diff --git a/mindspore/lite/tools/converter/converter.cc b/mindspore/lite/tools/converter/converter.cc
index 3f3f5a03a3f..87ab8a9910f 100644
--- a/mindspore/lite/tools/converter/converter.cc
+++ b/mindspore/lite/tools/converter/converter.cc
@@ -90,7 +90,7 @@ MetaGraphT *Converter::Convert(const converter::Flags *flag) {
     return nullptr;
   }
 
-  // graph = anfTransform->Transform(graph);
+  graph = anfTransform->Transform(graph);
 
   CreateQuantizer(graph, flag);
   if (mQuantizer != nullptr) {
diff --git a/mindspore/lite/tools/converter/graphdef_transform.cc b/mindspore/lite/tools/converter/graphdef_transform.cc
index ec92083597d..d0240ed9f39 100644
--- a/mindspore/lite/tools/converter/graphdef_transform.cc
+++ b/mindspore/lite/tools/converter/graphdef_transform.cc
@@ -100,20 +100,20 @@ int GraphDefTransform::Transform(const converter::Flags &ctx) {
   //  }
 
   // fusion
-  {
-    Optimizer fusionOptimizer;
-    fusionOptimizer.AddPass(new (std::nothrow) ConvBiasAddFusionPass());
-    fusionOptimizer.AddPass(new (std::nothrow) ConvBNFusionPass());
-    fusionOptimizer.AddPass(new (std::nothrow) ConvScaleFusionPass());
-    fusionOptimizer.AddPass(new (std::nothrow) ConvReluFusionPass());
-    fusionOptimizer.AddPass(new (std::nothrow) ConvRelu6FusionPass());
-    fusionOptimizer.AddPass(new (std::nothrow) IsolatedNodeRemovePass());
-    status = fusionOptimizer.Run(graphDefT);
-    if (status != RET_OK && status != RET_NO_CHANGE) {
-      MS_LOG(ERROR) << "Run fusionOptimizer graphPasses Failed";
-      return status;
-    }
-  }
+  // {
+  //   Optimizer fusionOptimizer;
+  //   fusionOptimizer.AddPass(new (std::nothrow) ConvBiasAddFusionPass());
+  //   fusionOptimizer.AddPass(new (std::nothrow) ConvBNFusionPass());
+  //   fusionOptimizer.AddPass(new (std::nothrow) ConvScaleFusionPass());
+  //   fusionOptimizer.AddPass(new (std::nothrow) ConvReluFusionPass());
+  //   fusionOptimizer.AddPass(new (std::nothrow) ConvRelu6FusionPass());
+  //   fusionOptimizer.AddPass(new (std::nothrow) IsolatedNodeRemovePass());
+  //   status = fusionOptimizer.Run(graphDefT);
+  //   if (status != RET_OK && status != RET_NO_CHANGE) {
+  //     MS_LOG(ERROR) << "Run fusionOptimizer graphPasses Failed";
+  //     return status;
+  //   }
+  // }
 
   // weight format trans
   if (ctx.formatTrans) {
diff --git a/mindspore/lite/tools/optimizer/fusion/conv_biasadd_fusion.cc b/mindspore/lite/tools/optimizer/fusion/conv_biasadd_fusion.cc
index 2d8d6a86786..c7ebce22322 100644
--- a/mindspore/lite/tools/optimizer/fusion/conv_biasadd_fusion.cc
+++ b/mindspore/lite/tools/optimizer/fusion/conv_biasadd_fusion.cc
@@ -89,10 +89,10 @@ void GenConvNewBias(const FuncGraphPtr &func_graph, const CNodePtr &conv_node, c
   auto add_weight_param = bias_add_weight->cast<ParameterPtr>()->default_param();
   auto add_weight_tensor = std::dynamic_pointer_cast<ParamValueLite>(add_weight_param);
   auto add_weight_data = reinterpret_cast<float *>(add_weight_tensor->tensor_addr());
-
-  if (add_weight_tensor->tensor_shape().empty()) {
-    if (EOK != memset_s(add_bias_data, kernel_nums * sizeof(float), *add_weight_data, kernel_nums * sizeof(float))) {
-      MS_LOG(EXCEPTION) << "memset_s conv_bias_data failed";
+  auto add_weight_shape = add_weight_tensor->tensor_shape();
+  if (add_weight_shape.empty() || (add_weight_shape.size() == 1 && add_weight_shape[0] ==1)) {
+      for (size_t i = 0; i < kernel_nums; i++) {
+        add_bias_data[i] = *add_weight_data;
     }
   } else {
     if (EOK != memcpy_s(add_bias_data, kernel_nums * sizeof(float), add_weight_data, kernel_nums * sizeof(float))) {
diff --git a/mindspore/lite/tools/optimizer/fusion/conv_transform_fusion.cc b/mindspore/lite/tools/optimizer/fusion/conv_transform_fusion.cc
index ee7e56de6ce..e4f346e0cf7 100644
--- a/mindspore/lite/tools/optimizer/fusion/conv_transform_fusion.cc
+++ b/mindspore/lite/tools/optimizer/fusion/conv_transform_fusion.cc
@@ -145,8 +145,8 @@ const {
   // conv has bias,bias_flag true
   bool bias_flag = false;
   if (conv_bias_node != nullptr) {
-    auto bias_weight_param = conv_weight_node->cast<ParameterPtr>()->default_param();
-    auto bias_tensor = std::dynamic_pointer_cast<ParamValueLite>(bias_weight_param);
+    auto conv_bias_param = conv_bias_node->cast<ParameterPtr>()->default_param();
+    auto bias_tensor = std::dynamic_pointer_cast<ParamValueLite>(conv_bias_param);
     bias_data = reinterpret_cast<float *>(bias_tensor->tensor_addr());
     bias_flag = true;
   } else {
@@ -187,7 +187,7 @@ const void ConvTransformFusion::CalNewBiasTensor(float *bias_data, int kernel_nu
   MS_ASSERT(bias_data != nullptr);
   if (bias_flag) {
     auto tmp_bias_data = new(std::nothrow) float[kernel_num];
-    if (EOK != memset_s(bias_data, kernel_num * sizeof(float), 0, kernel_num * sizeof(float))) {
+    if (EOK != memset_s(tmp_bias_data, kernel_num * sizeof(float), 0, kernel_num * sizeof(float))) {
       MS_LOG(EXCEPTION) << "memset bias data failed";
     }
     for (size_t i = 0; i < kernel_num; i++) {