modify log level for pynative

mindspore/ccsrc/backend/session/session_basic.cc

@@ -244,10 +244,10 @@ BaseRef CreateNodeOutputTensors(const AnfNodePtr &anf, const KernelGraphPtr &gra
   MS_EXCEPTION_IF_NULL(anf);
   MS_EXCEPTION_IF_NULL(tensor_to_node);
   MS_EXCEPTION_IF_NULL(node_to_tensor);
-  MS_LOG(INFO) << "Create tensor for output[" << anf->DebugString() << "]";
+  MS_LOG(DEBUG) << "Create tensor for output[" << anf->DebugString() << "]";
   auto item_with_index = AnfAlgo::VisitKernelWithReturnType(anf, 0);
   MS_EXCEPTION_IF_NULL(item_with_index.first);
-  MS_LOG(INFO) << "Create tensor for output after visit:" << item_with_index.first->DebugString();
+  MS_LOG(DEBUG) << "Create tensor for output after visit:" << item_with_index.first->DebugString();
   // special handle for maketuple
   if (AnfAlgo::CheckPrimitiveType(item_with_index.first, prim::kPrimMakeTuple)) {
     auto cnode = item_with_index.first->cast<CNodePtr>();
@@ -370,8 +370,8 @@ BaseRef CreateNodeOutputPlaceholder(const session::KernelWithIndex &node_output_
   MS_EXCEPTION_IF_NULL(node);
   MS_EXCEPTION_IF_NULL(graph);
   MS_EXCEPTION_IF_NULL(output_indexes);
-  MS_LOG(INFO) << "Create placeholder for output[" << node->DebugString() << "] index[" << node_output_pair.second
-               << "]";
+  MS_LOG(DEBUG) << "Create placeholder for output[" << node->DebugString() << "] index[" << node_output_pair.second
+                << "]";
   // if node is a value node, no need sync addr from device to host
   if (node->isa<ValueNode>()) {
     auto value_node = node->cast<ValueNodePtr>();
@@ -400,10 +400,10 @@ BaseRef CreateNodeOutputPlaceholder(const AnfNodePtr &anf, const KernelGraphPtr
                                     std::map<KernelWithIndex, std::vector<std::vector<size_t>>> *output_indexes) {
   MS_EXCEPTION_IF_NULL(anf);
   MS_EXCEPTION_IF_NULL(output_indexes);
-  MS_LOG(INFO) << "Create placeholder for output[" << anf->DebugString() << "]";
+  MS_LOG(DEBUG) << "Create placeholder for output[" << anf->DebugString() << "]";
   auto item_with_index = AnfAlgo::VisitKernelWithReturnType(anf, 0);
   MS_EXCEPTION_IF_NULL(item_with_index.first);
-  MS_LOG(INFO) << "Create placeholder for output after visit:" << item_with_index.first->DebugString();
+  MS_LOG(DEBUG) << "Create placeholder for output after visit:" << item_with_index.first->DebugString();
   // special handle for maketuple
   if (AnfAlgo::CheckPrimitiveType(item_with_index.first, prim::kPrimMakeTuple)) {
     auto cnode = item_with_index.first->cast<CNodePtr>();
@@ -1499,7 +1499,7 @@ void SessionBasic::UpdateOutputs(const std::shared_ptr<KernelGraph> &kernel_grap
   auto anf_outputs = kernel_graph->outputs();
   for (auto &item : anf_outputs) {
     MS_EXCEPTION_IF_NULL(item);
-    MS_LOG(INFO) << "Update output[" << item->DebugString() << "]";
+    MS_LOG(DEBUG) << "Update output[" << item->DebugString() << "]";
     outputs->emplace_back(CreateNodeOutputTensors(item, kernel_graph, input_tensors, &tensor_to_node, &node_to_tensor));
   }
 
@@ -1945,7 +1945,6 @@ CNodePtr SessionBasic::ConstructOutput(const AnfNodePtrList &outputs, const std:
 }
 
 void SessionBasic::CreateOutputNode(const CNodePtr &cnode, const std::shared_ptr<KernelGraph> &graph) {
-  MS_LOG(INFO) << "Start!";
   std::vector<AnfNodePtr> make_tuple_inputs;
   make_tuple_inputs.push_back(NewValueNode(prim::kPrimMakeTuple));
   MS_EXCEPTION_IF_NULL(graph);
@@ -1967,7 +1966,6 @@ void SessionBasic::CreateOutputNode(const CNodePtr &cnode, const std::shared_ptr
   // create output
   auto g_output = graph->NewCNode(make_tuple_inputs);
   graph->set_output(g_output);
-  MS_LOG(INFO) << "Finish!";
 }
 
 std::shared_ptr<KernelGraph> SessionBasic::ConstructSingleOpGraph(const OpRunInfo &op_run_info,
@@ -1983,7 +1981,6 @@ std::shared_ptr<KernelGraph> SessionBasic::ConstructSingleOpGraph(const OpRunInf
   MS_EXCEPTION_IF_NULL(op_prim);
   inputs.push_back(std::make_shared<ValueNode>(op_prim));
   // set input parameter
-  MS_LOG(INFO) << "Input tensor size: " << input_tensors.size();
   if (input_tensors.size() != tensors_mask.size()) {
     MS_LOG(EXCEPTION) << "Input tensors size " << input_tensors.size() << " should be equal to tensors mask size "
                       << tensors_mask.size();

mindspore/ccsrc/pipeline/pynative/pynative_execute.cc

@@ -468,7 +468,7 @@ void ConstructInputTensor(const OpExecInfoPtr &op_run_info, std::vector<int64_t>
   bool reg_exist = opt::ConstInputToAttrInfoRegistry::Instance().GetRegisterByOpName(op_run_info->op_name, &reg);
   if (op_run_info->is_dynamic_shape &&
       dynamic_shape_const_input_to_attr.find(op_run_info->op_name) == dynamic_shape_const_input_to_attr.end()) {
-    MS_LOG(INFO) << "current node is dynamic shape: " << op_run_info->op_name;
+    MS_LOG(DEBUG) << "current node is dynamic shape: " << op_run_info->op_name;
     reg_exist = false;
   }
   auto ms_context = MsContext::GetInstance();
@@ -1560,14 +1560,14 @@ py::object ForwardExecutor::RunOpWithBackendPolicy(MsBackendPolicy backend_polic
   switch (backend_policy) {
     case kMsBackendVmOnly: {
       // use vm only
-      MS_LOG(INFO) << "RunOp use VM only backend";
+      MS_LOG(DEBUG) << "RunOp use VM only backend";
       result = RunOpInVM(op_exec_info, status);
       break;
     }
     case kMsBackendGePrior: {
 #ifdef ENABLE_GE
       // use GE first, use vm when GE fails
-      MS_LOG(INFO) << "RunOp use GE first backend";
+      MS_LOG(DEBUG) << "RunOp use GE first backend";
       result = RunOpInGE(op_exec_info, status);
       if (*status != PYNATIVE_SUCCESS) {
         result = RunOpInVM(op_exec_info, status);
@@ -1577,7 +1577,7 @@ py::object ForwardExecutor::RunOpWithBackendPolicy(MsBackendPolicy backend_polic
     }
     case kMsBackendMsPrior: {
       // use Ms first,use others when ms failed
-      MS_LOG(INFO) << "RunOp use Ms first backend";
+      MS_LOG(DEBUG) << "RunOp use Ms first backend";
       result = RunOpInMs(op_exec_info, status);
       if (*status != PYNATIVE_SUCCESS) {
         MS_LOG(ERROR) << "RunOp use Ms backend failed!!!";
@@ -1591,7 +1591,7 @@ py::object ForwardExecutor::RunOpWithBackendPolicy(MsBackendPolicy backend_polic
 }
 
 py::object ForwardExecutor::RunOpInVM(const OpExecInfoPtr &op_exec_info, PynativeStatusCode *status) {
-  MS_LOG(INFO) << "RunOpInVM start";
+  MS_LOG(DEBUG) << "RunOpInVM start";
   MS_EXCEPTION_IF_NULL(status);
   MS_EXCEPTION_IF_NULL(op_exec_info);
   MS_EXCEPTION_IF_NULL(op_exec_info->py_primitive);
@@ -1617,14 +1617,14 @@ py::object ForwardExecutor::RunOpInVM(const OpExecInfoPtr &op_exec_info, Pynativ
       }
     }
     *status = PYNATIVE_SUCCESS;
-    MS_LOG(INFO) << "RunOpInVM end";
+    MS_LOG(DEBUG) << "RunOpInVM end";
     return std::move(result);
   }
 
   auto primitive = op_exec_info->py_primitive;
   MS_EXCEPTION_IF_NULL(primitive);
   auto result = primitive->RunPyComputeFunction(op_inputs);
-  MS_LOG(INFO) << "RunOpInVM end";
+  MS_LOG(DEBUG) << "RunOpInVM end";
   if (py::isinstance<py::none>(result)) {
     MS_LOG(ERROR) << "VM got the result none, please check whether it is failed to get func";
     *status = PYNATIVE_OP_NOT_IMPLEMENTED_ERR;
@@ -1642,7 +1642,7 @@ py::object ForwardExecutor::RunOpInVM(const OpExecInfoPtr &op_exec_info, Pynativ
 py::object ForwardExecutor::RunOpInMs(const OpExecInfoPtr &op_exec_info, PynativeStatusCode *status) {
   MS_EXCEPTION_IF_NULL(op_exec_info);
   MS_EXCEPTION_IF_NULL(status);
-  MS_LOG(INFO) << "Start run op [" << op_exec_info->op_name << "] with backend policy ms";
+  MS_LOG(DEBUG) << "Start run op [" << op_exec_info->op_name << "] with backend policy ms";
   auto ms_context = MsContext::GetInstance();
   ms_context->set_param<bool>(MS_CTX_ENABLE_PYNATIVE_INFER, true);
 
@@ -1696,7 +1696,7 @@ py::object ForwardExecutor::RunOpInMs(const OpExecInfoPtr &op_exec_info, Pynativ
   auto result = BaseRefToPyData(outputs);
   ms_context->set_param<bool>(MS_CTX_ENABLE_PYNATIVE_INFER, false);
   *status = PYNATIVE_SUCCESS;
-  MS_LOG(INFO) << "End run op [" << op_exec_info->op_name << "] with backend policy ms";
+  MS_LOG(DEBUG) << "End run op [" << op_exec_info->op_name << "] with backend policy ms";
   return result;
 }
 

mindspore/ccsrc/runtime/device/kernel_runtime.cc

@@ -717,7 +717,7 @@ void KernelRuntime::AssignValueNodeTensor(const ValueNodePtr &value_node, const
 void KernelRuntime::AssignStaticMemoryValueNode(session::KernelGraph *graph) {
   MS_EXCEPTION_IF_NULL(graph);
   MS_EXCEPTION_IF_NULL(mem_manager_);
-  MS_LOG(INFO) << "AssignStaticMemoryValueNode start";
+  MS_LOG(DEBUG) << "AssignStaticMemoryValueNode start";
   auto ms_context = MsContext::GetInstance();
   MS_EXCEPTION_IF_NULL(ms_context);
   // order the value nodes
@@ -757,7 +757,7 @@ void KernelRuntime::AssignStaticMemoryValueNode(session::KernelGraph *graph) {
       }
     }
   }
-  MS_LOG(INFO) << "AssignStaticMemoryValueNode end";
+  MS_LOG(DEBUG) << "AssignStaticMemoryValueNode end";
 }
 
 void KernelRuntime::AssignDynamicMemory(session::KernelGraph *graph) {

mindspore/core/ir/primitive.h

@@ -85,7 +85,7 @@ class Primitive : public Named {
   const std::unordered_map<std::string, ValuePtr> &evaluate_added_attrs() const { return evaluate_added_attrs_; }
   void set_evaluate_added_attrs(const std::unordered_map<std::string, ValuePtr> &attrs) {
     for (auto &attr : attrs) {
-      MS_LOG(INFO) << " set evalu attrl " << name() << attr.first;
+      MS_LOG(DEBUG) << " set evalu attrl " << name() << attr.first;
       attrs_[attr.first] = attr.second;
     }
   }