diff --git a/src/learner.cc b/src/learner.cc
index 78297404b..7df450811 100644
--- a/src/learner.cc
+++ b/src/learner.cc
@@ -860,10 +860,21 @@ class LearnerConfiguration : public Learner {
   }
 
   void InitEstimation(MetaInfo const& info, linalg::Tensor<float, 1>* base_score) {
+#ifndef XGBOOST_USE_HIP
     base_score->Reshape(1);
     collective::ApplyWithLabels(info, base_score->Data()->HostPointer(),
                                 sizeof(bst_float) * base_score->Size(),
                                 [&] { UsePtr(obj_)->InitEstimation(info, base_score); });
+#else
+    if (info.IsVerticalFederated()) {
+        base_score->Reshape(1);
+        collective::ApplyWithLabels(info, base_score->Data()->HostPointer(),
+                sizeof(bst_float) * base_score->Size(),
+                [&] { UsePtr(obj_)->InitEstimation(info, base_score); });
+    } else {
+      UsePtr(obj_)->InitEstimation(info, base_score);
+    }
+#endif
   }
 };
 
@@ -1475,10 +1486,21 @@ class LearnerImpl : public LearnerIO {
  private:
   void GetGradient(HostDeviceVector<bst_float> const& preds, MetaInfo const& info, int iteration,
                    HostDeviceVector<GradientPair>* out_gpair) {
+#ifndef XGBOOST_USE_HIP
     out_gpair->Resize(preds.Size());
     collective::ApplyWithLabels(info, out_gpair->HostPointer(),
                                 out_gpair->Size() * sizeof(GradientPair),
                                 [&] { obj_->GetGradient(preds, info, iteration, out_gpair); });
+#else
+    if (info.IsVerticalFederated()) {
+      out_gpair->Resize(preds.Size());
+      collective::ApplyWithLabels(info, out_gpair->HostPointer(),
+                                out_gpair->Size() * sizeof(GradientPair),
+                                [&] { obj_->GetGradient(preds, info, iteration, out_gpair); });
+    } else {
+      obj_->GetGradient(preds, info, iteration, out_gpair);
+    }
+#endif
   }
 
   /*! \brief random number transformation seed. */