!4103 Reuse parameter by ref info

Merge pull request !4103 from chenfei_mindspore/reuse-parameter-by-ref-info

mindspore/ccsrc/backend/session/anf_runtime_algorithm.cc

@@ -523,38 +523,39 @@ std::vector<Axis> AnfRuntimeAlgorithm::GetOutputReshapeType(const AnfNodePtr &no
 
 TypeId AnfRuntimeAlgorithm::GetOutputInferDataType(const AnfNodePtr &node, size_t output_idx) {
   MS_EXCEPTION_IF_NULL(node);
-  TypePtr type_ptr = node->Type();
-  MS_EXCEPTION_IF_NULL(type_ptr);
-  if (type_ptr->isa<TensorType>() && output_idx == 0) {
-    auto tensor_ptr = type_ptr->cast<TensorTypePtr>();
-    MS_EXCEPTION_IF_NULL(tensor_ptr);
-    TypePtr elem = tensor_ptr->element();
-    MS_EXCEPTION_IF_NULL(elem);
-    return elem->type_id();
-  } else if (type_ptr->isa<Tuple>()) {
-    auto tuple_ptr = type_ptr->cast<TuplePtr>();
-    MS_EXCEPTION_IF_NULL(tuple_ptr);
-    if (output_idx >= tuple_ptr->size()) {
-      MS_LOG(EXCEPTION) << "Output index " << output_idx << " must be less than output number " << tuple_ptr->size();
-    }
-    auto tuple_i = (*tuple_ptr)[output_idx];
-    MS_EXCEPTION_IF_NULL(tuple_i);
-    if (tuple_i->isa<TensorType>()) {
-      auto tensor_ptr = tuple_i->cast<TensorTypePtr>();
+  auto get_single_type = [](const TypePtr &type_ptr) -> TypeId {
+    MS_EXCEPTION_IF_NULL(type_ptr);
+    if (type_ptr->isa<TensorType>()) {
+      auto tensor_ptr = type_ptr->cast<TensorTypePtr>();
       MS_EXCEPTION_IF_NULL(tensor_ptr);
       TypePtr elem = tensor_ptr->element();
       MS_EXCEPTION_IF_NULL(elem);
       return elem->type_id();
-    } else if (tuple_i->isa<Number>()) {
-      return tuple_i->type_id();
-    } else {
-      MS_LOG(WARNING) << "Not support type " << tuple_i->ToString();
-      return tuple_i->type_id();
     }
-  } else if (type_ptr->isa<Number>()) {
+    if (type_ptr->isa<Number>()) {
+      return type_ptr->type_id();
+    }
     return type_ptr->type_id();
+  };
+  auto get_tuple_type = [get_single_type](const TypePtr &type_ptr, size_t output_idx) -> TypeId {
+    MS_EXCEPTION_IF_NULL(type_ptr);
+    if (!type_ptr->isa<Tuple>()) {
+      return get_single_type(type_ptr);
+    }
+    auto tuple_ptr = type_ptr->cast<TuplePtr>();
+    MS_EXCEPTION_IF_NULL(tuple_ptr);
+    if (output_idx >= tuple_ptr->size()) {
+      MS_LOG(EXCEPTION) << "Output index " << output_idx << " must be less than output number " << tuple_ptr->size();
+    }
+    return get_single_type((*tuple_ptr)[output_idx]);
+  };
+  TypePtr type_ptr = node->Type();
+  if (type_ptr->isa<RefType>()) {
+    auto ref_type_ptr = type_ptr->cast<RefTypePtr>();
+    MS_EXCEPTION_IF_NULL(ref_type_ptr);
+    return get_tuple_type(ref_type_ptr->subtype(), output_idx);
   }
-  return type_ptr->type_id();
+  return get_tuple_type(type_ptr, output_idx);
 }
 
 TypeId AnfRuntimeAlgorithm::GetPrevNodeOutputInferDataType(const AnfNodePtr &node, size_t input_idx) {

mindspore/ccsrc/backend/session/ascend_control_parser.cc

@@ -414,12 +414,6 @@ void AscendControlParser::ChildGraphDataAssign(
                           << node->DebugString(5) << " gives " << args.size();
       }
       for (size_t i = 0; i < args.size(); ++i) {
-        if (args[i]->isa<Parameter>() && memo->find(child_graph) == memo->end()) {
-          MS_LOG(INFO) << args[i]->DebugString() << " to " << params[i]->DebugString()
-                       << " should be reused, continue.";
-          link_list->emplace_back(args[i], params[i]);
-          continue;
-        }
         InsertMultipleAssignToGraph(kg, node, NOT_NULL(args[i]), NOT_NULL(params[i]));
       }
     }