diff --git a/src/objective/regression_obj.cu b/src/objective/regression_obj.cu
index 9ae9b076e..bc6f14c4e 100644
--- a/src/objective/regression_obj.cu
+++ b/src/objective/regression_obj.cu
@@ -39,6 +39,7 @@
 #include <iostream>
 #include <cmath>
 #include <exception>
+#include "common/gpu_error_check.h"
 
 #if defined(XGBOOST_USE_CUDA) || defined(XGBOOST_USE_HIP)
 #include "../common/cuda_context.cuh"  // for CUDAContext
@@ -655,21 +656,44 @@ class MeanAbsoluteError : public ObjFunction {
     return std::max(static_cast<std::size_t>(1), info.labels.Shape(1));
   }
 
-  void GetGradient(HostDeviceVector<float> const& preds, const MetaInfo& info,
-                   std::int32_t /*iter*/, linalg::Matrix<GradientPair>* out_gpair) override {
-    CheckRegInputs(info, preds);
-    auto labels = info.labels.View(ctx_->Device());
+#include "common/gpu_error_check.h"
 
+void GetGradient(HostDeviceVector<float> const& preds, const MetaInfo& info,
+                 std::int32_t iter, linalg::Matrix<GradientPair>* out_gpair) override {
+  std::cerr << "Entering GetGradient, iteration: " << iter << std::endl;
+
+  try {
+    GPU_CHECK_LAST();  // Check for any previous GPU errors
+
+    std::cerr << "Checking regression inputs..." << std::endl;
+    CheckRegInputs(info, preds);
+
+    std::cerr << "Setting up labels..." << std::endl;
+    auto labels = info.labels.View(ctx_->Device());
+    std::cerr << "Labels shape: " << labels.Shape()[0] << "x" << labels.Shape()[1] << std::endl;
+
+    std::cerr << "Setting up output gradient pairs..." << std::endl;
     out_gpair->SetDevice(ctx_->Device());
     out_gpair->Reshape(info.num_row_, this->Targets(info));
     auto gpair = out_gpair->View(ctx_->Device());
+    std::cerr << "Gradient pairs shape: " << gpair.Shape()[0] << "x" << gpair.Shape()[1] << std::endl;
 
+    GPU_CHECK_LAST();  // Check for GPU errors after memory operations
+
+    std::cerr << "Setting up predictions..." << std::endl;
     preds.SetDevice(ctx_->Device());
     auto predt = linalg::MakeTensorView(ctx_, &preds, info.num_row_, this->Targets(info));
+    std::cerr << "Predictions shape: " << predt.Shape()[0] << "x" << predt.Shape()[1] << std::endl;
+
+    std::cerr << "Setting up weights..." << std::endl;
     info.weights_.SetDevice(ctx_->Device());
     common::OptionalWeights weight{ctx_->IsCUDA() ? info.weights_.ConstDeviceSpan()
                                                   : info.weights_.ConstHostSpan()};
+    std::cerr << "Weights size: " << weight.Size() << std::endl;
 
+    GPU_CHECK_LAST();  // Check for GPU errors before kernel launch
+
+    std::cerr << "Running ElementWiseKernel..." << std::endl;
     linalg::ElementWiseKernel(
         ctx_, labels, [=] XGBOOST_DEVICE(std::size_t i, std::size_t j) mutable {
           auto sign = [](auto x) {
@@ -680,8 +704,19 @@ class MeanAbsoluteError : public ObjFunction {
           auto grad = sign(predt(i, j) - y) * hess;
           gpair(i, j) = GradientPair{grad, hess};
         });
+
+    GPU_CHECK_LAST();  // Check for GPU errors after kernel execution
+
+    std::cerr << "ElementWiseKernel completed successfully" << std::endl;
+  } catch (const std::exception& e) {
+    std::cerr << "Exception in GetGradient: " << e.what() << std::endl;
+    GPU_CHECK_LAST();  // Check for GPU errors in case of exception
+    throw;
   }
 
+  std::cerr << "Exiting GetGradient" << std::endl;
+}
+
   void InitEstimation(MetaInfo const& info, linalg::Tensor<float, 1>* base_margin) const override {
     CheckInitInputs(info);
     base_margin->Reshape(this->Targets(info));