031d66ec27
* Configuration for init estimation. * Check whether the model needs configuration based on const attribute `ModelFitted` instead of a mutable state. * Add parameter `boost_from_average` to tell whether the user has specified base score. * Add tests.
91 lines
2.8 KiB
C++
91 lines
2.8 KiB
C++
/*!
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* Copyright 2021-2022 by XGBoost Contributors
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*/
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#ifndef XGBOOST_COMMON_LINALG_OP_H_
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#define XGBOOST_COMMON_LINALG_OP_H_
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#include <cstdint> // std::int32_t
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#include <type_traits>
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#include "common.h"
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#include "threading_utils.h"
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#include "xgboost/generic_parameters.h"
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#include "xgboost/linalg.h"
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namespace xgboost {
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namespace linalg {
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template <typename T, int32_t D, typename Fn>
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void ElementWiseTransformHost(linalg::TensorView<T, D> t, int32_t n_threads, Fn&& fn) {
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if (t.Contiguous()) {
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auto ptr = t.Values().data();
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common::ParallelFor(t.Size(), n_threads, [&](size_t i) { ptr[i] = fn(i, ptr[i]); });
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} else {
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common::ParallelFor(t.Size(), n_threads, [&](size_t i) {
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auto& v = detail::Apply(t, linalg::UnravelIndex(i, t.Shape()));
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v = fn(i, v);
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});
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}
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}
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template <typename T, int32_t D, typename Fn>
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void ElementWiseKernelHost(linalg::TensorView<T, D> t, int32_t n_threads, Fn&& fn) {
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static_assert(std::is_void<std::result_of_t<Fn(size_t, T&)>>::value,
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"For function with return, use transform instead.");
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if (t.Contiguous()) {
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auto ptr = t.Values().data();
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common::ParallelFor(t.Size(), n_threads, [&](size_t i) { fn(i, ptr[i]); });
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} else {
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common::ParallelFor(t.Size(), n_threads, [&](size_t i) {
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auto& v = detail::Apply(t, linalg::UnravelIndex(i, t.Shape()));
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fn(i, v);
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});
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}
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}
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#if !defined(XGBOOST_USE_CUDA)
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template <typename T, int32_t D, typename Fn>
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void ElementWiseKernelDevice(linalg::TensorView<T, D>, Fn&&, void* = nullptr) {
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common::AssertGPUSupport();
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}
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template <typename T, int32_t D, typename Fn>
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void ElementWiseTransformDevice(linalg::TensorView<T, D>, Fn&&, void* = nullptr) {
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common::AssertGPUSupport();
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}
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template <typename T, int32_t D, typename Fn>
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void ElementWiseKernel(GenericParameter const* ctx, linalg::TensorView<T, D> t, Fn&& fn) {
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if (!ctx->IsCPU()) {
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common::AssertGPUSupport();
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}
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ElementWiseKernelHost(t, ctx->Threads(), fn);
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}
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#endif // !defined(XGBOOST_USE_CUDA)
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template <typename T, std::int32_t kDim>
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auto cbegin(TensorView<T, kDim> v) { // NOLINT
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auto it = common::MakeIndexTransformIter([&](size_t i) -> std::remove_cv_t<T> const& {
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return linalg::detail::Apply(v, linalg::UnravelIndex(i, v.Shape()));
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});
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return it;
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}
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template <typename T, std::int32_t kDim>
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auto cend(TensorView<T, kDim> v) { // NOLINT
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return cbegin(v) + v.Size();
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}
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template <typename T, std::int32_t kDim>
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auto begin(TensorView<T, kDim> v) { // NOLINT
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auto it = common::MakeIndexTransformIter(
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[&](size_t i) -> T& { return linalg::detail::Apply(v, linalg::UnravelIndex(i, v.Shape())); });
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return it;
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}
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template <typename T, std::int32_t kDim>
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auto end(TensorView<T, kDim> v) { // NOLINT
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return begin(v) + v.Size();
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}
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} // namespace linalg
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} // namespace xgboost
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#endif // XGBOOST_COMMON_LINALG_OP_H_
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