diff --git a/ge/host_kernels/gather_v2_kernel.cc b/ge/host_kernels/gather_v2_kernel.cc
index ee73626b..610d2c3b 100644
--- a/ge/host_kernels/gather_v2_kernel.cc
+++ b/ge/host_kernels/gather_v2_kernel.cc
@@ -208,7 +208,7 @@ Status GatherV2Kernel::GenData(const int64_t data_num, ConstGeTensorPtr tensor_x
       ret = ProcessAxis3<T>(tensor_x, output);
       break;
     default:
-      GELOGI("Only support 4 dims and below but input axis is %ld", axis);
+      GELOGI("Only support 4 dims and below but input axis is %ld.", axis);
       return NOT_CHANGED;
   }
   return ret;
@@ -267,7 +267,7 @@ Status GatherV2Kernel::Process(int64_t axis, DataType data_type, ConstGeTensorPt
       ret = GenData<uint64_t>(data_num, input_tensor_ptr, axis, output_ptr);
       break;
     default:
-      GELOGI("GatherV2Kernel does not support this Data type:%s", TypeUtils::DataTypeToSerialString(data_type).c_str());
+      GELOGI("GatherV2Kernel does not support this Data type:%s.", TypeUtils::DataTypeToSerialString(data_type).c_str());
       return NOT_CHANGED;
   }
   return ret;
@@ -278,7 +278,7 @@ Status GatherV2Kernel::SaveIndicesByDataType(ConstGeTensorPtr indices_tensor_ptr
     auto indices_ptr = const_cast<int32_t *>(reinterpret_cast<const int32_t *>(indices_tensor_ptr->GetData().data()));
     for (int64_t i = 0; i < indices_shape.GetShapeSize(); i++) {
       if (*(indices_ptr + i) < 0 || *(indices_ptr + i) >= x_shape.GetDim(axis)) {
-        GELOGW("indices %ld value is not in range [0, %ld)", i, x_shape.GetDim(axis));
+        GELOGW("indices %ld value is not in range [0, %ld).", i, x_shape.GetDim(axis));
         return NOT_CHANGED;
       }
       indicates_.push_back(*(indices_ptr + i));
@@ -288,7 +288,7 @@ Status GatherV2Kernel::SaveIndicesByDataType(ConstGeTensorPtr indices_tensor_ptr
     auto indices_ptr = const_cast<int64_t *>(reinterpret_cast<const int64_t *>(indices_tensor_ptr->GetData().data()));
     for (int64_t i = 0; i < indices_shape.GetShapeSize(); i++) {
       if (*(indices_ptr + i) < 0 || *(indices_ptr + i) >= x_shape.GetDim(axis)) {
-        GELOGW("indices %ld value is not in range [0, %ld)", i, x_shape.GetDim(axis));
+        GELOGW("indices %ld value is not in range [0, %ld).", i, x_shape.GetDim(axis));
         return NOT_CHANGED;
       }
       indicates_.push_back(*(indices_ptr + i));
@@ -330,13 +330,13 @@ Status GatherV2Kernel::Check(const OpDescPtr &op_desc_ptr, const vector<ConstGeT
   auto axis_shape = tensor2->GetTensorDesc().GetShape();
   // axis must be scalar
   if (axis_shape.GetDimNum() != 0) {
-    GELOGW("axis must be scalar but its shape is %zu", axis_shape.GetDimNum());
+    GELOGW("axis must be scalar but its shape is %zu.", axis_shape.GetDimNum());
     return NOT_CHANGED;
   }
   auto axis_data_type = tensor2->GetTensorDesc().GetDataType();
   bool is_valid_axis_data_type = axis_data_type == DT_INT32 || axis_data_type == DT_INT64;
   if (!is_valid_axis_data_type) {
-    GELOGW("axis datatype must be DT_INT32 or DT_INT64");
+    GELOGW("axis datatype must be DT_INT32 or DT_INT64.");
     return NOT_CHANGED;
   }
 
@@ -344,42 +344,42 @@ Status GatherV2Kernel::Check(const OpDescPtr &op_desc_ptr, const vector<ConstGeT
   auto indices_data_type = tensor1->GetTensorDesc().GetDataType();
   bool is_valid_indices_data_type = indices_data_type == DT_INT32 || indices_data_type == DT_INT64;
   if (!is_valid_indices_data_type) {
-    GELOGW("indices datatype must be DT_INT32 or DT_INT64");
+    GELOGW("indices datatype must be DT_INT32 or DT_INT64.");
     return NOT_CHANGED;
   }
   if (indices_shape.GetDimNum() > kMaxIndicatesDims) {
-    GELOGW("indices input only support 0 or 1 dims");
+    GELOGW("indices input only support 0 or 1 dims.");
     return NOT_CHANGED;
   }
   return SUCCESS;
 }
 void GatherV2Kernel::DebugPrint(int64_t axis, const GeShape &x_shape, const GeShape &indices_shape,
                                 const std::vector<int64_t> &y_shape) {
-  GELOGD("GatherV2Kernel axis:%ld x_shape:%zu indices_shape:%zu y_shape:%zu", axis, x_shape.GetDimNum(),
+  GELOGD("GatherV2Kernel axis:%ld x_shape:%zu indices_shape:%zu y_shape:%zu.", axis, x_shape.GetDimNum(),
          indices_shape.GetDimNum(), y_shape.size());
   for (size_t i = 0; i < x_shape.GetDimNum(); i++) {
-    GELOGD("GatherV2Kernel x_shape[%zu]: %ld", i, x_shape.GetDim(i));
+    GELOGD("GatherV2Kernel x_shape[%zu]: %ld.", i, x_shape.GetDim(i));
   }
   for (size_t i = 0; i < indices_shape.GetDimNum(); i++) {
-    GELOGD("GatherV2Kernel indices_shape[%zu]: %ld", i, indices_shape.GetDim(i));
+    GELOGD("GatherV2Kernel indices_shape[%zu]: %ld.", i, indices_shape.GetDim(i));
   }
   for (size_t i = 0; i < y_shape.size(); i++) {
-    GELOGD("GatherV2Kernel y_shape[%zu]: %ld", i, y_shape[i]);
+    GELOGD("GatherV2Kernel y_shape[%zu]: %ld.", i, y_shape[i]);
   }
   for (auto ele : indicates_) {
-    GELOGD("GatherV2Kernel indices:%ld", ele);
+    GELOGD("GatherV2Kernel indices:%ld.", ele);
   }
 }
 
 Status GatherV2Kernel::Compute(const OpDescPtr op_desc_ptr, const vector<ConstGeTensorPtr> &input,
                                vector<GeTensorPtr> &v_output) {
-  GELOGI("Enter GatherV2Kernel Process.");
+  GELOGI("Enter GatherV2Kernel Process");
   Status ret = Check(op_desc_ptr, input, v_output);
   if (ret != SUCCESS) {
-    GELOGW("param check failed.");
+    GELOGW("param check failed");
     return NOT_CHANGED;
   }
-  GELOGI("GatherV2Kernel[%s] start Process.", op_desc_ptr->GetName().c_str());
+  GELOGI("GatherV2Kernel[%s] start Process", op_desc_ptr->GetName().c_str());
   ConstGeTensorPtr tensor0 = input.at(kGatherV2InputIndexZero);
   ConstGeTensorPtr tensor1 = input.at(kGatherV2InputIndexOne);
   ConstGeTensorPtr tensor2 = input.at(kGatherV2InputIndexTwo);
@@ -394,7 +394,7 @@ Status GatherV2Kernel::Compute(const OpDescPtr op_desc_ptr, const vector<ConstGe
   axis = axis >= 0 ? axis : axis + x_shape.GetDimNum();
   // check axis value
   if (axis < 0 || (axis + 1) > static_cast<int64_t>(x_shape.GetDimNum())) {
-    GELOGW("axis is invalid");
+    GELOGW("axis is invalid!");
     return NOT_CHANGED;
   }
   auto indices_data_type = tensor1->GetTensorDesc().GetDataType();
@@ -407,7 +407,7 @@ Status GatherV2Kernel::Compute(const OpDescPtr op_desc_ptr, const vector<ConstGe
   // check input data type
   auto x_data_type = tensor0->GetTensorDesc().GetDataType();
   if (supported_type.find(x_data_type) == supported_type.end()) {
-    GELOGI("GatherV2Kernel does not support this Data type:%s", TypeUtils::DataTypeToSerialString(x_data_type).c_str());
+    GELOGI("GatherV2Kernel does not support this Data type:%s.", TypeUtils::DataTypeToSerialString(x_data_type).c_str());
     return NOT_CHANGED;
   }
   // calc output shape
@@ -442,13 +442,13 @@ Status GatherV2Kernel::Compute(const OpDescPtr op_desc_ptr, const vector<ConstGe
   auto ret_y = CalcStride(ystride_, y_shape);
   ret = (ret_x == SUCCESS && ret_y == SUCCESS) ? SUCCESS : NOT_CHANGED;
   if (ret != SUCCESS) {
-    GELOGE(ret, "CalcStride Failed");
+    GELOGE(ret, "CalcStride Failed.");
     return ret;
   }
 
   ret = Process(axis, x_data_type, tensor0, output_ptr);
   if (ret != SUCCESS) {
-    GELOGE(ret, "GenData failed, data_type: %s", TypeUtils::DataTypeToSerialString(x_data_type).c_str());
+    GELOGE(ret, "GenData failed, data_type: %s.", TypeUtils::DataTypeToSerialString(x_data_type).c_str());
     return ret;
   }
 
diff --git a/ge/host_kernels/strided_slice_kernel.cc b/ge/host_kernels/strided_slice_kernel.cc
index c7e4b2c8..ca051609 100644
--- a/ge/host_kernels/strided_slice_kernel.cc
+++ b/ge/host_kernels/strided_slice_kernel.cc
@@ -45,7 +45,7 @@ bool IsEllipsisMaskValid(const GeTensorDescPtr &input_desc, const uint32_t ellip
         ++ellipsis_num;
       }
       if (ellipsis_num > 1) {
-        GELOGW("Only one non-zero bit is allowed in ellipsis_mask.");
+        GELOGW("Only one non-zero bit is allowed in ellipsis_mask");
         return false;
       }
     }
@@ -84,14 +84,14 @@ void GetOriginStrideVec(const std::vector<ge::ConstGeTensorPtr> &input, vector<i
 }  // namespace
 Status StridedSliceKernel::Compute(const ge::OpDescPtr attr, const std::vector<ge::ConstGeTensorPtr> &input,
                                    vector<ge::GeTensorPtr> &v_output) {
-  GELOGD("StridedSliceKernel in.");
+  GELOGD("StridedSliceKernel in");
   // 1.Check input and attrs
   if (CheckAndGetAttr(attr) != SUCCESS) {
-    GELOGW("Check and get attrs failed.Ignore kernel.");
+    GELOGW("Check and get attrs failed.Ignore kernel");
     return NOT_CHANGED;
   }
   if (CheckInputParam(input) != SUCCESS) {
-    GELOGW("Check input params failed.Ignore kernel.");
+    GELOGW("Check input params failed.Ignore kernel");
     return NOT_CHANGED;
   }
   // 2.Init param with mask attrs.
@@ -100,7 +100,7 @@ Status StridedSliceKernel::Compute(const ge::OpDescPtr attr, const std::vector<g
   std::vector<int64_t> output_dims;
   std::vector<int64_t> stride_vec;
   if (InitParamWithAttrs(input, input_dims, begin_vec, output_dims, stride_vec) != SUCCESS) {
-    GELOGW("Init param with mask attrs failed.Ignore kernel.");
+    GELOGW("Init param with mask attrs failed.Ignore kernel");
     return NOT_CHANGED;
   }
 
@@ -114,13 +114,13 @@ Status StridedSliceKernel::Compute(const ge::OpDescPtr attr, const std::vector<g
   auto output_tensor_desc = attr->GetOutputDesc(0);
   GeTensorPtr output_ptr = MakeShared<GeTensor>(output_tensor_desc);
   if (output_ptr == nullptr) {
-    GELOGE(MEMALLOC_FAILED, "MakeShared GeTensor failed, node name %s.", attr->GetName().c_str());
+    GELOGE(MEMALLOC_FAILED, "MakeShared GeTensor failed, node name %s", attr->GetName().c_str());
     return NOT_CHANGED;
   }
   auto ret = OpUtils::SetOutputSliceData(data, static_cast<int64_t>(data_size), data_type, input_dims, begin_vec,
                                          output_dims, output_ptr.get(), stride_vec);
   if (ret != SUCCESS) {
-    GELOGE(INTERNAL_ERROR, "SetOutputSliceData failed.");
+    GELOGE(INTERNAL_ERROR, "SetOutputSliceData failed");
     return NOT_CHANGED;
   }
 
@@ -133,18 +133,18 @@ Status StridedSliceKernel::Compute(const ge::OpDescPtr attr, const std::vector<g
   GetOutputDims(final_dim_size, output_dims, v_dims);
   t_d.SetShape(GeShape(v_dims));
   v_output.push_back(output_ptr);
-  GELOGI("StridedSliceKernel success.");
+  GELOGI("StridedSliceKernel success");
   return SUCCESS;
 }
 Status StridedSliceKernel::CheckAndGetAttr(const OpDescPtr &attr) {
   if (attr == nullptr) {
-    GELOGE(PARAM_INVALID, "input opdescptr is nullptr.");
+    GELOGE(PARAM_INVALID, "input opdescptr is nullptr");
     return PARAM_INVALID;
   }
   // Get all op attr value of strided_slice
   for (auto &attr_2_value : attr_value_map_) {
     if (!AttrUtils::GetInt(attr, attr_2_value.first, attr_2_value.second)) {
-      GELOGE(PARAM_INVALID, "Get %s attr failed.", attr_2_value.first.c_str());
+      GELOGE(PARAM_INVALID, "Get %s attr failed", attr_2_value.first.c_str());
       return PARAM_INVALID;
     }
   }
@@ -159,7 +159,7 @@ Status StridedSliceKernel::CheckAndGetAttr(const OpDescPtr &attr) {
 }
 Status StridedSliceKernel::CheckInputParam(const std::vector<ConstGeTensorPtr> &input) {
   if (input.size() != kStridedSliceInputSize) {
-    GELOGE(PARAM_INVALID, "The number of input for strided slice must be %zu.", kStridedSliceInputSize);
+    GELOGE(PARAM_INVALID, "The number of input for strided slice must be %zu", kStridedSliceInputSize);
     return PARAM_INVALID;
   }
 
@@ -178,11 +178,11 @@ Status StridedSliceKernel::CheckInputParam(const std::vector<ConstGeTensorPtr> &
   auto stride_tensor_desc = begin_tensor->GetTensorDesc();
   if (begin_tensor_desc.GetDataType() != end_tensor_desc.GetDataType() ||
       end_tensor_desc.GetDataType() != stride_tensor_desc.GetDataType()) {
-    GELOGW("Data type of StridedSlice OP(begin,end,strides) must be same.");
+    GELOGW("Data type of StridedSlice OP(begin,end,strides) must be same");
     return PARAM_INVALID;
   }
   if (kIndexNumberType.find(begin_tensor_desc.GetDataType()) == kIndexNumberType.end()) {
-    GELOGW("Data type of StridedSlice OP(begin,end,strides) must be int32 or int64.");
+    GELOGW("Data type of StridedSlice OP(begin,end,strides) must be int32 or int64");
     return PARAM_INVALID;
   }
 
@@ -190,7 +190,7 @@ Status StridedSliceKernel::CheckInputParam(const std::vector<ConstGeTensorPtr> &
   auto x_data_type = weight0->GetTensorDesc().GetDataType();
   auto x_data_size = GetSizeByDataType(x_data_type);
   if (x_data_size < 0) {
-    GELOGW("Data type of x input %s is not supported.", TypeUtils::DataTypeToSerialString(x_data_type).c_str());
+    GELOGW("Data type of x input %s is not supported", TypeUtils::DataTypeToSerialString(x_data_type).c_str());
     return PARAM_INVALID;
   }
   size_t weight0_size = weight0->GetData().size() / x_data_size;
@@ -198,12 +198,12 @@ Status StridedSliceKernel::CheckInputParam(const std::vector<ConstGeTensorPtr> &
   size_t end_data_size = end_tensor->GetData().size();
   size_t stride_data_size = stride_tensor->GetData().size();
   if ((weight0_size == 0) || (begin_data_size == 0) || (end_data_size == 0) || (stride_data_size == 0)) {
-    GELOGW("Data size of inputs is 0.");
+    GELOGW("Data size of inputs is 0");
     return PARAM_INVALID;
   }
   // check dim size
   if (!((begin_data_size == end_data_size) && (end_data_size == stride_data_size))) {
-    GELOGW("The sizes of begin, end and stride is not supported.");
+    GELOGW("The sizes of begin, end and stride is not supported");
     return PARAM_INVALID;
   }
   return SUCCESS;
@@ -250,15 +250,15 @@ Status StridedSliceKernel::InitParamWithAttrs(const std::vector<ConstGeTensorPtr
       end_i = x_dims.at(i);
       stride_i = 1;
     }
-    GELOGD("Before mask calculate. Begin is : %ld\t,end is : %ld\t stride is : %ld\t x_dim_i is : %ld.",
+    GELOGD("Before mask calculate. Begin is : %ld\t,end is : %ld\t stride is : %ld\t x_dim_i is : %ld",
            begin_i, end_i, stride_i, x_dims.at(i));
     auto ret = MaskCal(i, begin_i, end_i, x_dims.at(i));
     if (ret != SUCCESS) {
-      GELOGW("MaskCal failed, because of data overflow.");
+      GELOGW("MaskCal failed, because of data overflow");
       return NOT_CHANGED;
     }
     int64_t dim_final;
-    GELOGD("Before stride calculate. Begin is : %ld\t,end is : %ld\t stride is : %ld\t x_dim_i is : %ld.",
+    GELOGD("Before stride calculate. Begin is : %ld\t,end is : %ld\t stride is : %ld\t x_dim_i is : %ld",
            begin_i, end_i, stride_i, x_dims.at(i));
     (void) StrideCal(x_dims.at(i), begin_i, end_i, stride_i, dim_final);
     output_dims.push_back(dim_final);
@@ -273,7 +273,7 @@ void StridedSliceKernel::ExpandDimsWithNewAxis(const ConstGeTensorPtr &begin_ten
                                                vector<int64_t> &x_dims) {
   auto begin_data_type_size = GetSizeByDataType(begin_tensor->GetTensorDesc().GetDataType());
   if (begin_data_type_size == 0) {
-    GELOGW("Param begin_data_type_size should not be zero.");
+    GELOGW("Param begin_data_type_size should not be zero");
     return;
   }
   size_t begin_vec_size = begin_tensor->GetData().size() / begin_data_type_size;