     auto handle = dev_ctx.cudnn_handle();
     auto workspace_handle = dev_ctx.cudnn_workspace_handle();
 
-    PADDLE_ENFORCE_CUDA_SUCCESS(
-        platform::dynload::cudnnSetConvolutionMathType(cudnn_conv_desc,
-                                                       CUDNN_DEFAULT_MATH),
-        platform::errors::External(
-            "Call of cudnnSetConvolutionMathType(cudnn_conv_desc, "
-            "CUDNN_DEFAULT_MATH) failed, where cudnn_conv_desc is configured: "
-            "padding = %d, strides = %d, dilations = %d.",
-            framework::make_ddim(padding_common), framework::make_ddim(strides),
-            framework::make_ddim(dilations)));
+    PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::cudnnSetConvolutionMathType(
+        cudnn_conv_desc, CUDNN_DEFAULT_MATH));
 
     auto x_dims = framework::vectorize(transformed_input.dims());
     auto f_dims = framework::vectorize(filter->dims());

          platform::dynload::cudnnGetConvolutionForwardAlgorithm(
              handle, cudnn_input_desc, cudnn_filter_desc, cudnn_conv_desc,
              cudnn_output_desc, CUDNN_CONVOLUTION_FWD_SPECIFY_WORKSPACE_LIMIT,
              workspace_size_limit, &algo),
          platform::errors::External(
              "Call of cudnnGetConvolutionForwardAlgorithm failed."));
      VLOG(3) << "cuDNN forward algo " << algo;
    } else {
      std::function<cudnnConvolutionFwdAlgo_t()> search_func =

                  handle, cudnn_input_desc, input_data, cudnn_filter_desc,
                  filter_data, cudnn_conv_desc, cudnn_output_desc, output_data,
                  kNUM_CUDNN_FWD_ALGS, &returned_algo_count,
                  fwd_perf_stat.data(), cudnn_workspace, workspace_size_limit));
        };
        workspace_handle.RunFuncSync(cudnn_find_func, workspace_size_limit);
        VLOG(3) << "Perf result: (algo: stat, time, memory)";
