Searched refs:feature_idx (Results 1 – 6 of 6) sorted by relevance
/external/tensorflow/tensorflow/core/kernels/boosted_trees/ |
D | quantile_ops.cc | 302 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()
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D | training_ops.cc | 178 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()
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D | stats_ops.cc | 108 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() [all …]
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/external/libaom/libaom/av1/encoder/ |
D | partition_strategy.c | 809 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()
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D | tx_search.c | 1846 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()
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/external/libvpx/libvpx/vp9/encoder/ |
D | vp9_encodeframe.c | 3596 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() [all …]
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