[CodeStyle] fix macos inconsistent-missing-override warnings and add -Werror (#47264)

* fix macos inconsistent-missing-override warnings

* fix inconsistent-missing-override error in test

cmake/flags.cmake

@@ -214,7 +214,8 @@ if(APPLE)
         CACHE STRING "Build architectures for OSX" FORCE)
   endif()
   # On Mac OS X register class specifier is deprecated and will cause warning error on latest clang 10.0
-  set(COMMON_FLAGS -Wno-deprecated-register -Werror=format)
+  set(COMMON_FLAGS -Wno-deprecated-register -Werror=format
+                   -Werror=inconsistent-missing-override)
 endif()
 
 if(WITH_HETERPS AND WITH_PSLIB)

paddle/fluid/eager/accumulation/accumulation_node.h

@@ -46,7 +46,7 @@ class GradNodeAccumulation : public GradNodeBase {
 
   void ClearTensorWrappers() override { VLOG(5) << "Do nothing here now"; }
 
-  std::string name() { return "GradNodeAccumulation"; }
+  std::string name() override { return "GradNodeAccumulation"; }
 
   /**
    * Register ReduceHook

paddle/fluid/eager/custom_operator/custom_operator_node.h

@@ -46,7 +46,7 @@ class RunCustomOpNode : public GradNodeBase {
       bool is_new_grad = false)  // NOLINT
       override;
 
-  std::string name() {
+  std::string name() override {
     return paddle::string::Sprintf("RunCustomOpNode: %s_grad", op_type_);
   }
 
@@ -116,7 +116,7 @@ class RunCustomOpDoubleGradNode : public GradNodeBase {
       bool is_new_grad = false)  // NOLINT
       override;
 
-  std::string name() {
+  std::string name() override {
     return paddle::string::Sprintf("RunCustomOpDoubleGradNode: %s_grad_grad",
                                    op_type_);
   }

paddle/fluid/framework/infershape_utils.h

@@ -59,9 +59,9 @@ class CompatMetaTensor : public phi::MetaTensor {
 
   bool initialized() const override { return initialized_; };
 
-  bool is_selected_rows() const;
-  bool is_tensor_array() const;
-  bool is_dense() const;
+  bool is_selected_rows() const override;
+  bool is_tensor_array() const override;
+  bool is_dense() const override;
 
   operator unspecified_bool_type() const override {
     return initialized_ ? unspecified_bool_true : 0;

paddle/fluid/imperative/infer_var_type_context.h

@@ -68,12 +68,12 @@ class RuntimeInferVarTypeContext : public framework::InferVarTypeContext {
     return (it != outputs_.end() && it->second.size() > 0);
   }
 
-  size_t InputSize(const std::string& name) const {
+  size_t InputSize(const std::string& name) const override {
     return inputs_.at(name).size();
   }
 
   const std::string& InputVarName(const std::string& name,
-                                  const int index = 0) const {
+                                  const int index = 0) const override {
     return GetNameFromVar(inputs_.at(name)[index]);
   }
 

paddle/fluid/inference/api/analysis_predictor.h

@@ -143,13 +143,13 @@ class AnalysisPredictor : public PaddlePredictor {
   ///
   /// \return input names
   ///
-  std::vector<std::string> GetInputNames();
+  std::vector<std::string> GetInputNames() override;
   ///
   /// \brief Get the output names
   ///
   /// \return output names
   ///
-  std::vector<std::string> GetOutputNames();
+  std::vector<std::string> GetOutputNames() override;
 
   ///
   /// \brief Get the Input Tensor object
@@ -227,7 +227,7 @@ class AnalysisPredictor : public PaddlePredictor {
   /// \brief Clear the intermediate tensors of the predictor
   ///
   ///
-  void ClearIntermediateTensor();
+  void ClearIntermediateTensor() override;
 
   ///
   /// \brief Release all tmp tensor to compress the size of the memory pool.

paddle/fluid/memory/allocation/auto_growth_best_fit_allocator_test.cc

@@ -33,7 +33,7 @@ class RecordedAllocator : public Allocator {
     return new Allocation(malloc(size), size, platform::CPUPlace());
   }
 
-  void FreeImpl(phi::Allocation *allocation) {
+  void FreeImpl(phi::Allocation *allocation) override {
     allocated_size_ -= allocation->size();
     free(allocation->ptr());
     delete allocation;
@@ -88,7 +88,7 @@ class LimitedResourceAllocator : public Allocator {
     return new Allocation(malloc(size), size, platform::CPUPlace());
   }
 
-  void FreeImpl(phi::Allocation *allocation) {
+  void FreeImpl(phi::Allocation *allocation) override {
     allocated_size_ -= allocation->size();
     free(allocation->ptr());
     delete allocation;

paddle/fluid/operators/cross_entropy_op.cc

@@ -346,14 +346,14 @@ class CrossEntropyGradientOp2 : public CrossEntropyGradientOpBase {
   }
 
  protected:
-  virtual framework::DDim GetXDim(framework::InferShapeContext* ctx) const {
+  framework::DDim GetXDim(framework::InferShapeContext* ctx) const override {
     auto x_shape = ctx->GetInputDim("XShape");
     return framework::DDim(x_shape.Get(), x_shape.size() - 1);
   }
 
-  virtual const char* VarNameWithXLoD() const { return "XShape"; }
+  const char* VarNameWithXLoD() const override { return "XShape"; }
 
-  virtual bool IsSoftLabel(framework::InferShapeContext* ctx) const {
+  bool IsSoftLabel(framework::InferShapeContext* ctx) const override {
     return false;
   }
 };

paddle/fluid/operators/decode_jpeg_op.cc

@@ -41,7 +41,7 @@ class DecodeJpegOp : public framework::OperatorWithKernel {
   framework::OpKernelType GetKernelTypeForVar(
       const std::string& var_name,
       const phi::DenseTensor& tensor,
-      const framework::OpKernelType& expected_kernel_type) const {
+      const framework::OpKernelType& expected_kernel_type) const override {
     if (var_name == "X") {
       return expected_kernel_type;
     }

paddle/fluid/operators/elementwise/elementwise_div_op.h

@@ -51,7 +51,7 @@ class ElementwiseDivOpDoubleGrad : public framework::OperatorWithKernel {
   framework::OpKernelType GetKernelTypeForVar(
       const std::string& var_name,
       const phi::DenseTensor& tensor,
-      const framework::OpKernelType& expected_kernel_type) const {
+      const framework::OpKernelType& expected_kernel_type) const override {
     if (framework::IsComplexType(expected_kernel_type.data_type_)) {
       // only promote inputs’s types when contains complex input
       return framework::OpKernelType(

paddle/fluid/operators/elementwise/elementwise_mul_op.h

@@ -38,7 +38,7 @@ class ElementwiseMulOp : public ElementwiseOp {
   framework::OpKernelType GetKernelTypeForVar(
       const std::string& var_name,
       const phi::DenseTensor& tensor,
-      const framework::OpKernelType& expected_kernel_type) const {
+      const framework::OpKernelType& expected_kernel_type) const override {
     if (framework::IsComplexType(expected_kernel_type.data_type_)) {
       // only promote inputs’s types when contains complex input
       return framework::OpKernelType(

paddle/fluid/operators/elementwise/elementwise_op.h

@@ -357,7 +357,7 @@ class ElementwiseOpDoubleGrad : public framework::OperatorWithKernel {
   framework::OpKernelType GetKernelTypeForVar(
       const std::string &var_name,
       const phi::DenseTensor &tensor,
-      const framework::OpKernelType &expected_kernel_type) const {
+      const framework::OpKernelType &expected_kernel_type) const override {
     if (framework::IsComplexType(expected_kernel_type.data_type_)) {
       // only promote inputs’s types when contains complex input
       return framework::OpKernelType(
@@ -409,7 +409,7 @@ class ElementwiseOpDoubleGradWithoutDXDY
   framework::OpKernelType GetKernelTypeForVar(
       const std::string &var_name,
       const phi::DenseTensor &tensor,
-      const framework::OpKernelType &expected_kernel_type) const {
+      const framework::OpKernelType &expected_kernel_type) const override {
     if (framework::IsComplexType(expected_kernel_type.data_type_)) {
       // only promote inputs’s types when contains complex input
       return framework::OpKernelType(
@@ -461,7 +461,7 @@ class ElementwiseOpTripleGrad : public framework::OperatorWithKernel {
   framework::OpKernelType GetKernelTypeForVar(
       const std::string &var_name,
       const phi::DenseTensor &tensor,
-      const framework::OpKernelType &expected_kernel_type) const {
+      const framework::OpKernelType &expected_kernel_type) const override {
     if (framework::IsComplexType(expected_kernel_type.data_type_)) {
       // only promote inputs’s types when contains complex input
       return framework::OpKernelType(

paddle/fluid/operators/inplace_abn_op.cc

@@ -73,7 +73,7 @@ class InplaceABNGradOp : public paddle::operators::BatchNormGradOp {
  public:
   using paddle::operators::BatchNormGradOp::BatchNormGradOp;
 
-  void InferShape(framework::InferShapeContext* ctx) const {
+  void InferShape(framework::InferShapeContext* ctx) const override {
     // check input
     OP_INOUT_CHECK(ctx->HasInput("Scale"), "Input", "Scale", "InplaceABNGrad");
     OP_INOUT_CHECK(ctx->HasInput(framework::GradVarName("Y")),

paddle/fluid/operators/optimizers/sgd_op.cc

@@ -60,7 +60,7 @@ class SGDOp : public framework::OperatorWithKernel {
   framework::OpKernelType GetKernelTypeForVar(
       const std::string &var_name,
       const phi::DenseTensor &tensor,
-      const framework::OpKernelType &expected_kernel_type) const {
+      const framework::OpKernelType &expected_kernel_type) const override {
     if (var_name == "LearningRate") {
       return framework::OpKernelType(
           framework::TransToProtoVarType(tensor.dtype()),

paddle/fluid/operators/pad2d_op.cc

@@ -718,7 +718,7 @@ class Pad2dOp : public framework::OperatorWithKernel {
   framework::OpKernelType GetKernelTypeForVar(
       const std::string& var_name,
       const phi::DenseTensor& tensor,
-      const framework::OpKernelType& expected_kernel_type) const {
+      const framework::OpKernelType& expected_kernel_type) const override {
 #ifdef PADDLE_WITH_MKLDNN
     if ((expected_kernel_type.data_layout_ == phi::DataLayout::kMKLDNN) &&
         (tensor.layout() != phi::DataLayout::kMKLDNN)) {