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

De-duplicate GPU parameters. (#4454)

Browse Source 
* Only define `gpu_id` and `n_gpus` in `LearnerTrainParam`
* Pass LearnerTrainParam through XGBoost vid factory method.
* Disable all GPU usage when GPU related parameters are not specified (fixes XGBoost choosing GPU over aggressively).
* Test learner train param io.
* Fix gpu pickling.
This commit is contained in:
Jiaming Yuan
2019-05-29 11:55:57 +08:00
committed by GitHub
parent a3fedbeaa8
commit c589eff941
69 changed files with 927 additions and 562 deletions
Download Patch File Download Diff File Expand all files Collapse all files

7
tests/cpp/objective/test_hinge.cc
View File

@@ -1,13 +1,14 @@
// Copyright by Contributors
#include <xgboost/objective.h>
#include <xgboost/generic_parameters.h>
#include <limits>
#include "../helpers.h"
TEST(Objective, DeclareUnifiedTest(HingeObj)) {
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("binary:hinge");
std::vector<std::pair<std::string, std::string> > args;
obj->Configure(args);
xgboost::LearnerTrainParam tparam = xgboost::CreateEmptyGenericParam(0, NGPUS);
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("binary:hinge", &tparam);
xgboost::bst_float eps = std::numeric_limits<xgboost::bst_float>::min();
CheckObjFunction(obj,
{-1.0f, -0.5f, 0.5f, 1.0f, -1.0f, -0.5f, 0.5f, 1.0f},

25
tests/cpp/objective/test_multiclass_obj.cc
View File

@@ -1,13 +1,16 @@
/*!
* Copyright 2018 XGBoost contributors
* Copyright 2018-2019 XGBoost contributors
*/
#include <xgboost/objective.h>
#include <xgboost/generic_parameters.h>
#include "../../src/common/common.h"
#include "../helpers.h"
TEST(Objective, DeclareUnifiedTest(SoftmaxMultiClassObjGPair)) {
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("multi:softmax");
xgboost::LearnerTrainParam lparam = xgboost::CreateEmptyGenericParam(0, NGPUS);
std::vector<std::pair<std::string, std::string>> args {{"num_class", "3"}};
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("multi:softmax", &lparam);
obj->Configure(args);
CheckObjFunction(obj,
{1.0f, 0.0f, 2.0f, 2.0f, 0.0f, 1.0f}, // preds
@@ -22,9 +25,11 @@ TEST(Objective, DeclareUnifiedTest(SoftmaxMultiClassObjGPair)) {
}
TEST(Objective, DeclareUnifiedTest(SoftmaxMultiClassBasic)) {
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("multi:softmax");
std::vector<std::pair<std::string, std::string>> args
{std::pair<std::string, std::string>("num_class", "3")};
auto lparam = xgboost::CreateEmptyGenericParam(0, NGPUS);
std::vector<std::pair<std::string, std::string>> args{
std::pair<std::string, std::string>("num_class", "3")};
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("multi:softmax", &lparam);
obj->Configure(args);
xgboost::HostDeviceVector<xgboost::bst_float> io_preds = {2.0f, 0.0f, 1.0f,
@@ -42,9 +47,11 @@ TEST(Objective, DeclareUnifiedTest(SoftmaxMultiClassBasic)) {
}
TEST(Objective, DeclareUnifiedTest(SoftprobMultiClassBasic)) {
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("multi:softprob");
std::vector<std::pair<std::string, std::string>> args
{std::pair<std::string, std::string>("num_class", "3")};
xgboost::LearnerTrainParam lparam = xgboost::CreateEmptyGenericParam(0, NGPUS);
std::vector<std::pair<std::string, std::string>> args {
std::pair<std::string, std::string>("num_class", "3")};
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("multi:softprob", &lparam);
obj->Configure(args);
xgboost::HostDeviceVector<xgboost::bst_float> io_preds = {2.0f, 0.0f, 1.0f};

9
tests/cpp/objective/test_objective.cc
View File

@@ -1,13 +1,18 @@
// Copyright by Contributors
#include <gtest/gtest.h>
#include <xgboost/objective.h>
#include <xgboost/generic_parameters.h>
#include "../helpers.h"
TEST(Objective, UnknownFunction) {
xgboost::ObjFunction* obj = nullptr;
EXPECT_ANY_THROW(obj = xgboost::ObjFunction::Create("unknown_name"));
EXPECT_NO_THROW(obj = xgboost::ObjFunction::Create("reg:squarederror"));
xgboost::LearnerTrainParam tparam;
std::vector<std::pair<std::string, std::string>> args;
tparam.InitAllowUnknown(args);
EXPECT_ANY_THROW(obj = xgboost::ObjFunction::Create("unknown_name", &tparam));
EXPECT_NO_THROW(obj = xgboost::ObjFunction::Create("reg:squarederror", &tparam));
if (obj) {
delete obj;
}

10
tests/cpp/objective/test_ranking_obj.cc
View File

@@ -1,11 +1,15 @@
// Copyright by Contributors
#include <xgboost/objective.h>
#include <xgboost/generic_parameters.h>
#include "../helpers.h"
TEST(Objective, PairwiseRankingGPair) {
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("rank:pairwise");
std::vector<std::pair<std::string, std::string> > args;
xgboost::LearnerTrainParam tparam;
std::vector<std::pair<std::string, std::string>> args;
tparam.InitAllowUnknown(args);
xgboost::ObjFunction * obj =
xgboost::ObjFunction::Create("rank:pairwise", &tparam);
obj->Configure(args);
// Test with setting sample weight to second query group
CheckRankingObjFunction(obj,

125
tests/cpp/objective/test_regression_obj.cc
View File

@@ -3,12 +3,16 @@
*/
#include <gtest/gtest.h>
#include <xgboost/objective.h>
#include <xgboost/generic_parameters.h>
#include "../helpers.h"
TEST(Objective, DeclareUnifiedTest(LinearRegressionGPair)) {
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("reg:squarederror");
std::vector<std::pair<std::string, std::string> > args;
xgboost::LearnerTrainParam tparam = xgboost::CreateEmptyGenericParam(0, NGPUS);
std::vector<std::pair<std::string, std::string>> args;
xgboost::ObjFunction * obj =
xgboost::ObjFunction::Create("reg:squarederror", &tparam);
obj->Configure(args);
CheckObjFunction(obj,
{0, 0.1f, 0.9f, 1, 0, 0.1f, 0.9f, 1},
@@ -28,8 +32,10 @@ TEST(Objective, DeclareUnifiedTest(LinearRegressionGPair)) {
}
TEST(Objective, DeclareUnifiedTest(LogisticRegressionGPair)) {
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("reg:logistic");
std::vector<std::pair<std::string, std::string> > args;
xgboost::LearnerTrainParam tparam = xgboost::CreateEmptyGenericParam(0, NGPUS);
std::vector<std::pair<std::string, std::string>> args;
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("reg:logistic", &tparam);
obj->Configure(args);
CheckObjFunction(obj,
{ 0, 0.1f, 0.9f, 1, 0, 0.1f, 0.9f, 1}, // preds
@@ -42,8 +48,10 @@ TEST(Objective, DeclareUnifiedTest(LogisticRegressionGPair)) {
}
TEST(Objective, DeclareUnifiedTest(LogisticRegressionBasic)) {
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("reg:logistic");
std::vector<std::pair<std::string, std::string> > args;
xgboost::LearnerTrainParam lparam = xgboost::CreateEmptyGenericParam(0, NGPUS);
std::vector<std::pair<std::string, std::string>> args;
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("reg:logistic", &lparam);
obj->Configure(args);
// test label validation
@@ -70,8 +78,10 @@ TEST(Objective, DeclareUnifiedTest(LogisticRegressionBasic)) {
}
TEST(Objective, DeclareUnifiedTest(LogisticRawGPair)) {
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("binary:logitraw");
std::vector<std::pair<std::string, std::string> > args;
xgboost::LearnerTrainParam lparam = xgboost::CreateEmptyGenericParam(0, NGPUS);
std::vector<std::pair<std::string, std::string>> args;
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("binary:logitraw", &lparam);
obj->Configure(args);
CheckObjFunction(obj,
{ 0, 0.1f, 0.9f, 1, 0, 0.1f, 0.9f, 1},
@@ -84,8 +94,10 @@ TEST(Objective, DeclareUnifiedTest(LogisticRawGPair)) {
}
TEST(Objective, DeclareUnifiedTest(PoissonRegressionGPair)) {
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("count:poisson");
std::vector<std::pair<std::string, std::string> > args;
xgboost::LearnerTrainParam lparam = xgboost::CreateEmptyGenericParam(0, NGPUS);
std::vector<std::pair<std::string, std::string>> args;
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("count:poisson", &lparam);
args.emplace_back(std::make_pair("max_delta_step", "0.1f"));
obj->Configure(args);
CheckObjFunction(obj,
@@ -104,8 +116,10 @@ TEST(Objective, DeclareUnifiedTest(PoissonRegressionGPair)) {
}
TEST(Objective, DeclareUnifiedTest(PoissonRegressionBasic)) {
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("count:poisson");
std::vector<std::pair<std::string, std::string> > args;
xgboost::LearnerTrainParam lparam = xgboost::CreateEmptyGenericParam(0, NGPUS);
std::vector<std::pair<std::string, std::string>> args;
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("count:poisson", &lparam);
obj->Configure(args);
// test label validation
@@ -130,8 +144,10 @@ TEST(Objective, DeclareUnifiedTest(PoissonRegressionBasic)) {
}
TEST(Objective, DeclareUnifiedTest(GammaRegressionGPair)) {
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("reg:gamma");
std::vector<std::pair<std::string, std::string> > args;
xgboost::LearnerTrainParam lparam = xgboost::CreateEmptyGenericParam(0, NGPUS);
std::vector<std::pair<std::string, std::string>> args;
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("reg:gamma", &lparam);
obj->Configure(args);
CheckObjFunction(obj,
{0, 0.1f, 0.9f, 1, 0, 0.1f, 0.9f, 1},
@@ -149,8 +165,10 @@ TEST(Objective, DeclareUnifiedTest(GammaRegressionGPair)) {
}
TEST(Objective, DeclareUnifiedTest(GammaRegressionBasic)) {
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("reg:gamma");
std::vector<std::pair<std::string, std::string> > args;
xgboost::LearnerTrainParam lparam = xgboost::CreateEmptyGenericParam(0, NGPUS);
std::vector<std::pair<std::string, std::string>> args;
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("reg:gamma", &lparam);
obj->Configure(args);
// test label validation
@@ -175,8 +193,10 @@ TEST(Objective, DeclareUnifiedTest(GammaRegressionBasic)) {
}
TEST(Objective, DeclareUnifiedTest(TweedieRegressionGPair)) {
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("reg:tweedie");
std::vector<std::pair<std::string, std::string> > args;
xgboost::LearnerTrainParam lparam = xgboost::CreateEmptyGenericParam(0, NGPUS);
std::vector<std::pair<std::string, std::string>> args;
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("reg:tweedie", &lparam);
args.emplace_back(std::make_pair("tweedie_variance_power", "1.1f"));
obj->Configure(args);
CheckObjFunction(obj,
@@ -195,9 +215,65 @@ TEST(Objective, DeclareUnifiedTest(TweedieRegressionGPair)) {
delete obj;
}
#if defined(__CUDACC__)
TEST(Objective, CPU_vs_CUDA) {
xgboost::LearnerTrainParam lparam = xgboost::CreateEmptyGenericParam(0, 1);
xgboost::ObjFunction * obj =
xgboost::ObjFunction::Create("reg:squarederror", &lparam);
xgboost::HostDeviceVector<xgboost::GradientPair> cpu_out_preds;
xgboost::HostDeviceVector<xgboost::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;
preds.Resize(kRows);
auto& h_preds = preds.HostVector();
for (size_t i = 0; i < h_preds.size(); ++i) {
h_preds[i] = static_cast<float>(i);
}
auto& info = (*ppdmat)->Info();
info.labels_.Resize(kRows);
auto& h_labels = info.labels_.HostVector();
for (size_t i = 0; i < h_labels.size(); ++i) {
h_labels[i] = 1 / (float)(i+1);
}
{
// CPU
lparam.n_gpus = 0;
obj->GetGradient(preds, info, 0, &cpu_out_preds);
}
{
// CUDA
lparam.n_gpus = 1;
obj->GetGradient(preds, info, 0, &cuda_out_preds);
}
auto& h_cpu_out = cpu_out_preds.HostVector();
auto& h_cuda_out = cuda_out_preds.HostVector();
float sgrad = 0;
float shess = 0;
for (size_t i = 0; i < kRows; ++i) {
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);
delete ppdmat;
delete obj;
}
#endif
TEST(Objective, DeclareUnifiedTest(TweedieRegressionBasic)) {
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("reg:tweedie");
std::vector<std::pair<std::string, std::string> > args;
xgboost::LearnerTrainParam lparam = xgboost::CreateEmptyGenericParam(0, NGPUS);
std::vector<std::pair<std::string, std::string>> args;
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("reg:tweedie", &lparam);
obj->Configure(args);
// test label validation
@@ -225,8 +301,11 @@ TEST(Objective, DeclareUnifiedTest(TweedieRegressionBasic)) {
// CoxRegression not implemented in GPU code, no need for testing.
#if !defined(__CUDACC__)
TEST(Objective, CoxRegressionGPair) {
xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("survival:cox");
std::vector<std::pair<std::string, std::string> > args;
xgboost::LearnerTrainParam lparam = xgboost::CreateEmptyGenericParam(0, 0);
std::vector<std::pair<std::string, std::string>> args;
xgboost::ObjFunction * obj =
xgboost::ObjFunction::Create("survival:cox", &lparam);
obj->Configure(args);
CheckObjFunction(obj,
{ 0, 0.1f, 0.9f, 1, 0, 0.1f, 0.9f, 1},