refine the slice Op to improve the performance of xlnet for fp16 training (#24967)

paddle/fluid/operators/slice_op.cu

@@ -13,12 +13,12 @@ See the License for the specific language governing permissions and
 limitations under the License. */
 
 #include <thrust/device_vector.h>
+#include "paddle/fluid/framework/tensor_util.h"
 #include "paddle/fluid/operators/math/math_function.h"
 #include "paddle/fluid/operators/slice_op.h"
 #include "paddle/fluid/platform/cuda_device_function.h"
 #include "paddle/fluid/platform/cuda_primitives.h"
 #include "paddle/fluid/platform/float16.h"
-
 namespace paddle {
 namespace operators {
 
@@ -94,17 +94,22 @@ class SliceGradKernel<paddle::platform::CUDADeviceContext,
     dim3 blocks((numel - 1) / PADDLE_CUDA_NUM_THREADS + 1);
     dim3 threads(PADDLE_CUDA_NUM_THREADS);
     auto stream = ctx.cuda_device_context().stream();
-
-    auto out_shape = framework::vectorize<int64_t>(out_dims);
-    thrust::device_vector<int64_t> out_dims_vec(out_shape.begin(),
-                                                out_shape.end());
-    auto in_shape = framework::vectorize<int64_t>(in_dims);
-    thrust::device_vector<int64_t> in_dims_vec(in_shape.begin(),
-                                               in_shape.end());
-    thrust::device_vector<int64_t> offsets_vec(offsets.begin(), offsets.end());
-    const int64_t* out_dims_ptr = thrust::raw_pointer_cast(out_dims_vec.data());
-    const int64_t* in_dims_ptr = thrust::raw_pointer_cast(in_dims_vec.data());
-    const int64_t* offsets_ptr = thrust::raw_pointer_cast(offsets_vec.data());
+    const std::vector<int64_t> out_shape =
+        framework::vectorize<int64_t>(out_dims);
+    const std::vector<int64_t> in_shape =
+        framework::vectorize<int64_t>(in_dims);
+
+    framework::Tensor out_dims_tensor;
+    framework::Tensor in_dims_tensor;
+    framework::Tensor offsets_tensor;
+    framework::TensorFromVector(out_shape, ctx.device_context(),
+                                &out_dims_tensor);
+    framework::TensorFromVector(in_shape, ctx.device_context(),
+                                &in_dims_tensor);
+    framework::TensorFromVector(offsets, ctx.device_context(), &offsets_tensor);
+    const int64_t* out_dims_ptr = out_dims_tensor.data<int64_t>();
+    const int64_t* in_dims_ptr = in_dims_tensor.data<int64_t>();
+    const int64_t* offsets_ptr = offsets_tensor.data<int64_t>();
 
     switch (rank) {
       case 1: