!27174 modify VM error whitelist

Merge pull request !27174 from zhaosida/code_clean_master

mindspore/ccsrc/backend/kernel_compiler/tbe/tbe_utils.cc

@@ -171,9 +171,9 @@ void TbeUtils::SaveJsonInfo(const std::string &json_name, const std::string &inf
   std::string path = config_path + kCceKernelMeta + json_name + kInfoSuffix;
   auto realpath = Common::CreatePrefixPath(path);
   if (!realpath.has_value()) {
-    MS_LOG(WARNING) << "Invalid path is: " << realpath.value()
-                    << "Please check (1) whether the path exists, (2) whether the path has the access "
-                    << "permission, (3) whether the path is too long. ";
+    MS_LOG(WARNING) << "Invalid environment variable '" << kCOMPILER_CACHE_PATH
+                    << "', the path is: " << realpath.value() << ". Please check (1) whether the path exists, "
+                    << "(2) whether the path has the access permission, (3) whether the path is too long. ";
     return;
   }
   ChangeFileMode(realpath.value(), S_IWUSR);

mindspore/ccsrc/backend/session/session_basic.cc

@@ -1872,8 +1872,8 @@ void SessionBasic::Summary(KernelGraph *graph) {
   static bool is_first = true;
   if (is_first && !IsSupportSummary()) {
     is_first = false;
-    MS_LOG(ERROR) << "The Summary operator can not collect data correctly. Detail: the data sink mode is used and the"
-                     " sink size(in model.train() python api) is not equal to 1.";
+    MS_LOG(WARNING) << "The Summary operator can not collect data correctly. Detail: the data sink mode is used and the"
+                       " sink size(in model.train() python api) is not equal to 1.";
   }
   SetSummaryNodes(graph);
   auto summary_outputs = graph->summary_nodes();
@@ -2482,7 +2482,7 @@ void PreProcessOnSplitIndex(const KernelGraphPtr &graph, vector<uint32_t> *split
   if (split_index_num >= grads_count) {
     MS_LOG(WARNING) << "The context configuration all_reduce_fusion_config's upper boundary value should be smaller "
                     << "than total grads count: " << grads_count << ", but got: " << *split_index
-                    << ". Now all AllReduce operations will be fused into one AllReduce operation.";
+                    << ". Now all AllReduce operators will be fused into one AllReduce operator.";
     split_index->clear();
     split_index->push_back(grads_count - 1);
   } else if (split_index_num < grads_count - 1) {

mindspore/ccsrc/runtime/device/ascend/kernel_select_ascend.cc

@@ -284,7 +284,7 @@ bool TagRaiseReduce(const std::shared_ptr<kernel::KernelBuildInfo> &kernel_build
   }
   if (flag) {
     auto node_name = AnfAlgo::GetCNodeName(cnode);
-    MS_LOG(WARNING) << "Node:[" << node_name << "] don't support int64, reduce precision from int64 to int32.";
+    MS_LOG(WARNING) << "Operator:[" << node_name << "] don't support int64, reduce precision from int64 to int32.";
   }
   return true;
 }
@@ -491,8 +491,9 @@ KernelSelectStatus SelectCustomKernelInfo(const CNodePtr &kernel_node, KernelTyp
   } else if (func_type == kCustomTypeAICPU) {
     *kernel_type = KernelType::AICPU_KERNEL;
   } else {
-    MS_LOG(EXCEPTION) << "Unsupported func type for Custom op on Ascend, it should be 'tbe', 'ir_builder', "
-                      << "'tvm_compute' or 'hybrid', but got [" << func_type << "] for Custom op [" << op_name << "]";
+    MS_LOG(EXCEPTION) << "Unsupported func type for Custom operator on Ascend, it should be 'tbe', 'ir_builder', "
+                      << "'tvm_compute' or 'hybrid', but got [" << func_type << "]"
+                      << " for Custom operator [" << op_name << "]";
   }
   static const std::map<KernelType, kernel::OpImplyType> kKernelImplyTypeMap{
     {KernelType::TBE_KERNEL, kernel::OpImplyType::kTBE},

mindspore/ccsrc/runtime/device/ascend/tasksink/task_generator.cc

@@ -325,7 +325,7 @@ void TaskGenerator::DumpTaskInfo(const std::string &real_filename) {
   }
   already_printed = true;
   MS_LOG(WARNING) << "The functionality of dumping task debug info is disabled, "
-                  << "please enable ENABLE_DUMP_IR with '-D on' and recomiple source.";
+                  << "please recompile the source codes with '-D on' option.";
 }
 void TaskGenerator::DumpTaskInfo(const string &real_filename,
                                  const std::vector<TaskDebugInfoPtr> &task_debug_info_list) {
@@ -335,7 +335,7 @@ void TaskGenerator::DumpTaskInfo(const string &real_filename,
   }
   already_printed = true;
   MS_LOG(WARNING) << "The functionality of dumping task debug info is disabled, "
-                  << "please enable ENABLE_DUMP_IR with '-D on' and recomiple source.";
+                  << "please recompile the source codes with '-D on' option.";
 }
 #endif
 

mindspore/ccsrc/runtime/device/cpu/kernel_select_cpu.cc

@@ -431,13 +431,13 @@ void SetKernelInfo(const CNodePtr &kernel_node) {
         kernel::CPUKernelRegistrar(op_name, KernelAttr(),
                                    []() { return std::make_shared<kernel::CustomAOTCpuKernel>(); });
       } else {
-        MS_LOG(EXCEPTION) << "Unsupported func type for Custom op on CPU, it should be 'pyfunc' or 'aot', but got ["
-                          << tp << "] for Custom op [" << op_name << "]";
+        MS_LOG(EXCEPTION) << "Unsupported func type for Custom operator on CPU, it should be 'pyfunc' or 'aot', "
+                          << "but got [" << tp << "] for Custom operator [" << op_name << "]";
       }
     }
     // If Custom op has not set reg info, then infer info from inputs
     if (mindspore::kernel::OpLib::FindOp(op_name, kernel::OpImplyType::kCPU) == nullptr) {
-      MS_LOG(WARNING) << "Not find operator information for Custom op[" << op_name << "]. "
+      MS_LOG(WARNING) << "Not find operator information for Custom operator[" << op_name << "]. "
                       << "Infer operator information from inputs. For more details, "
                       << "please refer to 'mindspore.ops.Custom' at https://www.mindspore.cn.";
       return UpdateCustomKernelBuildInfoAndAttrs(kernel_node);

mindspore/ccsrc/runtime/device/kernel_runtime.cc

@@ -960,7 +960,7 @@ void KernelRuntime::AssignStaticMemoryValueNode(const session::KernelGraph &grap
           }
         } else {
           if (mem_manager_->MallocMem(kStaticMem, device_address->size_, device_address, graph.graph_id())) {
-            MS_LOG(EXCEPTION) << "MallocMem kStaticMem failed";
+            MS_LOG(EXCEPTION) << "MallocStaticMem failed";
           }
         }
       }