Merge branch 'master' into unity
Conflicts: src/learner/evaluation-inl.hpp wrapper/xgboost_R.cpp wrapper/xgboost_wrapper.cpp wrapper/xgboost_wrapper.h
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@@ -51,9 +51,9 @@ class GBLinear : public IGradBooster<FMatrix> {
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// for all the output group
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for (int gid = 0; gid < ngroup; ++gid) {
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double sum_grad = 0.0, sum_hess = 0.0;
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const unsigned ndata = static_cast<unsigned>(rowset.size());
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const bst_omp_uint ndata = static_cast<bst_omp_uint>(rowset.size());
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#pragma omp parallel for schedule(static) reduction(+: sum_grad, sum_hess)
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for (unsigned i = 0; i < ndata; ++i) {
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for (bst_omp_uint i = 0; i < ndata; ++i) {
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bst_gpair &p = gpair[rowset[i] * ngroup + gid];
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if (p.hess >= 0.0f) {
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sum_grad += p.grad; sum_hess += p.hess;
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@@ -65,7 +65,7 @@ class GBLinear : public IGradBooster<FMatrix> {
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model.bias()[gid] += dw;
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// update grad value
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#pragma omp parallel for schedule(static)
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for (unsigned i = 0; i < ndata; ++i) {
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for (bst_omp_uint i = 0; i < ndata; ++i) {
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bst_gpair &p = gpair[rowset[i] * ngroup + gid];
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if (p.hess >= 0.0f) {
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p.grad += p.hess * dw;
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@@ -73,9 +73,9 @@ class GBLinear : public IGradBooster<FMatrix> {
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}
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}
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// number of features
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const unsigned nfeat = static_cast<unsigned>(feat_index.size());
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const bst_omp_uint nfeat = static_cast<bst_omp_uint>(feat_index.size());
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#pragma omp parallel for schedule(static)
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for (unsigned i = 0; i < nfeat; ++i) {
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for (bst_omp_uint i = 0; i < nfeat; ++i) {
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const bst_uint fid = feat_index[i];
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for (int gid = 0; gid < ngroup; ++gid) {
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double sum_grad = 0.0, sum_hess = 0.0;
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@@ -117,9 +117,9 @@ class GBLinear : public IGradBooster<FMatrix> {
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// k is number of group
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preds.resize(preds.size() + batch.size * ngroup);
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// parallel over local batch
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const unsigned nsize = static_cast<unsigned>(batch.size);
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const bst_omp_uint nsize = static_cast<bst_omp_uint>(batch.size);
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#pragma omp parallel for schedule(static)
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for (unsigned i = 0; i < nsize; ++i) {
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for (bst_omp_uint i = 0; i < nsize; ++i) {
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const size_t ridx = batch.base_rowid + i;
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// loop over output groups
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for (int gid = 0; gid < ngroup; ++gid) {
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@@ -94,8 +94,9 @@ class GBTree : public IGradBooster<FMatrix> {
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"must have exactly ngroup*nrow gpairs");
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std::vector<bst_gpair> tmp(gpair.size()/ngroup);
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for (int gid = 0; gid < ngroup; ++gid) {
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bst_omp_uint nsize = static_cast<bst_omp_uint>(tmp.size());
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#pragma omp parallel for schedule(static)
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for (size_t i = 0; i < tmp.size(); ++i) {
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for (bst_omp_uint i = 0; i < nsize; ++i) {
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tmp[i] = gpair[i * ngroup + gid];
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}
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this->BoostNewTrees(tmp, fmat, info, gid);
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@@ -125,9 +126,9 @@ class GBTree : public IGradBooster<FMatrix> {
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while (iter->Next()) {
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const SparseBatch &batch = iter->Value();
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// parallel over local batch
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const unsigned nsize = static_cast<unsigned>(batch.size);
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const bst_omp_uint nsize = static_cast<bst_omp_uint>(batch.size);
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#pragma omp parallel for schedule(static)
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for (unsigned i = 0; i < nsize; ++i) {
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for (bst_omp_uint i = 0; i < nsize; ++i) {
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const int tid = omp_get_thread_num();
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tree::RegTree::FVec &feats = thread_temp[tid];
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int64_t ridx = static_cast<int64_t>(batch.base_rowid + i);
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