Fix.

dmlc · Jul 28, 2022 · be31d98 · be31d98
1 parent 1e4d161
commit be31d98
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Showing 4 changed files with 30 additions and 23 deletions.
diff --git a/include/xgboost/linalg.h b/include/xgboost/linalg.h
@@ -679,7 +679,7 @@ class Tensor {
     }
     if (device >= 0) {
       data_.SetDevice(device);
-      data_.DevicePointer();  // Pull to device;
+      data_.ConstDevicePointer();  // Pull to device;
     }
     CHECK_EQ(data_.Size(), detail::CalcSize(shape_));
   }

diff --git a/src/learner.cc b/src/learner.cc
@@ -416,22 +416,11 @@ class LearnerConfiguration : public Learner {
 
     this->ConfigureTargets();
 
-    // Before 1.0.0, we save `base_score` into binary as a transformed value by objective.
-    // After 1.0.0 we save the value provided by user and keep it immutable instead.  To
-    // keep the stability, we initialize it in binary LoadModel instead of configuration.
-    // Under what condition should we omit the transformation:
-    //
-    // - base_score is loaded from old binary model.
-    //
-    // What are the other possible conditions:
-    //
-    // - model loaded from new binary or JSON.
-    // - model is created from scratch.
-    // - model is configured second time due to change of parameter
-    this->ConfigureLearnerParam(p_fmat);
-
+    learner_model_param_.task = obj_->Task();  // required by gbm configuration.
     this->ConfigureGBM(old_tparam, args);
     ctx_.ConfigureGpuId(this->gbm_->UseGPU());
+    this->ConfigureLearnerParam(p_fmat);
+
     this->ConfigureMetrics(args);
 
     this->need_configuration_ = false;
@@ -447,6 +436,18 @@ class LearnerConfiguration : public Learner {
    * \brief Calculate the `base_score` based on input data.
    */
   void ConfigureLearnerParam(DMatrix const* p_fmat) {
+    // Before 1.0.0, we save `base_score` into binary as a transformed value by objective.
+    // After 1.0.0 we save the value provided by user and keep it immutable instead.  To
+    // keep the stability, we initialize it in binary LoadModel instead of configuration.
+    // Under what condition should we omit the transformation:
+    //
+    // - base_score is loaded from old binary model.
+    //
+    // What are the other possible conditions:
+    //
+    // - model loaded from new binary or JSON.
+    // - model is created from scratch.
+    // - model is configured second time due to change of parameter
     CHECK(obj_);
     float world = rabit::GetWorldSize();
     if (base_score_.Size() != 0) {

diff --git a/tests/cpp/helpers.h b/tests/cpp/helpers.h
@@ -455,9 +455,11 @@ RMMAllocatorPtr SetUpRMMResourceForCppTests(int argc, char** argv);
 /*
  * \brief Make learner model param
  */
-inline LearnerModelParam MakeMP(bst_feature_t n_features, float base_score, uint32_t n_groups) {
+inline LearnerModelParam MakeMP(bst_feature_t n_features, float base_score, uint32_t n_groups,
+                                int32_t device = Context::kCpuId) {
   size_t shape[1]{1};
-  LearnerModelParam mparam(n_features, linalg::Tensor<float, 1>{{base_score}, shape}, n_groups);
+  LearnerModelParam mparam(n_features, linalg::Tensor<float, 1>{{base_score}, shape, device},
+                           n_groups);
   return mparam;
 }
 

diff --git a/tests/cpp/predictor/test_gpu_predictor.cu b/tests/cpp/predictor/test_gpu_predictor.cu
@@ -35,8 +35,9 @@ TEST(GPUPredictor, Basic) {
     int n_row = i, n_col = i;
     auto dmat = RandomDataGenerator(n_row, n_col, 0).GenerateDMatrix();
 
-    LearnerModelParam mparam{MakeMP(n_col, .5, 1)};
-    GenericParameter ctx;
+    Context ctx;
+    ctx.gpu_id = 0;
+    LearnerModelParam mparam{MakeMP(n_col, .5, 1, ctx.gpu_id)};
     gbm::GBTreeModel model = CreateTestModel(&mparam, &ctx);
 
     // Test predict batch
@@ -90,9 +91,10 @@ TEST(GPUPredictor, ExternalMemoryTest) {
   gpu_predictor->Configure({});
 
   const int n_classes = 3;
-  LearnerModelParam mparam{MakeMP(5, .5, n_classes)};
-
   Context ctx;
+  ctx.gpu_id = 0;
+  LearnerModelParam mparam{MakeMP(5, .5, n_classes, ctx.gpu_id)};
+
   gbm::GBTreeModel model = CreateTestModel(&mparam, &ctx, n_classes);
   std::vector<std::unique_ptr<DMatrix>> dmats;
 
@@ -163,8 +165,9 @@ TEST(GpuPredictor, LesserFeatures) {
 TEST(GPUPredictor, ShapStump) {
   cudaSetDevice(0);
 
-  LearnerModelParam mparam{MakeMP(1, .5, 1)};
   Context ctx;
+  ctx.gpu_id = 0;
+  LearnerModelParam mparam{MakeMP(1, .5, 1, ctx.gpu_id)};
   gbm::GBTreeModel model(&mparam, &ctx);
 
   std::vector<std::unique_ptr<RegTree>> trees;
@@ -189,8 +192,9 @@ TEST(GPUPredictor, ShapStump) {
 }
 
 TEST(GPUPredictor, Shap) {
-  LearnerModelParam mparam{MakeMP(1, .5, 1)};
   Context ctx;
+  ctx.gpu_id = 0;
+  LearnerModelParam mparam{MakeMP(1, .5, 1, ctx.gpu_id)};
   gbm::GBTreeModel model(&mparam, &ctx);
 
   std::vector<std::unique_ptr<RegTree>> trees;