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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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36
src/predictor/gpu_predictor.cu
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@@ -1,5 +1,5 @@
/*!
* Copyright 2017-2020 by Contributors
* Copyright 2017-2021 by Contributors
*/
#include <thrust/copy.h>
#include <thrust/device_ptr.h>
@@ -644,7 +644,7 @@ class GPUPredictor : public xgboost::Predictor {
}
template <typename Adapter, typename Loader>
void DispatchedInplacePredict(dmlc::any const &x,
void DispatchedInplacePredict(dmlc::any const &x, std::shared_ptr<DMatrix> p_m,
const gbm::GBTreeModel &model, float,
PredictionCacheEntry *out_preds,
uint32_t tree_begin, uint32_t tree_end) const {
@@ -659,16 +659,20 @@ class GPUPredictor : public xgboost::Predictor {
CHECK_EQ(this->generic_param_->gpu_id, m->DeviceIdx())
<< "XGBoost is running on device: " << this->generic_param_->gpu_id << ", "
<< "but data is on: " << m->DeviceIdx();
MetaInfo info;
info.num_col_ = m->NumColumns();
info.num_row_ = m->NumRows();
this->InitOutPredictions(info, &(out_preds->predictions), model);
if (p_m) {
p_m->Info().num_row_ = m->NumRows();
this->InitOutPredictions(p_m->Info(), &(out_preds->predictions), model);
} else {
MetaInfo info;
info.num_row_ = m->NumRows();
this->InitOutPredictions(info, &(out_preds->predictions), model);
}
const uint32_t BLOCK_THREADS = 128;
auto GRID_SIZE = static_cast<uint32_t>(common::DivRoundUp(info.num_row_, BLOCK_THREADS));
auto GRID_SIZE = static_cast<uint32_t>(common::DivRoundUp(m->NumRows(), BLOCK_THREADS));
size_t shared_memory_bytes =
SharedMemoryBytes<BLOCK_THREADS>(info.num_col_, max_shared_memory_bytes);
SharedMemoryBytes<BLOCK_THREADS>(m->NumColumns(), max_shared_memory_bytes);
bool use_shared = shared_memory_bytes != 0;
size_t entry_start = 0;
@@ -680,23 +684,25 @@ class GPUPredictor : public xgboost::Predictor {
d_model.categories_tree_segments.ConstDeviceSpan(),
d_model.categories_node_segments.ConstDeviceSpan(),
d_model.categories.ConstDeviceSpan(), tree_begin, tree_end, m->NumColumns(),
info.num_row_, entry_start, use_shared, output_groups);
m->NumRows(), entry_start, use_shared, output_groups);
}
void InplacePredict(dmlc::any const &x, const gbm::GBTreeModel &model,
float missing, PredictionCacheEntry *out_preds,
uint32_t tree_begin, unsigned tree_end) const override {
bool InplacePredict(dmlc::any const &x, std::shared_ptr<DMatrix> p_m,
const gbm::GBTreeModel &model, float missing,
PredictionCacheEntry *out_preds, uint32_t tree_begin,
unsigned tree_end) const override {
if (x.type() == typeid(std::shared_ptr<data::CupyAdapter>)) {
this->DispatchedInplacePredict<
data::CupyAdapter, DeviceAdapterLoader<data::CupyAdapterBatch>>(
x, model, missing, out_preds, tree_begin, tree_end);
x, p_m, model, missing, out_preds, tree_begin, tree_end);
} else if (x.type() == typeid(std::shared_ptr<data::CudfAdapter>)) {
this->DispatchedInplacePredict<
data::CudfAdapter, DeviceAdapterLoader<data::CudfAdapterBatch>>(
x, model, missing, out_preds, tree_begin, tree_end);
x, p_m, model, missing, out_preds, tree_begin, tree_end);
} else {
LOG(FATAL) << "Only CuPy and CuDF are supported by GPU Predictor.";
return false;
}
return true;
}
void PredictContribution(DMatrix* p_fmat,