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Cmake improvements (#2487)

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* Cmake improvements
* Add google test to cmake
This commit is contained in:
Rory Mitchell
2017-07-06 18:05:11 +12:00
committed by GitHub
parent 8ceeb32bad
commit e939192978
13 changed files with 291 additions and 257 deletions
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8
tests/cpp/objective/test_multiclass_metric.cc
View File

@@ -10,9 +10,9 @@ TEST(Metric, MultiClassError) {
EXPECT_NEAR(GetMetricEval(
metric, {1, 0, 0, 0, 1, 0, 0, 0, 1}, {0, 1, 2}), 0, 1e-10);
EXPECT_NEAR(GetMetricEval(metric,
{0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1},
{0.1f, 0.1f, 0.1f, 0.1f, 0.1f, 0.1f, 0.1f, 0.1f, 0.1f},
{0, 1, 2}),
0.666, 0.001);
0.666f, 0.001f);
}
TEST(Metric, MultiClassLogLoss) {
@@ -22,7 +22,7 @@ TEST(Metric, MultiClassLogLoss) {
EXPECT_NEAR(GetMetricEval(
metric, {1, 0, 0, 0, 1, 0, 0, 0, 1}, {0, 1, 2}), 0, 1e-10);
EXPECT_NEAR(GetMetricEval(metric,
{0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1},
{0.1f, 0.1f, 0.1f, 0.1f, 0.1f, 0.1f, 0.1f, 0.1f, 0.1f},
{0, 1, 2}),
2.302, 0.001);
2.302f, 0.001f);
}

90
tests/cpp/objective/test_regression_obj.cc
View File

@@ -8,10 +8,10 @@ TEST(Objective, LinearRegressionGPair) {
std::vector<std::pair<std::string, std::string> > args;
obj->Configure(args);
CheckObjFunction(obj,
{0, 0.1, 0.9, 1, 0, 0.1, 0.9, 1},
{0, 0.1f, 0.9f, 1, 0, 0.1f, 0.9f, 1},
{0, 0, 0, 0, 1, 1, 1, 1},
{1, 1, 1, 1, 1, 1, 1, 1},
{0, 0.1, 0.9, 1.0, -1.0, -0.9, -0.1, 0},
{0, 0.1f, 0.9f, 1.0f, -1.0f, -0.9f, -0.1f, 0},
{1, 1, 1, 1, 1, 1, 1, 1});
ASSERT_NO_THROW(obj->DefaultEvalMetric());
@@ -22,11 +22,11 @@ TEST(Objective, LogisticRegressionGPair) {
std::vector<std::pair<std::string, std::string> > args;
obj->Configure(args);
CheckObjFunction(obj,
{ 0, 0.1, 0.9, 1, 0, 0.1, 0.9, 1},
{ 0, 0.1f, 0.9f, 1, 0, 0.1f, 0.9f, 1},
{ 0, 0, 0, 0, 1, 1, 1, 1},
{ 1, 1, 1, 1, 1, 1, 1, 1},
{ 0.5, 0.52, 0.71, 0.73, -0.5, -0.47, -0.28, -0.26},
{0.25, 0.24, 0.20, 0.19, 0.25, 0.24, 0.20, 0.19});
{ 0.5f, 0.52f, 0.71f, 0.73f, -0.5f, -0.47f, -0.28f, -0.26f},
{0.25f, 0.24f, 0.20f, 0.19f, 0.25f, 0.24f, 0.20f, 0.19f});
}
TEST(Objective, LogisticRegressionBasic) {
@@ -36,21 +36,21 @@ TEST(Objective, LogisticRegressionBasic) {
// test label validation
EXPECT_ANY_THROW(CheckObjFunction(obj, {0}, {10}, {1}, {0}, {0}))
<< "Expected error when label not in range [0,1] for LogisticRegression";
<< "Expected error when label not in range [0,1f] for LogisticRegression";
// test ProbToMargin
EXPECT_NEAR(obj->ProbToMargin(0.1), -2.197, 0.01);
EXPECT_NEAR(obj->ProbToMargin(0.5), 0, 0.01);
EXPECT_NEAR(obj->ProbToMargin(0.9), 2.197, 0.01);
EXPECT_NEAR(obj->ProbToMargin(0.1f), -2.197f, 0.01f);
EXPECT_NEAR(obj->ProbToMargin(0.5f), 0, 0.01f);
EXPECT_NEAR(obj->ProbToMargin(0.9f), 2.197f, 0.01f);
EXPECT_ANY_THROW(obj->ProbToMargin(10))
<< "Expected error when base_score not in range [0,1] for LogisticRegression";
<< "Expected error when base_score not in range [0,1f] for LogisticRegression";
// test PredTransform
std::vector<xgboost::bst_float> preds = {0, 0.1, 0.5, 0.9, 1};
std::vector<xgboost::bst_float> out_preds = {0.5, 0.524, 0.622, 0.710, 0.731};
std::vector<xgboost::bst_float> preds = {0, 0.1f, 0.5f, 0.9f, 1};
std::vector<xgboost::bst_float> out_preds = {0.5f, 0.524f, 0.622f, 0.710f, 0.731f};
obj->PredTransform(&preds);
for (int i = 0; i < static_cast<int>(preds.size()); ++i) {
EXPECT_NEAR(preds[i], out_preds[i], 0.01);
EXPECT_NEAR(preds[i], out_preds[i], 0.01f);
}
}
@@ -59,24 +59,24 @@ TEST(Objective, LogisticRawGPair) {
std::vector<std::pair<std::string, std::string> > args;
obj->Configure(args);
CheckObjFunction(obj,
{ 0, 0.1, 0.9, 1, 0, 0.1, 0.9, 1},
{ 0, 0.1f, 0.9f, 1, 0, 0.1f, 0.9f, 1},
{ 0, 0, 0, 0, 1, 1, 1, 1},
{ 1, 1, 1, 1, 1, 1, 1, 1},
{ 0.5, 0.52, 0.71, 0.73, -0.5, -0.47, -0.28, -0.26},
{0.25, 0.24, 0.20, 0.19, 0.25, 0.24, 0.20, 0.19});
{ 0.5f, 0.52f, 0.71f, 0.73f, -0.5f, -0.47f, -0.28f, -0.26f},
{0.25f, 0.24f, 0.20f, 0.19f, 0.25f, 0.24f, 0.20f, 0.19f});
}
TEST(Objective, PoissonRegressionGPair) {
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("count:poisson");
std::vector<std::pair<std::string, std::string> > args;
args.push_back(std::make_pair("max_delta_step", "0.1"));
args.push_back(std::make_pair("max_delta_step", "0.1f"));
obj->Configure(args);
CheckObjFunction(obj,
{ 0, 0.1, 0.9, 1, 0, 0.1, 0.9, 1},
{ 0, 0.1f, 0.9f, 1, 0, 0.1f, 0.9f, 1},
{ 0, 0, 0, 0, 1, 1, 1, 1},
{ 1, 1, 1, 1, 1, 1, 1, 1},
{ 1, 1.10, 2.45, 2.71, 0, 0.10, 1.45, 1.71},
{1.10, 1.22, 2.71, 3.00, 1.10, 1.22, 2.71, 3.00});
{ 1, 1.10f, 2.45f, 2.71f, 0, 0.10f, 1.45f, 1.71f},
{1.10f, 1.22f, 2.71f, 3.00f, 1.10f, 1.22f, 2.71f, 3.00f});
}
TEST(Objective, PoissonRegressionBasic) {
@@ -89,16 +89,16 @@ TEST(Objective, PoissonRegressionBasic) {
<< "Expected error when label < 0 for PoissonRegression";
// test ProbToMargin
EXPECT_NEAR(obj->ProbToMargin(0.1), -2.30, 0.01);
EXPECT_NEAR(obj->ProbToMargin(0.5), -0.69, 0.01);
EXPECT_NEAR(obj->ProbToMargin(0.9), -0.10, 0.01);
EXPECT_NEAR(obj->ProbToMargin(0.1f), -2.30f, 0.01f);
EXPECT_NEAR(obj->ProbToMargin(0.5f), -0.69f, 0.01f);
EXPECT_NEAR(obj->ProbToMargin(0.9f), -0.10f, 0.01f);
// test PredTransform
std::vector<xgboost::bst_float> preds = {0, 0.1, 0.5, 0.9, 1};
std::vector<xgboost::bst_float> out_preds = {1, 1.10, 1.64, 2.45, 2.71};
std::vector<xgboost::bst_float> preds = {0, 0.1f, 0.5f, 0.9f, 1};
std::vector<xgboost::bst_float> out_preds = {1, 1.10f, 1.64f, 2.45f, 2.71f};
obj->PredTransform(&preds);
for (int i = 0; i < static_cast<int>(preds.size()); ++i) {
EXPECT_NEAR(preds[i], out_preds[i], 0.01);
EXPECT_NEAR(preds[i], out_preds[i], 0.01f);
}
}
@@ -107,11 +107,11 @@ TEST(Objective, GammaRegressionGPair) {
std::vector<std::pair<std::string, std::string> > args;
obj->Configure(args);
CheckObjFunction(obj,
{0, 0.1, 0.9, 1, 0, 0.1, 0.9, 1},
{0, 0.1f, 0.9f, 1, 0, 0.1f, 0.9f, 1},
{0, 0, 0, 0, 1, 1, 1, 1},
{1, 1, 1, 1, 1, 1, 1, 1},
{1, 1, 1, 1, 0, 0.09, 0.59, 0.63},
{0, 0, 0, 0, 1, 0.90, 0.40, 0.36});
{1, 1, 1, 1, 0, 0.09f, 0.59f, 0.63f},
{0, 0, 0, 0, 1, 0.90f, 0.40f, 0.36f});
}
TEST(Objective, GammaRegressionBasic) {
@@ -124,30 +124,30 @@ TEST(Objective, GammaRegressionBasic) {
<< "Expected error when label < 0 for GammaRegression";
// test ProbToMargin
EXPECT_NEAR(obj->ProbToMargin(0.1), -2.30, 0.01);
EXPECT_NEAR(obj->ProbToMargin(0.5), -0.69, 0.01);
EXPECT_NEAR(obj->ProbToMargin(0.9), -0.10, 0.01);
EXPECT_NEAR(obj->ProbToMargin(0.1f), -2.30f, 0.01f);
EXPECT_NEAR(obj->ProbToMargin(0.5f), -0.69f, 0.01f);
EXPECT_NEAR(obj->ProbToMargin(0.9f), -0.10f, 0.01f);
// test PredTransform
std::vector<xgboost::bst_float> preds = {0, 0.1, 0.5, 0.9, 1};
std::vector<xgboost::bst_float> out_preds = {1, 1.10, 1.64, 2.45, 2.71};
std::vector<xgboost::bst_float> preds = {0, 0.1f, 0.5f, 0.9f, 1};
std::vector<xgboost::bst_float> out_preds = {1, 1.10f, 1.64f, 2.45f, 2.71f};
obj->PredTransform(&preds);
for (int i = 0; i < static_cast<int>(preds.size()); ++i) {
EXPECT_NEAR(preds[i], out_preds[i], 0.01);
EXPECT_NEAR(preds[i], out_preds[i], 0.01f);
}
}
TEST(Objective, TweedieRegressionGPair) {
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("reg:tweedie");
std::vector<std::pair<std::string, std::string> > args;
args.push_back(std::make_pair("tweedie_variance_power", "1.1"));
args.push_back(std::make_pair("tweedie_variance_power", "1.1f"));
obj->Configure(args);
CheckObjFunction(obj,
{ 0, 0.1, 0.9, 1, 0, 0.1, 0.9, 1},
{ 0, 0.1f, 0.9f, 1, 0, 0.1f, 0.9f, 1},
{ 0, 0, 0, 0, 1, 1, 1, 1},
{ 1, 1, 1, 1, 1, 1, 1, 1},
{ 1, 1.09, 2.24, 2.45, 0, 0.10, 1.33, 1.55},
{0.89, 0.98, 2.02, 2.21, 1, 1.08, 2.11, 2.30});
{ 1, 1.09f, 2.24f, 2.45f, 0, 0.10f, 1.33f, 1.55f},
{0.89f, 0.98f, 2.02f, 2.21f, 1, 1.08f, 2.11f, 2.30f});
}
TEST(Objective, TweedieRegressionBasic) {
@@ -160,15 +160,15 @@ TEST(Objective, TweedieRegressionBasic) {
<< "Expected error when label < 0 for TweedieRegression";
// test ProbToMargin
EXPECT_NEAR(obj->ProbToMargin(0.1), 0.10, 0.01);
EXPECT_NEAR(obj->ProbToMargin(0.5), 0.5, 0.01);
EXPECT_NEAR(obj->ProbToMargin(0.9), 0.89, 0.01);
EXPECT_NEAR(obj->ProbToMargin(0.1f), 0.10f, 0.01f);
EXPECT_NEAR(obj->ProbToMargin(0.5f), 0.5f, 0.01f);
EXPECT_NEAR(obj->ProbToMargin(0.9f), 0.89f, 0.01f);
// test PredTransform
std::vector<xgboost::bst_float> preds = {0, 0.1, 0.5, 0.9, 1};
std::vector<xgboost::bst_float> out_preds = {1, 1.10, 1.64, 2.45, 2.71};
std::vector<xgboost::bst_float> preds = {0, 0.1f, 0.5f, 0.9f, 1};
std::vector<xgboost::bst_float> out_preds = {1, 1.10f, 1.64f, 2.45f, 2.71f};
obj->PredTransform(&preds);
for (int i = 0; i < static_cast<int>(preds.size()); ++i) {
EXPECT_NEAR(preds[i], out_preds[i], 0.01);
EXPECT_NEAR(preds[i], out_preds[i], 0.01f);
}
}