diff --git a/mindspore/lite/tools/common/node_util.cc b/mindspore/lite/tools/common/node_util.cc
index 1ad5189f12..9b5c452e45 100644
--- a/mindspore/lite/tools/common/node_util.cc
+++ b/mindspore/lite/tools/common/node_util.cc
@@ -79,7 +79,8 @@ static const std::vector<schema::PrimitiveType> int8OpList = {
   schema::PrimitiveType_Squeeze,      schema::PrimitiveType_Sub,
   schema::PrimitiveType_StridedSlice, schema::PrimitiveType_TopK,
   schema::PrimitiveType_Unsqueeze,    schema::PrimitiveType_MatMul,
-  schema::PrimitiveType_Pad,          schema::PrimitiveType_DeConv2D};
+  schema::PrimitiveType_Pad,          schema::PrimitiveType_DeConv2D,
+  schema::PrimitiveType_Scale};
 
 static const std::vector<schema::PrimitiveType> needInsertOpList = {
   schema::PrimitiveType_Eltwise, schema::PrimitiveType_Activation,   schema::PrimitiveType_Concat,
diff --git a/mindspore/lite/tools/converter/quantizer/aware_quantizer.cc b/mindspore/lite/tools/converter/quantizer/aware_quantizer.cc
index 3ec4cf5f6a..5913d474c2 100644
--- a/mindspore/lite/tools/converter/quantizer/aware_quantizer.cc
+++ b/mindspore/lite/tools/converter/quantizer/aware_quantizer.cc
@@ -106,7 +106,7 @@ STATUS AwareQuantizer::GenerateQuantParam() {
   for (auto graphInputIndex : graph->inputIndex) {
     auto status = mInputArray->SetInputArrayQP(graph, graphInputIndex);
     if (status != RET_OK) {
-      MS_LOG(ERROR) << "SetInputArrayQP failed";
+      MS_LOG(WARNING) << "SetInputArrayQP failed";
       return status;
     }
   }
@@ -121,8 +121,8 @@ STATUS AwareQuantizer::GenerateQuantParam() {
     }
     auto quantParamCalcer = quantParamRegister->GetQuantParamCalcer(GetCNodeTType(*node));
     if (quantParamCalcer == nullptr) {
-      MS_LOG(ERROR) << "Can not find QuantParamCalcer for " << node->name.c_str()
-                    << ", type: " << GetCNodeTTypeName(*node).c_str() << " set node to QuantNone and skip";
+      MS_LOG(WARNING) << "Can not find QuantParamCalcer for " << node->name.c_str()
+                      << ", type: " << GetCNodeTTypeName(*node).c_str() << " set node to QuantNone and skip";
       node->quantType = static_cast<schema::QuantType>(QuantType_QUANT_NONE);
     } else {
       auto status = quantParamCalcer->Calc(graph, *node);
@@ -154,7 +154,7 @@ STATUS AwareQuantizer::DoQuantize() {
         GetCNodeTType(*node) == schema::PrimitiveType_MatMul) {
       auto inputIndexes = node->inputIndex;
       if (inputIndexes.size() < 2) {
-        MS_LOG(ERROR) << node->name.c_str() << " node input has invalid inputs tensor count";
+        MS_LOG(WARNING) << node->name.c_str() << " node input has invalid inputs tensor count";
         return RET_ERROR;
       }
       // quant weight
@@ -162,7 +162,7 @@ STATUS AwareQuantizer::DoQuantize() {
       if (!weightTensor->quantParams.empty() && weightTensor->quantParams.at(0)->inited) {
         status = QuantConvWeight(graph, node.get());
         if (status != RET_OK) {
-          MS_LOG(ERROR) << "QuantConvWeight failed!";
+          MS_LOG(WARNING) << "QuantConvWeight failed!";
           return RET_ERROR;
         }
       }
@@ -172,7 +172,7 @@ STATUS AwareQuantizer::DoQuantize() {
         if (!biasTensor->quantParams.empty() && biasTensor->quantParams.at(0)->inited) {
           status = QuantConvBias(graph, node.get());
           if (status != RET_OK) {
-            MS_LOG(ERROR) << "QuantConvBias failed!";
+            MS_LOG(WARNING) << "QuantConvBias failed!";
             return RET_ERROR;
           }
         }
@@ -180,13 +180,15 @@ STATUS AwareQuantizer::DoQuantize() {
     } else if (GetCNodeTType(*node) == schema::PrimitiveType_DetectionPostProcess) {
       status = QuantDetectionPostProcessConstTensor(graph, node.get());
       if (status != RET_OK) {
-        MS_LOG(ERROR) << "QuantDetectionPostProcessConstTensor failed!";
+        MS_LOG(WARNING) << "QuantDetectionPostProcessConstTensor failed!";
         return RET_ERROR;
       }
-    } else if (GetCNodeTType(*node) == schema::PrimitiveType_Add) {
-      status = QuantAddConstTensor(graph, node.get());
+    } else if (GetCNodeTType(*node) == schema::PrimitiveType_Add ||
+               GetCNodeTType(*node) == schema::PrimitiveType_Scale ||
+               GetCNodeTType(*node) == schema::PrimitiveType_Mul) {
+      status = QuantArithmeticConstTensor(graph, node.get());
       if (status != RET_OK) {
-        MS_LOG(ERROR) << "QuantAddConstTensor failed!";
+        MS_LOG(WARNING) << "QuantArithmeticConstTensor failed!";
         return RET_ERROR;
       }
     }
@@ -203,7 +205,7 @@ STATUS AwareQuantizer::DoQuantize() {
   return RET_OK;
 }
 
-STATUS AwareQuantizer::QuantAddConstTensor(const schema::MetaGraphT *graph, schema::CNodeT *node) {
+STATUS AwareQuantizer::QuantArithmeticConstTensor(const schema::MetaGraphT *graph, schema::CNodeT *node) {
   MS_ASSERT(graph != nullptr);
   MS_ASSERT(node != nullptr);
   for (size_t i = 0; i < node->inputIndex.size(); i++) {
@@ -211,28 +213,40 @@ STATUS AwareQuantizer::QuantAddConstTensor(const schema::MetaGraphT *graph, sche
     MS_ASSERT(graph->allTensors.size() > inTensorIdx);
     auto &inTensor = graph->allTensors.at(inTensorIdx);
     MS_ASSERT(inTensor != nullptr);
-    if (inTensor->refCount == 999) {
-      switch (inTensor->dataType) {
-        case TypeId::kNumberTypeFloat: {
-          auto quantParam = GetTensorQuantParam(inTensor);
-          MS_ASSERT(quantParam != nullptr);
-          MS_ASSERT(quantParam->inited);
-          auto constTensorShapeSize = GetShapeSize(*(inTensor.get()));
-          vector<uint8_t> qDatas(constTensorShapeSize);
-          void *inData = inTensor->data.data();
-          auto *castedInData = static_cast<float *>(inData);
-          for (size_t j = 0; j < constTensorShapeSize; j++) {
-            qDatas[j] = QuantizeData<uint8_t>(castedInData[j], quantParam.get());
-          }
-          inTensor->data = std::move(qDatas);
-          inTensor->dataType = kNumberTypeUInt8;
-        } break;
-        case kNumberTypeUInt8:
-          break;
-        default:
-          MS_LOG(ERROR) << "Unsupported dataType: " << inTensor->dataType;
-          return RET_ERROR;
+    if (!inTensor->data.empty()) {
+      if (inTensor->dataType == TypeId::kNumberTypeInt8) {
+        continue;
       }
+      if (inTensor->dataType != TypeId::kNumberTypeFloat32 && inTensor->dataType != TypeId::kNumberTypeFloat &&
+          inTensor->dataType != TypeId::kNumberTypeUInt8) {
+        MS_LOG(WARNING) << node->name.c_str() << "'s weight data is not float or uint8";
+        return RET_ERROR;
+      }
+
+      auto quantParam = GetTensorQuantParam(inTensor);
+      MS_ASSERT(quantParam != nullptr);
+      MS_ASSERT(quantParam->inited);
+      auto constTensorShapeSize = GetShapeSize(*(inTensor.get()));
+      vector<int8_t> qDatas(constTensorShapeSize);
+      void *inData = inTensor->data.data();
+      if (inTensor->dataType == TypeId::kNumberTypeFloat ||
+          inTensor->dataType == TypeId::kNumberTypeFloat32) {  // normal awareing quant
+        auto *weightData = static_cast<float *>(inData);
+        for (size_t j = 0; j < constTensorShapeSize; j++) {
+          qDatas[j] = QuantizeData<int8_t>(weightData[j], quantParam.get());
+        }
+      } else {  // tflite awareing quant
+        auto *weightData = static_cast<uint8_t *>(inData);
+        for (size_t j = 0; j < constTensorShapeSize; j++) {
+          qDatas[j] = (int32_t)weightData[j] - 128;
+        }
+        quantParam->zeroPoint -= 128;
+        inTensor->quantParams.clear();
+        inTensor->quantParams.emplace_back(quantParam.release());
+      }
+
+      ::memcpy(inTensor->data.data(), qDatas.data(), constTensorShapeSize);
+      inTensor->dataType = TypeId::kNumberTypeInt8;
     }
   }
   return RET_OK;
@@ -245,21 +259,21 @@ STATUS AwareQuantizer::QuantDetectionPostProcessConstTensor(const schema::MetaGr
   MS_ASSERT(constTensor != nullptr);
   const auto *constData = reinterpret_cast<const float *>(constTensor->data.data());
 
-  if (constTensor->nodeType == schema::NodeType::NodeType_ValueNode &&
-      constTensor->dataType == TypeId::kNumberTypeFloat) {
+  if (!constTensor->data.empty() &&
+      (constTensor->dataType == TypeId::kNumberTypeFloat || constTensor->dataType == TypeId::kNumberTypeFloat32)) {
     size_t constTensorShapeSize = GetShapeSize(*constTensor);
     std::unique_ptr<QuantParamT> quantParam = GetTensorQuantParam(constTensor);
     if (quantParam == nullptr) {
       MS_LOG(ERROR) << "new QuantParamT failed";
       return RET_NULL_PTR;
     }
-    vector<uint8_t> qDatas(constTensorShapeSize);
+    vector<int8_t> qDatas(constTensorShapeSize);
     for (size_t j = 0; j < constTensorShapeSize; j++) {
       float rawData = constData[j];
-      qDatas[j] = QuantizeData<uint8_t>(rawData, quantParam.get());
+      qDatas[j] = QuantizeData<int8_t>(rawData, quantParam.get());
     }
-    constTensor->data = std::move(qDatas);
-    constTensor->dataType = TypeId::kNumberTypeUInt8;
+    ::memcpy(constTensor->data.data(), qDatas.data(), constTensorShapeSize);
+    constTensor->dataType = TypeId::kNumberTypeInt8;
   }
   return RET_OK;
 }
@@ -340,13 +354,14 @@ STATUS AwareQuantizer::QuantConvWeight(const schema::MetaGraphT *subGraph, schem
   }
   if (weightTensor->dataType != TypeId::kNumberTypeFloat32 && weightTensor->dataType != TypeId::kNumberTypeFloat &&
       weightTensor->dataType != TypeId::kNumberTypeUInt8) {
-    MS_LOG(ERROR) << "conv " << node->name.c_str() << "'s weight data is not float or uint8";
+    MS_LOG(WARNING) << "conv " << node->name.c_str() << "'s weight data is not float or uint8";
     return RET_ERROR;
   }
   size_t wShapeSize = GetShapeSize(*(weightTensor.get()));
   void *oriWeightData = weightTensor->data.data();
   MS_ASSERT(node->quantParam.at(1)->param.front() != nullptr);
   vector<int8_t> qDatas(wShapeSize);
+  // todo support perchannel
   auto weightQauntParam = GetTensorQuantParam(weightTensor);
   if (weightTensor->dataType == TypeId::kNumberTypeFloat ||
       weightTensor->dataType == TypeId::kNumberTypeFloat32) {  // normal awareing quant
diff --git a/mindspore/lite/tools/converter/quantizer/aware_quantizer.h b/mindspore/lite/tools/converter/quantizer/aware_quantizer.h
index f7038b1126..61d0318330 100644
--- a/mindspore/lite/tools/converter/quantizer/aware_quantizer.h
+++ b/mindspore/lite/tools/converter/quantizer/aware_quantizer.h
@@ -67,7 +67,7 @@ class AwareQuantizer : public FbQuantizer {
 
   STATUS GenerateDefaultQuantParam(const schema::MetaGraphT *subGraph);
 
-  STATUS QuantAddConstTensor(const schema::MetaGraphT *graph, schema::CNodeT *node);
+  STATUS QuantArithmeticConstTensor(const schema::MetaGraphT *graph, schema::CNodeT *node);
 
   STATUS QuantDetectionPostProcessConstTensor(const schema::MetaGraphT *subGraph, schema::CNodeT *node);
 
diff --git a/mindspore/lite/tools/converter/quantizer/calc_quant_param.cc b/mindspore/lite/tools/converter/quantizer/calc_quant_param.cc
index 2370c5e5e8..44c7f2acc2 100644
--- a/mindspore/lite/tools/converter/quantizer/calc_quant_param.cc
+++ b/mindspore/lite/tools/converter/quantizer/calc_quant_param.cc
@@ -474,6 +474,7 @@ QuantParamCalcRegister::QuantParamCalcRegister() {
     _registerMap[schema::PrimitiveType_Activation] = std::make_shared<CalcActivation>();
     _registerMap[schema::PrimitiveType_Add] = std::make_shared<CalcAdd>();
     _registerMap[schema::PrimitiveType_Mul] = commonCalcer;
+    _registerMap[schema::PrimitiveType_Scale] = commonCalcer;
     _registerMap[schema::PrimitiveType_Conv2D] = commonCalcer;
     _registerMap[schema::PrimitiveType_DeConv2D] = commonCalcer;
     _registerMap[schema::PrimitiveType_DepthwiseConv2D] = commonCalcer;