282b1729da
* Specify the number of threads for parallel sort. - Pass context object into argsort. - Replace macros with inline functions.
41 lines
1.4 KiB
C++
41 lines
1.4 KiB
C++
/*!
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* Copyright 2020 by XGBoost Contributors
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* \file random.cc
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*/
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#include "random.h"
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namespace xgboost {
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namespace common {
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std::shared_ptr<HostDeviceVector<bst_feature_t>> ColumnSampler::ColSample(
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std::shared_ptr<HostDeviceVector<bst_feature_t>> p_features, float colsample) {
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if (colsample == 1.0f) {
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return p_features;
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}
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const auto &features = p_features->HostVector();
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CHECK_GT(features.size(), 0);
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int n = std::max(1, static_cast<int>(colsample * features.size()));
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auto p_new_features = std::make_shared<HostDeviceVector<bst_feature_t>>();
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auto &new_features = *p_new_features;
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if (feature_weights_.size() != 0) {
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auto const &h_features = p_features->HostVector();
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std::vector<float> weights(h_features.size());
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for (size_t i = 0; i < h_features.size(); ++i) {
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weights[i] = feature_weights_[h_features[i]];
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}
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CHECK(ctx_);
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new_features.HostVector() =
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WeightedSamplingWithoutReplacement(ctx_, p_features->HostVector(), weights, n);
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} else {
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new_features.Resize(features.size());
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std::copy(features.begin(), features.end(), new_features.HostVector().begin());
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std::shuffle(new_features.HostVector().begin(), new_features.HostVector().end(), rng_);
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new_features.Resize(n);
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}
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std::sort(new_features.HostVector().begin(), new_features.HostVector().end());
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return p_new_features;
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}
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} // namespace common
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} // namespace xgboost
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