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Add Model and Configurable interface. (#4945)

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* Apply Configurable to objective functions.
* Apply Model to Learner and Regtree, gbm.
* Add Load/SaveConfig to objs.
* Refactor obj tests to use smart pointer.
* Dummy methods for Save/Load Model.
This commit is contained in:
Jiaming Yuan
2019-10-18 01:56:02 -04:00
committed by GitHub
parent 9fc681001a
commit ae536756ae
31 changed files with 521 additions and 187 deletions
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140
tests/cpp/objective/test_regression_obj.cc
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@@ -4,14 +4,17 @@
#include <gtest/gtest.h>
#include <xgboost/objective.h>
#include <xgboost/generic_parameters.h>
#include <xgboost/json.h>
#include "../helpers.h"
namespace xgboost {
TEST(Objective, DeclareUnifiedTest(LinearRegressionGPair)) {
xgboost::GenericParameter tparam = xgboost::CreateEmptyGenericParam(GPUIDX);
GenericParameter tparam = CreateEmptyGenericParam(GPUIDX);
std::vector<std::pair<std::string, std::string>> args;
xgboost::ObjFunction * obj =
xgboost::ObjFunction::Create("reg:squarederror", &tparam);
std::unique_ptr<ObjFunction> obj {
ObjFunction::Create("reg:squarederror", &tparam)
};
obj->Configure(args);
CheckObjFunction(obj,
@@ -27,17 +30,15 @@ TEST(Objective, DeclareUnifiedTest(LinearRegressionGPair)) {
{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());
delete obj;
}
TEST(Objective, DeclareUnifiedTest(SquaredLog)) {
xgboost::GenericParameter tparam = xgboost::CreateEmptyGenericParam(GPUIDX);
GenericParameter tparam = CreateEmptyGenericParam(GPUIDX);
std::vector<std::pair<std::string, std::string>> args;
xgboost::ObjFunction * obj =
xgboost::ObjFunction::Create("reg:squaredlogerror", &tparam);
std::unique_ptr<ObjFunction> obj { ObjFunction::Create("reg:squaredlogerror", &tparam) };
obj->Configure(args);
CheckConfigReload(obj, "reg:squaredlogerror");
CheckObjFunction(obj,
{0.1f, 0.2f, 0.4f, 0.8f, 1.6f}, // pred
@@ -52,31 +53,33 @@ TEST(Objective, DeclareUnifiedTest(SquaredLog)) {
{-0.5435f, -0.4257f, -0.25475f, -0.05855f, 0.1009f},
{ 1.3205f, 1.0492f, 0.69215f, 0.34115f, 0.1091f});
ASSERT_EQ(obj->DefaultEvalMetric(), std::string{"rmsle"});
delete obj;
}
TEST(Objective, DeclareUnifiedTest(LogisticRegressionGPair)) {
xgboost::GenericParameter tparam = xgboost::CreateEmptyGenericParam(GPUIDX);
GenericParameter tparam = CreateEmptyGenericParam(GPUIDX);
std::vector<std::pair<std::string, std::string>> args;
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("reg:logistic", &tparam);
std::unique_ptr<ObjFunction> obj { ObjFunction::Create("reg:logistic", &tparam) };
obj->Configure(args);
CheckConfigReload(obj, "reg:logistic");
CheckObjFunction(obj,
{ 0, 0.1f, 0.9f, 1, 0, 0.1f, 0.9f, 1}, // preds
{ 0, 0, 0, 0, 1, 1, 1, 1}, // labels
{ 1, 1, 1, 1, 1, 1, 1, 1}, // weights
{ 0.5f, 0.52f, 0.71f, 0.73f, -0.5f, -0.47f, -0.28f, -0.26f}, // out_grad
{0.25f, 0.24f, 0.20f, 0.19f, 0.25f, 0.24f, 0.20f, 0.19f}); // out_hess
delete obj;
}
TEST(Objective, DeclareUnifiedTest(LogisticRegressionBasic)) {
xgboost::GenericParameter lparam = xgboost::CreateEmptyGenericParam(GPUIDX);
GenericParameter lparam = CreateEmptyGenericParam(GPUIDX);
std::vector<std::pair<std::string, std::string>> args;
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("reg:logistic", &lparam);
std::unique_ptr<ObjFunction> obj {
ObjFunction::Create("reg:logistic", &lparam)
};
obj->Configure(args);
CheckConfigReload(obj, "reg:logistic");
// test label validation
EXPECT_ANY_THROW(CheckObjFunction(obj, {0}, {10}, {1}, {0}, {0}))
@@ -90,40 +93,42 @@ TEST(Objective, DeclareUnifiedTest(LogisticRegressionBasic)) {
<< "Expected error when base_score not in range [0,1f] for LogisticRegression";
// test PredTransform
xgboost::HostDeviceVector<xgboost::bst_float> io_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};
HostDeviceVector<bst_float> io_preds = {0, 0.1f, 0.5f, 0.9f, 1};
std::vector<bst_float> out_preds = {0.5f, 0.524f, 0.622f, 0.710f, 0.731f};
obj->PredTransform(&io_preds);
auto& preds = io_preds.HostVector();
for (int i = 0; i < static_cast<int>(io_preds.Size()); ++i) {
EXPECT_NEAR(preds[i], out_preds[i], 0.01f);
}
delete obj;
}
TEST(Objective, DeclareUnifiedTest(LogisticRawGPair)) {
xgboost::GenericParameter lparam = xgboost::CreateEmptyGenericParam(GPUIDX);
GenericParameter lparam = CreateEmptyGenericParam(GPUIDX);
std::vector<std::pair<std::string, std::string>> args;
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("binary:logitraw", &lparam);
std::unique_ptr<ObjFunction> obj {
ObjFunction::Create("binary:logitraw", &lparam)
};
obj->Configure(args);
CheckObjFunction(obj,
{ 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},
{ 0.5f, 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});
delete obj;
}
TEST(Objective, DeclareUnifiedTest(PoissonRegressionGPair)) {
xgboost::GenericParameter lparam = xgboost::CreateEmptyGenericParam(GPUIDX);
GenericParameter lparam = CreateEmptyGenericParam(GPUIDX);
std::vector<std::pair<std::string, std::string>> args;
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("count:poisson", &lparam);
std::unique_ptr<ObjFunction> obj {
ObjFunction::Create("count:poisson", &lparam)
};
args.emplace_back(std::make_pair("max_delta_step", "0.1f"));
obj->Configure(args);
CheckObjFunction(obj,
{ 0, 0.1f, 0.9f, 1, 0, 0.1f, 0.9f, 1},
{ 0, 0, 0, 0, 1, 1, 1, 1},
@@ -136,15 +141,17 @@ TEST(Objective, DeclareUnifiedTest(PoissonRegressionGPair)) {
{}, // Empty weight
{ 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});
delete obj;
}
TEST(Objective, DeclareUnifiedTest(PoissonRegressionBasic)) {
xgboost::GenericParameter lparam = xgboost::CreateEmptyGenericParam(GPUIDX);
GenericParameter lparam = CreateEmptyGenericParam(GPUIDX);
std::vector<std::pair<std::string, std::string>> args;
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("count:poisson", &lparam);
std::unique_ptr<ObjFunction> obj {
ObjFunction::Create("count:poisson", &lparam)
};
obj->Configure(args);
CheckConfigReload(obj, "count:poisson");
// test label validation
EXPECT_ANY_THROW(CheckObjFunction(obj, {0}, {-1}, {1}, {0}, {0}))
@@ -156,21 +163,21 @@ TEST(Objective, DeclareUnifiedTest(PoissonRegressionBasic)) {
EXPECT_NEAR(obj->ProbToMargin(0.9f), -0.10f, 0.01f);
// test PredTransform
xgboost::HostDeviceVector<xgboost::bst_float> io_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};
HostDeviceVector<bst_float> io_preds = {0, 0.1f, 0.5f, 0.9f, 1};
std::vector<bst_float> out_preds = {1, 1.10f, 1.64f, 2.45f, 2.71f};
obj->PredTransform(&io_preds);
auto& preds = io_preds.HostVector();
for (int i = 0; i < static_cast<int>(io_preds.Size()); ++i) {
EXPECT_NEAR(preds[i], out_preds[i], 0.01f);
}
delete obj;
}
TEST(Objective, DeclareUnifiedTest(GammaRegressionGPair)) {
xgboost::GenericParameter lparam = xgboost::CreateEmptyGenericParam(GPUIDX);
GenericParameter lparam = CreateEmptyGenericParam(GPUIDX);
std::vector<std::pair<std::string, std::string>> args;
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("reg:gamma", &lparam);
std::unique_ptr<ObjFunction> obj {
ObjFunction::Create("reg:gamma", &lparam)
};
obj->Configure(args);
CheckObjFunction(obj,
@@ -185,15 +192,17 @@ TEST(Objective, DeclareUnifiedTest(GammaRegressionGPair)) {
{}, // Empty weight
{1, 1, 1, 1, 0, 0.09f, 0.59f, 0.63f},
{0, 0, 0, 0, 1, 0.90f, 0.40f, 0.36f});
delete obj;
}
TEST(Objective, DeclareUnifiedTest(GammaRegressionBasic)) {
xgboost::GenericParameter lparam = xgboost::CreateEmptyGenericParam(GPUIDX);
GenericParameter lparam = CreateEmptyGenericParam(GPUIDX);
std::vector<std::pair<std::string, std::string>> args;
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("reg:gamma", &lparam);
std::unique_ptr<ObjFunction> obj {
ObjFunction::Create("reg:gamma", &lparam)
};
obj->Configure(args);
CheckConfigReload(obj, "reg:gamma");
// test label validation
EXPECT_ANY_THROW(CheckObjFunction(obj, {0}, {-1}, {1}, {0}, {0}))
@@ -205,24 +214,25 @@ TEST(Objective, DeclareUnifiedTest(GammaRegressionBasic)) {
EXPECT_NEAR(obj->ProbToMargin(0.9f), -0.10f, 0.01f);
// test PredTransform
xgboost::HostDeviceVector<xgboost::bst_float> io_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};
HostDeviceVector<bst_float> io_preds = {0, 0.1f, 0.5f, 0.9f, 1};
std::vector<bst_float> out_preds = {1, 1.10f, 1.64f, 2.45f, 2.71f};
obj->PredTransform(&io_preds);
auto& preds = io_preds.HostVector();
for (int i = 0; i < static_cast<int>(io_preds.Size()); ++i) {
EXPECT_NEAR(preds[i], out_preds[i], 0.01f);
}
delete obj;
}
TEST(Objective, DeclareUnifiedTest(TweedieRegressionGPair)) {
xgboost::GenericParameter lparam = xgboost::CreateEmptyGenericParam(GPUIDX);
GenericParameter lparam = CreateEmptyGenericParam(GPUIDX);
std::vector<std::pair<std::string, std::string>> args;
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("reg:tweedie", &lparam);
std::unique_ptr<ObjFunction> obj {
ObjFunction::Create("reg:tweedie", &lparam)
};
args.emplace_back(std::make_pair("tweedie_variance_power", "1.1f"));
obj->Configure(args);
CheckObjFunction(obj,
{ 0, 0.1f, 0.9f, 1, 0, 0.1f, 0.9f, 1},
{ 0, 0, 0, 0, 1, 1, 1, 1},
@@ -236,22 +246,21 @@ TEST(Objective, DeclareUnifiedTest(TweedieRegressionGPair)) {
{ 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});
ASSERT_EQ(obj->DefaultEvalMetric(), std::string{"tweedie-nloglik@1.1"});
delete obj;
}
#if defined(__CUDACC__)
TEST(Objective, CPU_vs_CUDA) {
xgboost::GenericParameter lparam = xgboost::CreateEmptyGenericParam(GPUIDX);
GenericParameter lparam = CreateEmptyGenericParam(GPUIDX);
xgboost::ObjFunction * obj =
xgboost::ObjFunction::Create("reg:squarederror", &lparam);
xgboost::HostDeviceVector<xgboost::GradientPair> cpu_out_preds;
xgboost::HostDeviceVector<xgboost::GradientPair> cuda_out_preds;
ObjFunction * obj =
ObjFunction::Create("reg:squarederror", &lparam);
HostDeviceVector<GradientPair> cpu_out_preds;
HostDeviceVector<GradientPair> cuda_out_preds;
constexpr size_t kRows = 400;
constexpr size_t kCols = 100;
auto ppdmat = xgboost::CreateDMatrix(kRows, kCols, 0, 0);
xgboost::HostDeviceVector<float> preds;
auto ppdmat = CreateDMatrix(kRows, kCols, 0, 0);
HostDeviceVector<float> preds;
preds.Resize(kRows);
auto& h_preds = preds.HostVector();
for (size_t i = 0; i < h_preds.size(); ++i) {
@@ -285,8 +294,8 @@ TEST(Objective, CPU_vs_CUDA) {
sgrad += std::pow(h_cpu_out[i].GetGrad() - h_cuda_out[i].GetGrad(), 2);
shess += std::pow(h_cpu_out[i].GetHess() - h_cuda_out[i].GetHess(), 2);
}
ASSERT_NEAR(sgrad, 0.0f, xgboost::kRtEps);
ASSERT_NEAR(shess, 0.0f, xgboost::kRtEps);
ASSERT_NEAR(sgrad, 0.0f, kRtEps);
ASSERT_NEAR(shess, 0.0f, kRtEps);
delete ppdmat;
delete obj;
@@ -294,11 +303,14 @@ TEST(Objective, CPU_vs_CUDA) {
#endif
TEST(Objective, DeclareUnifiedTest(TweedieRegressionBasic)) {
xgboost::GenericParameter lparam = xgboost::CreateEmptyGenericParam(GPUIDX);
GenericParameter lparam = CreateEmptyGenericParam(GPUIDX);
std::vector<std::pair<std::string, std::string>> args;
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("reg:tweedie", &lparam);
std::unique_ptr<ObjFunction> obj {
ObjFunction::Create("reg:tweedie", &lparam)
};
obj->Configure(args);
CheckConfigReload(obj, "reg:tweedie");
// test label validation
EXPECT_ANY_THROW(CheckObjFunction(obj, {0}, {-1}, {1}, {0}, {0}))
@@ -310,25 +322,23 @@ TEST(Objective, DeclareUnifiedTest(TweedieRegressionBasic)) {
EXPECT_NEAR(obj->ProbToMargin(0.9f), -0.10f, 0.01f);
// test PredTransform
xgboost::HostDeviceVector<xgboost::bst_float> io_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};
HostDeviceVector<bst_float> io_preds = {0, 0.1f, 0.5f, 0.9f, 1};
std::vector<bst_float> out_preds = {1, 1.10f, 1.64f, 2.45f, 2.71f};
obj->PredTransform(&io_preds);
auto& preds = io_preds.HostVector();
for (int i = 0; i < static_cast<int>(io_preds.Size()); ++i) {
EXPECT_NEAR(preds[i], out_preds[i], 0.01f);
}
delete obj;
}
// CoxRegression not implemented in GPU code, no need for testing.
#if !defined(__CUDACC__)
TEST(Objective, CoxRegressionGPair) {
xgboost::GenericParameter lparam = xgboost::CreateEmptyGenericParam(GPUIDX);
GenericParameter lparam = CreateEmptyGenericParam(GPUIDX);
std::vector<std::pair<std::string, std::string>> args;
xgboost::ObjFunction * obj =
xgboost::ObjFunction::Create("survival:cox", &lparam);
std::unique_ptr<ObjFunction> obj {
ObjFunction::Create("survival:cox", &lparam)
};
obj->Configure(args);
CheckObjFunction(obj,
@@ -337,7 +347,7 @@ TEST(Objective, CoxRegressionGPair) {
{ 1, 1, 1, 1, 1, 1, 1, 1},
{ 0, 0, 0, -0.799f, -0.788f, -0.590f, 0.910f, 1.006f},
{ 0, 0, 0, 0.160f, 0.186f, 0.348f, 0.610f, 0.639f});
delete obj;
}
#endif
} // namespace xgboost