add warning info to statistics how much nodes using raise or reduce to selected kernel info

mindspore/ccsrc/device/ascend/kernel_select_ascend.cc

@@ -342,7 +342,7 @@ void AddNodeAndKernelDataType(const CNodePtr &kernel_node, const kernel::KernelB
                               std::vector<int> *node_mix_precision_datatype_index) {
   MS_EXCEPTION_IF_NULL(node_mix_precision_datatype);
   bool add_node_datatype_flag = false;
-  if (node_mix_precision_datatype->size() == 0) {
+  if (node_mix_precision_datatype->empty()) {
     add_node_datatype_flag = true;
   }
   for (size_t input_index = 0; input_index < kernel_build_info.GetInputNum(); ++input_index) {
@@ -464,8 +464,9 @@ std::vector<std::shared_ptr<kernel::KernelBuildInfo>> FilterRaisedOrReducePrecis
 }
 }  // namespace
 
-void SelectKernelInfo(const CNodePtr &kernel_node) {
+int SelectKernelInfo(const CNodePtr &kernel_node) {
   std::vector<std::shared_ptr<kernel::KernelBuildInfo>> kernel_info_list;
+  int status = kStatusAllMatched;
   MS_EXCEPTION_IF_NULL(kernel_node);
   bool precision_reduce = false;
   std::shared_ptr<kernel::KernelBuildInfo> selected_kernel_info = nullptr;
@@ -486,11 +487,13 @@ void SelectKernelInfo(const CNodePtr &kernel_node) {
                               << "] cannot find valid kernel info, not supported the type" << buffer.str();
     } else {
       PrintRaiseOrReducePrecisionSelectedInfo(kernel_node, selected_kernel_info, precision_reduce);
+      status = precision_reduce ? kStatusReducePrecision : kStatusRaisePrecision;
     }
   }
   AnfAlgo::SetSelectKernelBuildInfo(selected_kernel_info, kernel_node.get());
   // Set format and data type for input tensor.
   SetTensorDeviceInfo(*selected_kernel_info, kernel_node);
+  return status;
 }
 
 bool CheckKernelAccuracySupported(const CNodePtr &kernel_node,

mindspore/ccsrc/device/ascend/kernel_select_ascend.h

@@ -21,7 +21,7 @@
 namespace mindspore {
 namespace device {
 namespace ascend {
-void SelectKernelInfo(const CNodePtr &kernel_node);
+int SelectKernelInfo(const CNodePtr &kernel_node);
 bool CheckKernelAccuracySupported(const CNodePtr &kernel_node, const kernel::KernelBuildInfoPtr &new_kernel_build_info);
 }  // namespace ascend
 }  // namespace device

mindspore/ccsrc/session/ascend_session.cc

@@ -312,10 +312,25 @@ py::tuple AscendSession::RunOp(const OpRunInfo &op_run_info, const GraphInfo &gr
 // compile graph steps
 void AscendSession::SelectKernel(const KernelGraph &kernel_graph) const {
   MS_LOG(INFO) << "Start!";
+  size_t raise_precision_count = 0;
+  size_t reduce_precision_count = 0;
   for (const auto &cnode : kernel_graph.execution_order()) {
-    device::ascend::SelectKernelInfo(cnode);
+    auto status = device::ascend::SelectKernelInfo(cnode);
+    if (status == kStatusRaisePrecision) {
+      raise_precision_count++;
+    } else if (status == kStatusReducePrecision) {
+      reduce_precision_count++;
+    }
     MS_LOG(INFO) << "Select ApplyKernel: " << cnode->DebugString();
   }
+  if (raise_precision_count > 0) {
+    MS_LOG(WARNING) << "There has " << raise_precision_count
+                    << " node/nodes used raise precision to selected the kernel!";
+  }
+  if (reduce_precision_count > 0) {
+    MS_LOG(WARNING) << "There has " << reduce_precision_count
+                    << " node/nodes used reduce precision to selected the kernel!";
+  }
   MS_LOG(INFO) << "Finish!";
 }
 

mindspore/ccsrc/utils/utils.h

@@ -184,7 +184,10 @@ constexpr auto kControlDependBehindIndex = 2;
 // index define of depend
 constexpr auto kRealInputIndexInDepend = 1;
 constexpr auto kDependAttachNodeIndex = 2;
-
+// status of kernel select result
+const int kStatusReducePrecision = -1;
+const int kStatusRaisePrecision = 1;
+const int kStatusAllMatched = 0;
 // format
 constexpr auto kOpFormat_DEFAULT = "DefaultFormat";
 constexpr auto kOpFormat_NC1KHKWHWC0 = "NC1KHKWHWC0";