| /* |
| * Copyright (c) 2020, 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 "av1/common/cfl.h" |
| #include "av1/common/reconintra.h" |
| #include "av1/encoder/block.h" |
| #include "av1/encoder/hybrid_fwd_txfm.h" |
| #include "av1/common/idct.h" |
| #include "av1/encoder/model_rd.h" |
| #include "av1/encoder/random.h" |
| #include "av1/encoder/rdopt_utils.h" |
| #include "av1/encoder/sorting_network.h" |
| #include "av1/encoder/tx_prune_model_weights.h" |
| #include "av1/encoder/tx_search.h" |
| #include "av1/encoder/txb_rdopt.h" |
| |
| #define PROB_THRESH_OFFSET_TX_TYPE 100 |
| |
| struct rdcost_block_args { |
| const AV1_COMP *cpi; |
| MACROBLOCK *x; |
| ENTROPY_CONTEXT t_above[MAX_MIB_SIZE]; |
| ENTROPY_CONTEXT t_left[MAX_MIB_SIZE]; |
| RD_STATS rd_stats; |
| int64_t current_rd; |
| int64_t best_rd; |
| int exit_early; |
| int incomplete_exit; |
| FAST_TX_SEARCH_MODE ftxs_mode; |
| int skip_trellis; |
| }; |
| |
| typedef struct { |
| int64_t rd; |
| int txb_entropy_ctx; |
| TX_TYPE tx_type; |
| } TxCandidateInfo; |
| |
| // origin_threshold * 128 / 100 |
| static const uint32_t skip_pred_threshold[3][BLOCK_SIZES_ALL] = { |
| { |
| 64, 64, 64, 70, 60, 60, 68, 68, 68, 68, 68, |
| 68, 68, 68, 68, 68, 64, 64, 70, 70, 68, 68, |
| }, |
| { |
| 88, 88, 88, 86, 87, 87, 68, 68, 68, 68, 68, |
| 68, 68, 68, 68, 68, 88, 88, 86, 86, 68, 68, |
| }, |
| { |
| 90, 93, 93, 90, 93, 93, 74, 74, 74, 74, 74, |
| 74, 74, 74, 74, 74, 90, 90, 90, 90, 74, 74, |
| }, |
| }; |
| |
| // lookup table for predict_skip_txfm |
| // int max_tx_size = max_txsize_rect_lookup[bsize]; |
| // if (tx_size_high[max_tx_size] > 16 || tx_size_wide[max_tx_size] > 16) |
| // max_tx_size = AOMMIN(max_txsize_lookup[bsize], TX_16X16); |
| static const TX_SIZE max_predict_sf_tx_size[BLOCK_SIZES_ALL] = { |
| TX_4X4, TX_4X8, TX_8X4, TX_8X8, TX_8X16, TX_16X8, |
| TX_16X16, TX_16X16, TX_16X16, TX_16X16, TX_16X16, TX_16X16, |
| TX_16X16, TX_16X16, TX_16X16, TX_16X16, TX_4X16, TX_16X4, |
| TX_8X8, TX_8X8, TX_16X16, TX_16X16, |
| }; |
| |
| // look-up table for sqrt of number of pixels in a transform block |
| // rounded up to the nearest integer. |
| static const int sqrt_tx_pixels_2d[TX_SIZES_ALL] = { 4, 8, 16, 32, 32, 6, 6, |
| 12, 12, 23, 23, 32, 32, 8, |
| 8, 16, 16, 23, 23 }; |
| |
| static INLINE uint32_t get_block_residue_hash(MACROBLOCK *x, BLOCK_SIZE bsize) { |
| const int rows = block_size_high[bsize]; |
| const int cols = block_size_wide[bsize]; |
| const int16_t *diff = x->plane[0].src_diff; |
| const uint32_t hash = |
| av1_get_crc32c_value(&x->txfm_search_info.mb_rd_record->crc_calculator, |
| (uint8_t *)diff, 2 * rows * cols); |
| return (hash << 5) + bsize; |
| } |
| |
| static INLINE int32_t find_mb_rd_info(const MB_RD_RECORD *const mb_rd_record, |
| const int64_t ref_best_rd, |
| const uint32_t hash) { |
| int32_t match_index = -1; |
| if (ref_best_rd != INT64_MAX) { |
| for (int i = 0; i < mb_rd_record->num; ++i) { |
| const int index = (mb_rd_record->index_start + i) % RD_RECORD_BUFFER_LEN; |
| // If there is a match in the mb_rd_record, fetch the RD decision and |
| // terminate early. |
| if (mb_rd_record->mb_rd_info[index].hash_value == hash) { |
| match_index = index; |
| break; |
| } |
| } |
| } |
| return match_index; |
| } |
| |
| static AOM_INLINE void fetch_mb_rd_info(int n4, |
| const MB_RD_INFO *const mb_rd_info, |
| RD_STATS *const rd_stats, |
| MACROBLOCK *const x) { |
| MACROBLOCKD *const xd = &x->e_mbd; |
| MB_MODE_INFO *const mbmi = xd->mi[0]; |
| mbmi->tx_size = mb_rd_info->tx_size; |
| memcpy(x->txfm_search_info.blk_skip, mb_rd_info->blk_skip, |
| sizeof(mb_rd_info->blk_skip[0]) * n4); |
| av1_copy(mbmi->inter_tx_size, mb_rd_info->inter_tx_size); |
| av1_copy_array(xd->tx_type_map, mb_rd_info->tx_type_map, n4); |
| *rd_stats = mb_rd_info->rd_stats; |
| } |
| |
| int64_t av1_pixel_diff_dist(const MACROBLOCK *x, int plane, int blk_row, |
| int blk_col, const BLOCK_SIZE plane_bsize, |
| const BLOCK_SIZE tx_bsize, |
| unsigned int *block_mse_q8) { |
| int visible_rows, visible_cols; |
| const MACROBLOCKD *xd = &x->e_mbd; |
| get_txb_dimensions(xd, plane, plane_bsize, blk_row, blk_col, tx_bsize, NULL, |
| NULL, &visible_cols, &visible_rows); |
| const int diff_stride = block_size_wide[plane_bsize]; |
| const int16_t *diff = x->plane[plane].src_diff; |
| |
| diff += ((blk_row * diff_stride + blk_col) << MI_SIZE_LOG2); |
| uint64_t sse = |
| aom_sum_squares_2d_i16(diff, diff_stride, visible_cols, visible_rows); |
| if (block_mse_q8 != NULL) { |
| if (visible_cols > 0 && visible_rows > 0) |
| *block_mse_q8 = |
| (unsigned int)((256 * sse) / (visible_cols * visible_rows)); |
| else |
| *block_mse_q8 = UINT_MAX; |
| } |
| return sse; |
| } |
| |
| // Computes the residual block's SSE and mean on all visible 4x4s in the |
| // transform block |
| static INLINE int64_t pixel_diff_stats( |
| MACROBLOCK *x, int plane, int blk_row, int blk_col, |
| const BLOCK_SIZE plane_bsize, const BLOCK_SIZE tx_bsize, |
| unsigned int *block_mse_q8, int64_t *per_px_mean, uint64_t *block_var) { |
| int visible_rows, visible_cols; |
| const MACROBLOCKD *xd = &x->e_mbd; |
| get_txb_dimensions(xd, plane, plane_bsize, blk_row, blk_col, tx_bsize, NULL, |
| NULL, &visible_cols, &visible_rows); |
| const int diff_stride = block_size_wide[plane_bsize]; |
| const int16_t *diff = x->plane[plane].src_diff; |
| |
| diff += ((blk_row * diff_stride + blk_col) << MI_SIZE_LOG2); |
| uint64_t sse = 0; |
| int sum = 0; |
| sse = aom_sum_sse_2d_i16(diff, diff_stride, visible_cols, visible_rows, &sum); |
| if (visible_cols > 0 && visible_rows > 0) { |
| double norm_factor = 1.0 / (visible_cols * visible_rows); |
| int sign_sum = sum > 0 ? 1 : -1; |
| // Conversion to transform domain |
| *per_px_mean = (int64_t)(norm_factor * abs(sum)) << 7; |
| *per_px_mean = sign_sum * (*per_px_mean); |
| *block_mse_q8 = (unsigned int)(norm_factor * (256 * sse)); |
| *block_var = (uint64_t)(sse - (uint64_t)(norm_factor * sum * sum)); |
| } else { |
| *block_mse_q8 = UINT_MAX; |
| } |
| return sse; |
| } |
| |
| // Uses simple features on top of DCT coefficients to quickly predict |
| // whether optimal RD decision is to skip encoding the residual. |
| // The sse value is stored in dist. |
| static int predict_skip_txfm(MACROBLOCK *x, BLOCK_SIZE bsize, int64_t *dist, |
| int reduced_tx_set) { |
| const TxfmSearchParams *txfm_params = &x->txfm_search_params; |
| const int bw = block_size_wide[bsize]; |
| const int bh = block_size_high[bsize]; |
| const MACROBLOCKD *xd = &x->e_mbd; |
| const int16_t dc_q = av1_dc_quant_QTX(x->qindex, 0, xd->bd); |
| |
| *dist = av1_pixel_diff_dist(x, 0, 0, 0, bsize, bsize, NULL); |
| |
| const int64_t mse = *dist / bw / bh; |
| // Normalized quantizer takes the transform upscaling factor (8 for tx size |
| // smaller than 32) into account. |
| const int16_t normalized_dc_q = dc_q >> 3; |
| const int64_t mse_thresh = (int64_t)normalized_dc_q * normalized_dc_q / 8; |
| // For faster early skip decision, use dist to compare against threshold so |
| // that quality risk is less for the skip=1 decision. Otherwise, use mse |
| // since the fwd_txfm coeff checks will take care of quality |
| // TODO(any): Use dist to return 0 when skip_txfm_level is 1 |
| int64_t pred_err = (txfm_params->skip_txfm_level >= 2) ? *dist : mse; |
| // Predict not to skip when error is larger than threshold. |
| if (pred_err > mse_thresh) return 0; |
| // Return as skip otherwise for aggressive early skip |
| else if (txfm_params->skip_txfm_level >= 2) |
| return 1; |
| |
| const int max_tx_size = max_predict_sf_tx_size[bsize]; |
| const int tx_h = tx_size_high[max_tx_size]; |
| const int tx_w = tx_size_wide[max_tx_size]; |
| DECLARE_ALIGNED(32, tran_low_t, coefs[32 * 32]); |
| TxfmParam param; |
| param.tx_type = DCT_DCT; |
| param.tx_size = max_tx_size; |
| param.bd = xd->bd; |
| param.is_hbd = is_cur_buf_hbd(xd); |
| param.lossless = 0; |
| param.tx_set_type = av1_get_ext_tx_set_type( |
| param.tx_size, is_inter_block(xd->mi[0]), reduced_tx_set); |
| const int bd_idx = (xd->bd == 8) ? 0 : ((xd->bd == 10) ? 1 : 2); |
| const uint32_t max_qcoef_thresh = skip_pred_threshold[bd_idx][bsize]; |
| const int16_t *src_diff = x->plane[0].src_diff; |
| const int n_coeff = tx_w * tx_h; |
| const int16_t ac_q = av1_ac_quant_QTX(x->qindex, 0, xd->bd); |
| const uint32_t dc_thresh = max_qcoef_thresh * dc_q; |
| const uint32_t ac_thresh = max_qcoef_thresh * ac_q; |
| for (int row = 0; row < bh; row += tx_h) { |
| for (int col = 0; col < bw; col += tx_w) { |
| av1_fwd_txfm(src_diff + col, coefs, bw, ¶m); |
| // Operating on TX domain, not pixels; we want the QTX quantizers |
| const uint32_t dc_coef = (((uint32_t)abs(coefs[0])) << 7); |
| if (dc_coef >= dc_thresh) return 0; |
| for (int i = 1; i < n_coeff; ++i) { |
| const uint32_t ac_coef = (((uint32_t)abs(coefs[i])) << 7); |
| if (ac_coef >= ac_thresh) return 0; |
| } |
| } |
| src_diff += tx_h * bw; |
| } |
| return 1; |
| } |
| |
| // Used to set proper context for early termination with skip = 1. |
| static AOM_INLINE void set_skip_txfm(MACROBLOCK *x, RD_STATS *rd_stats, |
| BLOCK_SIZE bsize, int64_t dist) { |
| MACROBLOCKD *const xd = &x->e_mbd; |
| MB_MODE_INFO *const mbmi = xd->mi[0]; |
| const int n4 = bsize_to_num_blk(bsize); |
| const TX_SIZE tx_size = max_txsize_rect_lookup[bsize]; |
| memset(xd->tx_type_map, DCT_DCT, sizeof(xd->tx_type_map[0]) * n4); |
| memset(mbmi->inter_tx_size, tx_size, sizeof(mbmi->inter_tx_size)); |
| mbmi->tx_size = tx_size; |
| for (int i = 0; i < n4; ++i) |
| set_blk_skip(x->txfm_search_info.blk_skip, 0, i, 1); |
| rd_stats->skip_txfm = 1; |
| if (is_cur_buf_hbd(xd)) dist = ROUND_POWER_OF_TWO(dist, (xd->bd - 8) * 2); |
| rd_stats->dist = rd_stats->sse = (dist << 4); |
| // Though decision is to make the block as skip based on luma stats, |
| // it is possible that block becomes non skip after chroma rd. In addition |
| // intermediate non skip costs calculated by caller function will be |
| // incorrect, if rate is set as zero (i.e., if zero_blk_rate is not |
| // accounted). Hence intermediate rate is populated to code the luma tx blks |
| // as skip, the caller function based on final rd decision (i.e., skip vs |
| // non-skip) sets the final rate accordingly. Here the rate populated |
| // corresponds to coding all the tx blocks with zero_blk_rate (based on max tx |
| // size possible) in the current block. Eg: For 128*128 block, rate would be |
| // 4 * zero_blk_rate where zero_blk_rate corresponds to coding of one 64x64 tx |
| // block as 'all zeros' |
| ENTROPY_CONTEXT ctxa[MAX_MIB_SIZE]; |
| ENTROPY_CONTEXT ctxl[MAX_MIB_SIZE]; |
| av1_get_entropy_contexts(bsize, &xd->plane[0], ctxa, ctxl); |
| ENTROPY_CONTEXT *ta = ctxa; |
| ENTROPY_CONTEXT *tl = ctxl; |
| const TX_SIZE txs_ctx = get_txsize_entropy_ctx(tx_size); |
| TXB_CTX txb_ctx; |
| get_txb_ctx(bsize, tx_size, 0, ta, tl, &txb_ctx); |
| const int zero_blk_rate = x->coeff_costs.coeff_costs[txs_ctx][PLANE_TYPE_Y] |
| .txb_skip_cost[txb_ctx.txb_skip_ctx][1]; |
| rd_stats->rate = zero_blk_rate * |
| (block_size_wide[bsize] >> tx_size_wide_log2[tx_size]) * |
| (block_size_high[bsize] >> tx_size_high_log2[tx_size]); |
| } |
| |
| static AOM_INLINE void save_mb_rd_info(int n4, uint32_t hash, |
| const MACROBLOCK *const x, |
| const RD_STATS *const rd_stats, |
| MB_RD_RECORD *mb_rd_record) { |
| int index; |
| if (mb_rd_record->num < RD_RECORD_BUFFER_LEN) { |
| index = |
| (mb_rd_record->index_start + mb_rd_record->num) % RD_RECORD_BUFFER_LEN; |
| ++mb_rd_record->num; |
| } else { |
| index = mb_rd_record->index_start; |
| mb_rd_record->index_start = |
| (mb_rd_record->index_start + 1) % RD_RECORD_BUFFER_LEN; |
| } |
| MB_RD_INFO *const mb_rd_info = &mb_rd_record->mb_rd_info[index]; |
| const MACROBLOCKD *const xd = &x->e_mbd; |
| const MB_MODE_INFO *const mbmi = xd->mi[0]; |
| mb_rd_info->hash_value = hash; |
| mb_rd_info->tx_size = mbmi->tx_size; |
| memcpy(mb_rd_info->blk_skip, x->txfm_search_info.blk_skip, |
| sizeof(mb_rd_info->blk_skip[0]) * n4); |
| av1_copy(mb_rd_info->inter_tx_size, mbmi->inter_tx_size); |
| av1_copy_array(mb_rd_info->tx_type_map, xd->tx_type_map, n4); |
| mb_rd_info->rd_stats = *rd_stats; |
| } |
| |
| static int get_search_init_depth(int mi_width, int mi_height, int is_inter, |
| const SPEED_FEATURES *sf, |
| int tx_size_search_method) { |
| if (tx_size_search_method == USE_LARGESTALL) return MAX_VARTX_DEPTH; |
| |
| if (sf->tx_sf.tx_size_search_lgr_block) { |
| if (mi_width > mi_size_wide[BLOCK_64X64] || |
| mi_height > mi_size_high[BLOCK_64X64]) |
| return MAX_VARTX_DEPTH; |
| } |
| |
| if (is_inter) { |
| return (mi_height != mi_width) |
| ? sf->tx_sf.inter_tx_size_search_init_depth_rect |
| : sf->tx_sf.inter_tx_size_search_init_depth_sqr; |
| } else { |
| return (mi_height != mi_width) |
| ? sf->tx_sf.intra_tx_size_search_init_depth_rect |
| : sf->tx_sf.intra_tx_size_search_init_depth_sqr; |
| } |
| } |
| |
| static AOM_INLINE void select_tx_block( |
| const AV1_COMP *cpi, MACROBLOCK *x, int blk_row, int blk_col, int block, |
| TX_SIZE tx_size, int depth, BLOCK_SIZE plane_bsize, ENTROPY_CONTEXT *ta, |
| ENTROPY_CONTEXT *tl, TXFM_CONTEXT *tx_above, TXFM_CONTEXT *tx_left, |
| RD_STATS *rd_stats, int64_t prev_level_rd, int64_t ref_best_rd, |
| int *is_cost_valid, FAST_TX_SEARCH_MODE ftxs_mode); |
| |
| // NOTE: CONFIG_COLLECT_RD_STATS has 3 possible values |
| // 0: Do not collect any RD stats |
| // 1: Collect RD stats for transform units |
| // 2: Collect RD stats for partition units |
| #if CONFIG_COLLECT_RD_STATS |
| |
| static AOM_INLINE void get_energy_distribution_fine( |
| const AV1_COMP *cpi, BLOCK_SIZE bsize, const uint8_t *src, int src_stride, |
| const uint8_t *dst, int dst_stride, int need_4th, double *hordist, |
| double *verdist) { |
| const int bw = block_size_wide[bsize]; |
| const int bh = block_size_high[bsize]; |
| unsigned int esq[16] = { 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 }; |
| |
| if (bsize < BLOCK_16X16 || (bsize >= BLOCK_4X16 && bsize <= BLOCK_32X8)) { |
| // Special cases: calculate 'esq' values manually, as we don't have 'vf' |
| // functions for the 16 (very small) sub-blocks of this block. |
| const int w_shift = (bw == 4) ? 0 : (bw == 8) ? 1 : (bw == 16) ? 2 : 3; |
| const int h_shift = (bh == 4) ? 0 : (bh == 8) ? 1 : (bh == 16) ? 2 : 3; |
| assert(bw <= 32); |
| assert(bh <= 32); |
| assert(((bw - 1) >> w_shift) + (((bh - 1) >> h_shift) << 2) == 15); |
| if (cpi->common.seq_params->use_highbitdepth) { |
| const uint16_t *src16 = CONVERT_TO_SHORTPTR(src); |
| const uint16_t *dst16 = CONVERT_TO_SHORTPTR(dst); |
| for (int i = 0; i < bh; ++i) |
| for (int j = 0; j < bw; ++j) { |
| const int index = (j >> w_shift) + ((i >> h_shift) << 2); |
| esq[index] += |
| (src16[j + i * src_stride] - dst16[j + i * dst_stride]) * |
| (src16[j + i * src_stride] - dst16[j + i * dst_stride]); |
| } |
| } else { |
| for (int i = 0; i < bh; ++i) |
| for (int j = 0; j < bw; ++j) { |
| const int index = (j >> w_shift) + ((i >> h_shift) << 2); |
| esq[index] += (src[j + i * src_stride] - dst[j + i * dst_stride]) * |
| (src[j + i * src_stride] - dst[j + i * dst_stride]); |
| } |
| } |
| } else { // Calculate 'esq' values using 'vf' functions on the 16 sub-blocks. |
| const int f_index = |
| (bsize < BLOCK_SIZES) ? bsize - BLOCK_16X16 : bsize - BLOCK_8X16; |
| assert(f_index >= 0 && f_index < BLOCK_SIZES_ALL); |
| const BLOCK_SIZE subsize = (BLOCK_SIZE)f_index; |
| assert(block_size_wide[bsize] == 4 * block_size_wide[subsize]); |
| assert(block_size_high[bsize] == 4 * block_size_high[subsize]); |
| cpi->ppi->fn_ptr[subsize].vf(src, src_stride, dst, dst_stride, &esq[0]); |
| cpi->ppi->fn_ptr[subsize].vf(src + bw / 4, src_stride, dst + bw / 4, |
| dst_stride, &esq[1]); |
| cpi->ppi->fn_ptr[subsize].vf(src + bw / 2, src_stride, dst + bw / 2, |
| dst_stride, &esq[2]); |
| cpi->ppi->fn_ptr[subsize].vf(src + 3 * bw / 4, src_stride, dst + 3 * bw / 4, |
| dst_stride, &esq[3]); |
| src += bh / 4 * src_stride; |
| dst += bh / 4 * dst_stride; |
| |
| cpi->ppi->fn_ptr[subsize].vf(src, src_stride, dst, dst_stride, &esq[4]); |
| cpi->ppi->fn_ptr[subsize].vf(src + bw / 4, src_stride, dst + bw / 4, |
| dst_stride, &esq[5]); |
| cpi->ppi->fn_ptr[subsize].vf(src + bw / 2, src_stride, dst + bw / 2, |
| dst_stride, &esq[6]); |
| cpi->ppi->fn_ptr[subsize].vf(src + 3 * bw / 4, src_stride, dst + 3 * bw / 4, |
| dst_stride, &esq[7]); |
| src += bh / 4 * src_stride; |
| dst += bh / 4 * dst_stride; |
| |
| cpi->ppi->fn_ptr[subsize].vf(src, src_stride, dst, dst_stride, &esq[8]); |
| cpi->ppi->fn_ptr[subsize].vf(src + bw / 4, src_stride, dst + bw / 4, |
| dst_stride, &esq[9]); |
| cpi->ppi->fn_ptr[subsize].vf(src + bw / 2, src_stride, dst + bw / 2, |
| dst_stride, &esq[10]); |
| cpi->ppi->fn_ptr[subsize].vf(src + 3 * bw / 4, src_stride, dst + 3 * bw / 4, |
| dst_stride, &esq[11]); |
| src += bh / 4 * src_stride; |
| dst += bh / 4 * dst_stride; |
| |
| cpi->ppi->fn_ptr[subsize].vf(src, src_stride, dst, dst_stride, &esq[12]); |
| cpi->ppi->fn_ptr[subsize].vf(src + bw / 4, src_stride, dst + bw / 4, |
| dst_stride, &esq[13]); |
| cpi->ppi->fn_ptr[subsize].vf(src + bw / 2, src_stride, dst + bw / 2, |
| dst_stride, &esq[14]); |
| cpi->ppi->fn_ptr[subsize].vf(src + 3 * bw / 4, src_stride, dst + 3 * bw / 4, |
| dst_stride, &esq[15]); |
| } |
| |
| double total = (double)esq[0] + esq[1] + esq[2] + esq[3] + esq[4] + esq[5] + |
| esq[6] + esq[7] + esq[8] + esq[9] + esq[10] + esq[11] + |
| esq[12] + esq[13] + esq[14] + esq[15]; |
| if (total > 0) { |
| const double e_recip = 1.0 / total; |
| hordist[0] = ((double)esq[0] + esq[4] + esq[8] + esq[12]) * e_recip; |
| hordist[1] = ((double)esq[1] + esq[5] + esq[9] + esq[13]) * e_recip; |
| hordist[2] = ((double)esq[2] + esq[6] + esq[10] + esq[14]) * e_recip; |
| if (need_4th) { |
| hordist[3] = ((double)esq[3] + esq[7] + esq[11] + esq[15]) * e_recip; |
| } |
| verdist[0] = ((double)esq[0] + esq[1] + esq[2] + esq[3]) * e_recip; |
| verdist[1] = ((double)esq[4] + esq[5] + esq[6] + esq[7]) * e_recip; |
| verdist[2] = ((double)esq[8] + esq[9] + esq[10] + esq[11]) * e_recip; |
| if (need_4th) { |
| verdist[3] = ((double)esq[12] + esq[13] + esq[14] + esq[15]) * e_recip; |
| } |
| } else { |
| hordist[0] = verdist[0] = 0.25; |
| hordist[1] = verdist[1] = 0.25; |
| hordist[2] = verdist[2] = 0.25; |
| if (need_4th) { |
| hordist[3] = verdist[3] = 0.25; |
| } |
| } |
| } |
| |
| static double get_sse_norm(const int16_t *diff, int stride, int w, int h) { |
| double sum = 0.0; |
| for (int j = 0; j < h; ++j) { |
| for (int i = 0; i < w; ++i) { |
| const int err = diff[j * stride + i]; |
| sum += err * err; |
| } |
| } |
| assert(w > 0 && h > 0); |
| return sum / (w * h); |
| } |
| |
| static double get_sad_norm(const int16_t *diff, int stride, int w, int h) { |
| double sum = 0.0; |
| for (int j = 0; j < h; ++j) { |
| for (int i = 0; i < w; ++i) { |
| sum += abs(diff[j * stride + i]); |
| } |
| } |
| assert(w > 0 && h > 0); |
| return sum / (w * h); |
| } |
| |
| static AOM_INLINE void get_2x2_normalized_sses_and_sads( |
| const AV1_COMP *const cpi, BLOCK_SIZE tx_bsize, const uint8_t *const src, |
| int src_stride, const uint8_t *const dst, int dst_stride, |
| const int16_t *const src_diff, int diff_stride, double *const sse_norm_arr, |
| double *const sad_norm_arr) { |
| const BLOCK_SIZE tx_bsize_half = |
| get_partition_subsize(tx_bsize, PARTITION_SPLIT); |
| if (tx_bsize_half == BLOCK_INVALID) { // manually calculate stats |
| const int half_width = block_size_wide[tx_bsize] / 2; |
| const int half_height = block_size_high[tx_bsize] / 2; |
| for (int row = 0; row < 2; ++row) { |
| for (int col = 0; col < 2; ++col) { |
| const int16_t *const this_src_diff = |
| src_diff + row * half_height * diff_stride + col * half_width; |
| if (sse_norm_arr) { |
| sse_norm_arr[row * 2 + col] = |
| get_sse_norm(this_src_diff, diff_stride, half_width, half_height); |
| } |
| if (sad_norm_arr) { |
| sad_norm_arr[row * 2 + col] = |
| get_sad_norm(this_src_diff, diff_stride, half_width, half_height); |
| } |
| } |
| } |
| } else { // use function pointers to calculate stats |
| const int half_width = block_size_wide[tx_bsize_half]; |
| const int half_height = block_size_high[tx_bsize_half]; |
| const int num_samples_half = half_width * half_height; |
| for (int row = 0; row < 2; ++row) { |
| for (int col = 0; col < 2; ++col) { |
| const uint8_t *const this_src = |
| src + row * half_height * src_stride + col * half_width; |
| const uint8_t *const this_dst = |
| dst + row * half_height * dst_stride + col * half_width; |
| |
| if (sse_norm_arr) { |
| unsigned int this_sse; |
| cpi->ppi->fn_ptr[tx_bsize_half].vf(this_src, src_stride, this_dst, |
| dst_stride, &this_sse); |
| sse_norm_arr[row * 2 + col] = (double)this_sse / num_samples_half; |
| } |
| |
| if (sad_norm_arr) { |
| const unsigned int this_sad = cpi->ppi->fn_ptr[tx_bsize_half].sdf( |
| this_src, src_stride, this_dst, dst_stride); |
| sad_norm_arr[row * 2 + col] = (double)this_sad / num_samples_half; |
| } |
| } |
| } |
| } |
| } |
| |
| #if CONFIG_COLLECT_RD_STATS == 1 |
| static double get_mean(const int16_t *diff, int stride, int w, int h) { |
| double sum = 0.0; |
| for (int j = 0; j < h; ++j) { |
| for (int i = 0; i < w; ++i) { |
| sum += diff[j * stride + i]; |
| } |
| } |
| assert(w > 0 && h > 0); |
| return sum / (w * h); |
| } |
| static AOM_INLINE void PrintTransformUnitStats( |
| const AV1_COMP *const cpi, MACROBLOCK *x, const RD_STATS *const rd_stats, |
| int blk_row, int blk_col, BLOCK_SIZE plane_bsize, TX_SIZE tx_size, |
| TX_TYPE tx_type, int64_t rd) { |
| if (rd_stats->rate == INT_MAX || rd_stats->dist == INT64_MAX) return; |
| |
| // Generate small sample to restrict output size. |
| static unsigned int seed = 21743; |
| if (lcg_rand16(&seed) % 256 > 0) return; |
| |
| const char output_file[] = "tu_stats.txt"; |
| FILE *fout = fopen(output_file, "a"); |
| if (!fout) return; |
| |
| const BLOCK_SIZE tx_bsize = txsize_to_bsize[tx_size]; |
| const MACROBLOCKD *const xd = &x->e_mbd; |
| const int plane = 0; |
| struct macroblock_plane *const p = &x->plane[plane]; |
| const struct macroblockd_plane *const pd = &xd->plane[plane]; |
| const int txw = tx_size_wide[tx_size]; |
| const int txh = tx_size_high[tx_size]; |
| const int dequant_shift = (is_cur_buf_hbd(xd)) ? xd->bd - 5 : 3; |
| const int q_step = p->dequant_QTX[1] >> dequant_shift; |
| const int num_samples = txw * txh; |
| |
| const double rate_norm = (double)rd_stats->rate / num_samples; |
| const double dist_norm = (double)rd_stats->dist / num_samples; |
| |
| fprintf(fout, "%g %g", rate_norm, dist_norm); |
| |
| const int src_stride = p->src.stride; |
| const uint8_t *const src = |
| &p->src.buf[(blk_row * src_stride + blk_col) << MI_SIZE_LOG2]; |
| const int dst_stride = pd->dst.stride; |
| const uint8_t *const dst = |
| &pd->dst.buf[(blk_row * dst_stride + blk_col) << MI_SIZE_LOG2]; |
| unsigned int sse; |
| cpi->ppi->fn_ptr[tx_bsize].vf(src, src_stride, dst, dst_stride, &sse); |
| const double sse_norm = (double)sse / num_samples; |
| |
| const unsigned int sad = |
| cpi->ppi->fn_ptr[tx_bsize].sdf(src, src_stride, dst, dst_stride); |
| const double sad_norm = (double)sad / num_samples; |
| |
| fprintf(fout, " %g %g", sse_norm, sad_norm); |
| |
| const int diff_stride = block_size_wide[plane_bsize]; |
| const int16_t *const src_diff = |
| &p->src_diff[(blk_row * diff_stride + blk_col) << MI_SIZE_LOG2]; |
| |
| double sse_norm_arr[4], sad_norm_arr[4]; |
| get_2x2_normalized_sses_and_sads(cpi, tx_bsize, src, src_stride, dst, |
| dst_stride, src_diff, diff_stride, |
| sse_norm_arr, sad_norm_arr); |
| for (int i = 0; i < 4; ++i) { |
| fprintf(fout, " %g", sse_norm_arr[i]); |
| } |
| for (int i = 0; i < 4; ++i) { |
| fprintf(fout, " %g", sad_norm_arr[i]); |
| } |
| |
| const TX_TYPE_1D tx_type_1d_row = htx_tab[tx_type]; |
| const TX_TYPE_1D tx_type_1d_col = vtx_tab[tx_type]; |
| |
| fprintf(fout, " %d %d %d %d %d", q_step, tx_size_wide[tx_size], |
| tx_size_high[tx_size], tx_type_1d_row, tx_type_1d_col); |
| |
| int model_rate; |
| int64_t model_dist; |
| model_rd_sse_fn[MODELRD_CURVFIT](cpi, x, tx_bsize, plane, sse, num_samples, |
| &model_rate, &model_dist); |
| const double model_rate_norm = (double)model_rate / num_samples; |
| const double model_dist_norm = (double)model_dist / num_samples; |
| fprintf(fout, " %g %g", model_rate_norm, model_dist_norm); |
| |
| const double mean = get_mean(src_diff, diff_stride, txw, txh); |
| float hor_corr, vert_corr; |
| av1_get_horver_correlation_full(src_diff, diff_stride, txw, txh, &hor_corr, |
| &vert_corr); |
| fprintf(fout, " %g %g %g", mean, hor_corr, vert_corr); |
| |
| double hdist[4] = { 0 }, vdist[4] = { 0 }; |
| get_energy_distribution_fine(cpi, tx_bsize, src, src_stride, dst, dst_stride, |
| 1, hdist, vdist); |
| fprintf(fout, " %g %g %g %g %g %g %g %g", hdist[0], hdist[1], hdist[2], |
| hdist[3], vdist[0], vdist[1], vdist[2], vdist[3]); |
| |
| fprintf(fout, " %d %" PRId64, x->rdmult, rd); |
| |
| fprintf(fout, "\n"); |
| fclose(fout); |
| } |
| #endif // CONFIG_COLLECT_RD_STATS == 1 |
| |
| #if CONFIG_COLLECT_RD_STATS >= 2 |
| static int64_t get_sse(const AV1_COMP *cpi, const MACROBLOCK *x) { |
| const AV1_COMMON *cm = &cpi->common; |
| const int num_planes = av1_num_planes(cm); |
| const MACROBLOCKD *xd = &x->e_mbd; |
| const MB_MODE_INFO *mbmi = xd->mi[0]; |
| int64_t total_sse = 0; |
| for (int plane = 0; plane < num_planes; ++plane) { |
| const struct macroblock_plane *const p = &x->plane[plane]; |
| const struct macroblockd_plane *const pd = &xd->plane[plane]; |
| const BLOCK_SIZE bs = |
| get_plane_block_size(mbmi->bsize, pd->subsampling_x, pd->subsampling_y); |
| unsigned int sse; |
| |
| if (plane) continue; |
| |
| cpi->ppi->fn_ptr[bs].vf(p->src.buf, p->src.stride, pd->dst.buf, |
| pd->dst.stride, &sse); |
| total_sse += sse; |
| } |
| total_sse <<= 4; |
| return total_sse; |
| } |
| |
| static int get_est_rate_dist(const TileDataEnc *tile_data, BLOCK_SIZE bsize, |
| int64_t sse, int *est_residue_cost, |
| int64_t *est_dist) { |
| const InterModeRdModel *md = &tile_data->inter_mode_rd_models[bsize]; |
| if (md->ready) { |
| if (sse < md->dist_mean) { |
| *est_residue_cost = 0; |
| *est_dist = sse; |
| } else { |
| *est_dist = (int64_t)round(md->dist_mean); |
| const double est_ld = md->a * sse + md->b; |
| // Clamp estimated rate cost by INT_MAX / 2. |
| // TODO(angiebird@google.com): find better solution than clamping. |
| if (fabs(est_ld) < 1e-2) { |
| *est_residue_cost = INT_MAX / 2; |
| } else { |
| double est_residue_cost_dbl = ((sse - md->dist_mean) / est_ld); |
| if (est_residue_cost_dbl < 0) { |
| *est_residue_cost = 0; |
| } else { |
| *est_residue_cost = |
| (int)AOMMIN((int64_t)round(est_residue_cost_dbl), INT_MAX / 2); |
| } |
| } |
| if (*est_residue_cost <= 0) { |
| *est_residue_cost = 0; |
| *est_dist = sse; |
| } |
| } |
| return 1; |
| } |
| return 0; |
| } |
| |
| static double get_highbd_diff_mean(const uint8_t *src8, int src_stride, |
| const uint8_t *dst8, int dst_stride, int w, |
| int h) { |
| const uint16_t *src = CONVERT_TO_SHORTPTR(src8); |
| const uint16_t *dst = CONVERT_TO_SHORTPTR(dst8); |
| double sum = 0.0; |
| for (int j = 0; j < h; ++j) { |
| for (int i = 0; i < w; ++i) { |
| const int diff = src[j * src_stride + i] - dst[j * dst_stride + i]; |
| sum += diff; |
| } |
| } |
| assert(w > 0 && h > 0); |
| return sum / (w * h); |
| } |
| |
| static double get_diff_mean(const uint8_t *src, int src_stride, |
| const uint8_t *dst, int dst_stride, int w, int h) { |
| double sum = 0.0; |
| for (int j = 0; j < h; ++j) { |
| for (int i = 0; i < w; ++i) { |
| const int diff = src[j * src_stride + i] - dst[j * dst_stride + i]; |
| sum += diff; |
| } |
| } |
| assert(w > 0 && h > 0); |
| return sum / (w * h); |
| } |
| |
| static AOM_INLINE void PrintPredictionUnitStats(const AV1_COMP *const cpi, |
| const TileDataEnc *tile_data, |
| MACROBLOCK *x, |
| const RD_STATS *const rd_stats, |
| BLOCK_SIZE plane_bsize) { |
| if (rd_stats->rate == INT_MAX || rd_stats->dist == INT64_MAX) return; |
| |
| if (cpi->sf.inter_sf.inter_mode_rd_model_estimation == 1 && |
| (tile_data == NULL || |
| !tile_data->inter_mode_rd_models[plane_bsize].ready)) |
| return; |
| (void)tile_data; |
| // Generate small sample to restrict output size. |
| static unsigned int seed = 95014; |
| |
| if ((lcg_rand16(&seed) % (1 << (14 - num_pels_log2_lookup[plane_bsize]))) != |
| 1) |
| return; |
| |
| const char output_file[] = "pu_stats.txt"; |
| FILE *fout = fopen(output_file, "a"); |
| if (!fout) return; |
| |
| MACROBLOCKD *const xd = &x->e_mbd; |
| const int plane = 0; |
| struct macroblock_plane *const p = &x->plane[plane]; |
| struct macroblockd_plane *pd = &xd->plane[plane]; |
| const int diff_stride = block_size_wide[plane_bsize]; |
| int bw, bh; |
| get_txb_dimensions(xd, plane, plane_bsize, 0, 0, plane_bsize, NULL, NULL, &bw, |
| &bh); |
| const int num_samples = bw * bh; |
| const int dequant_shift = (is_cur_buf_hbd(xd)) ? xd->bd - 5 : 3; |
| const int q_step = p->dequant_QTX[1] >> dequant_shift; |
| const int shift = (xd->bd - 8); |
| |
| const double rate_norm = (double)rd_stats->rate / num_samples; |
| const double dist_norm = (double)rd_stats->dist / num_samples; |
| const double rdcost_norm = |
| (double)RDCOST(x->rdmult, rd_stats->rate, rd_stats->dist) / num_samples; |
| |
| fprintf(fout, "%g %g %g", rate_norm, dist_norm, rdcost_norm); |
| |
| const int src_stride = p->src.stride; |
| const uint8_t *const src = p->src.buf; |
| const int dst_stride = pd->dst.stride; |
| const uint8_t *const dst = pd->dst.buf; |
| const int16_t *const src_diff = p->src_diff; |
| |
| int64_t sse = calculate_sse(xd, p, pd, bw, bh); |
| const double sse_norm = (double)sse / num_samples; |
| |
| const unsigned int sad = |
| cpi->ppi->fn_ptr[plane_bsize].sdf(src, src_stride, dst, dst_stride); |
| const double sad_norm = |
| (double)sad / (1 << num_pels_log2_lookup[plane_bsize]); |
| |
| fprintf(fout, " %g %g", sse_norm, sad_norm); |
| |
| double sse_norm_arr[4], sad_norm_arr[4]; |
| get_2x2_normalized_sses_and_sads(cpi, plane_bsize, src, src_stride, dst, |
| dst_stride, src_diff, diff_stride, |
| sse_norm_arr, sad_norm_arr); |
| if (shift) { |
| for (int k = 0; k < 4; ++k) sse_norm_arr[k] /= (1 << (2 * shift)); |
| for (int k = 0; k < 4; ++k) sad_norm_arr[k] /= (1 << shift); |
| } |
| for (int i = 0; i < 4; ++i) { |
| fprintf(fout, " %g", sse_norm_arr[i]); |
| } |
| for (int i = 0; i < 4; ++i) { |
| fprintf(fout, " %g", sad_norm_arr[i]); |
| } |
| |
| fprintf(fout, " %d %d %d %d", q_step, x->rdmult, bw, bh); |
| |
| int model_rate; |
| int64_t model_dist; |
| model_rd_sse_fn[MODELRD_CURVFIT](cpi, x, plane_bsize, plane, sse, num_samples, |
| &model_rate, &model_dist); |
| const double model_rdcost_norm = |
| (double)RDCOST(x->rdmult, model_rate, model_dist) / num_samples; |
| const double model_rate_norm = (double)model_rate / num_samples; |
| const double model_dist_norm = (double)model_dist / num_samples; |
| fprintf(fout, " %g %g %g", model_rate_norm, model_dist_norm, |
| model_rdcost_norm); |
| |
| double mean; |
| if (is_cur_buf_hbd(xd)) { |
| mean = get_highbd_diff_mean(p->src.buf, p->src.stride, pd->dst.buf, |
| pd->dst.stride, bw, bh); |
| } else { |
| mean = get_diff_mean(p->src.buf, p->src.stride, pd->dst.buf, pd->dst.stride, |
| bw, bh); |
| } |
| mean /= (1 << shift); |
| float hor_corr, vert_corr; |
| av1_get_horver_correlation_full(src_diff, diff_stride, bw, bh, &hor_corr, |
| &vert_corr); |
| fprintf(fout, " %g %g %g", mean, hor_corr, vert_corr); |
| |
| double hdist[4] = { 0 }, vdist[4] = { 0 }; |
| get_energy_distribution_fine(cpi, plane_bsize, src, src_stride, dst, |
| dst_stride, 1, hdist, vdist); |
| fprintf(fout, " %g %g %g %g %g %g %g %g", hdist[0], hdist[1], hdist[2], |
| hdist[3], vdist[0], vdist[1], vdist[2], vdist[3]); |
| |
| if (cpi->sf.inter_sf.inter_mode_rd_model_estimation == 1) { |
| assert(tile_data->inter_mode_rd_models[plane_bsize].ready); |
| const int64_t overall_sse = get_sse(cpi, x); |
| int est_residue_cost = 0; |
| int64_t est_dist = 0; |
| get_est_rate_dist(tile_data, plane_bsize, overall_sse, &est_residue_cost, |
| &est_dist); |
| const double est_residue_cost_norm = (double)est_residue_cost / num_samples; |
| const double est_dist_norm = (double)est_dist / num_samples; |
| const double est_rdcost_norm = |
| (double)RDCOST(x->rdmult, est_residue_cost, est_dist) / num_samples; |
| fprintf(fout, " %g %g %g", est_residue_cost_norm, est_dist_norm, |
| est_rdcost_norm); |
| } |
| |
| fprintf(fout, "\n"); |
| fclose(fout); |
| } |
| #endif // CONFIG_COLLECT_RD_STATS >= 2 |
| #endif // CONFIG_COLLECT_RD_STATS |
| |
| static AOM_INLINE void inverse_transform_block_facade(MACROBLOCK *const x, |
| int plane, int block, |
| int blk_row, int blk_col, |
| int eob, |
| int reduced_tx_set) { |
| if (!eob) return; |
| struct macroblock_plane *const p = &x->plane[plane]; |
| MACROBLOCKD *const xd = &x->e_mbd; |
| tran_low_t *dqcoeff = p->dqcoeff + BLOCK_OFFSET(block); |
| const PLANE_TYPE plane_type = get_plane_type(plane); |
| const TX_SIZE tx_size = av1_get_tx_size(plane, xd); |
| const TX_TYPE tx_type = av1_get_tx_type(xd, plane_type, blk_row, blk_col, |
| tx_size, reduced_tx_set); |
| |
| struct macroblockd_plane *const pd = &xd->plane[plane]; |
| const int dst_stride = pd->dst.stride; |
| uint8_t *dst = &pd->dst.buf[(blk_row * dst_stride + blk_col) << MI_SIZE_LOG2]; |
| av1_inverse_transform_block(xd, dqcoeff, plane, tx_type, tx_size, dst, |
| dst_stride, eob, reduced_tx_set); |
| } |
| |
| static INLINE void recon_intra(const AV1_COMP *cpi, MACROBLOCK *x, int plane, |
| int block, int blk_row, int blk_col, |
| BLOCK_SIZE plane_bsize, TX_SIZE tx_size, |
| const TXB_CTX *const txb_ctx, int skip_trellis, |
| TX_TYPE best_tx_type, int do_quant, |
| int *rate_cost, uint16_t best_eob) { |
| const AV1_COMMON *cm = &cpi->common; |
| MACROBLOCKD *xd = &x->e_mbd; |
| MB_MODE_INFO *mbmi = xd->mi[0]; |
| const int is_inter = is_inter_block(mbmi); |
| if (!is_inter && best_eob && |
| (blk_row + tx_size_high_unit[tx_size] < mi_size_high[plane_bsize] || |
| blk_col + tx_size_wide_unit[tx_size] < mi_size_wide[plane_bsize])) { |
| // if the quantized coefficients are stored in the dqcoeff buffer, we don't |
| // need to do transform and quantization again. |
| if (do_quant) { |
| TxfmParam txfm_param_intra; |
| QUANT_PARAM quant_param_intra; |
| av1_setup_xform(cm, x, tx_size, best_tx_type, &txfm_param_intra); |
| av1_setup_quant(tx_size, !skip_trellis, |
| skip_trellis |
| ? (USE_B_QUANT_NO_TRELLIS ? AV1_XFORM_QUANT_B |
| : AV1_XFORM_QUANT_FP) |
| : AV1_XFORM_QUANT_FP, |
| cpi->oxcf.q_cfg.quant_b_adapt, &quant_param_intra); |
| av1_setup_qmatrix(&cm->quant_params, xd, plane, tx_size, best_tx_type, |
| &quant_param_intra); |
| av1_xform_quant(x, plane, block, blk_row, blk_col, plane_bsize, |
| &txfm_param_intra, &quant_param_intra); |
| if (quant_param_intra.use_optimize_b) { |
| av1_optimize_b(cpi, x, plane, block, tx_size, best_tx_type, txb_ctx, |
| rate_cost); |
| } |
| } |
| |
| inverse_transform_block_facade(x, plane, block, blk_row, blk_col, |
| x->plane[plane].eobs[block], |
| cm->features.reduced_tx_set_used); |
| |
| // This may happen because of hash collision. The eob stored in the hash |
| // table is non-zero, but the real eob is zero. We need to make sure tx_type |
| // is DCT_DCT in this case. |
| if (plane == 0 && x->plane[plane].eobs[block] == 0 && |
| best_tx_type != DCT_DCT) { |
| update_txk_array(xd, blk_row, blk_col, tx_size, DCT_DCT); |
| } |
| } |
| } |
| |
| static unsigned pixel_dist_visible_only( |
| const AV1_COMP *const cpi, const MACROBLOCK *x, const uint8_t *src, |
| const int src_stride, const uint8_t *dst, const int dst_stride, |
| const BLOCK_SIZE tx_bsize, int txb_rows, int txb_cols, int visible_rows, |
| int visible_cols) { |
| unsigned sse; |
| |
| if (txb_rows == visible_rows && txb_cols == visible_cols) { |
| cpi->ppi->fn_ptr[tx_bsize].vf(src, src_stride, dst, dst_stride, &sse); |
| return sse; |
| } |
| |
| #if CONFIG_AV1_HIGHBITDEPTH |
| const MACROBLOCKD *xd = &x->e_mbd; |
| if (is_cur_buf_hbd(xd)) { |
| uint64_t sse64 = aom_highbd_sse_odd_size(src, src_stride, dst, dst_stride, |
| visible_cols, visible_rows); |
| return (unsigned int)ROUND_POWER_OF_TWO(sse64, (xd->bd - 8) * 2); |
| } |
| #else |
| (void)x; |
| #endif |
| sse = aom_sse_odd_size(src, src_stride, dst, dst_stride, visible_cols, |
| visible_rows); |
| return sse; |
| } |
| |
| // Compute the pixel domain distortion from src and dst on all visible 4x4s in |
| // the |
| // transform block. |
| static unsigned pixel_dist(const AV1_COMP *const cpi, const MACROBLOCK *x, |
| int plane, const uint8_t *src, const int src_stride, |
| const uint8_t *dst, const int dst_stride, |
| int blk_row, int blk_col, |
| const BLOCK_SIZE plane_bsize, |
| const BLOCK_SIZE tx_bsize) { |
| int txb_rows, txb_cols, visible_rows, visible_cols; |
| const MACROBLOCKD *xd = &x->e_mbd; |
| |
| get_txb_dimensions(xd, plane, plane_bsize, blk_row, blk_col, tx_bsize, |
| &txb_cols, &txb_rows, &visible_cols, &visible_rows); |
| assert(visible_rows > 0); |
| assert(visible_cols > 0); |
| |
| unsigned sse = pixel_dist_visible_only(cpi, x, src, src_stride, dst, |
| dst_stride, tx_bsize, txb_rows, |
| txb_cols, visible_rows, visible_cols); |
| |
| return sse; |
| } |
| |
| static INLINE int64_t dist_block_px_domain(const AV1_COMP *cpi, MACROBLOCK *x, |
| int plane, BLOCK_SIZE plane_bsize, |
| int block, int blk_row, int blk_col, |
| TX_SIZE tx_size) { |
| MACROBLOCKD *const xd = &x->e_mbd; |
| const struct macroblock_plane *const p = &x->plane[plane]; |
| const uint16_t eob = p->eobs[block]; |
| const BLOCK_SIZE tx_bsize = txsize_to_bsize[tx_size]; |
| const int bsw = block_size_wide[tx_bsize]; |
| const int bsh = block_size_high[tx_bsize]; |
| const int src_stride = x->plane[plane].src.stride; |
| const int dst_stride = xd->plane[plane].dst.stride; |
| // Scale the transform block index to pixel unit. |
| const int src_idx = (blk_row * src_stride + blk_col) << MI_SIZE_LOG2; |
| const int dst_idx = (blk_row * dst_stride + blk_col) << MI_SIZE_LOG2; |
| const uint8_t *src = &x->plane[plane].src.buf[src_idx]; |
| const uint8_t *dst = &xd->plane[plane].dst.buf[dst_idx]; |
| const tran_low_t *dqcoeff = p->dqcoeff + BLOCK_OFFSET(block); |
| |
| assert(cpi != NULL); |
| assert(tx_size_wide_log2[0] == tx_size_high_log2[0]); |
| |
| uint8_t *recon; |
| DECLARE_ALIGNED(16, uint16_t, recon16[MAX_TX_SQUARE]); |
| |
| #if CONFIG_AV1_HIGHBITDEPTH |
| if (is_cur_buf_hbd(xd)) { |
| recon = CONVERT_TO_BYTEPTR(recon16); |
| aom_highbd_convolve_copy(CONVERT_TO_SHORTPTR(dst), dst_stride, |
| CONVERT_TO_SHORTPTR(recon), MAX_TX_SIZE, bsw, bsh); |
| } else { |
| recon = (uint8_t *)recon16; |
| aom_convolve_copy(dst, dst_stride, recon, MAX_TX_SIZE, bsw, bsh); |
| } |
| #else |
| recon = (uint8_t *)recon16; |
| aom_convolve_copy(dst, dst_stride, recon, MAX_TX_SIZE, bsw, bsh); |
| #endif |
| |
| const PLANE_TYPE plane_type = get_plane_type(plane); |
| TX_TYPE tx_type = av1_get_tx_type(xd, plane_type, blk_row, blk_col, tx_size, |
| cpi->common.features.reduced_tx_set_used); |
| av1_inverse_transform_block(xd, dqcoeff, plane, tx_type, tx_size, recon, |
| MAX_TX_SIZE, eob, |
| cpi->common.features.reduced_tx_set_used); |
| |
| return 16 * pixel_dist(cpi, x, plane, src, src_stride, recon, MAX_TX_SIZE, |
| blk_row, blk_col, plane_bsize, tx_bsize); |
| } |
| |
| // pruning thresholds for prune_txk_type and prune_txk_type_separ |
| static const int prune_factors[5] = { 200, 200, 120, 80, 40 }; // scale 1000 |
| static const int mul_factors[5] = { 80, 80, 70, 50, 30 }; // scale 100 |
| |
| // R-D costs are sorted in ascending order. |
| static INLINE void sort_rd(int64_t rds[], int txk[], int len) { |
| int i, j, k; |
| |
| for (i = 1; i <= len - 1; ++i) { |
| for (j = 0; j < i; ++j) { |
| if (rds[j] > rds[i]) { |
| int64_t temprd; |
| int tempi; |
| |
| temprd = rds[i]; |
| tempi = txk[i]; |
| |
| for (k = i; k > j; k--) { |
| rds[k] = rds[k - 1]; |
| txk[k] = txk[k - 1]; |
| } |
| |
| rds[j] = temprd; |
| txk[j] = tempi; |
| break; |
| } |
| } |
| } |
| } |
| |
| static INLINE int64_t av1_block_error_qm(const tran_low_t *coeff, |
| const tran_low_t *dqcoeff, |
| intptr_t block_size, |
| const qm_val_t *qmatrix, |
| const int16_t *scan, int64_t *ssz) { |
| int i; |
| int64_t error = 0, sqcoeff = 0; |
| |
| for (i = 0; i < block_size; i++) { |
| int64_t weight = qmatrix[scan[i]]; |
| int64_t dd = coeff[i] - dqcoeff[i]; |
| dd *= weight; |
| int64_t cc = coeff[i]; |
| cc *= weight; |
| // The ranges of coeff and dqcoeff are |
| // bd8 : 18 bits (including sign) |
| // bd10: 20 bits (including sign) |
| // bd12: 22 bits (including sign) |
| // As AOM_QM_BITS is 5, the intermediate quantities in the calculation |
| // below should fit in 54 bits, thus no overflow should happen. |
| error += (dd * dd + (1 << (2 * AOM_QM_BITS - 1))) >> (2 * AOM_QM_BITS); |
| sqcoeff += (cc * cc + (1 << (2 * AOM_QM_BITS - 1))) >> (2 * AOM_QM_BITS); |
| } |
| |
| *ssz = sqcoeff; |
| return error; |
| } |
| |
| static INLINE void dist_block_tx_domain(MACROBLOCK *x, int plane, int block, |
| TX_SIZE tx_size, |
| const qm_val_t *qmatrix, |
| const int16_t *scan, int64_t *out_dist, |
| int64_t *out_sse) { |
| const struct macroblock_plane *const p = &x->plane[plane]; |
| // Transform domain distortion computation is more efficient as it does |
| // not involve an inverse transform, but it is less accurate. |
| const int buffer_length = av1_get_max_eob(tx_size); |
| int64_t this_sse; |
| // TX-domain results need to shift down to Q2/D10 to match pixel |
| // domain distortion values which are in Q2^2 |
| int shift = (MAX_TX_SCALE - av1_get_tx_scale(tx_size)) * 2; |
| const int block_offset = BLOCK_OFFSET(block); |
| tran_low_t *const coeff = p->coeff + block_offset; |
| tran_low_t *const dqcoeff = p->dqcoeff + block_offset; |
| #if CONFIG_AV1_HIGHBITDEPTH |
| MACROBLOCKD *const xd = &x->e_mbd; |
| if (is_cur_buf_hbd(xd)) { |
| // TODO(veluca): handle use_qm_dist_metric for HBD too. |
| *out_dist = av1_highbd_block_error(coeff, dqcoeff, buffer_length, &this_sse, |
| xd->bd); |
| } else { |
| #endif |
| if (qmatrix == NULL || !x->txfm_search_params.use_qm_dist_metric) { |
| *out_dist = av1_block_error(coeff, dqcoeff, buffer_length, &this_sse); |
| } else { |
| *out_dist = av1_block_error_qm(coeff, dqcoeff, buffer_length, qmatrix, |
| scan, &this_sse); |
| } |
| #if CONFIG_AV1_HIGHBITDEPTH |
| } |
| #endif |
| |
| *out_dist = RIGHT_SIGNED_SHIFT(*out_dist, shift); |
| *out_sse = RIGHT_SIGNED_SHIFT(this_sse, shift); |
| } |
| |
| uint16_t prune_txk_type_separ(const AV1_COMP *cpi, MACROBLOCK *x, int plane, |
| int block, TX_SIZE tx_size, int blk_row, |
| int blk_col, BLOCK_SIZE plane_bsize, int *txk_map, |
| int16_t allowed_tx_mask, int prune_factor, |
| const TXB_CTX *const txb_ctx, |
| int reduced_tx_set_used, int64_t ref_best_rd, |
| int num_sel) { |
| const AV1_COMMON *cm = &cpi->common; |
| MACROBLOCKD *xd = &x->e_mbd; |
| |
| int idx; |
| |
| int64_t rds_v[4]; |
| int64_t rds_h[4]; |
| int idx_v[4] = { 0, 1, 2, 3 }; |
| int idx_h[4] = { 0, 1, 2, 3 }; |
| int skip_v[4] = { 0 }; |
| int skip_h[4] = { 0 }; |
| const int idx_map[16] = { |
| DCT_DCT, DCT_ADST, DCT_FLIPADST, V_DCT, |
| ADST_DCT, ADST_ADST, ADST_FLIPADST, V_ADST, |
| FLIPADST_DCT, FLIPADST_ADST, FLIPADST_FLIPADST, V_FLIPADST, |
| H_DCT, H_ADST, H_FLIPADST, IDTX |
| }; |
| |
| const int sel_pattern_v[16] = { |
| 0, 0, 1, 1, 0, 2, 1, 2, 2, 0, 3, 1, 3, 2, 3, 3 |
| }; |
| const int sel_pattern_h[16] = { |
| 0, 1, 0, 1, 2, 0, 2, 1, 2, 3, 0, 3, 1, 3, 2, 3 |
| }; |
| |
| QUANT_PARAM quant_param; |
| TxfmParam txfm_param; |
| av1_setup_xform(cm, x, tx_size, DCT_DCT, &txfm_param); |
| av1_setup_quant(tx_size, 1, AV1_XFORM_QUANT_B, cpi->oxcf.q_cfg.quant_b_adapt, |
| &quant_param); |
| int tx_type; |
| // to ensure we can try ones even outside of ext_tx_set of current block |
| // this function should only be called for size < 16 |
| assert(txsize_sqr_up_map[tx_size] <= TX_16X16); |
| txfm_param.tx_set_type = EXT_TX_SET_ALL16; |
| |
| int rate_cost = 0; |
| int64_t dist = 0, sse = 0; |
| // evaluate horizontal with vertical DCT |
| for (idx = 0; idx < 4; ++idx) { |
| tx_type = idx_map[idx]; |
| txfm_param.tx_type = tx_type; |
| |
| av1_setup_qmatrix(&cm->quant_params, xd, plane, tx_size, tx_type, |
| &quant_param); |
| |
| av1_xform_quant(x, plane, block, blk_row, blk_col, plane_bsize, &txfm_param, |
| &quant_param); |
| |
| const SCAN_ORDER *const scan_order = |
| get_scan(txfm_param.tx_size, txfm_param.tx_type); |
| dist_block_tx_domain(x, plane, block, tx_size, quant_param.qmatrix, |
| scan_order->scan, &dist, &sse); |
| |
| rate_cost = av1_cost_coeffs_txb_laplacian(x, plane, block, tx_size, tx_type, |
| txb_ctx, reduced_tx_set_used, 0); |
| |
| rds_h[idx] = RDCOST(x->rdmult, rate_cost, dist); |
| |
| if ((rds_h[idx] - (rds_h[idx] >> 2)) > ref_best_rd) { |
| skip_h[idx] = 1; |
| } |
| } |
| sort_rd(rds_h, idx_h, 4); |
| for (idx = 1; idx < 4; idx++) { |
| if (rds_h[idx] > rds_h[0] * 1.2) skip_h[idx_h[idx]] = 1; |
| } |
| |
| if (skip_h[idx_h[0]]) return (uint16_t)0xFFFF; |
| |
| // evaluate vertical with the best horizontal chosen |
| rds_v[0] = rds_h[0]; |
| int start_v = 1, end_v = 4; |
| const int *idx_map_v = idx_map + idx_h[0]; |
| |
| for (idx = start_v; idx < end_v; ++idx) { |
| tx_type = idx_map_v[idx_v[idx] * 4]; |
| txfm_param.tx_type = tx_type; |
| |
| av1_setup_qmatrix(&cm->quant_params, xd, plane, tx_size, tx_type, |
| &quant_param); |
| |
| av1_xform_quant(x, plane, block, blk_row, blk_col, plane_bsize, &txfm_param, |
| &quant_param); |
| |
| const SCAN_ORDER *const scan_order = |
| get_scan(txfm_param.tx_size, txfm_param.tx_type); |
| dist_block_tx_domain(x, plane, block, tx_size, quant_param.qmatrix, |
| scan_order->scan, &dist, &sse); |
| |
| rate_cost = av1_cost_coeffs_txb_laplacian(x, plane, block, tx_size, tx_type, |
| txb_ctx, reduced_tx_set_used, 0); |
| |
| rds_v[idx] = RDCOST(x->rdmult, rate_cost, dist); |
| |
| if ((rds_v[idx] - (rds_v[idx] >> 2)) > ref_best_rd) { |
| skip_v[idx] = 1; |
| } |
| } |
| sort_rd(rds_v, idx_v, 4); |
| for (idx = 1; idx < 4; idx++) { |
| if (rds_v[idx] > rds_v[0] * 1.2) skip_v[idx_v[idx]] = 1; |
| } |
| |
| // combine rd_h and rd_v to prune tx candidates |
| int i_v, i_h; |
| int64_t rds[16]; |
| int num_cand = 0, last = TX_TYPES - 1; |
| |
| for (int i = 0; i < 16; i++) { |
| i_v = sel_pattern_v[i]; |
| i_h = sel_pattern_h[i]; |
| tx_type = idx_map[idx_v[i_v] * 4 + idx_h[i_h]]; |
| if (!(allowed_tx_mask & (1 << tx_type)) || skip_h[idx_h[i_h]] || |
| skip_v[idx_v[i_v]]) { |
| txk_map[last] = tx_type; |
| last--; |
| } else { |
| txk_map[num_cand] = tx_type; |
| rds[num_cand] = rds_v[i_v] + rds_h[i_h]; |
| if (rds[num_cand] == 0) rds[num_cand] = 1; |
| num_cand++; |
| } |
| } |
| sort_rd(rds, txk_map, num_cand); |
| |
| uint16_t prune = (uint16_t)(~(1 << txk_map[0])); |
| num_sel = AOMMIN(num_sel, num_cand); |
| |
| for (int i = 1; i < num_sel; i++) { |
| int64_t factor = 1800 * (rds[i] - rds[0]) / (rds[0]); |
| if (factor < (int64_t)prune_factor) |
| prune &= ~(1 << txk_map[i]); |
| else |
| break; |
| } |
| return prune; |
| } |
| |
| uint16_t prune_txk_type(const AV1_COMP *cpi, MACROBLOCK *x, int plane, |
| int block, TX_SIZE tx_size, int blk_row, int blk_col, |
| BLOCK_SIZE plane_bsize, int *txk_map, |
| uint16_t allowed_tx_mask, int prune_factor, |
| const TXB_CTX *const txb_ctx, int reduced_tx_set_used) { |
| const AV1_COMMON *cm = &cpi->common; |
| MACROBLOCKD *xd = &x->e_mbd; |
| int tx_type; |
| |
| int64_t rds[TX_TYPES]; |
| |
| int num_cand = 0; |
| int last = TX_TYPES - 1; |
| |
| TxfmParam txfm_param; |
| QUANT_PARAM quant_param; |
| av1_setup_xform(cm, x, tx_size, DCT_DCT, &txfm_param); |
| av1_setup_quant(tx_size, 1, AV1_XFORM_QUANT_B, cpi->oxcf.q_cfg.quant_b_adapt, |
| &quant_param); |
| |
| for (int idx = 0; idx < TX_TYPES; idx++) { |
| tx_type = idx; |
| int rate_cost = 0; |
| int64_t dist = 0, sse = 0; |
| if (!(allowed_tx_mask & (1 << tx_type))) { |
| txk_map[last] = tx_type; |
| last--; |
| continue; |
| } |
| txfm_param.tx_type = tx_type; |
| |
| av1_setup_qmatrix(&cm->quant_params, xd, plane, tx_size, tx_type, |
| &quant_param); |
| |
| // do txfm and quantization |
| av1_xform_quant(x, plane, block, blk_row, blk_col, plane_bsize, &txfm_param, |
| &quant_param); |
| // estimate rate cost |
| rate_cost = av1_cost_coeffs_txb_laplacian(x, plane, block, tx_size, tx_type, |
| txb_ctx, reduced_tx_set_used, 0); |
| // tx domain dist |
| const SCAN_ORDER *const scan_order = |
| get_scan(txfm_param.tx_size, txfm_param.tx_type); |
| dist_block_tx_domain(x, plane, block, tx_size, quant_param.qmatrix, |
| scan_order->scan, &dist, &sse); |
| |
| txk_map[num_cand] = tx_type; |
| rds[num_cand] = RDCOST(x->rdmult, rate_cost, dist); |
| if (rds[num_cand] == 0) rds[num_cand] = 1; |
| num_cand++; |
| } |
| |
| if (num_cand == 0) return (uint16_t)0xFFFF; |
| |
| sort_rd(rds, txk_map, num_cand); |
| uint16_t prune = (uint16_t)(~(1 << txk_map[0])); |
| |
| // 0 < prune_factor <= 1000 controls aggressiveness |
| int64_t factor = 0; |
| for (int idx = 1; idx < num_cand; idx++) { |
| factor = 1000 * (rds[idx] - rds[0]) / rds[0]; |
| if (factor < (int64_t)prune_factor) |
| prune &= ~(1 << txk_map[idx]); |
| else |
| break; |
| } |
| return prune; |
| } |
| |
| // These thresholds were calibrated to provide a certain number of TX types |
| // pruned by the model on average, i.e. selecting a threshold with index i |
| // will lead to pruning i+1 TX types on average |
| static const float *prune_2D_adaptive_thresholds[] = { |
| // TX_4X4 |
| (float[]){ 0.00549f, 0.01306f, 0.02039f, 0.02747f, 0.03406f, 0.04065f, |
| 0.04724f, 0.05383f, 0.06067f, 0.06799f, 0.07605f, 0.08533f, |
| 0.09778f, 0.11780f }, |
| // TX_8X8 |
| (float[]){ 0.00037f, 0.00183f, 0.00525f, 0.01038f, 0.01697f, 0.02502f, |
| 0.03381f, 0.04333f, 0.05286f, 0.06287f, 0.07434f, 0.08850f, |
| 0.10803f, 0.14124f }, |
| // TX_16X16 |
| (float[]){ 0.01404f, 0.02000f, 0.04211f, 0.05164f, 0.05798f, 0.06335f, |
| 0.06897f, 0.07629f, 0.08875f, 0.11169f }, |
| // TX_32X32 |
| NULL, |
| // TX_64X64 |
| NULL, |
| // TX_4X8 |
| (float[]){ 0.00183f, 0.00745f, 0.01428f, 0.02185f, 0.02966f, 0.03723f, |
| 0.04456f, 0.05188f, 0.05920f, 0.06702f, 0.07605f, 0.08704f, |
| 0.10168f, 0.12585f }, |
| // TX_8X4 |
| (float[]){ 0.00085f, 0.00476f, 0.01135f, 0.01892f, 0.02698f, 0.03528f, |
| 0.04358f, 0.05164f, 0.05994f, 0.06848f, 0.07849f, 0.09021f, |
| 0.10583f, 0.13123f }, |
| // TX_8X16 |
| (float[]){ 0.00037f, 0.00232f, 0.00671f, 0.01257f, 0.01965f, 0.02722f, |
| 0.03552f, 0.04382f, 0.05237f, 0.06189f, 0.07336f, 0.08728f, |
| 0.10730f, 0.14221f }, |
| // TX_16X8 |
| (float[]){ 0.00061f, 0.00330f, 0.00818f, 0.01453f, 0.02185f, 0.02966f, |
| 0.03772f, 0.04578f, 0.05383f, 0.06262f, 0.07288f, 0.08582f, |
| 0.10339f, 0.13464f }, |
| // TX_16X32 |
| NULL, |
| // TX_32X16 |
| NULL, |
| // TX_32X64 |
| NULL, |
| // TX_64X32 |
| NULL, |
| // TX_4X16 |
| (float[]){ 0.00232f, 0.00671f, 0.01257f, 0.01941f, 0.02673f, 0.03430f, |
| 0.04211f, 0.04968f, 0.05750f, 0.06580f, 0.07507f, 0.08655f, |
| 0.10242f, 0.12878f }, |
| // TX_16X4 |
| (float[]){ 0.00110f, 0.00525f, 0.01208f, 0.01990f, 0.02795f, 0.03601f, |
| 0.04358f, 0.05115f, 0.05896f, 0.06702f, 0.07629f, 0.08752f, |
| 0.10217f, 0.12610f }, |
| // TX_8X32 |
| NULL, |
| // TX_32X8 |
| NULL, |
| // TX_16X64 |
| NULL, |
| // TX_64X16 |
| NULL, |
| }; |
| |
| static INLINE float get_adaptive_thresholds( |
| TX_SIZE tx_size, TxSetType tx_set_type, |
| TX_TYPE_PRUNE_MODE prune_2d_txfm_mode) { |
| const int prune_aggr_table[5][2] = { |
| { 4, 1 }, { 6, 3 }, { 9, 6 }, { 9, 6 }, { 12, 9 } |
| }; |
| int pruning_aggressiveness = 0; |
| if (tx_set_type == EXT_TX_SET_ALL16) |
| pruning_aggressiveness = |
| prune_aggr_table[prune_2d_txfm_mode - TX_TYPE_PRUNE_1][0]; |
| else if (tx_set_type == EXT_TX_SET_DTT9_IDTX_1DDCT) |
| pruning_aggressiveness = |
| prune_aggr_table[prune_2d_txfm_mode - TX_TYPE_PRUNE_1][1]; |
| |
| return prune_2D_adaptive_thresholds[tx_size][pruning_aggressiveness]; |
| } |
| |
| static AOM_INLINE void get_energy_distribution_finer(const int16_t *diff, |
| int stride, int bw, int bh, |
| float *hordist, |
| float *verdist) { |
| // First compute downscaled block energy values (esq); downscale factors |
| // are defined by w_shift and h_shift. |
| unsigned int esq[256]; |
| const int w_shift = bw <= 8 ? 0 : 1; |
| const int h_shift = bh <= 8 ? 0 : 1; |
| const int esq_w = bw >> w_shift; |
| const int esq_h = bh >> h_shift; |
| const int esq_sz = esq_w * esq_h; |
| int i, j; |
| memset(esq, 0, esq_sz * sizeof(esq[0])); |
| if (w_shift) { |
| for (i = 0; i < bh; i++) { |
| unsigned int *cur_esq_row = esq + (i >> h_shift) * esq_w; |
| const int16_t *cur_diff_row = diff + i * stride; |
| for (j = 0; j < bw; j += 2) { |
| cur_esq_row[j >> 1] += (cur_diff_row[j] * cur_diff_row[j] + |
| cur_diff_row[j + 1] * cur_diff_row[j + 1]); |
| } |
| } |
| } else { |
| for (i = 0; i < bh; i++) { |
| unsigned int *cur_esq_row = esq + (i >> h_shift) * esq_w; |
| const int16_t *cur_diff_row = diff + i * stride; |
| for (j = 0; j < bw; j++) { |
| cur_esq_row[j] += cur_diff_row[j] * cur_diff_row[j]; |
| } |
| } |
| } |
| |
| uint64_t total = 0; |
| for (i = 0; i < esq_sz; i++) total += esq[i]; |
| |
| // Output hordist and verdist arrays are normalized 1D projections of esq |
| if (total == 0) { |
| float hor_val = 1.0f / esq_w; |
| for (j = 0; j < esq_w - 1; j++) hordist[j] = hor_val; |
| float ver_val = 1.0f / esq_h; |
| for (i = 0; i < esq_h - 1; i++) verdist[i] = ver_val; |
| return; |
| } |
| |
| const float e_recip = 1.0f / (float)total; |
| memset(hordist, 0, (esq_w - 1) * sizeof(hordist[0])); |
| memset(verdist, 0, (esq_h - 1) * sizeof(verdist[0])); |
| const unsigned int *cur_esq_row; |
| for (i = 0; i < esq_h - 1; i++) { |
| cur_esq_row = esq + i * esq_w; |
| for (j = 0; j < esq_w - 1; j++) { |
| hordist[j] += (float)cur_esq_row[j]; |
| verdist[i] += (float)cur_esq_row[j]; |
| } |
| verdist[i] += (float)cur_esq_row[j]; |
| } |
| cur_esq_row = esq + i * esq_w; |
| for (j = 0; j < esq_w - 1; j++) hordist[j] += (float)cur_esq_row[j]; |
| |
| for (j = 0; j < esq_w - 1; j++) hordist[j] *= e_recip; |
| for (i = 0; i < esq_h - 1; i++) verdist[i] *= e_recip; |
| } |
| |
| static AOM_INLINE bool check_bit_mask(uint16_t mask, int val) { |
| return mask & (1 << val); |
| } |
| |
| static AOM_INLINE void set_bit_mask(uint16_t *mask, int val) { |
| *mask |= (1 << val); |
| } |
| |
| static AOM_INLINE void unset_bit_mask(uint16_t *mask, int val) { |
| *mask &= ~(1 << val); |
| } |
| |
| static void prune_tx_2D(MACROBLOCK *x, BLOCK_SIZE bsize, TX_SIZE tx_size, |
| int blk_row, int blk_col, TxSetType tx_set_type, |
| TX_TYPE_PRUNE_MODE prune_2d_txfm_mode, int *txk_map, |
| uint16_t *allowed_tx_mask) { |
| // This table is used because the search order is different from the enum |
| // order. |
| static const int tx_type_table_2D[16] = { |
| DCT_DCT, DCT_ADST, DCT_FLIPADST, V_DCT, |
| ADST_DCT, ADST_ADST, ADST_FLIPADST, V_ADST, |
| FLIPADST_DCT, FLIPADST_ADST, FLIPADST_FLIPADST, V_FLIPADST, |
| H_DCT, H_ADST, H_FLIPADST, IDTX |
| }; |
| if (tx_set_type != EXT_TX_SET_ALL16 && |
| tx_set_type != EXT_TX_SET_DTT9_IDTX_1DDCT) |
| return; |
| #if CONFIG_NN_V2 |
| NN_CONFIG_V2 *nn_config_hor = av1_tx_type_nnconfig_map_hor[tx_size]; |
| NN_CONFIG_V2 *nn_config_ver = av1_tx_type_nnconfig_map_ver[tx_size]; |
| #else |
| const NN_CONFIG *nn_config_hor = av1_tx_type_nnconfig_map_hor[tx_size]; |
| const NN_CONFIG *nn_config_ver = av1_tx_type_nnconfig_map_ver[tx_size]; |
| #endif |
| if (!nn_config_hor || !nn_config_ver) return; // Model not established yet. |
| |
| float hfeatures[16], vfeatures[16]; |
| float hscores[4], vscores[4]; |
| float scores_2D_raw[16]; |
| const int bw = tx_size_wide[tx_size]; |
| const int bh = tx_size_high[tx_size]; |
| const int hfeatures_num = bw <= 8 ? bw : bw / 2; |
| const int vfeatures_num = bh <= 8 ? bh : bh / 2; |
| assert(hfeatures_num <= 16); |
| assert(vfeatures_num <= 16); |
| |
| const struct macroblock_plane *const p = &x->plane[0]; |
| const int diff_stride = block_size_wide[bsize]; |
| const int16_t *diff = p->src_diff + 4 * blk_row * diff_stride + 4 * blk_col; |
| get_energy_distribution_finer(diff, diff_stride, bw, bh, hfeatures, |
| vfeatures); |
| |
| av1_get_horver_correlation_full(diff, diff_stride, bw, bh, |
| &hfeatures[hfeatures_num - 1], |
| &vfeatures[vfeatures_num - 1]); |
| |
| #if CONFIG_NN_V2 |
| av1_nn_predict_v2(hfeatures, nn_config_hor, 0, hscores); |
| av1_nn_predict_v2(vfeatures, nn_config_ver, 0, vscores); |
| #else |
| av1_nn_predict(hfeatures, nn_config_hor, 1, hscores); |
| av1_nn_predict(vfeatures, nn_config_ver, 1, vscores); |
| #endif |
| |
| for (int i = 0; i < 4; i++) { |
| float *cur_scores_2D = scores_2D_raw + i * 4; |
| cur_scores_2D[0] = vscores[i] * hscores[0]; |
| cur_scores_2D[1] = vscores[i] * hscores[1]; |
| cur_scores_2D[2] = vscores[i] * hscores[2]; |
| cur_scores_2D[3] = vscores[i] * hscores[3]; |
| } |
| |
| assert(TX_TYPES == 16); |
| // This version of the function only works when there are at most 16 classes. |
| // So we will need to change the optimization or use av1_nn_softmax instead if |
| // this ever gets changed. |
| av1_nn_fast_softmax_16(scores_2D_raw, scores_2D_raw); |
| |
| const float score_thresh = |
| get_adaptive_thresholds(tx_size, tx_set_type, prune_2d_txfm_mode); |
| |
| // Always keep the TX type with the highest score, prune all others with |
| // score below score_thresh. |
| int max_score_i = 0; |
| float max_score = 0.0f; |
| uint16_t allow_bitmask = 0; |
| float sum_score = 0.0; |
| // Calculate sum of allowed tx type score and Populate allow bit mask based |
| // on score_thresh and allowed_tx_mask |
| int allow_count = 0; |
| int tx_type_allowed[16] = { TX_TYPE_INVALID, TX_TYPE_INVALID, TX_TYPE_INVALID, |
| TX_TYPE_INVALID, TX_TYPE_INVALID, TX_TYPE_INVALID, |
| TX_TYPE_INVALID, TX_TYPE_INVALID, TX_TYPE_INVALID, |
| TX_TYPE_INVALID, TX_TYPE_INVALID, TX_TYPE_INVALID, |
| TX_TYPE_INVALID, TX_TYPE_INVALID, TX_TYPE_INVALID, |
| TX_TYPE_INVALID }; |
| float scores_2D[16] = { |
| -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, |
| }; |
| for (int tx_idx = 0; tx_idx < TX_TYPES; tx_idx++) { |
| const int allow_tx_type = |
| check_bit_mask(*allowed_tx_mask, tx_type_table_2D[tx_idx]); |
| if (!allow_tx_type) { |
| continue; |
| } |
| if (scores_2D_raw[tx_idx] > max_score) { |
| max_score = scores_2D_raw[tx_idx]; |
| max_score_i = tx_idx; |
| } |
| if (scores_2D_raw[tx_idx] >= score_thresh) { |
| // Set allow mask based on score_thresh |
| set_bit_mask(&allow_bitmask, tx_type_table_2D[tx_idx]); |
| |
| // Accumulate score of allowed tx type |
| sum_score += scores_2D_raw[tx_idx]; |
| |
| scores_2D[allow_count] = scores_2D_raw[tx_idx]; |
| tx_type_allowed[allow_count] = tx_type_table_2D[tx_idx]; |
| allow_count += 1; |
| } |
| } |
| if (!check_bit_mask(allow_bitmask, tx_type_table_2D[max_score_i])) { |
| // If even the tx_type with max score is pruned, this means that no other |
| // tx_type is feasible. When this happens, we force enable max_score_i and |
| // end the search. |
| set_bit_mask(&allow_bitmask, tx_type_table_2D[max_score_i]); |
| memcpy(txk_map, tx_type_table_2D, sizeof(tx_type_table_2D)); |
| *allowed_tx_mask = allow_bitmask; |
| return; |
| } |
| |
| // Sort tx type probability of all types |
| if (allow_count <= 8) { |
| av1_sort_fi32_8(scores_2D, tx_type_allowed); |
| } else { |
| av1_sort_fi32_16(scores_2D, tx_type_allowed); |
| } |
| |
| // Enable more pruning based on tx type probability and number of allowed tx |
| // types |
| if (prune_2d_txfm_mode >= TX_TYPE_PRUNE_4) { |
| float temp_score = 0.0; |
| float score_ratio = 0.0; |
| int tx_idx, tx_count = 0; |
| const float inv_sum_score = 100 / sum_score; |
| // Get allowed tx types based on sorted probability score and tx count |
| for (tx_idx = 0; tx_idx < allow_count; tx_idx++) { |
| // Skip the tx type which has more than 30% of cumulative |
| // probability and allowed tx type count is more than 2 |
| if (score_ratio > 30.0 && tx_count >= 2) break; |
| |
| assert(check_bit_mask(allow_bitmask, tx_type_allowed[tx_idx])); |
| // Calculate cumulative probability |
| temp_score += scores_2D[tx_idx]; |
| |
| // Calculate percentage of cumulative probability of allowed tx type |
| score_ratio = temp_score * inv_sum_score; |
| tx_count++; |
| } |
| // Set remaining tx types as pruned |
| for (; tx_idx < allow_count; tx_idx++) |
| unset_bit_mask(&allow_bitmask, tx_type_allowed[tx_idx]); |
| } |
| |
| memcpy(txk_map, tx_type_allowed, sizeof(tx_type_table_2D)); |
| *allowed_tx_mask = allow_bitmask; |
| } |
| |
| static float get_dev(float mean, double x2_sum, int num) { |
| const float e_x2 = (float)(x2_sum / num); |
| const float diff = e_x2 - mean * mean; |
| const float dev = (diff > 0) ? sqrtf(diff) : 0; |
| return dev; |
| } |
| |
| // Writes the features required by the ML model to predict tx split based on |
| // mean and standard deviation values of the block and sub-blocks. |
| // Returns the number of elements written to the output array which is at most |
| // 12 currently. Hence 'features' buffer should be able to accommodate at least |
| // 12 elements. |
| static AOM_INLINE int get_mean_dev_features(const int16_t *data, int stride, |
| int bw, int bh, float *features) { |
| const int16_t *const data_ptr = &data[0]; |
| const int subh = (bh >= bw) ? (bh >> 1) : bh; |
| const int subw = (bw >= bh) ? (bw >> 1) : bw; |
| const int num = bw * bh; |
| const int sub_num = subw * subh; |
| int feature_idx = 2; |
| int total_x_sum = 0; |
| int64_t total_x2_sum = 0; |
| int num_sub_blks = 0; |
| double mean2_sum = 0.0f; |
| float dev_sum = 0.0f; |
| |
| for (int row = 0; row < bh; row += subh) { |
| for (int col = 0; col < bw; col += subw) { |
| int x_sum; |
| int64_t x2_sum; |
| // TODO(any): Write a SIMD version. Clear registers. |
| aom_get_blk_sse_sum(data_ptr + row * stride + col, stride, subw, subh, |
| &x_sum, &x2_sum); |
| total_x_sum += x_sum; |
| total_x2_sum += x2_sum; |
| |
| const float mean = (float)x_sum / sub_num; |
| const float dev = get_dev(mean, (double)x2_sum, sub_num); |
| features[feature_idx++] = mean; |
| features[feature_idx++] = dev; |
| mean2_sum += (double)(mean * mean); |
| dev_sum += dev; |
| num_sub_blks++; |
| } |
| } |
| |
| const float lvl0_mean = (float)total_x_sum / num; |
| features[0] = lvl0_mean; |
| features[1] = get_dev(lvl0_mean, (double)total_x2_sum, num); |
| |
| // Deviation of means. |
| features[feature_idx++] = get_dev(lvl0_mean, mean2_sum, num_sub_blks); |
| // Mean of deviations. |
| features[feature_idx++] = dev_sum / num_sub_blks; |
| |
| return feature_idx; |
| } |
| |
| static int ml_predict_tx_split(MACROBLOCK *x, BLOCK_SIZE bsize, int blk_row, |
| int blk_col, TX_SIZE tx_size) { |
| const NN_CONFIG *nn_config = av1_tx_split_nnconfig_map[tx_size]; |
| if (!nn_config) return -1; |
| |
| const int diff_stride = block_size_wide[bsize]; |
| const int16_t *diff = |
| x->plane[0].src_diff + 4 * blk_row * diff_stride + 4 * blk_col; |
| const int bw = tx_size_wide[tx_size]; |
| const int bh = tx_size_high[tx_size]; |
| |
| float features[64] = { 0.0f }; |
| get_mean_dev_features(diff, diff_stride, bw, bh, features); |
| |
| float score = 0.0f; |
| av1_nn_predict(features, nn_config, 1, &score); |
| |
| int int_score = (int)(score * 10000); |
| return clamp(int_score, -80000, 80000); |
| } |
| |
| static INLINE uint16_t |
| get_tx_mask(const AV1_COMP *cpi, MACROBLOCK *x, int plane, int block, |
| int blk_row, int blk_col, BLOCK_SIZE plane_bsize, TX_SIZE tx_size, |
| const TXB_CTX *const txb_ctx, FAST_TX_SEARCH_MODE ftxs_mode, |
| int64_t ref_best_rd, TX_TYPE *allowed_txk_types, int *txk_map) { |
| const AV1_COMMON *cm = &cpi->common; |
| MACROBLOCKD *xd = &x->e_mbd; |
| MB_MODE_INFO *mbmi = xd->mi[0]; |
| const TxfmSearchParams *txfm_params = &x->txfm_search_params; |
| const int is_inter = is_inter_block(mbmi); |
| const int fast_tx_search = ftxs_mode & FTXS_DCT_AND_1D_DCT_ONLY; |
| // if txk_allowed = TX_TYPES, >1 tx types are allowed, else, if txk_allowed < |
| // TX_TYPES, only that specific tx type is allowed. |
| TX_TYPE txk_allowed = TX_TYPES; |
| |
| const FRAME_UPDATE_TYPE update_type = |
| get_frame_update_type(&cpi->ppi->gf_group, cpi->gf_frame_index); |
| int use_actual_frame_probs = 1; |
| const int *tx_type_probs; |
| #if CONFIG_FPMT_TEST |
| use_actual_frame_probs = |
| (cpi->ppi->fpmt_unit_test_cfg == PARALLEL_SIMULATION_ENCODE) ? 0 : 1; |
| if (!use_actual_frame_probs) { |
| tx_type_probs = |
| (int *)cpi->ppi->temp_frame_probs.tx_type_probs[update_type][tx_size]; |
| } |
| #endif |
| if (use_actual_frame_probs) { |
| tx_type_probs = cpi->ppi->frame_probs.tx_type_probs[update_type][tx_size]; |
| } |
| |
| if ((!is_inter && txfm_params->use_default_intra_tx_type) || |
| (is_inter && txfm_params->default_inter_tx_type_prob_thresh == 0)) { |
| txk_allowed = |
| get_default_tx_type(0, xd, tx_size, cpi->use_screen_content_tools); |
| } else if (is_inter && |
| txfm_params->default_inter_tx_type_prob_thresh != INT_MAX) { |
| if (tx_type_probs[DEFAULT_INTER_TX_TYPE] > |
| txfm_params->default_inter_tx_type_prob_thresh) { |
| txk_allowed = DEFAULT_INTER_TX_TYPE; |
| } else { |
| int force_tx_type = 0; |
| int max_prob = 0; |
| const int tx_type_prob_threshold = |
| txfm_params->default_inter_tx_type_prob_thresh + |
| PROB_THRESH_OFFSET_TX_TYPE; |
| for (int i = 1; i < TX_TYPES; i++) { // find maximum probability. |
| if (tx_type_probs[i] > max_prob) { |
| max_prob = tx_type_probs[i]; |
| force_tx_type = i; |
| } |
| } |
| if (max_prob > tx_type_prob_threshold) // force tx type with max prob. |
| txk_allowed = force_tx_type; |
| else if (x->rd_model == LOW_TXFM_RD) { |
| if (plane == 0) txk_allowed = DCT_DCT; |
| } |
| } |
| } else if (x->rd_model == LOW_TXFM_RD) { |
| if (plane == 0) txk_allowed = DCT_DCT; |
| } |
| |
| const TxSetType tx_set_type = av1_get_ext_tx_set_type( |
| tx_size, is_inter, cm->features.reduced_tx_set_used); |
| |
| TX_TYPE uv_tx_type = DCT_DCT; |
| if (plane) { |
| // tx_type of PLANE_TYPE_UV should be the same as PLANE_TYPE_Y |
| uv_tx_type = txk_allowed = |
| av1_get_tx_type(xd, get_plane_type(plane), blk_row, blk_col, tx_size, |
| cm->features.reduced_tx_set_used); |
| } |
| PREDICTION_MODE intra_dir = |
| mbmi->filter_intra_mode_info.use_filter_intra |
| ? fimode_to_intradir[mbmi->filter_intra_mode_info.filter_intra_mode] |
| : mbmi->mode; |
| uint16_t ext_tx_used_flag = |
| cpi->sf.tx_sf.tx_type_search.use_reduced_intra_txset != 0 && |
| tx_set_type == EXT_TX_SET_DTT4_IDTX_1DDCT |
| ? av1_reduced_intra_tx_used_flag[intra_dir] |
| : av1_ext_tx_used_flag[tx_set_type]; |
| |
| if (cpi->sf.tx_sf.tx_type_search.use_reduced_intra_txset == 2) |
| ext_tx_used_flag &= av1_derived_intra_tx_used_flag[intra_dir]; |
| |
| if (xd->lossless[mbmi->segment_id] || txsize_sqr_up_map[tx_size] > TX_32X32 || |
| ext_tx_used_flag == 0x0001 || |
| (is_inter && cpi->oxcf.txfm_cfg.use_inter_dct_only) || |
| (!is_inter && cpi->oxcf.txfm_cfg.use_intra_dct_only)) { |
| txk_allowed = DCT_DCT; |
| } |
| |
| if (cpi->oxcf.txfm_cfg.enable_flip_idtx == 0) |
| ext_tx_used_flag &= DCT_ADST_TX_MASK; |
| |
| uint16_t allowed_tx_mask = 0; // 1: allow; 0: skip. |
| if (txk_allowed < TX_TYPES) { |
| allowed_tx_mask = 1 << txk_allowed; |
| allowed_tx_mask &= ext_tx_used_flag; |
| } else if (fast_tx_search) { |
| allowed_tx_mask = 0x0c01; // V_DCT, H_DCT, DCT_DCT |
| allowed_tx_mask &= ext_tx_used_flag; |
| } else { |
| assert(plane == 0); |
| allowed_tx_mask = ext_tx_used_flag; |
| int num_allowed = 0; |
| int i; |
| |
| if (cpi->sf.tx_sf.tx_type_search.prune_tx_type_using_stats) { |
| static const int thresh_arr[2][7] = { { 10, 15, 15, 10, 15, 15, 15 }, |
| { 10, 17, 17, 10, 17, 17, 17 } }; |
| const int thresh = |
| thresh_arr[cpi->sf.tx_sf.tx_type_search.prune_tx_type_using_stats - 1] |
| [update_type]; |
| uint16_t prune = 0; |
| int max_prob = -1; |
| int max_idx = 0; |
| for (i = 0; i < TX_TYPES; i++) { |
| if (tx_type_probs[i] > max_prob && (allowed_tx_mask & (1 << i))) { |
| max_prob = tx_type_probs[i]; |
| max_idx = i; |
| } |
| if (tx_type_probs[i] < thresh) prune |= (1 << i); |
| } |
| if ((prune >> max_idx) & 0x01) prune &= ~(1 << max_idx); |
| allowed_tx_mask &= (~prune); |
| } |
| for (i = 0; i < TX_TYPES; i++) { |
| if (allowed_tx_mask & (1 << i)) num_allowed++; |
| } |
| assert(num_allowed > 0); |
| |
| if (num_allowed > 2 && cpi->sf.tx_sf.tx_type_search.prune_tx_type_est_rd) { |
| int pf = prune_factors[txfm_params->prune_2d_txfm_mode]; |
| int mf = mul_factors[txfm_params->prune_2d_txfm_mode]; |
| if (num_allowed <= 7) { |
| const uint16_t prune = |
| prune_txk_type(cpi, x, plane, block, tx_size, blk_row, blk_col, |
| plane_bsize, txk_map, allowed_tx_mask, pf, txb_ctx, |
| cm->features.reduced_tx_set_used); |
| allowed_tx_mask &= (~prune); |
| } else { |
| const int num_sel = (num_allowed * mf + 50) / 100; |
| const uint16_t prune = prune_txk_type_separ( |
| cpi, x, plane, block, tx_size, blk_row, blk_col, plane_bsize, |
| txk_map, allowed_tx_mask, pf, txb_ctx, |
| cm->features.reduced_tx_set_used, ref_best_rd, num_sel); |
| |
| allowed_tx_mask &= (~prune); |
| } |
| } else { |
| assert(num_allowed > 0); |
| int allowed_tx_count = |
| (txfm_params->prune_2d_txfm_mode >= TX_TYPE_PRUNE_4) ? 1 : 5; |
| // !fast_tx_search && txk_end != txk_start && plane == 0 |
| if (txfm_params->prune_2d_txfm_mode >= TX_TYPE_PRUNE_1 && is_inter && |
| num_allowed > allowed_tx_count) { |
| prune_tx_2D(x, plane_bsize, tx_size, blk_row, blk_col, tx_set_type, |
| txfm_params->prune_2d_txfm_mode, txk_map, &allowed_tx_mask); |
| } |
| } |
| } |
| |
| // Need to have at least one transform type allowed. |
| if (allowed_tx_mask == 0) { |
| txk_allowed = (plane ? uv_tx_type : DCT_DCT); |
| allowed_tx_mask = (1 << txk_allowed); |
| } |
| |
| assert(IMPLIES(txk_allowed < TX_TYPES, allowed_tx_mask == 1 << txk_allowed)); |
| *allowed_txk_types = txk_allowed; |
| return allowed_tx_mask; |
| } |
| |
| #if CONFIG_RD_DEBUG |
| static INLINE void update_txb_coeff_cost(RD_STATS *rd_stats, int plane, |
| int txb_coeff_cost) { |
| rd_stats->txb_coeff_cost[plane] += txb_coeff_cost; |
| } |
| #endif |
| |
| static INLINE int cost_coeffs(MACROBLOCK *x, int plane, int block, |
| TX_SIZE tx_size, const TX_TYPE tx_type, |
| const TXB_CTX *const txb_ctx, |
| int reduced_tx_set_used) { |
| #if TXCOEFF_COST_TIMER |
| struct aom_usec_timer timer; |
| aom_usec_timer_start(&timer); |
| #endif |
| const int cost = av1_cost_coeffs_txb(x, plane, block, tx_size, tx_type, |
| txb_ctx, reduced_tx_set_used); |
| #if TXCOEFF_COST_TIMER |
| AV1_COMMON *tmp_cm = (AV1_COMMON *)&cpi->common; |
| aom_usec_timer_mark(&timer); |
| const int64_t elapsed_time = aom_usec_timer_elapsed(&timer); |
| tmp_cm->txcoeff_cost_timer += elapsed_time; |
| ++tmp_cm->txcoeff_cost_count; |
| #endif |
| return cost; |
| } |
| |
| static int skip_trellis_opt_based_on_satd(MACROBLOCK *x, |
| QUANT_PARAM *quant_param, int plane, |
| int block, TX_SIZE tx_size, |
| int quant_b_adapt, int qstep, |
| unsigned int coeff_opt_satd_threshold, |
| int skip_trellis, int dc_only_blk) { |
| if (skip_trellis || (coeff_opt_satd_threshold == UINT_MAX)) |
| return skip_trellis; |
| |
| const struct macroblock_plane *const p = &x->plane[plane]; |
| const int block_offset = BLOCK_OFFSET(block); |
| tran_low_t *const coeff_ptr = p->coeff + block_offset; |
| const int n_coeffs = av1_get_max_eob(tx_size); |
| const int shift = (MAX_TX_SCALE - av1_get_tx_scale(tx_size)); |
| int satd = (dc_only_blk) ? abs(coeff_ptr[0]) : aom_satd(coeff_ptr, n_coeffs); |
| satd = RIGHT_SIGNED_SHIFT(satd, shift); |
| satd >>= (x->e_mbd.bd - 8); |
| |
| const int skip_block_trellis = |
| ((uint64_t)satd > |
| (uint64_t)coeff_opt_satd_threshold * qstep * sqrt_tx_pixels_2d[tx_size]); |
| |
| av1_setup_quant( |
| tx_size, !skip_block_trellis, |
| skip_block_trellis |
| ? (USE_B_QUANT_NO_TRELLIS ? AV1_XFORM_QUANT_B : AV1_XFORM_QUANT_FP) |
| : AV1_XFORM_QUANT_FP, |
| quant_b_adapt, quant_param); |
| |
| return skip_block_trellis; |
| } |
| |
| // Predict DC only blocks if the residual variance is below a qstep based |
| // threshold.For such blocks, transform type search is bypassed. |
| static INLINE void predict_dc_only_block( |
| MACROBLOCK *x, int plane, BLOCK_SIZE plane_bsize, TX_SIZE tx_size, |
| int block, int blk_row, int blk_col, RD_STATS *best_rd_stats, |
| int64_t *block_sse, unsigned int *block_mse_q8, int64_t *per_px_mean, |
| int *dc_only_blk) { |
| MACROBLOCKD *xd = &x->e_mbd; |
| MB_MODE_INFO *mbmi = xd->mi[0]; |
| const int dequant_shift = (is_cur_buf_hbd(xd)) ? xd->bd - 5 : 3; |
| const int qstep = x->plane[plane].dequant_QTX[1] >> dequant_shift; |
| uint64_t block_var = UINT64_MAX; |
| const int dc_qstep = x->plane[plane].dequant_QTX[0] >> 3; |
| *block_sse = pixel_diff_stats(x, plane, blk_row, blk_col, plane_bsize, |
| txsize_to_bsize[tx_size], block_mse_q8, |
| per_px_mean, &block_var); |
| assert((*block_mse_q8) != UINT_MAX); |
| uint64_t var_threshold = (uint64_t)(1.8 * qstep * qstep); |
| if (is_cur_buf_hbd(xd)) |
| block_var = ROUND_POWER_OF_TWO(block_var, (xd->bd - 8) * 2); |
| |
| if (block_var >= var_threshold) return; |
| const unsigned int predict_dc_level = x->txfm_search_params.predict_dc_level; |
| assert(predict_dc_level != 0); |
| |
| // Prediction of skip block if residual mean and variance are less |
| // than qstep based threshold |
| if ((llabs(*per_px_mean) * dc_coeff_scale[tx_size]) < (dc_qstep << 12)) { |
| // If the normalized mean of residual block is less than the dc qstep and |
| // the normalized block variance is less than ac qstep, then the block is |
| // assumed to be a skip block and its rdcost is updated accordingly. |
| best_rd_stats->skip_txfm = 1; |
| |
| x->plane[plane].eobs[block] = 0; |
| |
| if (is_cur_buf_hbd(xd)) |
| *block_sse = ROUND_POWER_OF_TWO((*block_sse), (xd->bd - 8) * 2); |
| |
| best_rd_stats->dist = (*block_sse) << 4; |
| best_rd_stats->sse = best_rd_stats->dist; |
| |
| ENTROPY_CONTEXT ctxa[MAX_MIB_SIZE]; |
| ENTROPY_CONTEXT ctxl[MAX_MIB_SIZE]; |
| av1_get_entropy_contexts(plane_bsize, &xd->plane[plane], ctxa, ctxl); |
| ENTROPY_CONTEXT *ta = ctxa; |
| ENTROPY_CONTEXT *tl = ctxl; |
| const TX_SIZE txs_ctx = get_txsize_entropy_ctx(tx_size); |
| TXB_CTX txb_ctx_tmp; |
| const PLANE_TYPE plane_type = get_plane_type(plane); |
| get_txb_ctx(plane_bsize, tx_size, plane, ta, tl, &txb_ctx_tmp); |
| const int zero_blk_rate = x->coeff_costs.coeff_costs[txs_ctx][plane_type] |
| .txb_skip_cost[txb_ctx_tmp.txb_skip_ctx][1]; |
| best_rd_stats->rate = zero_blk_rate; |
| |
| best_rd_stats->rdcost = |
| RDCOST(x->rdmult, best_rd_stats->rate, best_rd_stats->sse); |
| |
| x->plane[plane].txb_entropy_ctx[block] = 0; |
| } else if (predict_dc_level > 1) { |
| // Predict DC only blocks based on residual variance. |
| // For chroma plane, this prediction is disabled for intra blocks. |
| if ((plane == 0) || (plane > 0 && is_inter_block(mbmi))) *dc_only_blk = 1; |
| } |
| } |
| |
| // Search for the best transform type for a given transform block. |
| // This function can be used for both inter and intra, both luma and chroma. |
| static void search_tx_type(const AV1_COMP *cpi, MACROBLOCK *x, int plane, |
| int block, int blk_row, int blk_col, |
| BLOCK_SIZE plane_bsize, TX_SIZE tx_size, |
| const TXB_CTX *const txb_ctx, |
| FAST_TX_SEARCH_MODE ftxs_mode, int skip_trellis, |
| int64_t ref_best_rd, RD_STATS *best_rd_stats) { |
| const AV1_COMMON *cm = &cpi->common; |
| MACROBLOCKD *xd = &x->e_mbd; |
| MB_MODE_INFO *mbmi = xd->mi[0]; |
| const TxfmSearchParams *txfm_params = &x->txfm_search_params; |
| int64_t best_rd = INT64_MAX; |
| uint16_t best_eob = 0; |
| TX_TYPE best_tx_type = DCT_DCT; |
| int rate_cost = 0; |
| struct macroblock_plane *const p = &x->plane[plane]; |
| tran_low_t *orig_dqcoeff = p->dqcoeff; |
| tran_low_t *best_dqcoeff = x->dqcoeff_buf; |
| const int tx_type_map_idx = |
| plane ? 0 : blk_row * xd->tx_type_map_stride + blk_col; |
| av1_invalid_rd_stats(best_rd_stats); |
| |
| skip_trellis |= !is_trellis_used(cpi->optimize_seg_arr[xd->mi[0]->segment_id], |
| DRY_RUN_NORMAL); |
| |
| uint8_t best_txb_ctx = 0; |
| // txk_allowed = TX_TYPES: >1 tx types are allowed |
| // txk_allowed < TX_TYPES: only that specific tx type is allowed. |
| TX_TYPE txk_allowed = TX_TYPES; |
| int txk_map[TX_TYPES] = { |
| 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 |
| }; |
| const int dequant_shift = (is_cur_buf_hbd(xd)) ? xd->bd - 5 : 3; |
| const int qstep = x->plane[plane].dequant_QTX[1] >> dequant_shift; |
| |
| const uint8_t txw = tx_size_wide[tx_size]; |
| const uint8_t txh = tx_size_high[tx_size]; |
| int64_t block_sse; |
| unsigned int block_mse_q8; |
| int dc_only_blk = 0; |
| const bool predict_dc_block = |
| txfm_params->predict_dc_level >= 1 && txw != 64 && txh != 64; |
| int64_t per_px_mean = INT64_MAX; |
| if (predict_dc_block) { |
| predict_dc_only_block(x, plane, plane_bsize, tx_size, block, blk_row, |
| blk_col, best_rd_stats, &block_sse, &block_mse_q8, |
| &per_px_mean, &dc_only_blk); |
| if (best_rd_stats->skip_txfm == 1) { |
| const TX_TYPE tx_type = DCT_DCT; |
| if (plane == 0) xd->tx_type_map[tx_type_map_idx] = tx_type; |
| return; |
| } |
| } else { |
| block_sse = av1_pixel_diff_dist(x, plane, blk_row, blk_col, plane_bsize, |
| txsize_to_bsize[tx_size], &block_mse_q8); |
| assert(block_mse_q8 != UINT_MAX); |
| } |
| |
| // Bit mask to indicate which transform types are allowed in the RD search. |
| uint16_t tx_mask; |
| |
| // Use DCT_DCT transform for DC only block. |
| if (dc_only_blk || cpi->sf.rt_sf.dct_only_palette_nonrd == 1) |
| tx_mask = 1 << DCT_DCT; |
| else |
| tx_mask = get_tx_mask(cpi, x, plane, block, blk_row, blk_col, plane_bsize, |
| tx_size, txb_ctx, ftxs_mode, ref_best_rd, |
| &txk_allowed, txk_map); |
| const uint16_t allowed_tx_mask = tx_mask; |
| |
| if (is_cur_buf_hbd(xd)) { |
| block_sse = ROUND_POWER_OF_TWO(block_sse, (xd->bd - 8) * 2); |
| block_mse_q8 = ROUND_POWER_OF_TWO(block_mse_q8, (xd->bd - 8) * 2); |
| } |
| block_sse *= 16; |
| // Use mse / qstep^2 based threshold logic to take decision of R-D |
| // optimization of coeffs. For smaller residuals, coeff optimization |
| // would be helpful. For larger residuals, R-D optimization may not be |
| // effective. |
| // TODO(any): Experiment with variance and mean based thresholds |
| const int perform_block_coeff_opt = |
| ((uint64_t)block_mse_q8 <= |
| (uint64_t)txfm_params->coeff_opt_thresholds[0] * qstep * qstep); |
| skip_trellis |= !perform_block_coeff_opt; |
| |
| // Flag to indicate if distortion should be calculated in transform domain or |
| // not during iterating through transform type candidates. |
| // Transform domain distortion is accurate for higher residuals. |
| // TODO(any): Experiment with variance and mean based thresholds |
| int use_transform_domain_distortion = |
| (txfm_params->use_transform_domain_distortion > 0) && |
| (block_mse_q8 >= txfm_params->tx_domain_dist_threshold) && |
| // Any 64-pt transforms only preserves half the coefficients. |
| // Therefore transform domain distortion is not valid for these |
| // transform sizes. |
| (txsize_sqr_up_map[tx_size] != TX_64X64) && |
| // Use pixel domain distortion for DC only blocks |
| !dc_only_blk; |
| // Flag to indicate if an extra calculation of distortion in the pixel domain |
| // should be performed at the end, after the best transform type has been |
| // decided. |
| int calc_pixel_domain_distortion_final = |
| txfm_params->use_transform_domain_distortion == 1 && |
| use_transform_domain_distortion && x->rd_model != LOW_TXFM_RD; |
| if (calc_pixel_domain_distortion_final && |
| (txk_allowed < TX_TYPES || allowed_tx_mask == 0x0001)) |
| calc_pixel_domain_distortion_final = use_transform_domain_distortion = 0; |
| |
| const uint16_t *eobs_ptr = x->plane[plane].eobs; |
| |
| TxfmParam txfm_param; |
| QUANT_PARAM quant_param; |
| int skip_trellis_based_on_satd[TX_TYPES] = { 0 }; |
| av1_setup_xform(cm, x, tx_size, DCT_DCT, &txfm_param); |
| av1_setup_quant(tx_size, !skip_trellis, |
| skip_trellis ? (USE_B_QUANT_NO_TRELLIS ? AV1_XFORM_QUANT_B |
| : AV1_XFORM_QUANT_FP) |
| : AV1_XFORM_QUANT_FP, |
| cpi->oxcf.q_cfg.quant_b_adapt, &quant_param); |
| |
| // Iterate through all transform type candidates. |
| for (int idx = 0; idx < TX_TYPES; ++idx) { |
| const TX_TYPE tx_type = (TX_TYPE)txk_map[idx]; |
| if (tx_type == TX_TYPE_INVALID || !check_bit_mask(allowed_tx_mask, tx_type)) |
| continue; |
| txfm_param.tx_type = tx_type; |
| if (av1_use_qmatrix(&cm->quant_params, xd, mbmi->segment_id)) { |
| av1_setup_qmatrix(&cm->quant_params, xd, plane, tx_size, tx_type, |
| &quant_param); |
| } |
| if (plane == 0) xd->tx_type_map[tx_type_map_idx] = tx_type; |
| RD_STATS this_rd_stats; |
| av1_invalid_rd_stats(&this_rd_stats); |
| |
| if (!dc_only_blk) |
| av1_xform(x, plane, block, blk_row, blk_col, plane_bsize, &txfm_param); |
| else |
| av1_xform_dc_only(x, plane, block, &txfm_param, per_px_mean); |
| |
| skip_trellis_based_on_satd[tx_type] = skip_trellis_opt_based_on_satd( |
| x, &quant_param, plane, block, tx_size, cpi->oxcf.q_cfg.quant_b_adapt, |
| qstep, txfm_params->coeff_opt_thresholds[1], skip_trellis, dc_only_blk); |
| |
| av1_quant(x, plane, block, &txfm_param, &quant_param); |
| |
| // Calculate rate cost of quantized coefficients. |
| if (quant_param.use_optimize_b) { |
| // TODO(aomedia:3209): update Trellis quantization to take into account |
| // quantization matrices. |
| av1_optimize_b(cpi, x, plane, block, tx_size, tx_type, txb_ctx, |
| &rate_cost); |
| } else { |
| rate_cost = cost_coeffs(x, plane, block, tx_size, tx_type, txb_ctx, |
| cm->features.reduced_tx_set_used); |
| } |
| |
| // If rd cost based on coeff rate alone is already more than best_rd, |
| // terminate early. |
| if (RDCOST(x->rdmult, rate_cost, 0) > best_rd) continue; |
| |
| // Calculate distortion. |
| if (eobs_ptr[block] == 0) { |
| // When eob is 0, pixel domain distortion is more efficient and accurate. |
| this_rd_stats.dist = this_rd_stats.sse = block_sse; |
| } else if (dc_only_blk) { |
| this_rd_stats.sse = block_sse; |
| this_rd_stats.dist = dist_block_px_domain( |
| cpi, x, plane, plane_bsize, block, blk_row, blk_col, tx_size); |
| } else if (use_transform_domain_distortion) { |
| const SCAN_ORDER *const scan_order = |
| get_scan(txfm_param.tx_size, txfm_param.tx_type); |
| dist_block_tx_domain(x, plane, block, tx_size, quant_param.qmatrix, |
| scan_order->scan, &this_rd_stats.dist, |
| &this_rd_stats.sse); |
| } else { |
| int64_t sse_diff = INT64_MAX; |
| // high_energy threshold assumes that every pixel within a txfm block |
| // has a residue energy of at least 25% of the maximum, i.e. 128 * 128 |
| // for 8 bit. |
| const int64_t high_energy_thresh = |
| ((int64_t)128 * 128 * tx_size_2d[tx_size]); |
| const int is_high_energy = (block_sse >= high_energy_thresh); |
| if (tx_size == TX_64X64 || is_high_energy) { |
| // Because 3 out 4 quadrants of transform coefficients are forced to |
| // zero, the inverse transform has a tendency to overflow. sse_diff |
| // is effectively the energy of those 3 quadrants, here we use it |
| // to decide if we should do pixel domain distortion. If the energy |
| // is mostly in first quadrant, then it is unlikely that we have |
| // overflow issue in inverse transform. |
| const SCAN_ORDER *const scan_order = |
| get_scan(txfm_param.tx_size, txfm_param.tx_type); |
| dist_block_tx_domain(x, plane, block, tx_size, quant_param.qmatrix, |
| scan_order->scan, &this_rd_stats.dist, |
| &this_rd_stats.sse); |
| sse_diff = block_sse - this_rd_stats.sse; |
| } |
| if (tx_size != TX_64X64 || !is_high_energy || |
| (sse_diff * 2) < this_rd_stats.sse) { |
| const int64_t tx_domain_dist = this_rd_stats.dist; |
| this_rd_stats.dist = dist_block_px_domain( |
| cpi, x, plane, plane_bsize, block, blk_row, blk_col, tx_size); |
| // For high energy blocks, occasionally, the pixel domain distortion |
| // can be artificially low due to clamping at reconstruction stage |
| // even when inverse transform output is hugely different from the |
| // actual residue. |
| if (is_high_energy && this_rd_stats.dist < tx_domain_dist) |
| this_rd_stats.dist = tx_domain_dist; |
| } else { |
| assert(sse_diff < INT64_MAX); |
| this_rd_stats.dist += sse_diff; |
| } |
| this_rd_stats.sse = block_sse; |
| } |
| |
| this_rd_stats.rate = rate_cost; |
| |
| const int64_t rd = |
| RDCOST(x->rdmult, this_rd_stats.rate, this_rd_stats.dist); |
| |
| if (rd < best_rd) { |
| best_rd = rd; |
| *best_rd_stats = this_rd_stats; |
| best_tx_type = tx_type; |
| best_txb_ctx = x->plane[plane].txb_entropy_ctx[block]; |
| best_eob = x->plane[plane].eobs[block]; |
| // Swap dqcoeff buffers |
| tran_low_t *const tmp_dqcoeff = best_dqcoeff; |
| best_dqcoeff = p->dqcoeff; |
| p->dqcoeff = tmp_dqcoeff; |
| } |
| |
| #if CONFIG_COLLECT_RD_STATS == 1 |
| if (plane == 0) { |
| PrintTransformUnitStats(cpi, x, &this_rd_stats, blk_row, blk_col, |
| plane_bsize, tx_size, tx_type, rd); |
| } |
| #endif // CONFIG_COLLECT_RD_STATS == 1 |
| |
| #if COLLECT_TX_SIZE_DATA |
| // Generate small sample to restrict output size. |
| static unsigned int seed = 21743; |
| if (lcg_rand16(&seed) % 200 == 0) { |
| FILE *fp = NULL; |
| |
| if (within_border) { |
| fp = fopen(av1_tx_size_data_output_file, "a"); |
| } |
| |
| if (fp) { |
| // Transform info and RD |
| const int txb_w = tx_size_wide[tx_size]; |
| const int txb_h = tx_size_high[tx_size]; |
| |
| // Residue signal. |
| const int diff_stride = block_size_wide[plane_bsize]; |
| struct macroblock_plane *const p = &x->plane[plane]; |
| const int16_t *src_diff = |
| &p->src_diff[(blk_row * diff_stride + blk_col) * 4]; |
| |
| for (int r = 0; r < txb_h; ++r) { |
| for (int c = 0; c < txb_w; ++c) { |
| fprintf(fp, "%d,", src_diff[c]); |
| } |
| src_diff += diff_stride; |
| } |
| |
| fprintf(fp, "%d,%d,%d,%" PRId64, txb_w, txb_h, tx_type, rd); |
| fprintf(fp, "\n"); |
| fclose(fp); |
| } |
| } |
| #endif // COLLECT_TX_SIZE_DATA |
| |
| // If the current best RD cost is much worse than the reference RD cost, |
| // terminate early. |
| if (cpi->sf.tx_sf.adaptive_txb_search_level) { |
| if ((best_rd - (best_rd >> cpi->sf.tx_sf.adaptive_txb_search_level)) > |
| ref_best_rd) { |
| break; |
| } |
| } |
| |
| // Terminate transform type search if the block has been quantized to |
| // all zero. |
| if (cpi->sf.tx_sf.tx_type_search.skip_tx_search && !best_eob) break; |
| } |
| |
| assert(best_rd != INT64_MAX); |
| |
| best_rd_stats->skip_txfm = best_eob == 0; |
| if (plane == 0) update_txk_array(xd, blk_row, blk_col, tx_size, best_tx_type); |
| x->plane[plane].txb_entropy_ctx[block] = best_txb_ctx; |
| x->plane[plane].eobs[block] = best_eob; |
| skip_trellis = skip_trellis_based_on_satd[best_tx_type]; |
| |
| // Point dqcoeff to the quantized coefficients corresponding to the best |
| // transform type, then we can skip transform and quantization, e.g. in the |
| // final pixel domain distortion calculation and recon_intra(). |
| p->dqcoeff = best_dqcoeff; |
| |
| if (calc_pixel_domain_distortion_final && best_eob) { |
| best_rd_stats->dist = dist_block_px_domain( |
| cpi, x, plane, plane_bsize, block, blk_row, blk_col, tx_size); |
| best_rd_stats->sse = block_sse; |
| } |
| |
| // Intra mode needs decoded pixels such that the next transform block |
| // can use them for prediction. |
| recon_intra(cpi, x, plane, block, blk_row, blk_col, plane_bsize, tx_size, |
| txb_ctx, skip_trellis, best_tx_type, 0, &rate_cost, best_eob); |
| p->dqcoeff = orig_dqcoeff; |
| } |
| |
| // Pick transform type for a luma transform block of tx_size. Note this function |
| // is used only for inter-predicted blocks. |
| static AOM_INLINE void tx_type_rd(const AV1_COMP *cpi, MACROBLOCK *x, |
| TX_SIZE tx_size, int blk_row, int blk_col, |
| int block, int plane_bsize, TXB_CTX *txb_ctx, |
| RD_STATS *rd_stats, |
| FAST_TX_SEARCH_MODE ftxs_mode, |
| int64_t ref_rdcost) { |
| assert(is_inter_block(x->e_mbd.mi[0])); |
| RD_STATS this_rd_stats; |
| const int skip_trellis = 0; |
| search_tx_type(cpi, x, 0, block, blk_row, blk_col, plane_bsize, tx_size, |
| txb_ctx, ftxs_mode, skip_trellis, ref_rdcost, &this_rd_stats); |
| |
| av1_merge_rd_stats(rd_stats, &this_rd_stats); |
| } |
| |
| static AOM_INLINE void try_tx_block_no_split( |
| const AV1_COMP *cpi, MACROBLOCK *x, int blk_row, int blk_col, int block, |
| TX_SIZE tx_size, int depth, BLOCK_SIZE plane_bsize, |
| const ENTROPY_CONTEXT *ta, const ENTROPY_CONTEXT *tl, |
| int txfm_partition_ctx, RD_STATS *rd_stats, int64_t ref_best_rd, |
| FAST_TX_SEARCH_MODE ftxs_mode, TxCandidateInfo *no_split) { |
| MACROBLOCKD *const xd = &x->e_mbd; |
| MB_MODE_INFO *const mbmi = xd->mi[0]; |
| struct macroblock_plane *const p = &x->plane[0]; |
| const int bw = mi_size_wide[plane_bsize]; |
| const ENTROPY_CONTEXT *const pta = ta + blk_col; |
| const ENTROPY_CONTEXT *const ptl = tl + blk_row; |
| const TX_SIZE txs_ctx = get_txsize_entropy_ctx(tx_size); |
| TXB_CTX txb_ctx; |
| get_txb_ctx(plane_bsize, tx_size, 0, pta, ptl, &txb_ctx); |
| const int zero_blk_rate = x->coeff_costs.coeff_costs[txs_ctx][PLANE_TYPE_Y] |
| .txb_skip_cost[txb_ctx.txb_skip_ctx][1]; |
| rd_stats->zero_rate = zero_blk_rate; |
| const int index = av1_get_txb_size_index(plane_bsize, blk_row, blk_col); |
| mbmi->inter_tx_size[index] = tx_size; |
| tx_type_rd(cpi, x, tx_size, blk_row, blk_col, block, plane_bsize, &txb_ctx, |
| rd_stats, ftxs_mode, ref_best_rd); |
| assert(rd_stats->rate < INT_MAX); |
| |
| const int pick_skip_txfm = |
| !xd->lossless[mbmi->segment_id] && |
| (rd_stats->skip_txfm == 1 || |
| RDCOST(x->rdmult, rd_stats->rate, rd_stats->dist) >= |
| RDCOST(x->rdmult, zero_blk_rate, rd_stats->sse)); |
| if (pick_skip_txfm) { |
| #if CONFIG_RD_DEBUG |
| update_txb_coeff_cost(rd_stats |