| /* |
| * Copyright (c) 2019, 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 <float.h> |
| |
| #include "av1/encoder/encodeframe_utils.h" |
| #include "av1/encoder/thirdpass.h" |
| #include "config/aom_dsp_rtcd.h" |
| |
| #include "av1/common/enums.h" |
| #include "av1/common/reconinter.h" |
| |
| #if !CONFIG_REALTIME_ONLY |
| #include "av1/encoder/cnn.h" |
| #include "av1/encoder/partition_model_weights.h" |
| #include "av1/encoder/partition_cnn_weights.h" |
| #endif |
| #include "av1/encoder/encoder.h" |
| |
| #include "av1/encoder/motion_search_facade.h" |
| #include "av1/encoder/partition_strategy.h" |
| #include "av1/encoder/partition_search.h" |
| #include "av1/encoder/rdopt.h" |
| |
| #if !CONFIG_REALTIME_ONLY |
| static AOM_INLINE void simple_motion_search_prune_part_features( |
| AV1_COMP *const cpi, MACROBLOCK *x, SIMPLE_MOTION_DATA_TREE *sms_tree, |
| int mi_row, int mi_col, BLOCK_SIZE bsize, float *features, |
| int features_to_get); |
| |
| static bool ext_ml_model_decision_before_none( |
| AV1_COMP *cpi, const float features_from_motion[FEATURE_SIZE_SMS_SPLIT], |
| int *partition_none_allowed, int *partition_horz_allowed, |
| int *partition_vert_allowed, int *do_rectangular_split, |
| int *do_square_split); |
| |
| static bool ext_ml_model_decision_before_none_part2( |
| AV1_COMP *cpi, |
| const float features_from_motion[FEATURE_SIZE_SMS_PRUNE_PART], |
| int *prune_horz, int *prune_vert); |
| |
| static bool ext_ml_model_decision_after_none( |
| ExtPartController *const ext_part_controller, const int is_intra_frame, |
| const float *const features_after_none, int *do_square_split, |
| int *do_rectangular_split); |
| |
| static bool ext_ml_model_decision_after_none_part2( |
| AV1_COMP *const cpi, const float *const features_terminate, |
| int *terminate_partition_search); |
| |
| static bool ext_ml_model_decision_after_split( |
| AV1_COMP *const cpi, const float *const features_terminate, |
| int *terminate_partition_search); |
| |
| static bool ext_ml_model_decision_after_split_part2( |
| ExtPartController *const ext_part_controller, const int is_intra_frame, |
| const float *const features_prune, int *prune_rect_part_horz, |
| int *prune_rect_part_vert); |
| |
| static bool ext_ml_model_decision_after_rect( |
| ExtPartController *const ext_part_controller, const int is_intra_frame, |
| const float *const features_after_rect, int *horza_partition_allowed, |
| int *horzb_partition_allowed, int *verta_partition_allowed, |
| int *vertb_partition_allowed); |
| |
| static bool ext_ml_model_decision_after_part_ab( |
| AV1_COMP *const cpi, MACROBLOCK *const x, BLOCK_SIZE bsize, int part_ctx, |
| int64_t best_rd, int64_t rect_part_rd[NUM_RECT_PARTS][SUB_PARTITIONS_RECT], |
| int64_t split_rd[SUB_PARTITIONS_SPLIT], int *const partition_horz4_allowed, |
| int *const partition_vert4_allowed, unsigned int pb_source_variance, |
| int mi_row, int mi_col); |
| |
| static INLINE int convert_bsize_to_idx(BLOCK_SIZE bsize) { |
| switch (bsize) { |
| case BLOCK_128X128: return 0; |
| case BLOCK_64X64: return 1; |
| case BLOCK_32X32: return 2; |
| case BLOCK_16X16: return 3; |
| case BLOCK_8X8: return 4; |
| default: assert(0 && "Invalid bsize"); return -1; |
| } |
| } |
| |
| static char *get_feature_file_name(int id) { |
| static char *feature_file_names[] = { |
| "feature_before_partition_none", |
| "feature_before_partition_none_prune_rect", |
| "feature_after_partition_none_prune", |
| "feature_after_partition_none_terminate", |
| "feature_after_partition_split_terminate", |
| "feature_after_partition_split_prune_rect", |
| "feature_after_partition_rect", |
| "feature_after_partition_ab", |
| }; |
| |
| return feature_file_names[id]; |
| } |
| |
| static void write_features_to_file(const char *const path, |
| const bool is_test_mode, |
| const float *features, |
| const int feature_size, const int id, |
| const int bsize, const int mi_row, |
| const int mi_col) { |
| if (!WRITE_FEATURE_TO_FILE && !is_test_mode) return; |
| |
| char filename[256]; |
| snprintf(filename, sizeof(filename), "%s/%s", path, |
| get_feature_file_name(id)); |
| FILE *pfile = fopen(filename, "a"); |
| if (pfile == NULL) return; |
| if (!is_test_mode) { |
| fprintf(pfile, "%d,%d,%d,%d,%d\n", id, bsize, mi_row, mi_col, feature_size); |
| } |
| for (int i = 0; i < feature_size; ++i) { |
| fprintf(pfile, "%.6f", features[i]); |
| if (i < feature_size - 1) fprintf(pfile, ","); |
| } |
| fprintf(pfile, "\n"); |
| fclose(pfile); |
| } |
| |
| // TODO(chiyotsai@google.com): This is very much a work in progress. We still |
| // need to the following: |
| // -- add support for hdres |
| // -- add support for pruning rectangular partitions |
| // -- use reconstructed pixels instead of source pixels for padding |
| // -- use chroma pixels in addition to luma pixels |
| void av1_intra_mode_cnn_partition(const AV1_COMMON *const cm, MACROBLOCK *x, |
| int quad_tree_idx, |
| int intra_cnn_based_part_prune_level, |
| PartitionSearchState *part_state) { |
| assert(cm->seq_params->sb_size >= BLOCK_64X64 && |
| "Invalid sb_size for intra_cnn!"); |
| const PartitionBlkParams *blk_params = &part_state->part_blk_params; |
| const BLOCK_SIZE bsize = blk_params->bsize; |
| |
| const int bsize_idx = convert_bsize_to_idx(bsize); |
| |
| if (bsize == BLOCK_128X128) { |
| return; |
| } |
| |
| PartitionSearchInfo *part_info = &x->part_search_info; |
| |
| // Precompute the CNN part and cache the result in MACROBLOCK |
| if (bsize == BLOCK_64X64 && !part_info->cnn_output_valid) { |
| const CNN_CONFIG *cnn_config = &av1_intra_mode_cnn_partition_cnn_config; |
| |
| // Prepare the output |
| const CNN_THREAD_DATA thread_data = { .num_workers = 1, .workers = NULL }; |
| const int num_outputs = 4; |
| const int output_dims[4] = { 1, 2, 4, 8 }; |
| const int out_chs[4] = { CNN_BRANCH_0_OUT_CH, CNN_BRANCH_1_OUT_CH, |
| CNN_BRANCH_2_OUT_CH, CNN_BRANCH_3_OUT_CH }; |
| float *output_buffer[CNN_TOT_OUT_CH]; |
| |
| float **cur_output_buf = output_buffer; |
| float *curr_buf_ptr = part_info->cnn_buffer; |
| for (int output_idx = 0; output_idx < num_outputs; output_idx++) { |
| const int num_chs = out_chs[output_idx]; |
| const int ch_size = output_dims[output_idx] * output_dims[output_idx]; |
| for (int ch = 0; ch < num_chs; ch++) { |
| cur_output_buf[ch] = curr_buf_ptr; |
| curr_buf_ptr += ch_size; |
| } |
| cur_output_buf += num_chs; |
| } |
| |
| CNN_MULTI_OUT output = { |
| .num_outputs = 4, |
| .output_channels = out_chs, |
| .output_strides = output_dims, |
| .output_buffer = output_buffer, |
| }; |
| |
| // Prepare the input |
| const MACROBLOCKD *xd = &x->e_mbd; |
| const int bit_depth = xd->bd; |
| const int dc_q = |
| av1_dc_quant_QTX(x->qindex, 0, bit_depth) >> (bit_depth - 8); |
| part_info->log_q = logf(1.0f + (float)(dc_q * dc_q) / 256.0f); |
| part_info->log_q = |
| (part_info->log_q - av1_intra_mode_cnn_partition_mean[0]) / |
| av1_intra_mode_cnn_partition_std[0]; |
| |
| const int width = 65, height = 65, |
| stride = x->plane[AOM_PLANE_Y].src.stride; |
| |
| if (xd->cur_buf->flags & YV12_FLAG_HIGHBITDEPTH) { |
| uint16_t *image[1] = { |
| CONVERT_TO_SHORTPTR(x->plane[AOM_PLANE_Y].src.buf) - stride - 1 |
| }; |
| |
| if (!av1_cnn_predict_img_multi_out_highbd(image, width, height, stride, |
| cnn_config, &thread_data, |
| bit_depth, &output)) { |
| aom_internal_error(cm->error, AOM_CODEC_MEM_ERROR, |
| "Error allocating CNN data"); |
| return; |
| } |
| } else { |
| uint8_t *image[1] = { x->plane[AOM_PLANE_Y].src.buf - stride - 1 }; |
| |
| if (!av1_cnn_predict_img_multi_out(image, width, height, stride, |
| cnn_config, &thread_data, &output)) { |
| aom_internal_error(cm->error, AOM_CODEC_MEM_ERROR, |
| "Error allocating CNN data"); |
| return; |
| } |
| } |
| |
| part_info->cnn_output_valid = 1; |
| } |
| |
| if (!part_info->cnn_output_valid) { |
| return; |
| } |
| |
| const NN_CONFIG *dnn_configs[5] = { |
| NULL, |
| &av1_intra_mode_cnn_partition_branch_0_dnn_config, |
| &av1_intra_mode_cnn_partition_branch_1_dnn_config, |
| &av1_intra_mode_cnn_partition_branch_2_dnn_config, |
| &av1_intra_mode_cnn_partition_branch_3_dnn_config, |
| }; |
| |
| const NN_CONFIG *dnn_config = dnn_configs[bsize_idx]; |
| |
| float dnn_features[100]; |
| float logits[4] = { 0.0f }; |
| |
| const float *branch_0 = part_info->cnn_buffer; |
| const float *branch_1 = branch_0 + CNN_BRANCH_0_OUT_SIZE; |
| const float *branch_2 = branch_1 + CNN_BRANCH_1_OUT_SIZE; |
| const float *branch_3 = branch_2 + CNN_BRANCH_2_OUT_SIZE; |
| |
| if (bsize == BLOCK_64X64) { |
| int f_idx = 0; |
| for (int ch_idx = 0; ch_idx < CNN_BRANCH_0_OUT_CH; ch_idx++) { |
| dnn_features[f_idx++] = branch_0[ch_idx]; |
| } |
| |
| const int spa_stride = 2 * 2; |
| for (int lin_idx = 0; lin_idx < spa_stride; lin_idx++) { |
| for (int ch_idx = 0; ch_idx < CNN_BRANCH_1_OUT_CH; ch_idx++) { |
| dnn_features[f_idx++] = branch_1[lin_idx + ch_idx * spa_stride]; |
| } |
| } |
| dnn_features[f_idx++] = part_info->log_q; |
| } else if (bsize == BLOCK_32X32) { |
| int f_idx = 0; |
| for (int idx = 0; idx < CNN_BRANCH_0_OUT_CH; idx++) { |
| dnn_features[f_idx++] = branch_0[idx]; |
| } |
| |
| const int curr_lin_idx = quad_to_linear_1[quad_tree_idx - 1]; |
| const int spa_stride = 2 * 2; |
| for (int ch_idx = 0; ch_idx < CNN_BRANCH_1_OUT_CH; ch_idx++) { |
| dnn_features[f_idx++] = branch_1[curr_lin_idx + ch_idx * spa_stride]; |
| } |
| dnn_features[f_idx++] = part_info->log_q; |
| } else if (bsize == BLOCK_16X16) { |
| int f_idx = 0; |
| const int prev_quad_idx = (quad_tree_idx - 1) / 4; |
| const int prev_lin_idx = quad_to_linear_1[prev_quad_idx - 1]; |
| const int prev_spa_stride = 2 * 2; |
| for (int ch_idx = 0; ch_idx < CNN_BRANCH_1_OUT_CH; ch_idx++) { |
| dnn_features[f_idx++] = branch_1[prev_lin_idx + ch_idx * prev_spa_stride]; |
| } |
| |
| const int curr_lin_idx = quad_to_linear_2[quad_tree_idx - 5]; |
| const int spa_stride = 4 * 4; |
| for (int ch_idx = 0; ch_idx < CNN_BRANCH_2_OUT_CH; ch_idx++) { |
| dnn_features[f_idx++] = branch_2[curr_lin_idx + ch_idx * spa_stride]; |
| } |
| dnn_features[f_idx++] = part_info->log_q; |
| } else if (bsize == BLOCK_8X8) { |
| int f_idx = 0; |
| const int prev_quad_idx = (quad_tree_idx - 1) / 4; |
| const int prev_lin_idx = quad_to_linear_2[prev_quad_idx - 5]; |
| const int prev_spa_stride = 4 * 4; |
| for (int ch_idx = 0; ch_idx < CNN_BRANCH_2_OUT_CH; ch_idx++) { |
| dnn_features[f_idx++] = branch_2[prev_lin_idx + ch_idx * prev_spa_stride]; |
| } |
| |
| const int curr_lin_idx = quad_to_linear_3[quad_tree_idx - 21]; |
| const int spa_stride = 8 * 8; |
| for (int ch_idx = 0; ch_idx < CNN_BRANCH_3_OUT_CH; ch_idx++) { |
| dnn_features[f_idx++] = branch_3[curr_lin_idx + ch_idx * spa_stride]; |
| } |
| dnn_features[f_idx++] = part_info->log_q; |
| } else { |
| assert(0 && "Invalid bsize in intra_cnn partition"); |
| } |
| |
| // Make decision |
| av1_nn_predict(dnn_features, dnn_config, 1, logits); |
| |
| const int is_720p_or_larger = AOMMIN(cm->width, cm->height) >= 720; |
| const int is_480p_or_larger = AOMMIN(cm->width, cm->height) >= 480; |
| float split_only_thresh = 100.0f, no_split_thresh = -100.0f; |
| if (is_720p_or_larger) { |
| split_only_thresh = |
| av1_intra_mode_cnn_partition_split_thresh_hdres[bsize_idx]; |
| no_split_thresh = |
| av1_intra_mode_cnn_partition_no_split_thresh_hdres[bsize_idx]; |
| } else if (is_480p_or_larger) { |
| split_only_thresh = |
| av1_intra_mode_cnn_partition_split_thresh_midres[bsize_idx]; |
| no_split_thresh = |
| av1_intra_mode_cnn_partition_no_split_thresh_midres[bsize_idx]; |
| } else { |
| split_only_thresh = |
| av1_intra_mode_cnn_partition_split_thresh_lowres[bsize_idx]; |
| no_split_thresh = |
| av1_intra_mode_cnn_partition_no_split_thresh_lowres[bsize_idx]; |
| } |
| |
| if (logits[0] > split_only_thresh) { |
| // As screen contents tend to choose larger partitions, do not prune |
| // PARTITION_NONE when intra_cnn_based_part_prune_level=1. |
| if (intra_cnn_based_part_prune_level != 1) { |
| part_state->partition_none_allowed = 0; |
| } |
| part_state->do_square_split = 1; |
| av1_disable_rect_partitions(part_state); |
| } |
| |
| if (logits[0] < no_split_thresh) { |
| av1_disable_square_split_partition(part_state); |
| } |
| } |
| |
| static INLINE int get_simple_motion_search_prune_agg(int qindex, |
| int prune_level, |
| int is_rect_part) { |
| assert(prune_level < TOTAL_AGG_LVLS); |
| if (prune_level == NO_PRUNING) { |
| return -1; |
| } |
| |
| // Aggressiveness value for SIMPLE_MOTION_SEARCH_PRUNE_LEVEL except |
| // QIDX_BASED_AGG_LVL |
| const int sms_prune_agg_levels[TOTAL_SIMPLE_AGG_LVLS] = { 0, 1, 2, 3 }; |
| if (prune_level < TOTAL_SIMPLE_AGG_LVLS) { |
| return sms_prune_agg_levels[prune_level]; |
| } |
| |
| // Map the QIDX_BASED_AGG_LVL to corresponding aggressiveness value. |
| // Aggressive pruning for lower quantizers in non-boosted frames to prune |
| // rectangular partitions. |
| const int qband = is_rect_part ? (qindex <= 90 ? 1 : 0) : 0; |
| const int sms_prune_agg_qindex_based[2] = { 1, 2 }; |
| return sms_prune_agg_qindex_based[qband]; |
| } |
| |
| void av1_simple_motion_search_based_split(AV1_COMP *const cpi, MACROBLOCK *x, |
| SIMPLE_MOTION_DATA_TREE *sms_tree, |
| PartitionSearchState *part_state) { |
| const AV1_COMMON *const cm = &cpi->common; |
| const PartitionBlkParams *blk_params = &part_state->part_blk_params; |
| const int mi_row = blk_params->mi_row, mi_col = blk_params->mi_col; |
| const BLOCK_SIZE bsize = blk_params->bsize; |
| |
| const int bsize_idx = convert_bsize_to_idx(bsize); |
| const int is_720p_or_larger = AOMMIN(cm->width, cm->height) >= 720; |
| const int is_480p_or_larger = AOMMIN(cm->width, cm->height) >= 480; |
| // res_idx is 0 for res < 480p, 1 for 480p, 2 for 720p+ |
| const int res_idx = is_480p_or_larger + is_720p_or_larger; |
| |
| assert(bsize_idx >= 0 && bsize_idx <= 4 && |
| "Invalid bsize in simple_motion_search_based_split"); |
| |
| const float *ml_mean = av1_simple_motion_search_split_mean[bsize_idx]; |
| const float *ml_std = av1_simple_motion_search_split_std[bsize_idx]; |
| const NN_CONFIG *nn_config = |
| av1_simple_motion_search_split_nn_config[bsize_idx]; |
| |
| const int agg = get_simple_motion_search_prune_agg( |
| x->qindex, cpi->sf.part_sf.simple_motion_search_prune_agg, 0); |
| if (agg < 0) { |
| return; |
| } |
| |
| const float split_only_thresh = |
| av1_simple_motion_search_split_thresh[agg][res_idx][bsize_idx]; |
| const float no_split_thresh = |
| av1_simple_motion_search_no_split_thresh[agg][res_idx][bsize_idx]; |
| |
| float features[FEATURE_SIZE_SMS_SPLIT] = { 0.0f }; |
| simple_motion_search_prune_part_features(cpi, x, sms_tree, mi_row, mi_col, |
| bsize, features, |
| FEATURE_SMS_SPLIT_MODEL_FLAG); |
| |
| // Write features to file |
| write_features_to_file(cpi->oxcf.partition_info_path, |
| cpi->ext_part_controller.test_mode, features, |
| FEATURE_SIZE_SMS_SPLIT, 0, bsize, mi_row, mi_col); |
| |
| // Note: it is intended to not normalize the features here, to keep it |
| // consistent for all features collected and passed to the external model. |
| if (ext_ml_model_decision_before_none( |
| cpi, features, &part_state->partition_none_allowed, |
| &part_state->partition_rect_allowed[HORZ], |
| &part_state->partition_rect_allowed[VERT], |
| &part_state->do_rectangular_split, &part_state->do_square_split)) { |
| return; |
| } |
| |
| for (int idx = 0; idx < FEATURE_SIZE_SMS_SPLIT; idx++) { |
| features[idx] = (features[idx] - ml_mean[idx]) / ml_std[idx]; |
| } |
| |
| float score = 0.0f; |
| |
| av1_nn_predict(features, nn_config, 1, &score); |
| |
| if (score > split_only_thresh) { |
| av1_set_square_split_only(part_state); |
| } |
| |
| if (cpi->sf.part_sf.simple_motion_search_split >= 2 && |
| score < no_split_thresh) { |
| av1_disable_square_split_partition(part_state); |
| } |
| |
| // If the score is very low, prune rectangular split since it is unlikely to |
| // occur. |
| if (cpi->sf.part_sf.simple_motion_search_rect_split) { |
| const float scale = res_idx >= 2 ? 3.0f : 2.0f; |
| const float rect_split_thresh = |
| scale * av1_simple_motion_search_no_split_thresh |
| [cpi->sf.part_sf.simple_motion_search_rect_split][res_idx] |
| [bsize_idx]; |
| if (score < rect_split_thresh) { |
| part_state->do_rectangular_split = 0; |
| } |
| } |
| } |
| |
| // Given a list of ref frames in refs, performs simple_motion_search on each of |
| // the refs and returns the ref with the smallest sse. Returns -1 if none of the |
| // ref in the list is available. Also stores the best sse and var in best_sse, |
| // best_var, respectively. If save_mv is 0, don't update mv_ref_fulls in |
| // sms_tree. If save_mv is 1, update mv_ref_fulls under sms_tree and the |
| // subtrees. |
| static int simple_motion_search_get_best_ref( |
| AV1_COMP *const cpi, MACROBLOCK *x, SIMPLE_MOTION_DATA_TREE *sms_tree, |
| int mi_row, int mi_col, BLOCK_SIZE bsize, const int *const refs, |
| int num_refs, int use_subpixel, int save_mv, unsigned int *best_sse, |
| unsigned int *best_var) { |
| const AV1_COMMON *const cm = &cpi->common; |
| int best_ref = -1; |
| |
| if (mi_col >= cm->mi_params.mi_cols || mi_row >= cm->mi_params.mi_rows) { |
| // If the whole block is outside of the image, set the var and sse to 0. |
| *best_var = 0; |
| *best_sse = 0; |
| |
| return best_ref; |
| } |
| |
| // Otherwise do loop through the reference frames and find the one with the |
| // minimum SSE |
| const MACROBLOCKD *xd = &x->e_mbd; |
| |
| const int num_planes = 1; |
| |
| *best_sse = INT_MAX; |
| |
| for (int ref_idx = 0; ref_idx < num_refs; ref_idx++) { |
| const int ref = refs[ref_idx]; |
| |
| if (cpi->ref_frame_flags & av1_ref_frame_flag_list[ref]) { |
| const FULLPEL_MV *start_mvs = sms_tree->start_mvs; |
| unsigned int curr_sse = 0, curr_var = 0; |
| int_mv best_mv = |
| av1_simple_motion_search(cpi, x, mi_row, mi_col, bsize, ref, |
| start_mvs[ref], num_planes, use_subpixel); |
| curr_var = cpi->ppi->fn_ptr[bsize].vf( |
| x->plane[0].src.buf, x->plane[0].src.stride, xd->plane[0].dst.buf, |
| xd->plane[0].dst.stride, &curr_sse); |
| if (curr_sse < *best_sse) { |
| *best_sse = curr_sse; |
| *best_var = curr_var; |
| best_ref = ref; |
| } |
| |
| if (save_mv) { |
| sms_tree->start_mvs[ref].row = best_mv.as_mv.row / 8; |
| sms_tree->start_mvs[ref].col = best_mv.as_mv.col / 8; |
| |
| if (bsize >= BLOCK_8X8) { |
| for (int r_idx = 0; r_idx < SUB_PARTITIONS_SPLIT; r_idx++) { |
| // Propagate the new motion vectors to a lower level |
| SIMPLE_MOTION_DATA_TREE *sub_tree = sms_tree->split[r_idx]; |
| sub_tree->start_mvs[ref] = sms_tree->start_mvs[ref]; |
| } |
| } |
| } |
| } |
| } |
| |
| return best_ref; |
| } |
| |
| // Collects features using simple_motion_search and store them in features. The |
| // features are also cached in SIMPLE_MOTION_DATA_TREE. By default, the features |
| // collected are the sse and var from the subblocks flagged by features_to_get. |
| // Furthermore, if features is not NULL, then 7 more features are appended to |
| // the end of features: |
| // - log(1.0 + dc_q ** 2) |
| // - whether an above macroblock exists |
| // - width of above macroblock |
| // - height of above macroblock |
| // - whether a left marcoblock exists |
| // - width of left macroblock |
| // - height of left macroblock |
| static AOM_INLINE void simple_motion_search_prune_part_features( |
| AV1_COMP *const cpi, MACROBLOCK *x, SIMPLE_MOTION_DATA_TREE *sms_tree, |
| int mi_row, int mi_col, BLOCK_SIZE bsize, float *features, |
| int features_to_get) { |
| const int w_mi = mi_size_wide[bsize]; |
| const int h_mi = mi_size_high[bsize]; |
| assert(mi_size_wide[bsize] == mi_size_high[bsize]); |
| assert(bsize >= BLOCK_8X8); |
| assert(cpi->ref_frame_flags & av1_ref_frame_flag_list[LAST_FRAME] || |
| cpi->ref_frame_flags & av1_ref_frame_flag_list[ALTREF_FRAME]); |
| |
| // Setting up motion search |
| const int ref_list[] = { cpi->rc.is_src_frame_alt_ref ? ALTREF_FRAME |
| : LAST_FRAME }; |
| const int num_refs = 1; |
| const int use_subpixel = 1; |
| |
| // Doing whole block first to update the mv |
| if (!sms_tree->sms_none_valid && features_to_get & FEATURE_SMS_NONE_FLAG) { |
| simple_motion_search_get_best_ref(cpi, x, sms_tree, mi_row, mi_col, bsize, |
| ref_list, num_refs, use_subpixel, 1, |
| &sms_tree->sms_none_feat[0], |
| &sms_tree->sms_none_feat[1]); |
| sms_tree->sms_none_valid = 1; |
| } |
| |
| // Split subblocks |
| if (features_to_get & FEATURE_SMS_SPLIT_FLAG) { |
| const BLOCK_SIZE subsize = get_partition_subsize(bsize, PARTITION_SPLIT); |
| for (int r_idx = 0; r_idx < SUB_PARTITIONS_SPLIT; r_idx++) { |
| const int sub_mi_col = mi_col + (r_idx & 1) * w_mi / 2; |
| const int sub_mi_row = mi_row + (r_idx >> 1) * h_mi / 2; |
| SIMPLE_MOTION_DATA_TREE *sub_tree = sms_tree->split[r_idx]; |
| |
| if (!sub_tree->sms_none_valid) { |
| simple_motion_search_get_best_ref( |
| cpi, x, sub_tree, sub_mi_row, sub_mi_col, subsize, ref_list, |
| num_refs, use_subpixel, 1, &sub_tree->sms_none_feat[0], |
| &sub_tree->sms_none_feat[1]); |
| sub_tree->sms_none_valid = 1; |
| } |
| } |
| } |
| |
| // Rectangular subblocks |
| if (!sms_tree->sms_rect_valid && features_to_get & FEATURE_SMS_RECT_FLAG) { |
| // Horz subblock |
| BLOCK_SIZE subsize = get_partition_subsize(bsize, PARTITION_HORZ); |
| for (int r_idx = 0; r_idx < SUB_PARTITIONS_RECT; r_idx++) { |
| const int sub_mi_col = mi_col + 0; |
| const int sub_mi_row = mi_row + r_idx * h_mi / 2; |
| |
| simple_motion_search_get_best_ref( |
| cpi, x, sms_tree, sub_mi_row, sub_mi_col, subsize, ref_list, num_refs, |
| use_subpixel, 0, &sms_tree->sms_rect_feat[2 * r_idx], |
| &sms_tree->sms_rect_feat[2 * r_idx + 1]); |
| } |
| |
| // Vert subblock |
| subsize = get_partition_subsize(bsize, PARTITION_VERT); |
| for (int r_idx = 0; r_idx < SUB_PARTITIONS_RECT; r_idx++) { |
| const int sub_mi_col = mi_col + r_idx * w_mi / 2; |
| const int sub_mi_row = mi_row + 0; |
| |
| simple_motion_search_get_best_ref( |
| cpi, x, sms_tree, sub_mi_row, sub_mi_col, subsize, ref_list, num_refs, |
| use_subpixel, 0, &sms_tree->sms_rect_feat[4 + 2 * r_idx], |
| &sms_tree->sms_rect_feat[4 + 2 * r_idx + 1]); |
| } |
| sms_tree->sms_rect_valid = 1; |
| } |
| |
| if (!features) return; |
| |
| int f_idx = 0; |
| if (features_to_get & FEATURE_SMS_NONE_FLAG) { |
| for (int sub_idx = 0; sub_idx < 2; sub_idx++) { |
| features[f_idx++] = logf(1.0f + sms_tree->sms_none_feat[sub_idx]); |
| } |
| } |
| |
| if (features_to_get & FEATURE_SMS_SPLIT_FLAG) { |
| for (int sub_idx = 0; sub_idx < SUB_PARTITIONS_SPLIT; sub_idx++) { |
| SIMPLE_MOTION_DATA_TREE *sub_tree = sms_tree->split[sub_idx]; |
| features[f_idx++] = logf(1.0f + sub_tree->sms_none_feat[0]); |
| features[f_idx++] = logf(1.0f + sub_tree->sms_none_feat[1]); |
| } |
| } |
| |
| if (features_to_get & FEATURE_SMS_RECT_FLAG) { |
| for (int sub_idx = 0; sub_idx < 8; sub_idx++) { |
| features[f_idx++] = logf(1.0f + sms_tree->sms_rect_feat[sub_idx]); |
| } |
| } |
| |
| const MACROBLOCKD *xd = &x->e_mbd; |
| set_offsets_for_motion_search(cpi, x, mi_row, mi_col, bsize); |
| |
| // Q_INDEX |
| const int dc_q = av1_dc_quant_QTX(x->qindex, 0, xd->bd) >> (xd->bd - 8); |
| features[f_idx++] = logf(1.0f + (float)(dc_q * dc_q) / 256.0f); |
| |
| // Neighbor stuff |
| const int has_above = !!xd->above_mbmi; |
| const int has_left = !!xd->left_mbmi; |
| const BLOCK_SIZE above_bsize = has_above ? xd->above_mbmi->bsize : bsize; |
| const BLOCK_SIZE left_bsize = has_left ? xd->left_mbmi->bsize : bsize; |
| features[f_idx++] = (float)has_above; |
| features[f_idx++] = (float)mi_size_wide_log2[above_bsize]; |
| features[f_idx++] = (float)mi_size_high_log2[above_bsize]; |
| features[f_idx++] = (float)has_left; |
| features[f_idx++] = (float)mi_size_wide_log2[left_bsize]; |
| features[f_idx++] = (float)mi_size_high_log2[left_bsize]; |
| } |
| |
| void av1_simple_motion_search_prune_rect(AV1_COMP *const cpi, MACROBLOCK *x, |
| SIMPLE_MOTION_DATA_TREE *sms_tree, |
| PartitionSearchState *part_state) { |
| const AV1_COMMON *const cm = &cpi->common; |
| const PartitionBlkParams *blk_params = &part_state->part_blk_params; |
| const int mi_row = blk_params->mi_row, mi_col = blk_params->mi_col; |
| const BLOCK_SIZE bsize = blk_params->bsize; |
| |
| const int bsize_idx = convert_bsize_to_idx(bsize); |
| const int is_720p_or_larger = AOMMIN(cm->width, cm->height) >= 720; |
| const int is_480p_or_larger = AOMMIN(cm->width, cm->height) >= 480; |
| // res_idx is 0 for lowres, 1 for 48p, 2 for 720p+ |
| const int res_idx = is_480p_or_larger + is_720p_or_larger; |
| |
| // Get model parameters |
| const NN_CONFIG *nn_config = |
| av1_simple_motion_search_prune_rect_nn_config[bsize_idx]; |
| const float *ml_mean = av1_simple_motion_search_prune_rect_mean[bsize_idx], |
| *ml_std = av1_simple_motion_search_prune_rect_std[bsize_idx]; |
| |
| const int agg = get_simple_motion_search_prune_agg( |
| x->qindex, cpi->sf.part_sf.simple_motion_search_prune_agg, 1); |
| if (agg < 0) { |
| return; |
| } |
| |
| const float prune_thresh = |
| av1_simple_motion_search_prune_rect_thresh[agg][res_idx][bsize_idx]; |
| |
| // If there is no valid threshold, return immediately. |
| if (!nn_config || prune_thresh == 0.0f) { |
| return; |
| } |
| |
| // Get features |
| float features[FEATURE_SIZE_SMS_PRUNE_PART] = { 0.0f }; |
| simple_motion_search_prune_part_features(cpi, x, sms_tree, mi_row, mi_col, |
| bsize, features, |
| FEATURE_SMS_PRUNE_PART_FLAG); |
| |
| // Note: it is intended to not normalize the features here, to keep it |
| // consistent for all features collected and passed to the external model. |
| if (cpi->sf.part_sf.simple_motion_search_prune_rect && |
| !frame_is_intra_only(cm) && |
| (part_state->partition_rect_allowed[HORZ] || |
| part_state->partition_rect_allowed[VERT]) && |
| bsize >= BLOCK_8X8 && !av1_superres_scaled(cm)) { |
| // Write features to file |
| write_features_to_file( |
| cpi->oxcf.partition_info_path, cpi->ext_part_controller.test_mode, |
| features, FEATURE_SIZE_SMS_PRUNE_PART, 1, bsize, mi_row, mi_col); |
| |
| if (ext_ml_model_decision_before_none_part2( |
| cpi, features, &part_state->prune_rect_part[HORZ], |
| &part_state->prune_rect_part[VERT])) { |
| return; |
| } |
| } |
| |
| for (int f_idx = 0; f_idx < FEATURE_SIZE_SMS_PRUNE_PART; f_idx++) { |
| features[f_idx] = (features[f_idx] - ml_mean[f_idx]) / ml_std[f_idx]; |
| } |
| |
| // Get probabilities |
| float scores[EXT_PARTITION_TYPES] = { 0.0f }, |
| probs[EXT_PARTITION_TYPES] = { 0.0f }; |
| const int num_classes = (bsize == BLOCK_128X128 || bsize == BLOCK_8X8) |
| ? PARTITION_TYPES |
| : EXT_PARTITION_TYPES; |
| |
| av1_nn_predict(features, nn_config, 1, scores); |
| |
| av1_nn_softmax(scores, probs, num_classes); |
| |
| // Determine if we should prune rectangular partitions. |
| if (probs[PARTITION_HORZ] <= prune_thresh) { |
| part_state->prune_rect_part[HORZ] = 1; |
| } |
| if (probs[PARTITION_VERT] <= prune_thresh) { |
| part_state->prune_rect_part[VERT] = 1; |
| } |
| } |
| |
| // Early terminates PARTITION_NONE using simple_motion_search features and the |
| // rate, distortion, and rdcost of PARTITION_NONE. This is only called when: |
| // - The frame is a show frame |
| // - The frame is not intra only |
| // - The current bsize is > BLOCK_8X8 |
| // - blk_row + blk_height/2 < total_rows and blk_col + blk_width/2 < total_cols |
| void av1_simple_motion_search_early_term_none( |
| AV1_COMP *const cpi, MACROBLOCK *x, SIMPLE_MOTION_DATA_TREE *sms_tree, |
| const RD_STATS *none_rdc, PartitionSearchState *part_state) { |
| const PartitionBlkParams *blk_params = &part_state->part_blk_params; |
| const int mi_row = blk_params->mi_row, mi_col = blk_params->mi_col; |
| const BLOCK_SIZE bsize = blk_params->bsize; |
| |
| float features[FEATURE_SIZE_SMS_TERM_NONE] = { 0.0f }; |
| simple_motion_search_prune_part_features(cpi, x, sms_tree, mi_row, mi_col, |
| bsize, features, |
| FEATURE_SMS_PRUNE_PART_FLAG); |
| int f_idx = FEATURE_SIZE_SMS_PRUNE_PART; |
| |
| features[f_idx++] = logf(1.0f + (float)none_rdc->rate); |
| features[f_idx++] = logf(1.0f + (float)none_rdc->dist); |
| features[f_idx++] = logf(1.0f + (float)none_rdc->rdcost); |
| |
| assert(f_idx == FEATURE_SIZE_SMS_TERM_NONE); |
| |
| const float *ml_mean = NULL; |
| const float *ml_std = NULL; |
| const float *ml_model = NULL; |
| |
| if (bsize == BLOCK_128X128) { |
| ml_mean = av1_simple_motion_search_term_none_mean_128; |
| ml_std = av1_simple_motion_search_term_none_std_128; |
| ml_model = av1_simple_motion_search_term_none_model_128; |
| } else if (bsize == BLOCK_64X64) { |
| ml_mean = av1_simple_motion_search_term_none_mean_64; |
| ml_std = av1_simple_motion_search_term_none_std_64; |
| ml_model = av1_simple_motion_search_term_none_model_64; |
| } else if (bsize == BLOCK_32X32) { |
| ml_mean = av1_simple_motion_search_term_none_mean_32; |
| ml_std = av1_simple_motion_search_term_none_std_32; |
| ml_model = av1_simple_motion_search_term_none_model_32; |
| } else if (bsize == BLOCK_16X16) { |
| ml_mean = av1_simple_motion_search_term_none_mean_16; |
| ml_std = av1_simple_motion_search_term_none_std_16; |
| ml_model = av1_simple_motion_search_term_none_model_16; |
| } else { |
| assert(0 && "Unexpected block size in simple_motion_term_none"); |
| } |
| |
| // Write features to file |
| write_features_to_file(cpi->oxcf.partition_info_path, |
| cpi->ext_part_controller.test_mode, features, |
| FEATURE_SIZE_SMS_TERM_NONE, 3, bsize, mi_row, mi_col); |
| |
| if (ext_ml_model_decision_after_none_part2( |
| cpi, features, &part_state->terminate_partition_search)) { |
| return; |
| } |
| |
| if (ml_model) { |
| float score = 0.0f; |
| for (f_idx = 0; f_idx < FEATURE_SIZE_SMS_TERM_NONE; f_idx++) { |
| score += |
| ml_model[f_idx] * (features[f_idx] - ml_mean[f_idx]) / ml_std[f_idx]; |
| } |
| score += ml_model[FEATURE_SIZE_SMS_TERM_NONE]; |
| |
| if (score >= 0.0f) { |
| part_state->terminate_partition_search = 1; |
| } |
| } |
| } |
| |
| void av1_get_max_min_partition_features(AV1_COMP *const cpi, MACROBLOCK *x, |
| int mi_row, int mi_col, |
| float *features) { |
| AV1_COMMON *const cm = &cpi->common; |
| MACROBLOCKD *xd = &x->e_mbd; |
| const BLOCK_SIZE sb_size = cm->seq_params->sb_size; |
| |
| // Currently this only allows 128X128 SB size. May extend it to 64X64 SB size. |
| assert(sb_size == BLOCK_128X128); |
| |
| int f_idx = 0; |
| |
| const int dc_q = av1_dc_quant_QTX(x->qindex, 0, xd->bd) >> (xd->bd - 8); |
| const float log_q_sq = logf(1.0f + (float)(dc_q * dc_q) / 256.0f); |
| |
| // Perform full-pixel single motion search in Y plane of 16x16 mbs in the sb |
| float sum_mv_row_sq = 0; |
| float sum_mv_row = 0; |
| float min_abs_mv_row = FLT_MAX; |
| float max_abs_mv_row = 0; |
| |
| float sum_mv_col_sq = 0; |
| float sum_mv_col = 0; |
| float min_abs_mv_col = FLT_MAX; |
| float max_abs_mv_col = 0; |
| |
| float sum_log_sse_sq = 0; |
| float sum_log_sse = 0; |
| float min_log_sse = FLT_MAX; |
| float max_log_sse = 0; |
| |
| const BLOCK_SIZE mb_size = BLOCK_16X16; |
| const int mb_rows = block_size_high[sb_size] / block_size_high[mb_size]; |
| const int mb_cols = block_size_wide[sb_size] / block_size_wide[mb_size]; |
| const int mb_in_mi_size_high_log2 = mi_size_high_log2[mb_size]; |
| const int mb_in_mi_size_wide_log2 = mi_size_wide_log2[mb_size]; |
| |
| for (int mb_row = 0; mb_row < mb_rows; mb_row++) |
| for (int mb_col = 0; mb_col < mb_cols; mb_col++) { |
| const int this_mi_row = mi_row + (mb_row << mb_in_mi_size_high_log2); |
| const int this_mi_col = mi_col + (mb_col << mb_in_mi_size_wide_log2); |
| unsigned int sse = 0; |
| unsigned int var = 0; |
| const FULLPEL_MV start_mv = kZeroFullMv; |
| int_mv best_mv = av1_simple_motion_sse_var( |
| cpi, x, this_mi_row, this_mi_col, mb_size, start_mv, 0, &sse, &var); |
| |
| const float mv_row = (float)(best_mv.as_mv.row / 8); |
| const float mv_col = (float)(best_mv.as_mv.col / 8); |
| const float log_sse = logf(1.0f + (float)sse); |
| const float abs_mv_row = fabsf(mv_row); |
| const float abs_mv_col = fabsf(mv_col); |
| |
| sum_mv_row_sq += mv_row * mv_row; |
| sum_mv_row += mv_row; |
| sum_mv_col_sq += mv_col * mv_col; |
| sum_mv_col += mv_col; |
| |
| if (abs_mv_row < min_abs_mv_row) min_abs_mv_row = abs_mv_row; |
| if (abs_mv_row > max_abs_mv_row) max_abs_mv_row = abs_mv_row; |
| if (abs_mv_col < min_abs_mv_col) min_abs_mv_col = abs_mv_col; |
| if (abs_mv_col > max_abs_mv_col) max_abs_mv_col = abs_mv_col; |
| |
| sum_log_sse_sq += log_sse * log_sse; |
| sum_log_sse += log_sse; |
| if (log_sse < min_log_sse) min_log_sse = log_sse; |
| if (log_sse > max_log_sse) max_log_sse = log_sse; |
| } |
| const int blks = mb_rows * mb_cols; |
| const float avg_mv_row = sum_mv_row / (float)blks; |
| const float var_mv_row = |
| sum_mv_row_sq / (float)blks - avg_mv_row * avg_mv_row; |
| |
| const float avg_mv_col = sum_mv_col / (float)blks; |
| const float var_mv_col = |
| sum_mv_col_sq / (float)blks - avg_mv_col * avg_mv_col; |
| |
| const float avg_log_sse = sum_log_sse / (float)blks; |
| const float var_log_sse = |
| sum_log_sse_sq / (float)blks - avg_log_sse * avg_log_sse; |
| |
| features[f_idx++] = avg_log_sse; |
| features[f_idx++] = avg_mv_col; |
| features[f_idx++] = avg_mv_row; |
| features[f_idx++] = log_q_sq; |
| features[f_idx++] = max_abs_mv_col; |
| features[f_idx++] = max_abs_mv_row; |
| features[f_idx++] = max_log_sse; |
| features[f_idx++] = min_abs_mv_col; |
| features[f_idx++] = min_abs_mv_row; |
| features[f_idx++] = min_log_sse; |
| features[f_idx++] = var_log_sse; |
| features[f_idx++] = var_mv_col; |
| features[f_idx++] = var_mv_row; |
| |
| assert(f_idx == FEATURE_SIZE_MAX_MIN_PART_PRED); |
| } |
| |
| // Convert result index to block size. |
| // result idx block size |
| // 0 BLOCK_16X16 |
| // 1 BLOCK_32X32 |
| // 2 BLOCK_64X64 |
| // 3 BLOCK_128X128 |
| static BLOCK_SIZE get_block_size(int idx) { |
| return (BLOCK_SIZE)((idx + 2) * 3); |
| } |
| |
| BLOCK_SIZE av1_predict_max_partition(const AV1_COMP *const cpi, |
| const MACROBLOCK *const x, |
| const float *features) { |
| float scores[MAX_NUM_CLASSES_MAX_MIN_PART_PRED] = { 0.0f }; |
| const NN_CONFIG *nn_config = &av1_max_part_pred_nn_config; |
| |
| assert(cpi->sf.part_sf.auto_max_partition_based_on_simple_motion != |
| NOT_IN_USE); |
| |
| av1_nn_predict(features, nn_config, 1, scores); |
| |
| int result = MAX_NUM_CLASSES_MAX_MIN_PART_PRED - 1; |
| if (cpi->sf.part_sf.auto_max_partition_based_on_simple_motion == |
| DIRECT_PRED) { |
| result = 0; |
| float max_score = scores[0]; |
| for (int i = 1; i < MAX_NUM_CLASSES_MAX_MIN_PART_PRED; ++i) { |
| if (scores[i] > max_score) { |
| max_score = scores[i]; |
| result = i; |
| } |
| } |
| return get_block_size(result); |
| } |
| |
| float probs[MAX_NUM_CLASSES_MAX_MIN_PART_PRED] = { 0.0f }; |
| av1_nn_softmax(scores, probs, MAX_NUM_CLASSES_MAX_MIN_PART_PRED); |
| |
| if (cpi->sf.part_sf.auto_max_partition_based_on_simple_motion == |
| RELAXED_PRED) { |
| for (result = MAX_NUM_CLASSES_MAX_MIN_PART_PRED - 1; result >= 0; |
| --result) { |
| if (result < MAX_NUM_CLASSES_MAX_MIN_PART_PRED - 1) { |
| probs[result] += probs[result + 1]; |
| } |
| if (probs[result] > 0.2) break; |
| } |
| } else if (cpi->sf.part_sf.auto_max_partition_based_on_simple_motion == |
| ADAPT_PRED) { |
| const BLOCK_SIZE sb_size = cpi->common.seq_params->sb_size; |
| // TODO(debargha): x->source_variance is unavailable at this point, |
| // so compute. The redundant recomputation later can be removed. |
| const unsigned int source_variance = av1_get_perpixel_variance_facade( |
| cpi, &x->e_mbd, &x->plane[0].src, sb_size, AOM_PLANE_Y); |
| if (source_variance > 16) { |
| const double thresh = source_variance < 128 ? 0.05 : 0.1; |
| for (result = MAX_NUM_CLASSES_MAX_MIN_PART_PRED - 1; result >= 0; |
| --result) { |
| if (result < MAX_NUM_CLASSES_MAX_MIN_PART_PRED - 1) { |
| probs[result] += probs[result + 1]; |
| } |
| if (probs[result] > thresh) break; |
| } |
| } |
| } |
| |
| return get_block_size(result); |
| } |
| |
| // Get the minimum partition block width and height(in log scale) under a |
| // SIMPLE_MOTION_DATA_TREE. |
| static AOM_INLINE void get_min_bsize(const SIMPLE_MOTION_DATA_TREE *sms_tree, |
| int *min_bw, int *min_bh) { |
| if (!sms_tree) return; |
| |
| const BLOCK_SIZE bsize = sms_tree->block_size; |
| if (bsize == BLOCK_4X4) { |
| *min_bw = 0; |
| *min_bh = 0; |
| return; |
| } |
| |
| PARTITION_TYPE part_type = sms_tree->partitioning; |
| if (part_type == PARTITION_INVALID) return; |
| |
| if (part_type == PARTITION_SPLIT) { |
| for (int i = 0; i < SUB_PARTITIONS_SPLIT; ++i) { |
| get_min_bsize(sms_tree->split[i], min_bw, min_bh); |
| } |
| } else { |
| if (part_type == PARTITION_HORZ_A || part_type == PARTITION_HORZ_B || |
| part_type == PARTITION_VERT_A || part_type == PARTITION_VERT_B) |
| part_type = PARTITION_SPLIT; |
| const BLOCK_SIZE subsize = get_partition_subsize(bsize, part_type); |
| if (subsize != BLOCK_INVALID) { |
| *min_bw = AOMMIN(*min_bw, mi_size_wide_log2[subsize]); |
| *min_bh = AOMMIN(*min_bh, mi_size_high_log2[subsize]); |
| } |
| } |
| } |
| |
| static INLINE void add_rd_feature(int64_t rd, int64_t best_rd, float *features, |
| int *feature_idx) { |
| const int rd_valid = rd > 0 && rd < INT64_MAX; |
| const float rd_ratio = rd_valid ? (float)rd / best_rd : 1.0f; |
| features[(*feature_idx)++] = (float)rd_valid; |
| features[(*feature_idx)++] = rd_ratio; |
| } |
| |
| #define FEATURES 31 |
| void av1_ml_early_term_after_split(AV1_COMP *const cpi, MACROBLOCK *const x, |
| SIMPLE_MOTION_DATA_TREE *const sms_tree, |
| int64_t best_rd, int64_t part_none_rd, |
| int64_t part_split_rd, |
| int64_t *split_block_rd, |
| PartitionSearchState *part_state) { |
| const PartitionBlkParams *blk_params = &part_state->part_blk_params; |
| const int mi_row = blk_params->mi_row, mi_col = blk_params->mi_col; |
| const BLOCK_SIZE bsize = blk_params->bsize; |
| |
| if (best_rd <= 0 || best_rd == INT64_MAX || |
| part_state->terminate_partition_search) |
| return; |
| |
| const AV1_COMMON *const cm = &cpi->common; |
| const int is_480p_or_larger = AOMMIN(cm->width, cm->height) >= 480; |
| const NN_CONFIG *nn_config = NULL; |
| float thresh = -1e6; |
| switch (bsize) { |
| case BLOCK_128X128: break; |
| case BLOCK_64X64: |
| nn_config = &av1_early_term_after_split_nnconfig_64; |
| thresh = is_480p_or_larger ? -2.0f : -1.2f; |
| break; |
| case BLOCK_32X32: |
| nn_config = &av1_early_term_after_split_nnconfig_32; |
| thresh = is_480p_or_larger ? -2.6f : -2.3f; |
| break; |
| case BLOCK_16X16: |
| nn_config = &av1_early_term_after_split_nnconfig_16; |
| thresh = is_480p_or_larger ? -2.0f : -2.4f; |
| break; |
| case BLOCK_8X8: |
| nn_config = &av1_early_term_after_split_nnconfig_8; |
| thresh = is_480p_or_larger ? -1.0f : -1.4f; |
| break; |
| case BLOCK_4X4: break; |
| default: |
| assert(0 && "Invalid block size in av1_ml_early_term_after_split()."); |
| break; |
| } |
| if (!nn_config) return; |
| |
| // Use more conservative threshold for level 1. |
| if (cpi->sf.part_sf.ml_early_term_after_part_split_level < 2) thresh -= 0.3f; |
| |
| const MACROBLOCKD *const xd = &x->e_mbd; |
| const int dc_q = av1_dc_quant_QTX(x->qindex, 0, xd->bd) >> (xd->bd - 8); |
| const int bs = block_size_wide[bsize]; |
| int f_idx = 0; |
| float features[FEATURES] = { 0.0f }; |
| |
| features[f_idx++] = logf(1.0f + (float)dc_q / 4.0f); |
| features[f_idx++] = logf(1.0f + (float)best_rd / bs / bs / 1024.0f); |
| |
| add_rd_feature(part_none_rd, best_rd, features, &f_idx); |
| add_rd_feature(part_split_rd, best_rd, features, &f_idx); |
| |
| for (int i = 0; i < SUB_PARTITIONS_SPLIT; ++i) { |
| add_rd_feature(split_block_rd[i], best_rd, features, &f_idx); |
| int min_bw = MAX_SB_SIZE_LOG2; |
| int min_bh = MAX_SB_SIZE_LOG2; |
| get_min_bsize(sms_tree->split[i], &min_bw, &min_bh); |
| features[f_idx++] = (float)min_bw; |
| features[f_idx++] = (float)min_bh; |
| } |
| |
| simple_motion_search_prune_part_features(cpi, x, sms_tree, mi_row, mi_col, |
| bsize, NULL, |
| FEATURE_SMS_PRUNE_PART_FLAG); |
| |
| features[f_idx++] = logf(1.0f + (float)sms_tree->sms_none_feat[1]); |
| |
| features[f_idx++] = logf(1.0f + (float)sms_tree->split[0]->sms_none_feat[1]); |
| features[f_idx++] = logf(1.0f + (float)sms_tree->split[1]->sms_none_feat[1]); |
| features[f_idx++] = logf(1.0f + (float)sms_tree->split[2]->sms_none_feat[1]); |
| features[f_idx++] = logf(1.0f + (float)sms_tree->split[3]->sms_none_feat[1]); |
| |
| features[f_idx++] = logf(1.0f + (float)sms_tree->sms_rect_feat[1]); |
| features[f_idx++] = logf(1.0f + (float)sms_tree->sms_rect_feat[3]); |
| features[f_idx++] = logf(1.0f + (float)sms_tree->sms_rect_feat[5]); |
| features[f_idx++] = logf(1.0f + (float)sms_tree->sms_rect_feat[7]); |
| |
| assert(f_idx == FEATURES); |
| |
| // Write features to file |
| write_features_to_file(cpi->oxcf.partition_info_path, |
| cpi->ext_part_controller.test_mode, features, FEATURES, |
| 4, bsize, mi_row, mi_col); |
| |
| if (ext_ml_model_decision_after_split( |
| cpi, features, &part_state->terminate_partition_search)) { |
| return; |
| } |
| |
| float score = 0.0f; |
| av1_nn_predict(features, nn_config, 1, &score); |
| // Score is indicator of confidence that we should NOT terminate. |
| if (score < thresh) { |
| part_state->terminate_partition_search = 1; |
| } |
| } |
| #undef FEATURES |
| |
| void av1_ml_prune_rect_partition(AV1_COMP *const cpi, const MACROBLOCK *const x, |
| int64_t best_rd, int64_t none_rd, |
| const int64_t *split_rd, |
| PartitionSearchState *part_state) { |
| const PartitionBlkParams *blk_params = &part_state->part_blk_params; |
| const int mi_row = blk_params->mi_row, mi_col = blk_params->mi_col; |
| const BLOCK_SIZE bsize = blk_params->bsize; |
| |
| if (bsize < BLOCK_8X8 || best_rd >= 1000000000) return; |
| best_rd = AOMMAX(best_rd, 1); |
| const NN_CONFIG *nn_config = NULL; |
| const float prob_thresholds[5] = { 0.01f, 0.01f, 0.004f, 0.002f, 0.002f }; |
| float cur_thresh = 0.0f; |
| switch (bsize) { |
| case BLOCK_8X8: |
| nn_config = &av1_rect_partition_nnconfig_8; |
| cur_thresh = prob_thresholds[0]; |
| break; |
| case BLOCK_16X16: |
| nn_config = &av1_rect_partition_nnconfig_16; |
| cur_thresh = prob_thresholds[1]; |
| break; |
| case BLOCK_32X32: |
| nn_config = &av1_rect_partition_nnconfig_32; |
| cur_thresh = prob_thresholds[2]; |
| break; |
| case BLOCK_64X64: |
| nn_config = &av1_rect_partition_nnconfig_64; |
| cur_thresh = prob_thresholds[3]; |
| break; |
| case BLOCK_128X128: |
| nn_config = &av1_rect_partition_nnconfig_128; |
| cur_thresh = prob_thresholds[4]; |
| break; |
| default: assert(0 && "Unexpected bsize."); |
| } |
| if (!nn_config) return; |
| |
| // 1. Compute input features |
| float features[9]; |
| |
| // RD cost ratios |
| for (int i = 0; i < 5; i++) features[i] = 1.0f; |
| if (none_rd > 0 && none_rd < 1000000000) |
| features[0] = (float)none_rd / (float)best_rd; |
| for (int i = 0; i < SUB_PARTITIONS_SPLIT; i++) { |
| if (split_rd[i] > 0 && split_rd[i] < 1000000000) |
| features[1 + i] = (float)split_rd[i] / (float)best_rd; |
| } |
| |
| // Variance ratios |
| const MACROBLOCKD *const xd = &x->e_mbd; |
| int whole_block_variance; |
| whole_block_variance = av1_get_perpixel_variance_facade( |
| cpi, xd, &x->plane[0].src, bsize, AOM_PLANE_Y); |
| whole_block_variance = AOMMAX(whole_block_variance, 1); |
| |
| int split_variance[SUB_PARTITIONS_SPLIT]; |
| const BLOCK_SIZE subsize = get_partition_subsize(bsize, PARTITION_SPLIT); |
| struct buf_2d buf; |
| buf.stride = x->plane[0].src.stride; |
| const int bw = block_size_wide[bsize]; |
| for (int i = 0; i < SUB_PARTITIONS_SPLIT; ++i) { |
| const int x_idx = (i & 1) * bw / 2; |
| const int y_idx = (i >> 1) * bw / 2; |
| buf.buf = x->plane[0].src.buf + x_idx + y_idx * buf.stride; |
| split_variance[i] = |
| av1_get_perpixel_variance_facade(cpi, xd, &buf, subsize, AOM_PLANE_Y); |
| } |
| |
| for (int i = 0; i < SUB_PARTITIONS_SPLIT; i++) |
| features[5 + i] = (float)split_variance[i] / (float)whole_block_variance; |
| |
| // Write features to file |
| write_features_to_file(cpi->oxcf.partition_info_path, |
| cpi->ext_part_controller.test_mode, features, |
| /*feature_size=*/9, 5, bsize, mi_row, mi_col); |
| |
| if (ext_ml_model_decision_after_split_part2( |
| &cpi->ext_part_controller, frame_is_intra_only(&cpi->common), |
| features, &part_state->prune_rect_part[HORZ], |
| &part_state->prune_rect_part[VERT])) { |
| return; |
| } |
| |
| // 2. Do the prediction and prune 0-2 partitions based on their probabilities |
| float raw_scores[3] = { 0.0f }; |
| av1_nn_predict(features, nn_config, 1, raw_scores); |
| float probs[3] = { 0.0f }; |
| av1_nn_softmax(raw_scores, probs, 3); |
| |
| // probs[0] is the probability of the fact that both rectangular partitions |
| // are worse than current best_rd |
| if (probs[1] <= cur_thresh) part_state->prune_rect_part[HORZ] = 1; |
| if (probs[2] <= cur_thresh) part_state->prune_rect_part[VERT] = 1; |
| } |
| |
| // Use a ML model to predict if horz_a, horz_b, vert_a, and vert_b should be |
| // considered. |
| void av1_ml_prune_ab_partition(AV1_COMP *const cpi, int part_ctx, int var_ctx, |
| int64_t best_rd, |
| PartitionSearchState *part_state, |
| int *ab_partitions_allowed) { |
| const PartitionBlkParams blk_params = part_state->part_blk_params; |
| const int mi_row = blk_params.mi_row; |
| const int mi_col = blk_params.mi_col; |
| const int bsize = blk_params.bsize; |
| |
| if (bsize < BLOCK_8X8 || best_rd >= 1000000000) return; |
| const NN_CONFIG *nn_config = NULL; |
| switch (bsize) { |
| case BLOCK_8X8: nn_config = NULL; break; |
| case BLOCK_16X16: nn_config = &av1_ab_partition_nnconfig_16; break; |
| case BLOCK_32X32: nn_config = &av1_ab_partition_nnconfig_32; break; |
| case BLOCK_64X64: nn_config = &av1_ab_partition_nnconfig_64; break; |
| case BLOCK_128X128: nn_config = &av1_ab_partition_nnconfig_128; break; |
| default: assert(0 && "Unexpected bsize."); |
| } |
| if (!nn_config) return; |
| |
| // Generate features. |
| float features[10]; |
| int feature_index = 0; |
| features[feature_index++] = (float)part_ctx; |
| features[feature_index++] = (float)var_ctx; |
| const int rdcost = (int)AOMMIN(INT_MAX, best_rd); |
| int sub_block_rdcost[8] = { 0 }; |
| int rd_index = 0; |
| for (int i = 0; i < SUB_PARTITIONS_RECT; ++i) { |
| const int64_t *horz_rd = part_state->rect_part_rd[HORZ]; |
| if (horz_rd[i] > 0 && horz_rd[i] < 1000000000) |
| sub_block_rdcost[rd_index] = (int)horz_rd[i]; |
| ++rd_index; |
| } |
| for (int i = 0; i < SUB_PARTITIONS_RECT; ++i) { |
| const int64_t *vert_rd = part_state->rect_part_rd[VERT]; |
| if (vert_rd[i] > 0 && vert_rd[i] < 1000000000) |
| sub_block_rdcost[rd_index] = (int)vert_rd[i]; |
| ++rd_index; |
| } |
| for (int i = 0; i < SUB_PARTITIONS_SPLIT; ++i) { |
| const int64_t *split_rd = part_state->split_rd; |
| if (split_rd[i] > 0 && split_rd[i] < 1000000000) |
| sub_block_rdcost[rd_index] = (int)split_rd[i]; |
| ++rd_index; |
| } |
| for (int i = 0; i < 8; ++i) { |
| // Ratio between the sub-block RD and the whole-block RD. |
| float rd_ratio = 1.0f; |
| if (sub_block_rdcost[i] > 0 && sub_block_rdcost[i] < rdcost) |
| rd_ratio = (float)sub_block_rdcost[i] / (float)rdcost; |
| features[feature_index++] = rd_ratio; |
| } |
| assert(feature_index == 10); |
| |
| // Write features to file |
| if (!frame_is_intra_only(&cpi->common)) { |
| write_features_to_file(cpi->oxcf.partition_info_path, |
| cpi->ext_part_controller.test_mode, features, |
| /*feature_size=*/10, 6, bsize, mi_row, mi_col); |
| } |
| |
| if (ext_ml_model_decision_after_rect( |
| &cpi->ext_part_controller, frame_is_intra_only(&cpi->common), |
| features, &ab_partitions_allowed[HORZ_A], |
| &ab_partitions_allowed[HORZ_B], &ab_partitions_allowed[VERT_A], |
| &ab_partitions_allowed[VERT_B])) { |
| return; |
| } |
| |
| // Calculate scores using the NN model. |
| float score[16] = { 0.0f }; |
| av1_nn_predict(features, nn_config, 1, score); |
| int int_score[16]; |
| int max_score = -1000; |
| for (int i = 0; i < 16; ++i) { |
| int_score[i] = (int)(100 * score[i]); |
| max_score = AOMMAX(int_score[i], max_score); |
| } |
| |
| // Make decisions based on the model scores. |
| int thresh = max_score; |
| switch (bsize) { |
| case BLOCK_16X16: thresh -= 150; break; |
| case BLOCK_32X32: thresh -= 100; break; |
| default: break; |
| } |
| av1_zero_array(ab_partitions_allowed, NUM_AB_PARTS); |
| for (int i = 0; i < 16; ++i) { |
| if (int_score[i] >= thresh) { |
| if ((i >> 0) & 1) ab_partitions_allowed[HORZ_A] = 1; |
| if ((i >> 1) & 1) ab_partitions_allowed[HORZ_B] = 1; |
| if ((i >> 2) & 1) ab_partitions_allowed[VERT_A] = 1; |
| if ((i >> 3) & 1) ab_partitions_allowed[VERT_B] = 1; |
| } |
| } |
| } |
| |
| #define FEATURES 18 |
| #define LABELS 4 |
| // Use a ML model to predict if horz4 and vert4 should be considered. |
| void av1_ml_prune_4_partition(AV1_COMP *const cpi, MACROBLOCK *const x, |
| int part_ctx, int64_t best_rd, |
| PartitionSearchState *part_state, |
| int *part4_allowed, |
| unsigned int pb_source_variance) { |
| const PartitionBlkParams blk_params = part_state->part_blk_params; |
| const int mi_row = blk_params.mi_row; |
| const int mi_col = blk_params.mi_col; |
| const int bsize = blk_params.bsize; |
| |
| int64_t(*rect_part_rd)[SUB_PARTITIONS_RECT] = part_state->rect_part_rd; |
| int64_t *split_rd = part_state->split_rd; |
| if (ext_ml_model_decision_after_part_ab( |
| cpi, x, bsize, part_ctx, best_rd, rect_part_rd, split_rd, |
| &part4_allowed[HORZ4], &part4_allowed[VERT4], pb_source_variance, |
| mi_row, mi_col)) |
| return; |
| |
| if (best_rd >= 1000000000) return; |
| int64_t *horz_rd = rect_part_rd[HORZ4]; |
| int64_t *vert_rd = rect_part_rd[VERT4]; |
| const NN_CONFIG *nn_config = NULL; |
| switch (bsize) { |
| case BLOCK_16X16: nn_config = &av1_4_partition_nnconfig_16; break; |
| case BLOCK_32X32: nn_config = &av1_4_partition_nnconfig_32; break; |
| case BLOCK_64X64: nn_config = &av1_4_partition_nnconfig_64; break; |
| default: assert(0 && "Unexpected bsize."); |
| } |
| if (!nn_config) return; |
| |
| // Generate features. |
| float features[FEATURES]; |
| int feature_index = 0; |
| features[feature_index++] = (float)part_ctx; |
| features[feature_index++] = (float)get_unsigned_bits(pb_source_variance); |
| |
| const int rdcost = (int)AOMMIN(INT_MAX, best_rd); |
| int sub_block_rdcost[8] = { 0 }; |
| int rd_index = 0; |
| for (int i = 0; i < SUB_PARTITIONS_RECT; ++i) { |
| if (horz_rd[i] > 0 && horz_rd[i] < 1000000000) |
| sub_block_rdcost[rd_index] = (int)horz_rd[i]; |
| ++rd_index; |
| } |
| for (int i = 0; i < SUB_PARTITIONS_RECT; ++i) { |
| if (vert_rd[i] > 0 && vert_rd[i] < 1000000000) |
| sub_block_rdcost[rd_index] = (int)vert_rd[i]; |
| ++rd_index; |
| } |
| for (int i = 0; i < SUB_PARTITIONS_SPLIT; ++i) { |
| if (split_rd[i] > 0 && split_rd[i] < 1000000000) |
| sub_block_rdcost[rd_index] = (int)split_rd[i]; |
| ++rd_index; |
| } |
| for (int i = 0; i < 8; ++i) { |
| // Ratio between the sub-block RD and the whole-block RD. |
| float rd_ratio = 1.0f; |
| if (sub_block_rdcost[i] > 0 && sub_block_rdcost[i] < rdcost) |
| rd_ratio = (float)sub_block_rdcost[i] / (float)rdcost; |
| features[feature_index++] = rd_ratio; |
| } |
| |
| // Get variance of the 1:4 and 4:1 sub-blocks. |
| unsigned int horz_4_source_var[SUB_PARTITIONS_PART4] = { 0 }; |
| unsigned int vert_4_source_var[SUB_PARTITIONS_PART4] = { 0 }; |
| { |
| BLOCK_SIZE horz_4_bs = get_partition_subsize(bsize, PARTITION_HORZ_4); |
| BLOCK_SIZE vert_4_bs = get_partition_subsize(bsize, PARTITION_VERT_4); |
| av1_setup_src_planes(x, cpi->source, mi_row, mi_col, |
| av1_num_planes(&cpi->common), bsize); |
| const int src_stride = x->plane[0].src.stride; |
| uint8_t *src = x->plane[0].src.buf; |
| const MACROBLOCKD *const xd = &x->e_mbd; |
| |
| struct buf_2d horz_4_src, vert_4_src; |
| horz_4_src.stride = src_stride; |
| vert_4_src.stride = src_stride; |
| |
| for (int i = 0; i < SUB_PARTITIONS_PART4; ++i) { |
| horz_4_src.buf = src + i * block_size_high[horz_4_bs] * src_stride; |
| vert_4_src.buf = src + i * block_size_wide[vert_4_bs]; |
| |
| horz_4_source_var[i] = av1_get_perpixel_variance_facade( |
| cpi, xd, &horz_4_src, horz_4_bs, AOM_PLANE_Y); |
| vert_4_source_var[i] = av1_get_perpixel_variance_facade( |
| cpi, xd, &vert_4_src, vert_4_bs, AOM_PLANE_Y); |
| } |
| } |
| |
| const float denom = (float)(pb_source_variance + 1); |
| const float low_b = 0.1f; |
| const float high_b = 10.0f; |
| for (int i = 0; i < SUB_PARTITIONS_PART4; ++i) { |
| // Ratio between the 4:1 sub-block variance and the whole-block variance. |
| float var_ratio = (float)(horz_4_source_var[i] + 1) / denom; |
| if (var_ratio < low_b) var_ratio = low_b; |
| if (var_ratio > high_b) var_ratio = high_b; |
| features[feature_index++] = var_ratio; |
| } |
| for (int i = 0; i < SUB_PARTITIONS_PART4; ++i) { |
| // Ratio between the 1:4 sub-block RD and the whole-block RD. |
| float var_ratio = (float)(vert_4_source_var[i] + 1) / denom; |
| if (var_ratio < low_b) var_ratio = low_b; |
| if (var_ratio > high_b) var_ratio = high_b; |
| features[feature_index++] = var_ratio; |
| } |
| assert(feature_index == FEATURES); |
| |
| // Write features to file |
| if (!frame_is_intra_only(&cpi->common)) { |
| write_features_to_file(cpi->oxcf.partition_info_path, |
| cpi->ext_part_controller.test_mode, features, |
| FEATURES, 7, bsize, mi_row, mi_col); |
| } |
| |
| // Calculate scores using the NN model. |
| float score[LABELS] = { 0.0f }; |
| av1_nn_predict(features, nn_config, 1, score); |
| int int_score[LABELS]; |
| int max_score = -1000; |
| for (int i = 0; i < LABELS; ++i) { |
| int_score[i] = (int)(100 * score[i]); |
| max_score = AOMMAX(int_score[i], max_score); |
| } |
| |
| // Make decisions based on the model scores. |
| int thresh = max_score; |
| switch (bsize) { |
| case BLOCK_16X16: thresh -= 500; break; |
| case BLOCK_32X32: thresh -= 500; break; |
| case BLOCK_64X64: thresh -= 200; break; |
| default: break; |
| } |
| av1_zero_array(part4_allowed, NUM_PART4_TYPES); |
| for (int i = 0; i < LABELS; ++i) { |
| if (int_score[i] >= thresh) { |
| if ((i >> 0) & 1) part4_allowed[HORZ4] = 1; |
| if ((i >> 1) & 1) part4_allowed[VERT4] = 1; |
| } |
| } |
| } |
| #undef FEATURES |
| #undef LABELS |
| |
| #define FEATURES 4 |
| void av1_ml_predict_breakout(AV1_COMP *const cpi, const MACROBLOCK *const x, |
| const RD_STATS *const rd_stats, |
| unsigned int pb_source_variance, int bit_depth, |
| PartitionSearchState *part_state) { |
| const PartitionBlkParams *blk_params = &part_state->part_blk_params; |
| const int mi_row = blk_params->mi_row, mi_col = blk_params->mi_col; |
| const BLOCK_SIZE bsize = blk_params->bsize; |
| |
| const NN_CONFIG *nn_config = NULL; |
| int thresh = 0; |
| switch (bsize) { |
| case BLOCK_8X8: |
| nn_config = &av1_partition_breakout_nnconfig_8; |
| thresh = cpi->sf.part_sf.ml_partition_search_breakout_thresh[0]; |
| break; |
| case BLOCK_16X16: |
| nn_config = &av1_partition_breakout_nnconfig_16; |
| thresh = cpi->sf.part_sf.ml_partition_search_breakout_thresh[1]; |
| break; |
| case BLOCK_32X32: |
| nn_config = &av1_partition_breakout_nnconfig_32; |
| thresh = cpi->sf.part_sf.ml_partition_search_breakout_thresh[2]; |
| break; |
| case BLOCK_64X64: |
| nn_config = &av1_partition_breakout_nnconfig_64; |
| thresh = cpi->sf.part_sf.ml_partition_search_breakout_thresh[3]; |
| break; |
| case BLOCK_128X128: |
| nn_config = &av1_partition_breakout_nnconfig_128; |
| thresh = cpi->sf.part_sf.ml_partition_search_breakout_thresh[4]; |
| break; |
| default: assert(0 && "Unexpected bsize."); |
| } |
| if (!nn_config || thresh < 0) return; |
| |
| const float ml_predict_breakout_thresh_scale[3] = { 1.15f, 1.05f, 1.0f }; |
| thresh = (int)((float)thresh * |
| ml_predict_breakout_thresh_scale |
| [cpi->sf.part_sf.ml_predict_breakout_level - 1]); |
| |
| // Generate feature values. |
| float features[FEATURES]; |
| int feature_index = 0; |
| |
| const int num_pels_log2 = num_pels_log2_lookup[bsize]; |
| float rate_f = (float)AOMMIN(rd_stats->rate, INT_MAX); |
| rate_f = ((float)x->rdmult / 128.0f / 512.0f / (float)(1 << num_pels_log2)) * |
| rate_f; |
| features[feature_index++] = rate_f; |
| |
| const float dist_f = |
| (float)(AOMMIN(rd_stats->dist, INT_MAX) >> num_pels_log2); |
| features[feature_index++] = dist_f; |
| |
| features[feature_index++] = (float)pb_source_variance; |
| |
| const int dc_q = (int)x->plane[0].dequant_QTX[0] >> (bit_depth - 8); |
| features[feature_index++] = (float)(dc_q * dc_q) / 256.0f; |
| assert(feature_index == FEATURES); |
| |
| // Write features to file |
| write_features_to_file(cpi->oxcf.partition_info_path, |
| cpi->ext_part_controller.test_mode, features, FEATURES, |
| 2, bsize, mi_row, mi_col); |
| |
| if (ext_ml_model_decision_after_none(&cpi->ext_part_controller, |
| frame_is_intra_only(&cpi->common), |
| features, &part_state->do_square_split, |
| &part_state->do_rectangular_split)) { |
| return; |
| } |
| |
| // Calculate score using the NN model. |
| float score = 0.0f; |
| av1_nn_predict(features, nn_config, 1, &score); |
| |
| // Make decision. |
| if ((int)(score * 100) >= thresh) { |
| part_state->do_square_split = 0; |
| part_state->do_rectangular_split = 0; |
| } |
| } |
| #undef FEATURES |
| |
| void av1_prune_partitions_before_search(AV1_COMP *const cpi, |
| MACROBLOCK *const x, |
| SIMPLE_MOTION_DATA_TREE *const sms_tree, |
| PartitionSearchState *part_state) { |
| const AV1_COMMON *const cm = &cpi->common; |
| const CommonModeInfoParams *const mi_params = &cm->mi_params; |
| |
| const PartitionBlkParams *blk_params = &part_state->part_blk_params; |
| const BLOCK_SIZE bsize = blk_params->bsize; |
| |
| if (cpi->third_pass_ctx) { |
| int mi_row = blk_params->mi_row; |
| int mi_col = blk_params->mi_col; |
| double ratio_h, ratio_w; |
| av1_get_third_pass_ratio(cpi->third_pass_ctx, 0, cm->height, cm->width, |
| &ratio_h, &ratio_w); |
| THIRD_PASS_MI_INFO *this_mi = av1_get_third_pass_mi( |
| cpi->third_pass_ctx, 0, mi_row, mi_col, ratio_h, ratio_w); |
| BLOCK_SIZE third_pass_bsize = |
| av1_get_third_pass_adjusted_blk_size(this_mi, ratio_h, ratio_w); |
| // check the actual partition of this block in the second pass |
| PARTITION_TYPE third_pass_part = |
| av1_third_pass_get_sb_part_type(cpi->third_pass_ctx, this_mi); |
| |
| int is_edge = (mi_row + mi_size_high[bsize] >= cm->mi_params.mi_rows) || |
| (mi_col + mi_size_wide[bsize] >= cm->mi_params.mi_cols); |
| |
| if (!is_edge && block_size_wide[bsize] >= 16) { |
| // If in second pass we used rectangular partition, then do not search for |
| // rectangular partition in the different direction. |
| if (third_pass_part != PARTITION_NONE) { |
| if (third_pass_part == PARTITION_HORZ || |
| third_pass_part == PARTITION_HORZ_4 || |
| third_pass_part == PARTITION_HORZ_A || |
| third_pass_part == PARTITION_HORZ_B) { |
| part_state->partition_rect_allowed[VERT] = 0; |
| } else if (third_pass_part == PARTITION_VERT || |
| third_pass_part == PARTITION_VERT_4 || |
| third_pass_part == PARTITION_VERT_A || |
| third_pass_part == PARTITION_VERT_B) { |
| part_state->partition_rect_allowed[HORZ] = 0; |
| } |
| } |
| |
| int minSize = AOMMIN(block_size_wide[third_pass_bsize], |
| block_size_high[third_pass_bsize]); |
| int maxSize = AOMMAX(block_size_wide[third_pass_bsize], |
| block_size_high[third_pass_bsize]); |
| if (block_size_wide[bsize] < minSize / 4) { |
| // Current partition is too small, just terminate |
| part_state->terminate_partition_search = 1; |
| return; |
| } else if (block_size_wide[bsize] < minSize / 2) { |
| if (third_pass_part != PARTITION_NONE) { |
| // Current partition is very small, and in second pass we used |
| // rectangular partition. Terminate the search here then. |
| part_state->terminate_partition_search = 1; |
| return; |
| } else { |
| // Partition is small, but we still check this partition, only disable |
| // further splits. |
| // TODO(any): check why this is not covered by the termination for < |
| // minSize/4. |
| av1_disable_square_split_partition(part_state); |
| av1_disable_rect_partitions(part_state); |
| return; |
| } |
| } else if (block_size_wide[bsize] > maxSize) { |
| // Partition is larger than in the second pass. Only allow split. |
| av1_set_square_split_only(part_state); |
| return; |
| } else if (block_size_wide[bsize] >= minSize && |
| block_size_wide[bsize] <= maxSize) { |
| // Partition is within a range where it is very likely to find a good |
| // choice, so do not prune anything. |
| return; |
| } |
| } |
| } |
| |
| // Prune rectangular partitions for larger blocks. |
| if (bsize > cpi->sf.part_sf.rect_partition_eval_thresh) { |
| part_state->do_rectangular_split = 0; |
| part_state->partition_rect_allowed[HORZ] = 0; |
| part_state->partition_rect_allowed[VERT] = 0; |
| } |
| |
| // Prune rectangular, AB and 4-way partition based on q index and block size |
| if (cpi->sf.part_sf.prune_rectangular_split_based_on_qidx == 1) { |
| if (bsize == BLOCK_8X8 && x->qindex < 35) |
| av1_disable_rect_partitions(part_state); |
| |
| } else if (cpi->sf.part_sf.prune_rectangular_split_based_on_qidx == 2) { |
| // Enumeration difference between two square partitions |
| const int sqr_bsize_step = BLOCK_32X32 - BLOCK_16X16; |
| int max_bsize = |
| BLOCK_32X32 - (x->qindex * 3 / QINDEX_RANGE) * sqr_bsize_step; |
| max_bsize = AOMMAX(max_bsize, BLOCK_4X4); |
| const BLOCK_SIZE max_prune_bsize = |
| (BLOCK_SIZE)AOMMIN(max_bsize, BLOCK_32X32); |
| |
| // Prune partition |
| // qidx 0 to 85: prune bsize below BLOCK_32X32 |
| // qidx 86 to 170: prune bsize below BLOCK_16X16 |
| // qidx 171 to 255: prune bsize below BLOCK_8X8 |
| if (bsize < max_prune_bsize) { |
| av1_disable_rect_partitions(part_state); |
| } |
| } |
| |
| if (cpi->sf.part_sf.prune_sub_8x8_partition_level && (bsize == BLOCK_8X8)) { |
| const MACROBLOCKD *const xd = &x->e_mbd; |
| int prune_sub_8x8 = 1; |
| if (cpi->sf.part_sf.prune_sub_8x8_partition_level == 1) { |
| int num_neighbors_lt_8x8 = 0; |
| if (xd->left_available) |
| num_neighbors_lt_8x8 += (xd->left_mbmi->bsize <= BLOCK_8X8); |
| if (xd->up_available) |
| num_neighbors_lt_8x8 += (xd->above_mbmi->bsize <= BLOCK_8X8); |
| // Evaluate only if both left and above blocks are of size <= BLOCK_8X8. |
| if (num_neighbors_lt_8x8 == 2) { |
| prune_sub_8x8 = 0; |
| } |
| } |
| if (prune_sub_8x8) { |
| av1_disable_all_splits(part_state); |
| } |
| } |
| |
| // A CNN-based speed feature pruning out either split or all non-split |
| // partition in INTRA frame coding. |
| const int try_intra_cnn_based_part_prune = |
| frame_is_intra_only(cm) && |
| cpi->sf.part_sf.intra_cnn_based_part_prune_level && |
| cm->seq_params->sb_size >= BLOCK_64X64 && bsize <= BLOCK_64X64 && |
| blk_params->bsize_at_least_8x8 && |
| av1_is_whole_blk_in_frame(blk_params, mi_params); |
| |
| if (try_intra_cnn_based_part_prune) { |
| av1_intra_mode_cnn_partition( |
| &cpi->common, x, x->part_search_info.quad_tree_idx, |
| cpi->sf.part_sf.intra_cnn_based_part_prune_level, part_state); |
| } |
| |
| // Use simple motion search to prune out split or non-split partitions. This |
| // must be done prior to PARTITION_SPLIT to propagate the initial mvs to a |
| // smaller blocksize. |
| const int try_split_only = |
| cpi->sf.part_sf.simple_motion_search_split && |
| part_state->do_square_split && blk_params->bsize_at_least_8x8 && |
| av1_is_whole_blk_in_frame(blk_params, mi_params) && |
| !frame_is_intra_only(cm) && !av1_superres_scaled(cm); |
| |
| if (try_split_only) { |
| av1_simple_motion_search_based_split(cpi, x, sms_tree, part_state); |
| } |
| |
| // Use simple motion search to prune out rectangular partition in some |
| // direction. The results are stored in prune_horz and prune_vert in order to |
| // bypass future related pruning checks if a pruning decision has been made. |
| |
| // We want to search at least one partition mode, so don't prune if NONE and |
| // SPLIT are disabled. |
| const int non_rect_part_allowed = |
| part_state->do_square_split || part_state->partition_none_allowed; |
| // Only run the model if the partitions are not already pruned. |
| const int rect_part_allowed = part_state->do_rectangular_split && |
| ((part_state->partition_rect_allowed[HORZ] && |
| !part_state->prune_rect_part[HORZ]) || |
| (part_state->partition_rect_allowed[VERT] && |
| !part_state->prune_rect_part[VERT])); |
| |
| const int try_prune_rect = cpi->sf.part_sf.simple_motion_search_prune_rect && |
| !frame_is_intra_only(cm) && |
| non_rect_part_allowed && rect_part_allowed && |
| !av1_superres_scaled(cm); |
| |
| if (try_prune_rect) { |
| av1_simple_motion_search_prune_rect(cpi, x, sms_tree, part_state); |
| } |
| } |
| |
| #ifndef NDEBUG |
| static AOM_INLINE int is_bsize_square(BLOCK_SIZE bsize) { |
| return block_size_wide[bsize] == block_size_high[bsize]; |
| } |
| #endif // NDEBUG |
| |
| void av1_prune_partitions_by_max_min_bsize(SuperBlockEnc *sb_enc, |
| PartitionSearchState *part_state) { |
| assert(is_bsize_square(sb_enc->max_partition_size)); |
| assert(is_bsize_square(sb_enc->min_partition_size)); |
| assert(sb_enc->min_partition_size <= sb_enc->max_partition_size); |
| const PartitionBlkParams *blk_params = &part_state->part_blk_params; |
| const BLOCK_SIZE bsize = blk_params->bsize; |
| assert(is_bsize_square(bsize)); |
| const int max_partition_size_1d = block_size_wide[sb_enc->max_partition_size]; |
| const int min_partition_size_1d = block_size_wide[sb_enc->min_partition_size]; |
| const int bsize_1d = block_size_wide[bsize]; |
| assert(min_partition_size_1d <= max_partition_size_1d); |
| const int is_le_min_sq_part = bsize_1d <= min_partition_size_1d; |
| const int is_gt_max_sq_part = bsize_1d > max_partition_size_1d; |
| if (is_gt_max_sq_part) { |
| // If current block size is larger than max, only allow split. |
| av1_set_square_split_only(part_state); |
| } else if (is_le_min_sq_part) { |
| // If current block size is less or equal to min, only allow none if valid |
| // block large enough; only allow split otherwise. |
| av1_disable_rect_partitions(part_state); |
| |
| // only disable square split when current block is not at the picture |
| // boundary. otherwise, inherit the square split flag from previous logic |
| if (av1_blk_has_rows_and_cols(blk_params)) { |
| part_state->do_square_split = 0; |
| } |
| part_state->partition_none_allowed = !(part_state->do_square_split); |
| } |
| } |
| |
| // Decide whether to evaluate the AB partition specified by part_type based on |
| // split and HORZ/VERT info |
| int evaluate_ab_partition_based_on_split( |
| const PC_TREE *pc_tree, PARTITION_TYPE rect_part, |
| const RD_RECT_PART_WIN_INFO *rect_part_win_info, int qindex, int split_idx1, |
| int split_idx2) { |
| int num_win = 0; |
| // Threshold for number of winners |
| // Conservative pruning for high quantizers |
| const int num_win_thresh = AOMMIN(3 * (2 * (MAXQ - qindex) / MAXQ), 3); |
| int sub_part_win = |
| (rect_part_win_info == NULL) ? (pc_tree->partitioning == rect_part) |
| : (rect_part == PARTITION_HORZ) ? rect_part_win_info->rect_part_win[HORZ] |
| : rect_part_win_info->rect_part_win[VERT]; |
| num_win += (sub_part_win) ? 1 : 0; |
| if (pc_tree->split[split_idx1]) { |
| num_win += |
| (pc_tree->split[split_idx1]->partitioning == PARTITION_NONE) ? 1 : 0; |
| } else { |
| num_win += 1; |
| } |
| if (pc_tree->split[split_idx2]) { |
| num_win += |
| (pc_tree->split[split_idx2]->partitioning == PARTITION_NONE) ? 1 : 0; |
| } else { |
| num_win += 1; |
| } |
| if (num_win < num_win_thresh) { |
| return 0; |
| } |
| return 1; |
| } |
| |
| void av1_prune_ab_partitions(AV1_COMP *cpi, const MACROBLOCK *x, |
| const PC_TREE *pc_tree, int pb_source_variance, |
| int64_t best_rdcost, |
| const RD_RECT_PART_WIN_INFO *rect_part_win_info, |
| bool ext_partition_allowed, |
| PartitionSearchState *part_state, |
| int *ab_partitions_allowed) { |
| int64_t *horz_rd = part_state->rect_part_rd[HORZ]; |
| int64_t *vert_rd = part_state->rect_part_rd[VERT]; |
| int64_t *split_rd = part_state->split_rd; |
| const PartitionCfg *const part_cfg = &cpi->oxcf.part_cfg; |
| // The standard AB partitions are allowed initially if ext-partition-types are |
| // allowed. |
| int horzab_partition_allowed = ext_partition_allowed && |
| part_cfg->enable_ab_partitions && |
| part_state->partition_rect_allowed[HORZ]; |
| int vertab_partition_allowed = ext_partition_allowed && |
| part_cfg->enable_ab_partitions && |
| part_state->partition_rect_allowed[VERT]; |
| |
| // Pruning: pruning out AB partitions on one main direction based on the |
| // current best partition and source variance. |
| if (cpi->sf.part_sf.prune_ext_partition_types_search_level) { |
| if (cpi->sf.part_sf.prune_ext_partition_types_search_level == 1) { |
| // TODO(debargha,huisu@google.com): may need to tune the threshold for |
| // pb_source_variance. |
| horzab_partition_allowed &= (pc_tree->partitioning == PARTITION_HORZ || |
| (pc_tree->partitioning == PARTITION_NONE && |
| pb_source_variance < 32) || |
| pc_tree->partitioning == PARTITION_SPLIT); |
| vertab_partition_allowed &= (pc_tree->partitioning == PARTITION_VERT || |
| (pc_tree->partitioning == PARTITION_NONE && |
| pb_source_variance < 32) || |
| pc_tree->partitioning == PARTITION_SPLIT); |
| } else { |
| horzab_partition_allowed &= (pc_tree->partitioning == PARTITION_HORZ || |
| pc_tree->partitioning == PARTITION_SPLIT); |
| vertab_partition_allowed &= (pc_tree->partitioning == PARTITION_VERT || |
| pc_tree->partitioning == PARTITION_SPLIT); |
| } |
| horz_rd[0] = (horz_rd[0] < INT64_MAX ? horz_rd[0] : 0); |
| horz_rd[1] = (horz_rd[1] < INT64_MAX ? horz_rd[1] : 0); |
| vert_rd[0] = (vert_rd[0] < INT64_MAX ? vert_rd[0] : 0); |
| vert_rd[1] = (vert_rd[1] < INT64_MAX ? vert_rd[1] : 0); |
| split_rd[0] = (split_rd[0] < INT64_MAX ? split_rd[0] : 0); |
| split_rd[1] = (split_rd[1] < INT64_MAX ? split_rd[1] : 0); |
| split_rd[2] = (split_rd[2] < INT64_MAX ? split_rd[2] : 0); |
| split_rd[3] = (split_rd[3] < INT64_MAX ? split_rd[3] : 0); |
| } |
| |
| // Pruning: pruning out horz_a or horz_b if the combined rdcost of its |
| // subblocks estimated from previous partitions is much higher than the best |
| // rd so far. |
| ab_partitions_allowed[HORZ_A] = horzab_partition_allowed; |
| ab_partitions_allowed[HORZ_B] = horzab_partition_allowed; |
| if (cpi->sf.part_sf.prune_ext_partition_types_search_level) { |
| const int64_t horz_a_rd = horz_rd[1] + split_rd[0] + split_rd[1]; |
| const int64_t horz_b_rd = horz_rd[0] + split_rd[2] + split_rd[3]; |
| switch (cpi->sf.part_sf.prune_ext_partition_types_search_level) { |
| case 1: |
| ab_partitions_allowed[HORZ_A] &= (horz_a_rd / 16 * 14 < best_rdcost); |
| ab_partitions_allowed[HORZ_B] &= (horz_b_rd / 16 * 14 < best_rdcost); |
| break; |
| case 2: |
| default: |
| ab_partitions_allowed[HORZ_A] &= (horz_a_rd / 16 * 15 < best_rdcost); |
| ab_partitions_allowed[HORZ_B] &= (horz_b_rd / 16 * 15 < best_rdcost); |
| break; |
| } |
| } |
| |
| // Pruning: pruning out vert_a or vert_b if the combined rdcost of its |
| // subblocks estimated from previous partitions is much higher than the best |
| // rd so far. |
| ab_partitions_allowed[VERT_A] = vertab_partition_allowed; |
| ab_partitions_allowed[VERT_B] = vertab_partition_allowed; |
| if (cpi->sf.part_sf.prune_ext_partition_types_search_level) { |
| const int64_t vert_a_rd = vert_rd[1] + split_rd[0] + split_rd[2]; |
| const int64_t vert_b_rd = vert_rd[0] + split_rd[1] + split_rd[3]; |
| switch (cpi->sf.part_sf.prune_ext_partition_types_search_level) { |
| case 1: |
| ab_partitions_allowed[VERT_A] &= (vert_a_rd / 16 * 14 < best_rdcost); |
| ab_partitions_allowed[VERT_B] &= (vert_b_rd / 16 * 14 < best_rdcost); |
| break; |
| case 2: |
| default: |
| ab_partitions_allowed[VERT_A] &= (vert_a_rd / 16 * 15 < best_rdcost); |
| ab_partitions_allowed[VERT_B] &= (vert_b_rd / 16 * 15 < best_rdcost); |
| break; |
| } |
| } |
| |
| // Pruning: pruning out some ab partitions using a DNN taking rd costs of |
| // sub-blocks from previous basic partition types. |
| if (cpi->sf.part_sf.ml_prune_partition && ext_partition_allowed && |
| part_state->partition_rect_allowed[HORZ] && |
| part_state->partition_rect_allowed[VERT]) { |
| // TODO(huisu@google.com): x->source_variance may not be the current |
| // block's variance. The correct one to use is pb_source_variance. Need to |
| // re-train the model to fix it. |
| av1_ml_prune_ab_partition(cpi, pc_tree->partitioning, |
| get_unsigned_bits(x->source_variance), |
| best_rdcost, part_state, ab_partitions_allowed); |
| } |
| |
| // Pruning: pruning AB partitions based on the number of horz/vert wins |
| // in the current block and sub-blocks in PARTITION_SPLIT. |
| if (cpi->sf.part_sf.prune_ext_part_using_split_info >= 2 && |
| ab_partitions_allowed[HORZ_A]) { |
| ab_partitions_allowed[HORZ_A] &= evaluate_ab_partition_based_on_split( |
| pc_tree, PARTITION_HORZ, rect_part_win_info, x->qindex, 0, 1); |
| } |
| if (cpi->sf.part_sf.prune_ext_part_using_split_info >= 2 && |
| ab_partitions_allowed[HORZ_B]) { |
| ab_partitions_allowed[HORZ_B] &= evaluate_ab_partition_based_on_split( |
| pc_tree, PARTITION_HORZ, rect_part_win_info, x->qindex, 2, 3); |
| } |
| if (cpi->sf.part_sf.prune_ext_part_using_split_info >= 2 && |
| ab_partitions_allowed[VERT_A]) { |
| ab_partitions_allowed[VERT_A] &= evaluate_ab_partition_based_on_split( |
| pc_tree, PARTITION_VERT, rect_part_win_info, x->qindex, 0, 2); |
| } |
| if (cpi->sf.part_sf.prune_ext_part_using_split_info >= 2 && |
| ab_partitions_allowed[VERT_B]) { |
| ab_partitions_allowed[VERT_B] &= evaluate_ab_partition_based_on_split( |
| pc_tree, PARTITION_VERT, rect_part_win_info, x->qindex, 1, 3); |
| } |
| } |
| |
| // Prepare features for the external model. Specifically, features after |
| // ab partition is searched. |
| static void prepare_features_after_part_ab( |
| const AV1_COMP *const cpi, MACROBLOCK *const x, BLOCK_SIZE bsize, |
| int part_ctx, int64_t best_rd, |
| int64_t rect_part_rd[NUM_RECT_PARTS][SUB_PARTITIONS_RECT], |
| int64_t split_rd[SUB_PARTITIONS_SPLIT], unsigned int pb_source_variance, |
| int mi_row, int mi_col, aom_partition_features_t *const features) { |
| int64_t *horz_rd = rect_part_rd[HORZ]; |
| int64_t *vert_rd = rect_part_rd[VERT]; |
| |
| // Generate features. |
| int feature_index = 0; |
| features->after_part_ab.f[feature_index++] = (float)part_ctx; |
| features->after_part_ab.f[feature_index++] = |
| (float)get_unsigned_bits(pb_source_variance); |
| |
| const int rdcost = (int)AOMMIN(INT_MAX, best_rd); |
| int sub_block_rdcost[8] = { 0 }; |
| int rd_index = 0; |
| for (int i = 0; i < SUB_PARTITIONS_RECT; ++i) { |
| if (horz_rd[i] > 0 && horz_rd[i] < 1000000000) |
| sub_block_rdcost[rd_index] = (int)horz_rd[i]; |
| ++rd_index; |
| } |
| for (int i = 0; i < SUB_PARTITIONS_RECT; ++i) { |
| if (vert_rd[i] > 0 && vert_rd[i] < 1000000000) |
| sub_block_rdcost[rd_index] = (int)vert_rd[i]; |
| ++rd_index; |
| } |
| for (int i = 0; i < SUB_PARTITIONS_SPLIT; ++i) { |
| if (split_rd[i] > 0 && split_rd[i] < 1000000000) |
| sub_block_rdcost[rd_index] = (int)split_rd[i]; |
| ++rd_index; |
| } |
| for (int i = 0; i < 8; ++i) { |
| // Ratio between the sub-block RD and the whole-block RD. |
| float rd_ratio = 1.0f; |
| if (sub_block_rdcost[i] > 0 && sub_block_rdcost[i] < rdcost) |
| rd_ratio = (float)sub_block_rdcost[i] / (float)rdcost; |
| features->after_part_ab.f[feature_index++] = rd_ratio; |
| } |
| |
| // Get variance of the 1:4 and 4:1 sub-blocks. |
| unsigned int horz_4_source_var[SUB_PARTITIONS_PART4] = { 0 }; |
| unsigned int vert_4_source_var[SUB_PARTITIONS_PART4] = { 0 }; |
| { |
| BLOCK_SIZE horz_4_bs = get_partition_subsize(bsize, PARTITION_HORZ_4); |
| BLOCK_SIZE vert_4_bs = get_partition_subsize(bsize, PARTITION_VERT_4); |
| av1_setup_src_planes(x, cpi->source, mi_row, mi_col, |
| av1_num_planes(&cpi->common), bsize); |
| const int src_stride = x->plane[0].src.stride; |
| uint8_t *src = x->plane[0].src.buf; |
| const MACROBLOCKD *const xd = &x->e_mbd; |
| |
| struct buf_2d horz_4_src, vert_4_src; |
| horz_4_src.stride = src_stride; |
| vert_4_src.stride = src_stride; |
| |
| for (int i = 0; i < SUB_PARTITIONS_PART4; ++i) { |
| horz_4_src.buf = src + i * block_size_high[horz_4_bs] * src_stride; |
| vert_4_src.buf = src + i * block_size_wide[vert_4_bs]; |
| |
| horz_4_source_var[i] = av1_get_perpixel_variance_facade( |
| cpi, xd, &horz_4_src, horz_4_bs, AOM_PLANE_Y); |
| vert_4_source_var[i] = av1_get_perpixel_variance_facade( |
| cpi, xd, &vert_4_src, vert_4_bs, AOM_PLANE_Y); |
| } |
| } |
| |
| const float denom = (float)(pb_source_variance + 1); |
| const float low_b = 0.1f; |
| const float high_b = 10.0f; |
| for (int i = 0; i < SUB_PARTITIONS_PART4; ++i) { |
| // Ratio between the 4:1 sub-block variance and the whole-block variance. |
| float var_ratio = (float)(horz_4_source_var[i] + 1) / denom; |
| if (var_ratio < low_b) var_ratio = low_b; |
| if (var_ratio > high_b) var_ratio = high_b; |
| features->after_part_ab.f[feature_index++] = var_ratio; |
| } |
| for (int i = 0; i < SUB_PARTITIONS_PART4; ++i) { |
| // Ratio between the 1:4 sub-block RD and the whole-block RD. |
| float var_ratio = (float)(vert_4_source_var[i] + 1) / denom; |
| if (var_ratio < low_b) var_ratio = low_b; |
| if (var_ratio > high_b) var_ratio = high_b; |
| features->after_part_ab.f[feature_index++] = var_ratio; |
| } |
| assert(feature_index == 18); |
| } |
| |
| // If the external partition model is used, we let it determine partition |
| // decisions before partition none. Specifically, these parameters: |
| // partition_none_allowed |
| // partition_horz_allowed |
| // partition_vert_allowed |
| // do_rectangular_split |
| // do_square_split |
| static bool ext_ml_model_decision_before_none( |
| AV1_COMP *cpi, const float features_from_motion[FEATURE_SIZE_SMS_SPLIT], |
| int *partition_none_allowed, int *partition_horz_allowed, |
| int *partition_vert_allowed, int *do_rectangular_split, |
| int *do_square_split) { |
| ExtPartController *const ext_part_controller = &cpi->ext_part_controller; |
| if (!ext_part_controller->ready) return false; |
| |
| // Setup features. |
| aom_partition_features_t features; |
| features.id = AOM_EXT_PART_FEATURE_BEFORE_NONE; |
| for (int i = 0; i < FEATURE_SIZE_SMS_SPLIT; ++i) { |
| features.before_part_none.f[i] = features_from_motion[i]; |
| } |
| |
| // Send necessary features to the external model. |
| av1_ext_part_send_features(ext_part_controller, &features); |
| |
| // Get partition decisions from the external model. |
| aom_partition_decision_t decision; |
| const bool valid_decision = |
| av1_ext_part_get_partition_decision(ext_part_controller, &decision); |
| if (!valid_decision) return false; |
| |
| // Populate decisions |
| *partition_none_allowed = decision.partition_none_allowed; |
| *partition_horz_allowed = decision.partition_rect_allowed[HORZ]; |
| *partition_vert_allowed = decision.partition_rect_allowed[VERT]; |
| *do_rectangular_split = decision.do_rectangular_split; |
| *do_square_split = decision.do_square_split; |
| |
| return true; |
| } |
| |
| // If the external partition model is used, we let it determine partition |
| // decisions before partition none. Specifically, these parameters: |
| // prune_horz |
| // prune_vert |
| static bool ext_ml_model_decision_before_none_part2( |
| AV1_COMP *cpi, |
| const float features_from_motion[FEATURE_SIZE_SMS_PRUNE_PART], |
| int *prune_horz, int *prune_vert) { |
| ExtPartController *const ext_part_controller = &cpi->ext_part_controller; |
| if (!ext_part_controller->ready) return false; |
| |
| // Setup features. |
| aom_partition_features_t features; |
| features.id = AOM_EXT_PART_FEATURE_BEFORE_NONE_PART2; |
| for (int i = 0; i < FEATURE_SIZE_SMS_PRUNE_PART; ++i) { |
| features.before_part_none.f_part2[i] = features_from_motion[i]; |
| } |
| |
| // Send necessary features to the external model. |
| av1_ext_part_send_features(ext_part_controller, &features); |
| |
| // Get partition decisions from the external model. |
| aom_partition_decision_t decision; |
| const bool valid_decision = |
| av1_ext_part_get_partition_decision(ext_part_controller, &decision); |
| if (!valid_decision) return false; |
| |
| // Populate decisions |
| *prune_horz = decision.prune_rect_part[HORZ]; |
| *prune_vert = decision.prune_rect_part[VERT]; |
| |
| return true; |
| } |
| |
| // If the external partition model is used, we let it determine partition |
| // decisions after none partition. Specifically, these parameters: |
| // do_square_split |
| // do_rectangular_split |
| bool ext_ml_model_decision_after_none( |
| ExtPartController *const ext_part_controller, const int is_intra_frame, |
| const float *const features_after_none, int *do_square_split, |
| int *do_rectangular_split) { |
| if (!ext_part_controller->ready || is_intra_frame) return false; |
| |
| // Setup features. |
| aom_partition_features_t features; |
| features.id = AOM_EXT_PART_FEATURE_AFTER_NONE; |
| for (int i = 0; i < 4; ++i) { |
| features.after_part_none.f[i] = features_after_none[i]; |
| } |
| |
| // Send necessary features to the external model. |
| av1_ext_part_send_features(ext_part_controller, &features); |
| |
| // Get partition decisions from the external model. |
| aom_partition_decision_t decision; |
| const bool valid_decision = |
| av1_ext_part_get_partition_decision(ext_part_controller, &decision); |
| if (!valid_decision) return false; |
| |
| // Populate decisions |
| *do_square_split = decision.do_square_split; |
| *do_rectangular_split = decision.do_rectangular_split; |
| |
| return true; |
| } |
| |
| // If the external partition model is used, we let it determine partition |
| // decisions after none partition. Specifically, these parameters: |
| // terminate_partition_search |
| bool ext_ml_model_decision_after_none_part2( |
| AV1_COMP *const cpi, const float *const features_terminate, |
| int *terminate_partition_search) { |
| AV1_COMMON *const cm = &cpi->common; |
| ExtPartController *const ext_part_controller = &cpi->ext_part_controller; |
| if (!ext_part_controller->ready || frame_is_intra_only(cm)) return false; |
| |
| // Setup features. |
| aom_partition_features_t features; |
| features.id = AOM_EXT_PART_FEATURE_AFTER_NONE_PART2; |
| for (int i = 0; i < FEATURE_SIZE_SMS_TERM_NONE; ++i) { |
| features.after_part_none.f_terminate[i] = features_terminate[i]; |
| } |
| |
| // Send necessary features to the external model. |
| av1_ext_part_send_features(ext_part_controller, &features); |
| |
| // Get partition decisions from the external model. |
| aom_partition_decision_t decision; |
| const bool valid_decision = |
| av1_ext_part_get_partition_decision(ext_part_controller, &decision); |
| if (!valid_decision) return false; |
| |
| // Populate decisions |
| *terminate_partition_search = decision.terminate_partition_search; |
| |
| return true; |
| } |
| |
| // If the external partition model is used, we let it determine partition |
| // decisions after none partition. Specifically, these parameters: |
| // terminate_partition_search |
| bool ext_ml_model_decision_after_split(AV1_COMP *const cpi, |
| const float *const features_terminate, |
| int *terminate_partition_search) { |
| const AV1_COMMON *const cm = &cpi->common; |
| ExtPartController *const ext_part_controller = &cpi->ext_part_controller; |
| if (frame_is_intra_only(cm) || !cpi->ext_part_controller.ready) { |
| return false; |
| } |
| |
| // Setup features. |
| aom_partition_features_t features; |
| features.id = AOM_EXT_PART_FEATURE_AFTER_SPLIT; |
| for (int i = 0; i < 31; ++i) { |
| features.after_part_split.f_terminate[i] = features_terminate[i]; |
| } |
| |
| // Send necessary features to the external model. |
| av1_ext_part_send_features(ext_part_controller, &features); |
| |
| // Get partition decisions from the external model. |
| aom_partition_decision_t decision; |
| const bool valid_decision = |
| av1_ext_part_get_partition_decision(ext_part_controller, &decision); |
| if (!valid_decision) return false; |
| |
| // Populate decisions |
| *terminate_partition_search = decision.terminate_partition_search; |
| |
| return true; |
| } |
| |
| // If the external partition model is used, we let it determine partition |
| // decisions after none partition. Specifically, these parameters: |
| // prune_rect_part[HORZ] |
| // prune_rect_part[VERT] |
| bool ext_ml_model_decision_after_split_part2( |
| ExtPartController *const ext_part_controller, const int is_intra_frame, |
| const float *const features_prune, int *prune_rect_part_horz, |
| int *prune_rect_part_vert) { |
| if (is_intra_frame || !ext_part_controller->ready) { |
| return false; |
| } |
| |
| // Setup features. |
| aom_partition_features_t features; |
| features.id = AOM_EXT_PART_FEATURE_AFTER_SPLIT_PART2; |
| for (int i = 0; i < 9; ++i) { |
| features.after_part_split.f_prune_rect[i] = features_prune[i]; |
| } |
| |
| // Send necessary features to the external model. |
| av1_ext_part_send_features(ext_part_controller, &features); |
| |
| // Get partition decisions from the external model. |
| aom_partition_decision_t decision; |
| const bool valid_decision = |
| av1_ext_part_get_partition_decision(ext_part_controller, &decision); |
| if (!valid_decision) return false; |
| |
| // Populate decisions |
| *prune_rect_part_horz = decision.prune_rect_part[0]; |
| *prune_rect_part_vert = decision.prune_rect_part[1]; |
| |
| return true; |
| } |
| |
| // If the external partition model is used, we let it determine partition |
| // decisions after rectangular partition. Specifically, these parameters: |
| // horza_partition_allowed |
| // horzb_partition_allowed |
| // verta_partition_allowed |
| // vertb_partition_allowed |
| static bool ext_ml_model_decision_after_rect( |
| ExtPartController *const ext_part_controller, const int is_intra_frame, |
| const float *const features_after_rect, int *horza_partition_allowed, |
| int *horzb_partition_allowed, int *verta_partition_allowed, |
| int *vertb_partition_allowed) { |
| if (is_intra_frame || !ext_part_controller->ready) return false; |
| |
| // Setup features. |
| aom_partition_features_t features; |
| features.id = AOM_EXT_PART_FEATURE_AFTER_RECT; |
| for (int i = 0; i < 10; ++i) { |
| features.after_part_rect.f[i] = features_after_rect[i]; |
| } |
| |
| // Send necessary features to the external model. |
| av1_ext_part_send_features(ext_part_controller, &features); |
| |
| // Get partition decisions from the external model. |
| aom_partition_decision_t decision; |
| const bool valid_decision = |
| av1_ext_part_get_partition_decision(ext_part_controller, &decision); |
| if (!valid_decision) return false; |
| |
| // Populate decisions |
| *horza_partition_allowed = decision.horza_partition_allowed; |
| *horzb_partition_allowed = decision.horzb_partition_allowed; |
| *verta_partition_allowed = decision.verta_partition_allowed; |
| *vertb_partition_allowed = decision.vertb_partition_allowed; |
| |
| return true; |
| } |
| |
| // If the external partition model is used, we let it determine partition |
| // decisions after AB partition. Specifically, these parameters: |
| // partition_vert4_allowed |
| // partition_horz4_allowed |
| static bool ext_ml_model_decision_after_part_ab( |
| AV1_COMP *const cpi, MACROBLOCK *const x, BLOCK_SIZE bsize, int part_ctx, |
| int64_t best_rd, int64_t rect_part_rd[NUM_RECT_PARTS][SUB_PARTITIONS_RECT], |
| int64_t split_rd[SUB_PARTITIONS_SPLIT], int *const partition_horz4_allowed, |
| int *const partition_vert4_allowed, unsigned int pb_source_variance, |
| int mi_row, int mi_col) { |
| const AV1_COMMON *const cm = &cpi->common; |
| ExtPartController *const ext_part_controller = &cpi->ext_part_controller; |
| |
| if (!frame_is_intra_only(cm) && ext_part_controller->ready) { |
| // Setup features. |
| aom_partition_features_t features; |
| features.id = AOM_EXT_PART_FEATURE_AFTER_AB; |
| prepare_features_after_part_ab(cpi, x, bsize, part_ctx, best_rd, |
| rect_part_rd, split_rd, pb_source_variance, |
| mi_row, mi_col, &features); |
| |
| // Send necessary features to the external model. |
| av1_ext_part_send_features(ext_part_controller, &features); |
| |
| // Get partition decisions from the external model. |
| aom_partition_decision_t decision; |
| const bool valid_decision = |
| av1_ext_part_get_partition_decision(ext_part_controller, &decision); |
| if (!valid_decision) return false; |
| |
| // Populate decisions |
| *partition_horz4_allowed = decision.partition_horz4_allowed; |
| *partition_vert4_allowed = decision.partition_vert4_allowed; |
| |
| return true; |
| } |
| |
| return false; |
| } |
| |
| // This function resembles "av1_setup_sms_tree()" in context_tree.c |
| // with function signature change. |
| static SIMPLE_MOTION_DATA_TREE *setup_sms_tree( |
| AV1_COMP *const cpi, SIMPLE_MOTION_DATA_TREE *sms_tree) { |
| AV1_COMMON *const cm = &cpi->common; |
| const int stat_generation_stage = is_stat_generation_stage(cpi); |
| const int is_sb_size_128 = cm->seq_params->sb_size == BLOCK_128X128; |
| const int tree_nodes = |
| av1_get_pc_tree_nodes(is_sb_size_128, stat_generation_stage); |
| int sms_tree_index = 0; |
| SIMPLE_MOTION_DATA_TREE *this_sms; |
| int square_index = 1; |
| int nodes; |
| this_sms = &sms_tree[0]; |
| |
| if (!stat_generation_stage) { |
| const int leaf_factor = is_sb_size_128 ? 4 : 1; |
| const int leaf_nodes = 256 * leaf_factor; |
| |
| // Sets up all the leaf nodes in the tree. |
| for (sms_tree_index = 0; sms_tree_index < leaf_nodes; ++sms_tree_index) { |
| SIMPLE_MOTION_DATA_TREE *const tree = &sms_tree[sms_tree_index]; |
| tree->block_size = square[0]; |
| } |
| |
| // Each node has 4 leaf nodes, fill each block_size level of the tree |
| // from leafs to the root. |
| for (nodes = leaf_nodes >> 2; nodes > 0; nodes >>= 2) { |
| for (int i = 0; i < nodes; ++i) { |
| SIMPLE_MOTION_DATA_TREE *const tree = &sms_tree[sms_tree_index]; |
| tree->block_size = square[square_index]; |
| for (int j = 0; j < 4; j++) tree->split[j] = this_sms++; |
| ++sms_tree_index; |
| } |
| ++square_index; |
| } |
| } else { |
| // Allocation for firstpass/LAP stage |
| // TODO(Mufaddal): refactor square_index to use a common block_size macro |
| // from firstpass.c |
| SIMPLE_MOTION_DATA_TREE *const tree = &sms_tree[sms_tree_index]; |
| square_index = 2; |
| tree->block_size = square[square_index]; |
| } |
| |
| // Set up the root node for the largest superblock size |
| return &sms_tree[tree_nodes - 1]; |
| } |
| |
| static void write_motion_feature_to_file( |
| const char *const path, const int sb_counter, const unsigned int *block_sse, |
| const unsigned int *block_var, const int num_blocks, const BLOCK_SIZE bsize, |
| const BLOCK_SIZE fixed_block_size, const int mi_row, const int mi_col) { |
| char filename[256]; |
| snprintf(filename, sizeof(filename), "%s/motion_search_feature_sb%d", path, |
| sb_counter); |
| FILE *pfile = fopen(filename, "w"); |
| fprintf(pfile, "%d,%d,%d,%d,%d\n", mi_row, mi_col, bsize, |
| block_size_wide[fixed_block_size], num_blocks); |
| for (int i = 0; i < num_blocks; ++i) { |
| fprintf(pfile, "%d", block_sse[i]); |
| if (i < num_blocks - 1) fprintf(pfile, ","); |
| } |
| fprintf(pfile, "\n"); |
| for (int i = 0; i < num_blocks; ++i) { |
| fprintf(pfile, "%d", block_var[i]); |
| if (i < num_blocks - 1) fprintf(pfile, ","); |
| } |
| fprintf(pfile, "\n"); |
| fclose(pfile); |
| } |
| |
| void av1_collect_motion_search_features_sb(AV1_COMP *const cpi, ThreadData *td, |
| TileDataEnc *tile_data, |
| const int mi_row, const int mi_col, |
| const BLOCK_SIZE bsize, |
| aom_partition_features_t *features) { |
| const AV1_COMMON *const cm = &cpi->common; |
| if (frame_is_intra_only(cm)) return; |
| |
| MACROBLOCK *const x = &td->mb; |
| const BLOCK_SIZE fixed_block_size = BLOCK_16X16; |
| const int col_step = mi_size_wide[fixed_block_size]; |
| const int row_step = mi_size_high[fixed_block_size]; |
| SIMPLE_MOTION_DATA_TREE *sms_tree = NULL; |
| const int stat_generation_stage = is_stat_generation_stage(cpi); |
| const int is_sb_size_128 = cm->seq_params->sb_size == BLOCK_128X128; |
| const int tree_nodes = |
| av1_get_pc_tree_nodes(is_sb_size_128, stat_generation_stage); |
| CHECK_MEM_ERROR(cm, sms_tree, aom_calloc(tree_nodes, sizeof(*sms_tree))); |
| SIMPLE_MOTION_DATA_TREE *sms_root = setup_sms_tree(cpi, sms_tree); |
| TileInfo *const tile_info = &tile_data->tile_info; |
| av1_set_offsets_without_segment_id(cpi, tile_info, x, mi_row, mi_col, bsize); |
| av1_init_simple_motion_search_mvs_for_sb(cpi, NULL, x, sms_root, mi_row, |
| mi_col); |
| av1_reset_simple_motion_tree_partition(sms_root, bsize); |
| const int ref_list[] = { cpi->rc.is_src_frame_alt_ref ? ALTREF_FRAME |
| : LAST_FRAME }; |
| const int mi_width = |
| AOMMIN(mi_size_wide[bsize], cm->mi_params.mi_cols - mi_col); |
| const int mi_height = |
| AOMMIN(mi_size_high[bsize], cm->mi_params.mi_rows - mi_row); |
| const int col_steps = (mi_width / col_step) + ((mi_width % col_step) > 0); |
| const int row_steps = (mi_height / row_step) + ((mi_height % row_step) > 0); |
| const int num_blocks = col_steps * row_steps; |
| unsigned int *block_sse = aom_calloc(num_blocks, sizeof(*block_sse)); |
| unsigned int *block_var = aom_calloc(num_blocks, sizeof(*block_var)); |
| if (!(block_sse && block_var)) { |
| aom_free(sms_tree); |
| aom_free(block_sse); |
| aom_free(block_var); |
| aom_internal_error(cm->error, AOM_CODEC_MEM_ERROR, |
| "Error allocating block_sse & block_var"); |
| } |
| int idx = 0; |
| |
| for (int row = mi_row; |
| row < AOMMIN(mi_row + mi_size_high[bsize], cm->mi_params.mi_rows); |
| row += row_step) { |
| for (int col = mi_col; |
| col < AOMMIN(mi_col + mi_size_wide[bsize], cm->mi_params.mi_cols); |
| col += col_step) { |
| simple_motion_search_get_best_ref( |
| cpi, x, sms_root, row, col, fixed_block_size, ref_list, |
| /*num_refs=*/1, /*use_subpixel=*/1, |
| /*save_mv=*/1, &block_sse[idx], &block_var[idx]); |
| ++idx; |
| } |
| } |
| if (features == NULL) { |
| write_motion_feature_to_file(cpi->oxcf.partition_info_path, cpi->sb_counter, |
| block_sse, block_var, idx, bsize, |
| fixed_block_size, mi_row, mi_col); |
| } else { |
| features->sb_features.motion_features.unit_length = |
| block_size_wide[fixed_block_size]; |
| features->sb_features.motion_features.num_units = idx; |
| for (int i = 0; i < idx; ++i) { |
| features->sb_features.motion_features.block_sse[i] = block_sse[i]; |
| features->sb_features.motion_features.block_var[i] = block_var[i]; |
| } |
| } |
| |
| aom_free(block_sse); |
| aom_free(block_var); |
| aom_free(sms_tree); |
| } |
| |
| void av1_prepare_motion_search_features_block( |
| AV1_COMP *const cpi, ThreadData *td, TileDataEnc *tile_data, |
| const int mi_row, const int mi_col, const BLOCK_SIZE bsize, |
| const int valid_partition_types, unsigned int *block_sse, |
| unsigned int *block_var, unsigned int sub_block_sse[4], |
| unsigned int sub_block_var[4], unsigned int horz_block_sse[2], |
| unsigned int horz_block_var[2], unsigned int vert_block_sse[2], |
| unsigned int vert_block_var[2]) { |
| const AV1_COMMON *const cm = &cpi->common; |
| if (frame_is_intra_only(cm)) return; |
| MACROBLOCK *const x = &td->mb; |
| SIMPLE_MOTION_DATA_TREE *sms_tree = NULL; |
| const int stat_generation_stage = is_stat_generation_stage(cpi); |
| const int is_sb_size_128 = cm->seq_params->sb_size == BLOCK_128X128; |
| const int tree_nodes = |
| av1_get_pc_tree_nodes(is_sb_size_128, stat_generation_stage); |
| CHECK_MEM_ERROR(cm, sms_tree, aom_calloc(tree_nodes, sizeof(*sms_tree))); |
| SIMPLE_MOTION_DATA_TREE *sms_root = setup_sms_tree(cpi, sms_tree); |
| TileInfo *const tile_info = &tile_data->tile_info; |
| av1_set_offsets_without_segment_id(cpi, tile_info, x, mi_row, mi_col, bsize); |
| av1_reset_simple_motion_tree_partition(sms_root, bsize); |
| const int ref_list[] = { cpi->rc.is_src_frame_alt_ref ? ALTREF_FRAME |
| : LAST_FRAME }; |
| const int sub_mi_width = mi_size_wide[bsize] / 2; |
| const int sub_mi_height = sub_mi_width; |
| simple_motion_search_get_best_ref( |
| cpi, x, sms_root, mi_row, mi_col, bsize, ref_list, /*num_refs=*/1, |
| /*use_subpixel=*/1, /*save_mv=*/1, block_sse, block_var); |
| // Split to 4 sub blocks. |
| if (valid_partition_types & (1 << PARTITION_SPLIT)) { |
| const BLOCK_SIZE subsize = get_partition_subsize(bsize, PARTITION_SPLIT); |
| for (int i = 0; i < 4; ++i) { |
| const int row = mi_row + (i >> 1) * sub_mi_height; |
| const int col = mi_col + (i & 1) * sub_mi_width; |
| simple_motion_search_get_best_ref(cpi, x, sms_root, row, col, subsize, |
| ref_list, /*num_refs=*/1, |
| /*use_subpixel=*/1, /*save_mv=*/1, |
| &sub_block_sse[i], &sub_block_var[i]); |
| } |
| } |
| // Horizontal split |
| if (valid_partition_types & (1 << PARTITION_HORZ)) { |
| const BLOCK_SIZE subsize = get_partition_subsize(bsize, PARTITION_HORZ); |
| for (int i = 0; i < 2; ++i) { |
| const int row = mi_row + (i & 1) * sub_mi_height; |
| const int col = mi_col; |
| simple_motion_search_get_best_ref(cpi, x, sms_root, row, col, subsize, |
| ref_list, /*num_refs=*/1, |
| /*use_subpixel=*/1, /*save_mv=*/1, |
| &horz_block_sse[i], &horz_block_var[i]); |
| } |
| } |
| // Vertical split |
| if (valid_partition_types & (1 << PARTITION_VERT)) { |
| const BLOCK_SIZE subsize = get_partition_subsize(bsize, PARTITION_VERT); |
| for (int i = 0; i < 2; ++i) { |
| const int row = mi_row; |
| const int col = mi_col + (i & 1) * sub_mi_width; |
| simple_motion_search_get_best_ref(cpi, x, sms_root, row, col, subsize, |
| ref_list, /*num_refs=*/1, |
| /*use_subpixel=*/1, /*save_mv=*/1, |
| &vert_block_sse[i], &vert_block_var[i]); |
| } |
| } |
| |
| aom_free(sms_tree); |
| } |
| #endif // !CONFIG_REALTIME_ONLY |
| |
| static INLINE void init_simple_motion_search_mvs( |
| SIMPLE_MOTION_DATA_TREE *sms_tree, const FULLPEL_MV *start_mvs) { |
| memcpy(sms_tree->start_mvs, start_mvs, sizeof(sms_tree->start_mvs)); |
| av1_zero(sms_tree->sms_none_feat); |
| |