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Searched refs:feature_idx (Results 1 – 6 of 6) sorted by relevance

/external/tensorflow/tensorflow/core/kernels/boosted_trees/
Dquantile_ops.cc302 for (int64 feature_idx = begin; feature_idx < end; ++feature_idx) { in Compute() local
303 QuantileStream* stream = stream_resource->stream(feature_idx); in Compute()
306 << feature_idx << "."; in Compute()
309 const Tensor& summaries = summaries_list[feature_idx]; in Compute()
324 stream_resource->stream(feature_idx)->PushSummary(summary_entries); in Compute()
531 for (int64 feature_idx = begin; feature_idx < end; feature_idx++) { in Compute() local
532 const Tensor& values_tensor = float_features_list[feature_idx]; in Compute()
538 feature_idx, TensorShape({num_values}), &output_t)); in Compute()
542 GetBuckets(feature_idx, bucket_boundaries_list); in Compute()
Dtraining_ops.cc178 for (int64 feature_idx = 0; feature_idx < num_features_; ++feature_idx) { in FindBestSplitsPerNode() local
179 const auto& node_ids = node_ids_list[feature_idx].vec<int32>(); in FindBestSplitsPerNode()
180 const auto& gains = gains_list[feature_idx].vec<float>(); in FindBestSplitsPerNode()
181 const auto& thresholds = thresholds_list[feature_idx].vec<int32>(); in FindBestSplitsPerNode()
183 left_node_contribs_list[feature_idx].matrix<float>(); in FindBestSplitsPerNode()
185 right_node_contribs_list[feature_idx].matrix<float>(); in FindBestSplitsPerNode()
194 candidate.feature_id = feature_ids(feature_idx); in FindBestSplitsPerNode()
Dstats_ops.cc108 for (int feature_idx = 0; feature_idx < num_features_; ++feature_idx) { in Compute() local
127 total_grad += stats_summary[feature_idx](node_id, bucket, 0); in Compute()
128 total_hess += stats_summary[feature_idx](node_id, bucket, 1); in Compute()
182 output_node_ids_list.allocate(feature_idx, {num_nodes}, in Compute()
188 feature_idx, {num_nodes}, &output_gains_t)); in Compute()
193 output_thresholds_list.allocate(feature_idx, {num_nodes}, in Compute()
199 feature_idx, {num_nodes, 1}, in Compute()
206 feature_idx, {num_nodes, 1}, in Compute()
1281 for (int feature_idx = 0; feature_idx < num_features_; ++feature_idx) { in Compute() local
1282 const auto& features = bucketized_features_list[feature_idx].vec<int32>(); in Compute()
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/external/libaom/libaom/av1/encoder/
Dpartition_strategy.c809 int *feature_idx) { in add_rd_feature() argument
812 features[(*feature_idx)++] = (float)rd_valid; in add_rd_feature()
813 features[(*feature_idx)++] = rd_ratio; in add_rd_feature()
Dtx_search.c1846 int feature_idx = 2; in get_mean_dev_features() local
1866 feature[feature_idx++] = mean; in get_mean_dev_features()
1867 feature[feature_idx++] = dev; in get_mean_dev_features()
1880 feature[feature_idx++] = get_dev(lvl0_mean, mean2_sum, blk_idx); in get_mean_dev_features()
1882 feature[feature_idx++] = dev_sum / blk_idx; in get_mean_dev_features()
/external/libvpx/libvpx/vp9/encoder/
Dvp9_encodeframe.c3596 int feature_idx = 0; in ml_predict_var_rd_paritioning() local
3600 features[feature_idx++] = logf((float)dc_q + 1.0f); in ml_predict_var_rd_paritioning()
3622 features[feature_idx++] = (float)has_above; in ml_predict_var_rd_paritioning()
3623 features[feature_idx++] = (float)b_width_log2_lookup[above_bsize]; in ml_predict_var_rd_paritioning()
3624 features[feature_idx++] = (float)b_height_log2_lookup[above_bsize]; in ml_predict_var_rd_paritioning()
3625 features[feature_idx++] = (float)has_left; in ml_predict_var_rd_paritioning()
3626 features[feature_idx++] = (float)b_width_log2_lookup[left_bsize]; in ml_predict_var_rd_paritioning()
3627 features[feature_idx++] = (float)b_height_log2_lookup[left_bsize]; in ml_predict_var_rd_paritioning()
3628 features[feature_idx++] = logf((float)var + 1.0f); in ml_predict_var_rd_paritioning()
3639 features[feature_idx++] = var_ratio; in ml_predict_var_rd_paritioning()
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