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xgboost/src/c_api/c_api.cc
Jiaming Yuan c1786849e3
Use array interface for CSC matrix. (#8672) 
* Use array interface for CSC matrix.

Use array interface for CSC matrix and align the interface with CSR and dense.

- Fix nthread issue in the R package DMatrix.
- Unify the behavior of handling `missing` with other inputs.
- Unify the behavior of handling `missing` around R, Python, Java, and Scala DMatrix.
- Expose `num_non_missing` to the JVM interface.
- Deprecate old CSR and CSC constructors.
2023-02-05 01:59:46 +08:00

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/**
* Copyright 2014-2023 by XGBoost Contributors
*/
#include "xgboost/c_api.h"
#include <rabit/c_api.h>
#include <cstring>
#include <fstream>
#include <memory>
#include <string>
#include <vector>
#include "../collective/communicator-inl.h"
#include "../common/charconv.h"
#include "../common/io.h"
#include "../data/adapter.h"
#include "../data/simple_dmatrix.h"
#include "c_api_error.h"
#include "c_api_utils.h"
#include "xgboost/base.h"
#include "xgboost/data.h"
#include "xgboost/global_config.h"
#include "xgboost/host_device_vector.h"
#include "xgboost/json.h"
#include "xgboost/learner.h"
#include "xgboost/logging.h"
#include "xgboost/string_view.h" // StringView
#include "xgboost/version_config.h"
#if defined(XGBOOST_USE_FEDERATED)
#include "../../plugin/federated/federated_server.h"
#endif
using namespace xgboost; // NOLINT(*);
XGB_DLL void XGBoostVersion(int* major, int* minor, int* patch) {
if (major) {
*major = XGBOOST_VER_MAJOR;
}
if (minor) {
*minor = XGBOOST_VER_MINOR;
}
if (patch) {
*patch = XGBOOST_VER_PATCH;
}
}
using GlobalConfigAPIThreadLocalStore = dmlc::ThreadLocalStore<XGBAPIThreadLocalEntry>;
#if !defined(XGBOOST_USE_CUDA)
namespace xgboost {
void XGBBuildInfoDevice(Json *p_info) {
auto &info = *p_info;
info["USE_CUDA"] = Boolean{false};
info["USE_NCCL"] = Boolean{false};
info["USE_RMM"] = Boolean{false};
}
} // namespace xgboost
#endif
namespace {
void DeprecatedFunc(StringView old, StringView since, StringView replacement) {
LOG(WARNING) << "`" << old << "` is deprecated since" << since << ", use `" << replacement
<< "` instead.";
}
} // anonymous namespace
XGB_DLL int XGBuildInfo(char const **out) {
API_BEGIN();
xgboost_CHECK_C_ARG_PTR(out);
Json info{Object{}};
#if defined(XGBOOST_BUILTIN_PREFETCH_PRESENT)
info["BUILTIN_PREFETCH_PRESENT"] = Boolean{true};
#else
info["BUILTIN_PREFETCH_PRESENT"] = Boolean{false};
#endif
#if defined(XGBOOST_MM_PREFETCH_PRESENT)
info["MM_PREFETCH_PRESENT"] = Boolean{true};
#else
info["MM_PREFETCH_PRESENT"] = Boolean{false};
#endif
#if defined(_OPENMP)
info["USE_OPENMP"] = Boolean{true};
#else
info["USE_OPENMP"] = Boolean{false};
#endif
#if defined(__GNUC__) && !defined(__clang__)
info["GCC_VERSION"] = std::vector<Json>{Json{Integer{__GNUC__}}, Json{Integer{__GNUC_MINOR__}},
Json{Integer{__GNUC_PATCHLEVEL__}}};
#endif
#if defined(__clang__)
info["CLANG_VERSION"] =
std::vector<Json>{Json{Integer{__clang_major__}}, Json{Integer{__clang_minor__}},
Json{Integer{__clang_patchlevel__}}};
#endif
#if !defined(NDEBUG)
info["DEBUG"] = Boolean{true};
#else
info["DEBUG"] = Boolean{false};
#endif
#if defined(XGBOOST_USE_FEDERATED)
info["USE_FEDERATED"] = Boolean{true};
#else
info["USE_FEDERATED"] = Boolean{false};
#endif
XGBBuildInfoDevice(&info);
auto &out_str = GlobalConfigAPIThreadLocalStore::Get()->ret_str;
Json::Dump(info, &out_str);
*out = out_str.c_str();
API_END();
}
XGB_DLL int XGBRegisterLogCallback(void (*callback)(const char*)) {
API_BEGIN_UNGUARD();
LogCallbackRegistry* registry = LogCallbackRegistryStore::Get();
registry->Register(callback);
API_END();
}
XGB_DLL int XGBSetGlobalConfig(const char* json_str) {
API_BEGIN();
xgboost_CHECK_C_ARG_PTR(json_str);
Json config{Json::Load(StringView{json_str})};
for (auto& items : get<Object>(config)) {
switch (items.second.GetValue().Type()) {
case xgboost::Value::ValueKind::kInteger: {
items.second = String{std::to_string(get<Integer const>(items.second))};
break;
}
case xgboost::Value::ValueKind::kBoolean: {
if (get<Boolean const>(items.second)) {
items.second = String{"true"};
} else {
items.second = String{"false"};
}
break;
}
case xgboost::Value::ValueKind::kNumber: {
auto n = get<Number const>(items.second);
char chars[NumericLimits<float>::kToCharsSize];
auto ec = to_chars(chars, chars + sizeof(chars), n).ec;
CHECK(ec == std::errc());
items.second = String{chars};
break;
}
default:
break;
}
}
auto unknown = FromJson(config, GlobalConfigThreadLocalStore::Get());
if (!unknown.empty()) {
std::stringstream ss;
ss << "Unknown global parameters: { ";
size_t i = 0;
for (auto const& item : unknown) {
ss << item.first;
i++;
if (i != unknown.size()) {
ss << ", ";
}
}
LOG(FATAL) << ss.str() << " }";
}
API_END();
}
XGB_DLL int XGBGetGlobalConfig(const char** json_str) {
API_BEGIN();
auto const& global_config = *GlobalConfigThreadLocalStore::Get();
Json config {ToJson(global_config)};
auto const* mgr = global_config.__MANAGER__();
for (auto& item : get<Object>(config)) {
auto const &str = get<String const>(item.second);
auto const &name = item.first;
auto e = mgr->Find(name);
CHECK(e);
if (dynamic_cast<dmlc::parameter::FieldEntry<int32_t> const*>(e) ||
dynamic_cast<dmlc::parameter::FieldEntry<int64_t> const*>(e) ||
dynamic_cast<dmlc::parameter::FieldEntry<uint32_t> const*>(e) ||
dynamic_cast<dmlc::parameter::FieldEntry<uint64_t> const*>(e)) {
auto i = std::strtoimax(str.data(), nullptr, 10);
CHECK_LE(i, static_cast<intmax_t>(std::numeric_limits<int64_t>::max()));
item.second = Integer(static_cast<int64_t>(i));
} else if (dynamic_cast<dmlc::parameter::FieldEntry<float> const *>(e) ||
dynamic_cast<dmlc::parameter::FieldEntry<double> const *>(e)) {
float f;
auto ec = from_chars(str.data(), str.data() + str.size(), f).ec;
CHECK(ec == std::errc());
item.second = Number(f);
} else if (dynamic_cast<dmlc::parameter::FieldEntry<bool> const *>(e)) {
item.second = Boolean(str != "0");
}
}
auto& local = *GlobalConfigAPIThreadLocalStore::Get();
Json::Dump(config, &local.ret_str);
xgboost_CHECK_C_ARG_PTR(json_str);
*json_str = local.ret_str.c_str();
API_END();
}
XGB_DLL int XGDMatrixCreateFromFile(const char *fname, int silent, DMatrixHandle *out) {
xgboost_CHECK_C_ARG_PTR(fname);
xgboost_CHECK_C_ARG_PTR(out);
Json config{Object()};
config["uri"] = std::string{fname};
config["silent"] = silent;
std::string config_str;
Json::Dump(config, &config_str);
return XGDMatrixCreateFromURI(config_str.c_str(), out);
}
XGB_DLL int XGDMatrixCreateFromURI(const char *config, DMatrixHandle *out) {
API_BEGIN();
xgboost_CHECK_C_ARG_PTR(config);
xgboost_CHECK_C_ARG_PTR(out);
auto jconfig = Json::Load(StringView{config});
std::string uri = RequiredArg<String>(jconfig, "uri", __func__);
auto silent = static_cast<bool>(OptionalArg<Integer, int64_t>(jconfig, "silent", 1));
auto data_split_mode =
static_cast<DataSplitMode>(OptionalArg<Integer, int64_t>(jconfig, "data_split_mode", 0));
*out = new std::shared_ptr<DMatrix>(DMatrix::Load(uri, silent, data_split_mode));
API_END();
}
XGB_DLL int XGDMatrixCreateFromDataIter(
void *data_handle, // a Java iterator
XGBCallbackDataIterNext *callback, // C++ callback defined in xgboost4j.cpp
const char *cache_info, DMatrixHandle *out) {
API_BEGIN();
std::string scache;
if (cache_info != nullptr) {
scache = cache_info;
}
xgboost::data::IteratorAdapter<DataIterHandle, XGBCallbackDataIterNext,
XGBoostBatchCSR> adapter(data_handle, callback);
xgboost_CHECK_C_ARG_PTR(out);
*out = new std::shared_ptr<DMatrix> {
DMatrix::Create(
&adapter, std::numeric_limits<float>::quiet_NaN(),
1, scache
)
};
API_END();
}
#ifndef XGBOOST_USE_CUDA
XGB_DLL int XGDMatrixCreateFromCudaColumnar(char const *, char const *, DMatrixHandle *) {
API_BEGIN();
common::AssertGPUSupport();
API_END();
}
XGB_DLL int XGDMatrixCreateFromCudaArrayInterface(char const *, char const *, DMatrixHandle *) {
API_BEGIN();
common::AssertGPUSupport();
API_END();
}
#endif
// Create from data iterator
XGB_DLL int XGDMatrixCreateFromCallback(DataIterHandle iter, DMatrixHandle proxy,
DataIterResetCallback *reset, XGDMatrixCallbackNext *next,
char const *config, DMatrixHandle *out) {
API_BEGIN();
xgboost_CHECK_C_ARG_PTR(config);
auto jconfig = Json::Load(StringView{config});
auto missing = GetMissing(jconfig);
std::string cache = RequiredArg<String>(jconfig, "cache_prefix", __func__);
auto n_threads = OptionalArg<Integer, int64_t>(jconfig, "nthread", 0);
xgboost_CHECK_C_ARG_PTR(next);
xgboost_CHECK_C_ARG_PTR(reset);
xgboost_CHECK_C_ARG_PTR(out);
*out = new std::shared_ptr<xgboost::DMatrix>{
xgboost::DMatrix::Create(iter, proxy, reset, next, missing, n_threads, cache)};
API_END();
}
XGB_DLL int XGDeviceQuantileDMatrixCreateFromCallback(DataIterHandle iter, DMatrixHandle proxy,
DataIterResetCallback *reset,
XGDMatrixCallbackNext *next, float missing,
int nthread, int max_bin,
DMatrixHandle *out) {
API_BEGIN();
DeprecatedFunc(__func__, "1.7.0", "XGQuantileDMatrixCreateFromCallback");
*out = new std::shared_ptr<xgboost::DMatrix>{
xgboost::DMatrix::Create(iter, proxy, nullptr, reset, next, missing, nthread, max_bin)};
API_END();
}
XGB_DLL int XGQuantileDMatrixCreateFromCallback(DataIterHandle iter, DMatrixHandle proxy,
DataIterHandle ref, DataIterResetCallback *reset,
XGDMatrixCallbackNext *next, char const *config,
DMatrixHandle *out) {
API_BEGIN();
std::shared_ptr<DMatrix> _ref{nullptr};
if (ref) {
auto pp_ref = static_cast<std::shared_ptr<xgboost::DMatrix> *>(ref);
StringView err{"Invalid handle to ref."};
CHECK(pp_ref) << err;
_ref = *pp_ref;
CHECK(_ref) << err;
}
xgboost_CHECK_C_ARG_PTR(config);
auto jconfig = Json::Load(StringView{config});
auto missing = GetMissing(jconfig);
auto n_threads = OptionalArg<Integer, int64_t>(jconfig, "nthread", 0);
auto max_bin = OptionalArg<Integer, int64_t>(jconfig, "max_bin", 256);
xgboost_CHECK_C_ARG_PTR(next);
xgboost_CHECK_C_ARG_PTR(reset);
xgboost_CHECK_C_ARG_PTR(out);
*out = new std::shared_ptr<xgboost::DMatrix>{
xgboost::DMatrix::Create(iter, proxy, _ref, reset, next, missing, n_threads, max_bin)};
API_END();
}
XGB_DLL int XGProxyDMatrixCreate(DMatrixHandle* out) {
API_BEGIN();
xgboost_CHECK_C_ARG_PTR(out);
*out = new std::shared_ptr<xgboost::DMatrix>(new xgboost::data::DMatrixProxy);;
API_END();
}
XGB_DLL int
XGProxyDMatrixSetDataCudaArrayInterface(DMatrixHandle handle,
char const *c_interface_str) {
API_BEGIN();
CHECK_HANDLE();
xgboost_CHECK_C_ARG_PTR(c_interface_str);
auto p_m = static_cast<std::shared_ptr<xgboost::DMatrix> *>(handle);
CHECK(p_m);
auto m = static_cast<xgboost::data::DMatrixProxy*>(p_m->get());
CHECK(m) << "Current DMatrix type does not support set data.";
m->SetCUDAArray(c_interface_str);
API_END();
}
XGB_DLL int XGProxyDMatrixSetDataCudaColumnar(DMatrixHandle handle,
char const *c_interface_str) {
API_BEGIN();
CHECK_HANDLE();
xgboost_CHECK_C_ARG_PTR(c_interface_str);
auto p_m = static_cast<std::shared_ptr<xgboost::DMatrix> *>(handle);
CHECK(p_m);
auto m = static_cast<xgboost::data::DMatrixProxy*>(p_m->get());
CHECK(m) << "Current DMatrix type does not support set data.";
m->SetCUDAArray(c_interface_str);
API_END();
}
XGB_DLL int XGProxyDMatrixSetDataDense(DMatrixHandle handle,
char const *c_interface_str) {
API_BEGIN();
CHECK_HANDLE();
xgboost_CHECK_C_ARG_PTR(c_interface_str);
auto p_m = static_cast<std::shared_ptr<xgboost::DMatrix> *>(handle);
CHECK(p_m);
auto m = static_cast<xgboost::data::DMatrixProxy*>(p_m->get());
CHECK(m) << "Current DMatrix type does not support set data.";
m->SetArrayData(c_interface_str);
API_END();
}
XGB_DLL int XGProxyDMatrixSetDataCSR(DMatrixHandle handle, char const *indptr,
char const *indices, char const *data,
xgboost::bst_ulong ncol) {
API_BEGIN();
CHECK_HANDLE();
xgboost_CHECK_C_ARG_PTR(indptr);
xgboost_CHECK_C_ARG_PTR(indices);
xgboost_CHECK_C_ARG_PTR(data);
auto p_m = static_cast<std::shared_ptr<xgboost::DMatrix> *>(handle);
CHECK(p_m);
auto m = static_cast<xgboost::data::DMatrixProxy*>(p_m->get());
CHECK(m) << "Current DMatrix type does not support set data.";
m->SetCSRData(indptr, indices, data, ncol, true);
API_END();
}
// End Create from data iterator
XGB_DLL int XGDMatrixCreateFromCSREx(const size_t *indptr, const unsigned *indices,
const bst_float *data, size_t nindptr, size_t nelem,
size_t num_col, DMatrixHandle *out) {
API_BEGIN();
DeprecatedFunc(__func__, "2.0.0", "XGDMatrixCreateFromCSR");
data::CSRAdapter adapter(indptr, indices, data, nindptr - 1, nelem, num_col);
*out = new std::shared_ptr<DMatrix>(DMatrix::Create(&adapter, std::nan(""), 1));
API_END();
}
XGB_DLL int XGDMatrixCreateFromCSR(char const *indptr, char const *indices, char const *data,
xgboost::bst_ulong ncol, char const *c_json_config,
DMatrixHandle *out) {
API_BEGIN();
xgboost_CHECK_C_ARG_PTR(indptr);
xgboost_CHECK_C_ARG_PTR(indices);
xgboost_CHECK_C_ARG_PTR(data);
data::CSRArrayAdapter adapter(StringView{indptr}, StringView{indices}, StringView{data}, ncol);
xgboost_CHECK_C_ARG_PTR(c_json_config);
auto config = Json::Load(StringView{c_json_config});
float missing = GetMissing(config);
auto n_threads = OptionalArg<Integer, int64_t>(config, "nthread", 0);
xgboost_CHECK_C_ARG_PTR(out);
*out = new std::shared_ptr<DMatrix>(DMatrix::Create(&adapter, missing, n_threads));
API_END();
}
XGB_DLL int XGDMatrixCreateFromDense(char const *data,
char const *c_json_config,
DMatrixHandle *out) {
API_BEGIN();
xgboost_CHECK_C_ARG_PTR(data);
xgboost::data::ArrayAdapter adapter{xgboost::data::ArrayAdapter(StringView{data})};
xgboost_CHECK_C_ARG_PTR(c_json_config);
auto config = Json::Load(StringView{c_json_config});
float missing = GetMissing(config);
auto n_threads = OptionalArg<Integer, int64_t>(config, "nthread", 0);
xgboost_CHECK_C_ARG_PTR(out);
*out = new std::shared_ptr<DMatrix>(DMatrix::Create(&adapter, missing, n_threads));
API_END();
}
XGB_DLL int XGDMatrixCreateFromCSC(char const *indptr, char const *indices, char const *data,
xgboost::bst_ulong nrow, char const *c_json_config,
DMatrixHandle *out) {
API_BEGIN();
xgboost_CHECK_C_ARG_PTR(indptr);
xgboost_CHECK_C_ARG_PTR(indices);
xgboost_CHECK_C_ARG_PTR(data);
data::CSCArrayAdapter adapter{StringView{indptr}, StringView{indices}, StringView{data}, nrow};
xgboost_CHECK_C_ARG_PTR(c_json_config);
auto config = Json::Load(StringView{c_json_config});
float missing = GetMissing(config);
auto n_threads = OptionalArg<Integer, int64_t>(config, "nthread", common::OmpGetNumThreads(0));
xgboost_CHECK_C_ARG_PTR(out);
*out = new std::shared_ptr<DMatrix>(DMatrix::Create(&adapter, missing, n_threads));
API_END();
}
XGB_DLL int XGDMatrixCreateFromCSCEx(const size_t *col_ptr, const unsigned *indices,
const bst_float *data, size_t nindptr, size_t, size_t num_row,
DMatrixHandle *out) {
API_BEGIN();
DeprecatedFunc(__func__, "2.0.0", "XGDMatrixCreateFromCSC");
data::CSCAdapter adapter(col_ptr, indices, data, nindptr - 1, num_row);
xgboost_CHECK_C_ARG_PTR(out);
*out = new std::shared_ptr<DMatrix>(DMatrix::Create(&adapter, std::nan(""), 1));
API_END();
}
XGB_DLL int XGDMatrixCreateFromMat(const bst_float* data,
xgboost::bst_ulong nrow,
xgboost::bst_ulong ncol, bst_float missing,
DMatrixHandle* out) {
API_BEGIN();
data::DenseAdapter adapter(data, nrow, ncol);
xgboost_CHECK_C_ARG_PTR(out);
*out = new std::shared_ptr<DMatrix>(DMatrix::Create(&adapter, missing, 1));
API_END();
}
XGB_DLL int XGDMatrixCreateFromMat_omp(const bst_float* data, // NOLINT
xgboost::bst_ulong nrow,
xgboost::bst_ulong ncol,
bst_float missing, DMatrixHandle* out,
int nthread) {
API_BEGIN();
data::DenseAdapter adapter(data, nrow, ncol);
xgboost_CHECK_C_ARG_PTR(out);
*out = new std::shared_ptr<DMatrix>(DMatrix::Create(&adapter, missing, nthread));
API_END();
}
XGB_DLL int XGDMatrixCreateFromDT(void** data, const char** feature_stypes,
xgboost::bst_ulong nrow,
xgboost::bst_ulong ncol, DMatrixHandle* out,
int nthread) {
API_BEGIN();
data::DataTableAdapter adapter(data, feature_stypes, nrow, ncol);
xgboost_CHECK_C_ARG_PTR(out);
*out = new std::shared_ptr<DMatrix>(DMatrix::Create(&adapter, std::nan(""), nthread));
API_END();
}
XGB_DLL int XGImportArrowRecordBatch(DataIterHandle data_handle, void *ptr_array,
void *ptr_schema) {
API_BEGIN();
static_cast<data::RecordBatchesIterAdapter *>(data_handle)
->SetData(static_cast<struct ArrowArray *>(ptr_array),
static_cast<struct ArrowSchema *>(ptr_schema));
API_END();
}
XGB_DLL int XGDMatrixCreateFromArrowCallback(XGDMatrixCallbackNext *next, char const *config,
DMatrixHandle *out) {
API_BEGIN();
xgboost_CHECK_C_ARG_PTR(config);
auto jconfig = Json::Load(StringView{config});
auto missing = GetMissing(jconfig);
auto n_batches = RequiredArg<Integer>(jconfig, "nbatch", __func__);
auto n_threads = OptionalArg<Integer, std::int64_t>(jconfig, "nthread", 0);
data::RecordBatchesIterAdapter adapter(next, n_batches);
xgboost_CHECK_C_ARG_PTR(out);
*out = new std::shared_ptr<DMatrix>(DMatrix::Create(&adapter, missing, n_threads));
API_END();
}
XGB_DLL int XGDMatrixSliceDMatrix(DMatrixHandle handle,
const int* idxset,
xgboost::bst_ulong len,
DMatrixHandle* out) {
xgboost_CHECK_C_ARG_PTR(out);
return XGDMatrixSliceDMatrixEx(handle, idxset, len, out, 0);
}
XGB_DLL int XGDMatrixSliceDMatrixEx(DMatrixHandle handle,
const int* idxset,
xgboost::bst_ulong len,
DMatrixHandle* out,
int allow_groups) {
API_BEGIN();
CHECK_HANDLE();
if (!allow_groups) {
CHECK_EQ(static_cast<std::shared_ptr<DMatrix>*>(handle)
->get()
->Info()
.group_ptr_.size(),
0U)
<< "slice does not support group structure";
}
DMatrix* dmat = static_cast<std::shared_ptr<DMatrix>*>(handle)->get();
*out = new std::shared_ptr<DMatrix>(
dmat->Slice({idxset, static_cast<std::size_t>(len)}));
API_END();
}
XGB_DLL int XGDMatrixFree(DMatrixHandle handle) {
API_BEGIN();
CHECK_HANDLE();
delete static_cast<std::shared_ptr<DMatrix>*>(handle);
API_END();
}
XGB_DLL int XGDMatrixSaveBinary(DMatrixHandle handle, const char* fname,
int) {
API_BEGIN();
CHECK_HANDLE();
auto dmat = static_cast<std::shared_ptr<DMatrix>*>(handle)->get();
xgboost_CHECK_C_ARG_PTR(fname);
if (data::SimpleDMatrix* derived = dynamic_cast<data::SimpleDMatrix*>(dmat)) {
derived->SaveToLocalFile(fname);
} else {
LOG(FATAL) << "binary saving only supported by SimpleDMatrix";
}
API_END();
}
XGB_DLL int XGDMatrixSetFloatInfo(DMatrixHandle handle, const char *field, const bst_float *info,
xgboost::bst_ulong len) {
API_BEGIN();
CHECK_HANDLE();
xgboost_CHECK_C_ARG_PTR(field);
auto const& p_fmat = *static_cast<std::shared_ptr<DMatrix> *>(handle);
p_fmat->SetInfo(field, info, xgboost::DataType::kFloat32, len);
API_END();
}
XGB_DLL int XGDMatrixSetInfoFromInterface(DMatrixHandle handle, char const *field,
char const *interface_c_str) {
API_BEGIN();
CHECK_HANDLE();
xgboost_CHECK_C_ARG_PTR(field);
auto const &p_fmat = *static_cast<std::shared_ptr<DMatrix> *>(handle);
p_fmat->SetInfo(field, interface_c_str);
API_END();
}
XGB_DLL int XGDMatrixSetUIntInfo(DMatrixHandle handle, const char *field, const unsigned *info,
xgboost::bst_ulong len) {
API_BEGIN();
CHECK_HANDLE();
xgboost_CHECK_C_ARG_PTR(field);
auto const &p_fmat = *static_cast<std::shared_ptr<DMatrix> *>(handle);
p_fmat->SetInfo(field, info, xgboost::DataType::kUInt32, len);
API_END();
}
XGB_DLL int XGDMatrixSetStrFeatureInfo(DMatrixHandle handle, const char *field,
const char **c_info,
const xgboost::bst_ulong size) {
API_BEGIN();
CHECK_HANDLE();
auto &info = static_cast<std::shared_ptr<DMatrix> *>(handle)->get()->Info();
xgboost_CHECK_C_ARG_PTR(field);
info.SetFeatureInfo(field, c_info, size);
API_END();
}
XGB_DLL int XGDMatrixGetStrFeatureInfo(DMatrixHandle handle, const char *field,
xgboost::bst_ulong *len,
const char ***out_features) {
API_BEGIN();
CHECK_HANDLE();
auto m = *static_cast<std::shared_ptr<DMatrix>*>(handle);
auto &info = static_cast<std::shared_ptr<DMatrix> *>(handle)->get()->Info();
std::vector<const char *> &charp_vecs = m->GetThreadLocal().ret_vec_charp;
std::vector<std::string> &str_vecs = m->GetThreadLocal().ret_vec_str;
xgboost_CHECK_C_ARG_PTR(field);
info.GetFeatureInfo(field, &str_vecs);
charp_vecs.resize(str_vecs.size());
for (size_t i = 0; i < str_vecs.size(); ++i) {
charp_vecs[i] = str_vecs[i].c_str();
}
xgboost_CHECK_C_ARG_PTR(out_features);
xgboost_CHECK_C_ARG_PTR(len);
*out_features = dmlc::BeginPtr(charp_vecs);
*len = static_cast<xgboost::bst_ulong>(charp_vecs.size());
API_END();
}
XGB_DLL int XGDMatrixSetDenseInfo(DMatrixHandle handle, const char *field, void const *data,
xgboost::bst_ulong size, int type) {
API_BEGIN();
CHECK_HANDLE();
auto const &p_fmat = *static_cast<std::shared_ptr<DMatrix> *>(handle);
CHECK(type >= 1 && type <= 4);
xgboost_CHECK_C_ARG_PTR(field);
p_fmat->SetInfo(field, data, static_cast<DataType>(type), size);
API_END();
}
XGB_DLL int XGDMatrixSetGroup(DMatrixHandle handle, const unsigned *group, xgboost::bst_ulong len) {
API_BEGIN();
CHECK_HANDLE();
LOG(WARNING) << "XGDMatrixSetGroup is deprecated, use `XGDMatrixSetUIntInfo` instead.";
auto const &p_fmat = *static_cast<std::shared_ptr<DMatrix> *>(handle);
p_fmat->SetInfo("group", group, xgboost::DataType::kUInt32, len);
API_END();
}
XGB_DLL int XGDMatrixGetFloatInfo(const DMatrixHandle handle,
const char* field,
xgboost::bst_ulong* out_len,
const bst_float** out_dptr) {
API_BEGIN();
CHECK_HANDLE();
xgboost_CHECK_C_ARG_PTR(field);
const MetaInfo& info = static_cast<std::shared_ptr<DMatrix>*>(handle)->get()->Info();
xgboost_CHECK_C_ARG_PTR(out_len);
xgboost_CHECK_C_ARG_PTR(out_dptr);
info.GetInfo(field, out_len, DataType::kFloat32, reinterpret_cast<void const**>(out_dptr));
API_END();
}
XGB_DLL int XGDMatrixGetUIntInfo(const DMatrixHandle handle,
const char *field,
xgboost::bst_ulong *out_len,
const unsigned **out_dptr) {
API_BEGIN();
CHECK_HANDLE();
xgboost_CHECK_C_ARG_PTR(field);
const MetaInfo& info = static_cast<std::shared_ptr<DMatrix>*>(handle)->get()->Info();
xgboost_CHECK_C_ARG_PTR(out_len);
xgboost_CHECK_C_ARG_PTR(out_dptr);
info.GetInfo(field, out_len, DataType::kUInt32, reinterpret_cast<void const**>(out_dptr));
API_END();
}
XGB_DLL int XGDMatrixNumRow(const DMatrixHandle handle,
xgboost::bst_ulong *out) {
API_BEGIN();
CHECK_HANDLE();
auto p_m = CastDMatrixHandle(handle);
xgboost_CHECK_C_ARG_PTR(out);
*out = static_cast<xgboost::bst_ulong>(p_m->Info().num_row_);
API_END();
}
XGB_DLL int XGDMatrixNumCol(const DMatrixHandle handle,
xgboost::bst_ulong *out) {
API_BEGIN();
CHECK_HANDLE();
auto p_m = CastDMatrixHandle(handle);
xgboost_CHECK_C_ARG_PTR(out);
*out = static_cast<xgboost::bst_ulong>(p_m->Info().num_col_);
API_END();
}
// We name the function non-missing instead of non-zero since zero is perfectly valid for XGBoost.
XGB_DLL int XGDMatrixNumNonMissing(DMatrixHandle const handle, xgboost::bst_ulong *out) {
API_BEGIN();
CHECK_HANDLE();
auto p_m = CastDMatrixHandle(handle);
xgboost_CHECK_C_ARG_PTR(out);
*out = static_cast<xgboost::bst_ulong>(p_m->Info().num_nonzero_);
API_END();
}
XGB_DLL int XGDMatrixGetDataAsCSR(DMatrixHandle const handle, char const *config,
xgboost::bst_ulong *out_indptr, unsigned *out_indices,
float *out_data) {
API_BEGIN();
CHECK_HANDLE();
xgboost_CHECK_C_ARG_PTR(config);
auto jconfig = Json::Load(StringView{config});
auto p_m = CastDMatrixHandle(handle);
xgboost_CHECK_C_ARG_PTR(out_indptr);
xgboost_CHECK_C_ARG_PTR(out_indices);
xgboost_CHECK_C_ARG_PTR(out_data);
CHECK_LE(p_m->Info().num_col_, std::numeric_limits<unsigned>::max());
for (auto const &page : p_m->GetBatches<ExtSparsePage>()) {
CHECK(page.page);
auto const &h_offset = page.page->offset.ConstHostVector();
std::copy(h_offset.cbegin(), h_offset.cend(), out_indptr);
auto pv = page.page->GetView();
common::ParallelFor(page.page->data.Size(), p_m->Ctx()->Threads(), [&](std::size_t i) {
auto fvalue = pv.data[i].fvalue;
auto findex = pv.data[i].index;
out_data[i] = fvalue;
out_indices[i] = findex;
});
}
API_END();
}
// xgboost implementation
XGB_DLL int XGBoosterCreate(const DMatrixHandle dmats[],
xgboost::bst_ulong len,
BoosterHandle *out) {
API_BEGIN();
std::vector<std::shared_ptr<DMatrix> > mats;
for (xgboost::bst_ulong i = 0; i < len; ++i) {
xgboost_CHECK_C_ARG_PTR(dmats);
mats.push_back(*static_cast<std::shared_ptr<DMatrix>*>(dmats[i]));
}
xgboost_CHECK_C_ARG_PTR(out);
*out = Learner::Create(mats);
API_END();
}
XGB_DLL int XGBoosterFree(BoosterHandle handle) {
API_BEGIN();
CHECK_HANDLE();
delete static_cast<Learner*>(handle);
API_END();
}
XGB_DLL int XGBoosterSetParam(BoosterHandle handle,
const char *name,
const char *value) {
API_BEGIN();
CHECK_HANDLE();
static_cast<Learner*>(handle)->SetParam(name, value);
API_END();
}
XGB_DLL int XGBoosterGetNumFeature(BoosterHandle handle,
xgboost::bst_ulong *out) {
API_BEGIN();
CHECK_HANDLE();
static_cast<Learner*>(handle)->Configure();
xgboost_CHECK_C_ARG_PTR(out);
*out = static_cast<Learner*>(handle)->GetNumFeature();
API_END();
}
XGB_DLL int XGBoosterBoostedRounds(BoosterHandle handle, int* out) {
API_BEGIN();
CHECK_HANDLE();
static_cast<Learner*>(handle)->Configure();
xgboost_CHECK_C_ARG_PTR(out);
*out = static_cast<Learner*>(handle)->BoostedRounds();
API_END();
}
XGB_DLL int XGBoosterLoadJsonConfig(BoosterHandle handle, char const* json_parameters) {
API_BEGIN();
CHECK_HANDLE();
xgboost_CHECK_C_ARG_PTR(json_parameters);
Json config { Json::Load(StringView{json_parameters}) };
static_cast<Learner*>(handle)->LoadConfig(config);
API_END();
}
XGB_DLL int XGBoosterSaveJsonConfig(BoosterHandle handle,
xgboost::bst_ulong *out_len,
char const** out_str) {
API_BEGIN();
CHECK_HANDLE();
Json config { Object() };
auto* learner = static_cast<Learner*>(handle);
learner->Configure();
learner->SaveConfig(&config);
std::string& raw_str = learner->GetThreadLocal().ret_str;
Json::Dump(config, &raw_str);
xgboost_CHECK_C_ARG_PTR(out_str);
xgboost_CHECK_C_ARG_PTR(out_len);
*out_str = raw_str.c_str();
*out_len = static_cast<xgboost::bst_ulong>(raw_str.length());
API_END();
}
XGB_DLL int XGBoosterUpdateOneIter(BoosterHandle handle,
int iter,
DMatrixHandle dtrain) {
API_BEGIN();
CHECK_HANDLE();
auto* bst = static_cast<Learner*>(handle);
xgboost_CHECK_C_ARG_PTR(dtrain);
auto *dtr = static_cast<std::shared_ptr<DMatrix> *>(dtrain);
CHECK(dtr);
bst->UpdateOneIter(iter, *dtr);
API_END();
}
XGB_DLL int XGBoosterBoostOneIter(BoosterHandle handle,
DMatrixHandle dtrain,
bst_float *grad,
bst_float *hess,
xgboost::bst_ulong len) {
API_BEGIN();
CHECK_HANDLE();
HostDeviceVector<GradientPair> tmp_gpair;
auto* bst = static_cast<Learner*>(handle);
auto* dtr =
static_cast<std::shared_ptr<DMatrix>*>(dtrain);
tmp_gpair.Resize(len);
std::vector<GradientPair>& tmp_gpair_h = tmp_gpair.HostVector();
if (len > 0) {
xgboost_CHECK_C_ARG_PTR(grad);
xgboost_CHECK_C_ARG_PTR(hess);
}
for (xgboost::bst_ulong i = 0; i < len; ++i) {
tmp_gpair_h[i] = GradientPair(grad[i], hess[i]);
}
bst->BoostOneIter(0, *dtr, &tmp_gpair);
API_END();
}
XGB_DLL int XGBoosterEvalOneIter(BoosterHandle handle,
int iter,
DMatrixHandle dmats[],
const char* evnames[],
xgboost::bst_ulong len,
const char** out_str) {
API_BEGIN();
CHECK_HANDLE();
auto* bst = static_cast<Learner*>(handle);
std::string& eval_str = bst->GetThreadLocal().ret_str;
std::vector<std::shared_ptr<DMatrix>> data_sets;
std::vector<std::string> data_names;
for (xgboost::bst_ulong i = 0; i < len; ++i) {
xgboost_CHECK_C_ARG_PTR(dmats);
data_sets.push_back(*static_cast<std::shared_ptr<DMatrix>*>(dmats[i]));
xgboost_CHECK_C_ARG_PTR(evnames);
data_names.emplace_back(evnames[i]);
}
eval_str = bst->EvalOneIter(iter, data_sets, data_names);
xgboost_CHECK_C_ARG_PTR(out_str);
*out_str = eval_str.c_str();
API_END();
}
XGB_DLL int XGBoosterPredict(BoosterHandle handle,
DMatrixHandle dmat,
int option_mask,
unsigned ntree_limit,
int training,
xgboost::bst_ulong *len,
const bst_float **out_result) {
API_BEGIN();
CHECK_HANDLE();
auto *learner = static_cast<Learner*>(handle);
auto& entry = learner->GetThreadLocal().prediction_entry;
auto iteration_end = GetIterationFromTreeLimit(ntree_limit, learner);
learner->Predict(*static_cast<std::shared_ptr<DMatrix> *>(dmat),
(option_mask & 1) != 0, &entry.predictions, 0, iteration_end,
static_cast<bool>(training), (option_mask & 2) != 0,
(option_mask & 4) != 0, (option_mask & 8) != 0,
(option_mask & 16) != 0);
xgboost_CHECK_C_ARG_PTR(len);
xgboost_CHECK_C_ARG_PTR(out_result);
*out_result = dmlc::BeginPtr(entry.predictions.ConstHostVector());
*len = static_cast<xgboost::bst_ulong>(entry.predictions.Size());
API_END();
}
XGB_DLL int XGBoosterPredictFromDMatrix(BoosterHandle handle,
DMatrixHandle dmat,
char const* c_json_config,
xgboost::bst_ulong const **out_shape,
xgboost::bst_ulong *out_dim,
bst_float const **out_result) {
API_BEGIN();
if (handle == nullptr) {
LOG(FATAL) << "Booster has not been initialized or has already been disposed.";
}
if (dmat == nullptr) {
LOG(FATAL) << "DMatrix has not been initialized or has already been disposed.";
}
xgboost_CHECK_C_ARG_PTR(c_json_config);
auto config = Json::Load(StringView{c_json_config});
auto *learner = static_cast<Learner*>(handle);
auto& entry = learner->GetThreadLocal().prediction_entry;
auto p_m = *static_cast<std::shared_ptr<DMatrix> *>(dmat);
auto type = PredictionType(RequiredArg<Integer>(config, "type", __func__));
auto iteration_begin = RequiredArg<Integer>(config, "iteration_begin", __func__);
auto iteration_end = RequiredArg<Integer>(config, "iteration_end", __func__);
auto const& j_config = get<Object const>(config);
auto ntree_limit_it = j_config.find("ntree_limit");
if (ntree_limit_it != j_config.cend() && !IsA<Null>(ntree_limit_it->second) &&
get<Integer const>(ntree_limit_it->second) != 0) {
CHECK(iteration_end == 0) <<
"Only one of the `ntree_limit` or `iteration_range` can be specified.";
LOG(WARNING) << "`ntree_limit` is deprecated, use `iteration_range` instead.";
iteration_end = GetIterationFromTreeLimit(get<Integer const>(ntree_limit_it->second), learner);
}
bool approximate = type == PredictionType::kApproxContribution ||
type == PredictionType::kApproxInteraction;
bool contribs = type == PredictionType::kContribution ||
type == PredictionType::kApproxContribution;
bool interactions = type == PredictionType::kInteraction ||
type == PredictionType::kApproxInteraction;
bool training = RequiredArg<Boolean>(config, "training", __func__);
learner->Predict(p_m, type == PredictionType::kMargin, &entry.predictions,
iteration_begin, iteration_end, training,
type == PredictionType::kLeaf, contribs, approximate,
interactions);
xgboost_CHECK_C_ARG_PTR(out_result);
*out_result = dmlc::BeginPtr(entry.predictions.ConstHostVector());
auto &shape = learner->GetThreadLocal().prediction_shape;
auto chunksize = p_m->Info().num_row_ == 0 ? 0 : entry.predictions.Size() / p_m->Info().num_row_;
auto rounds = iteration_end - iteration_begin;
rounds = rounds == 0 ? learner->BoostedRounds() : rounds;
// Determine shape
bool strict_shape = RequiredArg<Boolean>(config, "strict_shape", __func__);
xgboost_CHECK_C_ARG_PTR(out_dim);
xgboost_CHECK_C_ARG_PTR(out_shape);
CalcPredictShape(strict_shape, type, p_m->Info().num_row_,
p_m->Info().num_col_, chunksize, learner->Groups(), rounds,
&shape, out_dim);
*out_shape = dmlc::BeginPtr(shape);
API_END();
}
void InplacePredictImpl(std::shared_ptr<DMatrix> p_m, char const *c_json_config, Learner *learner,
xgboost::bst_ulong const **out_shape, xgboost::bst_ulong *out_dim,
const float **out_result) {
xgboost_CHECK_C_ARG_PTR(c_json_config);
auto config = Json::Load(StringView{c_json_config});
CHECK_EQ(get<Integer const>(config["cache_id"]), 0) << "Cache ID is not supported yet";
HostDeviceVector<float> *p_predt{nullptr};
auto type = PredictionType(RequiredArg<Integer>(config, "type", __func__));
float missing = GetMissing(config);
learner->InplacePredict(p_m, type, missing, &p_predt,
RequiredArg<Integer>(config, "iteration_begin", __func__),
RequiredArg<Integer>(config, "iteration_end", __func__));
CHECK(p_predt);
auto &shape = learner->GetThreadLocal().prediction_shape;
auto const &info = p_m->Info();
auto n_samples = info.num_row_;
auto n_features = info.num_col_;
auto chunksize = n_samples == 0 ? 0 : p_predt->Size() / n_samples;
bool strict_shape = RequiredArg<Boolean>(config, "strict_shape", __func__);
xgboost_CHECK_C_ARG_PTR(out_dim);
CalcPredictShape(strict_shape, type, n_samples, n_features, chunksize, learner->Groups(),
learner->BoostedRounds(), &shape, out_dim);
xgboost_CHECK_C_ARG_PTR(out_result);
xgboost_CHECK_C_ARG_PTR(out_shape);
*out_result = dmlc::BeginPtr(p_predt->HostVector());
*out_shape = dmlc::BeginPtr(shape);
}
XGB_DLL int XGBoosterPredictFromDense(BoosterHandle handle, char const *array_interface,
char const *c_json_config, DMatrixHandle m,
xgboost::bst_ulong const **out_shape,
xgboost::bst_ulong *out_dim, const float **out_result) {
API_BEGIN();
CHECK_HANDLE();
std::shared_ptr<DMatrix> p_m{nullptr};
if (!m) {
p_m.reset(new data::DMatrixProxy);
} else {
p_m = *static_cast<std::shared_ptr<DMatrix> *>(m);
}
auto proxy = dynamic_cast<data::DMatrixProxy *>(p_m.get());
CHECK(proxy) << "Invalid input type for inplace predict.";
xgboost_CHECK_C_ARG_PTR(array_interface);
proxy->SetArrayData(array_interface);
auto *learner = static_cast<xgboost::Learner *>(handle);
InplacePredictImpl(p_m, c_json_config, learner, out_shape, out_dim, out_result);
API_END();
}
XGB_DLL int XGBoosterPredictFromCSR(BoosterHandle handle, char const *indptr, char const *indices,
char const *data, xgboost::bst_ulong cols,
char const *c_json_config, DMatrixHandle m,
xgboost::bst_ulong const **out_shape,
xgboost::bst_ulong *out_dim, const float **out_result) {
API_BEGIN();
CHECK_HANDLE();
std::shared_ptr<DMatrix> p_m{nullptr};
if (!m) {
p_m.reset(new data::DMatrixProxy);
} else {
p_m = *static_cast<std::shared_ptr<DMatrix> *>(m);
}
auto proxy = dynamic_cast<data::DMatrixProxy *>(p_m.get());
CHECK(proxy) << "Invalid input type for inplace predict.";
xgboost_CHECK_C_ARG_PTR(indptr);
proxy->SetCSRData(indptr, indices, data, cols, true);
auto *learner = static_cast<xgboost::Learner *>(handle);
InplacePredictImpl(p_m, c_json_config, learner, out_shape, out_dim, out_result);
API_END();
}
#if !defined(XGBOOST_USE_CUDA)
XGB_DLL int XGBoosterPredictFromCUDAArray(BoosterHandle handle, char const *, char const *,
DMatrixHandle, xgboost::bst_ulong const **,
xgboost::bst_ulong *, const float **) {
API_BEGIN();
CHECK_HANDLE();
common::AssertGPUSupport();
API_END();
}
XGB_DLL int XGBoosterPredictFromCUDAColumnar(BoosterHandle handle, char const *, char const *,
DMatrixHandle, xgboost::bst_ulong const **,
xgboost::bst_ulong *, const float **) {
API_BEGIN();
CHECK_HANDLE();
common::AssertGPUSupport();
API_END();
}
#endif // !defined(XGBOOST_USE_CUDA)
XGB_DLL int XGBoosterLoadModel(BoosterHandle handle, const char* fname) {
API_BEGIN();
CHECK_HANDLE();
xgboost_CHECK_C_ARG_PTR(fname);
auto read_file = [&]() {
auto str = common::LoadSequentialFile(fname);
CHECK_GE(str.size(), 3); // "{}\0"
CHECK_EQ(str[0], '{');
return str;
};
if (common::FileExtension(fname) == "json") {
auto str = read_file();
Json in{Json::Load(StringView{str})};
static_cast<Learner*>(handle)->LoadModel(in);
} else if (common::FileExtension(fname) == "ubj") {
auto str = read_file();
Json in = Json::Load(StringView{str}, std::ios::binary);
static_cast<Learner *>(handle)->LoadModel(in);
} else {
std::unique_ptr<dmlc::Stream> fi(dmlc::Stream::Create(fname, "r"));
static_cast<Learner*>(handle)->LoadModel(fi.get());
}
API_END();
}
namespace {
void WarnOldModel() {
if (XGBOOST_VER_MAJOR >= 2) {
LOG(WARNING) << "Saving into deprecated binary model format, please consider using `json` or "
"`ubj`. Model format will default to JSON in XGBoost 2.2 if not specified.";
}
}
} // anonymous namespace
XGB_DLL int XGBoosterSaveModel(BoosterHandle handle, const char *fname) {
API_BEGIN();
CHECK_HANDLE();
xgboost_CHECK_C_ARG_PTR(fname);
std::unique_ptr<dmlc::Stream> fo(dmlc::Stream::Create(fname, "w"));
auto *learner = static_cast<Learner *>(handle);
learner->Configure();
auto save_json = [&](std::ios::openmode mode) {
Json out{Object()};
learner->SaveModel(&out);
std::vector<char> str;
Json::Dump(out, &str, mode);
fo->Write(str.data(), str.size());
};
if (common::FileExtension(fname) == "json") {
save_json(std::ios::out);
} else if (common::FileExtension(fname) == "ubj") {
save_json(std::ios::binary);
} else if (XGBOOST_VER_MAJOR == 2 && XGBOOST_VER_MINOR >= 2) {
LOG(WARNING) << "Saving model to JSON as default. You can use file extension `json`, `ubj` or "
"`deprecated` to choose between formats.";
save_json(std::ios::out);
} else {
WarnOldModel();
auto *bst = static_cast<Learner *>(handle);
bst->SaveModel(fo.get());
}
API_END();
}
XGB_DLL int XGBoosterLoadModelFromBuffer(BoosterHandle handle, const void *buf,
xgboost::bst_ulong len) {
API_BEGIN();
CHECK_HANDLE();
xgboost_CHECK_C_ARG_PTR(buf);
common::MemoryFixSizeBuffer fs((void *)buf, len); // NOLINT(*)
static_cast<Learner *>(handle)->LoadModel(&fs);
API_END();
}
XGB_DLL int XGBoosterSaveModelToBuffer(BoosterHandle handle, char const *json_config,
xgboost::bst_ulong *out_len, char const **out_dptr) {
API_BEGIN();
CHECK_HANDLE();
xgboost_CHECK_C_ARG_PTR(json_config);
xgboost_CHECK_C_ARG_PTR(out_dptr);
xgboost_CHECK_C_ARG_PTR(out_len);
auto config = Json::Load(StringView{json_config});
auto format = RequiredArg<String>(config, "format", __func__);
auto *learner = static_cast<Learner *>(handle);
learner->Configure();
auto save_json = [&](std::ios::openmode mode) {
std::vector<char> &raw_char_vec = learner->GetThreadLocal().ret_char_vec;
Json out{Object{}};
learner->SaveModel(&out);
Json::Dump(out, &raw_char_vec, mode);
*out_dptr = dmlc::BeginPtr(raw_char_vec);
*out_len = static_cast<xgboost::bst_ulong>(raw_char_vec.size());
};
Json out{Object{}};
if (format == "json") {
save_json(std::ios::out);
} else if (format == "ubj") {
save_json(std::ios::binary);
} else if (format == "deprecated") {
WarnOldModel();
auto &raw_str = learner->GetThreadLocal().ret_str;
raw_str.clear();
common::MemoryBufferStream fo(&raw_str);
learner->SaveModel(&fo);
*out_dptr = dmlc::BeginPtr(raw_str);
*out_len = static_cast<xgboost::bst_ulong>(raw_str.size());
} else {
LOG(FATAL) << "Unknown format: `" << format << "`";
}
API_END();
}
XGB_DLL int XGBoosterGetModelRaw(BoosterHandle handle, xgboost::bst_ulong *out_len,
const char **out_dptr) {
API_BEGIN();
CHECK_HANDLE();
auto *learner = static_cast<Learner*>(handle);
std::string& raw_str = learner->GetThreadLocal().ret_str;
raw_str.resize(0);
common::MemoryBufferStream fo(&raw_str);
DeprecatedFunc(__func__, "1.6.0", "XGBoosterSaveModelToBuffer");
learner->Configure();
learner->SaveModel(&fo);
xgboost_CHECK_C_ARG_PTR(out_dptr);
xgboost_CHECK_C_ARG_PTR(out_len);
*out_dptr = dmlc::BeginPtr(raw_str);
*out_len = static_cast<xgboost::bst_ulong>(raw_str.length());
API_END();
}
// The following two functions are `Load` and `Save` for memory based
// serialization methods. E.g. Python pickle.
XGB_DLL int XGBoosterSerializeToBuffer(BoosterHandle handle, xgboost::bst_ulong *out_len,
const char **out_dptr) {
API_BEGIN();
CHECK_HANDLE();
auto *learner = static_cast<Learner *>(handle);
std::string &raw_str = learner->GetThreadLocal().ret_str;
raw_str.resize(0);
common::MemoryBufferStream fo(&raw_str);
learner->Configure();
learner->Save(&fo);
xgboost_CHECK_C_ARG_PTR(out_dptr);
xgboost_CHECK_C_ARG_PTR(out_len);
*out_dptr = dmlc::BeginPtr(raw_str);
*out_len = static_cast<xgboost::bst_ulong>(raw_str.length());
API_END();
}
XGB_DLL int XGBoosterUnserializeFromBuffer(BoosterHandle handle,
const void *buf,
xgboost::bst_ulong len) {
API_BEGIN();
CHECK_HANDLE();
xgboost_CHECK_C_ARG_PTR(buf);
common::MemoryFixSizeBuffer fs((void*)buf, len); // NOLINT(*)
static_cast<Learner*>(handle)->Load(&fs);
API_END();
}
XGB_DLL int XGBoosterLoadRabitCheckpoint(BoosterHandle handle,
int* version) {
API_BEGIN();
CHECK_HANDLE();
auto* bst = static_cast<Learner*>(handle);
xgboost_CHECK_C_ARG_PTR(version);
*version = rabit::LoadCheckPoint();
if (*version != 0) {
bst->Configure();
}
API_END();
}
XGB_DLL int XGBoosterSaveRabitCheckpoint(BoosterHandle handle) {
API_BEGIN();
CHECK_HANDLE();
auto *learner = static_cast<Learner *>(handle);
learner->Configure();
rabit::CheckPoint();
API_END();
}
XGB_DLL int XGBoosterSlice(BoosterHandle handle, int begin_layer,
int end_layer, int step,
BoosterHandle *out) {
API_BEGIN();
CHECK_HANDLE();
xgboost_CHECK_C_ARG_PTR(out);
auto* learner = static_cast<Learner*>(handle);
bool out_of_bound = false;
auto p_out = learner->Slice(begin_layer, end_layer, step, &out_of_bound);
if (out_of_bound) {
return -2;
}
CHECK(p_out);
*out = p_out;
API_END();
}
inline void XGBoostDumpModelImpl(BoosterHandle handle, FeatureMap* fmap,
int with_stats, const char *format,
xgboost::bst_ulong *len,
const char ***out_models) {
auto *bst = static_cast<Learner*>(handle);
bst->Configure();
GenerateFeatureMap(bst, {}, bst->GetNumFeature(), fmap);
std::vector<std::string>& str_vecs = bst->GetThreadLocal().ret_vec_str;
std::vector<const char*>& charp_vecs = bst->GetThreadLocal().ret_vec_charp;
str_vecs = bst->DumpModel(*fmap, with_stats != 0, format);
charp_vecs.resize(str_vecs.size());
for (size_t i = 0; i < str_vecs.size(); ++i) {
charp_vecs[i] = str_vecs[i].c_str();
}
xgboost_CHECK_C_ARG_PTR(out_models);
xgboost_CHECK_C_ARG_PTR(len);
*out_models = dmlc::BeginPtr(charp_vecs);
*len = static_cast<xgboost::bst_ulong>(charp_vecs.size());
}
XGB_DLL int XGBoosterDumpModel(BoosterHandle handle,
const char* fmap,
int with_stats,
xgboost::bst_ulong* len,
const char*** out_models) {
API_BEGIN();
CHECK_HANDLE();
return XGBoosterDumpModelEx(handle, fmap, with_stats, "text", len, out_models);
API_END();
}
XGB_DLL int XGBoosterDumpModelEx(BoosterHandle handle,
const char* fmap,
int with_stats,
const char *format,
xgboost::bst_ulong* len,
const char*** out_models) {
API_BEGIN();
CHECK_HANDLE();
xgboost_CHECK_C_ARG_PTR(fmap);
std::string uri{fmap};
FeatureMap featmap = LoadFeatureMap(uri);
XGBoostDumpModelImpl(handle, &featmap, with_stats, format, len, out_models);
API_END();
}
XGB_DLL int XGBoosterDumpModelWithFeatures(BoosterHandle handle,
int fnum,
const char** fname,
const char** ftype,
int with_stats,
xgboost::bst_ulong* len,
const char*** out_models) {
return XGBoosterDumpModelExWithFeatures(handle, fnum, fname, ftype,
with_stats, "text", len, out_models);
}
XGB_DLL int XGBoosterDumpModelExWithFeatures(BoosterHandle handle,
int fnum,
const char** fname,
const char** ftype,
int with_stats,
const char *format,
xgboost::bst_ulong* len,
const char*** out_models) {
API_BEGIN();
CHECK_HANDLE();
FeatureMap featmap;
for (int i = 0; i < fnum; ++i) {
xgboost_CHECK_C_ARG_PTR(fname);
xgboost_CHECK_C_ARG_PTR(ftype);
featmap.PushBack(i, fname[i], ftype[i]);
}
XGBoostDumpModelImpl(handle, &featmap, with_stats, format, len, out_models);
API_END();
}
XGB_DLL int XGBoosterGetAttr(BoosterHandle handle, const char *key, const char **out,
int *success) {
auto* bst = static_cast<Learner*>(handle);
std::string& ret_str = bst->GetThreadLocal().ret_str;
API_BEGIN();
CHECK_HANDLE();
xgboost_CHECK_C_ARG_PTR(out);
xgboost_CHECK_C_ARG_PTR(success);
if (bst->GetAttr(key, &ret_str)) {
*out = ret_str.c_str();
*success = 1;
} else {
*out = nullptr;
*success = 0;
}
API_END();
}
XGB_DLL int XGBoosterSetAttr(BoosterHandle handle,
const char* key,
const char* value) {
API_BEGIN();
CHECK_HANDLE();
auto* bst = static_cast<Learner*>(handle);
xgboost_CHECK_C_ARG_PTR(key);
if (value == nullptr) {
bst->DelAttr(key);
} else {
xgboost_CHECK_C_ARG_PTR(value);
bst->SetAttr(key, value);
}
API_END();
}
XGB_DLL int XGBoosterGetAttrNames(BoosterHandle handle,
xgboost::bst_ulong* out_len,
const char*** out) {
API_BEGIN();
CHECK_HANDLE();
auto *learner = static_cast<Learner *>(handle);
std::vector<std::string> &str_vecs = learner->GetThreadLocal().ret_vec_str;
std::vector<const char *> &charp_vecs =
learner->GetThreadLocal().ret_vec_charp;
str_vecs = learner->GetAttrNames();
charp_vecs.resize(str_vecs.size());
for (size_t i = 0; i < str_vecs.size(); ++i) {
charp_vecs[i] = str_vecs[i].c_str();
}
xgboost_CHECK_C_ARG_PTR(out);
xgboost_CHECK_C_ARG_PTR(out_len);
*out = dmlc::BeginPtr(charp_vecs);
*out_len = static_cast<xgboost::bst_ulong>(charp_vecs.size());
API_END();
}
XGB_DLL int XGBoosterSetStrFeatureInfo(BoosterHandle handle, const char *field,
const char **features,
const xgboost::bst_ulong size) {
API_BEGIN();
CHECK_HANDLE();
auto *learner = static_cast<Learner *>(handle);
std::vector<std::string> feature_info;
if (size > 0) {
xgboost_CHECK_C_ARG_PTR(features);
}
for (size_t i = 0; i < size; ++i) {
feature_info.emplace_back(features[i]);
}
xgboost_CHECK_C_ARG_PTR(field);
if (!std::strcmp(field, "feature_name")) {
learner->SetFeatureNames(feature_info);
} else if (!std::strcmp(field, "feature_type")) {
learner->SetFeatureTypes(feature_info);
} else {
LOG(FATAL) << "Unknown field for Booster feature info:" << field;
}
API_END();
}
XGB_DLL int XGBoosterGetStrFeatureInfo(BoosterHandle handle, const char *field,
xgboost::bst_ulong *len,
const char ***out_features) {
API_BEGIN();
CHECK_HANDLE();
auto const *learner = static_cast<Learner const *>(handle);
std::vector<const char *> &charp_vecs =
learner->GetThreadLocal().ret_vec_charp;
std::vector<std::string> &str_vecs = learner->GetThreadLocal().ret_vec_str;
if (!std::strcmp(field, "feature_name")) {
learner->GetFeatureNames(&str_vecs);
} else if (!std::strcmp(field, "feature_type")) {
learner->GetFeatureTypes(&str_vecs);
} else {
LOG(FATAL) << "Unknown field for Booster feature info:" << field;
}
charp_vecs.resize(str_vecs.size());
for (size_t i = 0; i < str_vecs.size(); ++i) {
charp_vecs[i] = str_vecs[i].c_str();
}
xgboost_CHECK_C_ARG_PTR(out_features);
xgboost_CHECK_C_ARG_PTR(len);
*out_features = dmlc::BeginPtr(charp_vecs);
*len = static_cast<xgboost::bst_ulong>(charp_vecs.size());
API_END();
}
XGB_DLL int XGBoosterFeatureScore(BoosterHandle handle, char const *config,
xgboost::bst_ulong *out_n_features, char const ***out_features,
bst_ulong *out_dim, bst_ulong const **out_shape,
float const **out_scores) {
API_BEGIN();
CHECK_HANDLE();
auto *learner = static_cast<Learner *>(handle);
xgboost_CHECK_C_ARG_PTR(config);
auto jconfig = Json::Load(StringView{config});
auto importance = RequiredArg<String>(jconfig, "importance_type", __func__);
std::string feature_map_uri;
if (!IsA<Null>(jconfig["feature_map"])) {
feature_map_uri = get<String const>(jconfig["feature_map"]);
}
FeatureMap feature_map = LoadFeatureMap(feature_map_uri);
std::vector<Json> custom_feature_names;
if (!IsA<Null>(jconfig["feature_names"])) {
custom_feature_names = get<Array const>(jconfig["feature_names"]);
}
std::vector<int32_t> tree_idx;
if (!IsA<Null>(jconfig["tree_idx"])) {
auto j_tree_idx = get<Array const>(jconfig["tree_idx"]);
for (auto const &idx : j_tree_idx) {
tree_idx.push_back(get<Integer const>(idx));
}
}
auto &scores = learner->GetThreadLocal().ret_vec_float;
std::vector<bst_feature_t> features;
learner->CalcFeatureScore(importance, common::Span<int32_t const>(tree_idx), &features, &scores);
auto n_features = learner->GetNumFeature();
GenerateFeatureMap(learner, custom_feature_names, n_features, &feature_map);
auto& feature_names = learner->GetThreadLocal().ret_vec_str;
feature_names.resize(features.size());
auto& feature_names_c = learner->GetThreadLocal().ret_vec_charp;
feature_names_c.resize(features.size());
for (bst_feature_t i = 0; i < features.size(); ++i) {
feature_names[i] = feature_map.Name(features[i]);
feature_names_c[i] = feature_names[i].data();
}
xgboost_CHECK_C_ARG_PTR(out_n_features);
*out_n_features = feature_names.size();
CHECK_LE(features.size(), scores.size());
auto &shape = learner->GetThreadLocal().prediction_shape;
xgboost_CHECK_C_ARG_PTR(out_dim);
if (scores.size() > features.size()) {
// Linear model multi-class model
CHECK_EQ(scores.size() % features.size(), 0ul);
auto n_classes = scores.size() / features.size();
*out_dim = 2;
shape = {n_features, n_classes};
} else {
CHECK_EQ(features.size(), scores.size());
*out_dim = 1;
shape.resize(1);
shape.front() = scores.size();
}
xgboost_CHECK_C_ARG_PTR(out_shape);
xgboost_CHECK_C_ARG_PTR(out_scores);
xgboost_CHECK_C_ARG_PTR(out_features);
*out_shape = dmlc::BeginPtr(shape);
*out_scores = scores.data();
*out_features = dmlc::BeginPtr(feature_names_c);
API_END();
}
XGB_DLL int XGCommunicatorInit(char const* json_config) {
API_BEGIN();
xgboost_CHECK_C_ARG_PTR(json_config);
Json config{Json::Load(StringView{json_config})};
collective::Init(config);
API_END();
}
XGB_DLL int XGCommunicatorFinalize() {
API_BEGIN();
collective::Finalize();
API_END();
}
XGB_DLL int XGCommunicatorGetRank(void) {
return collective::GetRank();
}
XGB_DLL int XGCommunicatorGetWorldSize(void) {
return collective::GetWorldSize();
}
XGB_DLL int XGCommunicatorIsDistributed(void) {
return collective::IsDistributed();
}
XGB_DLL int XGCommunicatorPrint(char const *message) {
API_BEGIN();
collective::Print(message);
API_END();
}
XGB_DLL int XGCommunicatorGetProcessorName(char const **name_str) {
API_BEGIN();
auto& local = *GlobalConfigAPIThreadLocalStore::Get();
local.ret_str = collective::GetProcessorName();
xgboost_CHECK_C_ARG_PTR(name_str);
*name_str = local.ret_str.c_str();
API_END();
}
XGB_DLL int XGCommunicatorBroadcast(void *send_receive_buffer, size_t size, int root) {
API_BEGIN();
collective::Broadcast(send_receive_buffer, size, root);
API_END();
}
XGB_DLL int XGCommunicatorAllreduce(void *send_receive_buffer, size_t count, int enum_dtype,
int enum_op) {
API_BEGIN();
collective::Allreduce(send_receive_buffer, count, enum_dtype, enum_op);
API_END();
}
#if defined(XGBOOST_USE_FEDERATED)
XGB_DLL int XGBRunFederatedServer(int port, int world_size, char const *server_key_path,
char const *server_cert_path, char const *client_cert_path) {
API_BEGIN();
federated::RunServer(port, world_size, server_key_path, server_cert_path, client_cert_path);
API_END();
}
// Run a server without SSL for local testing.
XGB_DLL int XGBRunInsecureFederatedServer(int port, int world_size) {
API_BEGIN();
federated::RunInsecureServer(port, world_size);
API_END();
}
#endif
// force link rabit
static DMLC_ATTRIBUTE_UNUSED int XGBOOST_LINK_RABIT_C_API_ = RabitLinkTag();
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