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Copy data from Ellpack to GHist. (#8215)

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This commit is contained in:
Jiaming Yuan
2022-09-06 23:05:49 +08:00
committed by GitHub
parent 7ee10e3dbd
commit 441ffc017a
16 changed files with 466 additions and 112 deletions
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45
src/data/gradient_index.h
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@@ -69,7 +69,7 @@ class GHistIndexMatrix {
if (is_valid(elem)) {
bst_bin_t bin_idx{-1};
if (common::IsCat(ft, elem.column_idx)) {
bin_idx = cut.SearchCatBin(elem.value, elem.column_idx);
bin_idx = cut.SearchCatBin(elem.value, elem.column_idx, ptrs, values);
} else {
bin_idx = cut.SearchBin(elem.value, elem.column_idx, ptrs, values);
}
@@ -81,6 +81,17 @@ class GHistIndexMatrix {
});
}
// Gather hit_count from all threads
void GatherHitCount(int32_t n_threads, bst_bin_t n_bins_total) {
CHECK_EQ(hit_count.size(), n_bins_total);
common::ParallelFor(n_bins_total, n_threads, [&](bst_omp_uint idx) {
for (int32_t tid = 0; tid < n_threads; ++tid) {
hit_count[idx] += hit_count_tloc_[tid * n_bins_total + idx];
hit_count_tloc_[tid * n_bins_total + idx] = 0; // reset for next batch
}
});
}
template <typename Batch, typename IsValid>
void PushBatchImpl(int32_t n_threads, Batch const& batch, size_t rbegin, IsValid&& is_valid,
common::Span<FeatureType const> ft) {
@@ -95,33 +106,20 @@ class GHistIndexMatrix {
if (isDense_) {
index.SetBinOffset(cut.Ptrs());
}
uint32_t const* offsets = index.Offset();
if (isDense_) {
// Inside the lambda functions, bin_idx is the index for cut value across all
// features. By subtracting it with starting pointer of each feature, we can reduce
// it to smaller value and compress it to smaller types.
common::DispatchBinType(index.GetBinTypeSize(), [&](auto dtype) {
using T = decltype(dtype);
common::Span<T> index_data_span = {index.data<T>(), index.Size()};
SetIndexData(
index_data_span, rbegin, ft, batch_threads, batch, is_valid, n_bins_total,
[offsets](auto bin_idx, auto fidx) { return static_cast<T>(bin_idx - offsets[fidx]); });
SetIndexData(index_data_span, rbegin, ft, batch_threads, batch, is_valid, n_bins_total,
index.MakeCompressor<T>());
});
} else {
/* For sparse DMatrix we have to store index of feature for each bin
in index field to chose right offset. So offset is nullptr and index is
not reduced */
common::Span<uint32_t> index_data_span = {index.data<uint32_t>(), n_index};
// no compression
SetIndexData(index_data_span, rbegin, ft, batch_threads, batch, is_valid, n_bins_total,
[](auto idx, auto) { return idx; });
}
common::ParallelFor(n_bins_total, n_threads, [&](bst_omp_uint idx) {
for (int32_t tid = 0; tid < n_threads; ++tid) {
hit_count[idx] += hit_count_tloc_[tid * n_bins_total + idx];
hit_count_tloc_[tid * n_bins_total + idx] = 0; // reset for next batch
}
});
this->GatherHitCount(n_threads, n_bins_total);
}
public:
@@ -129,12 +127,12 @@ class GHistIndexMatrix {
std::vector<size_t> row_ptr;
/*! \brief The index data */
common::Index index;
/*! \brief hit count of each index */
/*! \brief hit count of each index, used for constructing the ColumnMatrix */
std::vector<size_t> hit_count;
/*! \brief The corresponding cuts */
common::HistogramCuts cut;
/*! \brief max_bin for each feature. */
size_t max_num_bins;
bst_bin_t max_num_bins;
/*! \brief base row index for current page (used by external memory) */
size_t base_rowid{0};
@@ -149,6 +147,13 @@ class GHistIndexMatrix {
* for push batch.
*/
GHistIndexMatrix(MetaInfo const& info, common::HistogramCuts&& cuts, bst_bin_t max_bin_per_feat);
/**
* \brief Constructor fro Iterative DMatrix where we might copy an existing ellpack page
* to host gradient index.
*/
GHistIndexMatrix(Context const* ctx, MetaInfo const& info, EllpackPage const& page,
BatchParam const& p);
/**
* \brief Constructor for external memory.
*/