fix ci error

paddle/fluid/lite/core/mir/fusion/quant_dequant_op_fuser.cc

@@ -99,15 +99,12 @@ void QuantDequantOpFuser::InsertNewNode(SSAGraph* graph,
   const int kNumFields = 5;
   const int kQuantizedWeightOffset = 0;
   const int kQuantizedOpOffset = 1;
-  const int kQuantizedOpOutOffset = 2;
   const int kDequantOpOffset = 3;
   const int kDequantOpOutOffset = 4;
 
   auto* quant_op_input = matched.at("quant_op_input");
   auto* quant_op_in_scale = matched.at("quant_op_in_scale");
   auto* quant_op = matched.at("quant_op");
-  auto* quant_op_out_scale = matched.at("quant_op_out_scale");
-  auto* quant_op_out = matched.at("quant_op_out");
 
   std::vector<Node*> nodes;
   for (int i = 0; i < times_; i++) {

paddle/fluid/lite/core/mir/fusion/quant_dequant_op_fuser.h

@@ -23,6 +23,18 @@ namespace lite {
 namespace mir {
 namespace fusion {
 
+/* The model trained by fluid quantization is a simulation of real int8.
+ * The quantized Ops(conv2d, mul, depthwise conv2d etc) have fake_quantop
+ * in front  and fake_dequantop behind.
+ *
+ * When in int8 mode, the pattern like "fake_quant + quantized_op +
+ * fake_dequant"
+ * can be detected by this fuser. The fuser extract the input_scale and
+ * the weight_scale info from fake_quant, fake_dequant op and fuse those into
+ * the quantized_op.
+ * In addition, the fuser delete fake_quant and fake_dequant op in the graph at
+ * the last.
+ */
 class QuantDequantOpFuser : public FuseBase {
  public:
   explicit QuantDequantOpFuser(const std::string& op_type,

paddle/fluid/lite/core/optimizer.h

@@ -48,22 +48,22 @@ class Optimizer {
 
     if (passes.empty()) {
       RunPasses(std::vector<std::string>{{
-          "lite_quant_dequant_fuse_pass",             //
-          "lite_conv_bn_fuse_pass",                   //
+          "lite_quant_dequant_fuse_pass",                    //
+          "lite_conv_bn_fuse_pass",                          //
           "lite_conv_elementwise_add_activation_fuse_pass",  //
 #ifdef LITE_WITH_LIGHT_WEIGHT_FRAMEWORK
           "lite_elementwise_add_activation_fuse_pass",  //
 #endif
-          "lite_fc_fuse_pass",                        //
-          "static_kernel_pick_pass",                  //
-          "variable_place_inference_pass",            //
-          "argument_type_display_pass",               //
-          "type_target_transform_pass",               //
-          "variable_place_inference_pass",            //
-          "argument_type_display_pass",               //
-          "io_copy_kernel_pick_pass",                 //
-          "variable_place_inference_pass",            //
-          "runtime_context_assign_pass",  //
+          "lite_fc_fuse_pass",              //
+          "static_kernel_pick_pass",        //
+          "variable_place_inference_pass",  //
+          "argument_type_display_pass",     //
+          "type_target_transform_pass",     //
+          "variable_place_inference_pass",  //
+          "argument_type_display_pass",     //
+          "io_copy_kernel_pick_pass",       //
+          "variable_place_inference_pass",  //
+          "runtime_context_assign_pass",    //
       }});
     } else {
       RunPasses(passes);

paddle/fluid/lite/operators/fake_dequantize_max_abs.h

@@ -33,9 +33,9 @@ class FakeDequantizeMaxAbsOpLite : public OpLite {
 
   explicit FakeDequantizeMaxAbsOpLite(const std::string &type) : OpLite(type) {}
 
-  bool CheckShape() const override {}
+  bool CheckShape() const override { return true; }
 
-  bool InferShape() const override {}
+  bool InferShape() const override { return true; }
 
   bool AttachImpl(const cpp::OpDesc &op_desc, lite::Scope *scope) override {
     auto x = op_desc.Input("X").front();

paddle/fluid/lite/operators/fake_quantize_moving_avg_max_abs.h

@@ -34,9 +34,9 @@ class FakeQuantizeMovingAvgMaxAbsOpLite : public OpLite {
   explicit FakeQuantizeMovingAvgMaxAbsOpLite(const std::string &type)
       : OpLite(type) {}
 
-  bool CheckShape() const override {}
+  bool CheckShape() const override { return true; }
 
-  bool InferShape() const override {}
+  bool InferShape() const override { return true; }
 
   bool AttachImpl(const cpp::OpDesc &op_desc, lite::Scope *scope) override {
     auto x = op_desc.Input("X").front();