Revert OMP guard. (#6987)
The guard protects the global variable from being changed by XGBoost. But this leads to a bug that the `n_threads` parameter is no longer used after the first iteration. This is due to the fact that `omp_set_num_threads` is only called once in `Learner::Configure` at the beginning of the training process. The guard is still useful for `gpu_id`, since this is called all the times in our codebase doesn't matter which iteration we are currently running.
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@ -163,7 +163,6 @@ inline float GetMissing(Json const &config) {
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// Safe guard some global variables from being changed by XGBoost.
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class XGBoostAPIGuard {
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int32_t n_threads_ {omp_get_max_threads()};
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int32_t device_id_ {0};
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#if defined(XGBOOST_USE_CUDA)
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@ -179,7 +178,6 @@ class XGBoostAPIGuard {
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SetGPUAttribute();
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}
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~XGBoostAPIGuard() {
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omp_set_num_threads(n_threads_);
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RestoreGPUAttribute();
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}
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};
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@ -278,37 +278,4 @@ TEST(CAPI, XGBGlobalConfig) {
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ASSERT_EQ(err.find("verbosity"), std::string::npos);
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}
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}
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TEST(CAPI, GlobalVariables) {
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size_t n_threads = omp_get_max_threads();
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size_t constexpr kRows = 10;
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bst_feature_t constexpr kCols = 2;
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DMatrixHandle handle;
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std::vector<float> data(kCols * kRows, 1.5);
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ASSERT_EQ(XGDMatrixCreateFromMat_omp(data.data(), kRows, kCols,
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std::numeric_limits<float>::quiet_NaN(),
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&handle, 0),
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0);
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std::vector<float> labels(kRows, 2.0f);
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ASSERT_EQ(XGDMatrixSetFloatInfo(handle, "label", labels.data(), labels.size()), 0);
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DMatrixHandle m_handles[1];
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m_handles[0] = handle;
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BoosterHandle booster;
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ASSERT_EQ(XGBoosterCreate(m_handles, 1, &booster), 0);
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ASSERT_EQ(XGBoosterSetParam(booster, "nthread", "16"), 0);
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omp_set_num_threads(1);
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ASSERT_EQ(XGBoosterUpdateOneIter(booster, 0, handle), 0);
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ASSERT_EQ(omp_get_max_threads(), 1);
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omp_set_num_threads(n_threads);
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XGDMatrixFree(handle);
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XGBoosterFree(booster);
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}
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} // namespace xgboost
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