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Reorder if-else statements to allow using of cpu branches for sycl-devices (#9682)

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This commit is contained in:
Dmitry Razdoburdin
2023-10-18 04:55:33 +02:00
committed by GitHub
parent 4c0e4422d0
commit ea9f09716b
14 changed files with 99 additions and 98 deletions
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52
src/metric/elementwise_metric.cu
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@@ -46,7 +46,26 @@ template <typename Fn>
PackedReduceResult Reduce(Context const* ctx, MetaInfo const& info, Fn&& loss) {
PackedReduceResult result;
auto labels = info.labels.View(ctx->Device());
if (ctx->IsCPU()) {
if (ctx->IsCUDA()) {
#if defined(XGBOOST_USE_CUDA)
dh::XGBCachingDeviceAllocator<char> alloc;
thrust::counting_iterator<size_t> begin(0);
thrust::counting_iterator<size_t> end = begin + labels.Size();
result = thrust::transform_reduce(
thrust::cuda::par(alloc), begin, end,
[=] XGBOOST_DEVICE(size_t i) {
auto idx = linalg::UnravelIndex(i, labels.Shape());
auto sample_id = std::get<0>(idx);
auto target_id = std::get<1>(idx);
auto res = loss(i, sample_id, target_id);
float v{std::get<0>(res)}, wt{std::get<1>(res)};
return PackedReduceResult{v, wt};
},
PackedReduceResult{}, thrust::plus<PackedReduceResult>());
#else
common::AssertGPUSupport();
#endif // defined(XGBOOST_USE_CUDA)
} else {
auto n_threads = ctx->Threads();
std::vector<double> score_tloc(n_threads, 0.0);
std::vector<double> weight_tloc(n_threads, 0.0);
@@ -69,25 +88,6 @@ PackedReduceResult Reduce(Context const* ctx, MetaInfo const& info, Fn&& loss) {
double residue_sum = std::accumulate(score_tloc.cbegin(), score_tloc.cend(), 0.0);
double weights_sum = std::accumulate(weight_tloc.cbegin(), weight_tloc.cend(), 0.0);
result = PackedReduceResult{residue_sum, weights_sum};
} else {
#if defined(XGBOOST_USE_CUDA)
dh::XGBCachingDeviceAllocator<char> alloc;
thrust::counting_iterator<size_t> begin(0);
thrust::counting_iterator<size_t> end = begin + labels.Size();
result = thrust::transform_reduce(
thrust::cuda::par(alloc), begin, end,
[=] XGBOOST_DEVICE(size_t i) {
auto idx = linalg::UnravelIndex(i, labels.Shape());
auto sample_id = std::get<0>(idx);
auto target_id = std::get<1>(idx);
auto res = loss(i, sample_id, target_id);
float v{std::get<0>(res)}, wt{std::get<1>(res)};
return PackedReduceResult{v, wt};
},
PackedReduceResult{}, thrust::plus<PackedReduceResult>());
#else
common::AssertGPUSupport();
#endif // defined(XGBOOST_USE_CUDA)
}
return result;
}
@@ -185,10 +185,10 @@ class PseudoErrorLoss : public MetricNoCache {
CHECK_EQ(info.labels.Shape(0), info.num_row_);
auto labels = info.labels.View(ctx_->Device());
preds.SetDevice(ctx_->Device());
auto predts = ctx_->IsCPU() ? preds.ConstHostSpan() : preds.ConstDeviceSpan();
auto predts = ctx_->IsCUDA() ? preds.ConstDeviceSpan() : preds.ConstHostSpan();
info.weights_.SetDevice(ctx_->Device());
common::OptionalWeights weights(ctx_->IsCPU() ? info.weights_.ConstHostSpan()
: info.weights_.ConstDeviceSpan());
common::OptionalWeights weights(ctx_->IsCUDA() ? info.weights_.ConstDeviceSpan()
: info.weights_.ConstHostSpan());
float slope = this->param_.huber_slope;
CHECK_NE(slope, 0.0) << "slope for pseudo huber cannot be 0.";
PackedReduceResult result =
@@ -351,10 +351,10 @@ struct EvalEWiseBase : public MetricNoCache {
}
auto labels = info.labels.View(ctx_->Device());
info.weights_.SetDevice(ctx_->Device());
common::OptionalWeights weights(ctx_->IsCPU() ? info.weights_.ConstHostSpan()
: info.weights_.ConstDeviceSpan());
common::OptionalWeights weights(ctx_->IsCUDA() ? info.weights_.ConstDeviceSpan()
: info.weights_.ConstHostSpan());
preds.SetDevice(ctx_->Device());
auto predts = ctx_->IsCPU() ? preds.ConstHostSpan() : preds.ConstDeviceSpan();
auto predts = ctx_->IsCUDA() ? preds.ConstDeviceSpan() : preds.ConstHostSpan();
auto d_policy = policy_;
auto result =