!1201 Pynative release memory after run finish

Merge pull request !1201 from JoyLvliang/pynative-release-memory-after-run-finish

mindspore/ccsrc/pynative/pynative_execute.cc

@@ -149,23 +149,19 @@ OpExecInfoPtr GenerateOpExecInfo(const py::args &args) {
   return op_exec_info;
 }
 
-std::string GetSingleOpGraphInfo(const OpExecInfoPtr &op_exec_info) {
+std::string GetSingleOpGraphInfo(const OpExecInfoPtr &op_exec_info,
+                                 const std::vector<tensor::TensorPtr> &input_tensors) {
   MS_EXCEPTION_IF_NULL(op_exec_info);
   std::string graph_info;
-  MS_EXCEPTION_IF_NULL(op_exec_info->abstract);
   // get input tensor info
-  size_t input_num = op_exec_info->op_inputs.size();
-  for (size_t index = 0; index < input_num; ++index) {
-    if (py::isinstance<tensor::Tensor>(op_exec_info->op_inputs[index])) {
-      auto tensor_ptr = py::cast<tensor::TensorPtr>(op_exec_info->op_inputs[index]);
-      MS_EXCEPTION_IF_NULL(tensor_ptr);
-      (void)graph_info.append(tensor_ptr->GetShapeAndDataTypeInfo() + "_");
-    }
+  for (const auto &input_tensor : input_tensors) {
+    MS_EXCEPTION_IF_NULL(input_tensor);
+    (void)graph_info.append(input_tensor->GetShapeAndDataTypeInfo() + "_");
   }
   // get prim and abstract info
+  MS_EXCEPTION_IF_NULL(op_exec_info->abstract);
   (void)graph_info.append(std::to_string((uintptr_t)(op_exec_info->py_primitive.get())) + "_" +
                           op_exec_info->abstract->ToString());
-  MS_LOG(INFO) << "Graph info [" << graph_info << "]";
   return graph_info;
 }
 
@@ -337,14 +333,14 @@ py::object RunOpInMs(const OpExecInfoPtr &op_exec_info, PynativeStatusCode *stat
   if (session == nullptr) {
     session = session::SessionFactory::Get().Create(device_target);
   }
-
   MS_EXCEPTION_IF_NULL(session);
   session->Init(ms_context->device_id());
 
-  std::string graph_info = GetSingleOpGraphInfo(op_exec_info);
   std::vector<tensor::TensorPtr> input_tensors;
   std::vector<int> tensors_mask;
   ConstructInputTensor(op_exec_info, &tensors_mask, &input_tensors);
+  // get graph info for checking it whether existing in the cache
+  std::string graph_info = GetSingleOpGraphInfo(op_exec_info, input_tensors);
   session->BuildOp(*op_exec_info, graph_info, input_tensors, tensors_mask);
   EraseValueNodeTensor(tensors_mask, &input_tensors);
   py::tuple result = session->RunOp(*op_exec_info, graph_info, input_tensors);

mindspore/ccsrc/session/ascend_session.cc

@@ -342,7 +342,7 @@ void AscendSession::BuildOp(const OpRunInfo &op_run_info, const GraphInfo &graph
                             const std::vector<tensor::TensorPtr> &input_tensors, const std::vector<int> &tensors_mask) {
   MS_LOG(INFO) << "Build op " << op_run_info.op_name << " start !";
   if (GraphCacheExist(graph_info)) {
-    MS_LOG(INFO) << "Build op " << op_run_info.op_name << " finish !";
+    MS_LOG(INFO) << "Build op " << op_run_info.op_name << " graph cache has existed !";
     return;
   }
 

mindspore/ccsrc/session/session_basic.cc

@@ -301,9 +301,13 @@ size_t LoadCtrlInputTensor(const std::shared_ptr<Context> &context, std::vector<
 ValueNodePtr ConstructRunOpValueNode(const std::shared_ptr<KernelGraph> &graph, const tensor::TensorPtr &input_tensor) {
   MS_EXCEPTION_IF_NULL(graph);
   MS_EXCEPTION_IF_NULL(input_tensor);
-  auto abstract = std::make_shared<abstract::AbstractTensor>(input_tensor);
   auto value_node = std::make_shared<ValueNode>(input_tensor);
+  // construct abstract of value node
+  auto type_of_tensor = input_tensor->Dtype();
+  auto shape_of_tensor = input_tensor->shape();
+  auto abstract = std::make_shared<abstract::AbstractTensor>(type_of_tensor, shape_of_tensor);
   value_node->set_abstract(abstract);
+  // add value node to graph
   auto input_value_node = graph->NewValueNode(value_node);
   graph->AddValueNodeToGraph(input_value_node);
   return input_value_node;
@@ -313,7 +317,7 @@ ParameterPtr ConstructRunOpParameter(const std::shared_ptr<KernelGraph> &graph,
                                      int tensor_mask) {
   auto param = graph->NewParameter();
   MS_EXCEPTION_IF_NULL(param);
-  if (tensor_mask == 1) {
+  if (tensor_mask == kParameterWeightTensorMask) {
     py::object obj;
     param->set_default_param(obj);
   }
@@ -329,8 +333,10 @@ ParameterPtr ConstructRunOpParameter(const std::shared_ptr<KernelGraph> &graph,
     kernel_build_info_builder->SetOutputsDeviceType(std::vector<TypeId>{input_tensor->device_address()->type_id()});
   }
   AnfAlgo::SetSelectKernelBuildInfo(kernel_build_info_builder->Build(), param.get());
-  // ftruct abstract of parameter
-  auto abstract = std::make_shared<abstract::AbstractTensor>(input_tensor);
+  // construct abstract of parameter
+  auto type_of_tensor = input_tensor->Dtype();
+  auto shape_of_tensor = input_tensor->shape();
+  auto abstract = std::make_shared<abstract::AbstractTensor>(type_of_tensor, shape_of_tensor);
   param->set_abstract(abstract);
   return param;
 }

mindspore/ccsrc/utils/utils.h

@@ -199,6 +199,8 @@ const size_t kShape4dDims = 4;
 const size_t kShape5dDims = 5;
 const size_t kCubeSize = 16;
 const size_t kMemAlignSize = 512;
+const int kParameterDataTensorMask = 0;
+const int kParameterWeightTensorMask = 1;
 const int kValueNodeTensorMask = 2;
 
 // define special index in special node