Update clang-tidy integration (apache#18815)

Run clang-tidy via cmake only on the code managed by mxnet (and not 3rdparty dependencies), update to clang-tidy-10 and run clang-tidy-10 -fix to fix all the warnings that are enforced on CI.

Developers can run clang-tidy by specifying the -DCMAKE_CXX_CLANG_TIDY="clang-tidy-10" to cmake, or using the python ci/build.py -R --platform ubuntu_cpu /work/runtime_functions.sh build_ubuntu_cpu_clang_tidy script.

.clang-tidy

@@ -17,45 +17,33 @@
 
 # The checks defined here will be run and will display by default as warnings.
 Checks: >
-    -*, cppcoreguidelines-c-copy-assignment-signature,
-    cppcoreguidelines-interfaces-global-init, cppcoreguidelines-no-malloc,
-    cppcoreguidelines-pro-bounds-constant-array-index, cppcoreguidelines-pro-type-const-cast,
-    cppcoreguidelines-pro-type-cstyle-cast, cppcoreguidelines-pro-type-member-init,
-    cppcoreguidelines-pro-type-static-cast-downcast, cppcoreguidelines-pro-type-union-access,
-    cppcoreguidelines-pro-type-vararg, cppcoreguidelines-slicing,
-    cppcoreguidelines-special-member-functions, clang-analyzer-security.FloatLoopCounter,
-    clang-analyzer-security.insecureAPI.*, clang-analyzer-core.CallAndMessage,
-    clang-analyzer-core.DivideZero, clang-analyzer-core.DynamicTypePropagation,
-    clang-analyzer-core.NonNullParamChecker, clang-analyzer-core.NullDereference,
-    clang-analyzer-core.StackAddressEscape, clang-analyzer-core.UndefinedBinaryOperatorResult,
-    clang-analyzer-core.VLASize, clang-analyzer-core.builtin.BuiltinFunctions,
-    clang-analyzer-core.builtin.NoReturnFunctions, clang-analyzer-core.uninitialized.ArraySubscript,
-    clang-analyzer-core.uninitialized.Assign, clang-analyzer-core.uninitialized.Branch,
-    clang-analyzer-core.uninitialized.CapturedBlockVariable,
-    clang-analyzer-core.uninitialized.UndefReturn, clang-analyzer-cplusplus.NewDelete,
-    clang-analyzer-cplusplus.NewDeleteLeaks, clang-analyzer-cplusplus.SelfAssignment,
-    clang-analyzer-deadcode.DeadStores, modernize-avoid-bind, modernize-deprecated-headers,
-    modernize-loop-convert, modernize-make-shared, modernize-pass-by-value,
+    -*, cppcoreguidelines-* clang-analyzer-*, modernize-*,
+    performance-faster-string-find, performance-for-range-copy,
+    performance-implicit-conversion-in-loop, performance-inefficient-algorithm,
+    performance-inefficient-string-concatenation, performance-trivially-destructible,
+    performance-inefficient-vector-operation, performance-move-const-arg,
+    performance-move-constructor-init, performance-noexcept-move-constructor,
+    performance-no-automatic-move, performance-unnecessary-copy-initialization,
+    performance-type-promotion-in-math-fn
+
+# performance checks not enabled due to segmentation fault in clang-tidy v8+:
+# performance-unnecessary-value-param
+
+# In order to trigger an error, you must have a rule defined both in checks and in this section.
+WarningsAsErrors: >
+    cppcoreguidelines-no-malloc, modernize-deprecated-headers,
+    modernize-loop-convert, modernize-make-shared, modernize-pass-by-value, modernize-make-unique,
     modernize-raw-string-literal, modernize-redundant-void-arg, modernize-replace-auto-ptr,
     modernize-replace-random-shuffle, modernize-return-braced-init-list, modernize-shrink-to-fit,
     modernize-unary-static-assert, modernize-use-bool-literals, modernize-use-default-member-init,
     modernize-use-emplace, modernize-use-equals-default, modernize-use-equals-delete,
     modernize-use-noexcept, modernize-use-nullptr, modernize-use-override,
-    modernize-use-transparent-functors, modernize-use-using, performance-*
+    modernize-use-transparent-functors, modernize-use-using,
+    performance-unnecessary-copy-initialization, performance-move-const-arg
 
-# cppcoreguidelines checks not enabled:
-# cppcoreguidelines-pro-bounds-pointer-arithmetic
-# cppcoreguidelines-pro-bounds-array-to-pointer-decay
-# cppcoreguidelines-pro-type-reinterpret-cast
-
-# modernize checks not enabled:
+# modernize checks not enforced:
 # modernize-use-auto
-# modernize-make-unique (C++14 and newer only)
-
-# In order to trigger an error, you must have a rule defined both in checks and in this section.
-WarningsAsErrors: >
-    cppcoreguidelines-no-malloc, modernize-use-nullptr, performance-unnecessary-copy-initialization,
-    modernize-use-emplace, performance-move-const-arg
+# modernize-avoid-bind
 
 # Todo: define a better regex match that includes most project headers, but excludes third party
 # code.

CMakeLists.txt

@@ -275,6 +275,7 @@ if(USE_MKLDNN)
   include_directories(${PROJECT_BINARY_DIR}/3rdparty/mkldnn/include)
   add_definitions(-DMXNET_USE_MKLDNN=1)
   list(APPEND mxnet_LINKER_LIBS dnnl)
+  set_target_properties(dnnl PROPERTIES CXX_CLANG_TIDY "")  # don't lint 3rdparty dependency
 endif()
 
 # Allow Cuda compiles outside of src tree to find things in 'src' and 'include'
@@ -405,6 +406,7 @@ if(USE_OPENMP)
      AND NOT CMAKE_CROSSCOMPILING)
     load_omp()
     list(APPEND mxnet_LINKER_LIBS omp)
+    set_target_properties(omp PROPERTIES CXX_CLANG_TIDY "")  # don't lint 3rdparty dependency
     if(UNIX)
       list(APPEND mxnet_LINKER_LIBS pthread)
     endif()
@@ -462,6 +464,8 @@ set(GTEST_MAIN_LIBRARY gtest_main)
 set(GTEST_LIBRARY gtest)
 
 add_subdirectory(${GTEST_ROOT})
+set_target_properties(gtest PROPERTIES CXX_CLANG_TIDY "")  # don't lint 3rdparty dependency
+set_target_properties(gtest_main PROPERTIES CXX_CLANG_TIDY "")  # don't lint 3rdparty dependency
 find_package(GTest REQUIRED)
 
 # cudnn detection
@@ -478,6 +482,7 @@ endif()
 
 if(EXISTS ${CMAKE_CURRENT_SOURCE_DIR}/3rdparty/dmlc-core/cmake)
   add_subdirectory("3rdparty/dmlc-core")
+  set_target_properties(dmlc PROPERTIES CXX_CLANG_TIDY "")  # don't lint 3rdparty dependency
 endif()
 
 FILE(GLOB_RECURSE SOURCE "src/*.cc" "src/*.h" "include/*.h")
@@ -492,7 +497,9 @@ FILE(GLOB_RECURSE NNVMSOURCE
   3rdparty/tvm/nnvm/src/core/*.h
   3rdparty/tvm/nnvm/src/pass/*.h
   3rdparty/tvm/nnvm/include/*.h)
-list(APPEND SOURCE ${NNVMSOURCE})
+add_library(nnvm OBJECT ${NNVMSOURCE})
+set_target_properties(nnvm PROPERTIES CXX_CLANG_TIDY "")  # don't lint 3rdparty dependency
+list(APPEND SOURCE $<TARGET_OBJECTS:nnvm>)
 
 # add source group
 FILE(GLOB_RECURSE GROUP_SOURCE "src/*.cc" "3rdparty/tvm/nnvm/*.cc" "plugin/*.cc")
@@ -743,6 +750,7 @@ if(USE_DIST_KVSTORE)
   add_subdirectory("3rdparty/ps-lite")
   add_definitions(-DMXNET_USE_DIST_KVSTORE)
   list(APPEND mxnet_LINKER_LIBS pslite)
+  set_target_properties(pslite PROPERTIES CXX_CLANG_TIDY "")  # don't lint 3rdparty dependency
 endif()
 
 if(USE_MKLDNN)
@@ -757,6 +765,9 @@ function(BuildTVMOP)
   # scope the variables in BuildTVM.cmake to avoid conflict
   include(cmake/BuildTVM.cmake)
   add_subdirectory("3rdparty/tvm")
+  set_target_properties(tvm PROPERTIES CXX_CLANG_TIDY "")  # don't lint 3rdparty dependency
+  set_target_properties(tvm_topi PROPERTIES CXX_CLANG_TIDY "")  # don't lint 3rdparty dependency
+  set_target_properties(tvm_runtime PROPERTIES CXX_CLANG_TIDY "")  # don't lint 3rdparty dependency
 endfunction()
 
 if(USE_TVM_OP)

ci/docker/Dockerfile.build.ubuntu

@@ -53,9 +53,9 @@ RUN export DEBIAN_FRONTEND=noninteractive && \
         protobuf-compiler \
         libprotobuf-dev \
         clang-6.0 \
-        clang-tidy-6.0 \
         python-yaml \
         clang-10 \
+        clang-tidy-10 \
         g++ \
         g++-8 \
         intel-mkl-2020.0-088 \

ci/docker/runtime_functions.sh

@@ -462,21 +462,18 @@ build_ubuntu_cpu_clang100() {
 build_ubuntu_cpu_clang_tidy() {
     set -ex
     cd /work/build
-    export CLANG_TIDY=/usr/lib/llvm-6.0/share/clang/run-clang-tidy.py
     # TODO(leezu) USE_OPENMP=OFF 3rdparty/dmlc-core/CMakeLists.txt:79 broken?
-    CXX=clang++-6.0 CC=clang-6.0 cmake \
+    CXX=clang++-10 CC=clang-10 cmake \
        -DUSE_MKL_IF_AVAILABLE=OFF \
        -DUSE_MKLDNN=OFF \
        -DUSE_CUDA=OFF \
        -DUSE_OPENMP=OFF \
        -DCMAKE_BUILD_TYPE=Debug \
        -DUSE_DIST_KVSTORE=ON \
        -DUSE_CPP_PACKAGE=ON \
-       -DCMAKE_EXPORT_COMPILE_COMMANDS=ON \
+       -DCMAKE_CXX_CLANG_TIDY=clang-tidy-10 \
        -G Ninja /work/mxnet
     ninja
-    cd /work/mxnet
-    $CLANG_TIDY -p /work/build -j $(nproc) -clang-tidy-binary clang-tidy-6.0 /work/mxnet/src
 }
 
 build_ubuntu_cpu_clang6_mkldnn() {

example/extensions/lib_custom_op/gemm_lib.cc

@@ -24,6 +24,7 @@
  */
 
 #include <iostream>
+#include <utility>
 #include "lib_api.h"
 
 // main matrix multiplication routine
@@ -179,23 +180,23 @@ REGISTER_OP(my_gemm)
 class MyStatefulGemm : public CustomStatefulOp {
  public:
   explicit MyStatefulGemm(int count,
-                          const std::unordered_map<std::string, std::string>& attrs)
-    : count(count), attrs_(attrs) {}
+                          std::unordered_map<std::string, std::string>  attrs)
+    : count(count), attrs_(std::move(attrs)) {}
 
   MXReturnValue Forward(std::vector<MXTensor>* inputs,
                         std::vector<MXTensor>* outputs,
-                        const OpResource& op_res) {
+                        const OpResource& op_res) override {
     std::cout << "Info: keyword + number of forward: " << ++count << std::endl;
     return forward(attrs_, inputs, outputs, op_res);
   }
 
   MXReturnValue Backward(std::vector<MXTensor>* inputs,
                          std::vector<MXTensor>* outputs,
-                         const OpResource& op_res) {
+                         const OpResource& op_res) override {
     return backward(attrs_, inputs, outputs, op_res);
   }
 
-  ~MyStatefulGemm() {}
+  ~MyStatefulGemm() = default;
 
  private:
   int count;

example/extensions/lib_custom_op/transposecsr_lib.cc

@@ -24,6 +24,7 @@
  */
 
 #include <iostream>
+#include <utility>
 #include "lib_api.h"
 
 void transpose(MXTensor& src, MXTensor& dst, const OpResource& res) {
@@ -151,19 +152,19 @@ REGISTER_OP(my_transposecsr)
 class MyStatefulTransposeCSR : public CustomStatefulOp {
   public:
     explicit MyStatefulTransposeCSR(int count,
-                                    const std::unordered_map<std::string, std::string>& attrs)
-      : count(count), attrs_(attrs) {}
+                                    std::unordered_map<std::string, std::string>  attrs)
+      : count(count), attrs_(std::move(attrs)) {}
 
     MXReturnValue Forward(std::vector<MXTensor>* inputs,
                           std::vector<MXTensor>* outputs,
-                          const OpResource& op_res) {
+                          const OpResource& op_res) override {
       std::cout << "Info: keyword + number of forward: " << ++count << std::endl;
       return forward(attrs_, inputs, outputs, op_res);
     }
 
     MXReturnValue Backward(std::vector<MXTensor>* inputs,
                            std::vector<MXTensor>* outputs,
-                           const OpResource& op_res) {
+                           const OpResource& op_res) override {
       return backward(attrs_, inputs, outputs, op_res);
     }
 

example/extensions/lib_custom_op/transposerowsp_lib.cc

@@ -24,6 +24,7 @@
  */
 
 #include <iostream>
+#include <utility>
 #include "lib_api.h"
 
 void transpose(MXTensor& src, MXTensor& dst, const OpResource& res) {
@@ -153,19 +154,19 @@ REGISTER_OP(my_transposerowsp)
 class MyStatefulTransposeRowSP : public CustomStatefulOp {
   public:
     explicit MyStatefulTransposeRowSP(int count,
-                                      const std::unordered_map<std::string, std::string>& attrs)
-      : count(count), attrs_(attrs) {}
+                                      std::unordered_map<std::string, std::string>  attrs)
+      : count(count), attrs_(std::move(attrs)) {}
 
     MXReturnValue Forward(std::vector<MXTensor>* inputs,
                           std::vector<MXTensor>* outputs,
-                          const OpResource& op_res) {
+                          const OpResource& op_res) override {
       std::cout << "Info: keyword + number of forward: " << ++count << std::endl;
       return forward(attrs_, inputs, outputs, op_res);
     }
 
     MXReturnValue Backward(std::vector<MXTensor>* inputs,
                            std::vector<MXTensor>* outputs,
-                           const OpResource& op_res) {
+                           const OpResource& op_res) override {
       return backward(attrs_, inputs, outputs, op_res);
     }
 

example/extensions/lib_pass/pass_lib.cc

@@ -23,7 +23,7 @@
  * \brief subgraph operator implementation library file
  */
 
-#include <math.h>
+#include <cmath>
 #include <iostream>
 #include <algorithm>
 #include "lib_api.h"
@@ -67,8 +67,7 @@ MXReturnValue jsonPass(const std::string& in_graph, const std::string** out_grap
   JsonVal nodes = json_val.map[JsonVal("nodes")];
 
   // loop over nodes
-  for(int i=0; i<nodes.list.size(); i++) {
-    JsonVal node = nodes.list[i];
+  for(auto node : nodes.list) {
     // get the op name
     std::string op = node.map[JsonVal("op")].str;
     // get node ID inputs to op

example/extensions/lib_subgraph/subgraph_lib.cc

@@ -23,9 +23,10 @@
  * \brief subgraph operator implementation library file
  */
 
-#include <math.h>
+#include <cmath>
 #include <iostream>
 #include <algorithm>
+#include <utility>
 #include "lib_api.h"
 
 /* function to execute log operator on floats */
@@ -69,8 +70,7 @@ MXReturnValue myExecutor(std::vector<MXTensor>* inputs,
   std::vector<void*> to_free;
 
   // loop over nodes
-  for(int i=0; i<nodes.list.size(); i++) {
-    JsonVal node = nodes.list[i];
+  for(auto node : nodes.list) {
     // get the op name
     std::string op = node.map[JsonVal("op")].str;
     // get node ID inputs to op
@@ -84,7 +84,7 @@ MXReturnValue myExecutor(std::vector<MXTensor>* inputs,
       // get input tensor based on node ID inputs from data storage
       MXTensor &input = data[node_inputs.list[0].list[0].num];
       // create temporary storage
-      MXTensor tmp(malloc(input.size()*4), input.shape, input.dtype, 0, MXContext::CPU(0), kDefaultStorage);
+      MXTensor tmp(malloc(input.size()*4), input.shape, input.dtype, 0, MXContext::CPU(0), kDefaultStorage);  // NOLINT
       // save allocated ptr to free later
       to_free.push_back(tmp.data_ptr);
       // execute log operator
@@ -95,7 +95,7 @@ MXReturnValue myExecutor(std::vector<MXTensor>* inputs,
       // get input tensor based on node ID inputs from data storage
       MXTensor &input = data[node_inputs.list[0].list[0].num];
       // create temporary storage
-      MXTensor tmp(malloc(input.size()*4), input.shape, input.dtype, 0, MXContext::CPU(0), kDefaultStorage);
+      MXTensor tmp(malloc(input.size()*4), input.shape, input.dtype, 0, MXContext::CPU(0), kDefaultStorage);  // NOLINT
       // save allocated ptr to free later
       to_free.push_back(tmp.data_ptr);
       // execute exp operator 
@@ -106,7 +106,7 @@ MXReturnValue myExecutor(std::vector<MXTensor>* inputs,
       std::cout << "Error! Unsupported op '" << op << "' found in myExecutor";
       // free allocated temporary storage
       for (void* ptr : to_free)
-        free(ptr);
+        free(ptr);  // NOLINT
       return MX_FAIL;
     }
   }
@@ -129,25 +129,25 @@ MXReturnValue myExecutor(std::vector<MXTensor>* inputs,
 
   // free allocated temporary storage
   for (void* ptr : to_free) {
-    free(ptr);
+    free(ptr);  // NOLINT
   }
 
   return MX_SUCCESS;
 }
 
 class MyStatefulOp : public CustomStatefulOp {
  public:
-  explicit MyStatefulOp(const std::string& sym,
+  explicit MyStatefulOp(std::string  sym,
                         const std::unordered_map<std::string, std::string>& attrs)
-    : subgraph_sym(sym), attrs_(attrs) {
+    : subgraph_sym(std::move(sym)), attrs_(attrs) {
     for (auto kv : attrs) {
       std::cout << "subgraphOp attributes: " << kv.first << " ==> " << kv.second << std::endl;
     }
   }
 
   MXReturnValue Forward(std::vector<MXTensor>* inputs,
                         std::vector<MXTensor>* outputs,
-                        const OpResource& op_res) {
+                        const OpResource& op_res) override {
     return myExecutor(inputs, outputs, subgraph_sym);
   }
 
@@ -299,20 +299,20 @@ class MySelector : public CustomOpSelector {
     }
     return false;
   }
-  virtual bool Select(int nodeID) {
+  bool Select(int nodeID) override {
     return chooseNode(nodeID);
   }
-  virtual bool SelectInput(int nodeID, int input_nodeID) {
+  bool SelectInput(int nodeID, int input_nodeID) override {
     return chooseNode(input_nodeID);
   }
-  virtual bool SelectOutput(int nodeID, int output_nodeID) {
+  bool SelectOutput(int nodeID, int output_nodeID) override {
     return chooseNode(output_nodeID);
   }
   virtual void Filter(std::vector<int>& candidates,
                       std::vector<int>& keep) {
     keep.insert(keep.end(), candidates.begin(), candidates.end());
   }
-  virtual void Reset() {}
+  void Reset() override {}
  private:
   std::string graph_json;
   JsonVal nodes;

src/api/operator/numpy/linalg/np_norm.cc

@@ -44,7 +44,7 @@ MXNET_REGISTER_API("_npi.norm")
   param.flag = args[4].operator int();
 
   attrs.op = op;
-  attrs.parsed = std::move(param);
+  attrs.parsed = param;
   SetAttrDict<op::NumpyNormParam>(&attrs);
 
   // inputs