diff --git a/paddle/phi/kernels/gpu/cross_entropy_kernel.cu b/paddle/phi/kernels/gpu/cross_entropy_kernel.cu
index a223cd7c738347cb86265c21cb7ac3d7a357f5c7..5e5ddec9912cc18622c77f305112ff381c4e0e89 100644
--- a/paddle/phi/kernels/gpu/cross_entropy_kernel.cu
+++ b/paddle/phi/kernels/gpu/cross_entropy_kernel.cu
@@ -14,6 +14,8 @@ limitations under the License. */
 
 #include "paddle/phi/kernels/cross_entropy_kernel.h"
 
+#include "glog/logging.h"
+
 #ifdef __NVCC__
 #include "cub/cub.cuh"
 #endif
@@ -468,8 +470,8 @@ __global__ void VectorizedSoftmaxForward(T* loss,
   using VecT = kps::details::VectorType<T, VecSize>;
 
   // each block deal with one batch
-  logits += blockIdx.x * mid_dim;
-  softmax += blockIdx.x * mid_dim;
+  logits += static_cast<int64_t>(blockIdx.x) * static_cast<int64_t>(mid_dim);
+  softmax += static_cast<int64_t>(blockIdx.x) * static_cast<int64_t>(mid_dim);
 
   const int input_offset = ((uint64_t)logits) % ALIGN_BYTES / sizeof(T);
   const int output_offset = ((uint64_t)softmax) % ALIGN_BYTES / sizeof(T);
@@ -1165,6 +1167,8 @@ static void SoftmaxWithCrossEntropyHardLabel(const GPUContext& dev_ctx,
                                              int dim,
                                              int D,
                                              const int ignore_index) {
+  VLOG(7) << "rank=" << rank << ", axis = " << axis << ", N = " << N
+          << ", dim = " << dim << ", D = " << D;
   auto stream = dev_ctx.stream();
   constexpr int max_dim = 320;
   if (D == 1) {
@@ -1247,11 +1251,11 @@ void CrossEntropyWithSoftmaxCUDAKernel(const GPUContext& dev_ctx,
                                        int axis,
                                        DenseTensor* softmax,
                                        DenseTensor* loss) {
-  PADDLE_ENFORCE_EQ(
-      dev_ctx.GetPlace().GetType(),
-      AllocationType::GPU,
-      phi::errors::Unavailable("softmax_with_cross_entropy operator's "
-                               "CUDA kernel only runs on GPU device."));
+  VLOG(7) << "logits.shape={" << logits.dims() << "}, label.shape={"
+          << label.dims() << "}, soft_label=" << soft_label
+          << ", use_softmax=" << use_softmax
+          << ", numeric_stable_mode=" << numeric_stable_mode
+          << ", ignore_index=" << ignore_index << ", axis=" << axis;
 
   // do not with softmax op, and input is softmax
   if (!use_softmax) {