change uint64_t to ulong, to make mac happy, this is final change
This commit is contained in:
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d00f27dc6b
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4787108b5f
@ -119,7 +119,7 @@ extern "C" {
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}
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}
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SEXP XGDMatrixGetInfo_R(SEXP handle, SEXP field) {
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uint64_t olen;
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bst_ulong olen;
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const float *res = XGDMatrixGetFloatInfo(R_ExternalPtrAddr(handle),
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CHAR(asChar(field)), &olen);
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SEXP ret = PROTECT(allocVector(REALSXP, olen));
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@ -188,7 +188,7 @@ extern "C" {
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&vec_dmats[0], &vec_sptr[0], len));
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}
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SEXP XGBoosterPredict_R(SEXP handle, SEXP dmat, SEXP output_margin) {
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uint64_t olen;
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bst_ulong olen;
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const float *res = XGBoosterPredict(R_ExternalPtrAddr(handle),
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R_ExternalPtrAddr(dmat),
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asInteger(output_margin),
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@ -207,7 +207,7 @@ extern "C" {
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XGBoosterSaveModel(R_ExternalPtrAddr(handle), CHAR(asChar(fname)));
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}
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void XGBoosterDumpModel_R(SEXP handle, SEXP fname, SEXP fmap) {
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uint64_t olen;
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bst_ulong olen;
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const char **res = XGBoosterDumpModel(R_ExternalPtrAddr(handle),
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CHAR(asChar(fmap)),
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&olen);
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@ -119,7 +119,7 @@ extern "C" {
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}
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}
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SEXP XGDMatrixGetInfo_R(SEXP handle, SEXP field) {
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uint64_t olen;
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bst_ulong olen;
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const float *res = XGDMatrixGetFloatInfo(R_ExternalPtrAddr(handle),
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CHAR(asChar(field)), &olen);
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SEXP ret = PROTECT(allocVector(REALSXP, olen));
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@ -188,7 +188,7 @@ extern "C" {
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&vec_dmats[0], &vec_sptr[0], len));
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}
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SEXP XGBoosterPredict_R(SEXP handle, SEXP dmat, SEXP output_margin) {
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uint64_t olen;
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bst_ulong olen;
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const float *res = XGBoosterPredict(R_ExternalPtrAddr(handle),
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R_ExternalPtrAddr(dmat),
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asInteger(output_margin),
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@ -207,7 +207,7 @@ extern "C" {
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XGBoosterSaveModel(R_ExternalPtrAddr(handle), CHAR(asChar(fname)));
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}
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void XGBoosterDumpModel_R(SEXP handle, SEXP fname, SEXP fmap) {
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uint64_t olen;
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bst_ulong olen;
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const char **res = XGBoosterDumpModel(R_ExternalPtrAddr(handle),
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CHAR(asChar(fmap)),
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&olen);
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@ -23,14 +23,14 @@ class Booster: public learner::BoostLearner<FMatrixS> {
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this->init_model = false;
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this->SetCacheData(mats);
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}
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const float *Pred(const DataMatrix &dmat, int output_margin, uint64_t *len) {
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const float *Pred(const DataMatrix &dmat, int output_margin, bst_ulong *len) {
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this->CheckInitModel();
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this->Predict(dmat, output_margin, &this->preds_);
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*len = this->preds_.size();
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return &this->preds_[0];
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}
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inline void BoostOneIter(const DataMatrix &train,
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float *grad, float *hess, uint64_t len) {
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float *grad, float *hess, bst_ulong len) {
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this->gpair_.resize(len);
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const bst_omp_uint ndata = static_cast<bst_omp_uint>(len);
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#pragma omp parallel for schedule(static)
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@ -48,7 +48,7 @@ class Booster: public learner::BoostLearner<FMatrixS> {
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learner::BoostLearner<FMatrixS>::LoadModel(fname);
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this->init_model = true;
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}
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inline const char** GetModelDump(const utils::FeatMap& fmap, bool with_stats, uint64_t *len) {
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inline const char** GetModelDump(const utils::FeatMap& fmap, bool with_stats, bst_ulong *len) {
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model_dump = this->DumpModel(fmap, with_stats);
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model_dump_cptr.resize(model_dump.size());
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for (size_t i = 0; i < model_dump.size(); ++i) {
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@ -76,37 +76,37 @@ extern "C"{
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void* XGDMatrixCreateFromFile(const char *fname, int silent) {
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return LoadDataMatrix(fname, silent, false);
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}
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void* XGDMatrixCreateFromCSR(const uint64_t *indptr,
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void* XGDMatrixCreateFromCSR(const bst_ulong *indptr,
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const unsigned *indices,
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const float *data,
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uint64_t nindptr,
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uint64_t nelem) {
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bst_ulong nindptr,
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bst_ulong nelem) {
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DMatrixSimple *p_mat = new DMatrixSimple();
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DMatrixSimple &mat = *p_mat;
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mat.row_ptr_.resize(nindptr);
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for (uint64_t i = 0; i < nindptr; ++i) {
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for (bst_ulong i = 0; i < nindptr; ++i) {
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mat.row_ptr_[i] = static_cast<size_t>(indptr[i]);
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}
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mat.row_data_.resize(nelem);
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for (uint64_t i = 0; i < nelem; ++i) {
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for (bst_ulong i = 0; i < nelem; ++i) {
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mat.row_data_[i] = SparseBatch::Entry(indices[i], data[i]);
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mat.info.info.num_col = std::max(mat.info.info.num_col,
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static_cast<uint64_t>(indices[i]+1));
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static_cast<size_t>(indices[i]+1));
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}
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mat.info.info.num_row = nindptr - 1;
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return p_mat;
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}
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void* XGDMatrixCreateFromMat(const float *data,
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uint64_t nrow,
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uint64_t ncol,
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bst_ulong nrow,
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bst_ulong ncol,
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float missing) {
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DMatrixSimple *p_mat = new DMatrixSimple();
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DMatrixSimple &mat = *p_mat;
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mat.info.info.num_row = nrow;
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mat.info.info.num_col = ncol;
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for (uint64_t i = 0; i < nrow; ++i, data += ncol) {
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uint64_t nelem = 0;
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for (uint64_t j = 0; j < ncol; ++j) {
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for (bst_ulong i = 0; i < nrow; ++i, data += ncol) {
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bst_ulong nelem = 0;
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for (bst_ulong j = 0; j < ncol; ++j) {
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if (data[j] != missing) {
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mat.row_data_.push_back(SparseBatch::Entry(j, data[j]));
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++nelem;
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@ -118,7 +118,7 @@ extern "C"{
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}
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void* XGDMatrixSliceDMatrix(void *handle,
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const int *idxset,
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uint64_t len) {
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bst_ulong len) {
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DMatrixSimple tmp;
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DataMatrix &dsrc = *static_cast<DataMatrix*>(handle);
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if (dsrc.magic != DMatrixSimple::kMagic) {
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@ -139,10 +139,10 @@ extern "C"{
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iter->BeforeFirst();
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utils::Assert(iter->Next(), "slice");
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const SparseBatch &batch = iter->Value();
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for (uint64_t i = 0; i < len; ++i) {
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for (bst_ulong i = 0; i < len; ++i) {
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const int ridx = idxset[i];
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SparseBatch::Inst inst = batch[ridx];
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utils::Check(static_cast<uint64_t>(ridx) < batch.size, "slice index exceed number of rows");
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utils::Check(static_cast<bst_ulong>(ridx) < batch.size, "slice index exceed number of rows");
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ret.row_data_.resize(ret.row_data_.size() + inst.length);
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memcpy(&ret.row_data_[ret.row_ptr_.back()], inst.data,
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sizeof(SparseBatch::Entry) * inst.length);
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@ -165,46 +165,46 @@ extern "C"{
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void XGDMatrixSaveBinary(void *handle, const char *fname, int silent) {
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SaveDataMatrix(*static_cast<DataMatrix*>(handle), fname, silent);
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}
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void XGDMatrixSetFloatInfo(void *handle, const char *field, const float *info, uint64_t len) {
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void XGDMatrixSetFloatInfo(void *handle, const char *field, const float *info, bst_ulong len) {
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std::vector<float> &vec =
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static_cast<DataMatrix*>(handle)->info.GetFloatInfo(field);
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vec.resize(len);
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memcpy(&vec[0], info, sizeof(float) * len);
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}
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void XGDMatrixSetUIntInfo(void *handle, const char *field, const unsigned *info, uint64_t len) {
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void XGDMatrixSetUIntInfo(void *handle, const char *field, const unsigned *info, bst_ulong len) {
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std::vector<unsigned> &vec =
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static_cast<DataMatrix*>(handle)->info.GetUIntInfo(field);
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vec.resize(len);
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memcpy(&vec[0], info, sizeof(unsigned) * len);
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}
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void XGDMatrixSetGroup(void *handle, const unsigned *group, uint64_t len) {
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void XGDMatrixSetGroup(void *handle, const unsigned *group, bst_ulong len) {
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DataMatrix *pmat = static_cast<DataMatrix*>(handle);
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pmat->info.group_ptr.resize(len + 1);
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pmat->info.group_ptr[0] = 0;
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for (uint64_t i = 0; i < len; ++i) {
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for (bst_ulong i = 0; i < len; ++i) {
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pmat->info.group_ptr[i+1] = pmat->info.group_ptr[i]+group[i];
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}
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}
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const float* XGDMatrixGetFloatInfo(const void *handle, const char *field, uint64_t* len) {
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const float* XGDMatrixGetFloatInfo(const void *handle, const char *field, bst_ulong* len) {
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const std::vector<float> &vec =
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static_cast<const DataMatrix*>(handle)->info.GetFloatInfo(field);
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*len = vec.size();
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return &vec[0];
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}
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const unsigned* XGDMatrixGetUIntInfo(const void *handle, const char *field, uint64_t* len) {
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const unsigned* XGDMatrixGetUIntInfo(const void *handle, const char *field, bst_ulong* len) {
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const std::vector<unsigned> &vec =
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static_cast<const DataMatrix*>(handle)->info.GetUIntInfo(field);
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*len = vec.size();
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return &vec[0];
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}
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uint64_t XGDMatrixNumRow(const void *handle) {
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bst_ulong XGDMatrixNumRow(const void *handle) {
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return static_cast<const DataMatrix*>(handle)->info.num_row();
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}
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// xgboost implementation
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void *XGBoosterCreate(void *dmats[], uint64_t len) {
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void *XGBoosterCreate(void *dmats[], bst_ulong len) {
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std::vector<DataMatrix*> mats;
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for (uint64_t i = 0; i < len; ++i) {
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for (bst_ulong i = 0; i < len; ++i) {
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DataMatrix *dtr = static_cast<DataMatrix*>(dmats[i]);
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mats.push_back(dtr);
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}
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@ -224,7 +224,7 @@ extern "C"{
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bst->UpdateOneIter(iter, *dtr);
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}
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void XGBoosterBoostOneIter(void *handle, void *dtrain,
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float *grad, float *hess, uint64_t len) {
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float *grad, float *hess, bst_ulong len) {
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Booster *bst = static_cast<Booster*>(handle);
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DataMatrix *dtr = static_cast<DataMatrix*>(dtrain);
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bst->CheckInitModel();
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@ -232,11 +232,11 @@ extern "C"{
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bst->BoostOneIter(*dtr, grad, hess, len);
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}
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const char* XGBoosterEvalOneIter(void *handle, int iter, void *dmats[],
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const char *evnames[], uint64_t len) {
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const char *evnames[], bst_ulong len) {
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Booster *bst = static_cast<Booster*>(handle);
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std::vector<std::string> names;
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std::vector<const DataMatrix*> mats;
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for (uint64_t i = 0; i < len; ++i) {
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for (bst_ulong i = 0; i < len; ++i) {
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mats.push_back(static_cast<DataMatrix*>(dmats[i]));
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names.push_back(std::string(evnames[i]));
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}
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@ -244,7 +244,7 @@ extern "C"{
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bst->eval_str = bst->EvalOneIter(iter, mats, names);
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return bst->eval_str.c_str();
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}
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const float *XGBoosterPredict(void *handle, void *dmat, int output_margin, uint64_t *len) {
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const float *XGBoosterPredict(void *handle, void *dmat, int output_margin, bst_ulong *len) {
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return static_cast<Booster*>(handle)->Pred(*static_cast<DataMatrix*>(dmat), output_margin, len);
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}
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void XGBoosterLoadModel(void *handle, const char *fname) {
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@ -253,7 +253,7 @@ extern "C"{
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void XGBoosterSaveModel(const void *handle, const char *fname) {
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static_cast<const Booster*>(handle)->SaveModel(fname);
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}
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const char** XGBoosterDumpModel(void *handle, const char *fmap, uint64_t *len){
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const char** XGBoosterDumpModel(void *handle, const char *fmap, bst_ulong *len){
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utils::FeatMap featmap;
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if (strlen(fmap) != 0) {
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featmap.LoadText(fmap);
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@ -7,8 +7,9 @@
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* can be used to create wrapper of other languages
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*/
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#include <cstdio>
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#include "../src/utils/utils.h"
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#define XGB_DLL
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// manually define unsign long
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typedef unsigned long bst_ulong;
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extern "C" {
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/*!
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@ -25,11 +26,11 @@ extern "C" {
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* \param nelem number of nonzero elements in the matrix
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* \return created dmatrix
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*/
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XGB_DLL void* XGDMatrixCreateFromCSR(const uint64_t *indptr,
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XGB_DLL void* XGDMatrixCreateFromCSR(const bst_ulong *indptr,
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const unsigned *indices,
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const float *data,
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uint64_t nindptr,
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uint64_t nelem);
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bst_ulong nindptr,
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bst_ulong nelem);
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/*!
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* \brief create matrix content from dense matrix
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* \param data pointer to the data space
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@ -39,8 +40,8 @@ extern "C" {
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* \return created dmatrix
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*/
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XGB_DLL void* XGDMatrixCreateFromMat(const float *data,
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uint64_t nrow,
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uint64_t ncol,
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bst_ulong nrow,
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bst_ulong ncol,
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float missing);
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/*!
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* \brief create a new dmatrix from sliced content of existing matrix
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@ -51,7 +52,7 @@ extern "C" {
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*/
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XGB_DLL void* XGDMatrixSliceDMatrix(void *handle,
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const int *idxset,
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uint64_t len);
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bst_ulong len);
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/*!
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* \brief free space in data matrix
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*/
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@ -70,7 +71,7 @@ extern "C" {
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* \param array pointer to float vector
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* \param len length of array
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*/
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XGB_DLL void XGDMatrixSetFloatInfo(void *handle, const char *field, const float *array, uint64_t len);
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XGB_DLL void XGDMatrixSetFloatInfo(void *handle, const char *field, const float *array, bst_ulong len);
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/*!
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* \brief set uint32 vector to a content in info
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* \param handle a instance of data matrix
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@ -78,14 +79,14 @@ extern "C" {
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* \param array pointer to float vector
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* \param len length of array
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*/
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XGB_DLL void XGDMatrixSetUIntInfo(void *handle, const char *field, const unsigned *array, uint64_t len);
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XGB_DLL void XGDMatrixSetUIntInfo(void *handle, const char *field, const unsigned *array, bst_ulong len);
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/*!
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* \brief set label of the training matrix
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* \param handle a instance of data matrix
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* \param group pointer to group size
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* \param len length of array
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*/
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XGB_DLL void XGDMatrixSetGroup(void *handle, const unsigned *group, uint64_t len);
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XGB_DLL void XGDMatrixSetGroup(void *handle, const unsigned *group, bst_ulong len);
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/*!
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* \brief get float info vector from matrix
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* \param handle a instance of data matrix
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@ -93,7 +94,7 @@ extern "C" {
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* \param out_len used to set result length
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* \return pointer to the result
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*/
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XGB_DLL const float* XGDMatrixGetFloatInfo(const void *handle, const char *field, uint64_t* out_len);
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XGB_DLL const float* XGDMatrixGetFloatInfo(const void *handle, const char *field, bst_ulong* out_len);
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/*!
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* \brief get uint32 info vector from matrix
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* \param handle a instance of data matrix
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@ -101,18 +102,18 @@ extern "C" {
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* \param out_len used to set result length
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* \return pointer to the result
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*/
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XGB_DLL const unsigned* XGDMatrixGetUIntInfo(const void *handle, const char *field, uint64_t* out_len);
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XGB_DLL const unsigned* XGDMatrixGetUIntInfo(const void *handle, const char *field, bst_ulong* out_len);
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/*!
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* \brief return number of rows
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*/
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XGB_DLL uint64_t XGDMatrixNumRow(const void *handle);
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XGB_DLL bst_ulong XGDMatrixNumRow(const void *handle);
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// --- start XGBoost class
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/*!
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* \brief create xgboost learner
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* \param dmats matrices that are set to be cached
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* \param len length of dmats
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*/
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XGB_DLL void *XGBoosterCreate(void* dmats[], uint64_t len);
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XGB_DLL void *XGBoosterCreate(void* dmats[], bst_ulong len);
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/*!
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* \brief free obj in handle
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* \param handle handle to be freed
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@ -142,7 +143,7 @@ extern "C" {
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* \param len length of grad/hess array
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*/
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XGB_DLL void XGBoosterBoostOneIter(void *handle, void *dtrain,
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float *grad, float *hess, uint64_t len);
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float *grad, float *hess, bst_ulong len);
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/*!
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* \brief get evaluation statistics for xgboost
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* \param handle handle
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@ -153,7 +154,7 @@ extern "C" {
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* \return the string containing evaluation stati
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*/
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XGB_DLL const char *XGBoosterEvalOneIter(void *handle, int iter, void *dmats[],
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const char *evnames[], uint64_t len);
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const char *evnames[], bst_ulong len);
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/*!
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* \brief make prediction based on dmat
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* \param handle handle
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@ -161,7 +162,7 @@ extern "C" {
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* \param output_margin whether only output raw margin value
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* \param len used to store length of returning result
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*/
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XGB_DLL const float *XGBoosterPredict(void *handle, void *dmat, int output_margin, uint64_t *len);
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XGB_DLL const float *XGBoosterPredict(void *handle, void *dmat, int output_margin, bst_ulong *len);
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/*!
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* \brief load model from existing file
|
||||
* \param handle handle
|
||||
@ -182,6 +183,6 @@ extern "C" {
|
||||
* \return char *data[], representing dump of each model
|
||||
*/
|
||||
XGB_DLL const char **XGBoosterDumpModel(void *handle, const char *fmap,
|
||||
uint64_t *out_len);
|
||||
bst_ulong *out_len);
|
||||
};
|
||||
#endif // XGBOOST_WRAPPER_H_
|
||||
|
||||
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Reference in New Issue
Block a user