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[Breaking] Remove num roots. (#5059)

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This commit is contained in:
Jiaming Yuan
2019-12-05 21:58:43 +08:00
committed by GitHub
parent f3d8536702
commit 64af1ecf86
23 changed files with 87 additions and 189 deletions
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26
src/predictor/cpu_predictor.cc
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@@ -19,13 +19,13 @@ class CPUPredictor : public Predictor {
static bst_float PredValue(const SparsePage::Inst& inst,
const std::vector<std::unique_ptr<RegTree>>& trees,
const std::vector<int>& tree_info, int bst_group,
unsigned root_index, RegTree::FVec* p_feats,
RegTree::FVec* p_feats,
unsigned tree_begin, unsigned tree_end) {
bst_float psum = 0.0f;
p_feats->Fill(inst);
for (size_t i = tree_begin; i < tree_end; ++i) {
if (tree_info[i] == bst_group) {
int tid = trees[i]->GetLeafIndex(*p_feats, root_index);
int tid = trees[i]->GetLeafIndex(*p_feats);
psum += (*trees[i])[tid].LeafValue();
}
}
@@ -47,7 +47,6 @@ class CPUPredictor : public Predictor {
std::vector<bst_float>* out_preds,
const gbm::GBTreeModel& model, int num_group,
unsigned tree_begin, unsigned tree_end) {
const MetaInfo& info = p_fmat->Info();
const int nthread = omp_get_max_threads();
InitThreadTemp(nthread, model.param.num_feature);
std::vector<bst_float>& preds = *out_preds;
@@ -81,7 +80,7 @@ class CPUPredictor : public Predictor {
const size_t offset = ridx[k] * num_group + gid;
preds[offset] += this->PredValue(
inst[k], model.trees, model.tree_info, gid,
info.GetRoot(ridx[k]), &feats, tree_begin, tree_end);
&feats, tree_begin, tree_end);
}
}
}
@@ -94,7 +93,7 @@ class CPUPredictor : public Predictor {
const size_t offset = ridx * num_group + gid;
preds[offset] +=
this->PredValue(inst, model.trees, model.tree_info, gid,
info.GetRoot(ridx), &feats, tree_begin, tree_end);
&feats, tree_begin, tree_end);
}
}
}
@@ -204,8 +203,7 @@ class CPUPredictor : public Predictor {
void PredictInstance(const SparsePage::Inst& inst,
std::vector<bst_float>* out_preds,
const gbm::GBTreeModel& model, unsigned ntree_limit,
unsigned root_index) override {
const gbm::GBTreeModel& model, unsigned ntree_limit) override {
if (thread_temp.size() == 0) {
thread_temp.resize(1, RegTree::FVec());
thread_temp[0].Init(model.param.num_feature);
@@ -219,7 +217,7 @@ class CPUPredictor : public Predictor {
// loop over output groups
for (int gid = 0; gid < model.param.num_output_group; ++gid) {
(*out_preds)[gid] =
PredValue(inst, model.trees, model.tree_info, gid, root_index,
PredValue(inst, model.trees, model.tree_info, gid,
&thread_temp[0], 0, ntree_limit) +
model.base_margin;
}
@@ -247,7 +245,7 @@ class CPUPredictor : public Predictor {
RegTree::FVec& feats = thread_temp[tid];
feats.Fill(batch[i]);
for (unsigned j = 0; j < ntree_limit; ++j) {
int tid = model.trees[j]->GetLeafIndex(feats, info.GetRoot(ridx));
int tid = model.trees[j]->GetLeafIndex(feats);
preds[ridx * ntree_limit + j] = static_cast<bst_float>(tid);
}
feats.Drop(batch[i]);
@@ -270,7 +268,7 @@ class CPUPredictor : public Predictor {
ntree_limit = static_cast<unsigned>(model.trees.size());
}
const int ngroup = model.param.num_output_group;
size_t ncolumns = model.param.num_feature + 1;
size_t const ncolumns = model.param.num_feature + 1;
// allocate space for (number of features + bias) times the number of rows
std::vector<bst_float>& contribs = *out_contribs;
contribs.resize(info.num_row_ * ncolumns * model.param.num_output_group);
@@ -290,15 +288,13 @@ class CPUPredictor : public Predictor {
#pragma omp parallel for schedule(static)
for (bst_omp_uint i = 0; i < nsize; ++i) {
auto row_idx = static_cast<size_t>(batch.base_rowid + i);
unsigned root_id = info.GetRoot(row_idx);
std::vector<bst_float> this_tree_contribs(ncolumns);
RegTree::FVec& feats = thread_temp[omp_get_thread_num()];
// loop over all classes
for (int gid = 0; gid < ngroup; ++gid) {
bst_float* p_contribs =
&contribs[(row_idx * ngroup + gid) * ncolumns];
feats.Fill(batch[i]);
std::vector<bst_float> this_tree_contribs;
this_tree_contribs.resize(ncolumns);
// calculate contributions
for (unsigned j = 0; j < ntree_limit; ++j) {
std::fill(this_tree_contribs.begin(), this_tree_contribs.end(), 0);
@@ -306,10 +302,10 @@ class CPUPredictor : public Predictor {
continue;
}
if (!approximate) {
model.trees[j]->CalculateContributions(feats, root_id, &this_tree_contribs[0],
model.trees[j]->CalculateContributions(feats, &this_tree_contribs[0],
condition, condition_feature);
} else {
model.trees[j]->CalculateContributionsApprox(feats, root_id, &this_tree_contribs[0]);
model.trees[j]->CalculateContributionsApprox(feats, &this_tree_contribs[0]);
}
for (int ci = 0 ; ci < ncolumns ; ++ci) {
p_contribs[ci] += this_tree_contribs[ci] *