refine code and comments, test=develop

paddle/fluid/operators/hierarchical_sigmoid_op.h

@@ -30,14 +30,14 @@ template <typename T, int MajorType = Eigen::RowMajor,
 using EigenMatrix = framework::EigenMatrix<T, MajorType, IndexType>;
 using platform::Transform;
 
-std::vector<int64_t> cal_rows(const framework::LoDTensor* path) {
+std::vector<int64_t> cal_rows(const framework::LoDTensor& path) {
   std::set<int64_t> tmp;
   std::vector<int64_t> rows;
   rows.clear();
-  for (size_t i = 0; i < static_cast<size_t>(path->dims()[0]); i++) {
-    for (size_t j = 0; j < static_cast<size_t>(path->dims()[1]); j++) {
+  for (size_t i = 0; i < static_cast<size_t>(path.dims()[0]); i++) {
+    for (size_t j = 0; j < static_cast<size_t>(path.dims()[1]); j++) {
       int64_t temp =
-          path->data<int64_t>()[i * static_cast<size_t>(path->dims()[1]) + j];
+          path.data<int64_t>()[i * static_cast<size_t>(path.dims()[1]) + j];
       if (temp >= 0) {
         tmp.insert(temp);
       }
@@ -188,7 +188,7 @@ class HierarchicalSigmoidGradOpKernel : public framework::OpKernel<T> {
       zero(dev_ctx, w_grad, static_cast<T>(0.0));
       bit_code->MulGradWeight(pre_out_grad, w_grad, *in);
     } else {
-      framework::Vector<int64_t> real_rows = cal_rows(path);
+      framework::Vector<int64_t> real_rows = cal_rows(*path);
       auto* w_grad =
           ctx.Output<framework::SelectedRows>(framework::GradVarName("W"));
       w_grad->set_rows(real_rows);