Fix the difference of Error type between graph&pynative mode

mindspore/ccsrc/frontend/operator/prim_structures.cc

@@ -150,11 +150,12 @@ AbstractBasePtr InferImplMakeSlice(const AnalysisEnginePtr &, const PrimitivePtr
   for (size_t index = 0; index < args_size; index++) {
     MS_EXCEPTION_IF_NULL(args_spec_list[index]);
     if (!args_spec_list[index]->isa<AbstractScalar>() && !args_spec_list[index]->isa<AbstractNone>()) {
-      MS_LOG(EXCEPTION) << "MakeSlice eval " << index << " parameter is neither AbstractScalar nor AbstractNone.";
+      MS_EXCEPTION(TypeError) << "MakeSlice eval " << index << " parameter is neither AbstractScalar nor AbstractNone.";
     }
     if (args_spec_list[index]->isa<AbstractScalar>() &&
         !dyn_cast<AbstractScalar>(args_spec_list[index])->BuildValue()->isa<Int32Imm>()) {
-      MS_LOG(EXCEPTION) << "MakeSlice eval " << index << " parameter is an AbstractScalar, but is not an int32 number.";
+      MS_EXCEPTION(TypeError) << "MakeSlice eval " << index
+                              << " parameter is an AbstractScalar, but is not an int32 number.";
     }
   }
   // Slice: start, end, step

tests/ut/python/ops/test_tuple_slice.py

@@ -114,13 +114,13 @@ test_cases = [
 
 test_cases_for_verify_exception = [
     ('SliceStartCross', {
-        'block': (NetWork_3(), {'exception': RuntimeError}),
+        'block': (NetWork_3(), {'exception': TypeError}),
         'desc_inputs': [Tensor(np.ones([2, 3, 4], np.int32)),
                         Tensor(np.zeros([2, 3, 4], np.int32)),
                         Tensor(np.ones([2, 3, 4], np.int32))],
     }),
     ('SliceStepZero', {
-        'block': (NetWork_3(), {'exception': RuntimeError}),
+        'block': (NetWork_3(), {'exception': TypeError}),
         'desc_inputs': [Tensor(np.ones([2, 3, 4], np.int32)),
                         Tensor(np.zeros([2, 3, 4], np.int32)),
                         Tensor(np.ones([2, 3, 4], np.int32))],