fix kernel by kernel and mindRT parameter bug

mindspore/ccsrc/debug/debugger/debugger.cc

@@ -1574,7 +1574,8 @@ void Debugger::LoadSingleParameterMindRT(const AnfNodePtr &node) {
     debug_services_->MoveTensorCurrentToPrev(tensor_name);
   }
   // Keep_prev is True for parameters.
-  bool ret = device_addr->LoadMemToHost(tensor_name, 0, format, int_shapes, type, 0, true, root_graph_id);
+  // force update for parameters.
+  bool ret = device_addr->LoadMemToHost(tensor_name, 0, format, int_shapes, type, 0, true, root_graph_id, true);
 
   if (!ret) {
     MS_LOG(ERROR) << "LoadMemToHost:"

mindspore/ccsrc/debug/debugger/debugger_utils.cc

@@ -155,7 +155,8 @@ bool CheckReadData(const CNodePtr &cnode) {
     if (dump_json_parser.NeedDump(kernel_name)) {
       read_data = true;
     }
-  } else if (debugger->debugger_enabled()) {
+  }
+  if (debugger->debugger_enabled()) {
     read_data = debugger->ReadNodeDataRequired(cnode);
   }
   return read_data;

mindspore/ccsrc/plugin/device/ascend/hal/device/ascend_device_address.cc

@@ -649,11 +649,11 @@ bool AscendDeviceAddress::DumpMemToFile(const std::string &filepath, const std::
  */
 bool AscendDeviceAddress::LoadMemToHost(const std::string &tensor_name, int execution_order, const std::string &,
                                         const ShapeVector &host_shape, TypeId host_type, size_t slot, bool keep_prev,
-                                        uint32_t root_graph_id) const {
+                                        uint32_t root_graph_id, bool force_update) const {
   bool ret = false;
   auto debugger = Debugger::GetInstance();
   MS_EXCEPTION_IF_NULL(debugger);
-  if (debugger->TensorExistsInCurrent(tensor_name)) {
+  if (debugger->TensorExistsInCurrent(tensor_name) && !force_update) {
     MS_LOG(INFO) << tensor_name << " already loaded for this step so not loading it again.";
     return true;
   }

mindspore/ccsrc/plugin/device/ascend/hal/device/ascend_device_address.h

@@ -62,7 +62,7 @@ class AscendDeviceAddress : public DeviceAddress {
 #ifdef ENABLE_DEBUGGER
   bool LoadMemToHost(const std::string &tensor_name, int execution_order, const std::string &host_fmt,
                      const ShapeVector &host_shape, TypeId host_type, size_t slot, bool keep_prev,
-                     uint32_t root_graph_id = 0) const override;
+                     uint32_t root_graph_id = 0, bool force_update = 0) const override;
 #endif
 
  private:

mindspore/ccsrc/plugin/device/gpu/hal/device/gpu_device_address.cc

@@ -185,14 +185,14 @@ GPUDeviceAddress::~GPUDeviceAddress() { ClearDeviceMemory(); }
 #ifdef ENABLE_DEBUGGER
 bool GPUDeviceAddress::LoadMemToHost(const std::string &tensor_name, int execution_order, const std::string &host_fmt,
                                      const ShapeVector &host_shape, TypeId host_type, size_t slot, bool keep_prev,
-                                     uint32_t root_graph_id) const {
+                                     uint32_t root_graph_id, bool force_update) const {
   bool ret = false;
   if (size_ == 0) {
     return true;
   }
 
   MS_EXCEPTION_IF_NULL(Debugger::GetInstance());
-  if (Debugger::GetInstance()->TensorExistsInCurrent(tensor_name)) {
+  if (Debugger::GetInstance()->TensorExistsInCurrent(tensor_name) && !force_update) {
     MS_LOG(INFO) << tensor_name << " already loaded for this step so not loading it again.";
     return true;
   }

mindspore/ccsrc/plugin/device/gpu/hal/device/gpu_device_address.h

@@ -56,7 +56,7 @@ class GPUDeviceAddress : public DeviceAddress {
 #ifdef ENABLE_DEBUGGER
   bool LoadMemToHost(const std::string &tensor_name, int execution_order, const std::string &host_fmt,
                      const ShapeVector &host_shape, TypeId host_type, size_t slot, bool keep_prev,
-                     uint32_t root_graph_id = 0) const override;
+                     uint32_t root_graph_id = 0, bool force_update = 0) const override;
 #endif
 
  private:

mindspore/ccsrc/runtime/device/device_address.h

@@ -141,7 +141,7 @@ class DeviceAddress : public mindspore::DeviceSync {
 #ifdef ENABLE_DEBUGGER
   virtual bool LoadMemToHost(const std::string &tensor_name, int execution_order, const std::string &host_fmt,
                              const ShapeVector &host_shape, TypeId host_type, size_t slot, bool keep_prev,
-                             uint32_t root_graph_id = 0) const {
+                             uint32_t root_graph_id = 0, bool force_update = 0) const {
     return true;
   }
 #endif