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author | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-04-19 00:47:55 +0000 |
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committer | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-04-19 00:47:55 +0000 |
commit | 26a029d407be480d791972afb5975cf62c9360a6 (patch) | |
tree | f435a8308119effd964b339f76abb83a57c29483 /third_party/aom/av1/encoder/tx_search.c | |
parent | Initial commit. (diff) | |
download | firefox-26a029d407be480d791972afb5975cf62c9360a6.tar.xz firefox-26a029d407be480d791972afb5975cf62c9360a6.zip |
Adding upstream version 124.0.1.upstream/124.0.1
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
Diffstat (limited to '')
-rw-r--r-- | third_party/aom/av1/encoder/tx_search.c | 3830 |
1 files changed, 3830 insertions, 0 deletions
diff --git a/third_party/aom/av1/encoder/tx_search.c b/third_party/aom/av1/encoder/tx_search.c new file mode 100644 index 0000000000..7292c01191 --- /dev/null +++ b/third_party/aom/av1/encoder/tx_search.c @@ -0,0 +1,3830 @@ +/* + * 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, 0, zero_blk_rate - rd_stats->rate); +#endif // CONFIG_RD_DEBUG + rd_stats->rate = zero_blk_rate; + rd_stats->dist = rd_stats->sse; + p->eobs[block] = 0; + update_txk_array(xd, blk_row, blk_col, tx_size, DCT_DCT); + } + rd_stats->skip_txfm = pick_skip_txfm; + set_blk_skip(x->txfm_search_info.blk_skip, 0, blk_row * bw + blk_col, + pick_skip_txfm); + + if (tx_size > TX_4X4 && depth < MAX_VARTX_DEPTH) + rd_stats->rate += x->mode_costs.txfm_partition_cost[txfm_partition_ctx][0]; + + no_split->rd = RDCOST(x->rdmult, rd_stats->rate, rd_stats->dist); + no_split->txb_entropy_ctx = p->txb_entropy_ctx[block]; + no_split->tx_type = + xd->tx_type_map[blk_row * xd->tx_type_map_stride + blk_col]; +} + +static AOM_INLINE void try_tx_block_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, ENTROPY_CONTEXT *ta, + ENTROPY_CONTEXT *tl, TXFM_CONTEXT *tx_above, TXFM_CONTEXT *tx_left, + int txfm_partition_ctx, int64_t no_split_rd, int64_t ref_best_rd, + FAST_TX_SEARCH_MODE ftxs_mode, RD_STATS *split_rd_stats) { + assert(tx_size < TX_SIZES_ALL); + MACROBLOCKD *const xd = &x->e_mbd; + const int max_blocks_high = max_block_high(xd, plane_bsize, 0); + const int max_blocks_wide = max_block_wide(xd, plane_bsize, 0); + const int txb_width = tx_size_wide_unit[tx_size]; + const int txb_height = tx_size_high_unit[tx_size]; + // Transform size after splitting current block. + const TX_SIZE sub_txs = sub_tx_size_map[tx_size]; + const int sub_txb_width = tx_size_wide_unit[sub_txs]; + const int sub_txb_height = tx_size_high_unit[sub_txs]; + const int sub_step = sub_txb_width * sub_txb_height; + const int nblks = (txb_height / sub_txb_height) * (txb_width / sub_txb_width); + assert(nblks > 0); + av1_init_rd_stats(split_rd_stats); + split_rd_stats->rate = + x->mode_costs.txfm_partition_cost[txfm_partition_ctx][1]; + + for (int r = 0, blk_idx = 0; r < txb_height; r += sub_txb_height) { + const int offsetr = blk_row + r; + if (offsetr >= max_blocks_high) break; + for (int c = 0; c < txb_width; c += sub_txb_width, ++blk_idx) { + assert(blk_idx < 4); + const int offsetc = blk_col + c; + if (offsetc >= max_blocks_wide) continue; + + RD_STATS this_rd_stats; + int this_cost_valid = 1; + select_tx_block(cpi, x, offsetr, offsetc, block, sub_txs, depth + 1, + plane_bsize, ta, tl, tx_above, tx_left, &this_rd_stats, + no_split_rd / nblks, ref_best_rd - split_rd_stats->rdcost, + &this_cost_valid, ftxs_mode); + if (!this_cost_valid) { + split_rd_stats->rdcost = INT64_MAX; + return; + } + av1_merge_rd_stats(split_rd_stats, &this_rd_stats); + split_rd_stats->rdcost = + RDCOST(x->rdmult, split_rd_stats->rate, split_rd_stats->dist); + if (split_rd_stats->rdcost > ref_best_rd) { + split_rd_stats->rdcost = INT64_MAX; + return; + } + block += sub_step; + } + } +} + +static float get_var(float mean, double x2_sum, int num) { + const float e_x2 = (float)(x2_sum / num); + const float diff = e_x2 - mean * mean; + return diff; +} + +static AOM_INLINE void get_blk_var_dev(const int16_t *data, int stride, int bw, + int bh, float *dev_of_mean, + float *var_of_vars) { + 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 total_x_sum = 0; + int64_t total_x2_sum = 0; + int blk_idx = 0; + float var_sum = 0.0f; + float mean_sum = 0.0f; + double var2_sum = 0.0f; + double mean2_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; + 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 var = get_var(mean, (double)x2_sum, sub_num); + mean_sum += mean; + mean2_sum += (double)(mean * mean); + var_sum += var; + var2_sum += var * var; + blk_idx++; + } + } + + const float lvl0_mean = (float)total_x_sum / num; + const float block_var = get_var(lvl0_mean, (double)total_x2_sum, num); + mean_sum += lvl0_mean; + mean2_sum += (double)(lvl0_mean * lvl0_mean); + var_sum += block_var; + var2_sum += block_var * block_var; + const float av_mean = mean_sum / 5; + + if (blk_idx > 1) { + // Deviation of means. + *dev_of_mean = get_dev(av_mean, mean2_sum, (blk_idx + 1)); + // Variance of variances. + const float mean_var = var_sum / (blk_idx + 1); + *var_of_vars = get_var(mean_var, var2_sum, (blk_idx + 1)); + } +} + +static void prune_tx_split_no_split(MACROBLOCK *x, BLOCK_SIZE bsize, + int blk_row, int blk_col, TX_SIZE tx_size, + int *try_no_split, int *try_split, + int pruning_level) { + 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 dev_of_means = 0.0f; + float var_of_vars = 0.0f; + + // This function calculates the deviation of means, and the variance of pixel + // variances of the block as well as it's sub-blocks. + get_blk_var_dev(diff, diff_stride, bw, bh, &dev_of_means, &var_of_vars); + const int dc_q = x->plane[0].dequant_QTX[0] >> 3; + const int ac_q = x->plane[0].dequant_QTX[1] >> 3; + const int no_split_thresh_scales[4] = { 0, 24, 8, 8 }; + const int no_split_thresh_scale = no_split_thresh_scales[pruning_level]; + const int split_thresh_scales[4] = { 0, 24, 10, 8 }; + const int split_thresh_scale = split_thresh_scales[pruning_level]; + + if ((dev_of_means <= dc_q) && + (split_thresh_scale * var_of_vars <= ac_q * ac_q)) { + *try_split = 0; + } + if ((dev_of_means > no_split_thresh_scale * dc_q) && + (var_of_vars > no_split_thresh_scale * ac_q * ac_q)) { + *try_no_split = 0; + } +} + +// Search for the best transform partition(recursive)/type for a given +// inter-predicted luma block. The obtained transform selection will be saved +// in xd->mi[0], the corresponding RD stats will be saved in rd_stats. +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) { + assert(tx_size < TX_SIZES_ALL); + av1_init_rd_stats(rd_stats); + if (ref_best_rd < 0) { + *is_cost_valid = 0; + return; + } + + MACROBLOCKD *const xd = &x->e_mbd; + assert(blk_row < max_block_high(xd, plane_bsize, 0) && + blk_col < max_block_wide(xd, plane_bsize, 0)); + MB_MODE_INFO *const mbmi = xd->mi[0]; + const int ctx = txfm_partition_context(tx_above + blk_col, tx_left + blk_row, + mbmi->bsize, tx_size); + struct macroblock_plane *const p = &x->plane[0]; + + int try_no_split = (cpi->oxcf.txfm_cfg.enable_tx64 || + txsize_sqr_up_map[tx_size] != TX_64X64) && + (cpi->oxcf.txfm_cfg.enable_rect_tx || + tx_size_wide[tx_size] == tx_size_high[tx_size]); + int try_split = tx_size > TX_4X4 && depth < MAX_VARTX_DEPTH; + TxCandidateInfo no_split = { INT64_MAX, 0, TX_TYPES }; + + // Prune tx_split and no-split based on sub-block properties. + if (tx_size != TX_4X4 && try_split == 1 && try_no_split == 1 && + cpi->sf.tx_sf.prune_tx_size_level > 0) { + prune_tx_split_no_split(x, plane_bsize, blk_row, blk_col, tx_size, + &try_no_split, &try_split, + cpi->sf.tx_sf.prune_tx_size_level); + } + + if (cpi->sf.rt_sf.skip_tx_no_split_var_based_partition) { + if (x->try_merge_partition && try_split && p->eobs[block]) try_no_split = 0; + } + + // Try using current block as a single transform block without split. + if (try_no_split) { + try_tx_block_no_split(cpi, x, blk_row, blk_col, block, tx_size, depth, + plane_bsize, ta, tl, ctx, rd_stats, ref_best_rd, + ftxs_mode, &no_split); + + // Speed features for early termination. + const int search_level = cpi->sf.tx_sf.adaptive_txb_search_level; + if (search_level) { + if ((no_split.rd - (no_split.rd >> (1 + search_level))) > ref_best_rd) { + *is_cost_valid = 0; + return; + } + if (no_split.rd - (no_split.rd >> (2 + search_level)) > prev_level_rd) { + try_split = 0; + } + } + if (cpi->sf.tx_sf.txb_split_cap) { + if (p->eobs[block] == 0) try_split = 0; + } + } + + // ML based speed feature to skip searching for split transform blocks. + if (x->e_mbd.bd == 8 && try_split && + !(ref_best_rd == INT64_MAX && no_split.rd == INT64_MAX)) { + const int threshold = cpi->sf.tx_sf.tx_type_search.ml_tx_split_thresh; + if (threshold >= 0) { + const int split_score = + ml_predict_tx_split(x, plane_bsize, blk_row, blk_col, tx_size); + if (split_score < -threshold) try_split = 0; + } + } + + RD_STATS split_rd_stats; + split_rd_stats.rdcost = INT64_MAX; + // Try splitting current block into smaller transform blocks. + if (try_split) { + try_tx_block_split(cpi, x, blk_row, blk_col, block, tx_size, depth, + plane_bsize, ta, tl, tx_above, tx_left, ctx, no_split.rd, + AOMMIN(no_split.rd, ref_best_rd), ftxs_mode, + &split_rd_stats); + } + + if (no_split.rd < split_rd_stats.rdcost) { + ENTROPY_CONTEXT *pta = ta + blk_col; + ENTROPY_CONTEXT *ptl = tl + blk_row; + p->txb_entropy_ctx[block] = no_split.txb_entropy_ctx; + av1_set_txb_context(x, 0, block, tx_size, pta, ptl); + txfm_partition_update(tx_above + blk_col, tx_left + blk_row, tx_size, + tx_size); + for (int idy = 0; idy < tx_size_high_unit[tx_size]; ++idy) { + for (int idx = 0; idx < tx_size_wide_unit[tx_size]; ++idx) { + const int index = + av1_get_txb_size_index(plane_bsize, blk_row + idy, blk_col + idx); + mbmi->inter_tx_size[index] = tx_size; + } + } + mbmi->tx_size = tx_size; + update_txk_array(xd, blk_row, blk_col, tx_size, no_split.tx_type); + const int bw = mi_size_wide[plane_bsize]; + set_blk_skip(x->txfm_search_info.blk_skip, 0, blk_row * bw + blk_col, + rd_stats->skip_txfm); + } else { + *rd_stats = split_rd_stats; + if (split_rd_stats.rdcost == INT64_MAX) *is_cost_valid = 0; + } +} + +static AOM_INLINE void choose_largest_tx_size(const AV1_COMP *const cpi, + MACROBLOCK *x, RD_STATS *rd_stats, + int64_t ref_best_rd, + BLOCK_SIZE bs) { + MACROBLOCKD *const xd = &x->e_mbd; + MB_MODE_INFO *const mbmi = xd->mi[0]; + const TxfmSearchParams *txfm_params = &x->txfm_search_params; + mbmi->tx_size = tx_size_from_tx_mode(bs, txfm_params->tx_mode_search_type); + + // If tx64 is not enabled, we need to go down to the next available size + if (!cpi->oxcf.txfm_cfg.enable_tx64 && cpi->oxcf.txfm_cfg.enable_rect_tx) { + static const TX_SIZE tx_size_max_32[TX_SIZES_ALL] = { + TX_4X4, // 4x4 transform + TX_8X8, // 8x8 transform + TX_16X16, // 16x16 transform + TX_32X32, // 32x32 transform + TX_32X32, // 64x64 transform + TX_4X8, // 4x8 transform + TX_8X4, // 8x4 transform + TX_8X16, // 8x16 transform + TX_16X8, // 16x8 transform + TX_16X32, // 16x32 transform + TX_32X16, // 32x16 transform + TX_32X32, // 32x64 transform + TX_32X32, // 64x32 transform + TX_4X16, // 4x16 transform + TX_16X4, // 16x4 transform + TX_8X32, // 8x32 transform + TX_32X8, // 32x8 transform + TX_16X32, // 16x64 transform + TX_32X16, // 64x16 transform + }; + mbmi->tx_size = tx_size_max_32[mbmi->tx_size]; + } else if (cpi->oxcf.txfm_cfg.enable_tx64 && + !cpi->oxcf.txfm_cfg.enable_rect_tx) { + static const TX_SIZE tx_size_max_square[TX_SIZES_ALL] = { + TX_4X4, // 4x4 transform + TX_8X8, // 8x8 transform + TX_16X16, // 16x16 transform + TX_32X32, // 32x32 transform + TX_64X64, // 64x64 transform + TX_4X4, // 4x8 transform + TX_4X4, // 8x4 transform + TX_8X8, // 8x16 transform + TX_8X8, // 16x8 transform + TX_16X16, // 16x32 transform + TX_16X16, // 32x16 transform + TX_32X32, // 32x64 transform + TX_32X32, // 64x32 transform + TX_4X4, // 4x16 transform + TX_4X4, // 16x4 transform + TX_8X8, // 8x32 transform + TX_8X8, // 32x8 transform + TX_16X16, // 16x64 transform + TX_16X16, // 64x16 transform + }; + mbmi->tx_size = tx_size_max_square[mbmi->tx_size]; + } else if (!cpi->oxcf.txfm_cfg.enable_tx64 && + !cpi->oxcf.txfm_cfg.enable_rect_tx) { + static const TX_SIZE tx_size_max_32_square[TX_SIZES_ALL] = { + TX_4X4, // 4x4 transform + TX_8X8, // 8x8 transform + TX_16X16, // 16x16 transform + TX_32X32, // 32x32 transform + TX_32X32, // 64x64 transform + TX_4X4, // 4x8 transform + TX_4X4, // 8x4 transform + TX_8X8, // 8x16 transform + TX_8X8, // 16x8 transform + TX_16X16, // 16x32 transform + TX_16X16, // 32x16 transform + TX_32X32, // 32x64 transform + TX_32X32, // 64x32 transform + TX_4X4, // 4x16 transform + TX_4X4, // 16x4 transform + TX_8X8, // 8x32 transform + TX_8X8, // 32x8 transform + TX_16X16, // 16x64 transform + TX_16X16, // 64x16 transform + }; + + mbmi->tx_size = tx_size_max_32_square[mbmi->tx_size]; + } + + const int skip_ctx = av1_get_skip_txfm_context(xd); + const int no_skip_txfm_rate = x->mode_costs.skip_txfm_cost[skip_ctx][0]; + const int skip_txfm_rate = x->mode_costs.skip_txfm_cost[skip_ctx][1]; + // Skip RDcost is used only for Inter blocks + const int64_t skip_txfm_rd = + is_inter_block(mbmi) ? RDCOST(x->rdmult, skip_txfm_rate, 0) : INT64_MAX; + const int64_t no_skip_txfm_rd = RDCOST(x->rdmult, no_skip_txfm_rate, 0); + const int skip_trellis = 0; + av1_txfm_rd_in_plane(x, cpi, rd_stats, ref_best_rd, + AOMMIN(no_skip_txfm_rd, skip_txfm_rd), AOM_PLANE_Y, bs, + mbmi->tx_size, FTXS_NONE, skip_trellis); +} + +static AOM_INLINE void choose_smallest_tx_size(const AV1_COMP *const cpi, + MACROBLOCK *x, + RD_STATS *rd_stats, + int64_t ref_best_rd, + BLOCK_SIZE bs) { + MACROBLOCKD *const xd = &x->e_mbd; + MB_MODE_INFO *const mbmi = xd->mi[0]; + + mbmi->tx_size = TX_4X4; + // TODO(any) : Pass this_rd based on skip/non-skip cost + const int skip_trellis = 0; + av1_txfm_rd_in_plane(x, cpi, rd_stats, ref_best_rd, 0, 0, bs, mbmi->tx_size, + FTXS_NONE, skip_trellis); +} + +#if !CONFIG_REALTIME_ONLY +static void ml_predict_intra_tx_depth_prune(MACROBLOCK *x, int blk_row, + int blk_col, BLOCK_SIZE bsize, + TX_SIZE tx_size) { + const MACROBLOCKD *const xd = &x->e_mbd; + const MB_MODE_INFO *const mbmi = xd->mi[0]; + + // Disable the pruning logic using NN model for the following cases: + // 1) Lossless coding as only 4x4 transform is evaluated in this case + // 2) When transform and current block sizes do not match as the features are + // obtained over the current block + // 3) When operating bit-depth is not 8-bit as the input features are not + // scaled according to bit-depth. + if (xd->lossless[mbmi->segment_id] || txsize_to_bsize[tx_size] != bsize || + xd->bd != 8) + return; + + // Currently NN model based pruning is supported only when largest transform + // size is 8x8 + if (tx_size != TX_8X8) return; + + // Neural network model is a sequential neural net and was trained using SGD + // optimizer. The model can be further improved in terms of speed/quality by + // considering the following experiments: + // 1) Generate ML model by training with balanced data for different learning + // rates and optimizers. + // 2) Experiment with ML model by adding features related to the statistics of + // top and left pixels to capture the accuracy of reconstructed neighbouring + // pixels for 4x4 blocks numbered 1, 2, 3 in 8x8 block, source variance of 4x4 + // sub-blocks, etc. + // 3) Generate ML models for transform blocks other than 8x8. + const NN_CONFIG *const nn_config = &av1_intra_tx_split_nnconfig_8x8; + const float *const intra_tx_prune_thresh = av1_intra_tx_prune_nn_thresh_8x8; + + float features[NUM_INTRA_TX_SPLIT_FEATURES] = { 0.0f }; + const int diff_stride = block_size_wide[bsize]; + + const int16_t *diff = x->plane[0].src_diff + MI_SIZE * blk_row * diff_stride + + MI_SIZE * blk_col; + const int bw = tx_size_wide[tx_size]; + const int bh = tx_size_high[tx_size]; + + int feature_idx = get_mean_dev_features(diff, diff_stride, bw, bh, features); + + features[feature_idx++] = log1pf((float)x->source_variance); + + const int dc_q = av1_dc_quant_QTX(x->qindex, 0, xd->bd) >> (xd->bd - 8); + const float log_dc_q_square = log1pf((float)(dc_q * dc_q) / 256.0f); + features[feature_idx++] = log_dc_q_square; + assert(feature_idx == NUM_INTRA_TX_SPLIT_FEATURES); + for (int i = 0; i < NUM_INTRA_TX_SPLIT_FEATURES; i++) { + features[i] = (features[i] - av1_intra_tx_split_8x8_mean[i]) / + av1_intra_tx_split_8x8_std[i]; + } + + float score; + av1_nn_predict(features, nn_config, 1, &score); + + TxfmSearchParams *const txfm_params = &x->txfm_search_params; + if (score <= intra_tx_prune_thresh[0]) + txfm_params->nn_prune_depths_for_intra_tx = TX_PRUNE_SPLIT; + else if (score > intra_tx_prune_thresh[1]) + txfm_params->nn_prune_depths_for_intra_tx = TX_PRUNE_LARGEST; +} +#endif // !CONFIG_REALTIME_ONLY + +// Search for the best uniform transform size and type for current coding block. +static AOM_INLINE void choose_tx_size_type_from_rd(const AV1_COMP *const cpi, + MACROBLOCK *x, + RD_STATS *rd_stats, + int64_t ref_best_rd, + BLOCK_SIZE bs) { + av1_invalid_rd_stats(rd_stats); + + MACROBLOCKD *const xd = &x->e_mbd; + MB_MODE_INFO *const mbmi = xd->mi[0]; + TxfmSearchParams *const txfm_params = &x->txfm_search_params; + const TX_SIZE max_rect_tx_size = max_txsize_rect_lookup[bs]; + const int tx_select = txfm_params->tx_mode_search_type == TX_MODE_SELECT; + int start_tx; + // The split depth can be at most MAX_TX_DEPTH, so the init_depth controls + // how many times of splitting is allowed during the RD search. + int init_depth; + + if (tx_select) { + start_tx = max_rect_tx_size; + init_depth = get_search_init_depth(mi_size_wide[bs], mi_size_high[bs], + is_inter_block(mbmi), &cpi->sf, + txfm_params->tx_size_search_method); + if (init_depth == MAX_TX_DEPTH && !cpi->oxcf.txfm_cfg.enable_tx64 && + txsize_sqr_up_map[start_tx] == TX_64X64) { + start_tx = sub_tx_size_map[start_tx]; + } + } else { + const TX_SIZE chosen_tx_size = + tx_size_from_tx_mode(bs, txfm_params->tx_mode_search_type); + start_tx = chosen_tx_size; + init_depth = MAX_TX_DEPTH; + } + + const int skip_trellis = 0; + uint8_t best_txk_type_map[MAX_MIB_SIZE * MAX_MIB_SIZE]; + uint8_t best_blk_skip[MAX_MIB_SIZE * MAX_MIB_SIZE]; + TX_SIZE best_tx_size = max_rect_tx_size; + int64_t best_rd = INT64_MAX; + const int num_blks = bsize_to_num_blk(bs); + x->rd_model = FULL_TXFM_RD; + int64_t rd[MAX_TX_DEPTH + 1] = { INT64_MAX, INT64_MAX, INT64_MAX }; + TxfmSearchInfo *txfm_info = &x->txfm_search_info; + for (int tx_size = start_tx, depth = init_depth; depth <= MAX_TX_DEPTH; + depth++, tx_size = sub_tx_size_map[tx_size]) { + if ((!cpi->oxcf.txfm_cfg.enable_tx64 && + txsize_sqr_up_map[tx_size] == TX_64X64) || + (!cpi->oxcf.txfm_cfg.enable_rect_tx && + tx_size_wide[tx_size] != tx_size_high[tx_size])) { + continue; + } + +#if !CONFIG_REALTIME_ONLY + if (txfm_params->nn_prune_depths_for_intra_tx == TX_PRUNE_SPLIT) break; + + // Set the flag to enable the evaluation of NN classifier to prune transform + // depths. As the features are based on intra residual information of + // largest transform, the evaluation of NN model is enabled only for this + // case. + txfm_params->enable_nn_prune_intra_tx_depths = + (cpi->sf.tx_sf.prune_intra_tx_depths_using_nn && tx_size == start_tx); +#endif + + RD_STATS this_rd_stats; + // When the speed feature use_rd_based_breakout_for_intra_tx_search is + // enabled, use the known minimum best_rd for early termination. + const int64_t rd_thresh = + cpi->sf.tx_sf.use_rd_based_breakout_for_intra_tx_search + ? AOMMIN(ref_best_rd, best_rd) + : ref_best_rd; + rd[depth] = av1_uniform_txfm_yrd(cpi, x, &this_rd_stats, rd_thresh, bs, + tx_size, FTXS_NONE, skip_trellis); + if (rd[depth] < best_rd) { + av1_copy_array(best_blk_skip, txfm_info->blk_skip, num_blks); + av1_copy_array(best_txk_type_map, xd->tx_type_map, num_blks); + best_tx_size = tx_size; + best_rd = rd[depth]; + *rd_stats = this_rd_stats; + } + if (tx_size == TX_4X4) break; + // If we are searching three depths, prune the smallest size depending + // on rd results for the first two depths for low contrast blocks. + if (depth > init_depth && depth != MAX_TX_DEPTH && + x->source_variance < 256) { + if (rd[depth - 1] != INT64_MAX && rd[depth] > rd[depth - 1]) break; + } + } + + if (rd_stats->rate != INT_MAX) { + mbmi->tx_size = best_tx_size; + av1_copy_array(xd->tx_type_map, best_txk_type_map, num_blks); + av1_copy_array(txfm_info->blk_skip, best_blk_skip, num_blks); + } + +#if !CONFIG_REALTIME_ONLY + // Reset the flags to avoid any unintentional evaluation of NN model and + // consumption of prune depths. + txfm_params->enable_nn_prune_intra_tx_depths = false; + txfm_params->nn_prune_depths_for_intra_tx = TX_PRUNE_NONE; +#endif +} + +// Search for the best transform type for the given transform block in the +// given plane/channel, and calculate the corresponding RD cost. +static AOM_INLINE void block_rd_txfm(int plane, int block, int blk_row, + int blk_col, BLOCK_SIZE plane_bsize, + TX_SIZE tx_size, void *arg) { + struct rdcost_block_args *args = arg; + if (args->exit_early) { + args->incomplete_exit = 1; + return; + } + + MACROBLOCK *const x = args->x; + MACROBLOCKD *const xd = &x->e_mbd; + const int is_inter = is_inter_block(xd->mi[0]); + const AV1_COMP *cpi = args->cpi; + ENTROPY_CONTEXT *a = args->t_above + blk_col; + ENTROPY_CONTEXT *l = args->t_left + blk_row; + const AV1_COMMON *cm = &cpi->common; + RD_STATS this_rd_stats; + av1_init_rd_stats(&this_rd_stats); + + if (!is_inter) { + av1_predict_intra_block_facade(cm, xd, plane, blk_col, blk_row, tx_size); + av1_subtract_txb(x, plane, plane_bsize, blk_col, blk_row, tx_size); +#if !CONFIG_REALTIME_ONLY + const TxfmSearchParams *const txfm_params = &x->txfm_search_params; + if (txfm_params->enable_nn_prune_intra_tx_depths) { + ml_predict_intra_tx_depth_prune(x, blk_row, blk_col, plane_bsize, + tx_size); + if (txfm_params->nn_prune_depths_for_intra_tx == TX_PRUNE_LARGEST) { + av1_invalid_rd_stats(&args->rd_stats); + args->exit_early = 1; + return; + } + } +#endif + } + + TXB_CTX txb_ctx; + get_txb_ctx(plane_bsize, tx_size, plane, a, l, &txb_ctx); + search_tx_type(cpi, x, plane, block, blk_row, blk_col, plane_bsize, tx_size, + &txb_ctx, args->ftxs_mode, args->skip_trellis, + args->best_rd - args->current_rd, &this_rd_stats); + + if (plane == AOM_PLANE_Y && xd->cfl.store_y) { + assert(!is_inter || plane_bsize < BLOCK_8X8); + cfl_store_tx(xd, blk_row, blk_col, tx_size, plane_bsize); + } + +#if CONFIG_RD_DEBUG + update_txb_coeff_cost(&this_rd_stats, plane, this_rd_stats.rate); +#endif // CONFIG_RD_DEBUG + av1_set_txb_context(x, plane, block, tx_size, a, l); + + const int blk_idx = + blk_row * (block_size_wide[plane_bsize] >> MI_SIZE_LOG2) + blk_col; + + TxfmSearchInfo *txfm_info = &x->txfm_search_info; + if (plane == 0) + set_blk_skip(txfm_info->blk_skip, plane, blk_idx, + x->plane[plane].eobs[block] == 0); + else + set_blk_skip(txfm_info->blk_skip, plane, blk_idx, 0); + + int64_t rd; + if (is_inter) { + const int64_t no_skip_txfm_rd = + RDCOST(x->rdmult, this_rd_stats.rate, this_rd_stats.dist); + const int64_t skip_txfm_rd = RDCOST(x->rdmult, 0, this_rd_stats.sse); + rd = AOMMIN(no_skip_txfm_rd, skip_txfm_rd); + this_rd_stats.skip_txfm &= !x->plane[plane].eobs[block]; + } else { + // Signal non-skip_txfm for Intra blocks + rd = RDCOST(x->rdmult, this_rd_stats.rate, this_rd_stats.dist); + this_rd_stats.skip_txfm = 0; + } + + av1_merge_rd_stats(&args->rd_stats, &this_rd_stats); + + args->current_rd += rd; + if (args->current_rd > args->best_rd) args->exit_early = 1; +} + +int64_t av1_estimate_txfm_yrd(const AV1_COMP *const cpi, MACROBLOCK *x, + RD_STATS *rd_stats, int64_t ref_best_rd, + BLOCK_SIZE bs, TX_SIZE tx_size) { + MACROBLOCKD *const xd = &x->e_mbd; + MB_MODE_INFO *const mbmi = xd->mi[0]; + const TxfmSearchParams *txfm_params = &x->txfm_search_params; + const ModeCosts *mode_costs = &x->mode_costs; + const int is_inter = is_inter_block(mbmi); + const int tx_select = txfm_params->tx_mode_search_type == TX_MODE_SELECT && + block_signals_txsize(mbmi->bsize); + int tx_size_rate = 0; + if (tx_select) { + const int ctx = txfm_partition_context( + xd->above_txfm_context, xd->left_txfm_context, mbmi->bsize, tx_size); + tx_size_rate = mode_costs->txfm_partition_cost[ctx][0]; + } + const int skip_ctx = av1_get_skip_txfm_context(xd); + const int no_skip_txfm_rate = mode_costs->skip_txfm_cost[skip_ctx][0]; + const int skip_txfm_rate = mode_costs->skip_txfm_cost[skip_ctx][1]; + const int64_t skip_txfm_rd = RDCOST(x->rdmult, skip_txfm_rate, 0); + const int64_t no_this_rd = + RDCOST(x->rdmult, no_skip_txfm_rate + tx_size_rate, 0); + mbmi->tx_size = tx_size; + + const uint8_t txw_unit = tx_size_wide_unit[tx_size]; + const uint8_t txh_unit = tx_size_high_unit[tx_size]; + const int step = txw_unit * txh_unit; + const int max_blocks_wide = max_block_wide(xd, bs, 0); + const int max_blocks_high = max_block_high(xd, bs, 0); + + struct rdcost_block_args args; + av1_zero(args); + args.x = x; + args.cpi = cpi; + args.best_rd = ref_best_rd; + args.current_rd = AOMMIN(no_this_rd, skip_txfm_rd); + av1_init_rd_stats(&args.rd_stats); + av1_get_entropy_contexts(bs, &xd->plane[0], args.t_above, args.t_left); + int i = 0; + for (int blk_row = 0; blk_row < max_blocks_high && !args.incomplete_exit; + blk_row += txh_unit) { + for (int blk_col = 0; blk_col < max_blocks_wide; blk_col += txw_unit) { + RD_STATS this_rd_stats; + av1_init_rd_stats(&this_rd_stats); + + if (args.exit_early) { + args.incomplete_exit = 1; + break; + } + + ENTROPY_CONTEXT *a = args.t_above + blk_col; + ENTROPY_CONTEXT *l = args.t_left + blk_row; + TXB_CTX txb_ctx; + get_txb_ctx(bs, tx_size, 0, a, l, &txb_ctx); + + TxfmParam txfm_param; + QUANT_PARAM quant_param; + av1_setup_xform(&cpi->common, x, tx_size, DCT_DCT, &txfm_param); + av1_setup_quant(tx_size, 0, AV1_XFORM_QUANT_B, 0, &quant_param); + + av1_xform(x, 0, i, blk_row, blk_col, bs, &txfm_param); + av1_quant(x, 0, i, &txfm_param, &quant_param); + + this_rd_stats.rate = + cost_coeffs(x, 0, i, tx_size, txfm_param.tx_type, &txb_ctx, 0); + + const SCAN_ORDER *const scan_order = + get_scan(txfm_param.tx_size, txfm_param.tx_type); + dist_block_tx_domain(x, 0, i, tx_size, quant_param.qmatrix, + scan_order->scan, &this_rd_stats.dist, + &this_rd_stats.sse); + + const int64_t no_skip_txfm_rd = + RDCOST(x->rdmult, this_rd_stats.rate, this_rd_stats.dist); + const int64_t skip_rd = RDCOST(x->rdmult, 0, this_rd_stats.sse); + + this_rd_stats.skip_txfm &= !x->plane[0].eobs[i]; + + av1_merge_rd_stats(&args.rd_stats, &this_rd_stats); + args.current_rd += AOMMIN(no_skip_txfm_rd, skip_rd); + + if (args.current_rd > ref_best_rd) { + args.exit_early = 1; + break; + } + + av1_set_txb_context(x, 0, i, tx_size, a, l); + i += step; + } + } + + if (args.incomplete_exit) av1_invalid_rd_stats(&args.rd_stats); + + *rd_stats = args.rd_stats; + if (rd_stats->rate == INT_MAX) return INT64_MAX; + + int64_t rd; + // rdstats->rate should include all the rate except skip/non-skip cost as the + // same is accounted in the caller functions after rd evaluation of all + // planes. However the decisions should be done after considering the + // skip/non-skip header cost + if (rd_stats->skip_txfm && is_inter) { + rd = RDCOST(x->rdmult, skip_txfm_rate, rd_stats->sse); + } else { + // Intra blocks are always signalled as non-skip + rd = RDCOST(x->rdmult, rd_stats->rate + no_skip_txfm_rate + tx_size_rate, + rd_stats->dist); + rd_stats->rate += tx_size_rate; + } + // Check if forcing the block to skip transform leads to smaller RD cost. + if (is_inter && !rd_stats->skip_txfm && !xd->lossless[mbmi->segment_id]) { + int64_t temp_skip_txfm_rd = + RDCOST(x->rdmult, skip_txfm_rate, rd_stats->sse); + if (temp_skip_txfm_rd <= rd) { + rd = temp_skip_txfm_rd; + rd_stats->rate = 0; + rd_stats->dist = rd_stats->sse; + rd_stats->skip_txfm = 1; + } + } + + return rd; +} + +int64_t av1_uniform_txfm_yrd(const AV1_COMP *const cpi, MACROBLOCK *x, + RD_STATS *rd_stats, int64_t ref_best_rd, + BLOCK_SIZE bs, TX_SIZE tx_size, + FAST_TX_SEARCH_MODE ftxs_mode, int skip_trellis) { + assert(IMPLIES(is_rect_tx(tx_size), is_rect_tx_allowed_bsize(bs))); + MACROBLOCKD *const xd = &x->e_mbd; + MB_MODE_INFO *const mbmi = xd->mi[0]; + const TxfmSearchParams *txfm_params = &x->txfm_search_params; + const ModeCosts *mode_costs = &x->mode_costs; + const int is_inter = is_inter_block(mbmi); + const int tx_select = txfm_params->tx_mode_search_type == TX_MODE_SELECT && + block_signals_txsize(mbmi->bsize); + int tx_size_rate = 0; + if (tx_select) { + const int ctx = txfm_partition_context( + xd->above_txfm_context, xd->left_txfm_context, mbmi->bsize, tx_size); + tx_size_rate = is_inter ? mode_costs->txfm_partition_cost[ctx][0] + : tx_size_cost(x, bs, tx_size); + } + const int skip_ctx = av1_get_skip_txfm_context(xd); + const int no_skip_txfm_rate = mode_costs->skip_txfm_cost[skip_ctx][0]; + const int skip_txfm_rate = mode_costs->skip_txfm_cost[skip_ctx][1]; + const int64_t skip_txfm_rd = + is_inter ? RDCOST(x->rdmult, skip_txfm_rate, 0) : INT64_MAX; + const int64_t no_this_rd = + RDCOST(x->rdmult, no_skip_txfm_rate + tx_size_rate, 0); + + mbmi->tx_size = tx_size; + av1_txfm_rd_in_plane(x, cpi, rd_stats, ref_best_rd, + AOMMIN(no_this_rd, skip_txfm_rd), AOM_PLANE_Y, bs, + tx_size, ftxs_mode, skip_trellis); + if (rd_stats->rate == INT_MAX) return INT64_MAX; + + int64_t rd; + // rdstats->rate should include all the rate except skip/non-skip cost as the + // same is accounted in the caller functions after rd evaluation of all + // planes. However the decisions should be done after considering the + // skip/non-skip header cost + if (rd_stats->skip_txfm && is_inter) { + rd = RDCOST(x->rdmult, skip_txfm_rate, rd_stats->sse); + } else { + // Intra blocks are always signalled as non-skip + rd = RDCOST(x->rdmult, rd_stats->rate + no_skip_txfm_rate + tx_size_rate, + rd_stats->dist); + rd_stats->rate += tx_size_rate; + } + // Check if forcing the block to skip transform leads to smaller RD cost. + if (is_inter && !rd_stats->skip_txfm && !xd->lossless[mbmi->segment_id]) { + int64_t temp_skip_txfm_rd = + RDCOST(x->rdmult, skip_txfm_rate, rd_stats->sse); + if (temp_skip_txfm_rd <= rd) { + rd = temp_skip_txfm_rd; + rd_stats->rate = 0; + rd_stats->dist = rd_stats->sse; + rd_stats->skip_txfm = 1; + } + } + + return rd; +} + +// Search for the best transform type for a luma inter-predicted block, given +// the transform block partitions. +// This function is used only when some speed features are enabled. +static AOM_INLINE void tx_block_yrd( + const AV1_COMP *cpi, MACROBLOCK *x, int blk_row, int blk_col, int block, + TX_SIZE tx_size, BLOCK_SIZE plane_bsize, int depth, + ENTROPY_CONTEXT *above_ctx, ENTROPY_CONTEXT *left_ctx, + TXFM_CONTEXT *tx_above, TXFM_CONTEXT *tx_left, int64_t ref_best_rd, + RD_STATS *rd_stats, FAST_TX_SEARCH_MODE ftxs_mode) { + assert(tx_size < TX_SIZES_ALL); + MACROBLOCKD *const xd = &x->e_mbd; + MB_MODE_INFO *const mbmi = xd->mi[0]; + assert(is_inter_block(mbmi)); + const int max_blocks_high = max_block_high(xd, plane_bsize, 0); + const int max_blocks_wide = max_block_wide(xd, plane_bsize, 0); + + if (blk_row >= max_blocks_high || blk_col >= max_blocks_wide) return; + + const TX_SIZE plane_tx_size = mbmi->inter_tx_size[av1_get_txb_size_index( + plane_bsize, blk_row, blk_col)]; + const int ctx = txfm_partition_context(tx_above + blk_col, tx_left + blk_row, + mbmi->bsize, tx_size); + + av1_init_rd_stats(rd_stats); + if (tx_size == plane_tx_size) { + ENTROPY_CONTEXT *ta = above_ctx + blk_col; + ENTROPY_CONTEXT *tl = left_ctx + 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, ta, tl, &txb_ctx); + + const int zero_blk_rate = + x->coeff_costs.coeff_costs[txs_ctx][get_plane_type(0)] + .txb_skip_cost[txb_ctx.txb_skip_ctx][1]; + rd_stats->zero_rate = zero_blk_rate; + tx_type_rd(cpi, x, tx_size, blk_row, blk_col, block, plane_bsize, &txb_ctx, + rd_stats, ftxs_mode, ref_best_rd); + const int mi_width = mi_size_wide[plane_bsize]; + TxfmSearchInfo *txfm_info = &x->txfm_search_info; + if (RDCOST(x->rdmult, rd_stats->rate, rd_stats->dist) >= + RDCOST(x->rdmult, zero_blk_rate, rd_stats->sse) || + rd_stats->skip_txfm == 1) { + rd_stats->rate = zero_blk_rate; + rd_stats->dist = rd_stats->sse; + rd_stats->skip_txfm = 1; + set_blk_skip(txfm_info->blk_skip, 0, blk_row * mi_width + blk_col, 1); + x->plane[0].eobs[block] = 0; + x->plane[0].txb_entropy_ctx[block] = 0; + update_txk_array(xd, blk_row, blk_col, tx_size, DCT_DCT); + } else { + rd_stats->skip_txfm = 0; + set_blk_skip(txfm_info->blk_skip, 0, blk_row * mi_width + blk_col, 0); + } + if (tx_size > TX_4X4 && depth < MAX_VARTX_DEPTH) + rd_stats->rate += x->mode_costs.txfm_partition_cost[ctx][0]; + av1_set_txb_context(x, 0, block, tx_size, ta, tl); + txfm_partition_update(tx_above + blk_col, tx_left + blk_row, tx_size, + tx_size); + } else { + const TX_SIZE sub_txs = sub_tx_size_map[tx_size]; + const int txb_width = tx_size_wide_unit[sub_txs]; + const int txb_height = tx_size_high_unit[sub_txs]; + const int step = txb_height * txb_width; + const int row_end = + AOMMIN(tx_size_high_unit[tx_size], max_blocks_high - blk_row); + const int col_end = + AOMMIN(tx_size_wide_unit[tx_size], max_blocks_wide - blk_col); + RD_STATS pn_rd_stats; + int64_t this_rd = 0; + assert(txb_width > 0 && txb_height > 0); + + for (int row = 0; row < row_end; row += txb_height) { + const int offsetr = blk_row + row; + for (int col = 0; col < col_end; col += txb_width) { + const int offsetc = blk_col + col; + + av1_init_rd_stats(&pn_rd_stats); + tx_block_yrd(cpi, x, offsetr, offsetc, block, sub_txs, plane_bsize, + depth + 1, above_ctx, left_ctx, tx_above, tx_left, + ref_best_rd - this_rd, &pn_rd_stats, ftxs_mode); + if (pn_rd_stats.rate == INT_MAX) { + av1_invalid_rd_stats(rd_stats); + return; + } + av1_merge_rd_stats(rd_stats, &pn_rd_stats); + this_rd += RDCOST(x->rdmult, pn_rd_stats.rate, pn_rd_stats.dist); + block += step; + } + } + + if (tx_size > TX_4X4 && depth < MAX_VARTX_DEPTH) + rd_stats->rate += x->mode_costs.txfm_partition_cost[ctx][1]; + } +} + +// search for tx type with tx sizes already decided for a inter-predicted luma +// partition block. It's used only when some speed features are enabled. +// Return value 0: early termination triggered, no valid rd cost available; +// 1: rd cost values are valid. +static int inter_block_yrd(const AV1_COMP *cpi, MACROBLOCK *x, + RD_STATS *rd_stats, BLOCK_SIZE bsize, + int64_t ref_best_rd, FAST_TX_SEARCH_MODE ftxs_mode) { + if (ref_best_rd < 0) { + av1_invalid_rd_stats(rd_stats); + return 0; + } + + av1_init_rd_stats(rd_stats); + + MACROBLOCKD *const xd = &x->e_mbd; + const TxfmSearchParams *txfm_params = &x->txfm_search_params; + const struct macroblockd_plane *const pd = &xd->plane[0]; + const int mi_width = mi_size_wide[bsize]; + const int mi_height = mi_size_high[bsize]; + const TX_SIZE max_tx_size = get_vartx_max_txsize(xd, bsize, 0); + const int bh = tx_size_high_unit[max_tx_size]; + const int bw = tx_size_wide_unit[max_tx_size]; + const int step = bw * bh; + const int init_depth = get_search_init_depth( + mi_width, mi_height, 1, &cpi->sf, txfm_params->tx_size_search_method); + ENTROPY_CONTEXT ctxa[MAX_MIB_SIZE]; + ENTROPY_CONTEXT ctxl[MAX_MIB_SIZE]; + TXFM_CONTEXT tx_above[MAX_MIB_SIZE]; + TXFM_CONTEXT tx_left[MAX_MIB_SIZE]; + av1_get_entropy_contexts(bsize, pd, ctxa, ctxl); + memcpy(tx_above, xd->above_txfm_context, sizeof(TXFM_CONTEXT) * mi_width); + memcpy(tx_left, xd->left_txfm_context, sizeof(TXFM_CONTEXT) * mi_height); + + int64_t this_rd = 0; + for (int idy = 0, block = 0; idy < mi_height; idy += bh) { + for (int idx = 0; idx < mi_width; idx += bw) { + RD_STATS pn_rd_stats; + av1_init_rd_stats(&pn_rd_stats); + tx_block_yrd(cpi, x, idy, idx, block, max_tx_size, bsize, init_depth, + ctxa, ctxl, tx_above, tx_left, ref_best_rd - this_rd, + &pn_rd_stats, ftxs_mode); + if (pn_rd_stats.rate == INT_MAX) { + av1_invalid_rd_stats(rd_stats); + return 0; + } + av1_merge_rd_stats(rd_stats, &pn_rd_stats); + this_rd += + AOMMIN(RDCOST(x->rdmult, pn_rd_stats.rate, pn_rd_stats.dist), + RDCOST(x->rdmult, pn_rd_stats.zero_rate, pn_rd_stats.sse)); + block += step; + } + } + + const int skip_ctx = av1_get_skip_txfm_context(xd); + const int no_skip_txfm_rate = x->mode_costs.skip_txfm_cost[skip_ctx][0]; + const int skip_txfm_rate = x->mode_costs.skip_txfm_cost[skip_ctx][1]; + const int64_t skip_txfm_rd = RDCOST(x->rdmult, skip_txfm_rate, rd_stats->sse); + this_rd = + RDCOST(x->rdmult, rd_stats->rate + no_skip_txfm_rate, rd_stats->dist); + if (skip_txfm_rd < this_rd) { + this_rd = skip_txfm_rd; + rd_stats->rate = 0; + rd_stats->dist = rd_stats->sse; + rd_stats->skip_txfm = 1; + } + + const int is_cost_valid = this_rd > ref_best_rd; + if (!is_cost_valid) { + // reset cost value + av1_invalid_rd_stats(rd_stats); + } + return is_cost_valid; +} + +// Search for the best transform size and type for current inter-predicted +// luma block with recursive transform block partitioning. The obtained +// transform selection will be saved in xd->mi[0], the corresponding RD stats +// will be saved in rd_stats. The returned value is the corresponding RD cost. +static int64_t select_tx_size_and_type(const AV1_COMP *cpi, MACROBLOCK *x, + RD_STATS *rd_stats, BLOCK_SIZE bsize, + int64_t ref_best_rd) { + MACROBLOCKD *const xd = &x->e_mbd; + const TxfmSearchParams *txfm_params = &x->txfm_search_params; + assert(is_inter_block(xd->mi[0])); + assert(bsize < BLOCK_SIZES_ALL); + const int fast_tx_search = txfm_params->tx_size_search_method > USE_FULL_RD; + int64_t rd_thresh = ref_best_rd; + if (rd_thresh == 0) { + av1_invalid_rd_stats(rd_stats); + return INT64_MAX; + } + if (fast_tx_search && rd_thresh < INT64_MAX) { + if (INT64_MAX - rd_thresh > (rd_thresh >> 3)) rd_thresh += (rd_thresh >> 3); + } + assert(rd_thresh > 0); + const FAST_TX_SEARCH_MODE ftxs_mode = + fast_tx_search ? FTXS_DCT_AND_1D_DCT_ONLY : FTXS_NONE; + const struct macroblockd_plane *const pd = &xd->plane[0]; + assert(bsize < BLOCK_SIZES_ALL); + const int mi_width = mi_size_wide[bsize]; + const int mi_height = mi_size_high[bsize]; + ENTROPY_CONTEXT ctxa[MAX_MIB_SIZE]; + ENTROPY_CONTEXT ctxl[MAX_MIB_SIZE]; + TXFM_CONTEXT tx_above[MAX_MIB_SIZE]; + TXFM_CONTEXT tx_left[MAX_MIB_SIZE]; + av1_get_entropy_contexts(bsize, pd, ctxa, ctxl); + memcpy(tx_above, xd->above_txfm_context, sizeof(TXFM_CONTEXT) * mi_width); + memcpy(tx_left, xd->left_txfm_context, sizeof(TXFM_CONTEXT) * mi_height); + const int init_depth = get_search_init_depth( + mi_width, mi_height, 1, &cpi->sf, txfm_params->tx_size_search_method); + const TX_SIZE max_tx_size = max_txsize_rect_lookup[bsize]; + const int bh = tx_size_high_unit[max_tx_size]; + const int bw = tx_size_wide_unit[max_tx_size]; + const int step = bw * bh; + const int skip_ctx = av1_get_skip_txfm_context(xd); + const int no_skip_txfm_cost = x->mode_costs.skip_txfm_cost[skip_ctx][0]; + const int skip_txfm_cost = x->mode_costs.skip_txfm_cost[skip_ctx][1]; + int64_t skip_txfm_rd = RDCOST(x->rdmult, skip_txfm_cost, 0); + int64_t no_skip_txfm_rd = RDCOST(x->rdmult, no_skip_txfm_cost, 0); + int block = 0; + + av1_init_rd_stats(rd_stats); + for (int idy = 0; idy < max_block_high(xd, bsize, 0); idy += bh) { + for (int idx = 0; idx < max_block_wide(xd, bsize, 0); idx += bw) { + const int64_t best_rd_sofar = + (rd_thresh == INT64_MAX) + ? INT64_MAX + : (rd_thresh - (AOMMIN(skip_txfm_rd, no_skip_txfm_rd))); + int is_cost_valid = 1; + RD_STATS pn_rd_stats; + // Search for the best transform block size and type for the sub-block. + select_tx_block(cpi, x, idy, idx, block, max_tx_size, init_depth, bsize, + ctxa, ctxl, tx_above, tx_left, &pn_rd_stats, INT64_MAX, + best_rd_sofar, &is_cost_valid, ftxs_mode); + if (!is_cost_valid || pn_rd_stats.rate == INT_MAX) { + av1_invalid_rd_stats(rd_stats); + return INT64_MAX; + } + av1_merge_rd_stats(rd_stats, &pn_rd_stats); + skip_txfm_rd = RDCOST(x->rdmult, skip_txfm_cost, rd_stats->sse); + no_skip_txfm_rd = + RDCOST(x->rdmult, rd_stats->rate + no_skip_txfm_cost, rd_stats->dist); + block += step; + } + } + + if (rd_stats->rate == INT_MAX) return INT64_MAX; + + rd_stats->skip_txfm = (skip_txfm_rd <= no_skip_txfm_rd); + + // If fast_tx_search is true, only DCT and 1D DCT were tested in + // select_inter_block_yrd() above. Do a better search for tx type with + // tx sizes already decided. + if (fast_tx_search && cpi->sf.tx_sf.refine_fast_tx_search_results) { + if (!inter_block_yrd(cpi, x, rd_stats, bsize, ref_best_rd, FTXS_NONE)) + return INT64_MAX; + } + + int64_t final_rd; + if (rd_stats->skip_txfm) { + final_rd = RDCOST(x->rdmult, skip_txfm_cost, rd_stats->sse); + } else { + final_rd = + RDCOST(x->rdmult, rd_stats->rate + no_skip_txfm_cost, rd_stats->dist); + if (!xd->lossless[xd->mi[0]->segment_id]) { + final_rd = + AOMMIN(final_rd, RDCOST(x->rdmult, skip_txfm_cost, rd_stats->sse)); + } + } + + return final_rd; +} + +// Return 1 to terminate transform search early. The decision is made based on +// the comparison with the reference RD cost and the model-estimated RD cost. +static AOM_INLINE int model_based_tx_search_prune(const AV1_COMP *cpi, + MACROBLOCK *x, + BLOCK_SIZE bsize, + int64_t ref_best_rd) { + const int level = cpi->sf.tx_sf.model_based_prune_tx_search_level; + assert(level >= 0 && level <= 2); + int model_rate; + int64_t model_dist; + uint8_t model_skip; + MACROBLOCKD *const xd = &x->e_mbd; + model_rd_sb_fn[MODELRD_TYPE_TX_SEARCH_PRUNE]( + cpi, bsize, x, xd, 0, 0, &model_rate, &model_dist, &model_skip, NULL, + NULL, NULL, NULL); + if (model_skip) return 0; + const int64_t model_rd = RDCOST(x->rdmult, model_rate, model_dist); + // TODO(debargha, urvang): Improve the model and make the check below + // tighter. + static const int prune_factor_by8[] = { 3, 5 }; + const int factor = prune_factor_by8[level - 1]; + return ((model_rd * factor) >> 3) > ref_best_rd; +} + +void av1_pick_recursive_tx_size_type_yrd(const AV1_COMP *cpi, MACROBLOCK *x, + RD_STATS *rd_stats, BLOCK_SIZE bsize, + int64_t ref_best_rd) { + MACROBLOCKD *const xd = &x->e_mbd; + const TxfmSearchParams *txfm_params = &x->txfm_search_params; + assert(is_inter_block(xd->mi[0])); + + av1_invalid_rd_stats(rd_stats); + + // If modeled RD cost is a lot worse than the best so far, terminate early. + if (cpi->sf.tx_sf.model_based_prune_tx_search_level && + ref_best_rd != INT64_MAX) { + if (model_based_tx_search_prune(cpi, x, bsize, ref_best_rd)) return; + } + + // Hashing based speed feature. If the hash of the prediction residue block is + // found in the hash table, use previous search results and terminate early. + uint32_t hash = 0; + MB_RD_RECORD *mb_rd_record = NULL; + const int mi_row = x->e_mbd.mi_row; + const int mi_col = x->e_mbd.mi_col; + const int within_border = + mi_row >= xd->tile.mi_row_start && + (mi_row + mi_size_high[bsize] < xd->tile.mi_row_end) && + mi_col >= xd->tile.mi_col_start && + (mi_col + mi_size_wide[bsize] < xd->tile.mi_col_end); + const int is_mb_rd_hash_enabled = + (within_border && cpi->sf.rd_sf.use_mb_rd_hash); + const int n4 = bsize_to_num_blk(bsize); + if (is_mb_rd_hash_enabled) { + hash = get_block_residue_hash(x, bsize); + mb_rd_record = x->txfm_search_info.mb_rd_record; + const int match_index = find_mb_rd_info(mb_rd_record, ref_best_rd, hash); + if (match_index != -1) { + MB_RD_INFO *mb_rd_info = &mb_rd_record->mb_rd_info[match_index]; + fetch_mb_rd_info(n4, mb_rd_info, rd_stats, x); + return; + } + } + + // If we predict that skip is the optimal RD decision - set the respective + // context and terminate early. + int64_t dist; + if (txfm_params->skip_txfm_level && + predict_skip_txfm(x, bsize, &dist, + cpi->common.features.reduced_tx_set_used)) { + set_skip_txfm(x, rd_stats, bsize, dist); + // Save the RD search results into mb_rd_record. + if (is_mb_rd_hash_enabled) + save_mb_rd_info(n4, hash, x, rd_stats, mb_rd_record); + return; + } +#if CONFIG_SPEED_STATS + ++x->txfm_search_info.tx_search_count; +#endif // CONFIG_SPEED_STATS + + const int64_t rd = + select_tx_size_and_type(cpi, x, rd_stats, bsize, ref_best_rd); + + if (rd == INT64_MAX) { + // We should always find at least one candidate unless ref_best_rd is less + // than INT64_MAX (in which case, all the calls to select_tx_size_fix_type + // might have failed to find something better) + assert(ref_best_rd != INT64_MAX); + av1_invalid_rd_stats(rd_stats); + return; + } + + // Save the RD search results into mb_rd_record. + if (is_mb_rd_hash_enabled) { + assert(mb_rd_record != NULL); + save_mb_rd_info(n4, hash, x, rd_stats, mb_rd_record); + } +} + +void av1_pick_uniform_tx_size_type_yrd(const AV1_COMP *const cpi, MACROBLOCK *x, + RD_STATS *rd_stats, BLOCK_SIZE bs, + int64_t ref_best_rd) { + MACROBLOCKD *const xd = &x->e_mbd; + MB_MODE_INFO *const mbmi = xd->mi[0]; + const TxfmSearchParams *tx_params = &x->txfm_search_params; + assert(bs == mbmi->bsize); + const int is_inter = is_inter_block(mbmi); + const int mi_row = xd->mi_row; + const int mi_col = xd->mi_col; + + av1_init_rd_stats(rd_stats); + + // Hashing based speed feature for inter blocks. If the hash of the residue + // block is found in the table, use previously saved search results and + // terminate early. + uint32_t hash = 0; + MB_RD_RECORD *mb_rd_record = NULL; + const int num_blks = bsize_to_num_blk(bs); + if (is_inter && cpi->sf.rd_sf.use_mb_rd_hash) { + const int within_border = + mi_row >= xd->tile.mi_row_start && + (mi_row + mi_size_high[bs] < xd->tile.mi_row_end) && + mi_col >= xd->tile.mi_col_start && + (mi_col + mi_size_wide[bs] < xd->tile.mi_col_end); + if (within_border) { + hash = get_block_residue_hash(x, bs); + mb_rd_record = x->txfm_search_info.mb_rd_record; + const int match_index = find_mb_rd_info(mb_rd_record, ref_best_rd, hash); + if (match_index != -1) { + MB_RD_INFO *mb_rd_info = &mb_rd_record->mb_rd_info[match_index]; + fetch_mb_rd_info(num_blks, mb_rd_info, rd_stats, x); + return; + } + } + } + + // If we predict that skip is the optimal RD decision - set the respective + // context and terminate early. + int64_t dist; + if (tx_params->skip_txfm_level && is_inter && + !xd->lossless[mbmi->segment_id] && + predict_skip_txfm(x, bs, &dist, + cpi->common.features.reduced_tx_set_used)) { + // Populate rdstats as per skip decision + set_skip_txfm(x, rd_stats, bs, dist); + // Save the RD search results into mb_rd_record. + if (mb_rd_record) { + save_mb_rd_info(num_blks, hash, x, rd_stats, mb_rd_record); + } + return; + } + + if (xd->lossless[mbmi->segment_id]) { + // Lossless mode can only pick the smallest (4x4) transform size. + choose_smallest_tx_size(cpi, x, rd_stats, ref_best_rd, bs); + } else if (tx_params->tx_size_search_method == USE_LARGESTALL) { + choose_largest_tx_size(cpi, x, rd_stats, ref_best_rd, bs); + } else { + choose_tx_size_type_from_rd(cpi, x, rd_stats, ref_best_rd, bs); + } + + // Save the RD search results into mb_rd_record for possible reuse in future. + if (mb_rd_record) { + save_mb_rd_info(num_blks, hash, x, rd_stats, mb_rd_record); + } +} + +int av1_txfm_uvrd(const AV1_COMP *const cpi, MACROBLOCK *x, RD_STATS *rd_stats, + BLOCK_SIZE bsize, int64_t ref_best_rd) { + av1_init_rd_stats(rd_stats); + if (ref_best_rd < 0) return 0; + if (!x->e_mbd.is_chroma_ref) return 1; + + MACROBLOCKD *const xd = &x->e_mbd; + MB_MODE_INFO *const mbmi = xd->mi[0]; + struct macroblockd_plane *const pd = &xd->plane[AOM_PLANE_U]; + const int is_inter = is_inter_block(mbmi); + int64_t this_rd = 0, skip_txfm_rd = 0; + const BLOCK_SIZE plane_bsize = + get_plane_block_size(bsize, pd->subsampling_x, pd->subsampling_y); + + if (is_inter) { + for (int plane = 1; plane < MAX_MB_PLANE; ++plane) + av1_subtract_plane(x, plane_bsize, plane); + } + + const int skip_trellis = 0; + const TX_SIZE uv_tx_size = av1_get_tx_size(AOM_PLANE_U, xd); + int is_cost_valid = 1; + for (int plane = 1; plane < MAX_MB_PLANE; ++plane) { + RD_STATS this_rd_stats; + int64_t chroma_ref_best_rd = ref_best_rd; + // For inter blocks, refined ref_best_rd is used for early exit + // For intra blocks, even though current rd crosses ref_best_rd, early + // exit is not recommended as current rd is used for gating subsequent + // modes as well (say, for angular modes) + // TODO(any): Extend the early exit mechanism for intra modes as well + if (cpi->sf.inter_sf.perform_best_rd_based_gating_for_chroma && is_inter && + chroma_ref_best_rd != INT64_MAX) + chroma_ref_best_rd = ref_best_rd - AOMMIN(this_rd, skip_txfm_rd); + av1_txfm_rd_in_plane(x, cpi, &this_rd_stats, chroma_ref_best_rd, 0, plane, + plane_bsize, uv_tx_size, FTXS_NONE, skip_trellis); + if (this_rd_stats.rate == INT_MAX) { + is_cost_valid = 0; + break; + } + av1_merge_rd_stats(rd_stats, &this_rd_stats); + this_rd = RDCOST(x->rdmult, rd_stats->rate, rd_stats->dist); + skip_txfm_rd = RDCOST(x->rdmult, 0, rd_stats->sse); + if (AOMMIN(this_rd, skip_txfm_rd) > ref_best_rd) { + is_cost_valid = 0; + break; + } + } + + if (!is_cost_valid) { + // reset cost value + av1_invalid_rd_stats(rd_stats); + } + + return is_cost_valid; +} + +void av1_txfm_rd_in_plane(MACROBLOCK *x, const AV1_COMP *cpi, + RD_STATS *rd_stats, int64_t ref_best_rd, + int64_t current_rd, int plane, BLOCK_SIZE plane_bsize, + TX_SIZE tx_size, FAST_TX_SEARCH_MODE ftxs_mode, + int skip_trellis) { + assert(IMPLIES(plane == 0, x->e_mbd.mi[0]->tx_size == tx_size)); + + if (!cpi->oxcf.txfm_cfg.enable_tx64 && + txsize_sqr_up_map[tx_size] == TX_64X64) { + av1_invalid_rd_stats(rd_stats); + return; + } + + if (current_rd > ref_best_rd) { + av1_invalid_rd_stats(rd_stats); + return; + } + + MACROBLOCKD *const xd = &x->e_mbd; + const struct macroblockd_plane *const pd = &xd->plane[plane]; + struct rdcost_block_args args; + av1_zero(args); + args.x = x; + args.cpi = cpi; + args.best_rd = ref_best_rd; + args.current_rd = current_rd; + args.ftxs_mode = ftxs_mode; + args.skip_trellis = skip_trellis; + av1_init_rd_stats(&args.rd_stats); + + av1_get_entropy_contexts(plane_bsize, pd, args.t_above, args.t_left); + av1_foreach_transformed_block_in_plane(xd, plane_bsize, plane, block_rd_txfm, + &args); + + MB_MODE_INFO *const mbmi = xd->mi[0]; + const int is_inter = is_inter_block(mbmi); + const int invalid_rd = is_inter ? args.incomplete_exit : args.exit_early; + + if (invalid_rd) { + av1_invalid_rd_stats(rd_stats); + } else { + *rd_stats = args.rd_stats; + } +} + +int av1_txfm_search(const AV1_COMP *cpi, MACROBLOCK *x, BLOCK_SIZE bsize, + RD_STATS *rd_stats, RD_STATS *rd_stats_y, + RD_STATS *rd_stats_uv, int mode_rate, int64_t ref_best_rd) { + MACROBLOCKD *const xd = &x->e_mbd; + TxfmSearchParams *txfm_params = &x->txfm_search_params; + const int skip_ctx = av1_get_skip_txfm_context(xd); + const int skip_txfm_cost[2] = { x->mode_costs.skip_txfm_cost[skip_ctx][0], + x->mode_costs.skip_txfm_cost[skip_ctx][1] }; + const int64_t min_header_rate = + mode_rate + AOMMIN(skip_txfm_cost[0], skip_txfm_cost[1]); + // Account for minimum skip and non_skip rd. + // Eventually either one of them will be added to mode_rate + const int64_t min_header_rd_possible = RDCOST(x->rdmult, min_header_rate, 0); + if (min_header_rd_possible > ref_best_rd) { + av1_invalid_rd_stats(rd_stats_y); + return 0; + } + + const AV1_COMMON *cm = &cpi->common; + MB_MODE_INFO *const mbmi = xd->mi[0]; + const int64_t mode_rd = RDCOST(x->rdmult, mode_rate, 0); + const int64_t rd_thresh = + ref_best_rd == INT64_MAX ? INT64_MAX : ref_best_rd - mode_rd; + av1_init_rd_stats(rd_stats); + av1_init_rd_stats(rd_stats_y); + rd_stats->rate = mode_rate; + + // cost and distortion + av1_subtract_plane(x, bsize, 0); + if (txfm_params->tx_mode_search_type == TX_MODE_SELECT && + !xd->lossless[mbmi->segment_id]) { + av1_pick_recursive_tx_size_type_yrd(cpi, x, rd_stats_y, bsize, rd_thresh); +#if CONFIG_COLLECT_RD_STATS == 2 + PrintPredictionUnitStats(cpi, tile_data, x, rd_stats_y, bsize); +#endif // CONFIG_COLLECT_RD_STATS == 2 + } else { + av1_pick_uniform_tx_size_type_yrd(cpi, x, rd_stats_y, bsize, rd_thresh); + memset(mbmi->inter_tx_size, mbmi->tx_size, sizeof(mbmi->inter_tx_size)); + for (int i = 0; i < xd->height * xd->width; ++i) + set_blk_skip(x->txfm_search_info.blk_skip, 0, i, rd_stats_y->skip_txfm); + } + + if (rd_stats_y->rate == INT_MAX) return 0; + + av1_merge_rd_stats(rd_stats, rd_stats_y); + + const int64_t non_skip_txfm_rdcosty = + RDCOST(x->rdmult, rd_stats->rate + skip_txfm_cost[0], rd_stats->dist); + const int64_t skip_txfm_rdcosty = + RDCOST(x->rdmult, mode_rate + skip_txfm_cost[1], rd_stats->sse); + const int64_t min_rdcosty = AOMMIN(non_skip_txfm_rdcosty, skip_txfm_rdcosty); + if (min_rdcosty > ref_best_rd) return 0; + + av1_init_rd_stats(rd_stats_uv); + const int num_planes = av1_num_planes(cm); + if (num_planes > 1) { + int64_t ref_best_chroma_rd = ref_best_rd; + // Calculate best rd cost possible for chroma + if (cpi->sf.inter_sf.perform_best_rd_based_gating_for_chroma && + (ref_best_chroma_rd != INT64_MAX)) { + ref_best_chroma_rd = (ref_best_chroma_rd - + AOMMIN(non_skip_txfm_rdcosty, skip_txfm_rdcosty)); + } + const int is_cost_valid_uv = + av1_txfm_uvrd(cpi, x, rd_stats_uv, bsize, ref_best_chroma_rd); + if (!is_cost_valid_uv) return 0; + av1_merge_rd_stats(rd_stats, rd_stats_uv); + } + + int choose_skip_txfm = rd_stats->skip_txfm; + if (!choose_skip_txfm && !xd->lossless[mbmi->segment_id]) { + const int64_t rdcost_no_skip_txfm = RDCOST( + x->rdmult, rd_stats_y->rate + rd_stats_uv->rate + skip_txfm_cost[0], + rd_stats->dist); + const int64_t rdcost_skip_txfm = + RDCOST(x->rdmult, skip_txfm_cost[1], rd_stats->sse); + if (rdcost_no_skip_txfm >= rdcost_skip_txfm) choose_skip_txfm = 1; + } + if (choose_skip_txfm) { + rd_stats_y->rate = 0; + rd_stats_uv->rate = 0; + rd_stats->rate = mode_rate + skip_txfm_cost[1]; + rd_stats->dist = rd_stats->sse; + rd_stats_y->dist = rd_stats_y->sse; + rd_stats_uv->dist = rd_stats_uv->sse; + mbmi->skip_txfm = 1; + if (rd_stats->skip_txfm) { + const int64_t tmprd = RDCOST(x->rdmult, rd_stats->rate, rd_stats->dist); + if (tmprd > ref_best_rd) return 0; + } + } else { + rd_stats->rate += skip_txfm_cost[0]; + mbmi->skip_txfm = 0; + } + + return 1; +} |