difference
291 // between neighboring motion vectors in this instance.
292 EXPECT_EQ(result_mv.as_mv.row, 1);
293 EXPECT_EQ(result_mv.as_mv.col, 1);
294 }
295
TEST(TplModelTest,ComputeMVBitsTest)296 TEST(TplModelTest, ComputeMVBitsTest) {
297 TplDepFrame tpl_frame;
298 tpl_frame.is_valid = true;
299 tpl_frame.mi_rows = 16;
300 tpl_frame.mi_cols = 16;
301 tpl_frame.stride = 24;
302 uint8_t right_shift = 2;
303 int step = 1 << right_shift;
304 // Test values for motion vectors.
305 int mv_vals_ordered[16] = { 1, 2, 3, 4, 5, 6, 7, 8,
306 9, 10, 11, 12, 13, 14, 15, 16 };
307 int mv_vals[16] = { 1, 16, 2, 15, 3, 14, 4, 13, 5, 12, 6, 11, 7, 10, 8, 9 };
308 int index = 0;
309
310 // 16x16 blocks means we need to allocate a 100 size array.
311 // According to av1_tpl_ptr_pos:
312 // (row >> right_shift) * stride + (col >> right_shift)
313 // (16 >> 2) * 24 + (16 >> 2) = 100
314 TplDepStats stats_buf[100];
315 tpl_frame.tpl_stats_ptr = stats_buf;
316
317 for (int row = 0; row < tpl_frame.mi_rows; row += step) {
318 for (int col = 0; col < tpl_frame.mi_cols; col += step) {
319 TplDepStats tpl_stats;
320 tpl_stats.ref_frame_index[0] = 0;
321 int_mv mv;
322 mv.as_mv.row = mv_vals_ordered[index];
323 mv.as_mv.col = mv_vals_ordered[index];
324 index++;
325 tpl_stats.mv[0] = mv;
326 tpl_frame.tpl_stats_ptr[av1_tpl_ptr_pos(row, col, tpl_frame.stride,
327 right_shift)] = tpl_stats;
328 }
329 }
330
331 double result = av1_tpl_compute_frame_mv_entropy(&tpl_frame, right_shift);
332
333 // Expect the result to be low because the motion vectors are ordered.
334 // The estimation algorithm takes this into account and reduces the cost.
335 EXPECT_NEAR(result, 20, 5);
336
337 index = 0;
338 for (int row = 0; row < tpl_frame.mi_rows; row += step) {
339 for (int col = 0; col < tpl_frame.mi_cols; col += step) {
340 TplDepStats tpl_stats;
341 tpl_stats.ref_frame_index[0] = 0;
342 int_mv mv;
343 mv.as_mv.row = mv_vals[index];
344 mv.as_mv.col = mv_vals[index];
345 index++;
346 tpl_stats.mv[0] = mv;
347 tpl_frame.tpl_stats_ptr[av1_tpl_ptr_pos(row, col, tpl_frame.stride,
348 right_shift)] = tpl_stats;
349 }
350 }
351
352 result = av1_tpl_compute_frame_mv_entropy(&tpl_frame, right_shift);
353
354 // Expect the result to be higher because the vectors are not ordered.
355 // Neighboring vectors will have different values, increasing the cost.
356 EXPECT_NEAR(result, 70, 5);
357 }
358 #if CONFIG_BITRATE_ACCURACY
359
TEST(TplModelTest,VbrRcInfoSetGopBitBudget)360 TEST(TplModelTest, VbrRcInfoSetGopBitBudget) {
361 VBR_RATECTRL_INFO vbr_rc_info;
362 const double total_bit_budget = 2000;
363 const int show_frame_count = 8;
364 const int gop_show_frame_count = 4;
365 av1_vbr_rc_init(&vbr_rc_info, total_bit_budget, show_frame_count);
366 av1_vbr_rc_set_gop_bit_budget(&vbr_rc_info, gop_show_frame_count);
367 EXPECT_NEAR(vbr_rc_info.gop_bit_budget, 1000, epsilon);
368 }
369
init_toy_gf_group(GF_GROUP * gf_group)370 void init_toy_gf_group(GF_GROUP *gf_group) {
371 av1_zero(*gf_group);
372 gf_group->size = 4;
373 const FRAME_UPDATE_TYPE update_type[4] = { KF_UPDATE, ARF_UPDATE,
374 INTNL_ARF_UPDATE, LF_UPDATE };
375 for (int i = 0; i < gf_group->size; ++i) {
376 gf_group->update_type[i] = update_type[i];
377 }
378 }
379
init_toy_vbr_rc_info(VBR_RATECTRL_INFO * vbr_rc_info,int gop_size)380 void init_toy_vbr_rc_info(VBR_RATECTRL_INFO *vbr_rc_info, int gop_size) {
381 int total_bit_budget = 2000;
382 int show_frame_count = 8;
383 av1_vbr_rc_init(vbr_rc_info, total_bit_budget, show_frame_count);
384
385 for (int i = 0; i < gop_size; ++i) {
386 vbr_rc_info->qstep_ratio_list[i] = 1;
387 }
388 }
389
init_toy_tpl_txfm_stats(std::vector<TplTxfmStats> * stats_list)390 void init_toy_tpl_txfm_stats(std::vector<TplTxfmStats> *stats_list) {
391 for (size_t i = 0; i < stats_list->size(); i++) {
392 TplTxfmStats *txfm_stats = &stats_list->at(i);
393 av1_init_tpl_txfm_stats(txfm_stats);
394 txfm_stats->txfm_block_count = 8;
395 for (int j = 0; j < txfm_stats->coeff_num; j++) {
396 txfm_stats->abs_coeff_sum[j] = 1000 + j;
397 }
398 av1_tpl_txfm_stats_update_abs_coeff_mean(txfm_stats);
399 }
400 }
401
402 /*
403 * Helper method to brute-force search for the closest q_index
404 * that achieves the specified bit budget.
405 */
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)406 int find_gop_q_iterative(double bit_budget, aom_bit_depth_t bit_depth,
407 const double *update_type_scale_factors,
408 int frame_count,
409 const FRAME_UPDATE_TYPE *update_type_list,
410 const double *qstep_ratio_list,
411 const TplTxfmStats *stats_list, int *q_index_list,
412 double *estimated_bitrate_byframe) {
413 int best_q = 255;
414 double curr_estimate = av1_vbr_rc_info_estimate_gop_bitrate(
415 best_q, bit_depth, update_type_scale_factors, frame_count,
416 update_type_list, qstep_ratio_list, stats_list, q_index_list,
417 estimated_bitrate_byframe);
418 double min_bits_diff = fabs(curr_estimate - bit_budget);
419 // Start at q = 254 because we already have an estimate for q = 255.
420 for (int q = 254; q >= 0; q--) {
421 double curr_estimate = av1_vbr_rc_info_estimate_gop_bitrate(
422 q, bit_depth, update_type_scale_factors, frame_count, update_type_list,
423 qstep_ratio_list, stats_list, q_index_list, estimated_bitrate_byframe);
424 double bits_diff = fabs(curr_estimate - bit_budget);
425 if (bits_diff <= min_bits_diff) {
426 min_bits_diff = bits_diff;
427 best_q = q;
428 }
429 }
430 return best_q;
431 }
432
TEST(TplModelTest,EstimateFrameRateTest)433 TEST(TplModelTest, EstimateFrameRateTest) {
434 GF_GROUP gf_group;
435 init_toy_gf_group(&gf_group);
436
437 VBR_RATECTRL_INFO vbr_rc_info;
438 init_toy_vbr_rc_info(&vbr_rc_info, gf_group.size);
439
440 std::vector<TplTxfmStats> stats_list(gf_group.size);
441 init_toy_tpl_txfm_stats(&stats_list);
442
443 std::vector<double> est_bitrate_list(gf_group.size);
444 init_toy_tpl_txfm_stats(&stats_list);
445 const aom_bit_depth_t bit_depth = AOM_BITS_8;
446
447 const int q = 125;
448
449 // Case1: all scale factors are 0
450 double scale_factors[FRAME_UPDATE_TYPES] = { 0 };
451 double estimate = av1_vbr_rc_info_estimate_gop_bitrate(
452 q, bit_depth, scale_factors, gf_group.size, gf_group.update_type,
453 vbr_rc_info.qstep_ratio_list, stats_list.data(), vbr_rc_info.q_index_list,
454 est_bitrate_list.data());
455 EXPECT_NEAR(estimate, 0, epsilon);
456
457 // Case2: all scale factors are 1
458 for (int i = 0; i < FRAME_UPDATE_TYPES; i++) {
459 scale_factors[i] = 1;
460 }
461 estimate = av1_vbr_rc_info_estimate_gop_bitrate(
462 q, bit_depth, scale_factors, gf_group.size, gf_group.update_type,
463 vbr_rc_info.qstep_ratio_list, stats_list.data(), vbr_rc_info.q_index_list,
464 est_bitrate_list.data());
465 double ref_estimate = 0;
466 for (int i = 0; i < gf_group.size; i++) {
467 ref_estimate += est_bitrate_list[i];
468 }
469 EXPECT_NEAR(estimate, ref_estimate, epsilon);
470
471 // Case3: Key frame scale factor is 0 and others are 1
472 for (int i = 0; i < FRAME_UPDATE_TYPES; i++) {
473 if (i == KF_UPDATE) {
474 scale_factors[i] = 0;
475 } else {
476 scale_factors[i] = 1;
477 }
478 }
479 estimate = av1_vbr_rc_info_estimate_gop_bitrate(
480 q, bit_depth, scale_factors, gf_group.size, gf_group.update_type,
481 vbr_rc_info.qstep_ratio_list, stats_list.data(), vbr_rc_info.q_index_list,
482 est_bitrate_list.data());
483 ref_estimate = 0;
484 for (int i = 0; i < gf_group.size; i++) {
485 if (gf_group.update_type[i] != KF_UPDATE) {
486 ref_estimate += est_bitrate_list[i];
487 }
488 }
489 EXPECT_NEAR(estimate, ref_estimate, epsilon);
490 }
491
TEST(TplModelTest,VbrRcInfoEstimateBaseQTest)492 TEST(TplModelTest, VbrRcInfoEstimateBaseQTest) {
493 GF_GROUP gf_group;
494 init_toy_gf_group(&gf_group);
495
496 VBR_RATECTRL_INFO vbr_rc_info;
497 init_toy_vbr_rc_info(&vbr_rc_info, gf_group.size);
498
499 std::vector<TplTxfmStats> stats_list(gf_group.size);
500 init_toy_tpl_txfm_stats(&stats_list);
501 const aom_bit_depth_t bit_depth = AOM_BITS_8;
502
503 // Test multiple bit budgets.
504 const std::vector<double> bit_budgets = { 0, 2470, 19200, 30750,
505 41315, 65017, DBL_MAX };
506
507 for (double bit_budget : bit_budgets) {
508 // Binary search method to find the optimal q.
509 const int base_q = av1_vbr_rc_info_estimate_base_q(
510 bit_budget, bit_depth, vbr_rc_info.scale_factors, gf_group.size,
511 gf_group.update_type, vbr_rc_info.qstep_ratio_list, stats_list.data(),
512 vbr_rc_info.q_index_list, nullptr);
513 const int ref_base_q = find_gop_q_iterative(
514 bit_budget, bit_depth, vbr_rc_info.scale_factors, gf_group.size,
515 gf_group.update_type, vbr_rc_info.qstep_ratio_list, stats_list.data(),
516 vbr_rc_info.q_index_list, nullptr);
517 if (bit_budget == 0) {
518 EXPECT_EQ(base_q, 255);
519 } else if (bit_budget == DBL_MAX) {
520 EXPECT_EQ(base_q, 0);
521 }
522 EXPECT_EQ(base_q, ref_base_q);
523 }
524 }
525 #endif // CONFIG_BITRATE_ACCURACY
526
527 } // namespace
528