!15710 gpu inference syupport multi-outputs

From: @wilfchen
Reviewed-by: @limingqi107,@cristoval
Signed-off-by: @cristoval

mindspore/ccsrc/backend/session/anf_runtime_algorithm.cc

@@ -48,6 +48,7 @@ using kernel::KernelModPtr;
 namespace {
 constexpr size_t kNopNodeInputSize = 2;
 constexpr size_t kNopNodeRealInputIndex = 1;
+constexpr size_t kReturnDataIndex = 1;
 
 using PrimitiveSet = std::unordered_set<PrimitivePtr, PrimitiveHasher, PrimitiveEqual>;
 
@@ -1919,5 +1920,16 @@ void AnfRuntimeAlgorithm::InferShape(const CNodePtr &node) {
   auto eval_result = opt::CppInferShape(primitive, args_spec_list);
   node->set_abstract(eval_result);
 }
+
+void AnfRuntimeAlgorithm::InsertMakeTupleForOutput(NotNull<KernelGraphPtr> root_graph) {
+  auto return_node = root_graph->get_return();
+  MS_EXCEPTION_IF_NULL(return_node);
+  if (return_node->size() <= kReturnDataIndex) {
+    return;
+  }
+  auto make_tuple = root_graph->NewCNode(
+    {NewValueNode(std::make_shared<Primitive>(prim::kPrimMakeTuple->name())), root_graph->output()});
+  root_graph->set_output(make_tuple);
+}
 }  // namespace session
 }  // namespace mindspore

mindspore/ccsrc/backend/session/anf_runtime_algorithm.h

@@ -266,6 +266,7 @@ class AnfRuntimeAlgorithm {
   // Find real input nodes.
   static void GetAllFatherRealNode(const AnfNodePtr &anf_node, std::vector<AnfNodePtr> *result,
                                    std::set<AnfNodePtr> *visited);
+  static void InsertMakeTupleForOutput(NotNull<KernelGraphPtr> root_graph);
 };
 }  // namespace session
 using AnfAlgo = session::AnfRuntimeAlgorithm;

mindspore/ccsrc/backend/session/ascend_session.cc

@@ -85,7 +85,6 @@ static constexpr uint32_t kLabelSwitchLabelId = 2;
 namespace mindspore {
 namespace session {
 const size_t kInvalidIndex = SIZE_MAX;
-constexpr size_t kReturnDataIndex = 1;
 constexpr char SR_TAG[] = "sr_tag";
 constexpr char BACKWARD[] = "backward";
 namespace {
@@ -143,16 +142,6 @@ std::vector<CNodePtr> GetCNodes(const std::vector<AnfNodePtr> &anf_nodes) {
   }
   return cnodes;
 }
-void InsertMakeTupleForOutput(NotNull<KernelGraphPtr> root_graph) {
-  auto return_node = root_graph->get_return();
-  MS_EXCEPTION_IF_NULL(return_node);
-  if (return_node->size() <= kReturnDataIndex) {
-    return;
-  }
-  auto make_tuple = root_graph->NewCNode(
-    {NewValueNode(std::make_shared<Primitive>(prim::kPrimMakeTuple->name())), root_graph->output()});
-  root_graph->set_output(make_tuple);
-}
 
 TensorPtr GetCNodeOutputStubTensor(const KernelWithIndex &kernel_with_index,
                                    const std::map<KernelWithIndex, OutputTensorInfo> &node_output_info,
@@ -483,7 +472,7 @@ GraphId AscendSession::CompileGraphImpl(NotNull<FuncGraphPtr> func_graph) {
   // empty graph dont entry to backend
   if (root_graph->execution_order().empty()) {
     MS_LOG(INFO) << root_graph->ToString() << " is empty graph.";
-    InsertMakeTupleForOutput(NOT_NULL(root_graph));
+    AnfAlgo::InsertMakeTupleForOutput(NOT_NULL(root_graph));
     root_graph->set_executable(false);
     InitRuntimeResource();
     return root_graph->graph_id();
@@ -511,7 +500,7 @@ GraphId AscendSession::CompileGraphImpl(NotNull<FuncGraphPtr> func_graph) {
   UpdateRefOutputMap(NOT_NULL(root_graph), NOT_NULL(&memo));
   memo.clear();
   // add make_tuple to the output graph
-  InsertMakeTupleForOutput(NOT_NULL(root_graph));
+  AnfAlgo::InsertMakeTupleForOutput(NOT_NULL(root_graph));
   // root root_graph valiate,include genearte execute order and so on
   RootGraphExecutorValidate(NOT_NULL(root_graph));
   // dump graph before remove nop nodes

mindspore/ccsrc/backend/session/gpu_session.cc

@@ -314,7 +314,9 @@ GraphId GPUSession::CompileGraphImpl(NotNull<FuncGraphPtr> func_graph) {
   if (all_graphs.size() != 1) {
     MS_LOG(EXCEPTION) << "Gpu backend does not support multi-graph schedule. graph num" << all_graphs.size();
   }
-
+  // Insert maketuple graph output in case of multi-outputs.
+  // The ConvertTupleOutputToMaketuple pass will insert TupleGetItem.
+  AnfAlgo::InsertMakeTupleForOutput(NOT_NULL(root_graph));
   opt::BackendCommonOptimization(root_graph);
   return CompileGraphImpl(root_graph);
 }