fix compilation errors on mac arm64 (#46135)

cmake/external/protobuf.cmake

@@ -268,8 +268,6 @@ function(build_protobuf TARGET_NAME BUILD_FOR_HOST)
       DOWNLOAD_DIR ${PROTOBUF_SOURCE_DIR}
       DOWNLOAD_COMMAND rm -rf arm_protobuf.tar.gz && wget --no-check-certificate
                        ${ARM_PROTOBUF_URL} && tar zxvf arm_protobuf.tar.gz
-      #DOWNLOAD_COMMAND    cp /home/wangbin44/Paddle/build/arm_protobuf.tar.gz .
-      #                    && tar zxvf arm_protobuf.tar.gz
       UPDATE_COMMAND ""
       CMAKE_ARGS -DCMAKE_INSTALL_PREFIX:PATH=${PROTOBUF_INSTALL_DIR}
                  -DCMAKE_BUILD_TYPE:STRING=${THIRD_PARTY_BUILD_TYPE}

cmake/external/xxhash.cmake

@@ -97,5 +97,4 @@ endif()
 
 add_library(xxhash STATIC IMPORTED GLOBAL)
 set_property(TARGET xxhash PROPERTY IMPORTED_LOCATION ${XXHASH_LIBRARIES})
-include_directories(${XXHASH_INCLUDE_DIR})
 add_dependencies(xxhash extern_xxhash)

paddle/fluid/eager/pylayer/py_layer_node.h

@@ -45,7 +45,7 @@ class GradNodePyLayer : public GradNodeBase {
 
   void ClearTensorWrappers() override { VLOG(6) << "Do nothing here now"; }
 
-  std::string name() {
+  std::string name() override {
     return "GradNodePyLayer_" + std::string(Py_TYPE(ctx_)->tp_name);
   }
 

paddle/fluid/inference/capi_exp/CMakeLists.txt

@@ -31,6 +31,18 @@ cc_library(
   DEPS paddle_inference)
 set_target_properties(paddle_inference_c_shared PROPERTIES OUTPUT_NAME
                                                            paddle_inference_c)
+
+if(APPLE)
+  target_link_libraries(
+    paddle_inference_c_shared
+    xxhash
+    utf8proc
+    cryptopp
+    protobuf
+    gflags
+    cblas)
+endif()
+
 if(WIN32)
   target_link_libraries(paddle_inference_c_shared shlwapi.lib)
 endif()

paddle/fluid/operators/abs_op.cc

@@ -154,7 +154,7 @@ class AbsDoubleGradOp : public framework::OperatorWithKernel {
   framework::OpKernelType GetKernelTypeForVar(
       const std::string& var_name,
       const framework::Tensor& tensor,
-      const framework::OpKernelType& expected_kernel_type) const {
+      const framework::OpKernelType& expected_kernel_type) const override {
     return framework::OpKernelType(
         framework::TransToProtoVarType(tensor.dtype()),
         tensor.place(),

paddle/fluid/operators/activation_op.cc

@@ -125,7 +125,7 @@ class ActivationOp : public framework::OperatorWithKernel {
   framework::OpKernelType GetKernelTypeForVar(
       const std::string& var_name,
       const Tensor& tensor,
-      const framework::OpKernelType& expected_kernel_type) const {
+      const framework::OpKernelType& expected_kernel_type) const override {
 #ifdef PADDLE_WITH_MKLDNN
     // When activation is first oneDNN op (there was some non oneDNN op
     // previously)

paddle/fluid/operators/cross_entropy_op.cc

@@ -142,7 +142,7 @@ class CrossEntropyGradientOpBase : public framework::OperatorWithKernel {
  public:
   using framework::OperatorWithKernel::OperatorWithKernel;
 
-  void InferShape(framework::InferShapeContext* ctx) const {
+  void InferShape(framework::InferShapeContext* ctx) const override {
     OP_INOUT_CHECK(
         ctx->HasInput("Label"), "Input", "Label", "CrossEntropyGradientOpBase");
     OP_INOUT_CHECK(ctx->HasInput(framework::GradVarName("Y")),

paddle/fluid/operators/dequantize_abs_max_op.cc

@@ -69,7 +69,7 @@ class DequantizeMaxAbsOp : public framework::OperatorWithKernel {
   }
 
   framework::OpKernelType GetExpectedKernelType(
-      const framework::ExecutionContext& ctx) const {
+      const framework::ExecutionContext& ctx) const override {
     auto data_type = OperatorWithKernel::IndicateVarDataType(ctx, "X");
     auto type = framework::OpKernelType(data_type, ctx.device_context());
     return type;

paddle/fluid/operators/dequantize_log_op.cc

@@ -76,7 +76,7 @@ class DequantizeLogOp : public framework::OperatorWithKernel {
   }
 
   framework::OpKernelType GetExpectedKernelType(
-      const framework::ExecutionContext& ctx) const {
+      const framework::ExecutionContext& ctx) const override {
     auto data_type = OperatorWithKernel::IndicateVarDataType(ctx, "X");
     auto type = framework::OpKernelType(data_type, ctx.device_context());
     return type;

paddle/fluid/operators/kron_op.cc

@@ -39,7 +39,7 @@ class KronOp : public framework::OperatorWithKernel {
   framework::OpKernelType GetKernelTypeForVar(
       const std::string& var_name,
       const framework::Tensor& 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(
@@ -121,7 +121,7 @@ class KronGradOp : public framework::OperatorWithKernel {
   framework::OpKernelType GetKernelTypeForVar(
       const std::string& var_name,
       const framework::Tensor& 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/matmul_op.cc

@@ -714,7 +714,7 @@ class MatMulOp : public framework::OperatorWithKernel {
   framework::OpKernelType GetKernelTypeForVar(
       const std::string &var_name,
       const framework::Tensor &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/matmul_v2_op.cc

@@ -150,7 +150,7 @@ class MatMulV2Op : public framework::OperatorWithKernel {
   framework::OpKernelType GetKernelTypeForVar(
       const std::string& var_name,
       const framework::Tensor& 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(
@@ -225,7 +225,7 @@ class MatMulV2OpGrad : public framework::OperatorWithKernel {
   framework::OpKernelType GetKernelTypeForVar(
       const std::string& var_name,
       const framework::Tensor& 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/pad3d_op.cc

@@ -54,7 +54,7 @@ class Pad3dOp : public framework::OperatorWithKernel {
   framework::OpKernelType GetKernelTypeForVar(
       const std::string& var_name,
       const Tensor& 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_ == framework::DataLayout::kMKLDNN) &&
         (tensor.layout() != framework::DataLayout::kMKLDNN)) {

paddle/fluid/operators/prelu_op.cc

@@ -71,7 +71,7 @@ class PReluOp : public framework::OperatorWithKernel {
   framework::OpKernelType GetKernelTypeForVar(
       const std::string &var_name,
       const Tensor &tensor,
-      const framework::OpKernelType &expected_kernel_type) const {
+      const framework::OpKernelType &expected_kernel_type) const override {
     return innerGetKernelTypeForVar(tensor, expected_kernel_type);
   }
 };
@@ -150,7 +150,7 @@ class PReluGradOp : public framework::OperatorWithKernel {
   framework::OpKernelType GetKernelTypeForVar(
       const std::string &var_name,
       const Tensor &tensor,
-      const framework::OpKernelType &expected_kernel_type) const {
+      const framework::OpKernelType &expected_kernel_type) const override {
     return innerGetKernelTypeForVar(tensor, expected_kernel_type);
   }
 };

paddle/phi/core/string_tensor.h

@@ -123,7 +123,7 @@ class StringTensor : public TensorBase,
   }
   void* AllocateFrom(Allocator* allocator,
                      DataType dtype,
-                     size_t requested_size = 0);
+                     size_t requested_size = 0) override;
   dtype::pstring* mutable_data(const phi::Place& place,
                                size_t requested_size = 0);
 

paddle/phi/core/tensor_array.h

@@ -83,7 +83,7 @@ class TensorArray : public TensorBase,
   /// \return Void pointer
   void* AllocateFrom(Allocator* allocator,
                      DataType dtype,
-                     size_t requested_size = 0);
+                     size_t requested_size = 0) override;
 
   bool empty() const { return tensors_.empty(); }