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Small refactor to categoricals (#7858)

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This commit is contained in:
Rory Mitchell
2022-05-05 17:47:02 +02:00
committed by GitHub
parent 14ef38b834
commit 7ef54e39ec
7 changed files with 110 additions and 150 deletions
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68
src/tree/gpu_hist/evaluator.cu
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@@ -30,46 +30,40 @@ void GPUHistEvaluator<GradientSumT>::Reset(common::HistogramCuts const &cuts,
// This condition avoids sort-based split function calls if the users want
// onehot-encoding-based splits.
// For some reason, any_of adds 1.5 minutes to compilation time for CUDA 11.x.
has_sort_ = thrust::any_of(thrust::cuda::par(alloc), beg, end, [=] XGBOOST_DEVICE(size_t i) {
auto idx = i - 1;
if (common::IsCat(ft, idx)) {
auto n_bins = ptrs[i] - ptrs[idx];
bool use_sort = !common::UseOneHot(n_bins, to_onehot);
return use_sort;
}
return false;
});
need_sort_histogram_ =
thrust::any_of(thrust::cuda::par(alloc), beg, end, [=] XGBOOST_DEVICE(size_t i) {
auto idx = i - 1;
if (common::IsCat(ft, idx)) {
auto n_bins = ptrs[i] - ptrs[idx];
bool use_sort = !common::UseOneHot(n_bins, to_onehot);
return use_sort;
}
return false;
});
if (has_sort_) {
auto bit_storage_size = common::CatBitField::ComputeStorageSize(cuts.MaxCategory() + 1);
CHECK_NE(bit_storage_size, 0);
// We need to allocate for all nodes since the updater can grow the tree layer by
// layer, all nodes in the same layer must be preserved until that layer is
// finished. We can allocate one layer at a time, but the best case is reducing the
// size of the bitset by about a half, at the cost of invoking CUDA malloc many more
// times than necessary.
split_cats_.resize(param.MaxNodes() * bit_storage_size);
h_split_cats_.resize(split_cats_.size());
dh::safe_cuda(
cudaMemsetAsync(split_cats_.data().get(), '\0', split_cats_.size() * sizeof(CatST)));
node_categorical_storage_size_ =
common::CatBitField::ComputeStorageSize(cuts.MaxCategory() + 1);
CHECK_NE(node_categorical_storage_size_, 0);
split_cats_.resize(node_categorical_storage_size_);
h_split_cats_.resize(node_categorical_storage_size_);
dh::safe_cuda(
cudaMemsetAsync(split_cats_.data().get(), '\0', split_cats_.size() * sizeof(CatST)));
cat_sorted_idx_.resize(cuts.cut_values_.Size() * 2); // evaluate 2 nodes at a time.
sort_input_.resize(cat_sorted_idx_.size());
cat_sorted_idx_.resize(cuts.cut_values_.Size() * 2); // evaluate 2 nodes at a time.
sort_input_.resize(cat_sorted_idx_.size());
/**
* cache feature index binary search result
*/
feature_idx_.resize(cat_sorted_idx_.size());
auto d_fidxes = dh::ToSpan(feature_idx_);
auto it = thrust::make_counting_iterator(0ul);
auto values = cuts.cut_values_.ConstDeviceSpan();
auto ptrs = cuts.cut_ptrs_.ConstDeviceSpan();
thrust::transform(thrust::cuda::par(alloc), it, it + feature_idx_.size(),
feature_idx_.begin(), [=] XGBOOST_DEVICE(size_t i) {
auto fidx = dh::SegmentId(ptrs, i);
return fidx;
});
}
/**
* cache feature index binary search result
*/
feature_idx_.resize(cat_sorted_idx_.size());
auto d_fidxes = dh::ToSpan(feature_idx_);
auto it = thrust::make_counting_iterator(0ul);
auto values = cuts.cut_values_.ConstDeviceSpan();
thrust::transform(thrust::cuda::par(alloc), it, it + feature_idx_.size(), feature_idx_.begin(),
[=] XGBOOST_DEVICE(size_t i) {
auto fidx = dh::SegmentId(ptrs, i);
return fidx;
});
}
}