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Enhance inplace prediction. (#6653)

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* Accept array interface for csr and array.
* Accept an optional proxy dmatrix for metainfo.

This constructs an explicit `_ProxyDMatrix` type in Python.

* Remove unused doc.
* Add strict output.
This commit is contained in:
Jiaming Yuan
2021-02-02 11:41:46 +08:00
committed by GitHub
parent 87ab1ad607
commit 411592a347
22 changed files with 955 additions and 530 deletions
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127
src/c_api/c_api.cc
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@@ -21,6 +21,7 @@
#include "xgboost/global_config.h"
#include "c_api_error.h"
#include "c_api_utils.h"
#include "../common/io.h"
#include "../common/charconv.h"
#include "../data/adapter.h"
@@ -617,90 +618,92 @@ XGB_DLL int XGBoosterPredict(BoosterHandle handle,
API_END();
}
template <typename T>
void InplacePredictImpl(std::shared_ptr<T> x, std::shared_ptr<DMatrix> p_m,
char const *c_json_config, Learner *learner,
size_t n_rows, size_t n_cols,
xgboost::bst_ulong const **out_shape,
xgboost::bst_ulong *out_dim, const float **out_result) {
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(get<Integer const>(config["type"]));
learner->InplacePredict(x, p_m, type, get<Number const>(config["missing"]),
&p_predt,
get<Integer const>(config["iteration_begin"]),
get<Integer const>(config["iteration_end"]));
CHECK(p_predt);
auto &shape = learner->GetThreadLocal().prediction_shape;
auto chunksize = n_rows == 0 ? 0 : p_predt->Size() / n_rows;
bool strict_shape = get<Boolean const>(config["strict_shape"]);
CalcPredictShape(strict_shape, type, n_rows, n_cols, chunksize, learner->Groups(),
learner->BoostedRounds(), &shape, out_dim);
*out_result = dmlc::BeginPtr(p_predt->HostVector());
*out_shape = dmlc::BeginPtr(shape);
}
// A hidden API as cache id is not being supported yet.
XGB_DLL int XGBoosterPredictFromDense(BoosterHandle handle, float *values,
xgboost::bst_ulong n_rows,
xgboost::bst_ulong n_cols,
float missing,
unsigned iteration_begin,
unsigned iteration_end,
char const* c_type,
xgboost::bst_ulong cache_id,
xgboost::bst_ulong *out_len,
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();
CHECK_EQ(cache_id, 0) << "Cache ID is not supported yet";
std::shared_ptr<xgboost::data::ArrayAdapter> x{
new xgboost::data::ArrayAdapter(StringView{array_interface})};
std::shared_ptr<DMatrix> p_m {nullptr};
if (m) {
p_m = *static_cast<std::shared_ptr<DMatrix> *>(m);
}
auto *learner = static_cast<xgboost::Learner *>(handle);
std::shared_ptr<xgboost::data::DenseAdapter> x{
new xgboost::data::DenseAdapter(values, n_rows, n_cols)};
HostDeviceVector<float>* p_predt { nullptr };
std::string type { c_type };
learner->InplacePredict(x, type, missing, &p_predt, iteration_begin, iteration_end);
CHECK(p_predt);
*out_result = dmlc::BeginPtr(p_predt->HostVector());
*out_len = static_cast<xgboost::bst_ulong>(p_predt->Size());
InplacePredictImpl(x, p_m, c_json_config, learner, x->NumRows(),
x->NumColumns(), out_shape, out_dim, out_result);
API_END();
}
// A hidden API as cache id is not being supported yet.
XGB_DLL int XGBoosterPredictFromCSR(BoosterHandle handle,
const size_t* indptr,
const unsigned* indices,
const bst_float* data,
size_t nindptr,
size_t nelem,
size_t num_col,
float missing,
unsigned iteration_begin,
unsigned iteration_end,
char const *c_type,
xgboost::bst_ulong cache_id,
xgboost::bst_ulong *out_len,
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();
CHECK_EQ(cache_id, 0) << "Cache ID is not supported yet";
std::shared_ptr<xgboost::data::CSRArrayAdapter> x{
new xgboost::data::CSRArrayAdapter{
StringView{indptr}, StringView{indices}, StringView{data}, cols}};
std::shared_ptr<DMatrix> p_m {nullptr};
if (m) {
p_m = *static_cast<std::shared_ptr<DMatrix> *>(m);
}
auto *learner = static_cast<xgboost::Learner *>(handle);
std::shared_ptr<xgboost::data::CSRAdapter> x{
new xgboost::data::CSRAdapter(indptr, indices, data, nindptr - 1, nelem, num_col)};
HostDeviceVector<float>* p_predt { nullptr };
std::string type { c_type };
learner->InplacePredict(x, type, missing, &p_predt, iteration_begin, iteration_end);
CHECK(p_predt);
*out_result = dmlc::BeginPtr(p_predt->HostVector());
*out_len = static_cast<xgboost::bst_ulong>(p_predt->Size());
InplacePredictImpl(x, p_m, c_json_config, learner, x->NumRows(),
x->NumColumns(), out_shape, out_dim, out_result);
API_END();
}
#if !defined(XGBOOST_USE_CUDA)
XGB_DLL int XGBoosterPredictFromArrayInterfaceColumns(BoosterHandle handle,
char const* c_json_strs,
float missing,
unsigned iteration_begin,
unsigned iteration_end,
char const* c_type,
xgboost::bst_ulong cache_id,
xgboost::bst_ulong *out_len,
float const** out_result) {
XGB_DLL int XGBoosterPredictFromArrayInterface(
BoosterHandle handle, char const *c_json_strs, 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();
common::AssertGPUSupport();
API_END();
}
XGB_DLL int XGBoosterPredictFromArrayInterface(BoosterHandle handle,
char const* c_json_strs,
float missing,
unsigned iteration_begin,
unsigned iteration_end,
char const* c_type,
xgboost::bst_ulong cache_id,
xgboost::bst_ulong *out_len,
const float **out_result) {
XGB_DLL int XGBoosterPredictFromArrayInterfaceColumns(
BoosterHandle handle, char const *c_json_strs, 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();
common::AssertGPUSupport();