Hendrik/xgboost
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

[GPU-Plugin] Resolve double compilation issue (#2479)

Browse Source
This commit is contained in:
Rory Mitchell
2017-07-03 13:29:10 +12:00
committed by GitHub
parent 5f1b0bb386
commit ed8bc4521e
11 changed files with 161 additions and 138 deletions
Download Patch File Download Diff File Expand all files Collapse all files

122
plugin/updater_gpu/src/updater_gpu.cu
View File

@@ -1,8 +1,11 @@
/*!
* Copyright 2017 XGBoost contributors
*/
#include "updater_gpu.cuh"
#include <xgboost/tree_updater.h>
#include <vector>
#include <utility>
#include <string>
#include "../../../src/common/random.h"
#include "../../../src/common/sync.h"
#include "../../../src/tree/param.h"
@@ -11,87 +14,64 @@
namespace xgboost {
namespace tree {
DMLC_REGISTRY_FILE_TAG(updater_gpumaker);
/*! \brief column-wise update to construct a tree */
template <typename TStats>
class GPUMaker : public TreeUpdater {
public:
void Init(
const std::vector<std::pair<std::string, std::string>>& args) override {
param.InitAllowUnknown(args);
builder.Init(param);
}
GPUMaker::GPUMaker() : builder(new exact::GPUBuilder<int16_t>()) {}
void Update(const std::vector<bst_gpair>& gpair, DMatrix* dmat,
const std::vector<RegTree*>& trees) override {
TStats::CheckInfo(dmat->info());
// rescale learning rate according to size of trees
float lr = param.learning_rate;
param.learning_rate = lr / trees.size();
builder.UpdateParam(param);
void GPUMaker::Init(
const std::vector<std::pair<std::string, std::string>>& args) {
param.InitAllowUnknown(args);
builder->Init(param);
}
try {
// build tree
for (size_t i = 0; i < trees.size(); ++i) {
builder.Update(gpair, dmat, trees[i]);
}
} catch (const std::exception& e) {
LOG(FATAL) << "GPU plugin exception: " << e.what() << std::endl;
}
param.learning_rate = lr;
}
void GPUMaker::Update(const std::vector<bst_gpair>& gpair, DMatrix* dmat,
const std::vector<RegTree*>& trees) {
GradStats::CheckInfo(dmat->info());
// rescale learning rate according to size of trees
float lr = param.learning_rate;
param.learning_rate = lr / trees.size();
builder->UpdateParam(param);
protected:
// training parameter
TrainParam param;
exact::GPUBuilder<int16_t> builder;
};
template <typename TStats>
class GPUHistMaker : public TreeUpdater {
public:
void Init(
const std::vector<std::pair<std::string, std::string>>& args) override {
param.InitAllowUnknown(args);
builder.Init(param);
}
void Update(const std::vector<bst_gpair>& gpair, DMatrix* dmat,
const std::vector<RegTree*>& trees) override {
TStats::CheckInfo(dmat->info());
// rescale learning rate according to size of trees
float lr = param.learning_rate;
param.learning_rate = lr / trees.size();
builder.UpdateParam(param);
try {
// build tree
try {
for (size_t i = 0; i < trees.size(); ++i) {
builder.Update(gpair, dmat, trees[i]);
}
} catch (const std::exception& e) {
LOG(FATAL) << "GPU plugin exception: " << e.what() << std::endl;
for (size_t i = 0; i < trees.size(); ++i) {
builder->Update(gpair, dmat, trees[i]);
}
param.learning_rate = lr;
} catch (const std::exception& e) {
LOG(FATAL) << "GPU plugin exception: " << e.what() << std::endl;
}
param.learning_rate = lr;
}
bool UpdatePredictionCache(const DMatrix* data,
std::vector<bst_float>* out_preds) override {
return builder.UpdatePredictionCache(data, out_preds);
GPUHistMaker::GPUHistMaker() : builder(new GPUHistBuilder()) {}
void GPUHistMaker::Init(
const std::vector<std::pair<std::string, std::string>>& args) {
param.InitAllowUnknown(args);
builder->Init(param);
}
void GPUHistMaker::Update(const std::vector<bst_gpair>& gpair, DMatrix* dmat,
const std::vector<RegTree*>& trees) {
GradStats::CheckInfo(dmat->info());
// rescale learning rate according to size of trees
float lr = param.learning_rate;
param.learning_rate = lr / trees.size();
builder->UpdateParam(param);
// build tree
try {
for (size_t i = 0; i < trees.size(); ++i) {
builder->Update(gpair, dmat, trees[i]);
}
} catch (const std::exception& e) {
LOG(FATAL) << "GPU plugin exception: " << e.what() << std::endl;
}
param.learning_rate = lr;
}
protected:
// training parameter
TrainParam param;
GPUHistBuilder builder;
};
bool GPUHistMaker::UpdatePredictionCache(const DMatrix* data,
std::vector<bst_float>* out_preds) {
return builder->UpdatePredictionCache(data, out_preds);
}
XGBOOST_REGISTER_TREE_UPDATER(GPUMaker, "grow_gpu")
.describe("Grow tree with GPU.")
.set_body([]() { return new GPUMaker<GradStats>(); });
XGBOOST_REGISTER_TREE_UPDATER(GPUHistMaker, "grow_gpu_hist")
.describe("Grow tree with GPU.")
.set_body([]() { return new GPUHistMaker<GradStats>(); });
} // namespace tree
} // namespace xgboost