Calculate base_score based on input labels for mae. (#8107)

Fit an intercept as base score for abs loss.
This commit is contained in:
Jiaming Yuan
2022-09-20 20:53:54 +08:00
committed by GitHub
parent 4f42aa5f12
commit fffb1fca52
42 changed files with 999 additions and 343 deletions

47
src/common/stats.cu Normal file
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/*!
* Copyright 2022 by XGBoost Contributors
*/
#include <thrust/iterator/counting_iterator.h> // thrust::make_counting_iterator
#include "common.h" // common::OptionalWeights
#include "device_helpers.cuh" // dh::MakeTransformIterator, tcbegin, tcend
#include "stats.cuh" // common::SegmentedQuantile, common::SegmentedWeightedQuantile
#include "xgboost/generic_parameters.h" // Context
#include "xgboost/host_device_vector.h" // HostDeviceVector
#include "xgboost/linalg.h" // linalg::TensorView, UnravelIndex, Apply
namespace xgboost {
namespace common {
namespace cuda {
float Median(Context const* ctx, linalg::TensorView<float const, 2> t,
common::OptionalWeights weights) {
HostDeviceVector<size_t> segments{0, t.Size()};
segments.SetDevice(ctx->gpu_id);
auto d_segments = segments.ConstDeviceSpan();
auto val_it = dh::MakeTransformIterator<float>(
thrust::make_counting_iterator(0ul), [=] XGBOOST_DEVICE(size_t i) {
return linalg::detail::Apply(t, linalg::UnravelIndex(i, t.Shape()));
});
HostDeviceVector<float> quantile{0};
quantile.SetDevice(ctx->gpu_id);
if (weights.Empty()) {
common::SegmentedQuantile(ctx, 0.5, dh::tcbegin(d_segments), dh::tcend(d_segments), val_it,
val_it + t.Size(), &quantile);
} else {
CHECK_NE(t.Shape(1), 0);
auto w_it = dh::MakeTransformIterator<float>(thrust::make_counting_iterator(0ul),
[=] XGBOOST_DEVICE(size_t i) {
auto sample_idx = i / t.Shape(1);
return weights[sample_idx];
});
common::SegmentedWeightedQuantile(ctx, 0.5, dh::tcbegin(d_segments), dh::tcend(d_segments),
val_it, val_it + t.Size(), w_it, w_it + t.Size(), &quantile);
}
CHECK_EQ(quantile.Size(), 1);
return quantile.HostVector().front();
}
} // namespace cuda
} // namespace common
} // namespace xgboost