82 lines
3.1 KiB
C++
82 lines
3.1 KiB
C++
/**
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* Copyright 2022-2024, XGBoost Contributors
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*
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* @brief Utilities for estimating initial score.
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*/
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#include "fit_stump.h"
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#include <cinttypes> // std::int32_t
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#include <cstddef> // std::size_t
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#include "../collective/aggregator.h"
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#include "../collective/communicator-inl.h"
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#include "../common/common.h" // AssertGPUSupport
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#include "../common/numeric.h" // cpu_impl::Reduce
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#include "../common/threading_utils.h" // ParallelFor
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#include "../common/transform_iterator.h" // MakeIndexTransformIter
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#include "xgboost/base.h" // bst_target_t, GradientPairPrecise
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#include "xgboost/context.h" // Context
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#include "xgboost/linalg.h" // TensorView, Tensor, Constant
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#include "xgboost/logging.h" // CHECK_EQ
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namespace xgboost::tree {
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namespace cpu_impl {
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void FitStump(Context const* ctx, MetaInfo const& info,
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linalg::TensorView<GradientPair const, 2> gpair,
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linalg::VectorView<float> out) {
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auto n_targets = out.Size();
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CHECK_EQ(n_targets, gpair.Shape(1));
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linalg::Tensor<GradientPairPrecise, 2> sum_tloc =
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linalg::Constant(ctx, GradientPairPrecise{}, ctx->Threads(), n_targets);
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auto h_sum_tloc = sum_tloc.HostView();
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// first dim for gpair is samples, second dim is target.
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// Reduce by column, parallel by samples
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common::ParallelFor(gpair.Shape(0), ctx->Threads(), [&](auto i) {
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for (bst_target_t t = 0; t < n_targets; ++t) {
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h_sum_tloc(omp_get_thread_num(), t) += GradientPairPrecise{gpair(i, t)};
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}
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});
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// Aggregate to the first row.
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auto h_sum = h_sum_tloc.Slice(0, linalg::All());
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for (std::int32_t i = 1; i < ctx->Threads(); ++i) {
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for (bst_target_t j = 0; j < n_targets; ++j) {
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h_sum(j) += h_sum_tloc(i, j);
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}
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}
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CHECK(h_sum.CContiguous());
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auto as_double = linalg::MakeTensorView(
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ctx, common::Span{reinterpret_cast<double*>(h_sum.Values().data()), h_sum.Size() * 2},
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h_sum.Size() * 2);
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auto rc = collective::GlobalSum(ctx, info, as_double);
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collective::SafeColl(rc);
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for (std::size_t i = 0; i < h_sum.Size(); ++i) {
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out(i) = static_cast<float>(CalcUnregularizedWeight(h_sum(i).GetGrad(), h_sum(i).GetHess()));
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}
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}
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} // namespace cpu_impl
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namespace cuda_impl {
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void FitStump(Context const* ctx, MetaInfo const& info,
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linalg::TensorView<GradientPair const, 2> gpair, linalg::VectorView<float> out);
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#if !defined(XGBOOST_USE_CUDA)
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inline void FitStump(Context const*, MetaInfo const&, linalg::TensorView<GradientPair const, 2>,
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linalg::VectorView<float>) {
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common::AssertGPUSupport();
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}
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#endif // !defined(XGBOOST_USE_CUDA)
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} // namespace cuda_impl
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void FitStump(Context const* ctx, MetaInfo const& info, linalg::Matrix<GradientPair> const& gpair,
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bst_target_t n_targets, linalg::Vector<float>* out) {
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out->SetDevice(ctx->Device());
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out->Reshape(n_targets);
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gpair.SetDevice(ctx->Device());
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auto gpair_t = gpair.View(ctx->Device());
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ctx->IsCUDA() ? cuda_impl::FitStump(ctx, info, gpair_t, out->View(ctx->Device()))
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: cpu_impl::FitStump(ctx, info, gpair_t, out->HostView());
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}
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} // namespace xgboost::tree
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