Optimize the InferShape of concat by removing the use of std::vector.

lite/operators/concat_op.cc

@@ -27,11 +27,8 @@ bool ConcatOpLite::CheckShape() const {
 }
 
 bool ConcatOpLite::InferShape() const {
-  std::vector<lite::DDim> input_dims;
-  for (auto p : param_.x) {
-    input_dims.push_back(p->dims());
-  }
-  const size_t n = input_dims.size();
+  std::vector<lite::Tensor *> &inputs = param_.x;
+  const size_t n = inputs.size();
   CHECK_GT_OR_FALSE(n, 0);
 
   int axis = 0;
@@ -42,17 +39,18 @@ bool ConcatOpLite::InferShape() const {
     axis = axis_tensor_val[0];
   }
   if (axis < 0) {
-    axis += input_dims[0].size();
+    axis += inputs[0]->dims().size();
   }
 
-  auto &out_dims = input_dims[0];
+  auto out_dims = inputs[0]->dims();
   size_t in_zero_dims_size = out_dims.size();
   for (size_t i = 1; i < n; i++) {
+    auto &input_dims_i = inputs[i]->dims();
     for (size_t j = 0; j < in_zero_dims_size; j++) {
       if (j == static_cast<size_t>(axis)) {
-        out_dims[axis] += input_dims[i][j];
+        out_dims[axis] += input_dims_i[j];
       } else {
-        CHECK_EQ_OR_FALSE(out_dims[j], input_dims[i][j]);
+        CHECK_EQ_OR_FALSE(out_dims[j], input_dims_i[j]);
       }
     }
   }
@@ -60,7 +58,7 @@ bool ConcatOpLite::InferShape() const {
     out_dims[axis] = -1;
   }
   // Set output dims
-  param_.output->Resize(lite::DDim(out_dims));
+  param_.output->Resize(out_dims);
   auto out_lod = param_.output->mutable_lod();
   *out_lod = param_.x[0]->lod();
   return true;