Fix CPP lint. (#8807)
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@@ -19,7 +19,7 @@ const MetaInfo &SparsePageDMatrix::Info() const { return info_; }
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namespace detail {
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// Use device dispatch
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std::size_t NSamplesDevice(DMatrixProxy *)
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std::size_t NSamplesDevice(DMatrixProxy *) // NOLINT
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#if defined(XGBOOST_USE_CUDA)
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; // NOLINT
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#else
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@@ -28,7 +28,7 @@ std::size_t NSamplesDevice(DMatrixProxy *)
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return 0;
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}
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#endif
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std::size_t NFeaturesDevice(DMatrixProxy *)
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std::size_t NFeaturesDevice(DMatrixProxy *) // NOLINT
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#if defined(XGBOOST_USE_CUDA)
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; // NOLINT
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#else
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@@ -5,7 +5,7 @@
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#include <algorithm>
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#include <cassert>
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#include <cub/cub.cuh>
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#include <cub/cub.cuh> // NOLINT
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#include <limits>
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#include <memory>
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#include <tuple>
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@@ -6,6 +6,7 @@
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#define XGBOOST_METRIC_METRIC_COMMON_H_
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#include <limits>
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#include <memory> // shared_ptr
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#include <string>
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#include "../common/common.h"
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@@ -3,8 +3,8 @@
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*/
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#include <thrust/sort.h>
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#include <cstdint> // std::int32_t
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#include <cub/cub.cuh>
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#include <cstdint> // std::int32_t
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#include <cub/cub.cuh> // NOLINT
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#include "../common/cuda_context.cuh" // CUDAContext
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#include "../common/device_helpers.cuh"
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@@ -3,10 +3,11 @@
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*/
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#include "cpu_treeshap.h"
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#include <cinttypes> // std::uint32_t
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#include <algorithm> // copy
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#include <cinttypes> // std::uint32_t
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#include "predict_fn.h" // GetNextNode
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#include "xgboost/base.h" // bst_node_t
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#include "predict_fn.h" // GetNextNode
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#include "xgboost/base.h" // bst_node_t
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#include "xgboost/logging.h"
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#include "xgboost/tree_model.h" // RegTree
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@@ -1,6 +1,10 @@
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#ifndef XGBOOST_PREDICTOR_CPU_TREESHAP_H_
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#define XGBOOST_PREDICTOR_CPU_TREESHAP_H_
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/**
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* Copyright by XGBoost Contributors 2017-2022
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*/
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#include <vector> // vector
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#include "xgboost/tree_model.h" // RegTree
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namespace xgboost {
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@@ -15,3 +19,4 @@ void CalculateContributions(RegTree const &tree, const RegTree::FVec &feat,
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std::vector<float> *mean_values, bst_float *out_contribs, int condition,
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unsigned condition_feature);
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} // namespace xgboost
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#endif // XGBOOST_PREDICTOR_CPU_TREESHAP_H_
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@@ -359,8 +359,8 @@ void GPUHistEvaluator::LaunchEvaluateSplits(
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// One block for each feature
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uint32_t constexpr kBlockThreads = 32;
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dh::LaunchKernel{static_cast<uint32_t>(combined_num_features), kBlockThreads,
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0}(
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dh::LaunchKernel {static_cast<uint32_t>(combined_num_features), kBlockThreads,
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0}(
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EvaluateSplitsKernel<kBlockThreads>, max_active_features, d_inputs,
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shared_inputs,
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this->SortedIdx(d_inputs.size(), shared_inputs.feature_values.size()),
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@@ -299,7 +299,7 @@ void BuildGradientHistogram(CUDAContext const* ctx, EllpackDeviceAccessor const&
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min(grid_size,
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unsigned(common::DivRoundUp(items_per_group, kMinItemsPerBlock)));
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dh::LaunchKernel{dim3(grid_size, num_groups), static_cast<uint32_t>(kBlockThreads), smem_size,
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dh::LaunchKernel {dim3(grid_size, num_groups), static_cast<uint32_t>(kBlockThreads), smem_size,
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ctx->Stream()} (kernel, matrix, feature_groups, d_ridx, histogram.data(),
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gpair.data(), rounding);
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};
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