[Core] Fix the missing of the input and output scale after the...

[Core] Fix the missing of the input and output scale after the lite_elementwise_activation_fuse_pass is applied (#4066)

lite/core/mir/fusion/elementwise_add_activation_fuser.cc

@@ -75,9 +75,8 @@ void ElementwiseActivationFuser::InsertNewNode(SSAGraph* graph,
 }
 
 cpp::OpDesc ElementwiseActivationFuser::GenOpDesc(const key2nodes_t& matched) {
-  auto* desc = matched.at("elt")->stmt()->op_info();
-
-  cpp::OpDesc op_desc;
+  auto op_desc = *matched.at("elt")->stmt()->op_info();
+  auto* act_op_desc = matched.at("act")->stmt()->op_info();
   if (eltwise_type_ == "elementwise_add") {
     op_desc.SetType("fusion_elementwise_add_activation");
   } else if (eltwise_type_ == "elementwise_sub") {
@@ -87,13 +86,12 @@ cpp::OpDesc ElementwiseActivationFuser::GenOpDesc(const key2nodes_t& matched) {
   } else {
     LOG(FATAL) << "not supported elementwise_type: " << eltwise_type_;
   }
-
-  op_desc.SetInput("X", {matched.at("x")->arg()->name});
-  op_desc.SetInput("Y", {matched.at("y")->arg()->name});
-  op_desc.SetOutput("Out", {matched.at("output")->arg()->name});
-
-  op_desc.SetAttr("axis", desc->GetAttr<int>("axis"));
   op_desc.SetAttr("act_type", act_type_);
+  auto& out_name = matched.at("output")->arg()->name;
+  op_desc.SetOutput("Out", {out_name});
+  if (act_op_desc->HasOutputScale(out_name)) {
+    op_desc.SetOutputScale(out_name, act_op_desc->GetOutputScale(out_name));
+  }
   return op_desc;
 }
 

lite/core/mir/fusion/scale_activation_fuser.cc

@@ -61,20 +61,23 @@ void ScaleActivationFuser::InsertNewNode(SSAGraph* graph,
 }
 
 cpp::OpDesc ScaleActivationFuser::GenOpDesc(const key2nodes_t& matched) {
-  cpp::OpDesc op_desc = *matched.at("scale")->stmt()->op_info();
-  op_desc.SetOutput("Out", {matched.at("output")->arg()->name});
-  cpp::OpDesc act_op_desc = *matched.at("act")->stmt()->op_info();
-
+  auto op_desc = *matched.at("scale")->stmt()->op_info();
+  auto* act_op_desc = matched.at("act")->stmt()->op_info();
   op_desc.SetAttr("activation_type", act_type_);
   if (act_type_ == "relu") {
     op_desc.SetAttr("fuse_relu", true);
   } else if (act_type_ == "relu6") {
-    float alpha = act_op_desc.GetAttr<float>("threshold");
+    float alpha = act_op_desc->GetAttr<float>("threshold");
     op_desc.SetAttr("alpha", alpha);
   } else if (act_type_ == "leaky_relu") {
-    float alpha = act_op_desc.GetAttr<float>("alpha");
+    float alpha = act_op_desc->GetAttr<float>("alpha");
     op_desc.SetAttr("alpha", alpha);
   }
+  auto& out_name = matched.at("output")->arg()->name;
+  op_desc.SetOutput("Out", {out_name});
+  if (act_op_desc->HasOutputScale(out_name)) {
+    op_desc.SetOutputScale(out_name, act_op_desc->GetOutputScale(out_name));
+  }
   return op_desc;
 }
 

lite/core/mir/quantized_op_attributes_inference_pass.cc

@@ -32,6 +32,7 @@ void QuantizedOpAttributesInferencePass::Apply(
   // Only for fully quantized model which is only supported by MTK and RK NPU.
   // Replace the output_scale with the input_scale of the adjacent quantized
   // ops, and fix the missing of the attribute 'enable_int8'.
+  VLOG(5) << "\n" << Visualize(graph.get());
   for (auto& op_node : graph->StmtTopologicalOrder()) {
     if (!op_node->IsStmt()) continue;
     auto& inst = op_node->AsStmt();