From 1c666db34962694b57b8c48a9f4f1a8a858062c9 Mon Sep 17 00:00:00 2001
From: Hendrik Groove <hendrik.groove@dw.com>
Date: Mon, 21 Oct 2024 23:49:22 +0200
Subject: [PATCH] reset learner

---
 src/learner.cc | 51 +++++++++++++++++++-------------------------------
 1 file changed, 19 insertions(+), 32 deletions(-)

diff --git a/src/learner.cc b/src/learner.cc
index 02b3bc569..a56829aad 100644
--- a/src/learner.cc
+++ b/src/learner.cc
@@ -61,8 +61,6 @@
 #include "xgboost/predictor.h"            // for PredictionContainer, PredictionCacheEntry
 #include "xgboost/string_view.h"          // for operator<<, StringView
 #include "xgboost/task.h"                 // for ObjInfo
-#include <iostream>
-#include <exception>
 
 namespace {
 const char* kMaxDeltaStepDefaultValue = "0.7";
@@ -1264,44 +1262,33 @@ class LearnerImpl : public LearnerIO {
     return out_impl;
   }
 
-void UpdateOneIter(int iter, std::shared_ptr<DMatrix> train) override {
-  monitor_.Start("UpdateOneIter");
-  TrainingObserver::Instance().Update(iter);
-  
-  this->Configure();
-  
-  this->InitBaseScore(train.get());
+  void UpdateOneIter(int iter, std::shared_ptr<DMatrix> train) override {
+    monitor_.Start("UpdateOneIter");
+    TrainingObserver::Instance().Update(iter);
+    this->Configure();
+    this->InitBaseScore(train.get());
 
-  if (ctx_.seed_per_iteration) {
-    common::GlobalRandom().seed(ctx_.seed * kRandSeedMagic + iter);
-  }
+    if (ctx_.seed_per_iteration) {
+      common::GlobalRandom().seed(ctx_.seed * kRandSeedMagic + iter);
+    }
 
-  this->ValidateDMatrix(train.get(), true);
+    this->ValidateDMatrix(train.get(), true);
 
-  auto& predt = prediction_container_.Cache(train, ctx_.Device());
+    auto& predt = prediction_container_.Cache(train, ctx_.Device());
 
-  monitor_.Start("PredictRaw");
-  this->PredictRaw(train.get(), &predt, true, 0, 0);
-  TrainingObserver::Instance().Observe(predt.predictions, "Predictions");
-  monitor_.Stop("PredictRaw");
+    monitor_.Start("PredictRaw");
+    this->PredictRaw(train.get(), &predt, true, 0, 0);
+    TrainingObserver::Instance().Observe(predt.predictions, "Predictions");
+    monitor_.Stop("PredictRaw");
 
-  monitor_.Start("GetGradient");
-  try {
+    monitor_.Start("GetGradient");
     GetGradient(predt.predictions, train->Info(), iter, &gpair_);
-  } catch (const std::exception& e) {
-    throw;
-  }
-  monitor_.Stop("GetGradient");
-  TrainingObserver::Instance().Observe(*gpair_.Data(), "Gradients");
+    monitor_.Stop("GetGradient");
+    TrainingObserver::Instance().Observe(*gpair_.Data(), "Gradients");
 
-  try {
     gbm_->DoBoost(train.get(), &gpair_, &predt, obj_.get());
-  } catch (const std::exception& e) {
-    throw;
+    monitor_.Stop("UpdateOneIter");
   }
-  
-  monitor_.Stop("UpdateOneIter");
-}
 
   void BoostOneIter(int iter, std::shared_ptr<DMatrix> train,
                     linalg::Matrix<GradientPair>* in_gpair) override {
@@ -1503,4 +1490,4 @@ Learner* Learner::Create(
     const std::vector<std::shared_ptr<DMatrix> >& cache_data) {
   return new LearnerImpl(cache_data);
 }
-}  // namespace xgboost
+}  // namespace xgboost
\ No newline at end of file