| /* |
| * Copyright (c) 2021, Alliance for Open Media. All rights reserved |
| * |
| * This source code is subject to the terms of the BSD 3-Clause Clear License |
| * and the Alliance for Open Media Patent License 1.0. If the BSD 3-Clause Clear |
| * License was not distributed with this source code in the LICENSE file, you |
| * can obtain it at aomedia.org/license/software-license/bsd-3-c-c/. 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 |
| * aomedia.org/license/patent-license/. |
| */ |
| |
| #include <float.h> |
| |
| #include "av1/encoder/context_tree.h" |
| #include "av1/encoder/encodeframe_utils.h" |
| #include "config/aom_dsp_rtcd.h" |
| |
| #include "aom_ports/system_state.h" |
| |
| #include "av1/common/enums.h" |
| #include "av1/common/reconinter.h" |
| #include "av1/common/reconintra.h" |
| |
| #include "av1/encoder/cnn.h" |
| #include "av1/encoder/partition_model_weights.h" |
| #include "av1/encoder/partition_cnn_weights.h" |
| #include "av1/encoder/encoder.h" |
| |
| #include "av1/encoder/motion_search_facade.h" |
| #include "av1/encoder/partition_search.h" |
| #include "av1/encoder/rdopt.h" |
| #if CONFIG_EXT_RECUR_PARTITIONS |
| #include "av1/common/idct.h" |
| #include "av1/encoder/hybrid_fwd_txfm.h" |
| #endif // CONFIG_EXT_RECUR_PARTITIONS |
| |
| #if CONFIG_ML_PART_SPLIT |
| #include "av1/encoder/simple_intrapred_tflite.h" |
| #endif // CONFIG_ML_PART_SPLIT |
| |
| 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 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; |
| } |
| } |
| |
| // 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, |
| BLOCK_SIZE bsize, int quad_tree_idx, |
| int *partition_none_allowed, |
| int *partition_horz_allowed, |
| int *partition_vert_allowed, |
| int *do_rectangular_split, |
| int *do_square_split) { |
| assert(cm->sb_size >= BLOCK_64X64 && "Invalid sb_size for intra_cnn!"); |
| 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) { |
| aom_clear_system_state(); |
| 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, cm->seq_params.base_y_dc_delta_q, |
| bit_depth) >> |
| (bit_depth - 8); |
| part_info->log_q = logf(1.0f + (float)((int64_t)dc_q * (int64_t)dc_q) / |
| (256 << (2 * QUANT_TABLE_BITS))); |
| 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; |
| |
| uint16_t *image[1] = { x->plane[AOM_PLANE_Y].src.buf - stride - 1 }; |
| |
| av1_cnn_predict_img_multi_out_highbd(image, width, height, stride, |
| cnn_config, &thread_data, bit_depth, |
| &output); |
| |
| 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]; |
| |
| aom_clear_system_state(); |
| 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); |
| aom_clear_system_state(); |
| |
| 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) { |
| *partition_none_allowed = 0; |
| *partition_horz_allowed = 0; |
| *partition_vert_allowed = 0; |
| *do_rectangular_split = 0; |
| } |
| |
| if (logits[0] < no_split_thresh) { |
| *do_square_split = 0; |
| } |
| } |
| |
| void av1_simple_motion_search_based_split( |
| AV1_COMP *const cpi, MACROBLOCK *x, SIMPLE_MOTION_DATA_TREE *sms_tree, |
| int mi_row, int mi_col, BLOCK_SIZE bsize, int *partition_none_allowed, |
| int *partition_horz_allowed, int *partition_vert_allowed, |
| int *do_rectangular_split, int *do_square_split) { |
| aom_clear_system_state(); |
| (void)partition_horz_allowed; |
| (void)partition_vert_allowed; |
| (void)do_rectangular_split; |
| |
| const AV1_COMMON *const cm = &cpi->common; |
| 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 = cpi->sf.part_sf.simple_motion_search_prune_agg; |
| |
| 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); |
| 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); |
| aom_clear_system_state(); |
| |
| if (score > split_only_thresh) { |
| *partition_none_allowed = 0; |
| #if CONFIG_EXT_RECUR_PARTITIONS |
| (void)partition_horz_allowed; |
| (void)partition_vert_allowed; |
| (void)do_rectangular_split; |
| #else |
| *partition_horz_allowed = 0; |
| *partition_vert_allowed = 0; |
| *do_rectangular_split = 0; |
| #endif // !CONFIG_EXT_RECUR_PARTITIONS |
| } |
| |
| if (cpi->sf.part_sf.simple_motion_search_split >= 2 && |
| score < no_split_thresh) { |
| *do_square_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 (ref == INVALID_IDX) continue; |
| if (cm->ref_frame_flags & (1 << 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->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]; |
| if (sub_tree) { |
| 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]); |
| // Setting up motion search |
| int ref_list[1]; |
| ref_list[0] = get_closest_pastcur_ref_index(&cpi->common); |
| |
| 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; |
| |
| aom_clear_system_state(); |
| 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]); |
| } |
| } |
| aom_clear_system_state(); |
| |
| 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, cpi->common.seq_params.base_y_dc_delta_q, |
| xd->bd) >> |
| (xd->bd - 8); |
| features[f_idx++] = logf(1.0f + (float)((int64_t)dc_q * (int64_t)dc_q) / |
| (256 << (2 * QUANT_TABLE_BITS))); |
| |
| // 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->sb_type[xd->tree_type == CHROMA_PART] : bsize; |
| const BLOCK_SIZE left_bsize = |
| has_left ? xd->left_mbmi->sb_type[xd->tree_type == CHROMA_PART] : 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, |
| int mi_row, int mi_col, BLOCK_SIZE bsize, int partition_horz_allowed, |
| int partition_vert_allowed, bool *prune_horz, bool *prune_vert) { |
| // TODO(urvang): Need to change for uneven 4-way partition support. |
| #if CONFIG_EXT_RECUR_PARTITIONS |
| assert(0 && "Not implemented"); |
| #endif // CONFIG_EXT_RECUR_PARTITIONS |
| aom_clear_system_state(); |
| const AV1_COMMON *const cm = &cpi->common; |
| 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 = cpi->sf.part_sf.simple_motion_search_prune_agg; |
| 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); |
| 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); |
| aom_clear_system_state(); |
| |
| av1_nn_softmax(scores, probs, num_classes); |
| |
| // Determine if we should prune rectangular partitions. |
| if (cpi->sf.part_sf.simple_motion_search_prune_rect && |
| !frame_is_intra_only(cm) && |
| (partition_horz_allowed || partition_vert_allowed) && |
| bsize >= BLOCK_8X8 && !av1_superres_scaled(cm)) { |
| *prune_horz = probs[PARTITION_HORZ] <= prune_thresh; |
| *prune_vert = probs[PARTITION_VERT] <= prune_thresh; |
| } |
| } |
| |
| // 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, |
| int mi_row, int mi_col, BLOCK_SIZE bsize, const RD_STATS *none_rdc, |
| int *early_terminate) { |
| // TODO(chiyotsai@google.com): There are other features we can extract from |
| // PARTITION_NONE. Play with this later. |
| 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; |
| #if CONFIG_BLOCK_256 |
| } else if (bsize == BLOCK_256X256) { |
| return; |
| #endif // CONFIG_BLOCK_256 |
| } else { |
| assert(0 && "Unexpected block size in simple_motion_term_none"); |
| } |
| |
| 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) { |
| *early_terminate = 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->sb_size; |
| |
| assert(sb_size == BLOCK_128X128); |
| |
| int f_idx = 0; |
| const int dc_q = av1_dc_quant_QTX(x->qindex, 0, |
| cm->seq_params.base_y_dc_delta_q, xd->bd) >> |
| (xd->bd - 8); |
| aom_clear_system_state(); |
| const float log_q_sq = logf(1.0f + (float)((int64_t)dc_q * (int64_t)dc_q) / |
| (256 << (2 * QUANT_TABLE_BITS))); |
| |
| // 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); |
| |
| aom_clear_system_state(); |
| 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; |
| } |
| aom_clear_system_state(); |
| const float avg_mv_row = sum_mv_row / 64.0f; |
| const float var_mv_row = sum_mv_row_sq / 64.0f - avg_mv_row * avg_mv_row; |
| |
| const float avg_mv_col = sum_mv_col / 64.0f; |
| const float var_mv_col = sum_mv_col_sq / 64.0f - avg_mv_col * avg_mv_col; |
| |
| const float avg_log_sse = sum_log_sse / 64.0f; |
| const float var_log_sse = sum_log_sse_sq / 64.0f - 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); |
| } |
| |
| 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 }, |
| probs[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); |
| |
| aom_clear_system_state(); |
| av1_nn_predict(features, nn_config, 1, scores); |
| av1_nn_softmax(scores, probs, MAX_NUM_CLASSES_MAX_MIN_PART_PRED); |
| |
| 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_prob = probs[0]; |
| for (int i = 1; i < MAX_NUM_CLASSES_MAX_MIN_PART_PRED; ++i) { |
| if (probs[i] > max_prob) { |
| max_prob = probs[i]; |
| result = i; |
| } |
| } |
| } else 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.sb_size; |
| const MACROBLOCKD *const xd = &x->e_mbd; |
| // 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_high_get_sby_perpixel_variance( |
| cpi, &x->plane[0].src, sb_size, xd->bd); |
| 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 (BLOCK_SIZE)((result + 2) * 3); |
| } |
| |
| // 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 !CONFIG_EXT_RECUR_PARTITIONS |
| 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; |
| #endif // !CONFIG_EXT_RECUR_PARTITIONS |
| 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, |
| BLOCK_SIZE bsize, int64_t best_rd, |
| int64_t part_none_rd, int64_t part_split_rd, |
| int64_t *split_block_rd, int mi_row, |
| int mi_col, |
| int *const terminate_partition_search) { |
| if (best_rd <= 0 || best_rd == INT64_MAX || *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, |
| cm->seq_params.base_y_dc_delta_q, xd->bd) >> |
| (xd->bd - 8); |
| const int bs = block_size_wide[bsize]; |
| int f_idx = 0; |
| float features[FEATURES] = { 0.0f }; |
| |
| aom_clear_system_state(); |
| features[f_idx++] = logf(1.0f + (float)dc_q / (4 << QUANT_TABLE_BITS)); |
| 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); |
| |
| 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) *terminate_partition_search = 1; |
| } |
| #undef FEATURES |
| |
| void av1_ml_prune_rect_partition(const AV1_COMP *const cpi, |
| const MACROBLOCK *const x, BLOCK_SIZE bsize, |
| int64_t best_rd, int64_t none_rd, |
| int64_t *split_rd, bool *const dst_prune_horz, |
| bool *const dst_prune_vert) { |
| 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; |
| aom_clear_system_state(); |
| |
| // 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_high_get_sby_perpixel_variance(cpi, &x->plane[0].src, bsize, xd->bd); |
| 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_high_get_sby_perpixel_variance(cpi, &buf, subsize, xd->bd); |
| } |
| |
| for (int i = 0; i < SUB_PARTITIONS_SPLIT; i++) |
| features[5 + i] = (float)split_variance[i] / (float)whole_block_variance; |
| |
| // 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); |
| aom_clear_system_state(); |
| 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) (*dst_prune_horz) = 1; |
| if (probs[2] <= cur_thresh) (*dst_prune_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( |
| BLOCK_SIZE bsize, int part_ctx, int var_ctx, int64_t best_rd, |
| int64_t horz_rd[SUB_PARTITIONS_RECT], int64_t vert_rd[SUB_PARTITIONS_RECT], |
| int64_t split_rd[SUB_PARTITIONS_SPLIT], int *const horza_partition_allowed, |
| int *const horzb_partition_allowed, int *const verta_partition_allowed, |
| int *const vertb_partition_allowed) { |
| 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; |
| |
| aom_clear_system_state(); |
| |
| // 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) { |
| 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; |
| } |
| assert(feature_index == 10); |
| |
| // Calculate scores using the NN model. |
| float score[16] = { 0.0f }; |
| av1_nn_predict(features, nn_config, 1, score); |
| aom_clear_system_state(); |
| 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; |
| } |
| *horza_partition_allowed = 0; |
| *horzb_partition_allowed = 0; |
| *verta_partition_allowed = 0; |
| *vertb_partition_allowed = 0; |
| for (int i = 0; i < 16; ++i) { |
| if (int_score[i] >= thresh) { |
| if ((i >> 0) & 1) *horza_partition_allowed = 1; |
| if ((i >> 1) & 1) *horzb_partition_allowed = 1; |
| if ((i >> 2) & 1) *verta_partition_allowed = 1; |
| if ((i >> 3) & 1) *vertb_partition_allowed = 1; |
| } |
| } |
| } |
| |
| #if !CONFIG_EXT_RECUR_PARTITIONS |
| #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( |
| 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], int *const partition_horz4_allowed, |
| int *const partition_vert4_allowed, unsigned int pb_source_variance, |
| int mi_row, int mi_col) { |
| if (best_rd >= 1000000000) return; |
| int64_t *horz_rd = rect_part_rd[HORZ]; |
| int64_t *vert_rd = rect_part_rd[VERT]; |
| 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; |
| |
| aom_clear_system_state(); |
| |
| // 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 }; |
| { |
| #if CONFIG_EXT_RECUR_PARTITIONS |
| BLOCK_SIZE horz_4_bs = get_partition_subsize(bsize, PARTITION_HORZ_3); |
| BLOCK_SIZE vert_4_bs = get_partition_subsize(bsize, PARTITION_VERT_3); |
| #else // CONFIG_EXT_RECUR_PARTITIONS |
| BLOCK_SIZE horz_4_bs = get_partition_subsize(bsize, PARTITION_HORZ_4); |
| BLOCK_SIZE vert_4_bs = get_partition_subsize(bsize, PARTITION_VERT_4); |
| #endif // CONFIG_EXT_RECUR_PARTITIONS |
| av1_setup_src_planes(x, cpi->source, mi_row, mi_col, |
| av1_num_planes(&cpi->common), NULL); |
| const int src_stride = x->plane[0].src.stride; |
| uint16_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_high_get_sby_perpixel_variance( |
| cpi, &horz_4_src, horz_4_bs, xd->bd); |
| vert_4_source_var[i] = av1_high_get_sby_perpixel_variance( |
| cpi, &vert_4_src, vert_4_bs, xd->bd); |
| } |
| } |
| |
| 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); |
| |
| // Calculate scores using the NN model. |
| float score[LABELS] = { 0.0f }; |
| av1_nn_predict(features, nn_config, 1, score); |
| aom_clear_system_state(); |
| 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; |
| } |
| *partition_horz4_allowed = 0; |
| *partition_vert4_allowed = 0; |
| for (int i = 0; i < LABELS; ++i) { |
| if (int_score[i] >= thresh) { |
| if ((i >> 0) & 1) *partition_horz4_allowed = 1; |
| if ((i >> 1) & 1) *partition_vert4_allowed = 1; |
| } |
| } |
| } |
| #undef FEATURES |
| #undef LABELS |
| |
| #endif // !CONFIG_EXT_RECUR_PARTITIONS |
| |
| #define FEATURES 4 |
| int av1_ml_predict_breakout(const AV1_COMP *const cpi, BLOCK_SIZE bsize, |
| const MACROBLOCK *const x, |
| const RD_STATS *const rd_stats, |
| unsigned int pb_source_variance) { |
| 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; |
| #if CONFIG_BLOCK_256 |
| case BLOCK_256X256: return 0; break; |
| #endif // CONFIG_BLOCK_256 |
| default: assert(0 && "Unexpected bsize."); |
| } |
| if (!nn_config || thresh < 0) return 0; |
| |
| // Generate feature values. |
| float features[FEATURES]; |
| int feature_index = 0; |
| aom_clear_system_state(); |
| |
| 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]; |
| features[feature_index++] = |
| ((float)dc_q * (float)dc_q) / (256 << (2 * QUANT_TABLE_BITS)); |
| |
| assert(feature_index == FEATURES); |
| |
| // Calculate score using the NN model. |
| float score = 0.0f; |
| av1_nn_predict(features, nn_config, 1, &score); |
| aom_clear_system_state(); |
| |
| // Make decision. |
| return (int)(score * 100) >= thresh; |
| } |
| #undef FEATURES |
| |
| void av1_prune_partitions_before_search( |
| AV1_COMP *const cpi, MACROBLOCK *const x, int mi_row, int mi_col, |
| BLOCK_SIZE bsize, SIMPLE_MOTION_DATA_TREE *const sms_tree, |
| int *partition_none_allowed, int *partition_horz_allowed, |
| int *partition_vert_allowed, int *do_rectangular_split, |
| int *do_square_split, bool *prune_horz, bool *prune_vert, |
| const PC_TREE *pc_tree) { |
| #if !CONFIG_EXT_RECUR_PARTITIONS |
| (void)pc_tree; |
| #endif // !CONFIG_EXT_RECUR_PARTITIONS |
| const AV1_COMMON *const cm = &cpi->common; |
| const CommonModeInfoParams *const mi_params = &cm->mi_params; |
| MACROBLOCKD *const xd = &x->e_mbd; |
| |
| // A CNN-based speed feature pruning out either split or all non-split |
| // partition in INTRA frame coding. |
| const int try_intra_cnn_split = |
| !cpi->is_screen_content_type && frame_is_intra_only(cm) && |
| cpi->sf.part_sf.intra_cnn_split && xd->tree_type != CHROMA_PART && |
| cm->sb_size >= BLOCK_64X64 && bsize <= BLOCK_64X64 && |
| bsize >= BLOCK_8X8 && |
| mi_row + mi_size_high[bsize] <= mi_params->mi_rows && |
| mi_col + mi_size_wide[bsize] <= mi_params->mi_cols; |
| |
| if (try_intra_cnn_split) { |
| av1_intra_mode_cnn_partition( |
| &cpi->common, x, bsize, x->part_search_info.quad_tree_idx, |
| partition_none_allowed, partition_horz_allowed, partition_vert_allowed, |
| do_rectangular_split, do_square_split); |
| } |
| |
| // 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->is_screen_content_type && |
| cpi->sf.part_sf.simple_motion_search_split && *do_square_split && |
| bsize >= BLOCK_8X8 && |
| mi_row + mi_size_high[bsize] <= mi_params->mi_rows && |
| mi_col + mi_size_wide[bsize] <= mi_params->mi_cols && |
| !frame_is_intra_only(cm) && !av1_superres_scaled(cm) && |
| is_square_block(bsize) && sms_tree && *partition_none_allowed; |
| |
| if (try_split_only) { |
| av1_simple_motion_search_based_split( |
| cpi, x, sms_tree, mi_row, mi_col, bsize, partition_none_allowed, |
| partition_horz_allowed, partition_vert_allowed, do_rectangular_split, |
| do_square_split); |
| #if CONFIG_EXT_RECUR_PARTITIONS |
| if (!*partition_none_allowed) { |
| av1_cache_best_partition(x->sms_bufs, mi_row, mi_col, bsize, cm->sb_size, |
| PARTITION_HORZ); |
| const int mi_step = block_size_high[bsize] / 2; |
| BLOCK_SIZE subsize = get_partition_subsize(bsize, PARTITION_HORZ); |
| av1_cache_best_partition(x->sms_bufs, mi_row, mi_col, subsize, |
| cm->sb_size, PARTITION_VERT); |
| av1_cache_best_partition(x->sms_bufs, mi_row + mi_step, mi_col, subsize, |
| cm->sb_size, PARTITION_VERT); |
| } |
| (void)pc_tree; |
| #endif // CONFIG_EXT_RECUR_PARTITIONS |
| } |
| |
| // 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. |
| const int try_prune_rect = |
| !cpi->is_screen_content_type && |
| cpi->sf.part_sf.simple_motion_search_prune_rect && |
| !frame_is_intra_only(cm) && *do_rectangular_split && |
| (*do_square_split || *partition_none_allowed || |
| (*prune_horz && *prune_vert)) && |
| (*partition_horz_allowed || *partition_vert_allowed) && |
| bsize >= BLOCK_8X8; |
| |
| if (try_prune_rect) { |
| av1_simple_motion_search_prune_rect( |
| cpi, x, sms_tree, mi_row, mi_col, bsize, *partition_horz_allowed, |
| *partition_vert_allowed, prune_horz, prune_vert); |
| } |
| } |
| |
| void av1_prune_partitions_by_max_min_bsize( |
| SuperBlockEnc *sb_enc, BLOCK_SIZE bsize, int is_not_edge_block, |
| int *partition_none_allowed, int *partition_horz_allowed, |
| int *partition_vert_allowed, int *do_square_split) { |
| 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); |
| #if !CONFIG_EXT_RECUR_PARTITIONS |
| assert(is_bsize_square(bsize)); |
| #endif // !CONFIG_EXT_RECUR_PARTITIONS |
| const int max_partition_size_1d = block_size_wide[sb_enc->max_partition_size]; |
| |
| #if CONFIG_EXT_RECUR_PARTITIONS |
| assert(is_bsize_geq(sb_enc->max_partition_size, sb_enc->min_partition_size)); |
| const int block_height = block_size_high[bsize]; |
| const int block_width = block_size_wide[bsize]; |
| const int is_le_min_sq_part = is_bsize_geq(sb_enc->min_partition_size, bsize); |
| const int is_gt_max_sq_part = (block_height > max_partition_size_1d) || |
| (block_width > max_partition_size_1d); |
| #else // CONFIG_EXT_RECUR_PARTITIONS |
| const int min_partition_size_1d = block_size_wide[sb_enc->min_partition_size]; |
| const int bsize_1d = block_size_wide[bsize]; |
| 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; |
| assert(min_partition_size_1d <= max_partition_size_1d); |
| #endif // CONFIG_EXT_RECUR_PARTITIONS |
| |
| #if CONFIG_EXT_RECUR_PARTITIONS |
| (void)do_square_split; |
| (void)is_not_edge_block; |
| #endif |
| if (is_gt_max_sq_part) { |
| // If current block size is larger than max, only allow split. |
| *partition_none_allowed = 0; |
| #if CONFIG_EXT_RECUR_PARTITIONS |
| *partition_horz_allowed = 1; |
| *partition_vert_allowed = 1; |
| #else // CONFIG_EXT_RECUR_PARTITIONS |
| *partition_horz_allowed = 0; |
| *partition_vert_allowed = 0; |
| *do_square_split = 1; |
| #endif // CONFIG_EXT_RECUR_PARTITIONS |
| } 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. |
| *partition_horz_allowed = 0; |
| *partition_vert_allowed = 0; |
| // only disable square split when current block is not at the picture |
| // boundary. otherwise, inherit the square split flag from previous logic |
| #if CONFIG_EXT_RECUR_PARTITIONS |
| *partition_none_allowed = 1; |
| #else // CONFIG_EXT_RECUR_PARTITIONS |
| if (is_not_edge_block) *do_square_split = 0; |
| *partition_none_allowed = !(*do_square_split); |
| #endif // CONFIG_EXT_RECUR_PARTITIONS |
| } |
| } |
| |
| // 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 CONFIG_EXTENDED_SDP |
| REGION_TYPE cur_region_type = pc_tree->region_type; |
| if (pc_tree->split[cur_region_type][split_idx1]) { |
| num_win += (pc_tree->split[cur_region_type][split_idx1]->partitioning == |
| PARTITION_NONE); |
| } else { |
| num_win += 1; |
| } |
| if (pc_tree->split[cur_region_type][split_idx2]) { |
| num_win += (pc_tree->split[cur_region_type][split_idx2]->partitioning == |
| PARTITION_NONE); |
| #else |
| 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; |
| #endif // CONFIG_EXTENDED_SDP |
| } else { |
| num_win += 1; |
| } |
| if (num_win < num_win_thresh) { |
| return 0; |
| } |
| return 1; |
| } |
| |
| void av1_prune_ab_partitions( |
| const AV1_COMP *cpi, const MACROBLOCK *x, const PC_TREE *pc_tree, |
| BLOCK_SIZE bsize, int pb_source_variance, int64_t best_rdcost, |
| int64_t rect_part_rd[NUM_RECT_PARTS][SUB_PARTITIONS_RECT], |
| int64_t split_rd[SUB_PARTITIONS_SPLIT], |
| const RD_RECT_PART_WIN_INFO *rect_part_win_info, int ext_partition_allowed, |
| int partition_horz_allowed, int partition_vert_allowed, |
| int *horza_partition_allowed, int *horzb_partition_allowed, |
| int *verta_partition_allowed, int *vertb_partition_allowed) { |
| int64_t *horz_rd = rect_part_rd[HORZ]; |
| int64_t *vert_rd = rect_part_rd[VERT]; |
| const PartitionCfg *const part_cfg = &cpi->oxcf.part_cfg; |
| // The standard AB partitions are allowed initially if ext-partition-types are |
| // allowed. |
| const MACROBLOCKD *xd = &x->e_mbd; |
| int horzab_partition_allowed = |
| ext_partition_allowed & part_cfg->enable_ab_partitions && |
| (xd->tree_type != CHROMA_PART || bsize > BLOCK_8X8); |
| int vertab_partition_allowed = |
| ext_partition_allowed & part_cfg->enable_ab_partitions && |
| (xd->tree_type != CHROMA_PART || bsize > BLOCK_8X8); |
| |
| // 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. |
| *horza_partition_allowed = horzab_partition_allowed; |
| *horzb_partition_allowed = 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: |
| *horza_partition_allowed &= (horz_a_rd / 16 * 14 < best_rdcost); |
| *horzb_partition_allowed &= (horz_b_rd / 16 * 14 < best_rdcost); |
| break; |
| case 2: |
| default: |
| *horza_partition_allowed &= (horz_a_rd / 16 * 15 < best_rdcost); |
| *horzb_partition_allowed &= (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. |
| *verta_partition_allowed = vertab_partition_allowed; |
| *vertb_partition_allowed = 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: |
| *verta_partition_allowed &= (vert_a_rd / 16 * 14 < best_rdcost); |
| *vertb_partition_allowed &= (vert_b_rd / 16 * 14 < best_rdcost); |
| break; |
| case 2: |
| default: |
| *verta_partition_allowed &= (vert_a_rd / 16 * 15 < best_rdcost); |
| *vertb_partition_allowed &= (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_ab_partition && ext_partition_allowed && |
| partition_horz_allowed && partition_vert_allowed) { |
| // 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(bsize, pc_tree->partitioning, |
| get_unsigned_bits(x->source_variance), |
| best_rdcost, horz_rd, vert_rd, split_rd, |
| horza_partition_allowed, horzb_partition_allowed, |
| verta_partition_allowed, vertb_partition_allowed); |
| } |
| |
| // Disable ab partitions if they are disabled by the encoder parameter. |
| *horza_partition_allowed &= part_cfg->enable_ab_partitions; |
| *horzb_partition_allowed &= part_cfg->enable_ab_partitions; |
| *verta_partition_allowed &= part_cfg->enable_ab_partitions; |
| *vertb_partition_allowed &= part_cfg->enable_ab_partitions; |
| |
| // 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_ab_partition_using_split_info && |
| *horza_partition_allowed) { |
| *horza_partition_allowed &= evaluate_ab_partition_based_on_split( |
| pc_tree, PARTITION_HORZ, rect_part_win_info, x->qindex, 0, 1); |
| } |
| if (cpi->sf.part_sf.prune_ab_partition_using_split_info && |
| *horzb_partition_allowed) { |
| *horzb_partition_allowed &= evaluate_ab_partition_based_on_split( |
| pc_tree, PARTITION_HORZ, rect_part_win_info, x->qindex, 2, 3); |
| } |
| if (cpi->sf.part_sf.prune_ab_partition_using_split_info && |
| *verta_partition_allowed) { |
| *verta_partition_allowed &= evaluate_ab_partition_based_on_split( |
| pc_tree, PARTITION_VERT, rect_part_win_info, x->qindex, 0, 2); |
| } |
| if (cpi->sf.part_sf.prune_ab_partition_using_split_info && |
| *vertb_partition_allowed) { |
| *vertb_partition_allowed &= evaluate_ab_partition_based_on_split( |
| pc_tree, PARTITION_VERT, rect_part_win_info, x->qindex, 1, 3); |
| } |
| } |
| |
| #if CONFIG_EXT_RECUR_PARTITIONS |
| // Gets the number of sms data in a single dimension |
| static INLINE int get_sms_count_from_length(int mi_length) { |
| switch (mi_length) { |
| #if CONFIG_BLOCK_256 |
| case 64: return BLOCK_256_COUNT; |
| #endif // CONFIG_BLOCK_256 |
| case 32: return BLOCK_128_COUNT; |
| case 16: return BLOCK_64_COUNT; |
| case 8: return BLOCK_32_COUNT; |
| case 4: return BLOCK_16_COUNT; |
| case 2: return BLOCK_8_COUNT; |
| case 1: return BLOCK_4_COUNT; |
| default: assert(0 && "Invalid mi_width"); return -1; |
| } |
| } |
| |
| // Gets the linear index corresponds to the current block. |
| |
| static INLINE int get_sms_arr_1d_idx(int mi_bsize, int mi_in_sb) { |
| int idx = -1; |
| if (mi_bsize <= 2) { |
| idx = mi_in_sb; |
| } else if (mi_bsize <= 8) { |
| assert(mi_in_sb % (mi_bsize / 4) == 0); |
| idx = mi_in_sb / (mi_bsize / 4); |
| } else { |
| assert(mi_in_sb % (mi_bsize / 2) == 0); |
| idx = mi_in_sb / (mi_bsize / 2); |
| } |
| assert(idx >= 0 && idx < get_sms_count_from_length(mi_bsize)); |
| |
| return idx; |
| } |
| |
| #define MAKE_SMS_ARR_SWITCH_CASE(width, height) \ |
| case BLOCK_##width##X##height: { \ |
| return sms_bufs->b_##width##x##height; \ |
| } |
| |
| // Returns the buffer in SimpleMotionDataBufs that correspond to bsize. |
| static INLINE SimpleMotionData *get_sms_arr(SimpleMotionDataBufs *sms_bufs, |
| BLOCK_SIZE bsize) { |
| switch (bsize) { |
| // Square blocks |
| #if CONFIG_BLOCK_256 |
| MAKE_SMS_ARR_SWITCH_CASE(256, 256); |
| #endif // CONFIG_BLOCK_256 |
| MAKE_SMS_ARR_SWITCH_CASE(128, 128); |
| MAKE_SMS_ARR_SWITCH_CASE(64, 64); |
| MAKE_SMS_ARR_SWITCH_CASE(32, 32); |
| MAKE_SMS_ARR_SWITCH_CASE(16, 16); |
| MAKE_SMS_ARR_SWITCH_CASE(8, 8); |
| MAKE_SMS_ARR_SWITCH_CASE(4, 4); |
| |
| // 1:2 blocks |
| #if CONFIG_BLOCK_256 |
| MAKE_SMS_ARR_SWITCH_CASE(128, 256); |
| #endif // CONFIG_BLOCK_256 |
| MAKE_SMS_ARR_SWITCH_CASE(64, 128); |
| MAKE_SMS_ARR_SWITCH_CASE(32, 64); |
| MAKE_SMS_ARR_SWITCH_CASE(16, 32); |
| MAKE_SMS_ARR_SWITCH_CASE(8, 16); |
| MAKE_SMS_ARR_SWITCH_CASE(4, 8); |
| |
| // 2:1 blocks |
| #if CONFIG_BLOCK_256 |
| MAKE_SMS_ARR_SWITCH_CASE(256, 128); |
| #endif // CONFIG_BLOCK_256 |
| MAKE_SMS_ARR_SWITCH_CASE(128, 64); |
| MAKE_SMS_ARR_SWITCH_CASE(64, 32); |
| MAKE_SMS_ARR_SWITCH_CASE(32, 16); |
| MAKE_SMS_ARR_SWITCH_CASE(16, 8); |
| MAKE_SMS_ARR_SWITCH_CASE(8, 4); |
| |
| // 1:4 blocks |
| MAKE_SMS_ARR_SWITCH_CASE(16, 64); |
| MAKE_SMS_ARR_SWITCH_CASE(8, 32); |
| MAKE_SMS_ARR_SWITCH_CASE(4, 16); |
| |
| // 4:1 blocks |
| MAKE_SMS_ARR_SWITCH_CASE(64, 16); |
| MAKE_SMS_ARR_SWITCH_CASE(32, 8); |
| MAKE_SMS_ARR_SWITCH_CASE(16, 4); |
| |
| #if CONFIG_FLEX_PARTITION |
| // 1:8 blocks |
| MAKE_SMS_ARR_SWITCH_CASE(8, 64); |
| MAKE_SMS_ARR_SWITCH_CASE(4, 32); |
| |
| // 8:1 blocks |
| MAKE_SMS_ARR_SWITCH_CASE(64, 8); |
| MAKE_SMS_ARR_SWITCH_CASE(32, 4); |
| |
| // 16:1 blocks |
| MAKE_SMS_ARR_SWITCH_CASE(64, 4); |
| |
| // 1:16 blocks |
| MAKE_SMS_ARR_SWITCH_CASE(4, 64); |
| #endif // CONFIG_FLEX_PARTITION |
| |
| default: assert(0 && "Invalid bsize"); return NULL; |
| } |
| } |
| #undef MAKE_SMS_ARR_SWITCH_CASE |
| |
| void av1_reset_prev_partition(SimpleMotionDataBufs *sms_bufs) { |
| for (BLOCK_SIZE bsize = BLOCK_4X4; bsize < BLOCK_SIZES_ALL; bsize++) { |
| SimpleMotionData *sms_arr = get_sms_arr(sms_bufs, bsize); |
| const int mi_wide = mi_size_wide[bsize]; |
| const int mi_high = mi_size_high[bsize]; |
| const int sms_wide = get_sms_count_from_length(mi_wide); |
| const int sms_high = get_sms_count_from_length(mi_high); |
| const int sms_count = sms_wide * sms_high; |
| for (int idx = 0; idx < sms_count; idx++) { |
| sms_arr[idx].has_prev_partition = false; |
| } |
| } |
| } |
| // Retrieves the SimpleMotionData from SimpleMotionDataBufs |
| SimpleMotionData *av1_get_sms_data_entry(SimpleMotionDataBufs *sms_bufs, |
| int mi_row, int mi_col, |
| BLOCK_SIZE bsize, BLOCK_SIZE sb_size) { |
| assert(mi_size_high[sb_size] == mi_size_wide[sb_size]); |
| assert(bsize < BLOCK_SIZES_ALL); |
| const int mi_in_sb = mi_size_high[sb_size]; |
| const int mi_row_in_sb = mi_row % mi_in_sb; |
| const int mi_col_in_sb = mi_col % mi_in_sb; |
| const int mi_high = mi_size_high[bsize]; |
| const int mi_wide = mi_size_wide[bsize]; |
| const int idx_row_in_sb = get_sms_arr_1d_idx(mi_high, mi_row_in_sb); |
| const int idx_col_in_sb = get_sms_arr_1d_idx(mi_wide, mi_col_in_sb); |
| const int arr_stride = get_sms_count_from_length(mi_wide); |
| SimpleMotionData *sms_arr = get_sms_arr(sms_bufs, bsize); |
| return &sms_arr[idx_row_in_sb * arr_stride + idx_col_in_sb]; |
| } |
| |
| void av1_cache_best_partition(SimpleMotionDataBufs *sms_bufs, int mi_row, |
| int mi_col, BLOCK_SIZE bsize, BLOCK_SIZE sb_size, |
| PARTITION_TYPE partition) { |
| SimpleMotionData *cur_block = |
| av1_get_sms_data_entry(sms_bufs, mi_row, mi_col, bsize, sb_size); |
| cur_block->has_prev_partition = 1; |
| cur_block->prev_partition = partition; |
| } |
| |
| // Performs a simple motion search and store the result in sms_data. |
| static void compute_sms_data(AV1_COMP *const cpi, const TileInfo *const tile, |
| MACROBLOCK *x, SimpleMotionData *sms_data, |
| int mi_row, int mi_col, BLOCK_SIZE bsize) { |
| const AV1_COMMON *const cm = &cpi->common; |
| const int ref_frame = get_closest_pastcur_ref_index(cm); |
| assert(ref_frame >= 0); |
| 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. |
| sms_data->sse = 0; |
| sms_data->var = 0; |
| sms_data->dist = 0; |
| sms_data->rate = 0; |
| sms_data->rdcost = 0; |
| sms_data->valid = 1; |
| return; |
| } |
| av1_set_offsets(cpi, tile, x, mi_row, mi_col, bsize, NULL); |
| // We need to update the rd-mult here to in case we are doing simple motion |
| // search on a subblock of the current coding block. |
| const int orig_rdmult = x->rdmult; |
| const AQ_MODE aq_mode = cpi->oxcf.q_cfg.aq_mode; |
| MB_MODE_INFO *mbmi = x->e_mbd.mi[0]; |
| setup_block_rdmult(cpi, x, mi_row, mi_col, bsize, aq_mode, mbmi); |
| // Set error per bit for current rdmult |
| av1_set_error_per_bit(&x->mv_costs, x->rdmult); |
| if (cm->ref_frame_flags & (1 << ref_frame)) { |
| const MACROBLOCKD *xd = &x->e_mbd; |
| const uint16_t *src_buf = x->plane[0].src.buf; |
| const uint16_t *dst_buf = xd->plane[0].dst.buf; |
| const int src_stride = x->plane[0].src.stride; |
| const int dst_stride = xd->plane[0].dst.stride; |
| if (sms_data->num_start_mvs == 0) { |
| sms_data->start_mv_list[sms_data->num_start_mvs++] = kZeroMv; |
| } |
| sms_data->rdcost = INT64_MAX; |
| SimpleMotionData best_data = *sms_data; |
| for (int idx = 0; idx < sms_data->num_start_mvs; idx++) { |
| const MV start_mv = sms_data->start_mv_list[idx]; |
| const FULLPEL_MV start_mv_full = get_fullmv_from_mv(&start_mv); |
| av1_simple_motion_search_ext(cpi, tile, x, mi_row, mi_col, bsize, |
| ref_frame, start_mv_full, 1, 1, sms_data); |
| sms_data->var = cpi->fn_ptr[bsize].vf(src_buf, src_stride, dst_buf, |
| dst_stride, &sms_data->sse); |
| sms_data->dist = 16 * sms_data->sse; |
| sms_data->rate = 0; |
| sms_data->rdcost = RDCOST(x->rdmult, sms_data->rate, sms_data->dist); |
| if (sms_data->rdcost <= best_data.rdcost) { |
| best_data = *sms_data; |
| } |
| } |
| *sms_data = best_data; |
| } |
| sms_data->valid = 1; |
| sms_data->bsize = bsize; |
| sms_data->mi_row = mi_row; |
| sms_data->mi_col = mi_col; |
| x->rdmult = orig_rdmult; |
| return; |
| } |
| |
| static INLINE void add_start_mv_to_block(SimpleMotionData *block, MV start_mv) { |
| if (block->num_start_mvs == kSMSMaxStartMVs) { |
| return; |
| } |
| for (int idx = 0; idx < block->num_start_mvs; idx++) { |
| const int_mv *cur_mv = (int_mv *)&block->start_mv_list[idx]; |
| if (((int_mv *)&start_mv)->as_int == cur_mv->as_int) { |
| return; |
| } |
| } |
| block->start_mv_list[block->num_start_mvs++] = start_mv; |
| } |
| |
| static INLINE void add_start_mv_to_partition( |
| SimpleMotionDataBufs *sms_bufs, int mi_row, int mi_col, BLOCK_SIZE bsize, |
| BLOCK_SIZE sb_size, PARTITION_TYPE partition, MV start_mv) { |
| assert(bsize < BLOCK_SIZES_ALL); |
| const int eighth_step_h = block_size_high[bsize] / 8; |
| const int eighth_step_w = block_size_wide[bsize] / 8; |
| static const int subblock_count[ALL_PARTITION_TYPES] = { |
| 1, // PARTITION_NONE |
| 2, // PARTITION_HORZ |
| 2, // PARTITION_VERT |
| 4, // PARTITION_HORZ_3 |
| 4, // PARTITION_VERT_3 |
| 4, // PARTITION_HORZ_4A |
| 4, // PARTITION_HORZ_4B |
| 4, // PARTITION_VERT_4A |
| 4, // PARTITION_VERT_4B |
| 4, // PARTITION_SPLIT |
| }; |
| // PARTITION x NUM_SUBBLOCKS x (ROW and COL) |
| static const int step_multiplier[ALL_PARTITION_TYPES][4][2] = { |
| { { 0, 0 }, { 0, 0 }, { 0, 0 }, { 0, 0 } }, // PARTITION_NONE |
| { { 0, 0 }, { 4, 0 }, { 0, 0 }, { 0, 0 } }, // PARTITION_HORZ |
| { { 0, 0 }, { 0, 4 }, { 0, 0 }, { 0, 0 } }, // PARTITION_VERT |
| { { 0, 0 }, { 2, 0 }, { 2, 4 }, { 6, 0 } }, // PARTITION_HORZ_3 |
| { { 0, 0 }, { 0, 2 }, { 4, 2 }, { 0, 6 } }, // PARTITION_VERT_3 |
| { { 0, 0 }, { 1, 0 }, { 3, 0 }, { 7, 0 } }, // PARTITION_HORZ_4A |
| { { 0, 0 }, { 1, 0 }, { 5, 0 }, { 7, 0 } }, // PARTITION_HORZ_4B |
| { { 0, 0 }, { 0, 1 }, { 0, 3 }, { 0, 7 } }, // PARTITION_VERT_4A |
| { { 0, 0 }, { 0, 1 }, { 0, 5 }, { 0, 7 } }, // PARTITION_VERT_4B |
| { { 0, 0 }, { 0, 4 }, { 4, 0 }, { 4, 4 } }, // PARTITION_SPLIT |
| }; |
| |
| // Sizes of subblocks. |
| const BLOCK_SIZE part_subsize = get_partition_subsize(bsize, partition); |
| if (part_subsize == BLOCK_INVALID) return; |
| |
| BLOCK_SIZE subsizes[4] = { part_subsize, part_subsize, part_subsize, |
| part_subsize }; |
| if (partition == PARTITION_HORZ_4A) { |
| subsizes[2] = get_partition_subsize(bsize, PARTITION_HORZ); |
| subsizes[1] = get_partition_subsize(subsizes[2], PARTITION_HORZ); |
| } else if (partition == PARTITION_HORZ_4B) { |
| subsizes[1] = get_partition_subsize(bsize, PARTITION_HORZ); |
| subsizes[2] = get_partition_subsize(subsizes[1], PARTITION_HORZ); |
| } else if (partition == PARTITION_VERT_4A) { |
| subsizes[2] = get_partition_subsize(bsize, PARTITION_VERT); |
| subsizes[1] = get_partition_subsize(subsizes[2], PARTITION_VERT); |
| } else if (partition == PARTITION_VERT_4B) { |
| subsizes[1] = get_partition_subsize(bsize, PARTITION_VERT); |
| subsizes[2] = get_partition_subsize(subsizes[1], PARTITION_VERT); |
| } |
| if (partition == PARTITION_HORZ_3) { |
| subsizes[1] = get_h_partition_subsize(sb_size, 1, PARTITION_HORZ_3); |
| subsizes[2] = get_h_partition_subsize(sb_size, 2, PARTITION_HORZ_3); |
| } else if (partition == PARTITION_VERT_3) { |
| subsizes[1] = get_h_partition_subsize(sb_size, 1, PARTITION_VERT_3); |
| subsizes[2] = get_h_partition_subsize(sb_size, 2, PARTITION_VERT_3); |
| } |
| |
| for (int idx = 0; idx < subblock_count[partition]; idx++) { |
| const int sub_row = |
| mi_row + step_multiplier[partition][idx][0] * eighth_step_h / 4; |
| const int sub_col = |
| mi_col + step_multiplier[partition][idx][1] * eighth_step_w / 4; |
| SimpleMotionData *subblock = av1_get_sms_data_entry( |
| sms_bufs, sub_row, sub_col, subsizes[idx], sb_size); |
| add_start_mv_to_block(subblock, start_mv); |
| } |
| } |
| |
| // Computes and stores the simple motion search data for the block at mi_row, |
| // mi_col with block size bsize. |
| SimpleMotionData *av1_get_sms_data(AV1_COMP *const cpi, |
| const TileInfo *const tile, MACROBLOCK *x, |
| int mi_row, int mi_col, BLOCK_SIZE bsize) { |
| const AV1_COMMON *const cm = &cpi->common; |
| const BLOCK_SIZE sb_size = cm->sb_size; |
| SimpleMotionDataBufs *sms_bufs = x->sms_bufs; |
| SimpleMotionData *cur_block = |
| av1_get_sms_data_entry(sms_bufs, mi_row, mi_col, bsize, sb_size); |
| const int valid = cur_block->valid; |
| if (!valid) { |
| compute_sms_data(cpi, tile, x, cur_block, mi_row, mi_col, bsize); |
| for (PARTITION_TYPE partition = PARTITION_NONE; |
| partition < EXT_PARTITION_TYPES; partition++) { |
| add_start_mv_to_partition(sms_bufs, mi_row, mi_col, bsize, sb_size, |
| partition, cur_block->fullmv); |
| } |
| } |
| return cur_block; |
| } |
| |
| PARTITION_TYPE av1_get_prev_partition(MACROBLOCK *x, int mi_row, int mi_col, |
| BLOCK_SIZE bsize, BLOCK_SIZE sb_size) { |
| SimpleMotionDataBufs *sms_bufs = x->sms_bufs; |
| const SimpleMotionData *cur_block = |
| av1_get_sms_data_entry(sms_bufs, mi_row, mi_col, bsize, sb_size); |
| if (cur_block->has_prev_partition) { |
| return cur_block->prev_partition; |
| } else { |
| return PARTITION_INVALID; |
| } |
| } |
| |
| static AOM_INLINE int64_t clip_rate(const int rate) { |
| if (rate == INT_MAX) { |
| return av1_cost_symbol(EC_MIN_PROB); |
| } |
| return rate; |
| } |
| |
| void av1_gather_erp_rect_features( |
| float *ml_features, AV1_COMP *cpi, MACROBLOCK *x, const TileInfo *tile_info, |
| const PC_TREE *pc_tree, const PartitionSearchState *part_search_state, |
| int64_t part_none_rd, const int (*mi_pos_rect)[SUB_PARTITIONS_RECT][2]) { |
| const PartitionBlkParams *blk_params = &part_search_state->part_blk_params; |
| const BLOCK_SIZE bsize = blk_params->bsize; |
| int num_features = 0; |
| // Partition costs |
| ml_features[num_features++] = x->rdmult; |
| ml_features[num_features++] = part_none_rd; |
| ml_features[num_features++] = |
| clip_rate(part_search_state->partition_cost[PARTITION_NONE]); |
| ml_features[num_features++] = |
| clip_rate(part_search_state->partition_cost[PARTITION_HORZ]); |
| ml_features[num_features++] = |
| clip_rate(part_search_state->partition_cost[PARTITION_VERT]); |
| |
| const SimpleMotionData *blk_none = av1_get_sms_data( |
| cpi, tile_info, x, blk_params->mi_row, blk_params->mi_col, bsize); |
| |
| const BLOCK_SIZE h_size = get_partition_subsize(bsize, PARTITION_HORZ); |
| const SimpleMotionData *blk_h1 = |
| h_size != BLOCK_INVALID |
| ? av1_get_sms_data(cpi, tile_info, x, mi_pos_rect[HORZ][0][0], |
| mi_pos_rect[HORZ][0][1], h_size) |
| : NULL; |
| const SimpleMotionData *blk_h2 = |
| h_size != BLOCK_INVALID |
| ? av1_get_sms_data(cpi, tile_info, x, mi_pos_rect[HORZ][1][0], |
| mi_pos_rect[HORZ][1][1], h_size) |
| : NULL; |
| |
| const BLOCK_SIZE v_size = get_partition_subsize(bsize, PARTITION_VERT); |
| const SimpleMotionData *blk_v1 = |
| v_size != BLOCK_INVALID |
| ? av1_get_sms_data(cpi, tile_info, x, mi_pos_rect[VERT][0][0], |
| mi_pos_rect[VERT][0][1], v_size) |
| : NULL; |
| const SimpleMotionData *blk_v2 = |
| v_size != BLOCK_INVALID |
| ? av1_get_sms_data(cpi, tile_info, x, mi_pos_rect[VERT][1][0], |
| mi_pos_rect[VERT][1][1], v_size) |
| : NULL; |
| |
| // Results of SMS on the subblocks |
| ml_features[num_features++] = blk_none->sse; |
| ml_features[num_features++] = blk_none->var; |
| if (h_size != BLOCK_INVALID) { |
| ml_features[num_features++] = 1; |
| ml_features[num_features++] = blk_h1->sse; |
| ml_features[num_features++] = blk_h1->var; |
| ml_features[num_features++] = blk_h2->sse; |
| ml_features[num_features++] = blk_h2->var; |
| } else { |
| ml_features[num_features++] = 0; |
| ml_features[num_features++] = 0; |
| ml_features[num_features++] = 0; |
| ml_features[num_features++] = 0; |
| ml_features[num_features++] = 0; |
| } |
| if (v_size != BLOCK_INVALID) { |
| ml_features[num_features++] = 1; |
| ml_features[num_features++] = blk_v1->sse; |
| ml_features[num_features++] = blk_v1->var; |
| ml_features[num_features++] = blk_v2->sse; |
| ml_features[num_features++] = blk_v2->var; |
| } else { |
| ml_features[num_features++] = 0; |
| ml_features[num_features++] = 0; |
| ml_features[num_features++] = 0; |
| ml_features[num_features++] = 0; |
| ml_features[num_features++] = 0; |
| } |
| |
| // Whether we are in the middle of a PARTITION_3 subblock |
| const PC_TREE *parent = pc_tree->parent; |
| #if CONFIG_EXTENDED_SDP |
| REGION_TYPE cur_region_type = pc_tree->region_type; |
| ml_features[num_features++] = |
| parent && (parent->horizontal3[cur_region_type][1] == pc_tree || |
| parent->horizontal3[cur_region_type][2] == pc_tree); |
| ml_features[num_features++] = |
| parent && (parent->vertical3[cur_region_type][1] == pc_tree || |
| parent->vertical3[cur_region_type][2] == pc_tree); |
| #else |
| ml_features[num_features++] = parent && (parent->horizontal3[1] == pc_tree || |
| parent->horizontal3[2] == pc_tree); |
| ml_features[num_features++] = parent && (parent->vertical3[1] == pc_tree || |
| parent->vertical3[2] == pc_tree); |
| #endif // CONFIG_EXTENDED_SDP |
| assert(num_features == 19); |
| } |
| |
| #if CONFIG_ML_PART_SPLIT |
| |
| enum { |
| FEATURE_LOG_QP_SQUARED = 0, |
| FEATURE_HAS_ABOVE, |
| FEATURE_LOG_ABOVE_WIDTH, |
| FEATURE_LOG_ABOVE_HEIGHT, |
| FEATURE_HAS_LEFT, |
| FEATURE_LOG_LEFT_WIDTH, |
| FEATURE_LOG_LEFT_HEIGHT, |
| FEATURE_NORM_BEST_0_SSE, |
| FEATURE_NORM_BEST_0_VAR, |
| FEATURE_NORM_BEST_1_SSE, |
| FEATURE_NORM_BEST_1_VAR, |
| FEATURE_NORM_BEST_2_SSE, |
| FEATURE_NORM_BEST_2_VAR, |
| FEATURE_NORM_BEST_SSE_0_00, |
| FEATURE_NORM_BEST_VAR_0_00, |
| FEATURE_NORM_BEST_SSE_0_01, |
| FEATURE_NORM_BEST_VAR_0_01, |
| FEATURE_NORM_BEST_SSE_0_10, |
| FEATURE_NORM_BEST_VAR_0_10, |
| FEATURE_NORM_BEST_SSE_0_11, |
| FEATURE_NORM_BEST_VAR_0_11, |
| FEATURE_NORM_BEST_SSE_1_00, |
| FEATURE_NORM_BEST_VAR_1_00, |
| FEATURE_NORM_BEST_SSE_1_01, |
| FEATURE_NORM_BEST_VAR_1_01, |
| FEATURE_NORM_BEST_SSE_1_10, |
| FEATURE_NORM_BEST_VAR_1_10, |
| FEATURE_NORM_BEST_SSE_1_11, |
| FEATURE_NORM_BEST_VAR_1_11, |
| FEATURE_NORM_BEST_SSE_2_00, |
| FEATURE_NORM_BEST_VAR_2_00, |
| FEATURE_NORM_BEST_SSE_2_01, |
| FEATURE_NORM_BEST_VAR_2_01, |
| FEATURE_NORM_BEST_SSE_2_10, |
| FEATURE_NORM_BEST_VAR_2_10, |
| FEATURE_NORM_BEST_SSE_2_11, |
| FEATURE_NORM_BEST_VAR_2_11, |
| FEATURE_MAX |
| }; |
| |
| #define ZERO_ARRAY(arr) memset(arr, 0, sizeof(arr)) |
| |
| #define MAX_BLK_SIZE (MAX_TX_SIZE << 1) |
| #define MAX_BLK_SQUARE (MAX_BLK_SIZE * MAX_BLK_SIZE) |
| #define MAX_TX_RECT (MAX_TX_SIZE * MAX_BLK_SIZE) |
| |
| static AOM_INLINE void av1_ml_part_split_features_square(AV1_COMP *const cpi, |
| MACROBLOCK *x, |
| int mi_row, int mi_col, |
| BLOCK_SIZE bsize, |
| float *out_features) { |
| const AV1_COMMON *const cm = &cpi->common; |
| MACROBLOCKD *xd = &x->e_mbd; |
| MB_MODE_INFO *const mbmi = xd->mi[0]; |
| const int w_mi = mi_size_wide[bsize]; |
| const int h_mi = mi_size_high[bsize]; |
| DECLARE_ALIGNED(16, uint16_t, intrapred[MAX_TX_SQUARE]); |
| |
| // plus top line and left column |
| BLOCK_SIZE subsize_sq = get_partition_subsize( |
| get_partition_subsize(bsize, PARTITION_HORZ), PARTITION_VERT); |
| if (subsize_sq == BLOCK_INVALID) { |
| subsize_sq = get_partition_subsize( |
| get_partition_subsize(bsize, PARTITION_VERT), PARTITION_HORZ); |
| } |
| |
| if (subsize_sq != BLOCK_INVALID) { |
| const int w_sub_mi = mi_size_wide[subsize_sq]; |
| const int h_sub_mi = mi_size_high[subsize_sq]; |
| TX_SIZE tx_sub_size = max_txsize_rect_lookup[subsize_sq]; |
| unsigned int best_sub_sse[2][2][3] = { |
| { { INT_MAX, INT_MAX, INT_MAX }, { INT_MAX, INT_MAX, INT_MAX } }, |
| { { INT_MAX, INT_MAX, INT_MAX }, { INT_MAX, INT_MAX, INT_MAX } } |
| }; |
| unsigned int best_sub_var[2][2][3] = { |
| { { INT_MAX, INT_MAX, INT_MAX }, { INT_MAX, INT_MAX, INT_MAX } }, |
| { { INT_MAX, INT_MAX, INT_MAX }, { INT_MAX, INT_MAX, INT_MAX } } |
| }; |
| PREDICTION_MODE best_sub_mode[2][2][3] = { |
| { { MODE_INVALID, MODE_INVALID, MODE_INVALID }, |
| { MODE_INVALID, MODE_INVALID, MODE_INVALID } }, |
| { { MODE_INVALID, MODE_INVALID, MODE_INVALID }, |
| { MODE_INVALID, MODE_INVALID, MODE_INVALID } } |
| }; |
| |
| for (int row_off = 0, r_idx = 0; row_off < h_mi; |
| row_off += h_sub_mi, ++r_idx) { |
| int mi_row_left = xd->tile.mi_row_end - mi_row - row_off; |
| // Don't process beyond the tile boundary |
| if (mi_row_left < 0) break; |
| for (int col_off = 0, c_idx = 0; col_off < w_mi; |
| col_off += w_sub_mi, ++c_idx) { |
| int mi_col_left = xd->tile.mi_col_end - mi_col - col_off; |
| // Don't process beyond the tile boundary |
| if (mi_col_left < 0) break; |
| int src_off = (row_off << 2) * x->plane[0].src.stride + (col_off << 2); |
| xd->mb_to_top_edge = (-mi_row - row_off) << MI_SUBPEL_SIZE_LOG2; |
| xd->mb_to_left_edge = (-mi_col - col_off) << MI_SUBPEL_SIZE_LOG2; |
| mbmi->sb_type[0] = subsize_sq; |
| xd->up_available = (mi_row + row_off) > 0; |
| xd->left_available = (mi_col + col_off) > 0; |
| |
| for (PREDICTION_MODE intra_sub_mode = INTRA_MODE_START; |
| intra_sub_mode < INTRA_MODE_END; ++intra_sub_mode) { |
| memset(intrapred, 0, sizeof(intrapred)); |
| xd->up_available = (mi_row + row_off) > 0; |
| xd->left_available = (mi_col + col_off) > 0; |
| av1_predict_intra_block( |
| cm, xd, w_sub_mi << MI_SIZE_LOG2, h_sub_mi << MI_SIZE_LOG2, |
| tx_sub_size, intra_sub_mode, 0, 0, FILTER_INTRA_MODES, |
| x->plane[0].src.buf + src_off, x->plane[0].src.stride, intrapred, |
| MAX_TX_SIZE, 0, 0, 0); |
| |
| unsigned int curr_sse = 0, curr_var = 0; |
| curr_var = cpi->fn_ptr[txsize_to_bsize[tx_sub_size]].vf( |
| x->plane[0].src.buf + src_off, x->plane[0].src.stride, intrapred, |
| MAX_TX_SIZE, &curr_sse); |
| for (int cand = 0; cand < 3; cand++) { |
| if (curr_sse < best_sub_sse[r_idx][c_idx][cand]) { |
| for (int s = 2; s > cand; s--) { |
| best_sub_sse[r_idx][c_idx][s] = |
| best_sub_sse[r_idx][c_idx][s - 1]; |
| best_sub_var[r_idx][c_idx][s] = |
| best_sub_var[r_idx][c_idx][s - 1]; |
| best_sub_mode[r_idx][c_idx][s] = |
| best_sub_mode[r_idx][c_idx][s - 1]; |
| } |
| best_sub_sse[r_idx][c_idx][cand] = curr_sse; |
| best_sub_var[r_idx][c_idx][cand] = curr_var; |
| best_sub_mode[r_idx][c_idx][cand] = intra_sub_mode; |
| break; |
| } |
| } |
| } |
| if (out_features) { |
| const int sub_area_log2 = |
| mi_size_wide_log2[subsize_sq] + mi_size_high_log2[subsize_sq] + 4; |
| for (int cand = 0; cand < 3; ++cand) { |
| int foff = r_idx * 4 + c_idx * 2 + cand * 8; |
| out_features[FEATURE_NORM_BEST_SSE_0_00 + foff] = logf( |
| 1.0f + (best_sub_sse[r_idx][c_idx][cand] >> sub_area_log2)); |
| out_features[FEATURE_NORM_BEST_VAR_0_00 + foff] = logf( |
| 1.0f + (best_sub_var[r_idx][c_idx][cand] >> sub_area_log2)); |
| } |
| } |
| } |
| } |
| } |
| } |
| |
| static AOM_INLINE void av1_ml_part_split_features_none(AV1_COMP *const cpi, |
| MACROBLOCK *x, |
| int mi_row, int mi_col, |
| BLOCK_SIZE bsize, |
| float *out_features) { |
| const AV1_COMMON *const cm = &cpi->common; |
| MACROBLOCKD *xd = &x->e_mbd; |
| MB_MODE_INFO *const mbmi = xd->mi[0]; |
| const int w_mi = mi_size_wide[bsize]; |
| const int h_mi = mi_size_high[bsize]; |
| |
| TX_SIZE tx_size = max_txsize_rect_lookup[bsize]; |
| |
| unsigned int tx_w = tx_size_wide_unit[tx_size]; |
| unsigned int tx_h = tx_size_high_unit[tx_size]; |
| DECLARE_ALIGNED(16, uint16_t, intrapred[MAX_BLK_SQUARE]); |
| |
| xd->mb_to_top_edge = -mi_row << MI_SUBPEL_SIZE_LOG2; |
| xd->mb_to_left_edge = -mi_col << MI_SUBPEL_SIZE_LOG2; |
| mbmi->sb_type[0] = bsize; |
| unsigned int best_sse[3] = { INT_MAX, INT_MAX, INT_MAX }; |
| unsigned int best_var[3] = { 0, 0, 0 }; |
| PREDICTION_MODE best_mode[3] = { MODE_INVALID, MODE_INVALID, MODE_INVALID }; |
| for (PREDICTION_MODE intra_mode = INTRA_MODE_START; |
| intra_mode < INTRA_MODE_END; ++intra_mode) { |
| unsigned int curr_sse = 0, curr_var = 0; |
| memset(intrapred, 0, sizeof(intrapred)); |
| for (int row_off = 0; row_off < h_mi; row_off += tx_h) { |
| for (int col_off = 0; col_off < w_mi; col_off += tx_w) { |
| int src_off = (row_off << 2) * x->plane[0].src.stride + (col_off << 2); |
| int intr_off = (row_off << 2) * MAX_BLK_SIZE + (col_off << 2); |
| xd->up_available = (mi_row + row_off) > 0; |
| xd->left_available = (mi_col + col_off) > 0; |
| av1_predict_intra_block( |
| cm, xd, w_mi << MI_SIZE_LOG2, h_mi << MI_SIZE_LOG2, tx_size, |
| intra_mode, 0, 0, FILTER_INTRA_MODES, x->plane[0].src.buf + src_off, |
| x->plane[0].src.stride, intrapred + intr_off, MAX_BLK_SIZE, 0, 0, |
| 0); |
| unsigned int tmp = 0; |
| curr_var += cpi->fn_ptr[txsize_to_bsize[tx_size]].vf( |
| x->plane[0].src.buf + src_off, x->plane[0].src.stride, |
| intrapred + intr_off, MAX_BLK_SIZE, &tmp); |
| curr_sse += tmp; |
| } |
| } |
| for (int cand = 0; cand < 3; cand++) { |
| if (curr_sse < best_sse[cand]) { |
| for (int s = 2; s > cand; s--) { |
| best_sse[s] = best_sse[s - 1]; |
| best_var[s] = best_var[s - 1]; |
| best_mode[s] = best_mode[s - 1]; |
| } |
| best_sse[cand] = curr_sse; |
| best_var[cand] = curr_var; |
| best_mode[cand] = intra_mode; |
| break; |
| } |
| } |
| } |
| if (out_features) { |
| const int blk_area_log2 = |
| mi_size_wide_log2[bsize] + mi_size_high_log2[bsize] + 4; |
| out_features[FEATURE_NORM_BEST_0_SSE] = |
| logf(1.0f + (best_sse[0] >> blk_area_log2)); |
| out_features[FEATURE_NORM_BEST_0_VAR] = |
| logf(1.0f + (best_var[0] >> blk_area_log2)); |
| out_features[FEATURE_NORM_BEST_1_SSE] = |
| logf(1.0f + (best_sse[1] >> blk_area_log2)); |
| out_features[FEATURE_NORM_BEST_1_VAR] = |
| logf(1.0f + (best_var[1] >> blk_area_log2)); |
| out_features[FEATURE_NORM_BEST_2_SSE] = |
| logf(1.0f + (best_sse[2] >> blk_area_log2)); |
| out_features[FEATURE_NORM_BEST_2_VAR] = |
| logf(1.0f + (best_var[2] >> blk_area_log2)); |
| } |
| } |
| |
| static AOM_INLINE void av1_ml_part_split_features(AV1_COMP *const cpi, |
| MACROBLOCK *x, int mi_row, |
| int mi_col, BLOCK_SIZE bsize, |
| float *out_features) { |
| MACROBLOCKD *xd = &x->e_mbd; |
| MB_MODE_INFO *const mbmi = xd->mi[0]; |
| |
| av1_setup_src_planes(x, cpi->source, mi_row, mi_col, 1, NULL); |
| |
| if (out_features) { |
| // Q_INDEX |
| const int dc_q = |
| av1_dc_quant_QTX(x->qindex, 0, cpi->common.seq_params.base_y_dc_delta_q, |
| xd->bd) >> |
| (xd->bd - 8); |
| out_features[FEATURE_LOG_QP_SQUARED] = |
| logf(1.0f + (float)((int64_t)dc_q * (int64_t)dc_q) / |
| (256 << (2 * QUANT_TABLE_BITS))); |
| |
| // 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->sb_type[xd->tree_type == CHROMA_PART] |
| : bsize; |
| const BLOCK_SIZE left_bsize = |
| has_left ? xd->left_mbmi->sb_type[xd->tree_type == CHROMA_PART] : bsize; |
| |
| out_features[FEATURE_HAS_ABOVE] = (float)has_above; |
| out_features[FEATURE_LOG_ABOVE_WIDTH] = |
| (float)mi_size_wide_log2[above_bsize]; |
| out_features[FEATURE_LOG_ABOVE_HEIGHT] = |
| (float)mi_size_high_log2[above_bsize]; |
| out_features[FEATURE_HAS_LEFT] = (float)has_left; |
| out_features[FEATURE_LOG_LEFT_WIDTH] = (float)mi_size_wide_log2[left_bsize]; |
| out_features[FEATURE_LOG_LEFT_HEIGHT] = |
| (float)mi_size_high_log2[left_bsize]; |
| } |
| |
| int old1 = xd->mb_to_top_edge; |
| int old2 = xd->mb_to_left_edge; |
| int old3 = mbmi->sb_type[0]; |
| int old4 = mbmi->mrl_index; |
| mbmi->mrl_index = 0; |
| |
| av1_ml_part_split_features_square(cpi, x, mi_row, mi_col, bsize, |
| out_features); |
| av1_ml_part_split_features_none(cpi, x, mi_row, mi_col, bsize, out_features); |
| |
| xd->mb_to_top_edge = old1; |
| xd->mb_to_left_edge = old2; |
| mbmi->sb_type[0] = old3; |
| mbmi->mrl_index = old4; |
| |
| aom_clear_system_state(); |
| } |
| |
| static MODEL_TYPE get_model_type(BLOCK_SIZE bsize) { |
| switch (bsize) { |
| case BLOCK_128X128: return MODEL_128X128; |
| case BLOCK_64X64: return MODEL_64X64; |
| case BLOCK_32X32: return MODEL_32X32; |
| case BLOCK_16X16: return MODEL_16X16; |
| default: return MODEL_OTHER; |
| } |
| } |
| |
| int av1_ml_part_split_infer(AV1_COMP *const cpi, MACROBLOCK *x, int mi_row, |
| int mi_col, BLOCK_SIZE bsize, PC_TREE *pc_tree) { |
| const MACROBLOCKD *xd = &x->e_mbd; |
| int qp = cpi->common.quant_params.base_qindex; |
| bool key_frame = cpi->common.current_frame.frame_type == KEY_FRAME; |
| MODEL_TYPE model_type = get_model_type(bsize); |
| struct ModelParams params; |
| if (model_type != MODEL_OTHER && |
| av2_simple_intra_prune_none_tflite_params( |
| model_type, cpi->sf.part_sf.prune_split_ml_level, ¶ms)) { |
| printf("Error during inference 2\n"); |
| exit(1); |
| } |
| |
| const AV1_COMMON *const cm = &cpi->common; |
| int qp_offset; |
| switch (cm->seq_params.bit_depth) { |
| case AOM_BITS_10: qp_offset = qindex_10b_offset[1]; break; |
| case AOM_BITS_12: qp_offset = qindex_12b_offset[1]; break; |
| default: qp_offset = 0; break; |
| } |
| |
| if (!key_frame || xd->tree_type != LUMA_PART || model_type == MODEL_OTHER || |
| qp > (qp_offset + params.qp_high) || qp < (qp_offset + params.qp_low)) |
| return ML_PART_NOT_SURE; |
| |
| float ml_input[FEATURE_MAX] = { 0.0f }; |
| av1_ml_part_split_features(cpi, x, mi_row, mi_col, bsize, ml_input); |
| |
| float ml_output[1] = { 0.0f }; |
| |
| if (av2_simple_intra_prune_none_tflite_exec(cpi->common.partition_model, |
| ml_input, FEATURE_MAX, ml_output, |
| 1, model_type)) { |
| printf("Error during inference 0\n"); |
| exit(1); |
| } |
| |
| return ml_output[0] > params.thresh_high |
| ? ML_PART_FORCE_SPLIT |
| : (ml_output[0] < params.thresh_low ? ML_PART_PRUNE_SPLIT |
| : ML_PART_NOT_SURE); |
| } |
| #endif // CONFIG_ML_PART_SPLIT |
| |
| #endif // CONFIG_EXT_RECUR_PARTITIONS |