reduce Eigen transformation

test=develop

lite/kernels/x86/reduce_op_function.h

@@ -46,23 +46,6 @@ void ReduceFunctor(const lite::Tensor& input,
                    lite::Tensor* output,
                    const std::vector<int>& dims,
                    bool keep_dim) {
-  auto x = EigenTensor<T, D>::From(input);
-
-  auto reduce_dim = Eigen::array<int, R_D>();
-  auto x_rank = static_cast<int>(x.dimensions().size());
-  for (size_t i = 0; i < dims.size(); ++i) {
-    if (dims[i] < 0) {
-      reduce_dim[i] = x_rank + dims[i];
-    } else {
-      reduce_dim[i] = dims[i];
-    }
-  }
-
-  Functor functor;
-  if (D == 1) {
-    auto out = EigenScalar<T>::From(output);
-    functor(&x, &out, reduce_dim);
-  } else {
   auto te = strstr(typeid(Functor).name(), "SumFunctor");
   if (D == 3 && R_D == 1 && te != NULL) {
     const lite::DDim& input_dims = input.dims();
@@ -80,6 +63,23 @@ void ReduceFunctor(const lite::Tensor& input,
         output_data[out_d] = output_temp;
       }
     }
+  } else {
+    auto x = EigenTensor<T, D>::From(input);
+
+    auto reduce_dim = Eigen::array<int, R_D>();
+    auto x_rank = static_cast<int>(x.dimensions().size());
+    for (size_t i = 0; i < dims.size(); ++i) {
+      if (dims[i] < 0) {
+        reduce_dim[i] = x_rank + dims[i];
+      } else {
+        reduce_dim[i] = dims[i];
+      }
+    }
+
+    Functor functor;
+    if (D == 1) {
+      auto out = EigenScalar<T>::From(output);
+      functor(&x, &out, reduce_dim);
     } else {
       auto out = EigenTensor<T, (D - R_D)>::From(*output, output->dims());
       functor(&x, &out, reduce_dim);