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/**
* Copyright 2023, XGBoost contributors
*/
#include <xgboost/context.h> // for Context
#include <xgboost/learner.h> // for Learner
#include <xgboost/string_view.h> // for StringView
#include <limits> // for numeric_limits
#include <memory> // for shared_ptr
#include <string> // for string
#include <thread> // for thread
#include "../../../src/data/adapter.h" // for ArrayAdapter
#include "../../../src/data/device_adapter.cuh" // for CupyAdapter
#include "../../../src/data/proxy_dmatrix.h" // for DMatrixProxy
#include "../helpers.h" // for RandomDataGenerator
namespace xgboost {
void TestInplaceFallback(Context const* ctx) {
// prepare data
bst_idx_t n_samples{1024};
bst_feature_t n_features{32};
HostDeviceVector<float> X_storage;
// use a different device than the learner
auto data_ordinal = ctx->IsCPU() ? DeviceOrd::CUDA(0) : DeviceOrd::CPU();
auto X = RandomDataGenerator{n_samples, n_features, 0.0}
.Device(data_ordinal)
.GenerateArrayInterface(&X_storage);
HostDeviceVector<float> y_storage;
auto y = RandomDataGenerator{n_samples, 1u, 0.0}.GenerateArrayInterface(&y_storage);
std::shared_ptr<DMatrix> Xy;
if (data_ordinal.IsCPU()) {
auto X_adapter = data::ArrayAdapter{StringView{X}};
Xy.reset(DMatrix::Create(&X_adapter, std::numeric_limits<float>::quiet_NaN(), ctx->Threads()));
} else {
auto X_adapter = data::CupyAdapter{StringView{X}};
Xy.reset(DMatrix::Create(&X_adapter, std::numeric_limits<float>::quiet_NaN(), ctx->Threads()));
}
Xy->SetInfo("label", y);
// learner is configured to the device specified by ctx
std::unique_ptr<Learner> learner{Learner::Create({Xy})};
learner->SetParam("device", ctx->DeviceName());
for (std::int32_t i = 0; i < 3; ++i) {
learner->UpdateOneIter(i, Xy);
}
std::shared_ptr<DMatrix> p_m{new data::DMatrixProxy};
auto proxy = std::dynamic_pointer_cast<data::DMatrixProxy>(p_m);
if (data_ordinal.IsCPU()) {
proxy->SetArrayData(StringView{X});
} else {
proxy->SetCUDAArray(X.c_str());
}
HostDeviceVector<float>* out_predt{nullptr};
ConsoleLogger::Configure(Args{{"verbosity", "1"}});
std::string output;
learner->InplacePredict(p_m, PredictionType::kValue, std::numeric_limits<float>::quiet_NaN(),
&out_predt, 0, 0);
// test when the contexts match
Context new_ctx = *proxy->Ctx();
ASSERT_NE(new_ctx.Ordinal(), ctx->Ordinal());
learner->SetParam("device", new_ctx.DeviceName());
HostDeviceVector<float>* out_predt_1{nullptr};
// no warning is raised
::testing::internal::CaptureStderr();
learner->InplacePredict(p_m, PredictionType::kValue, std::numeric_limits<float>::quiet_NaN(),
&out_predt_1, 0, 0);
output = testing::internal::GetCapturedStderr();
ASSERT_TRUE(output.empty());
ASSERT_EQ(out_predt->ConstHostVector(), out_predt_1->ConstHostVector());
}
TEST(GBTree, InplacePredictFallback) {
auto ctx = MakeCUDACtx(0);
TestInplaceFallback(&ctx);
}
} // namespace xgboost
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