Polish code

test=develop

paddle/fluid/operators/lookup_table_op.cc

@@ -81,6 +81,10 @@ class LookupTableOpMaker : public framework::OpProtoAndCheckerMaker {
                      "Otherwise the given value indicates padding the output "
                      "with zeros whenever lookup encounters it in Ids.")
         .SetDefault(kNoPadding);
+    AddAttr<bool>("grad_inplace",
+                  "(boolean, default false) "
+                  "If the grad op reuse the input's variable.")
+        .SetDefault(false);
     AddComment(R"DOC(
 Lookup Table Operator.
 

paddle/fluid/operators/lookup_table_op.h

@@ -119,9 +119,30 @@ class LookupTableGradKernel : public framework::OpKernel<T> {
 
       auto *d_table_value = d_table->mutable_value();
       d_table_value->Resize({ids_num, table_dim[1]});
+      // FIXME(minqiyang):
       // memory optimization will NOT reuse Tensor with SelectedRows
       // so we could just share the tensor here directly.
-      d_table_value->ShareDataWith(*d_output);
+      // However, the InferVarType method will infer the output SelectedRows
+      // to Tensor sometimes, which is a bug, so we will add an attribute
+      // here to indicate the inplace and remove this attribute after
+      // the InferVarType's bug was fixed
+      bool grad_inplace = context.Attr<bool>("grad_inplace");
+      if (grad_inplace) {
+        d_table_value->ShareDataWith(*d_output);
+      } else {
+        d_table_value->mutable_data<T>(context.GetPlace());
+
+        d_table->set_height(table_dim[0]);
+
+        auto *d_output_data = d_output->data<T>();
+        auto *d_table_data = d_table_value->data<T>();
+
+        auto d_output_dims = d_output->dims();
+        PADDLE_ENFORCE_EQ(
+            d_table_value->dims(),
+            framework::flatten_to_2d(d_output_dims, d_output_dims.size() - 1));
+        memcpy(d_table_data, d_output_data, sizeof(T) * d_output->numel());
+      }
     } else {
       auto *ids = context.Input<LoDTensor>("Ids");
       auto *d_output = context.Input<LoDTensor>(framework::GradVarName("Out"));