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Rename and extract Context. (#8528)

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* Rename `GenericParameter` to `Context`.
* Rename header file to reflect the change.
* Rename all references.
This commit is contained in:
Jiaming Yuan 2022-12-07 04:58:54 +08:00 committed by GitHub
parent 05fc6f3ca9
commit 3e26107a9c
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GPG Key ID: 4AEE18F83AFDEB23
105 changed files with 548 additions and 574 deletions
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1
R-package/src/Makevars.in
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@ -68,6 +68,7 @@ OBJECTS= \
$(PKGROOT)/src/linear/updater_coordinate.o \
$(PKGROOT)/src/linear/updater_shotgun.o \
$(PKGROOT)/src/learner.o \
$(PKGROOT)/src/context.o \
$(PKGROOT)/src/logging.o \
$(PKGROOT)/src/global_config.o \
$(PKGROOT)/src/collective/communicator.o \

1
R-package/src/Makevars.win
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@ -68,6 +68,7 @@ OBJECTS= \
$(PKGROOT)/src/linear/updater_coordinate.o \
$(PKGROOT)/src/linear/updater_shotgun.o \
$(PKGROOT)/src/learner.o \
$(PKGROOT)/src/context.o \
$(PKGROOT)/src/logging.o \
$(PKGROOT)/src/global_config.o \
$(PKGROOT)/src/collective/communicator.o \

9
R-package/src/xgboost_R.cc
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@ -4,8 +4,8 @@
#include <dmlc/common.h>
#include <dmlc/omp.h>
#include <xgboost/c_api.h>
#include <xgboost/context.h>
#include <xgboost/data.h>
#include <xgboost/generic_parameters.h>
#include <xgboost/logging.h>
#include <cstdio>
@ -18,7 +18,8 @@
#include "../../src/c_api/c_api_error.h"
#include "../../src/common/threading_utils.h"
#include "./xgboost_R.h"
#include "./xgboost_R.h" // Must follow other include.
/*!
* \brief macro to annotate begin of api
@ -46,14 +47,14 @@
using dmlc::BeginPtr;
xgboost::GenericParameter const *BoosterCtx(BoosterHandle handle) {
xgboost::Context const *BoosterCtx(BoosterHandle handle) {
CHECK_HANDLE();
auto *learner = static_cast<xgboost::Learner *>(handle);
CHECK(learner);
return learner->Ctx();
}
xgboost::GenericParameter const *DMatrixCtx(DMatrixHandle handle) {
xgboost::Context const *DMatrixCtx(DMatrixHandle handle) {
CHECK_HANDLE();
auto p_m = static_cast<std::shared_ptr<xgboost::DMatrix> *>(handle);
CHECK(p_m);

47
include/xgboost/generic_parameters.h → include/xgboost/context.h
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@ -1,9 +1,9 @@
/*!
* Copyright 2014-2019 by Contributors
* \file generic_parameters.h
* Copyright 2014-2022 by Contributors
* \file context.h
*/
#ifndef XGBOOST_GENERIC_PARAMETERS_H_
#define XGBOOST_GENERIC_PARAMETERS_H_
#ifndef XGBOOST_CONTEXT_H_
#define XGBOOST_CONTEXT_H_
#include <xgboost/logging.h>
#include <xgboost/parameter.h>
@ -12,28 +12,28 @@
namespace xgboost {
struct GenericParameter : public XGBoostParameter<GenericParameter> {
struct Context : public XGBoostParameter<Context> {
private:
// cached value for CFS CPU limit. (used in containerized env)
int32_t cfs_cpu_count_; // NOLINT
std::int32_t cfs_cpu_count_; // NOLINT
public:
// Constant representing the device ID of CPU.
static int32_t constexpr kCpuId = -1;
static int64_t constexpr kDefaultSeed = 0;
static std::int32_t constexpr kCpuId = -1;
static std::int64_t constexpr kDefaultSeed = 0;
public:
GenericParameter();
Context();
// stored random seed
int64_t seed { kDefaultSeed };
std::int64_t seed{kDefaultSeed};
// whether seed the PRNG each iteration
bool seed_per_iteration{false};
// number of threads to use if OpenMP is enabled
// if equals 0, use system default
int nthread{0};
std::int32_t nthread{0};
// primary device, -1 means no gpu.
int gpu_id{kCpuId};
std::int32_t gpu_id{kCpuId};
// fail when gpu_id is invalid
bool fail_on_invalid_gpu_id{false};
bool validate_parameters{false};
@ -47,26 +47,25 @@ struct GenericParameter : public XGBoostParameter<GenericParameter> {
/*!
* Return automatically chosen threads.
*/
int32_t Threads() const;
std::int32_t Threads() const;
bool IsCPU() const { return gpu_id == kCpuId; }
bool IsCUDA() const { return !IsCPU(); }
// declare parameters
DMLC_DECLARE_PARAMETER(GenericParameter) {
DMLC_DECLARE_FIELD(seed).set_default(kDefaultSeed).describe(
"Random number seed during training.");
DMLC_DECLARE_PARAMETER(Context) {
DMLC_DECLARE_FIELD(seed)
.set_default(kDefaultSeed)
.describe("Random number seed during training.");
DMLC_DECLARE_ALIAS(seed, random_state);
DMLC_DECLARE_FIELD(seed_per_iteration)
.set_default(false)
.describe("Seed PRNG determnisticly via iterator number.");
DMLC_DECLARE_FIELD(nthread).set_default(0).describe(
"Number of threads to use.");
DMLC_DECLARE_FIELD(nthread).set_default(0).describe("Number of threads to use.");
DMLC_DECLARE_ALIAS(nthread, n_jobs);
DMLC_DECLARE_FIELD(gpu_id)
.set_default(-1)
.set_lower_bound(-1)
.describe("The primary GPU device ordinal.");
DMLC_DECLARE_FIELD(gpu_id).set_default(-1).set_lower_bound(-1).describe(
"The primary GPU device ordinal.");
DMLC_DECLARE_FIELD(fail_on_invalid_gpu_id)
.set_default(false)
.describe("Fail with error when gpu_id is invalid.");
@ -75,8 +74,6 @@ struct GenericParameter : public XGBoostParameter<GenericParameter> {
.describe("Enable checking whether parameters are used or not.");
}
};
using Context = GenericParameter;
} // namespace xgboost
#endif // XGBOOST_GENERIC_PARAMETERS_H_
#endif // XGBOOST_CONTEXT_H_

2
include/xgboost/data.h
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@ -11,7 +11,6 @@
#include <dmlc/data.h>
#include <dmlc/serializer.h>
#include <xgboost/base.h>
#include <xgboost/generic_parameters.h>
#include <xgboost/host_device_vector.h>
#include <xgboost/linalg.h>
#include <xgboost/span.h>
@ -28,6 +27,7 @@
namespace xgboost {
// forward declare dmatrix.
class DMatrix;
struct Context;
/*! \brief data type accepted by xgboost interface */
enum class DataType : uint8_t {

12
include/xgboost/gbm.h
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@ -28,7 +28,7 @@ class Json;
class FeatureMap;
class ObjFunction;
struct GenericParameter;
struct Context;
struct LearnerModelParam;
struct PredictionCacheEntry;
class PredictionContainer;
@ -38,8 +38,8 @@ class PredictionContainer;
*/
class GradientBooster : public Model, public Configurable {
protected:
GenericParameter const* ctx_;
explicit GradientBooster(GenericParameter const* ctx) : ctx_{ctx} {}
Context const* ctx_;
explicit GradientBooster(Context const* ctx) : ctx_{ctx} {}
public:
/*! \brief virtual destructor */
@ -193,9 +193,7 @@ class GradientBooster : public Model, public Configurable {
* \param learner_model_param pointer to global model parameters
* \return The created booster.
*/
static GradientBooster* Create(
const std::string& name,
GenericParameter const* generic_param,
static GradientBooster* Create(const std::string& name, Context const* ctx,
LearnerModelParam const* learner_model_param);
};
@ -206,7 +204,7 @@ struct GradientBoosterReg
: public dmlc::FunctionRegEntryBase<
GradientBoosterReg,
std::function<GradientBooster*(LearnerModelParam const* learner_model_param,
GenericParameter const* ctx)> > {};
Context const* ctx)> > {};
/*!
* \brief Macro to register gradient booster.

2
include/xgboost/learner.h
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@ -9,8 +9,8 @@
#define XGBOOST_LEARNER_H_
#include <xgboost/base.h>
#include <xgboost/context.h> // Context
#include <xgboost/feature_map.h>
#include <xgboost/generic_parameters.h> // Context
#include <xgboost/host_device_vector.h>
#include <xgboost/model.h>
#include <xgboost/predictor.h>

2
include/xgboost/linalg.h
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@ -8,7 +8,7 @@
#include <dmlc/endian.h>
#include <xgboost/base.h>
#include <xgboost/generic_parameters.h>
#include <xgboost/context.h> // fixme(jiamingy): Remove the dependency on this header.
#include <xgboost/host_device_vector.h>
#include <xgboost/json.h>
#include <xgboost/span.h>

6
include/xgboost/linear_updater.h
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@ -6,7 +6,6 @@
#include <dmlc/registry.h>
#include <xgboost/base.h>
#include <xgboost/data.h>
#include <xgboost/generic_parameters.h>
#include <xgboost/host_device_vector.h>
#include <xgboost/model.h>
@ -19,6 +18,7 @@
namespace xgboost {
class Json;
struct Context;
namespace gbm {
class GBLinearModel;
@ -29,7 +29,7 @@ class GBLinearModel;
*/
class LinearUpdater : public Configurable {
protected:
GenericParameter const* ctx_;
Context const* ctx_;
public:
/*! \brief virtual destructor */
@ -57,7 +57,7 @@ class LinearUpdater : public Configurable {
* \brief Create a linear updater given name
* \param name Name of the linear updater.
*/
static LinearUpdater* Create(const std::string& name, GenericParameter const*);
static LinearUpdater* Create(const std::string& name, Context const*);
};
/*!

9
include/xgboost/metric.h
View File

@ -9,7 +9,6 @@
#include <dmlc/registry.h>
#include <xgboost/model.h>
#include <xgboost/generic_parameters.h>
#include <xgboost/data.h>
#include <xgboost/base.h>
#include <xgboost/host_device_vector.h>
@ -20,13 +19,15 @@
#include <utility>
namespace xgboost {
struct Context;
/*!
* \brief interface of evaluation metric used to evaluate model performance.
* This has nothing to do with training, but merely act as evaluation purpose.
*/
class Metric : public Configurable {
protected:
GenericParameter const* tparam_;
Context const* tparam_;
public:
/*!
@ -68,10 +69,10 @@ class Metric : public Configurable {
* \param name name of the metric.
* name can be in form metric[@]param and the name will be matched in the
* registry.
* \param tparam A global generic parameter
* \param ctx A global context
* \return the created metric.
*/
static Metric* Create(const std::string& name, GenericParameter const* tparam);
static Metric* Create(const std::string& name, Context const* ctx);
};
/*!

14
include/xgboost/objective.h
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@ -10,19 +10,19 @@
#include <dmlc/registry.h>
#include <xgboost/base.h>
#include <xgboost/data.h>
#include <xgboost/model.h>
#include <xgboost/generic_parameters.h>
#include <xgboost/host_device_vector.h>
#include <xgboost/model.h>
#include <xgboost/task.h>
#include <vector>
#include <utility>
#include <string>
#include <functional>
#include <string>
#include <utility>
#include <vector>
namespace xgboost {
class RegTree;
struct Context;
/*! \brief interface of objective function */
class ObjFunction : public Configurable {
@ -120,10 +120,10 @@ class ObjFunction : public Configurable {
/*!
* \brief Create an objective function according to name.
* \param tparam Generic parameters.
* \param ctx Pointer to runtime parameters.
* \param name Name of the objective.
*/
static ObjFunction* Create(const std::string& name, GenericParameter const* tparam);
static ObjFunction* Create(const std::string& name, Context const* ctx);
};
/*!

16
include/xgboost/predictor.h
View File

@ -1,22 +1,22 @@
/*!
* Copyright 2017-2021 by Contributors
* Copyright 2017-2022 by Contributors
* \file predictor.h
* \brief Interface of predictor,
* performs predictions for a gradient booster.
*/
#pragma once
#include <xgboost/base.h>
#include <xgboost/context.h>
#include <xgboost/data.h>
#include <xgboost/generic_parameters.h>
#include <xgboost/host_device_vector.h>
#include <functional>
#include <memory>
#include <mutex>
#include <string>
#include <unordered_map>
#include <utility>
#include <vector>
#include <mutex>
// Forward declarations
namespace xgboost {
@ -73,7 +73,7 @@ class PredictionContainer {
*
* \param m shared pointer to the DMatrix that needs to be cached.
* \param device Which device should the cache be allocated on. Pass
* GenericParameter::kCpuId for CPU or positive integer for GPU id.
* Context::kCpuId for CPU or positive integer for GPU id.
*
* \return the cache entry for passed in DMatrix, either an existing cache or newly
* created.
@ -219,18 +219,16 @@ class Predictor {
* \brief Creates a new Predictor*.
*
* \param name Name of the predictor.
* \param generic_param Pointer to runtime parameters.
* \param ctx Pointer to runtime parameters.
*/
static Predictor* Create(
std::string const& name, GenericParameter const* generic_param);
static Predictor* Create(std::string const& name, Context const* ctx);
};
/*!
* \brief Registry entry for predictor.
*/
struct PredictorReg
: public dmlc::FunctionRegEntryBase<
PredictorReg, std::function<Predictor*(GenericParameter const*)>> {};
: public dmlc::FunctionRegEntryBase<PredictorReg, std::function<Predictor*(Context const*)>> {};
#define XGBOOST_REGISTER_PREDICTOR(UniqueId, Name) \
static DMLC_ATTRIBUTE_UNUSED ::xgboost::PredictorReg& \

14
include/xgboost/tree_updater.h
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@ -10,8 +10,8 @@
#include <dmlc/registry.h>
#include <xgboost/base.h>
#include <xgboost/context.h>
#include <xgboost/data.h>
#include <xgboost/generic_parameters.h>
#include <xgboost/host_device_vector.h>
#include <xgboost/linalg.h>
#include <xgboost/model.h>
@ -26,16 +26,17 @@
namespace xgboost {
class Json;
struct Context;
/*!
* \brief interface of tree update module, that performs update of a tree.
*/
class TreeUpdater : public Configurable {
protected:
GenericParameter const* ctx_ = nullptr;
Context const* ctx_ = nullptr;
public:
explicit TreeUpdater(const GenericParameter* ctx) : ctx_(ctx) {}
explicit TreeUpdater(const Context* ctx) : ctx_(ctx) {}
/*! \brief virtual destructor */
~TreeUpdater() override = default;
/*!
@ -90,9 +91,9 @@ class TreeUpdater : public Configurable {
/*!
* \brief Create a tree updater given name
* \param name Name of the tree updater.
* \param tparam A global runtime parameter
* \param ctx A global runtime parameter
*/
static TreeUpdater* Create(const std::string& name, GenericParameter const* tparam, ObjInfo task);
static TreeUpdater* Create(const std::string& name, Context const* ctx, ObjInfo task);
};
/*!
@ -100,8 +101,7 @@ class TreeUpdater : public Configurable {
*/
struct TreeUpdaterReg
: public dmlc::FunctionRegEntryBase<
TreeUpdaterReg,
std::function<TreeUpdater*(GenericParameter const* tparam, ObjInfo task)> > {};
TreeUpdaterReg, std::function<TreeUpdater*(Context const* ctx, ObjInfo task)>> {};
/*!
* \brief Macro to register tree updater.

4
plugin/updater_oneapi/predictor_oneapi.cc
View File

@ -330,7 +330,7 @@ class PredictorOneAPI : public Predictor {
}
public:
explicit PredictorOneAPI(GenericParameter const* generic_param) :
explicit PredictorOneAPI(Context const* generic_param) :
Predictor::Predictor{generic_param}, cpu_predictor(Predictor::Create("cpu_predictor", generic_param)) {
cl::sycl::default_selector selector;
qu_ = cl::sycl::queue(selector);
@ -441,7 +441,7 @@ class PredictorOneAPI : public Predictor {
XGBOOST_REGISTER_PREDICTOR(PredictorOneAPI, "oneapi_predictor")
.describe("Make predictions using DPC++.")
.set_body([](GenericParameter const* generic_param) {
.set_body([](Context const* generic_param) {
return new PredictorOneAPI(generic_param);
});
} // namespace predictor

4
src/collective/in_memory_handler.cc
View File

@ -114,7 +114,7 @@ class BroadcastFunctor {
int root_;
};
void InMemoryHandler::Init(int world_size, int rank) {
void InMemoryHandler::Init(int world_size, int) {
CHECK(world_size_ < world_size) << "In memory handler already initialized.";
std::unique_lock<std::mutex> lock(mutex_);
@ -124,7 +124,7 @@ void InMemoryHandler::Init(int world_size, int rank) {
cv_.notify_all();
}
void InMemoryHandler::Shutdown(uint64_t sequence_number, int rank) {
void InMemoryHandler::Shutdown(uint64_t sequence_number, int) {
CHECK(world_size_ > 0) << "In memory handler already shutdown.";
std::unique_lock<std::mutex> lock(mutex_);

10
src/common/hist_util.h
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@ -8,21 +8,21 @@
#define XGBOOST_COMMON_HIST_UTIL_H_
#include <xgboost/data.h>
#include <xgboost/generic_parameters.h>
#include <limits>
#include <vector>
#include <algorithm>
#include <limits>
#include <map>
#include <memory>
#include <utility>
#include <map>
#include <vector>
#include "algorithm.h" // SegmentId
#include "categorical.h"
#include "common.h"
#include "quantile.h"
#include "row_set.h"
#include "threading_utils.h"
#include "timer.h"
#include "algorithm.h" // SegmentId
namespace xgboost {
class GHistIndexMatrix;

2
src/common/linalg_op.cuh
View File

@ -4,9 +4,9 @@
#ifndef XGBOOST_COMMON_LINALG_OP_CUH_
#define XGBOOST_COMMON_LINALG_OP_CUH_
#include "xgboost/generic_parameters.h"
#include "device_helpers.cuh"
#include "linalg_op.h"
#include "xgboost/context.h"
#include "xgboost/linalg.h"
namespace xgboost {

4
src/common/linalg_op.h
View File

@ -9,7 +9,7 @@
#include "common.h"
#include "threading_utils.h"
#include "transform_iterator.h" // MakeIndexTransformIter
#include "xgboost/generic_parameters.h"
#include "xgboost/context.h" // Context
#include "xgboost/linalg.h"
namespace xgboost {
@ -54,7 +54,7 @@ void ElementWiseTransformDevice(linalg::TensorView<T, D>, Fn&&, void* = nullptr)
}
template <typename T, int32_t D, typename Fn>
void ElementWiseKernel(GenericParameter const* ctx, linalg::TensorView<T, D> t, Fn&& fn) {
void ElementWiseKernel(Context const* ctx, linalg::TensorView<T, D> t, Fn&& fn) {
if (!ctx->IsCPU()) {
common::AssertGPUSupport();
}

2
src/common/numeric.cc
View File

@ -7,7 +7,7 @@
#include <type_traits> // std::is_same
#include "threading_utils.h" // MemStackAllocator, ParallelFor, DefaultMaxThreads
#include "xgboost/generic_parameters.h" // Context
#include "xgboost/context.h" // Context
#include "xgboost/host_device_vector.h" // HostDeviceVector
namespace xgboost {

2
src/common/numeric.cu
View File

@ -6,7 +6,7 @@
#include "device_helpers.cuh" // dh::Reduce, safe_cuda, dh::XGBCachingDeviceAllocator
#include "numeric.h"
#include "xgboost/generic_parameters.h" // Context
#include "xgboost/context.h" // Context
#include "xgboost/host_device_vector.h" // HostDeviceVector
namespace xgboost {

2
src/common/numeric.h
View File

@ -12,7 +12,7 @@
#include "common.h" // AssertGPUSupport
#include "threading_utils.h" // MemStackAllocator, DefaultMaxThreads
#include "xgboost/generic_parameters.h" // Context
#include "xgboost/context.h" // Context
#include "xgboost/host_device_vector.h" // HostDeviceVector
namespace xgboost {

6
src/common/partition_builder.h
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@ -10,15 +10,15 @@
#include <xgboost/data.h>
#include <algorithm>
#include <limits>
#include <memory>
#include <utility>
#include <limits>
#include <vector>
#include "../tree/hist/expand_entry.h"
#include "categorical.h"
#include "column_matrix.h"
#include "../tree/hist/expand_entry.h"
#include "xgboost/generic_parameters.h"
#include "xgboost/context.h"
#include "xgboost/tree_model.h"
namespace xgboost {

2
src/common/stats.cu
View File

@ -7,7 +7,7 @@
#include "common.h" // common::OptionalWeights
#include "device_helpers.cuh" // dh::MakeTransformIterator, tcbegin, tcend
#include "stats.cuh" // common::SegmentedQuantile, common::SegmentedWeightedQuantile
#include "xgboost/generic_parameters.h" // Context
#include "xgboost/context.h" // Context
#include "xgboost/host_device_vector.h" // HostDeviceVector
#include "xgboost/linalg.h" // linalg::TensorView, UnravelIndex, Apply

2
src/common/stats.cuh
View File

@ -11,7 +11,7 @@
#include "device_helpers.cuh"
#include "linalg_op.cuh"
#include "xgboost/generic_parameters.h"
#include "xgboost/context.h"
#include "xgboost/linalg.h"
#include "xgboost/tree_model.h"

2
src/common/stats.h
View File

@ -10,7 +10,7 @@
#include "common.h" // AssertGPUSupport
#include "transform_iterator.h" // MakeIndexTransformIter
#include "xgboost/generic_parameters.h"
#include "xgboost/context.h" // Context
#include "xgboost/linalg.h"
namespace xgboost {

62
src/context.cc Normal file
View File

@ -0,0 +1,62 @@
/**
* Copyright 2014-2022 by XGBoost Contributors
*
* \brief Context object used for controlling runtime parameters.
*/
#include <xgboost/context.h>
#include "common/common.h"
#include "common/threading_utils.h"
namespace xgboost {
DMLC_REGISTER_PARAMETER(Context);
std::int32_t constexpr Context::kCpuId;
std::int64_t constexpr Context::kDefaultSeed;
Context::Context() : cfs_cpu_count_{common::GetCfsCPUCount()} {}
void Context::ConfigureGpuId(bool require_gpu) {
#if defined(XGBOOST_USE_CUDA)
if (gpu_id == kCpuId) { // 0. User didn't specify the `gpu_id'
if (require_gpu) { // 1. `tree_method' or `predictor' or both are using
// GPU.
// 2. Use device 0 as default.
this->UpdateAllowUnknown(Args{{"gpu_id", "0"}});
}
}
// 3. When booster is loaded from a memory image (Python pickle or R
// raw model), number of available GPUs could be different. Wrap around it.
int32_t n_gpus = common::AllVisibleGPUs();
if (n_gpus == 0) {
if (gpu_id != kCpuId) {
LOG(WARNING) << "No visible GPU is found, setting `gpu_id` to -1";
}
this->UpdateAllowUnknown(Args{{"gpu_id", std::to_string(kCpuId)}});
} else if (fail_on_invalid_gpu_id) {
CHECK(gpu_id == kCpuId || gpu_id < n_gpus)
<< "Only " << n_gpus << " GPUs are visible, gpu_id " << gpu_id << " is invalid.";
} else if (gpu_id != kCpuId && gpu_id >= n_gpus) {
LOG(WARNING) << "Only " << n_gpus << " GPUs are visible, setting `gpu_id` to "
<< gpu_id % n_gpus;
this->UpdateAllowUnknown(Args{{"gpu_id", std::to_string(gpu_id % n_gpus)}});
}
#else
// Just set it to CPU, don't think about it.
this->UpdateAllowUnknown(Args{{"gpu_id", std::to_string(kCpuId)}});
(void)(require_gpu);
#endif // defined(XGBOOST_USE_CUDA)
common::SetDevice(this->gpu_id);
}
std::int32_t Context::Threads() const {
auto n_threads = common::OmpGetNumThreads(nthread);
if (cfs_cpu_count_ > 0) {
n_threads = std::min(n_threads, cfs_cpu_count_);
}
return n_threads;
}
} // namespace xgboost

2
src/data/iterative_dmatrix.h
View File

@ -86,7 +86,7 @@ class IterativeDMatrix : public DMatrix {
LOG(FATAL) << "Slicing DMatrix is not supported for Quantile DMatrix.";
return nullptr;
}
DMatrix *SliceCol(std::size_t start, std::size_t size) override {
DMatrix *SliceCol(std::size_t, std::size_t) override {
LOG(FATAL) << "Slicing DMatrix columns is not supported for Quantile DMatrix.";
return nullptr;
}

8
src/data/proxy_dmatrix.h
View File

@ -10,10 +10,10 @@
#include <string>
#include <utility>
#include "xgboost/data.h"
#include "xgboost/generic_parameters.h"
#include "xgboost/c_api.h"
#include "adapter.h"
#include "xgboost/c_api.h"
#include "xgboost/context.h"
#include "xgboost/data.h"
namespace xgboost {
namespace data {
@ -87,7 +87,7 @@ class DMatrixProxy : public DMatrix {
LOG(FATAL) << "Slicing DMatrix is not supported for Proxy DMatrix.";
return nullptr;
}
DMatrix* SliceCol(std::size_t start, std::size_t size) override {
DMatrix* SliceCol(std::size_t, std::size_t) override {
LOG(FATAL) << "Slicing DMatrix columns is not supported for Proxy DMatrix.";
return nullptr;
}

2
src/data/simple_dmatrix.cc
View File

@ -53,7 +53,7 @@ DMatrix* SimpleDMatrix::SliceCol(std::size_t start, std::size_t size) {
auto& h_data = out_page.data.HostVector();
auto& h_offset = out_page.offset.HostVector();
size_t rptr{0};
for (auto i = 0; i < this->Info().num_row_; i++) {
for (bst_row_t i = 0; i < this->Info().num_row_; i++) {
auto inst = batch[i];
auto prev_size = h_data.size();
std::copy_if(inst.begin(), inst.end(), std::back_inserter(h_data), [&](Entry e) {

2
src/data/sparse_page_dmatrix.h
View File

@ -107,7 +107,7 @@ class SparsePageDMatrix : public DMatrix {
LOG(FATAL) << "Slicing DMatrix is not supported for external memory.";
return nullptr;
}
DMatrix *SliceCol(std::size_t start, std::size_t size) override {
DMatrix *SliceCol(std::size_t, std::size_t) override {
LOG(FATAL) << "Slicing DMatrix columns is not supported for external memory.";
return nullptr;
}

8
src/gbm/gblinear.cc
View File

@ -71,7 +71,7 @@ void LinearCheckLayer(unsigned layer_begin) {
*/
class GBLinear : public GradientBooster {
public:
explicit GBLinear(LearnerModelParam const* learner_model_param, GenericParameter const* ctx)
explicit GBLinear(LearnerModelParam const* learner_model_param, Context const* ctx)
: GradientBooster{ctx},
learner_model_param_{learner_model_param},
model_{learner_model_param},
@ -179,7 +179,7 @@ class GBLinear : public GradientBooster {
unsigned) override {
model_.LazyInitModel();
LinearCheckLayer(layer_begin);
auto base_margin = p_fmat->Info().base_margin_.View(GenericParameter::kCpuId);
auto base_margin = p_fmat->Info().base_margin_.View(Context::kCpuId);
const int ngroup = model_.learner_model_param->num_output_group;
const size_t ncolumns = model_.learner_model_param->num_feature + 1;
// allocate space for (#features + bias) times #groups times #rows
@ -250,7 +250,7 @@ class GBLinear : public GradientBooster {
linalg::TensorView<float, 2> scores{
*out_scores,
{learner_model_param_->num_feature, n_groups},
GenericParameter::kCpuId};
Context::kCpuId};
for (size_t i = 0; i < learner_model_param_->num_feature; ++i) {
for (bst_group_t g = 0; g < n_groups; ++g) {
scores(i, g) = model_[i][g];
@ -355,7 +355,7 @@ DMLC_REGISTER_PARAMETER(GBLinearTrainParam);
XGBOOST_REGISTER_GBM(GBLinear, "gblinear")
.describe("Linear booster, implement generalized linear model.")
.set_body([](LearnerModelParam const* booster_config, GenericParameter const* ctx) {
.set_body([](LearnerModelParam const* booster_config, Context const* ctx) {
return new GBLinear(booster_config, ctx);
});
} // namespace gbm

10
src/gbm/gbm.cc
View File

@ -3,21 +3,23 @@
* \file gbm.cc
* \brief Registry of gradient boosters.
*/
#include "xgboost/gbm.h"
#include <dmlc/registry.h>
#include <memory>
#include <string>
#include <vector>
#include <memory>
#include "xgboost/gbm.h"
#include "xgboost/context.h"
#include "xgboost/learner.h"
#include "xgboost/generic_parameters.h"
namespace dmlc {
DMLC_REGISTRY_ENABLE(::xgboost::GradientBoosterReg);
} // namespace dmlc
namespace xgboost {
GradientBooster* GradientBooster::Create(const std::string& name, GenericParameter const* ctx,
GradientBooster* GradientBooster::Create(const std::string& name, Context const* ctx,
LearnerModelParam const* learner_model_param) {
auto *e = ::dmlc::Registry< ::xgboost::GradientBoosterReg>::Get()->Find(name);
if (e == nullptr) {

14
src/gbm/gbtree.cc
View File

@ -67,7 +67,7 @@ void GBTree::Configure(const Args& cfg) {
#if defined(XGBOOST_USE_ONEAPI)
if (!oneapi_predictor_) {
oneapi_predictor_ = std::unique_ptr<Predictor>(
Predictor::Create("oneapi_predictor", this->generic_param_));
Predictor::Create("oneapi_predictor", this->ctx_));
}
oneapi_predictor_->Configure(cfg);
#endif // defined(XGBOOST_USE_ONEAPI)
@ -204,7 +204,7 @@ void GPUCopyGradient(HostDeviceVector<GradientPair> const*, bst_group_t, bst_gro
void CopyGradient(HostDeviceVector<GradientPair> const* in_gpair, int32_t n_threads,
bst_group_t n_groups, bst_group_t group_id,
HostDeviceVector<GradientPair>* out_gpair) {
if (in_gpair->DeviceIdx() != GenericParameter::kCpuId) {
if (in_gpair->DeviceIdx() != Context::kCpuId) {
GPUCopyGradient(in_gpair, n_groups, group_id, out_gpair);
} else {
std::vector<GradientPair> &tmp_h = out_gpair->HostVector();
@ -651,7 +651,7 @@ void GPUDartInplacePredictInc(common::Span<float> /*out_predts*/, common::Span<f
class Dart : public GBTree {
public:
explicit Dart(LearnerModelParam const* booster_config, GenericParameter const* ctx)
explicit Dart(LearnerModelParam const* booster_config, Context const* ctx)
: GBTree(booster_config, ctx) {}
void Configure(const Args& cfg) override {
@ -741,7 +741,7 @@ class Dart : public GBTree {
auto n_groups = model_.learner_model_param->num_output_group;
PredictionCacheEntry predts; // temporary storage for prediction
if (ctx_->gpu_id != GenericParameter::kCpuId) {
if (ctx_->gpu_id != Context::kCpuId) {
predts.predictions.SetDevice(ctx_->gpu_id);
}
predts.predictions.Resize(p_fmat->Info().num_row_ * n_groups, 0);
@ -763,7 +763,7 @@ class Dart : public GBTree {
CHECK_EQ(p_out_preds->predictions.Size(), predts.predictions.Size());
size_t n_rows = p_fmat->Info().num_row_;
if (predts.predictions.DeviceIdx() != GenericParameter::kCpuId) {
if (predts.predictions.DeviceIdx() != Context::kCpuId) {
p_out_preds->predictions.SetDevice(predts.predictions.DeviceIdx());
GPUDartPredictInc(p_out_preds->predictions.DeviceSpan(),
predts.predictions.DeviceSpan(), w, n_rows, n_groups,
@ -1019,13 +1019,13 @@ DMLC_REGISTER_PARAMETER(DartTrainParam);
XGBOOST_REGISTER_GBM(GBTree, "gbtree")
.describe("Tree booster, gradient boosted trees.")
.set_body([](LearnerModelParam const* booster_config, GenericParameter const* ctx) {
.set_body([](LearnerModelParam const* booster_config, Context const* ctx) {
auto* p = new GBTree(booster_config, ctx);
return p;
});
XGBOOST_REGISTER_GBM(Dart, "dart")
.describe("Tree booster, dart.")
.set_body([](LearnerModelParam const* booster_config, GenericParameter const* ctx) {
.set_body([](LearnerModelParam const* booster_config, Context const* ctx) {
GBTree* p = new Dart(booster_config, ctx);
return p;
});

6
src/gbm/gbtree.cu
View File

@ -1,10 +1,10 @@
/*!
* Copyright 2021 by Contributors
*/
#include "xgboost/span.h"
#include "xgboost/generic_parameters.h"
#include "xgboost/linalg.h"
#include "../common/device_helpers.cuh"
#include "xgboost/context.h"
#include "xgboost/linalg.h"
#include "xgboost/span.h"
namespace xgboost {
namespace gbm {

2
src/gbm/gbtree.h
View File

@ -190,7 +190,7 @@ bool SliceTrees(int32_t layer_begin, int32_t layer_end, int32_t step, GBTreeMode
// gradient boosted trees
class GBTree : public GradientBooster {
public:
explicit GBTree(LearnerModelParam const* booster_config, GenericParameter const* ctx)
explicit GBTree(LearnerModelParam const* booster_config, Context const* ctx)
: GradientBooster{ctx}, model_(booster_config, ctx_) {}
void Configure(const Args& cfg) override;

15
src/gbm/gbtree_model.h
View File

@ -5,16 +5,17 @@
#ifndef XGBOOST_GBM_GBTREE_MODEL_H_
#define XGBOOST_GBM_GBTREE_MODEL_H_
#include <dmlc/parameter.h>
#include <dmlc/io.h>
#include <xgboost/model.h>
#include <xgboost/tree_model.h>
#include <xgboost/parameter.h>
#include <dmlc/parameter.h>
#include <xgboost/context.h>
#include <xgboost/learner.h>
#include <xgboost/model.h>
#include <xgboost/parameter.h>
#include <xgboost/tree_model.h>
#include <memory>
#include <utility>
#include <string>
#include <utility>
#include <vector>
#include "../common/threading_utils.h"
@ -89,7 +90,7 @@ struct GBTreeModelParam : public dmlc::Parameter<GBTreeModelParam> {
struct GBTreeModel : public Model {
public:
explicit GBTreeModel(LearnerModelParam const* learner_model, GenericParameter const* ctx)
explicit GBTreeModel(LearnerModelParam const* learner_model, Context const* ctx)
: learner_model_param{learner_model}, ctx_{ctx} {}
void Configure(const Args& cfg) {
// initialize model parameters if not yet been initialized.
@ -143,7 +144,7 @@ struct GBTreeModel : public Model {
std::vector<int> tree_info;
private:
GenericParameter const* ctx_;
Context const* ctx_;
};
} // namespace gbm
} // namespace xgboost

57
src/learner.cc
View File

@ -35,10 +35,10 @@
#include "common/version.h"
#include "xgboost/base.h"
#include "xgboost/c_api.h"
#include "xgboost/context.h"
#include "xgboost/data.h"
#include "xgboost/feature_map.h"
#include "xgboost/gbm.h"
#include "xgboost/generic_parameters.h"
#include "xgboost/host_device_vector.h"
#include "xgboost/json.h"
#include "xgboost/logging.h"
@ -306,56 +306,6 @@ struct LearnerTrainParam : public XGBoostParameter<LearnerTrainParam> {
DMLC_REGISTER_PARAMETER(LearnerModelParamLegacy);
DMLC_REGISTER_PARAMETER(LearnerTrainParam);
DMLC_REGISTER_PARAMETER(GenericParameter);
int constexpr GenericParameter::kCpuId;
int64_t constexpr GenericParameter::kDefaultSeed;
GenericParameter::GenericParameter() : cfs_cpu_count_{common::GetCfsCPUCount()} {}
void GenericParameter::ConfigureGpuId(bool require_gpu) {
#if defined(XGBOOST_USE_CUDA)
if (gpu_id == kCpuId) { // 0. User didn't specify the `gpu_id'
if (require_gpu) { // 1. `tree_method' or `predictor' or both are using
// GPU.
// 2. Use device 0 as default.
this->UpdateAllowUnknown(Args{{"gpu_id", "0"}});
}
}
// 3. When booster is loaded from a memory image (Python pickle or R
// raw model), number of available GPUs could be different. Wrap around it.
int32_t n_gpus = common::AllVisibleGPUs();
if (n_gpus == 0) {
if (gpu_id != kCpuId) {
LOG(WARNING) << "No visible GPU is found, setting `gpu_id` to -1";
}
this->UpdateAllowUnknown(Args{{"gpu_id", std::to_string(kCpuId)}});
} else if (fail_on_invalid_gpu_id) {
CHECK(gpu_id == kCpuId || gpu_id < n_gpus)
<< "Only " << n_gpus << " GPUs are visible, gpu_id "
<< gpu_id << " is invalid.";
} else if (gpu_id != kCpuId && gpu_id >= n_gpus) {
LOG(WARNING) << "Only " << n_gpus
<< " GPUs are visible, setting `gpu_id` to " << gpu_id % n_gpus;
this->UpdateAllowUnknown(Args{{"gpu_id", std::to_string(gpu_id % n_gpus)}});
}
#else
// Just set it to CPU, don't think about it.
this->UpdateAllowUnknown(Args{{"gpu_id", std::to_string(kCpuId)}});
(void)(require_gpu);
#endif // defined(XGBOOST_USE_CUDA)
common::SetDevice(this->gpu_id);
}
int32_t GenericParameter::Threads() const {
auto n_threads = common::OmpGetNumThreads(nthread);
if (cfs_cpu_count_ > 0) {
n_threads = std::min(n_threads, cfs_cpu_count_);
}
return n_threads;
}
using LearnerAPIThreadLocalStore =
dmlc::ThreadLocalStore<std::map<Learner const *, XGBAPIThreadLocalEntry>>;
@ -461,7 +411,7 @@ class LearnerConfiguration : public Learner {
monitor_.Init("Learner");
auto& local_cache = (*ThreadLocalPredictionCache::Get())[this];
for (std::shared_ptr<DMatrix> const& d : cache) {
local_cache.Cache(d, GenericParameter::kCpuId);
local_cache.Cache(d, Context::kCpuId);
}
}
~LearnerConfiguration() override {
@ -541,6 +491,9 @@ class LearnerConfiguration : public Learner {
// If configuration is loaded, ensure that the model came from the same version
CHECK(IsA<Object>(in));
auto origin_version = Version::Load(in);
if (std::get<0>(Version::kInvalid) == std::get<0>(origin_version)) {
LOG(WARNING) << "Invalid version string in config";
}
if (!Version::Same(origin_version)) {
LOG(WARNING) << ModelMsg();

6
src/linear/coordinate_common.h
View File

@ -108,9 +108,9 @@ inline std::pair<double, double> GetGradient(int group_idx, int num_group, int f
*
* \return The gradient and diagonal Hessian entry for a given feature.
*/
inline std::pair<double, double>
GetGradientParallel(GenericParameter const *ctx, int group_idx, int num_group,
int fidx, const std::vector<GradientPair> &gpair,
inline std::pair<double, double> GetGradientParallel(Context const *ctx, int group_idx,
int num_group, int fidx,
const std::vector<GradientPair> &gpair,
DMatrix *p_fmat) {
std::vector<double> sum_grad_tloc(ctx->Threads(), 0.0);
std::vector<double> sum_hess_tloc(ctx->Threads(), 0.0);

4
src/linear/linear_updater.cc
View File

@ -11,13 +11,13 @@ DMLC_REGISTRY_ENABLE(::xgboost::LinearUpdaterReg);
namespace xgboost {
LinearUpdater* LinearUpdater::Create(const std::string& name, GenericParameter const* lparam) {
LinearUpdater* LinearUpdater::Create(const std::string& name, Context const* ctx) {
auto *e = ::dmlc::Registry< ::xgboost::LinearUpdaterReg>::Get()->Find(name);
if (e == nullptr) {
LOG(FATAL) << "Unknown linear updater " << name;
}
auto p_linear = (e->body)();
p_linear->ctx_ = lparam;
p_linear->ctx_ = ctx;
return p_linear;
}

22
src/metric/auc.cc
View File

@ -79,14 +79,14 @@ double MultiClassOVR(common::Span<float const> predts, MetaInfo const &info,
size_t n_classes, int32_t n_threads,
BinaryAUC &&binary_auc) {
CHECK_NE(n_classes, 0);
auto const labels = info.labels.View(GenericParameter::kCpuId);
auto const labels = info.labels.View(Context::kCpuId);
if (labels.Shape(0) != 0) {
CHECK_EQ(labels.Shape(1), 1) << "AUC doesn't support multi-target model.";
}
std::vector<double> results_storage(n_classes * 3, 0);
linalg::TensorView<double, 2> results(results_storage, {n_classes, static_cast<size_t>(3)},
GenericParameter::kCpuId);
Context::kCpuId);
auto local_area = results.Slice(linalg::All(), 0);
auto tp = results.Slice(linalg::All(), 1);
auto auc = results.Slice(linalg::All(), 2);
@ -94,7 +94,7 @@ double MultiClassOVR(common::Span<float const> predts, MetaInfo const &info,
auto weights = common::OptionalWeights{info.weights_.ConstHostSpan()};
auto predts_t = linalg::TensorView<float const, 2>(
predts, {static_cast<size_t>(info.num_row_), n_classes},
GenericParameter::kCpuId);
Context::kCpuId);
if (info.labels.Size() != 0) {
common::ParallelFor(n_classes, n_threads, [&](auto c) {
@ -215,7 +215,7 @@ std::pair<double, uint32_t> RankingAUC(std::vector<float> const &predts,
CHECK_GE(info.group_ptr_.size(), 2);
uint32_t n_groups = info.group_ptr_.size() - 1;
auto s_predts = common::Span<float const>{predts};
auto labels = info.labels.View(GenericParameter::kCpuId);
auto labels = info.labels.View(Context::kCpuId);
auto s_weights = info.weights_.ConstHostSpan();
std::atomic<uint32_t> invalid_groups{0};
@ -255,7 +255,7 @@ template <typename Curve>
class EvalAUC : public Metric {
double Eval(const HostDeviceVector<bst_float> &preds, const MetaInfo &info) override {
double auc {0};
if (tparam_->gpu_id != GenericParameter::kCpuId) {
if (tparam_->gpu_id != Context::kCpuId) {
preds.SetDevice(tparam_->gpu_id);
info.labels.SetDevice(tparam_->gpu_id);
info.weights_.SetDevice(tparam_->gpu_id);
@ -340,7 +340,7 @@ class EvalROCAUC : public EvalAUC<EvalROCAUC> {
double auc{0};
uint32_t valid_groups = 0;
auto n_threads = tparam_->Threads();
if (tparam_->gpu_id == GenericParameter::kCpuId) {
if (tparam_->gpu_id == Context::kCpuId) {
std::tie(auc, valid_groups) =
RankingAUC<true>(predts.ConstHostVector(), info, n_threads);
} else {
@ -355,7 +355,7 @@ class EvalROCAUC : public EvalAUC<EvalROCAUC> {
double auc{0};
auto n_threads = tparam_->Threads();
CHECK_NE(n_classes, 0);
if (tparam_->gpu_id == GenericParameter::kCpuId) {
if (tparam_->gpu_id == Context::kCpuId) {
auc = MultiClassOVR(predts.ConstHostVector(), info, n_classes, n_threads,
BinaryROCAUC);
} else {
@ -368,7 +368,7 @@ class EvalROCAUC : public EvalAUC<EvalROCAUC> {
std::tuple<double, double, double>
EvalBinary(HostDeviceVector<float> const &predts, MetaInfo const &info) {
double fp, tp, auc;
if (tparam_->gpu_id == GenericParameter::kCpuId) {
if (tparam_->gpu_id == Context::kCpuId) {
std::tie(fp, tp, auc) =
BinaryROCAUC(predts.ConstHostVector(), info.labels.HostView().Slice(linalg::All(), 0),
common::OptionalWeights{info.weights_.ConstHostSpan()});
@ -418,7 +418,7 @@ class EvalPRAUC : public EvalAUC<EvalPRAUC> {
std::tuple<double, double, double>
EvalBinary(HostDeviceVector<float> const &predts, MetaInfo const &info) {
double pr, re, auc;
if (tparam_->gpu_id == GenericParameter::kCpuId) {
if (tparam_->gpu_id == Context::kCpuId) {
std::tie(pr, re, auc) =
BinaryPRAUC(predts.ConstHostSpan(), info.labels.HostView().Slice(linalg::All(), 0),
common::OptionalWeights{info.weights_.ConstHostSpan()});
@ -431,7 +431,7 @@ class EvalPRAUC : public EvalAUC<EvalPRAUC> {
double EvalMultiClass(HostDeviceVector<float> const &predts, MetaInfo const &info,
size_t n_classes) {
if (tparam_->gpu_id == GenericParameter::kCpuId) {
if (tparam_->gpu_id == Context::kCpuId) {
auto n_threads = this->tparam_->Threads();
return MultiClassOVR(predts.ConstHostSpan(), info, n_classes, n_threads,
BinaryPRAUC);
@ -446,7 +446,7 @@ class EvalPRAUC : public EvalAUC<EvalPRAUC> {
double auc{0};
uint32_t valid_groups = 0;
auto n_threads = tparam_->Threads();
if (tparam_->gpu_id == GenericParameter::kCpuId) {
if (tparam_->gpu_id == Context::kCpuId) {
auto labels = info.labels.Data()->ConstHostSpan();
if (std::any_of(labels.cbegin(), labels.cend(), PRAUCLabelInvalid{})) {
InvalidLabels();

2
src/metric/elementwise_metric.cu
View File

@ -40,7 +40,7 @@ namespace {
* applying the weights. A tuple of {error_i, weight_i} is expected as return.
*/
template <typename Fn>
PackedReduceResult Reduce(GenericParameter const* ctx, MetaInfo const& info, Fn&& loss) {
PackedReduceResult Reduce(Context const* ctx, MetaInfo const& info, Fn&& loss) {
PackedReduceResult result;
auto labels = info.labels.View(ctx->gpu_id);
if (ctx->IsCPU()) {

6
src/metric/metric.cc
View File

@ -4,8 +4,8 @@
* \brief Registry of objective functions.
*/
#include <dmlc/registry.h>
#include <xgboost/context.h>
#include <xgboost/metric.h>
#include <xgboost/generic_parameters.h>
#include "metric_common.h"
@ -43,7 +43,7 @@ Metric* CreateMetricImpl(const std::string& name) {
}
Metric *
Metric::Create(const std::string& name, GenericParameter const* tparam) {
Metric::Create(const std::string& name, Context const* tparam) {
auto metric = CreateMetricImpl<MetricReg>(name);
if (metric == nullptr) {
LOG(FATAL) << "Unknown metric function " << name;
@ -54,7 +54,7 @@ Metric::Create(const std::string& name, GenericParameter const* tparam) {
}
Metric *
GPUMetric::CreateGPUMetric(const std::string& name, GenericParameter const* tparam) {
GPUMetric::CreateGPUMetric(const std::string& name, Context const* tparam) {
auto metric = CreateMetricImpl<MetricGPUReg>(name);
if (metric == nullptr) {
LOG(WARNING) << "Cannot find a GPU metric builder for metric " << name

3
src/metric/metric_common.h
View File

@ -12,12 +12,13 @@
#include "xgboost/metric.h"
namespace xgboost {
struct Context;
// This creates a GPU metric instance dynamically and adds it to the GPU metric registry, if not
// present already. This is created when there is a device ordinal present and if xgboost
// is compiled with CUDA support
struct GPUMetric : Metric {
static Metric *CreateGPUMetric(const std::string& name, GenericParameter const* tparam);
static Metric *CreateGPUMetric(const std::string &name, Context const *tparam);
};
/*!

5
src/metric/multiclass_metric.cu
View File

@ -126,10 +126,7 @@ class MultiClassMetricsReduction {
#endif // XGBOOST_USE_CUDA
PackedReduceResult Reduce(
const GenericParameter &tparam,
int device,
size_t n_class,
PackedReduceResult Reduce(const Context& tparam, int device, size_t n_class,
const HostDeviceVector<bst_float>& weights,
const HostDeviceVector<bst_float>& labels,
const HostDeviceVector<bst_float>& preds) {

4
src/metric/rank_metric.cc
View File

@ -118,7 +118,7 @@ struct EvalAMS : public Metric {
const double br = 10.0;
unsigned thresindex = 0;
double s_tp = 0.0, b_fp = 0.0, tams = 0.0;
const auto& labels = info.labels.View(GenericParameter::kCpuId);
const auto& labels = info.labels.View(Context::kCpuId);
for (unsigned i = 0; i < static_cast<unsigned>(ndata-1) && i < ntop; ++i) {
const unsigned ridx = rec[i].second;
const bst_float wt = info.GetWeight(ridx);
@ -191,7 +191,7 @@ struct EvalRank : public Metric, public EvalRankConfig {
std::vector<double> sum_tloc(tparam_->Threads(), 0.0);
if (!rank_gpu_ || tparam_->gpu_id < 0) {
const auto& labels = info.labels.View(GenericParameter::kCpuId);
const auto& labels = info.labels.View(Context::kCpuId);
const auto &h_preds = preds.ConstHostVector();
dmlc::OMPException exc;

4
src/metric/survival_metric.cu
View File

@ -123,7 +123,7 @@ class ElementWiseSurvivalMetricsReduction {
#endif // XGBOOST_USE_CUDA
PackedReduceResult Reduce(
const GenericParameter &ctx,
const Context &ctx,
const HostDeviceVector<bst_float>& weights,
const HostDeviceVector<bst_float>& labels_lower_bound,
const HostDeviceVector<bst_float>& labels_upper_bound,
@ -195,7 +195,7 @@ struct EvalAFTNLogLik {
};
template <typename Policy> struct EvalEWiseSurvivalBase : public Metric {
explicit EvalEWiseSurvivalBase(GenericParameter const *ctx) {
explicit EvalEWiseSurvivalBase(Context const *ctx) {
tparam_ = ctx;
}
EvalEWiseSurvivalBase() = default;

2
src/objective/adaptive.h
View File

@ -9,7 +9,7 @@
#include "../collective/communicator-inl.h"
#include "../common/common.h"
#include "xgboost/generic_parameters.h"
#include "xgboost/context.h"
#include "xgboost/host_device_vector.h"
#include "xgboost/tree_model.h"

5
src/objective/objective.cc
View File

@ -4,6 +4,7 @@
* \brief Registry of all objective functions.
*/
#include <dmlc/registry.h>
#include <xgboost/context.h>
#include <xgboost/objective.h>
#include <sstream>
@ -16,7 +17,7 @@ DMLC_REGISTRY_ENABLE(::xgboost::ObjFunctionReg);
namespace xgboost {
// implement factory functions
ObjFunction* ObjFunction::Create(const std::string& name, GenericParameter const* tparam) {
ObjFunction* ObjFunction::Create(const std::string& name, Context const* ctx) {
auto *e = ::dmlc::Registry< ::xgboost::ObjFunctionReg>::Get()->Find(name);
if (e == nullptr) {
std::stringstream ss;
@ -27,7 +28,7 @@ ObjFunction* ObjFunction::Create(const std::string& name, GenericParameter const
<< ss.str();
}
auto pobj = (e->body)();
pobj->ctx_ = tparam;
pobj->ctx_ = ctx;
return pobj;
}

2
src/objective/regression_obj.cu
View File

@ -23,8 +23,8 @@
#include "./regression_loss.h"
#include "adaptive.h"
#include "xgboost/base.h"
#include "xgboost/context.h"
#include "xgboost/data.h"
#include "xgboost/generic_parameters.h"
#include "xgboost/host_device_vector.h"
#include "xgboost/json.h"
#include "xgboost/linalg.h"

9
src/predictor/cpu_predictor.cc
View File

@ -1,5 +1,5 @@
/*!
* Copyright by Contributors 2017-2021
* Copyright by XGBoost Contributors 2017-2022
*/
#include <dmlc/any.h>
#include <dmlc/omp.h>
@ -351,8 +351,7 @@ class CPUPredictor : public Predictor {
}
public:
explicit CPUPredictor(GenericParameter const* generic_param) :
Predictor::Predictor{generic_param} {}
explicit CPUPredictor(Context const *ctx) : Predictor::Predictor{ctx} {}
void PredictBatch(DMatrix *dmat, PredictionCacheEntry *predts,
const gbm::GBTreeModel &model, uint32_t tree_begin,
@ -615,8 +614,6 @@ class CPUPredictor : public Predictor {
XGBOOST_REGISTER_PREDICTOR(CPUPredictor, "cpu_predictor")
.describe("Make predictions using CPU.")
.set_body([](GenericParameter const* generic_param) {
return new CPUPredictor(generic_param);
});
.set_body([](Context const *ctx) { return new CPUPredictor(ctx); });
} // namespace predictor
} // namespace xgboost

7
src/predictor/gpu_predictor.cu
View File

@ -723,8 +723,7 @@ class GPUPredictor : public xgboost::Predictor {
}
public:
explicit GPUPredictor(GenericParameter const* generic_param) :
Predictor::Predictor{generic_param} {}
explicit GPUPredictor(Context const* ctx) : Predictor::Predictor{ctx} {}
~GPUPredictor() override {
if (ctx_->gpu_id >= 0 && ctx_->gpu_id < common::AllVisibleGPUs()) {
@ -1027,9 +1026,7 @@ class GPUPredictor : public xgboost::Predictor {
XGBOOST_REGISTER_PREDICTOR(GPUPredictor, "gpu_predictor")
.describe("Make predictions using GPU.")
.set_body([](GenericParameter const* generic_param) {
return new GPUPredictor(generic_param);
});
.set_body([](Context const* ctx) { return new GPUPredictor(ctx); });
} // namespace predictor
} // namespace xgboost

16
src/predictor/predictor.cc
View File

@ -1,14 +1,15 @@
/*!
* Copyright 2017-2021 by Contributors
*/
#include "xgboost/predictor.h"
#include <dmlc/registry.h>
#include <mutex>
#include "xgboost/predictor.h"
#include "xgboost/data.h"
#include "xgboost/generic_parameters.h"
#include "../gbm/gbtree.h"
#include "xgboost/context.h"
#include "xgboost/data.h"
namespace dmlc {
DMLC_REGISTRY_ENABLE(::xgboost::PredictorReg);
@ -30,7 +31,7 @@ void PredictionContainer::ClearExpiredEntries() {
PredictionCacheEntry &PredictionContainer::Cache(std::shared_ptr<DMatrix> m, int32_t device) {
this->ClearExpiredEntries();
container_[m.get()].ref = m;
if (device != GenericParameter::kCpuId) {
if (device != Context::kCpuId) {
container_[m.get()].predictions.SetDevice(device);
}
return container_[m.get()];
@ -51,13 +52,12 @@ decltype(PredictionContainer::container_) const& PredictionContainer::Container(
void Predictor::Configure(
const std::vector<std::pair<std::string, std::string>>&) {
}
Predictor* Predictor::Create(
std::string const& name, GenericParameter const* generic_param) {
Predictor* Predictor::Create(std::string const& name, Context const* ctx) {
auto* e = ::dmlc::Registry<PredictorReg>::Get()->Find(name);
if (e == nullptr) {
LOG(FATAL) << "Unknown predictor type " << name;
}
auto p_predictor = (e->body)(generic_param);
auto p_predictor = (e->body)(ctx);
return p_predictor;
}

2
src/tree/common_row_partitioner.h
View File

@ -12,7 +12,7 @@
#include "../common/numeric.h" // Iota
#include "../common/partition_builder.h"
#include "hist/expand_entry.h" // CPUExpandEntry
#include "xgboost/generic_parameters.h" // Context
#include "xgboost/context.h" // Context
namespace xgboost {
namespace tree {

2
src/tree/gpu_hist/row_partitioner.cuh
View File

@ -9,7 +9,7 @@
#include "../../common/device_helpers.cuh"
#include "xgboost/base.h"
#include "xgboost/generic_parameters.h"
#include "xgboost/context.h"
#include "xgboost/task.h"
#include "xgboost/tree_model.h"

17
src/tree/hist/evaluate_splits.h
View File

@ -5,19 +5,20 @@
#define XGBOOST_TREE_HIST_EVALUATE_SPLITS_H_
#include <algorithm>
#include <limits>
#include <memory>
#include <numeric>
#include <limits>
#include <utility>
#include <vector>
#include "../param.h"
#include "../constraints.h"
#include "../split_evaluator.h"
#include "../../common/categorical.h"
#include "../../common/random.h"
#include "../../common/hist_util.h"
#include "../../common/random.h"
#include "../../data/gradient_index.h"
#include "../constraints.h"
#include "../param.h"
#include "../split_evaluator.h"
#include "xgboost/context.h"
namespace xgboost {
namespace tree {
@ -427,7 +428,7 @@ class HistEvaluator {
std::shared_ptr<common::ColumnSampler> sampler)
: param_{param},
column_sampler_{std::move(sampler)},
tree_evaluator_{param, static_cast<bst_feature_t>(info.num_col_), GenericParameter::kCpuId},
tree_evaluator_{param, static_cast<bst_feature_t>(info.num_col_), Context::kCpuId},
n_threads_{n_threads} {
interaction_constraints_.Configure(param, info.num_col_);
column_sampler_->Init(info.num_col_, info.feature_weights.HostVector(), param_.colsample_bynode,
@ -442,14 +443,14 @@ class HistEvaluator {
* \param p_last_tree The last tree being updated by tree updater
*/
template <typename Partitioner>
void UpdatePredictionCacheImpl(GenericParameter const *ctx, RegTree const *p_last_tree,
void UpdatePredictionCacheImpl(Context const *ctx, RegTree const *p_last_tree,
std::vector<Partitioner> const &partitioner,
linalg::VectorView<float> out_preds) {
CHECK_GT(out_preds.Size(), 0U);
CHECK(p_last_tree);
auto const &tree = *p_last_tree;
CHECK_EQ(out_preds.DeviceIdx(), GenericParameter::kCpuId);
CHECK_EQ(out_preds.DeviceIdx(), Context::kCpuId);
size_t n_nodes = p_last_tree->GetNodes().size();
for (auto &part : partitioner) {
CHECK_EQ(part.Size(), n_nodes);

19
src/tree/split_evaluator.h
View File

@ -10,17 +10,18 @@
#include <dmlc/registry.h>
#include <xgboost/base.h>
#include <algorithm>
#include <limits>
#include <utility>
#include <vector>
#include <limits>
#include <algorithm>
#include "xgboost/tree_model.h"
#include "xgboost/host_device_vector.h"
#include "xgboost/generic_parameters.h"
#include "../common/transform.h"
#include "../common/math.h"
#include "../common/transform.h"
#include "param.h"
#include "xgboost/context.h"
#include "xgboost/host_device_vector.h"
#include "xgboost/tree_model.h"
namespace xgboost {
namespace tree {
@ -38,7 +39,7 @@ class TreeEvaluator {
public:
TreeEvaluator(TrainParam const& p, bst_feature_t n_features, int32_t device) {
device_ = device;
if (device != GenericParameter::kCpuId) {
if (device != Context::kCpuId) {
lower_bounds_.SetDevice(device);
upper_bounds_.SetDevice(device);
monotone_.SetDevice(device);
@ -56,7 +57,7 @@ class TreeEvaluator {
has_constraint_ = true;
}
if (device_ != GenericParameter::kCpuId) {
if (device_ != Context::kCpuId) {
// Pull to device early.
lower_bounds_.ConstDeviceSpan();
upper_bounds_.ConstDeviceSpan();
@ -151,7 +152,7 @@ class TreeEvaluator {
public:
/* Get a view to the evaluator that can be passed down to device. */
template <typename ParamT = TrainParam> auto GetEvaluator() const {
if (device_ != GenericParameter::kCpuId) {
if (device_ != Context::kCpuId) {
auto constraints = monotone_.ConstDevicePointer();
return SplitEvaluator<ParamT>{constraints, lower_bounds_.ConstDevicePointer(),
upper_bounds_.ConstDevicePointer(), has_constraint_};

5
src/tree/tree_updater.cc
View File

@ -14,13 +14,12 @@ DMLC_REGISTRY_ENABLE(::xgboost::TreeUpdaterReg);
namespace xgboost {
TreeUpdater* TreeUpdater::Create(const std::string& name, GenericParameter const* tparam,
ObjInfo task) {
TreeUpdater* TreeUpdater::Create(const std::string& name, Context const* ctx, ObjInfo task) {
auto* e = ::dmlc::Registry< ::xgboost::TreeUpdaterReg>::Get()->Find(name);
if (e == nullptr) {
LOG(FATAL) << "Unknown tree updater " << name;
}
auto p_updater = (e->body)(tparam, task);
auto p_updater = (e->body)(ctx, task);
return p_updater;
}

6
src/tree/updater_approx.cc
View File

@ -256,7 +256,7 @@ class GlobalApproxUpdater : public TreeUpdater {
ObjInfo task_;
public:
explicit GlobalApproxUpdater(GenericParameter const *ctx, ObjInfo task)
explicit GlobalApproxUpdater(Context const *ctx, ObjInfo task)
: TreeUpdater(ctx), task_{task} {
monitor_.Init(__func__);
}
@ -337,8 +337,6 @@ XGBOOST_REGISTER_TREE_UPDATER(GlobalHistMaker, "grow_histmaker")
.describe(
"Tree constructor that uses approximate histogram construction "
"for each node.")
.set_body([](GenericParameter const *ctx, ObjInfo task) {
return new GlobalApproxUpdater(ctx, task);
});
.set_body([](Context const *ctx, ObjInfo task) { return new GlobalApproxUpdater(ctx, task); });
} // namespace tree
} // namespace xgboost

12
src/tree/updater_colmaker.cc
View File

@ -55,7 +55,7 @@ DMLC_REGISTER_PARAMETER(ColMakerTrainParam);
/*! \brief column-wise update to construct a tree */
class ColMaker: public TreeUpdater {
public:
explicit ColMaker(GenericParameter const *ctx) : TreeUpdater(ctx) {}
explicit ColMaker(Context const *ctx) : TreeUpdater(ctx) {}
void Configure(const Args &args) override {
param_.UpdateAllowUnknown(args);
colmaker_param_.UpdateAllowUnknown(args);
@ -159,11 +159,11 @@ class ColMaker: public TreeUpdater {
// constructor
explicit Builder(const TrainParam &param, const ColMakerTrainParam &colmaker_train_param,
FeatureInteractionConstraintHost _interaction_constraints,
GenericParameter const *ctx, const std::vector<float> &column_densities)
Context const *ctx, const std::vector<float> &column_densities)
: param_(param),
colmaker_train_param_{colmaker_train_param},
ctx_{ctx},
tree_evaluator_(param_, column_densities.size(), GenericParameter::kCpuId),
tree_evaluator_(param_, column_densities.size(), Context::kCpuId),
interaction_constraints_{std::move(_interaction_constraints)},
column_densities_(column_densities) {}
// update one tree, growing
@ -594,7 +594,7 @@ class ColMaker: public TreeUpdater {
const TrainParam& param_;
const ColMakerTrainParam& colmaker_train_param_;
// number of omp thread used during training
GenericParameter const* ctx_;
Context const* ctx_;
common::ColumnSampler column_sampler_;
// Instance Data: current node position in the tree of each instance
std::vector<int> position_;
@ -613,8 +613,6 @@ class ColMaker: public TreeUpdater {
XGBOOST_REGISTER_TREE_UPDATER(ColMaker, "grow_colmaker")
.describe("Grow tree with parallelization over columns.")
.set_body([](GenericParameter const* ctx, ObjInfo) {
return new ColMaker(ctx);
});
.set_body([](Context const *ctx, ObjInfo) { return new ColMaker(ctx); });
} // namespace tree
} // namespace xgboost

47
src/tree/updater_gpu_hist.cu
View File

@ -4,41 +4,40 @@
#include <thrust/copy.h>
#include <thrust/reduce.h>
#include <xgboost/tree_updater.h>
#include <algorithm>
#include <cmath>
#include <memory>
#include <limits>
#include <memory>
#include <utility>
#include <vector>
#include "xgboost/base.h"
#include "xgboost/data.h"
#include "xgboost/generic_parameters.h"
#include "xgboost/host_device_vector.h"
#include "xgboost/parameter.h"
#include "xgboost/span.h"
#include "xgboost/json.h"
#include "../collective/device_communicator.cuh"
#include "../common/io.h"
#include "../common/bitfield.h"
#include "../common/categorical.h"
#include "../common/device_helpers.cuh"
#include "../common/hist_util.h"
#include "../common/bitfield.h"
#include "../common/io.h"
#include "../common/timer.h"
#include "../common/categorical.h"
#include "../data/ellpack_page.cuh"
#include "param.h"
#include "driver.h"
#include "updater_gpu_common.cuh"
#include "split_evaluator.h"
#include "constraints.cuh"
#include "gpu_hist/feature_groups.cuh"
#include "gpu_hist/gradient_based_sampler.cuh"
#include "gpu_hist/row_partitioner.cuh"
#include "gpu_hist/histogram.cuh"
#include "driver.h"
#include "gpu_hist/evaluate_splits.cuh"
#include "gpu_hist/expand_entry.cuh"
#include "gpu_hist/feature_groups.cuh"
#include "gpu_hist/gradient_based_sampler.cuh"
#include "gpu_hist/histogram.cuh"
#include "gpu_hist/row_partitioner.cuh"
#include "param.h"
#include "split_evaluator.h"
#include "updater_gpu_common.cuh"
#include "xgboost/base.h"
#include "xgboost/context.h"
#include "xgboost/data.h"
#include "xgboost/host_device_vector.h"
#include "xgboost/json.h"
#include "xgboost/parameter.h"
#include "xgboost/span.h"
#include "xgboost/task.h"
#include "xgboost/tree_model.h"
@ -730,7 +729,7 @@ class GPUHistMaker : public TreeUpdater {
using GradientSumT = GradientPairPrecise;
public:
explicit GPUHistMaker(GenericParameter const* ctx, ObjInfo task)
explicit GPUHistMaker(Context const* ctx, ObjInfo task)
: TreeUpdater(ctx), task_{task} {};
void Configure(const Args& args) override {
// Used in test to count how many configurations are performed
@ -879,9 +878,7 @@ class GPUHistMaker : public TreeUpdater {
#if !defined(GTEST_TEST)
XGBOOST_REGISTER_TREE_UPDATER(GPUHistMaker, "grow_gpu_hist")
.describe("Grow tree with GPU.")
.set_body([](GenericParameter const* tparam, ObjInfo task) {
return new GPUHistMaker(tparam, task);
});
.set_body([](Context const* ctx, ObjInfo task) { return new GPUHistMaker(ctx, task); });
#endif // !defined(GTEST_TEST)
} // namespace tree

4
src/tree/updater_prune.cc
View File

@ -20,7 +20,7 @@ DMLC_REGISTRY_FILE_TAG(updater_prune);
/*! \brief pruner that prunes a tree after growing finishes */
class TreePruner : public TreeUpdater {
public:
explicit TreePruner(GenericParameter const* ctx, ObjInfo task) : TreeUpdater(ctx) {
explicit TreePruner(Context const* ctx, ObjInfo task) : TreeUpdater(ctx) {
syncher_.reset(TreeUpdater::Create("sync", ctx_, task));
pruner_monitor_.Init("TreePruner");
}
@ -110,6 +110,6 @@ class TreePruner : public TreeUpdater {
XGBOOST_REGISTER_TREE_UPDATER(TreePruner, "prune")
.describe("Pruner that prune the tree according to statistics.")
.set_body([](GenericParameter const* ctx, ObjInfo task) { return new TreePruner(ctx, task); });
.set_body([](Context const* ctx, ObjInfo task) { return new TreePruner(ctx, task); });
} // namespace tree
} // namespace xgboost

4
src/tree/updater_quantile_hist.cc
View File

@ -335,8 +335,6 @@ void QuantileHistMaker::Builder::InitData(DMatrix *fmat, const RegTree &tree,
XGBOOST_REGISTER_TREE_UPDATER(QuantileHistMaker, "grow_quantile_histmaker")
.describe("Grow tree using quantized histogram.")
.set_body([](GenericParameter const *ctx, ObjInfo task) {
return new QuantileHistMaker(ctx, task);
});
.set_body([](Context const *ctx, ObjInfo task) { return new QuantileHistMaker(ctx, task); });
} // namespace tree
} // namespace xgboost

5
src/tree/updater_quantile_hist.h
View File

@ -85,8 +85,7 @@ inline BatchParam HistBatch(TrainParam const& param) {
/*! \brief construct a tree using quantized feature values */
class QuantileHistMaker: public TreeUpdater {
public:
explicit QuantileHistMaker(GenericParameter const* ctx, ObjInfo task)
: TreeUpdater(ctx), task_{task} {}
explicit QuantileHistMaker(Context const* ctx, ObjInfo task) : TreeUpdater(ctx), task_{task} {}
void Configure(const Args& args) override;
void Update(HostDeviceVector<GradientPair>* gpair, DMatrix* dmat,
@ -120,7 +119,7 @@ class QuantileHistMaker: public TreeUpdater {
public:
// constructor
explicit Builder(const size_t n_trees, const TrainParam& param, DMatrix const* fmat,
ObjInfo task, GenericParameter const* ctx)
ObjInfo task, Context const* ctx)
: n_trees_(n_trees),
param_(param),
p_last_fmat_(fmat),

4
src/tree/updater_refresh.cc
View File

@ -24,7 +24,7 @@ DMLC_REGISTRY_FILE_TAG(updater_refresh);
/*! \brief pruner that prunes a tree after growing finishs */
class TreeRefresher : public TreeUpdater {
public:
explicit TreeRefresher(GenericParameter const *ctx) : TreeUpdater(ctx) {}
explicit TreeRefresher(Context const *ctx) : TreeUpdater(ctx) {}
void Configure(const Args &args) override { param_.UpdateAllowUnknown(args); }
void LoadConfig(Json const& in) override {
auto const& config = get<Object const>(in);
@ -160,6 +160,6 @@ class TreeRefresher : public TreeUpdater {
XGBOOST_REGISTER_TREE_UPDATER(TreeRefresher, "refresh")
.describe("Refresher that refreshes the weight and statistics according to data.")
.set_body([](GenericParameter const *ctx, ObjInfo) { return new TreeRefresher(ctx); });
.set_body([](Context const *ctx, ObjInfo) { return new TreeRefresher(ctx); });
} // namespace tree
} // namespace xgboost

4
src/tree/updater_sync.cc
View File

@ -24,7 +24,7 @@ DMLC_REGISTRY_FILE_TAG(updater_sync);
*/
class TreeSyncher : public TreeUpdater {
public:
explicit TreeSyncher(GenericParameter const* tparam) : TreeUpdater(tparam) {}
explicit TreeSyncher(Context const* tparam) : TreeUpdater(tparam) {}
void Configure(const Args&) override {}
void LoadConfig(Json const&) override {}
@ -56,6 +56,6 @@ class TreeSyncher : public TreeUpdater {
XGBOOST_REGISTER_TREE_UPDATER(TreeSyncher, "sync")
.describe("Syncher that synchronize the tree in all distributed nodes.")
.set_body([](GenericParameter const* tparam, ObjInfo) { return new TreeSyncher(tparam); });
.set_body([](Context const* ctx, ObjInfo) { return new TreeSyncher(ctx); });
} // namespace tree
} // namespace xgboost

2
tests/cpp/common/test_json.cc
View File

@ -590,7 +590,7 @@ TEST(Json, DISABLED_RoundTripExhaustive) {
}
};
int64_t int32_max = static_cast<int64_t>(std::numeric_limits<uint32_t>::max());
GenericParameter ctx;
Context ctx;
common::ParallelFor(int32_max, ctx.Threads(), [&](auto i) { test(static_cast<uint32_t>(i)); });
}

4
tests/cpp/common/test_linalg.cc
View File

@ -2,7 +2,7 @@
* Copyright 2021 by XGBoost Contributors
*/
#include <gtest/gtest.h>
#include <xgboost/generic_parameters.h>
#include <xgboost/context.h>
#include <xgboost/host_device_vector.h>
#include <xgboost/linalg.h>
@ -13,7 +13,7 @@
namespace xgboost {
namespace linalg {
namespace {
auto kCpuId = GenericParameter::kCpuId;
auto kCpuId = Context::kCpuId;
}
auto MakeMatrixFromTest(HostDeviceVector<float> *storage, size_t n_rows, size_t n_cols) {

6
tests/cpp/common/test_linalg.cu
View File

@ -4,7 +4,7 @@
#include <gtest/gtest.h>
#include "../../../src/common/linalg_op.cuh"
#include "xgboost/generic_parameters.h"
#include "xgboost/context.h"
#include "xgboost/linalg.h"
namespace xgboost {
@ -21,7 +21,7 @@ void TestElementWiseKernel() {
ASSERT_FALSE(t.CContiguous());
ElementWiseTransformDevice(t, [] __device__(size_t i, float) { return i; });
// CPU view
t = l.View(GenericParameter::kCpuId).Slice(linalg::All(), 1, linalg::All());
t = l.View(Context::kCpuId).Slice(linalg::All(), 1, linalg::All());
size_t k = 0;
for (size_t i = 0; i < l.Shape(0); ++i) {
for (size_t j = 0; j < l.Shape(2); ++j) {
@ -41,7 +41,7 @@ void TestElementWiseKernel() {
ElementWiseTransformDevice(t, [] XGBOOST_DEVICE(size_t i, float) { return i; });
ASSERT_TRUE(t.CContiguous());
// CPU view
t = l.View(GenericParameter::kCpuId);
t = l.View(Context::kCpuId);
size_t ind = 0;
for (size_t i = 0; i < l.Shape(0); ++i) {

2
tests/cpp/common/test_stats.cc
View File

@ -2,7 +2,7 @@
* Copyright 2022 by XGBoost Contributors
*/
#include <gtest/gtest.h>
#include <xgboost/generic_parameters.h>
#include <xgboost/context.h>
#include "../../../src/common/stats.h"

3
tests/cpp/common/test_stats.cu
View File

@ -2,12 +2,13 @@
* Copyright 2022 by XGBoost Contributors
*/
#include <gtest/gtest.h>
#include <utility>
#include <vector>
#include "../../../src/common/stats.cuh"
#include "xgboost/base.h"
#include "xgboost/generic_parameters.h"
#include "xgboost/context.h"
#include "xgboost/host_device_vector.h"
#include "xgboost/linalg.h"

2
tests/cpp/data/test_array_interface.cc
View File

@ -20,7 +20,7 @@ TEST(ArrayInterface, Initialize) {
HostDeviceVector<size_t> u64_storage(storage.Size());
std::string u64_arr_str{ArrayInterfaceStr(linalg::TensorView<size_t const, 2>{
u64_storage.ConstHostSpan(), {kRows, kCols}, GenericParameter::kCpuId})};
u64_storage.ConstHostSpan(), {kRows, kCols}, Context::kCpuId})};
std::copy(storage.ConstHostVector().cbegin(), storage.ConstHostVector().cend(),
u64_storage.HostSpan().begin());
auto u64_arr = ArrayInterface<2>{u64_arr_str};

4
tests/cpp/data/test_metainfo.cc
View File

@ -129,8 +129,8 @@ TEST(MetaInfo, SaveLoadBinary) {
EXPECT_EQ(inforead.group_ptr_, info.group_ptr_);
EXPECT_EQ(inforead.weights_.HostVector(), info.weights_.HostVector());
auto orig_margin = info.base_margin_.View(xgboost::GenericParameter::kCpuId);
auto read_margin = inforead.base_margin_.View(xgboost::GenericParameter::kCpuId);
auto orig_margin = info.base_margin_.View(xgboost::Context::kCpuId);
auto read_margin = inforead.base_margin_.View(xgboost::Context::kCpuId);
EXPECT_TRUE(std::equal(orig_margin.Values().cbegin(), orig_margin.Values().cend(),
read_margin.Values().cbegin()));

10
tests/cpp/data/test_metainfo.cu
View File

@ -1,13 +1,13 @@
/*! Copyright 2019-2021 by XGBoost Contributors */
#include <gtest/gtest.h>
#include <thrust/device_vector.h>
#include <xgboost/context.h>
#include <xgboost/data.h>
#include <xgboost/json.h>
#include <xgboost/generic_parameters.h>
#include <thrust/device_vector.h>
#include "test_array_interface.h"
#include "../../../src/common/device_helpers.cuh"
#include "../../../src/common/device_helpers.cuh"
#include "test_array_interface.h"
#include "test_metainfo.h"
namespace xgboost {
@ -65,7 +65,7 @@ TEST(MetaInfo, FromInterface) {
}
info.SetInfo(ctx, "base_margin", str.c_str());
auto const h_base_margin = info.base_margin_.View(GenericParameter::kCpuId);
auto const h_base_margin = info.base_margin_.View(Context::kCpuId);
ASSERT_EQ(h_base_margin.Size(), d_data.size());
for (size_t i = 0; i < d_data.size(); ++i) {
ASSERT_EQ(h_base_margin(i), d_data[i]);

12
tests/cpp/data/test_simple_dmatrix.cc
View File

@ -256,7 +256,7 @@ TEST(SimpleDMatrix, Slice) {
std::iota(upper.begin(), upper.end(), 1.0f);
auto& margin = p_m->Info().base_margin_;
margin = decltype(p_m->Info().base_margin_){{kRows, kClasses}, GenericParameter::kCpuId};
margin = decltype(p_m->Info().base_margin_){{kRows, kClasses}, Context::kCpuId};
std::array<int32_t, 3> ridxs {1, 3, 5};
std::unique_ptr<DMatrix> out { p_m->Slice(ridxs) };
@ -286,8 +286,8 @@ TEST(SimpleDMatrix, Slice) {
ASSERT_EQ(p_m->Info().weights_.HostVector().at(ridx),
out->Info().weights_.HostVector().at(i));
auto out_margin = out->Info().base_margin_.View(GenericParameter::kCpuId);
auto in_margin = margin.View(GenericParameter::kCpuId);
auto out_margin = out->Info().base_margin_.View(Context::kCpuId);
auto in_margin = margin.View(Context::kCpuId);
for (size_t j = 0; j < kClasses; ++j) {
ASSERT_EQ(out_margin(i, j), in_margin(ridx, j));
}
@ -318,7 +318,7 @@ TEST(SimpleDMatrix, SliceCol) {
std::iota(upper.begin(), upper.end(), 1.0f);
auto& margin = p_m->Info().base_margin_;
margin = decltype(p_m->Info().base_margin_){{kRows, kClasses}, GenericParameter::kCpuId};
margin = decltype(p_m->Info().base_margin_){{kRows, kClasses}, Context::kCpuId};
size_t constexpr kSlicCols {4};
for (auto slice = 0; slice < 2; slice++) {
@ -348,8 +348,8 @@ TEST(SimpleDMatrix, SliceCol) {
out->Info().labels_upper_bound_.HostVector().at(i));
ASSERT_EQ(p_m->Info().weights_.HostVector().at(i), out->Info().weights_.HostVector().at(i));
auto out_margin = out->Info().base_margin_.View(GenericParameter::kCpuId);
auto in_margin = margin.View(GenericParameter::kCpuId);
auto out_margin = out->Info().base_margin_.View(Context::kCpuId);
auto in_margin = margin.View(Context::kCpuId);
for (size_t j = 0; j < kClasses; ++j) {
ASSERT_EQ(out_margin(i, j), in_margin(i, j));
}

6
tests/cpp/gbm/test_gblinear.cc
View File

@ -7,11 +7,11 @@
#include <sstream>
#include "../helpers.h"
#include "xgboost/json.h"
#include "xgboost/logging.h"
#include "xgboost/context.h"
#include "xgboost/gbm.h"
#include "xgboost/generic_parameters.h"
#include "xgboost/json.h"
#include "xgboost/learner.h"
#include "xgboost/logging.h"
namespace xgboost {
namespace gbm {

2
tests/cpp/gbm/test_gbtree.cc
View File

@ -2,7 +2,7 @@
* Copyright 2019-2022 XGBoost contributors
*/
#include <gtest/gtest.h>
#include <xgboost/generic_parameters.h>
#include <xgboost/context.h>
#include "../../../src/data/adapter.h"
#include "../../../src/data/proxy_dmatrix.h"

13
tests/cpp/helpers.cc
View File

@ -532,7 +532,7 @@ std::unique_ptr<DMatrix> CreateSparsePageDMatrixWithRC(
return dmat;
}
gbm::GBTreeModel CreateTestModel(LearnerModelParam const* param, GenericParameter const* ctx,
gbm::GBTreeModel CreateTestModel(LearnerModelParam const* param, Context const* ctx,
size_t n_classes) {
gbm::GBTreeModel model(param, ctx);
@ -549,13 +549,12 @@ gbm::GBTreeModel CreateTestModel(LearnerModelParam const* param, GenericParamete
return model;
}
std::unique_ptr<GradientBooster> CreateTrainedGBM(
std::string name, Args kwargs, size_t kRows, size_t kCols,
std::unique_ptr<GradientBooster> CreateTrainedGBM(std::string name, Args kwargs, size_t kRows,
size_t kCols,
LearnerModelParam const* learner_model_param,
GenericParameter const* generic_param) {
auto caches = std::make_shared< PredictionContainer >();;
std::unique_ptr<GradientBooster> gbm {
GradientBooster::Create(name, generic_param, learner_model_param)};
Context const* ctx) {
auto caches = std::make_shared<PredictionContainer>();
std::unique_ptr<GradientBooster> gbm{GradientBooster::Create(name, ctx, learner_model_param)};
gbm->Configure(kwargs);
auto p_dmat = RandomDataGenerator(kRows, kCols, 0).GenerateDMatrix();

17
tests/cpp/helpers.h
View File

@ -8,7 +8,7 @@
#include <sys/stat.h>
#include <sys/types.h>
#include <xgboost/base.h>
#include <xgboost/generic_parameters.h>
#include <xgboost/context.h>
#include <xgboost/json.h>
#include <cstdio>
@ -355,18 +355,17 @@ std::unique_ptr<DMatrix> CreateSparsePageDMatrixWithRC(
size_t n_rows, size_t n_cols, size_t page_size, bool deterministic,
const dmlc::TemporaryDirectory& tempdir = dmlc::TemporaryDirectory());
gbm::GBTreeModel CreateTestModel(LearnerModelParam const* param, GenericParameter const* ctx,
gbm::GBTreeModel CreateTestModel(LearnerModelParam const* param, Context const* ctx,
size_t n_classes = 1);
std::unique_ptr<GradientBooster> CreateTrainedGBM(
std::string name, Args kwargs, size_t kRows, size_t kCols,
std::unique_ptr<GradientBooster> CreateTrainedGBM(std::string name, Args kwargs, size_t kRows,
size_t kCols,
LearnerModelParam const* learner_model_param,
GenericParameter const* generic_param);
Context const* generic_param);
inline GenericParameter CreateEmptyGenericParam(int gpu_id) {
xgboost::GenericParameter tparam;
std::vector<std::pair<std::string, std::string>> args {
{"gpu_id", std::to_string(gpu_id)}};
inline Context CreateEmptyGenericParam(int gpu_id) {
xgboost::Context tparam;
std::vector<std::pair<std::string, std::string>> args{{"gpu_id", std::to_string(gpu_id)}};
tparam.Init(args);
return tparam;
}

13
tests/cpp/linear/test_linear.cc
View File

@ -17,12 +17,12 @@ TEST(Linear, Shotgun) {
auto p_fmat = xgboost::RandomDataGenerator(kRows, kCols, 0).GenerateDMatrix();
auto lparam = xgboost::CreateEmptyGenericParam(GPUIDX);
auto ctx = xgboost::CreateEmptyGenericParam(GPUIDX);
LearnerModelParam mparam{MakeMP(kCols, .5, 1)};
{
auto updater = std::unique_ptr<xgboost::LinearUpdater>(
xgboost::LinearUpdater::Create("shotgun", &lparam));
auto updater =
std::unique_ptr<xgboost::LinearUpdater>(xgboost::LinearUpdater::Create("shotgun", &ctx));
updater->Configure({{"eta", "1."}});
xgboost::HostDeviceVector<xgboost::GradientPair> gpair(
p_fmat->Info().num_row_, xgboost::GradientPair(-5, 1.0));
@ -31,11 +31,10 @@ TEST(Linear, Shotgun) {
updater->Update(&gpair, p_fmat.get(), &model, gpair.Size());
ASSERT_EQ(model.Bias()[0], 5.0f);
}
{
auto updater = std::unique_ptr<xgboost::LinearUpdater>(
xgboost::LinearUpdater::Create("shotgun", &lparam));
xgboost::LinearUpdater::Create("shotgun", &ctx));
EXPECT_ANY_THROW(updater->Configure({{"feature_selector", "random"}}));
}
}
@ -50,11 +49,11 @@ TEST(Linear, coordinate) {
auto p_fmat = xgboost::RandomDataGenerator(kRows, kCols, 0).GenerateDMatrix();
auto lparam = xgboost::CreateEmptyGenericParam(GPUIDX);
auto ctx = xgboost::CreateEmptyGenericParam(GPUIDX);
LearnerModelParam mparam{MakeMP(kCols, .5, 1)};
auto updater = std::unique_ptr<xgboost::LinearUpdater>(
xgboost::LinearUpdater::Create("coord_descent", &lparam));
xgboost::LinearUpdater::Create("coord_descent", &ctx));
updater->Configure({{"eta", "1."}});
xgboost::HostDeviceVector<xgboost::GradientPair> gpair(
p_fmat->Info().num_row_, xgboost::GradientPair(-5, 1.0));

24
tests/cpp/metric/test_auc.cc
View File

@ -5,8 +5,8 @@ namespace xgboost {
namespace metric {
TEST(Metric, DeclareUnifiedTest(BinaryAUC)) {
auto tparam = xgboost::CreateEmptyGenericParam(GPUIDX);
std::unique_ptr<Metric> uni_ptr {Metric::Create("auc", &tparam)};
auto ctx = xgboost::CreateEmptyGenericParam(GPUIDX);
std::unique_ptr<Metric> uni_ptr {Metric::Create("auc", &ctx)};
Metric * metric = uni_ptr.get();
ASSERT_STREQ(metric->Name(), "auc");
@ -49,9 +49,9 @@ TEST(Metric, DeclareUnifiedTest(BinaryAUC)) {
}
TEST(Metric, DeclareUnifiedTest(MultiClassAUC)) {
auto tparam = CreateEmptyGenericParam(GPUIDX);
auto ctx = CreateEmptyGenericParam(GPUIDX);
std::unique_ptr<Metric> uni_ptr{
Metric::Create("auc", &tparam)};
Metric::Create("auc", &ctx)};
auto metric = uni_ptr.get();
// MultiClass
@ -115,8 +115,8 @@ TEST(Metric, DeclareUnifiedTest(MultiClassAUC)) {
}
TEST(Metric, DeclareUnifiedTest(RankingAUC)) {
auto tparam = CreateEmptyGenericParam(GPUIDX);
std::unique_ptr<Metric> metric{Metric::Create("auc", &tparam)};
auto ctx = CreateEmptyGenericParam(GPUIDX);
std::unique_ptr<Metric> metric{Metric::Create("auc", &ctx)};
// single group
EXPECT_NEAR(GetMetricEval(metric.get(), {0.7f, 0.2f, 0.3f, 0.6f},
@ -153,9 +153,9 @@ TEST(Metric, DeclareUnifiedTest(RankingAUC)) {
}
TEST(Metric, DeclareUnifiedTest(PRAUC)) {
auto tparam = xgboost::CreateEmptyGenericParam(GPUIDX);
auto ctx = xgboost::CreateEmptyGenericParam(GPUIDX);
xgboost::Metric *metric = xgboost::Metric::Create("aucpr", &tparam);
xgboost::Metric *metric = xgboost::Metric::Create("aucpr", &ctx);
ASSERT_STREQ(metric->Name(), "aucpr");
EXPECT_NEAR(GetMetricEval(metric, {0, 0, 1, 1}, {0, 0, 1, 1}), 1, 1e-10);
EXPECT_NEAR(GetMetricEval(metric, {0.1f, 0.9f, 0.1f, 0.9f}, {0, 0, 1, 1}),
@ -194,9 +194,9 @@ TEST(Metric, DeclareUnifiedTest(PRAUC)) {
}
TEST(Metric, DeclareUnifiedTest(MultiClassPRAUC)) {
auto tparam = xgboost::CreateEmptyGenericParam(GPUIDX);
auto ctx = xgboost::CreateEmptyGenericParam(GPUIDX);
std::unique_ptr<Metric> metric{Metric::Create("aucpr", &tparam)};
std::unique_ptr<Metric> metric{Metric::Create("aucpr", &ctx)};
float auc = 0;
std::vector<float> labels {1.0f, 0.0f, 2.0f};
@ -223,9 +223,9 @@ TEST(Metric, DeclareUnifiedTest(MultiClassPRAUC)) {
}
TEST(Metric, DeclareUnifiedTest(RankingPRAUC)) {
auto tparam = xgboost::CreateEmptyGenericParam(GPUIDX);
auto ctx = xgboost::CreateEmptyGenericParam(GPUIDX);
std::unique_ptr<Metric> metric{Metric::Create("aucpr", &tparam)};
std::unique_ptr<Metric> metric{Metric::Create("aucpr", &ctx)};
std::vector<float> labels {1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 1.0f};
std::vector<uint32_t> groups {0, 2, 6};

42
tests/cpp/metric/test_elementwise_metric.cc
View File

@ -13,8 +13,8 @@
namespace xgboost {
namespace {
inline void CheckDeterministicMetricElementWise(StringView name, int32_t device) {
auto lparam = CreateEmptyGenericParam(device);
std::unique_ptr<Metric> metric{Metric::Create(name.c_str(), &lparam)};
auto ctx = CreateEmptyGenericParam(device);
std::unique_ptr<Metric> metric{Metric::Create(name.c_str(), &ctx)};
HostDeviceVector<float> predts;
size_t n_samples = 2048;
@ -48,8 +48,8 @@ namespace xgboost {
namespace metric {
TEST(Metric, DeclareUnifiedTest(RMSE)) {
auto lparam = xgboost::CreateEmptyGenericParam(GPUIDX);
xgboost::Metric * metric = xgboost::Metric::Create("rmse", &lparam);
auto ctx = xgboost::CreateEmptyGenericParam(GPUIDX);
xgboost::Metric * metric = xgboost::Metric::Create("rmse", &ctx);
metric->Configure({});
ASSERT_STREQ(metric->Name(), "rmse");
EXPECT_NEAR(GetMetricEval(metric, {0, 1}, {0, 1}), 0, 1e-10);
@ -73,8 +73,8 @@ TEST(Metric, DeclareUnifiedTest(RMSE)) {
}
TEST(Metric, DeclareUnifiedTest(RMSLE)) {
auto lparam = xgboost::CreateEmptyGenericParam(GPUIDX);
xgboost::Metric * metric = xgboost::Metric::Create("rmsle", &lparam);
auto ctx = xgboost::CreateEmptyGenericParam(GPUIDX);
xgboost::Metric * metric = xgboost::Metric::Create("rmsle", &ctx);
metric->Configure({});
ASSERT_STREQ(metric->Name(), "rmsle");
EXPECT_NEAR(GetMetricEval(metric, {0, 1}, {0, 1}), 0, 1e-10);
@ -98,8 +98,8 @@ TEST(Metric, DeclareUnifiedTest(RMSLE)) {
}
TEST(Metric, DeclareUnifiedTest(MAE)) {
auto lparam = xgboost::CreateEmptyGenericParam(GPUIDX);
xgboost::Metric * metric = xgboost::Metric::Create("mae", &lparam);
auto ctx = xgboost::CreateEmptyGenericParam(GPUIDX);
xgboost::Metric * metric = xgboost::Metric::Create("mae", &ctx);
metric->Configure({});
ASSERT_STREQ(metric->Name(), "mae");
EXPECT_NEAR(GetMetricEval(metric, {0, 1}, {0, 1}), 0, 1e-10);
@ -123,8 +123,8 @@ TEST(Metric, DeclareUnifiedTest(MAE)) {
}
TEST(Metric, DeclareUnifiedTest(MAPE)) {
auto lparam = xgboost::CreateEmptyGenericParam(GPUIDX);
xgboost::Metric * metric = xgboost::Metric::Create("mape", &lparam);
auto ctx = xgboost::CreateEmptyGenericParam(GPUIDX);
xgboost::Metric * metric = xgboost::Metric::Create("mape", &ctx);
metric->Configure({});
ASSERT_STREQ(metric->Name(), "mape");
EXPECT_NEAR(GetMetricEval(metric, {150, 300}, {100, 200}), 0.5f, 1e-10);
@ -148,8 +148,8 @@ TEST(Metric, DeclareUnifiedTest(MAPE)) {
}
TEST(Metric, DeclareUnifiedTest(MPHE)) {
auto lparam = xgboost::CreateEmptyGenericParam(GPUIDX);
std::unique_ptr<xgboost::Metric> metric{xgboost::Metric::Create("mphe", &lparam)};
auto ctx = xgboost::CreateEmptyGenericParam(GPUIDX);
std::unique_ptr<xgboost::Metric> metric{xgboost::Metric::Create("mphe", &ctx)};
metric->Configure({});
ASSERT_STREQ(metric->Name(), "mphe");
EXPECT_NEAR(GetMetricEval(metric.get(), {0, 1}, {0, 1}), 0, 1e-10);
@ -179,8 +179,8 @@ TEST(Metric, DeclareUnifiedTest(MPHE)) {
}
TEST(Metric, DeclareUnifiedTest(LogLoss)) {
auto lparam = xgboost::CreateEmptyGenericParam(GPUIDX);
xgboost::Metric * metric = xgboost::Metric::Create("logloss", &lparam);
auto ctx = xgboost::CreateEmptyGenericParam(GPUIDX);
xgboost::Metric * metric = xgboost::Metric::Create("logloss", &ctx);
metric->Configure({});
ASSERT_STREQ(metric->Name(), "logloss");
EXPECT_NEAR(GetMetricEval(metric, {0, 1}, {0, 1}), 0, 1e-10);
@ -208,8 +208,8 @@ TEST(Metric, DeclareUnifiedTest(LogLoss)) {
}
TEST(Metric, DeclareUnifiedTest(Error)) {
auto lparam = xgboost::CreateEmptyGenericParam(GPUIDX);
xgboost::Metric * metric = xgboost::Metric::Create("error", &lparam);
auto ctx = xgboost::CreateEmptyGenericParam(GPUIDX);
xgboost::Metric * metric = xgboost::Metric::Create("error", &ctx);
metric->Configure({});
ASSERT_STREQ(metric->Name(), "error");
EXPECT_NEAR(GetMetricEval(metric, {0, 1}, {0, 1}), 0, 1e-10);
@ -228,16 +228,16 @@ TEST(Metric, DeclareUnifiedTest(Error)) {
{ 1, 2, 9, 8}),
0.55f, 0.001f);
EXPECT_ANY_THROW(xgboost::Metric::Create("error@abc", &lparam));
EXPECT_ANY_THROW(xgboost::Metric::Create("error@abc", &ctx));
delete metric;
metric = xgboost::Metric::Create("error@0.5f", &lparam);
metric = xgboost::Metric::Create("error@0.5f", &ctx);
metric->Configure({});
EXPECT_STREQ(metric->Name(), "error");
delete metric;
metric = xgboost::Metric::Create("error@0.1", &lparam);
metric = xgboost::Metric::Create("error@0.1", &ctx);
metric->Configure({});
ASSERT_STREQ(metric->Name(), "error@0.1");
EXPECT_STREQ(metric->Name(), "error@0.1");
@ -262,8 +262,8 @@ TEST(Metric, DeclareUnifiedTest(Error)) {
}
TEST(Metric, DeclareUnifiedTest(PoissionNegLogLik)) {
auto lparam = xgboost::CreateEmptyGenericParam(GPUIDX);
xgboost::Metric * metric = xgboost::Metric::Create("poisson-nloglik", &lparam);
auto ctx = xgboost::CreateEmptyGenericParam(GPUIDX);
xgboost::Metric * metric = xgboost::Metric::Create("poisson-nloglik", &ctx);
metric->Configure({});
ASSERT_STREQ(metric->Name(), "poisson-nloglik");
EXPECT_NEAR(GetMetricEval(metric, {0, 1}, {0, 1}), 0.5f, 1e-10);

10
tests/cpp/metric/test_metric.cc
View File

@ -4,16 +4,16 @@
#include "../helpers.h"
TEST(Metric, UnknownMetric) {
auto tparam = xgboost::CreateEmptyGenericParam(GPUIDX);
auto ctx = xgboost::CreateEmptyGenericParam(GPUIDX);
xgboost::Metric * metric = nullptr;
EXPECT_ANY_THROW(metric = xgboost::Metric::Create("unknown_name", &tparam));
EXPECT_NO_THROW(metric = xgboost::Metric::Create("rmse", &tparam));
EXPECT_ANY_THROW(metric = xgboost::Metric::Create("unknown_name", &ctx));
EXPECT_NO_THROW(metric = xgboost::Metric::Create("rmse", &ctx));
if (metric) {
delete metric;
}
metric = nullptr;
EXPECT_ANY_THROW(metric = xgboost::Metric::Create("unknown_name@1", &tparam));
EXPECT_NO_THROW(metric = xgboost::Metric::Create("error@0.5f", &tparam));
EXPECT_ANY_THROW(metric = xgboost::Metric::Create("unknown_name@1", &ctx));
EXPECT_NO_THROW(metric = xgboost::Metric::Create("error@0.5f", &ctx));
if (metric) {
delete metric;
}

16
tests/cpp/metric/test_multiclass_metric.cc
View File

@ -6,8 +6,8 @@
namespace xgboost {
inline void CheckDeterministicMetricMultiClass(StringView name, int32_t device) {
auto lparam = CreateEmptyGenericParam(device);
std::unique_ptr<Metric> metric{Metric::Create(name.c_str(), &lparam)};
auto ctx = CreateEmptyGenericParam(device);
std::unique_ptr<Metric> metric{Metric::Create(name.c_str(), &ctx)};
HostDeviceVector<float> predts;
MetaInfo info;
@ -43,9 +43,9 @@ inline void CheckDeterministicMetricMultiClass(StringView name, int32_t device)
} // namespace xgboost
inline void TestMultiClassError(int device) {
auto lparam = xgboost::CreateEmptyGenericParam(device);
lparam.gpu_id = device;
xgboost::Metric * metric = xgboost::Metric::Create("merror", &lparam);
auto ctx = xgboost::CreateEmptyGenericParam(device);
ctx.gpu_id = device;
xgboost::Metric * metric = xgboost::Metric::Create("merror", &ctx);
metric->Configure({});
ASSERT_STREQ(metric->Name(), "merror");
EXPECT_ANY_THROW(GetMetricEval(metric, {0}, {0, 0}));
@ -64,9 +64,9 @@ TEST(Metric, DeclareUnifiedTest(MultiClassError)) {
}
inline void TestMultiClassLogLoss(int device) {
auto lparam = xgboost::CreateEmptyGenericParam(device);
lparam.gpu_id = device;
xgboost::Metric * metric = xgboost::Metric::Create("mlogloss", &lparam);
auto ctx = xgboost::CreateEmptyGenericParam(device);
ctx.gpu_id = device;
xgboost::Metric * metric = xgboost::Metric::Create("mlogloss", &ctx);
metric->Configure({});
ASSERT_STREQ(metric->Name(), "mlogloss");
EXPECT_ANY_THROW(GetMetricEval(metric, {0}, {0, 0}));

36
tests/cpp/metric/test_rank_metric.cc
View File

@ -5,9 +5,9 @@
#if !defined(__CUDACC__)
TEST(Metric, AMS) {
auto tparam = xgboost::CreateEmptyGenericParam(GPUIDX);
EXPECT_ANY_THROW(xgboost::Metric::Create("ams", &tparam));
xgboost::Metric * metric = xgboost::Metric::Create("ams@0.5f", &tparam);
auto ctx = xgboost::CreateEmptyGenericParam(GPUIDX);
EXPECT_ANY_THROW(xgboost::Metric::Create("ams", &ctx));
xgboost::Metric* metric = xgboost::Metric::Create("ams@0.5f", &ctx);
ASSERT_STREQ(metric->Name(), "ams@0.5");
EXPECT_NEAR(GetMetricEval(metric, {0, 1}, {0, 1}), 0.311f, 0.001f);
EXPECT_NEAR(GetMetricEval(metric,
@ -16,7 +16,7 @@ TEST(Metric, AMS) {
0.29710f, 0.001f);
delete metric;
metric = xgboost::Metric::Create("ams@0", &tparam);
metric = xgboost::Metric::Create("ams@0", &ctx);
ASSERT_STREQ(metric->Name(), "ams@0");
EXPECT_NEAR(GetMetricEval(metric, {0, 1}, {0, 1}), 0.311f, 0.001f);
@ -28,8 +28,8 @@ TEST(Metric, DeclareUnifiedTest(Precision)) {
// When the limit for precision is not given, it takes the limit at
// std::numeric_limits<unsigned>::max(); hence all values are very small
// NOTE(AbdealiJK): Maybe this should be fixed to be num_row by default.
auto tparam = xgboost::CreateEmptyGenericParam(GPUIDX);
xgboost::Metric * metric = xgboost::Metric::Create("pre", &tparam);
auto ctx = xgboost::CreateEmptyGenericParam(GPUIDX);
xgboost::Metric * metric = xgboost::Metric::Create("pre", &ctx);
ASSERT_STREQ(metric->Name(), "pre");
EXPECT_NEAR(GetMetricEval(metric, {0, 1}, {0, 1}), 0, 1e-7);
EXPECT_NEAR(GetMetricEval(metric,
@ -38,7 +38,7 @@ TEST(Metric, DeclareUnifiedTest(Precision)) {
0, 1e-7);
delete metric;
metric = xgboost::Metric::Create("pre@2", &tparam);
metric = xgboost::Metric::Create("pre@2", &ctx);
ASSERT_STREQ(metric->Name(), "pre@2");
EXPECT_NEAR(GetMetricEval(metric, {0, 1}, {0, 1}), 0.5f, 1e-7);
EXPECT_NEAR(GetMetricEval(metric,
@ -52,8 +52,8 @@ TEST(Metric, DeclareUnifiedTest(Precision)) {
}
TEST(Metric, DeclareUnifiedTest(NDCG)) {
auto tparam = xgboost::CreateEmptyGenericParam(GPUIDX);
xgboost::Metric * metric = xgboost::Metric::Create("ndcg", &tparam);
auto ctx = xgboost::CreateEmptyGenericParam(GPUIDX);
xgboost::Metric * metric = xgboost::Metric::Create("ndcg", &ctx);
ASSERT_STREQ(metric->Name(), "ndcg");
EXPECT_ANY_THROW(GetMetricEval(metric, {0, 1}, {}));
EXPECT_NEAR(GetMetricEval(metric,
@ -66,7 +66,7 @@ TEST(Metric, DeclareUnifiedTest(NDCG)) {
0.6509f, 0.001f);
delete metric;
metric = xgboost::Metric::Create("ndcg@2", &tparam);
metric = xgboost::Metric::Create("ndcg@2", &ctx);
ASSERT_STREQ(metric->Name(), "ndcg@2");
EXPECT_NEAR(GetMetricEval(metric, {0, 1}, {0, 1}), 1, 1e-10);
EXPECT_NEAR(GetMetricEval(metric,
@ -75,7 +75,7 @@ TEST(Metric, DeclareUnifiedTest(NDCG)) {
0.3868f, 0.001f);
delete metric;
metric = xgboost::Metric::Create("ndcg@-", &tparam);
metric = xgboost::Metric::Create("ndcg@-", &ctx);
ASSERT_STREQ(metric->Name(), "ndcg-");
EXPECT_NEAR(GetMetricEval(metric,
xgboost::HostDeviceVector<xgboost::bst_float>{},
@ -86,7 +86,7 @@ TEST(Metric, DeclareUnifiedTest(NDCG)) {
{ 0, 0, 1, 1}),
0.6509f, 0.001f);
delete metric;
metric = xgboost::Metric::Create("ndcg-", &tparam);
metric = xgboost::Metric::Create("ndcg-", &ctx);
ASSERT_STREQ(metric->Name(), "ndcg-");
EXPECT_NEAR(GetMetricEval(metric,
xgboost::HostDeviceVector<xgboost::bst_float>{},
@ -98,7 +98,7 @@ TEST(Metric, DeclareUnifiedTest(NDCG)) {
0.6509f, 0.001f);
delete metric;
metric = xgboost::Metric::Create("ndcg@2-", &tparam);
metric = xgboost::Metric::Create("ndcg@2-", &ctx);
ASSERT_STREQ(metric->Name(), "ndcg@2-");
EXPECT_NEAR(GetMetricEval(metric, {0, 1}, {0, 1}), 1, 1e-10);
EXPECT_NEAR(GetMetricEval(metric,
@ -110,8 +110,8 @@ TEST(Metric, DeclareUnifiedTest(NDCG)) {
}
TEST(Metric, DeclareUnifiedTest(MAP)) {
auto tparam = xgboost::CreateEmptyGenericParam(GPUIDX);
xgboost::Metric * metric = xgboost::Metric::Create("map", &tparam);
auto ctx = xgboost::CreateEmptyGenericParam(GPUIDX);
xgboost::Metric * metric = xgboost::Metric::Create("map", &ctx);
ASSERT_STREQ(metric->Name(), "map");
EXPECT_NEAR(GetMetricEval(metric, {0, 1}, {0, 1}), 1, 1e-10);
EXPECT_NEAR(GetMetricEval(metric,
@ -131,21 +131,21 @@ TEST(Metric, DeclareUnifiedTest(MAP)) {
0.8611f, 0.001f);
delete metric;
metric = xgboost::Metric::Create("map@-", &tparam);
metric = xgboost::Metric::Create("map@-", &ctx);
ASSERT_STREQ(metric->Name(), "map-");
EXPECT_NEAR(GetMetricEval(metric,
xgboost::HostDeviceVector<xgboost::bst_float>{},
{}), 0, 1e-10);
delete metric;
metric = xgboost::Metric::Create("map-", &tparam);
metric = xgboost::Metric::Create("map-", &ctx);
ASSERT_STREQ(metric->Name(), "map-");
EXPECT_NEAR(GetMetricEval(metric,
xgboost::HostDeviceVector<xgboost::bst_float>{},
{}), 0, 1e-10);
delete metric;
metric = xgboost::Metric::Create("map@2", &tparam);
metric = xgboost::Metric::Create("map@2", &ctx);
ASSERT_STREQ(metric->Name(), "map@2");
EXPECT_NEAR(GetMetricEval(metric, {0, 1}, {0, 1}), 1, 1e-10);
EXPECT_NEAR(GetMetricEval(metric,

16
tests/cpp/metric/test_survival_metric.cu
View File

@ -13,8 +13,8 @@ namespace xgboost {
namespace common {
namespace {
inline void CheckDeterministicMetricElementWise(StringView name, int32_t device) {
auto lparam = CreateEmptyGenericParam(device);
std::unique_ptr<Metric> metric{Metric::Create(name.c_str(), &lparam)};
auto ctx = CreateEmptyGenericParam(device);
std::unique_ptr<Metric> metric{Metric::Create(name.c_str(), &ctx)};
metric->Configure(Args{});
HostDeviceVector<float> predts;
@ -48,7 +48,7 @@ inline void CheckDeterministicMetricElementWise(StringView name, int32_t device)
} // anonymous namespace
TEST(Metric, DeclareUnifiedTest(AFTNegLogLik)) {
auto lparam = xgboost::CreateEmptyGenericParam(GPUIDX);
auto ctx = xgboost::CreateEmptyGenericParam(GPUIDX);
/**
* Test aggregate output from the AFT metric over a small test data set.
@ -69,7 +69,7 @@ TEST(Metric, DeclareUnifiedTest(AFTNegLogLik)) {
};
for (const auto& test_case : std::vector<TestCase>{ {"normal", 2.1508f}, {"logistic", 2.1804f},
{"extreme", 2.0706f} }) {
std::unique_ptr<Metric> metric(Metric::Create("aft-nloglik", &lparam));
std::unique_ptr<Metric> metric(Metric::Create("aft-nloglik", &ctx));
metric->Configure({ {"aft_loss_distribution", test_case.dist_type},
{"aft_loss_distribution_scale", "1.0"} });
EXPECT_NEAR(metric->Eval(preds, info), test_case.reference_value, 1e-4);
@ -77,7 +77,7 @@ TEST(Metric, DeclareUnifiedTest(AFTNegLogLik)) {
}
TEST(Metric, DeclareUnifiedTest(IntervalRegressionAccuracy)) {
auto lparam = xgboost::CreateEmptyGenericParam(GPUIDX);
auto ctx = xgboost::CreateEmptyGenericParam(GPUIDX);
MetaInfo info;
info.num_row_ = 4;
@ -86,7 +86,7 @@ TEST(Metric, DeclareUnifiedTest(IntervalRegressionAccuracy)) {
info.weights_.HostVector() = std::vector<bst_float>();
HostDeviceVector<bst_float> preds(4, std::log(60.0f));
std::unique_ptr<Metric> metric(Metric::Create("interval-regression-accuracy", &lparam));
std::unique_ptr<Metric> metric(Metric::Create("interval-regression-accuracy", &ctx));
EXPECT_FLOAT_EQ(metric->Eval(preds, info), 0.75f);
info.labels_lower_bound_.HostVector()[2] = 70.0f;
EXPECT_FLOAT_EQ(metric->Eval(preds, info), 0.50f);
@ -102,8 +102,8 @@ TEST(Metric, DeclareUnifiedTest(IntervalRegressionAccuracy)) {
// Test configuration of AFT metric
TEST(AFTNegLogLikMetric, DeclareUnifiedTest(Configuration)) {
auto lparam = xgboost::CreateEmptyGenericParam(GPUIDX);
std::unique_ptr<Metric> metric(Metric::Create("aft-nloglik", &lparam));
auto ctx = xgboost::CreateEmptyGenericParam(GPUIDX);
std::unique_ptr<Metric> metric(Metric::Create("aft-nloglik", &ctx));
metric->Configure({{"aft_loss_distribution", "normal"}, {"aft_loss_distribution_scale", "10"}});
// Configuration round-trip test

20
tests/cpp/objective/test_aft_obj.cc
View File

@ -16,8 +16,8 @@ namespace xgboost {
namespace common {
TEST(Objective, DeclareUnifiedTest(AFTObjConfiguration)) {
auto lparam = CreateEmptyGenericParam(GPUIDX);
std::unique_ptr<ObjFunction> objective(ObjFunction::Create("survival:aft", &lparam));
auto ctx = CreateEmptyGenericParam(GPUIDX);
std::unique_ptr<ObjFunction> objective(ObjFunction::Create("survival:aft", &ctx));
objective->Configure({ {"aft_loss_distribution", "logistic"},
{"aft_loss_distribution_scale", "5"} });
@ -77,8 +77,8 @@ static inline void CheckGPairOverGridPoints(
}
TEST(Objective, DeclareUnifiedTest(AFTObjGPairUncensoredLabels)) {
auto lparam = CreateEmptyGenericParam(GPUIDX);
std::unique_ptr<ObjFunction> obj(ObjFunction::Create("survival:aft", &lparam));
auto ctx = CreateEmptyGenericParam(GPUIDX);
std::unique_ptr<ObjFunction> obj(ObjFunction::Create("survival:aft", &ctx));
CheckGPairOverGridPoints(obj.get(), 100.0f, 100.0f, "normal",
{ -3.9120f, -3.4013f, -2.8905f, -2.3798f, -1.8691f, -1.3583f, -0.8476f, -0.3368f, 0.1739f,
@ -101,8 +101,8 @@ TEST(Objective, DeclareUnifiedTest(AFTObjGPairUncensoredLabels)) {
}
TEST(Objective, DeclareUnifiedTest(AFTObjGPairLeftCensoredLabels)) {
auto lparam = CreateEmptyGenericParam(GPUIDX);
std::unique_ptr<ObjFunction> obj(ObjFunction::Create("survival:aft", &lparam));
auto ctx = CreateEmptyGenericParam(GPUIDX);
std::unique_ptr<ObjFunction> obj(ObjFunction::Create("survival:aft", &ctx));
CheckGPairOverGridPoints(obj.get(), 0.0f, 20.0f, "normal",
{ 0.0285f, 0.0832f, 0.1951f, 0.3804f, 0.6403f, 0.9643f, 1.3379f, 1.7475f, 2.1828f, 2.6361f,
@ -122,8 +122,8 @@ TEST(Objective, DeclareUnifiedTest(AFTObjGPairLeftCensoredLabels)) {
}
TEST(Objective, DeclareUnifiedTest(AFTObjGPairRightCensoredLabels)) {
auto lparam = CreateEmptyGenericParam(GPUIDX);
std::unique_ptr<ObjFunction> obj(ObjFunction::Create("survival:aft", &lparam));
auto ctx = CreateEmptyGenericParam(GPUIDX);
std::unique_ptr<ObjFunction> obj(ObjFunction::Create("survival:aft", &ctx));
CheckGPairOverGridPoints(obj.get(), 60.0f, std::numeric_limits<float>::infinity(), "normal",
{ -3.6583f, -3.1815f, -2.7135f, -2.2577f, -1.8190f, -1.4044f, -1.0239f, -0.6905f, -0.4190f,
@ -146,8 +146,8 @@ TEST(Objective, DeclareUnifiedTest(AFTObjGPairRightCensoredLabels)) {
}
TEST(Objective, DeclareUnifiedTest(AFTObjGPairIntervalCensoredLabels)) {
auto lparam = CreateEmptyGenericParam(GPUIDX);
std::unique_ptr<ObjFunction> obj(ObjFunction::Create("survival:aft", &lparam));
auto ctx = CreateEmptyGenericParam(GPUIDX);
std::unique_ptr<ObjFunction> obj(ObjFunction::Create("survival:aft", &ctx));
CheckGPairOverGridPoints(obj.get(), 16.0f, 200.0f, "normal",
{ -2.4435f, -1.9965f, -1.5691f, -1.1679f, -0.7990f, -0.4649f, -0.1596f, 0.1336f, 0.4370f,

6
tests/cpp/objective/test_hinge.cc
View File

@ -1,14 +1,14 @@
// Copyright by Contributors
#include <xgboost/objective.h>
#include <xgboost/generic_parameters.h>
#include <xgboost/context.h>
#include <limits>
#include "../helpers.h"
TEST(Objective, DeclareUnifiedTest(HingeObj)) {
xgboost::GenericParameter tparam = xgboost::CreateEmptyGenericParam(GPUIDX);
xgboost::Context ctx = xgboost::CreateEmptyGenericParam(GPUIDX);
std::unique_ptr<xgboost::ObjFunction> obj {
xgboost::ObjFunction::Create("binary:hinge", &tparam)
xgboost::ObjFunction::Create("binary:hinge", &ctx)
};
xgboost::bst_float eps = std::numeric_limits<xgboost::bst_float>::min();

14
tests/cpp/objective/test_multiclass_obj.cc
View File

@ -2,17 +2,17 @@
* Copyright 2018-2019 XGBoost contributors
*/
#include <xgboost/objective.h>
#include <xgboost/generic_parameters.h>
#include <xgboost/context.h>
#include "../../src/common/common.h"
#include "../helpers.h"
namespace xgboost {
TEST(Objective, DeclareUnifiedTest(SoftmaxMultiClassObjGPair)) {
GenericParameter lparam = CreateEmptyGenericParam(GPUIDX);
Context ctx = CreateEmptyGenericParam(GPUIDX);
std::vector<std::pair<std::string, std::string>> args {{"num_class", "3"}};
std::unique_ptr<ObjFunction> obj {
ObjFunction::Create("multi:softmax", &lparam)
ObjFunction::Create("multi:softmax", &ctx)
};
obj->Configure(args);
@ -36,11 +36,11 @@ TEST(Objective, DeclareUnifiedTest(SoftmaxMultiClassObjGPair)) {
}
TEST(Objective, DeclareUnifiedTest(SoftmaxMultiClassBasic)) {
auto lparam = CreateEmptyGenericParam(GPUIDX);
auto ctx = CreateEmptyGenericParam(GPUIDX);
std::vector<std::pair<std::string, std::string>> args{
std::pair<std::string, std::string>("num_class", "3")};
std::unique_ptr<ObjFunction> obj { ObjFunction::Create("multi:softmax", &lparam) };
std::unique_ptr<ObjFunction> obj{ObjFunction::Create("multi:softmax", &ctx)};
obj->Configure(args);
CheckConfigReload(obj, "multi:softmax");
@ -57,12 +57,12 @@ TEST(Objective, DeclareUnifiedTest(SoftmaxMultiClassBasic)) {
}
TEST(Objective, DeclareUnifiedTest(SoftprobMultiClassBasic)) {
GenericParameter lparam = CreateEmptyGenericParam(GPUIDX);
Context ctx = CreateEmptyGenericParam(GPUIDX);
std::vector<std::pair<std::string, std::string>> args {
std::pair<std::string, std::string>("num_class", "3")};
std::unique_ptr<ObjFunction> obj {
ObjFunction::Create("multi:softprob", &lparam)
ObjFunction::Create("multi:softprob", &ctx)
};
obj->Configure(args);
CheckConfigReload(obj, "multi:softprob");

6
tests/cpp/objective/test_objective.cc
View File

@ -1,13 +1,13 @@
// Copyright by Contributors
#include <gtest/gtest.h>
#include <xgboost/context.h>
#include <xgboost/objective.h>
#include <xgboost/generic_parameters.h>
#include "../helpers.h"
TEST(Objective, UnknownFunction) {
xgboost::ObjFunction* obj = nullptr;
xgboost::GenericParameter tparam;
xgboost::Context tparam;
std::vector<std::pair<std::string, std::string>> args;
tparam.UpdateAllowUnknown(args);
@ -21,7 +21,7 @@ TEST(Objective, UnknownFunction) {
namespace xgboost {
TEST(Objective, PredTransform) {
// Test that show PredTransform uses the same device with predictor.
xgboost::GenericParameter tparam;
xgboost::Context tparam;
tparam.UpdateAllowUnknown(Args{{"gpu_id", "0"}});
size_t n = 100;

39
tests/cpp/objective/test_ranking_obj.cc
View File

@ -1,18 +1,17 @@
// Copyright by Contributors
#include <xgboost/objective.h>
#include <xgboost/generic_parameters.h>
#include "../helpers.h"
#include <xgboost/context.h>
#include <xgboost/json.h>
#include <xgboost/objective.h>
#include "../helpers.h"
namespace xgboost {
TEST(Objective, DeclareUnifiedTest(PairwiseRankingGPair)) {
std::vector<std::pair<std::string, std::string>> args;
xgboost::GenericParameter lparam = xgboost::CreateEmptyGenericParam(GPUIDX);
xgboost::Context ctx = xgboost::CreateEmptyGenericParam(GPUIDX);
std::unique_ptr<xgboost::ObjFunction> obj {
xgboost::ObjFunction::Create("rank:pairwise", &lparam)
};
std::unique_ptr<xgboost::ObjFunction> obj{xgboost::ObjFunction::Create("rank:pairwise", &ctx)};
obj->Configure(args);
CheckConfigReload(obj, "rank:pairwise");
@ -37,12 +36,10 @@ TEST(Objective, DeclareUnifiedTest(PairwiseRankingGPair)) {
}
TEST(Objective, DeclareUnifiedTest(NDCG_JsonIO)) {
xgboost::GenericParameter tparam;
tparam.UpdateAllowUnknown(Args{});
xgboost::Context ctx;
ctx.UpdateAllowUnknown(Args{});
std::unique_ptr<xgboost::ObjFunction> obj {
xgboost::ObjFunction::Create("rank:ndcg", &tparam)
};
std::unique_ptr<xgboost::ObjFunction> obj{xgboost::ObjFunction::Create("rank:ndcg", &ctx)};
obj->Configure(Args{});
Json j_obj {Object()};
@ -58,11 +55,9 @@ TEST(Objective, DeclareUnifiedTest(NDCG_JsonIO)) {
TEST(Objective, DeclareUnifiedTest(PairwiseRankingGPairSameLabels)) {
std::vector<std::pair<std::string, std::string>> args;
xgboost::GenericParameter lparam = xgboost::CreateEmptyGenericParam(GPUIDX);
xgboost::Context ctx = xgboost::CreateEmptyGenericParam(GPUIDX);
std::unique_ptr<ObjFunction> obj {
ObjFunction::Create("rank:pairwise", &lparam)
};
std::unique_ptr<ObjFunction> obj{ObjFunction::Create("rank:pairwise", &ctx)};
obj->Configure(args);
// No computation of gradient/hessian, as there is no diversity in labels
CheckRankingObjFunction(obj,
@ -78,11 +73,9 @@ TEST(Objective, DeclareUnifiedTest(PairwiseRankingGPairSameLabels)) {
TEST(Objective, DeclareUnifiedTest(NDCGRankingGPair)) {
std::vector<std::pair<std::string, std::string>> args;
xgboost::GenericParameter lparam = xgboost::CreateEmptyGenericParam(GPUIDX);
xgboost::Context ctx = xgboost::CreateEmptyGenericParam(GPUIDX);
std::unique_ptr<xgboost::ObjFunction> obj {
xgboost::ObjFunction::Create("rank:ndcg", &lparam)
};
std::unique_ptr<xgboost::ObjFunction> obj{xgboost::ObjFunction::Create("rank:ndcg", &ctx)};
obj->Configure(args);
CheckConfigReload(obj, "rank:ndcg");
@ -107,11 +100,9 @@ TEST(Objective, DeclareUnifiedTest(NDCGRankingGPair)) {
TEST(Objective, DeclareUnifiedTest(MAPRankingGPair)) {
std::vector<std::pair<std::string, std::string>> args;
xgboost::GenericParameter lparam = xgboost::CreateEmptyGenericParam(GPUIDX);
xgboost::Context ctx = xgboost::CreateEmptyGenericParam(GPUIDX);
std::unique_ptr<xgboost::ObjFunction> obj {
xgboost::ObjFunction::Create("rank:map", &lparam)
};
std::unique_ptr<xgboost::ObjFunction> obj{xgboost::ObjFunction::Create("rank:map", &ctx)};
obj->Configure(args);
CheckConfigReload(obj, "rank:map");

75
tests/cpp/objective/test_regression_obj.cc
View File

@ -2,7 +2,7 @@
* Copyright 2017-2022 XGBoost contributors
*/
#include <gtest/gtest.h>
#include <xgboost/generic_parameters.h>
#include <xgboost/context.h>
#include <xgboost/json.h>
#include <xgboost/objective.h>
@ -12,12 +12,10 @@
namespace xgboost {
TEST(Objective, DeclareUnifiedTest(LinearRegressionGPair)) {
GenericParameter tparam = CreateEmptyGenericParam(GPUIDX);
Context ctx = CreateEmptyGenericParam(GPUIDX);
std::vector<std::pair<std::string, std::string>> args;
std::unique_ptr<ObjFunction> obj {
ObjFunction::Create("reg:squarederror", &tparam)
};
std::unique_ptr<ObjFunction> obj{ObjFunction::Create("reg:squarederror", &ctx)};
obj->Configure(args);
CheckObjFunction(obj,
@ -36,10 +34,10 @@ TEST(Objective, DeclareUnifiedTest(LinearRegressionGPair)) {
}
TEST(Objective, DeclareUnifiedTest(SquaredLog)) {
GenericParameter tparam = CreateEmptyGenericParam(GPUIDX);
Context ctx = CreateEmptyGenericParam(GPUIDX);
std::vector<std::pair<std::string, std::string>> args;
std::unique_ptr<ObjFunction> obj { ObjFunction::Create("reg:squaredlogerror", &tparam) };
std::unique_ptr<ObjFunction> obj{ObjFunction::Create("reg:squaredlogerror", &ctx)};
obj->Configure(args);
CheckConfigReload(obj, "reg:squaredlogerror");
@ -59,10 +57,10 @@ TEST(Objective, DeclareUnifiedTest(SquaredLog)) {
}
TEST(Objective, DeclareUnifiedTest(PseudoHuber)) {
GenericParameter tparam = CreateEmptyGenericParam(GPUIDX);
Context ctx = CreateEmptyGenericParam(GPUIDX);
Args args;
std::unique_ptr<ObjFunction> obj{ObjFunction::Create("reg:pseudohubererror", &tparam)};
std::unique_ptr<ObjFunction> obj{ObjFunction::Create("reg:pseudohubererror", &ctx)};
obj->Configure(args);
CheckConfigReload(obj, "reg:pseudohubererror");
@ -88,9 +86,9 @@ TEST(Objective, DeclareUnifiedTest(PseudoHuber)) {
}
TEST(Objective, DeclareUnifiedTest(LogisticRegressionGPair)) {
GenericParameter tparam = CreateEmptyGenericParam(GPUIDX);
Context ctx = CreateEmptyGenericParam(GPUIDX);
std::vector<std::pair<std::string, std::string>> args;
std::unique_ptr<ObjFunction> obj { ObjFunction::Create("reg:logistic", &tparam) };
std::unique_ptr<ObjFunction> obj{ObjFunction::Create("reg:logistic", &ctx)};
obj->Configure(args);
CheckConfigReload(obj, "reg:logistic");
@ -104,11 +102,9 @@ TEST(Objective, DeclareUnifiedTest(LogisticRegressionGPair)) {
}
TEST(Objective, DeclareUnifiedTest(LogisticRegressionBasic)) {
GenericParameter lparam = CreateEmptyGenericParam(GPUIDX);
Context ctx = CreateEmptyGenericParam(GPUIDX);
std::vector<std::pair<std::string, std::string>> args;
std::unique_ptr<ObjFunction> obj {
ObjFunction::Create("reg:logistic", &lparam)
};
std::unique_ptr<ObjFunction> obj{ObjFunction::Create("reg:logistic", &ctx)};
obj->Configure(args);
CheckConfigReload(obj, "reg:logistic");
@ -135,10 +131,10 @@ TEST(Objective, DeclareUnifiedTest(LogisticRegressionBasic)) {
}
TEST(Objective, DeclareUnifiedTest(LogisticRawGPair)) {
GenericParameter lparam = CreateEmptyGenericParam(GPUIDX);
Context ctx = CreateEmptyGenericParam(GPUIDX);
std::vector<std::pair<std::string, std::string>> args;
std::unique_ptr<ObjFunction> obj {
ObjFunction::Create("binary:logitraw", &lparam)
ObjFunction::Create("binary:logitraw", &ctx)
};
obj->Configure(args);
@ -151,10 +147,10 @@ TEST(Objective, DeclareUnifiedTest(LogisticRawGPair)) {
}
TEST(Objective, DeclareUnifiedTest(PoissonRegressionGPair)) {
GenericParameter lparam = CreateEmptyGenericParam(GPUIDX);
Context ctx = CreateEmptyGenericParam(GPUIDX);
std::vector<std::pair<std::string, std::string>> args;
std::unique_ptr<ObjFunction> obj {
ObjFunction::Create("count:poisson", &lparam)
ObjFunction::Create("count:poisson", &ctx)
};
args.emplace_back(std::make_pair("max_delta_step", "0.1f"));
@ -175,10 +171,10 @@ TEST(Objective, DeclareUnifiedTest(PoissonRegressionGPair)) {
}
TEST(Objective, DeclareUnifiedTest(PoissonRegressionBasic)) {
GenericParameter lparam = CreateEmptyGenericParam(GPUIDX);
Context ctx = CreateEmptyGenericParam(GPUIDX);
std::vector<std::pair<std::string, std::string>> args;
std::unique_ptr<ObjFunction> obj {
ObjFunction::Create("count:poisson", &lparam)
ObjFunction::Create("count:poisson", &ctx)
};
obj->Configure(args);
@ -204,10 +200,10 @@ TEST(Objective, DeclareUnifiedTest(PoissonRegressionBasic)) {
}
TEST(Objective, DeclareUnifiedTest(GammaRegressionGPair)) {
GenericParameter lparam = CreateEmptyGenericParam(GPUIDX);
Context ctx = CreateEmptyGenericParam(GPUIDX);
std::vector<std::pair<std::string, std::string>> args;
std::unique_ptr<ObjFunction> obj {
ObjFunction::Create("reg:gamma", &lparam)
ObjFunction::Create("reg:gamma", &ctx)
};
obj->Configure(args);
@ -226,11 +222,9 @@ TEST(Objective, DeclareUnifiedTest(GammaRegressionGPair)) {
}
TEST(Objective, DeclareUnifiedTest(GammaRegressionBasic)) {
GenericParameter lparam = CreateEmptyGenericParam(GPUIDX);
Context ctx = CreateEmptyGenericParam(GPUIDX);
std::vector<std::pair<std::string, std::string>> args;
std::unique_ptr<ObjFunction> obj {
ObjFunction::Create("reg:gamma", &lparam)
};
std::unique_ptr<ObjFunction> obj{ObjFunction::Create("reg:gamma", &ctx)};
obj->Configure(args);
CheckConfigReload(obj, "reg:gamma");
@ -257,11 +251,9 @@ TEST(Objective, DeclareUnifiedTest(GammaRegressionBasic)) {
}
TEST(Objective, DeclareUnifiedTest(TweedieRegressionGPair)) {
GenericParameter lparam = CreateEmptyGenericParam(GPUIDX);
Context ctx = CreateEmptyGenericParam(GPUIDX);
std::vector<std::pair<std::string, std::string>> args;
std::unique_ptr<ObjFunction> obj {
ObjFunction::Create("reg:tweedie", &lparam)
};
std::unique_ptr<ObjFunction> obj{ObjFunction::Create("reg:tweedie", &ctx)};
args.emplace_back(std::make_pair("tweedie_variance_power", "1.1f"));
obj->Configure(args);
@ -283,10 +275,9 @@ TEST(Objective, DeclareUnifiedTest(TweedieRegressionGPair)) {
#if defined(__CUDACC__)
TEST(Objective, CPU_vs_CUDA) {
GenericParameter lparam = CreateEmptyGenericParam(GPUIDX);
Context ctx = CreateEmptyGenericParam(GPUIDX);
ObjFunction * obj =
ObjFunction::Create("reg:squarederror", &lparam);
ObjFunction* obj = ObjFunction::Create("reg:squarederror", &ctx);
HostDeviceVector<GradientPair> cpu_out_preds;
HostDeviceVector<GradientPair> cuda_out_preds;
@ -309,12 +300,12 @@ TEST(Objective, CPU_vs_CUDA) {
{
// CPU
lparam.gpu_id = -1;
ctx.gpu_id = -1;
obj->GetGradient(preds, info, 0, &cpu_out_preds);
}
{
// CUDA
lparam.gpu_id = 0;
ctx.gpu_id = 0;
obj->GetGradient(preds, info, 0, &cuda_out_preds);
}
@ -335,11 +326,9 @@ TEST(Objective, CPU_vs_CUDA) {
#endif
TEST(Objective, DeclareUnifiedTest(TweedieRegressionBasic)) {
GenericParameter lparam = CreateEmptyGenericParam(GPUIDX);
Context ctx = CreateEmptyGenericParam(GPUIDX);
std::vector<std::pair<std::string, std::string>> args;
std::unique_ptr<ObjFunction> obj {
ObjFunction::Create("reg:tweedie", &lparam)
};
std::unique_ptr<ObjFunction> obj{ObjFunction::Create("reg:tweedie", &ctx)};
obj->Configure(args);
CheckConfigReload(obj, "reg:tweedie");
@ -366,11 +355,9 @@ TEST(Objective, DeclareUnifiedTest(TweedieRegressionBasic)) {
// CoxRegression not implemented in GPU code, no need for testing.
#if !defined(__CUDACC__)
TEST(Objective, CoxRegressionGPair) {
GenericParameter lparam = CreateEmptyGenericParam(GPUIDX);
Context ctx = CreateEmptyGenericParam(GPUIDX);
std::vector<std::pair<std::string, std::string>> args;
std::unique_ptr<ObjFunction> obj {
ObjFunction::Create("survival:cox", &lparam)
};
std::unique_ptr<ObjFunction> obj{ObjFunction::Create("survival:cox", &ctx)};
obj->Configure(args);
CheckObjFunction(obj,

4
tests/cpp/plugin/test_example_objective.cc
View File

@ -6,8 +6,8 @@
namespace xgboost {
TEST(Plugin, ExampleObjective) {
xgboost::GenericParameter tparam = CreateEmptyGenericParam(GPUIDX);
auto * obj = xgboost::ObjFunction::Create("mylogistic", &tparam);
xgboost::Context ctx = CreateEmptyGenericParam(GPUIDX);
auto* obj = xgboost::ObjFunction::Create("mylogistic", &ctx);
ASSERT_EQ(obj->DefaultEvalMetric(), std::string{"logloss"});
delete obj;
}

22
tests/cpp/plugin/test_regression_obj_oneapi.cc
View File

@ -3,13 +3,13 @@
*/
#include <gtest/gtest.h>
#include <xgboost/objective.h>
#include <xgboost/generic_parameters.h>
#include <xgboost/context.h>
#include <xgboost/json.h>
#include "../helpers.h"
namespace xgboost {
TEST(Plugin, LinearRegressionGPairOneAPI) {
GenericParameter tparam = CreateEmptyGenericParam(0);
Context tparam = CreateEmptyGenericParam(0);
std::vector<std::pair<std::string, std::string>> args;
std::unique_ptr<ObjFunction> obj {
@ -33,7 +33,7 @@ TEST(Plugin, LinearRegressionGPairOneAPI) {
}
TEST(Plugin, SquaredLogOneAPI) {
GenericParameter tparam = CreateEmptyGenericParam(0);
Context tparam = CreateEmptyGenericParam(0);
std::vector<std::pair<std::string, std::string>> args;
std::unique_ptr<ObjFunction> obj { ObjFunction::Create("reg:squaredlogerror_oneapi", &tparam) };
@ -56,7 +56,7 @@ TEST(Plugin, SquaredLogOneAPI) {
}
TEST(Plugin, LogisticRegressionGPairOneAPI) {
GenericParameter tparam = CreateEmptyGenericParam(0);
Context tparam = CreateEmptyGenericParam(0);
std::vector<std::pair<std::string, std::string>> args;
std::unique_ptr<ObjFunction> obj { ObjFunction::Create("reg:logistic_oneapi", &tparam) };
@ -72,7 +72,7 @@ TEST(Plugin, LogisticRegressionGPairOneAPI) {
}
TEST(Plugin, LogisticRegressionBasicOneAPI) {
GenericParameter lparam = CreateEmptyGenericParam(0);
Context lparam = CreateEmptyGenericParam(0);
std::vector<std::pair<std::string, std::string>> args;
std::unique_ptr<ObjFunction> obj {
ObjFunction::Create("reg:logistic_oneapi", &lparam)
@ -103,7 +103,7 @@ TEST(Plugin, LogisticRegressionBasicOneAPI) {
}
TEST(Plugin, LogisticRawGPairOneAPI) {
GenericParameter lparam = CreateEmptyGenericParam(0);
Context lparam = CreateEmptyGenericParam(0);
std::vector<std::pair<std::string, std::string>> args;
std::unique_ptr<ObjFunction> obj {
ObjFunction::Create("binary:logitraw_oneapi", &lparam)
@ -120,12 +120,12 @@ TEST(Plugin, LogisticRawGPairOneAPI) {
}
TEST(Plugin, CPUvsOneAPI) {
GenericParameter lparam = CreateEmptyGenericParam(0);
Context ctx = CreateEmptyGenericParam(0);
ObjFunction * obj_cpu =
ObjFunction::Create("reg:squarederror", &lparam);
ObjFunction::Create("reg:squarederror", &ctx);
ObjFunction * obj_oneapi =
ObjFunction::Create("reg:squarederror_oneapi", &lparam);
ObjFunction::Create("reg:squarederror_oneapi", &ctx);
HostDeviceVector<GradientPair> cpu_out_preds;
HostDeviceVector<GradientPair> oneapi_out_preds;
@ -148,12 +148,12 @@ TEST(Plugin, CPUvsOneAPI) {
{
// CPU
lparam.gpu_id = -1;
ctx.gpu_id = -1;
obj_cpu->GetGradient(preds, info, 0, &cpu_out_preds);
}
{
// oneapi
lparam.gpu_id = 0;
ctx.gpu_id = 0;
obj_oneapi->GetGradient(preds, info, 0, &oneapi_out_preds);
}

4
tests/cpp/predictor/test_cpu_predictor.cc
View File

@ -23,7 +23,7 @@ TEST(CpuPredictor, Basic) {
LearnerModelParam mparam{MakeMP(kCols, .0, 1)};
GenericParameter ctx;
Context ctx;
ctx.UpdateAllowUnknown(Args{});
gbm::GBTreeModel model = CreateTestModel(&mparam, &ctx);
@ -103,7 +103,7 @@ TEST(CpuPredictor, ExternalMemory) {
LearnerModelParam mparam{MakeMP(dmat->Info().num_col_, .0, 1)};
GenericParameter ctx;
Context ctx;
ctx.UpdateAllowUnknown(Args{});
gbm::GBTreeModel model = CreateTestModel(&mparam, &ctx);

8
tests/cpp/predictor/test_predictor.cc
View File

@ -5,8 +5,8 @@
#include "test_predictor.h"
#include <gtest/gtest.h>
#include <xgboost/context.h>
#include <xgboost/data.h>
#include <xgboost/generic_parameters.h>
#include <xgboost/host_device_vector.h>
#include <xgboost/predictor.h>
@ -26,7 +26,7 @@ TEST(Predictor, PredictionCache) {
// Add a cache that is immediately expired.
auto add_cache = [&]() {
auto p_dmat = RandomDataGenerator(kRows, kCols, 0).GenerateDMatrix();
container.Cache(p_dmat, GenericParameter::kCpuId);
container.Cache(p_dmat, Context::kCpuId);
m = p_dmat.get();
};
@ -216,7 +216,7 @@ void TestCategoricalPrediction(std::string name) {
float left_weight = 1.3f;
float right_weight = 1.7f;
GenericParameter ctx;
Context ctx;
ctx.UpdateAllowUnknown(Args{});
gbm::GBTreeModel model(&mparam, &ctx);
GBTreeModelForTest(&model, split_ind, split_cat, left_weight, right_weight);
@ -257,7 +257,7 @@ void TestCategoricalPredictLeaf(StringView name) {
float left_weight = 1.3f;
float right_weight = 1.7f;
GenericParameter ctx;
Context ctx;
ctx.UpdateAllowUnknown(Args{});
gbm::GBTreeModel model(&mparam, &ctx);

2
tests/cpp/predictor/test_predictor.h
View File

@ -19,7 +19,7 @@ void TestPredictionFromGradientIndex(std::string name, size_t rows, size_t cols,
std::unique_ptr<Predictor>(Predictor::Create(name, &lparam));
predictor->Configure({});
GenericParameter ctx;
Context ctx;
ctx.UpdateAllowUnknown(Args{});
gbm::GBTreeModel model = CreateTestModel(&mparam, &ctx, kClasses);

2
tests/cpp/test_learner.cc
View File

@ -363,7 +363,7 @@ TEST(Learner, ConstantSeed) {
CHECK_NE(v_0, v_1);
{
rng.seed(GenericParameter::kDefaultSeed);
rng.seed(Context::kDefaultSeed);
std::uniform_real_distribution<float> dist;
float v_2 = dist(rng);
CHECK_EQ(v_0, v_2);

8
tests/cpp/tree/gpu_hist/test_row_partitioner.cu
View File

@ -2,17 +2,17 @@
* Copyright 2019-2022 by XGBoost Contributors
*/
#include <gtest/gtest.h>
#include <algorithm>
#include <vector>
#include <thrust/device_vector.h>
#include <thrust/host_vector.h>
#include <thrust/sequence.h>
#include <algorithm>
#include <vector>
#include "../../../../src/tree/gpu_hist/row_partitioner.cuh"
#include "../../helpers.h"
#include "xgboost/base.h"
#include "xgboost/generic_parameters.h"
#include "xgboost/context.h"
#include "xgboost/task.h"
#include "xgboost/tree_model.h"

4
tests/cpp/tree/test_approx.cc
View File

@ -12,7 +12,7 @@ namespace xgboost {
namespace tree {
TEST(Approx, Partitioner) {
size_t n_samples = 1024, n_features = 1, base_rowid = 0;
GenericParameter ctx;
Context ctx;
CommonRowPartitioner partitioner{&ctx, n_samples, base_rowid};
ASSERT_EQ(partitioner.base_rowid, base_rowid);
ASSERT_EQ(partitioner.Size(), 1);
@ -69,7 +69,7 @@ TEST(Approx, Partitioner) {
namespace {
void TestLeafPartition(size_t n_samples) {
size_t const n_features = 2, base_rowid = 0;
GenericParameter ctx;
Context ctx;
common::RowSetCollection row_set;
CommonRowPartitioner partitioner{&ctx, n_samples, base_rowid};

18
tests/cpp/tree/test_gpu_hist.cu
View File

@ -18,7 +18,7 @@
#include "../filesystem.h" // dmlc::TemporaryDirectory
#include "../helpers.h"
#include "../histogram_helpers.h"
#include "xgboost/generic_parameters.h"
#include "xgboost/context.h"
#include "xgboost/json.h"
namespace xgboost {
@ -170,9 +170,9 @@ void TestHistogramIndexImpl() {
// Build 2 matrices and build a histogram maker with that
GenericParameter generic_param(CreateEmptyGenericParam(0));
tree::GPUHistMaker hist_maker{&generic_param,ObjInfo{ObjInfo::kRegression}},
hist_maker_ext{&generic_param,ObjInfo{ObjInfo::kRegression}};
Context ctx(CreateEmptyGenericParam(0));
tree::GPUHistMaker hist_maker{&ctx, ObjInfo{ObjInfo::kRegression}},
hist_maker_ext{&ctx, ObjInfo{ObjInfo::kRegression}};
std::unique_ptr<DMatrix> hist_maker_dmat(
CreateSparsePageDMatrixWithRC(kNRows, kNCols, 0, true));
@ -239,8 +239,8 @@ void UpdateTree(HostDeviceVector<GradientPair>* gpair, DMatrix* dmat,
{"sampling_method", sampling_method},
};
GenericParameter generic_param(CreateEmptyGenericParam(0));
tree::GPUHistMaker hist_maker{&generic_param,ObjInfo{ObjInfo::kRegression}};
Context ctx(CreateEmptyGenericParam(0));
tree::GPUHistMaker hist_maker{&ctx,ObjInfo{ObjInfo::kRegression}};
hist_maker.Configure(args);
std::vector<HostDeviceVector<bst_node_t>> position(1);
@ -384,9 +384,9 @@ TEST(GpuHist, ExternalMemoryWithSampling) {
}
TEST(GpuHist, ConfigIO) {
GenericParameter generic_param(CreateEmptyGenericParam(0));
Context ctx(CreateEmptyGenericParam(0));
std::unique_ptr<TreeUpdater> updater{
TreeUpdater::Create("grow_gpu_hist", &generic_param, ObjInfo{ObjInfo::kRegression})};
TreeUpdater::Create("grow_gpu_hist", &ctx, ObjInfo{ObjInfo::kRegression})};
updater->Configure(Args{});
Json j_updater { Object() };
@ -404,7 +404,7 @@ TEST(GpuHist, ConfigIO) {
}
TEST(GpuHist, MaxDepth) {
GenericParameter generic_param(CreateEmptyGenericParam(0));
Context ctx(CreateEmptyGenericParam(0));
size_t constexpr kRows = 16;
size_t constexpr kCols = 4;
auto p_mat = RandomDataGenerator{kRows, kCols, 0}.GenerateDMatrix();

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