xgboost/tests/cpp/helpers.cc
Philip Hyunsu Cho abf2f661be
Fix #3708: Use dmlc::TemporaryDirectory to handle temporaries in cross-platform way (#3783)
* Fix #3708: Use dmlc::TemporaryDirectory to handle temporaries in cross-platform way

Also install git inside NVIDIA GPU container

* Update dmlc-core
2018-10-18 10:16:04 -07:00

144 lines
4.8 KiB
C++

/*!
* Copyright 2016-2018 XGBoost contributors
*/
#include "./helpers.h"
#include "xgboost/c_api.h"
#include <random>
bool FileExists(const std::string name) {
struct stat st;
return stat(name.c_str(), &st) == 0;
}
long GetFileSize(const std::string filename) {
struct stat st;
stat(filename.c_str(), &st);
return st.st_size;
}
void CreateSimpleTestData(const std::string& filename) {
CreateBigTestData(filename, 6);
}
void CreateBigTestData(const std::string& filename, size_t n_entries) {
std::ofstream fo(filename.c_str());
const size_t entries_per_row = 3;
size_t n_rows = (n_entries + entries_per_row - 1) / entries_per_row;
for (size_t i = 0; i < n_rows; ++i) {
const char* row = i % 2 == 0 ? " 0:0 1:10 2:20\n" : " 0:0 3:30 4:40\n";
fo << i << row;
}
}
void _CheckObjFunction(xgboost::ObjFunction * obj,
std::vector<xgboost::bst_float> preds,
std::vector<xgboost::bst_float> labels,
std::vector<xgboost::bst_float> weights,
xgboost::MetaInfo info,
std::vector<xgboost::bst_float> out_grad,
std::vector<xgboost::bst_float> out_hess) {
xgboost::HostDeviceVector<xgboost::bst_float> in_preds(preds);
xgboost::HostDeviceVector<xgboost::GradientPair> out_gpair;
obj->GetGradient(in_preds, info, 1, &out_gpair);
std::vector<xgboost::GradientPair>& gpair = out_gpair.HostVector();
ASSERT_EQ(gpair.size(), in_preds.Size());
for (int i = 0; i < static_cast<int>(gpair.size()); ++i) {
EXPECT_NEAR(gpair[i].GetGrad(), out_grad[i], 0.01)
<< "Unexpected grad for pred=" << preds[i] << " label=" << labels[i]
<< " weight=" << weights[i];
EXPECT_NEAR(gpair[i].GetHess(), out_hess[i], 0.01)
<< "Unexpected hess for pred=" << preds[i] << " label=" << labels[i]
<< " weight=" << weights[i];
}
}
void CheckObjFunction(xgboost::ObjFunction * obj,
std::vector<xgboost::bst_float> preds,
std::vector<xgboost::bst_float> labels,
std::vector<xgboost::bst_float> weights,
std::vector<xgboost::bst_float> out_grad,
std::vector<xgboost::bst_float> out_hess) {
xgboost::MetaInfo info;
info.num_row_ = labels.size();
info.labels_.HostVector() = labels;
info.weights_.HostVector() = weights;
_CheckObjFunction(obj, preds, labels, weights, info, out_grad, out_hess);
}
void CheckRankingObjFunction(xgboost::ObjFunction * obj,
std::vector<xgboost::bst_float> preds,
std::vector<xgboost::bst_float> labels,
std::vector<xgboost::bst_float> weights,
std::vector<xgboost::bst_uint> groups,
std::vector<xgboost::bst_float> out_grad,
std::vector<xgboost::bst_float> out_hess) {
xgboost::MetaInfo info;
info.num_row_ = labels.size();
info.labels_.HostVector() = labels;
info.weights_.HostVector() = weights;
info.group_ptr_ = groups;
_CheckObjFunction(obj, preds, labels, weights, info, out_grad, out_hess);
}
xgboost::bst_float GetMetricEval(xgboost::Metric * metric,
std::vector<xgboost::bst_float> preds,
std::vector<xgboost::bst_float> labels,
std::vector<xgboost::bst_float> weights) {
xgboost::MetaInfo info;
info.num_row_ = labels.size();
info.labels_.HostVector() = labels;
info.weights_.HostVector() = weights;
return metric->Eval(preds, info, false);
}
namespace xgboost {
bool IsNear(std::vector<xgboost::bst_float>::const_iterator _beg1,
std::vector<xgboost::bst_float>::const_iterator _end1,
std::vector<xgboost::bst_float>::const_iterator _beg2) {
for (auto iter1 = _beg1, iter2 = _beg2; iter1 != _end1; ++iter1, ++iter2) {
if (std::abs(*iter1 - *iter2) > xgboost::kRtEps){
return false;
}
}
return true;
}
SimpleLCG::StateType SimpleLCG::operator()() {
state_ = (alpha_ * state_) % mod_;
return state_;
}
SimpleLCG::StateType SimpleLCG::Min() const {
return seed_ * alpha_;
}
SimpleLCG::StateType SimpleLCG::Max() const {
return max_value_;
}
std::shared_ptr<xgboost::DMatrix>* CreateDMatrix(int rows, int columns,
float sparsity, int seed) {
const float missing_value = -1;
std::vector<float> test_data(rows * columns);
xgboost::SimpleLCG gen(seed);
SimpleRealUniformDistribution<float> dis(0.0f, 1.0f);
for (auto &e : test_data) {
if (dis(&gen) < sparsity) {
e = missing_value;
} else {
e = dis(&gen);
}
}
DMatrixHandle handle;
XGDMatrixCreateFromMat(test_data.data(), rows, columns, missing_value,
&handle);
return static_cast<std::shared_ptr<xgboost::DMatrix> *>(handle);
}
} // namespace xgboost