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aomedia / aom / e95bcdf854e2072e6db8588823ad8e24cb019397 / . / av1 / encoder / tx_search.c
blob: 7292c01191758d245bf67381f7278fdc883acfaa [file] [log] [blame]
/*
* 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, &param);
// 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;
}