Fix: ApplyAdagrad CodeDEX.

mindspore/ccsrc/backend/kernel_compiler/cpu/apply_adagrad_cpu_kernel.cc

@@ -84,6 +84,7 @@ void ApplyAdagradCPUKernel::LaunchKernel(const std::vector<AddressPtr> &inputs)
 
   if (batch_size == 0) {
     MS_LOG(EXCEPTION) << "Error occur in launch kernel";
+    return;
   }
   while (start < length) {
     size_t end = (start + batch_size) > length ? length : (start + batch_size);
@@ -98,7 +99,8 @@ void ApplyAdagradCPUKernel::LaunchKernel(const std::vector<AddressPtr> &inputs)
 }
 
 template <typename T>
-void ApplyAdagradCPUKernel::LaunchApplyAdagrad(T var, T accum, T lr, T gradient, size_t start, size_t end) {
+void ApplyAdagradCPUKernel::LaunchApplyAdagrad(T const var, T const accum, const T lr, const T gradient, size_t start,
+                                               size_t end) {
   // DataType can only be float32 or float16, so eps will not be zero.
   using DataType = typename std::iterator_traits<T>::value_type;
   const DataType one = DataType(1);

mindspore/ccsrc/backend/kernel_compiler/cpu/apply_adagrad_cpu_kernel.h

@@ -38,7 +38,7 @@ class ApplyAdagradCPUKernel : public CPUKernel {
   template <typename T>
   void LaunchKernel(const std::vector<AddressPtr> &inputs);
   template <typename T>
-  void LaunchApplyAdagrad(T var, T accum, T lr, T gradient, size_t start, size_t end);
+  void LaunchApplyAdagrad(T const var, T const accum, const T lr, const T gradient, size_t start, size_t end);
   bool update_slots_{true};
   TypeId dtype_{kTypeUnknown};
 };