Update CUDA treelearner according to changes introduced for linear trees (#3750)

* Update cuda_tree_learner.cpp

* Update cuda_tree_learner.h

* Update cuda.yml

.github/workflows/cuda.yml

@@ -47,6 +47,7 @@ jobs:
             export ROOT_DOCKER_FOLDER=/LightGBM
             cat > docker.env <<EOF
             TASK=cuda
+            METHOD=source
             COMPILER=gcc
             GITHUB_ACTIONS=true
             OS_NAME=linux

src/treelearner/cuda_tree_learner.cpp

@@ -534,8 +534,8 @@ void CUDATreeLearner::InitGPU(int num_gpu) {
   copyDenseFeature();
 }
 
-Tree* CUDATreeLearner::Train(const score_t* gradients, const score_t *hessians) {
-  Tree *ret = SerialTreeLearner::Train(gradients, hessians);
+Tree* CUDATreeLearner::Train(const score_t* gradients, const score_t *hessians, bool is_first_tree) {
+  Tree *ret = SerialTreeLearner::Train(gradients, hessians, is_first_tree);
   return ret;
 }
 

src/treelearner/cuda_tree_learner.h

@@ -45,7 +45,7 @@ class CUDATreeLearner: public SerialTreeLearner {
     ~CUDATreeLearner();
     void Init(const Dataset* train_data, bool is_constant_hessian) override;
     void ResetTrainingDataInner(const Dataset* train_data, bool is_constant_hessian, bool reset_multi_val_bin) override;
-    Tree* Train(const score_t* gradients, const score_t *hessians);
+    Tree* Train(const score_t* gradients, const score_t *hessians, bool is_first_tree);
     void SetBaggingData(const Dataset* subset, const data_size_t* used_indices, data_size_t num_data) override {
       SerialTreeLearner::SetBaggingData(subset, used_indices, num_data);
       if (subset == nullptr && used_indices != nullptr) {