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

Pass shared pointer instead of raw pointer to Learner. (#5302)

Browse Source 
Extracted from https://github.com/dmlc/xgboost/pull/5220 .
This commit is contained in:
Jiaming Yuan
2020-02-11 14:16:38 +08:00
committed by GitHub
parent 2e0067e790
commit 29eeea709a
12 changed files with 97 additions and 73 deletions
Download Patch File Download Diff File Expand all files Collapse all files

23
tests/cpp/test_learner.cc
View File

@@ -1,4 +1,6 @@
// Copyright by Contributors
/*!
* Copyright 2017-2020 XGBoost contributors
*/
#include <gtest/gtest.h>
#include <vector>
#include "helpers.h"
@@ -79,13 +81,13 @@ TEST(Learner, CheckGroup) {
std::vector<std::shared_ptr<xgboost::DMatrix>> mat = {p_mat};
auto learner = std::unique_ptr<Learner>(Learner::Create(mat));
learner->SetParams({Arg{"objective", "rank:pairwise"}});
EXPECT_NO_THROW(learner->UpdateOneIter(0, p_mat.get()));
EXPECT_NO_THROW(learner->UpdateOneIter(0, p_mat));
group.resize(kNumGroups+1);
group[3] = 4;
group[4] = 1;
p_mat->Info().SetInfo("group", group.data(), DataType::kUInt32, kNumGroups+1);
EXPECT_ANY_THROW(learner->UpdateOneIter(0, p_mat.get()));
EXPECT_ANY_THROW(learner->UpdateOneIter(0, p_mat));
delete pp_mat;
}
@@ -107,7 +109,7 @@ TEST(Learner, SLOW_CheckMultiBatch) {
std::vector<std::shared_ptr<DMatrix>> mat{dmat};
auto learner = std::unique_ptr<Learner>(Learner::Create(mat));
learner->SetParams(Args{{"objective", "binary:logistic"}});
learner->UpdateOneIter(0, dmat.get());
learner->UpdateOneIter(0, dmat);
}
TEST(Learner, Configuration) {
@@ -142,6 +144,7 @@ TEST(Learner, JsonModelIO) {
auto pp_dmat = CreateDMatrix(kRows, 10, 0);
std::shared_ptr<DMatrix> p_dmat {*pp_dmat};
p_dmat->Info().labels_.Resize(kRows);
CHECK_NE(p_dmat->Info().num_col_, 0);
{
std::unique_ptr<Learner> learner { Learner::Create({p_dmat}) };
@@ -160,7 +163,7 @@ TEST(Learner, JsonModelIO) {
{
std::unique_ptr<Learner> learner { Learner::Create({p_dmat}) };
for (int32_t iter = 0; iter < kIters; ++iter) {
learner->UpdateOneIter(iter, p_dmat.get());
learner->UpdateOneIter(iter, p_dmat);
}
learner->SetAttr("best_score", "15.2");
@@ -197,20 +200,20 @@ TEST(Learner, GPUConfiguration) {
std::unique_ptr<Learner> learner {Learner::Create(mat)};
learner->SetParams({Arg{"booster", "gblinear"},
Arg{"updater", "gpu_coord_descent"}});
learner->UpdateOneIter(0, p_dmat.get());
learner->UpdateOneIter(0, p_dmat);
ASSERT_EQ(learner->GetGenericParameter().gpu_id, 0);
}
{
std::unique_ptr<Learner> learner {Learner::Create(mat)};
learner->SetParams({Arg{"tree_method", "gpu_hist"}});
learner->UpdateOneIter(0, p_dmat.get());
learner->UpdateOneIter(0, p_dmat);
ASSERT_EQ(learner->GetGenericParameter().gpu_id, 0);
}
{
// with CPU algorithm
std::unique_ptr<Learner> learner {Learner::Create(mat)};
learner->SetParams({Arg{"tree_method", "hist"}});
learner->UpdateOneIter(0, p_dmat.get());
learner->UpdateOneIter(0, p_dmat);
ASSERT_EQ(learner->GetGenericParameter().gpu_id, -1);
}
{
@@ -218,7 +221,7 @@ TEST(Learner, GPUConfiguration) {
std::unique_ptr<Learner> learner {Learner::Create(mat)};
learner->SetParams({Arg{"tree_method", "hist"},
Arg{"gpu_id", "0"}});
learner->UpdateOneIter(0, p_dmat.get());
learner->UpdateOneIter(0, p_dmat);
ASSERT_EQ(learner->GetGenericParameter().gpu_id, 0);
}
{
@@ -228,7 +231,7 @@ TEST(Learner, GPUConfiguration) {
std::unique_ptr<Learner> learner {Learner::Create(mat)};
learner->SetParams({Arg{"tree_method", "hist"},
Arg{"predictor", "gpu_predictor"}});
learner->UpdateOneIter(0, p_dmat.get());
learner->UpdateOneIter(0, p_dmat);
ASSERT_EQ(learner->GetGenericParameter().gpu_id, 0);
}