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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
105 changed files with 548 additions and 574 deletions
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22
src/metric/auc.cc
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@@ -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
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@@ -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
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@@ -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
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@@ -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);
};
/*!

11
src/metric/multiclass_metric.cu
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@@ -126,13 +126,10 @@ class MultiClassMetricsReduction {
#endif // XGBOOST_USE_CUDA
PackedReduceResult Reduce(
const GenericParameter &tparam,
int device,
size_t n_class,
const HostDeviceVector<bst_float>& weights,
const HostDeviceVector<bst_float>& labels,
const HostDeviceVector<bst_float>& preds) {
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) {
PackedReduceResult result;
if (device < 0) {

4
src/metric/rank_metric.cc
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@@ -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
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@@ -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;