diff --git a/paddle/operators/conv_cudnn_op.cu.cc b/paddle/operators/conv_cudnn_op.cu.cc
index 3f97dc7ee0a61944a8a57314b5ec7f33df619bf3..bc265dcc4f28d3d3f848bebbfed3e0c3e8791b6a 100644
--- a/paddle/operators/conv_cudnn_op.cu.cc
+++ b/paddle/operators/conv_cudnn_op.cu.cc
@@ -28,7 +28,8 @@ using ScopedFilterDescriptor = platform::ScopedFilterDescriptor;
 using ScopedConvolutionDescriptor = platform::ScopedConvolutionDescriptor;
 using DataLayout = platform::DataLayout;
 
-static constexpr size_t kCONV_CUDNN_WORKSPACE_LIMIT_BYTES = 1024 * 1024 * 1024;
+static constexpr size_t kCONV_CUDNN_WORKSPACE_LIMIT_BYTES =
+    static_cast<size_t>(1024) * 1024 * 1024;
 
 template <typename T>
 class CudnnConvOpKernel : public framework::OpKernel<T> {
@@ -44,7 +45,8 @@ class CudnnConvOpKernel : public framework::OpKernel<T> {
     std::vector<int> paddings = ctx.Attr<std::vector<int>>("paddings");
     std::vector<int> dilations = ctx.Attr<std::vector<int>>("dilations");
     int groups = ctx.Attr<int>("groups");
-    int user_workspace_size = ctx.Attr<int>("workspace_size_MB");
+    int64_t user_workspace_size =
+        static_cast<size_t>(ctx.Attr<int>("workspace_size_MB"));
 
     const T* input_data = input->data<T>();
     const T* filter_data = filter->data<T>();
@@ -163,7 +165,8 @@ class CudnnConvGradOpKernel : public framework::OpKernel<T> {
     std::vector<int> paddings = ctx.Attr<std::vector<int>>("paddings");
     std::vector<int> dilations = ctx.Attr<std::vector<int>>("dilations");
     int groups = ctx.Attr<int>("groups");
-    int user_workspace_size = ctx.Attr<int>("workspace_size_MB");
+    int64_t user_workspace_size =
+        static_cast<size_t>(ctx.Attr<int>("workspace_size_MB"));
 
     // ------------------- cudnn descriptors ---------------------
     ScopedTensorDescriptor input_desc;