diff --git a/paddle/operators/gemm_conv2d_op.h b/paddle/operators/gemm_conv2d_op.h
index 72de0a5cf3e640625d39edf45af623f131699ad1..f9215b46fcd9f091f88865df721481698ac0c8e7 100644
--- a/paddle/operators/gemm_conv2d_op.h
+++ b/paddle/operators/gemm_conv2d_op.h
@@ -75,8 +75,6 @@ class GemmConv2DKernel : public framework::OpKernel {
     framework::DDim output_matrix_shape = {output_channels,
                                            output_height * output_width};
 
-    auto device_context = context.device_context();
-
     // convolution operator: im2col + gemm
     int in_step = input_channels / groups;
     int out_step = output_channels / groups;
@@ -87,13 +85,13 @@ class GemmConv2DKernel : public framework::OpKernel {
         // im2col
         Tensor in_slice = in_batch.Slice<T>(g * in_step, (g + 1) * in_step);
         im2col(in_slice, col, strides[0], strides[1], paddings[0], paddings[1],
-               device_context);
+               context.device_context());
 
         // gemm
         Tensor out_slice = out_batch.Slice<T>(g * out_step, (g + 1) * out_step);
         Tensor filter_slice = filter.Slice<T>(g * out_step, (g + 1) * out_step);
-        math::matmul<Place, T>(device_context, filter_slice, false, col_matrix,
-                               false, T(1.0), &out_slice, T(0.0));
+        math::matmul<Place, T>(context.device_context(), filter_slice, false,
+                               col_matrix, false, T(1.0), &out_slice, T(0.0));
       }
     }
   }
@@ -159,8 +157,6 @@ class GemmConvGrad2DKernel : public framework::OpKernel {
                                            filter.numel() / filter.dims()[0]};
     filter.Resize(filter_matrix_shape);
 
-    auto device_context = context.device_context();
-
     // convolution backward input operator:  gemm + col2im
     // convolution backward weight operator: im2col + gemm
     int in_step = input_channels / groups;
@@ -182,7 +178,7 @@ class GemmConvGrad2DKernel : public framework::OpKernel {
               out_grad_batch.Slice<T>(g * out_step, (g + 1) * out_step);
           Tensor filter_slice =
               filter.Slice<T>(g * out_step, (g + 1) * out_step);
-          math::matmul<Place, T>(device_context, filter_slice, true,
+          math::matmul<Place, T>(context.device_context(), filter_slice, true,
                                  out_grad_slice, false, T(1.0), &col_matrix,
                                  T(0.0));
 
@@ -190,7 +186,7 @@ class GemmConvGrad2DKernel : public framework::OpKernel {
           Tensor in_grad_slice =
               in_grad_batch.Slice<T>(g * in_step, (g + 1) * in_step);
           col2im(in_grad_slice, col, strides[0], strides[1], paddings[0],
-                 paddings[1], device_context);
+                 paddings[1], context.device_context());
         }
       }
     }
@@ -212,14 +208,14 @@ class GemmConvGrad2DKernel : public framework::OpKernel {
               out_grad_batch.Slice<T>(g * out_step, (g + 1) * out_step);
           Tensor in_slice = in_batch.Slice<T>(g * in_step, (g + 1) * in_step);
           im2col(in_slice, col, strides[0], strides[1], paddings[0],
-                 paddings[1], device_context);
+                 paddings[1], context.device_context());
 
           // gemm
           Tensor filter_grad_slice =
               filter_grad_.Slice<T>(g * out_step, (g + 1) * out_step);
-          math::matmul<Place, T>(device_context, out_grad_slice, false,
-                                 col_matrix, true, T(1.0), &filter_grad_slice,
-                                 T(1.0));
+          math::matmul<Place, T>(context.device_context(), out_grad_slice,
+                                 false, col_matrix, true, T(1.0),
+                                 &filter_grad_slice, T(1.0));
         }
       }
     }