[1/N] Remove usage of C array (pytorch#139567)

Fixes #ISSUE_NUMBER

Pull Request resolved: pytorch#139567
Approved by: https://github.com/Skylion007, https://github.com/ezyang

c10/core/impl/DeviceGuardImplInterface.cpp

@@ -1,11 +1,12 @@
 #include <c10/core/impl/DeviceGuardImplInterface.h>
+#include <array>
 
 namespace c10::impl {
 
-// NOLINTNEXTLINE(modernize-avoid-c-arrays,cppcoreguidelines-avoid-c-arrays)
-std::atomic<const DeviceGuardImplInterface*>
-    device_guard_impl_registry[static_cast<size_t>(
-        DeviceType::COMPILE_TIME_MAX_DEVICE_TYPES)];
+std::array<
+    std::atomic<const DeviceGuardImplInterface*>,
+    static_cast<size_t>(DeviceType::COMPILE_TIME_MAX_DEVICE_TYPES)>
+    device_guard_impl_registry;
 
 DeviceGuardImplRegistrar::DeviceGuardImplRegistrar(
     DeviceType type,

c10/core/impl/DeviceGuardImplInterface.h

@@ -8,6 +8,7 @@
 // Just for C10_ANONYMOUS_VARIABLE
 #include <c10/util/Registry.h>
 
+#include <array>
 #include <atomic>
 
 namespace c10 {
@@ -327,10 +328,10 @@ struct NoOpDeviceGuardImpl final : public DeviceGuardImplInterface {
 // in a Meyer singleton), it implies that you must *leak* objects when
 // putting them in the registry.  This is done by deleting the destructor
 // on DeviceGuardImplInterface.
-// NOLINTNEXTLINE(*c-arrays*)
-extern C10_API std::atomic<const DeviceGuardImplInterface*>
-    device_guard_impl_registry[static_cast<size_t>(
-        DeviceType::COMPILE_TIME_MAX_DEVICE_TYPES)];
+extern C10_API std::array<
+    std::atomic<const DeviceGuardImplInterface*>,
+    static_cast<size_t>(DeviceType::COMPILE_TIME_MAX_DEVICE_TYPES)>
+    device_guard_impl_registry;
 
 // I can't conveniently use c10/util/Registry.h for the following reason:
 // c10/util/Registry.h gives me a slow way of Create'ing a object of some

torch/csrc/Module.cpp

@@ -1367,7 +1367,7 @@ static PyObject* THPModule_are_vmap_fallback_warnings_enabled(
   END_HANDLE_TH_ERRORS
 }
 
-static PyMethodDef TorchMethods[] = { // NOLINT
+static std::initializer_list<PyMethodDef> TorchMethods = {
     {"_initExtension", THPModule_initExtension, METH_O, nullptr},
     {"_autograd_init", THPAutograd_initExtension, METH_NOARGS, nullptr},
     {"_add_docstr", THPModule_addDocStr, METH_VARARGS, nullptr},
@@ -1703,7 +1703,7 @@ PyObject* initModule() {
   if (!(cmd))            \
   return nullptr
 
-  THPUtils_addPyMethodDefs(methods, TorchMethods);
+  THPUtils_addPyMethodDefs(methods, std::data(TorchMethods));
   THPUtils_addPyMethodDefs(methods, DataLoaderMethods);
   THPUtils_addPyMethodDefs(methods, torch::autograd::python_functions());
   THPUtils_addPyMethodDefs(methods, torch::multiprocessing::python_functions());
@@ -1848,7 +1848,8 @@ PyObject* initModule() {
   at::init();
 
   // Automatically translate errors thrown from pybind11 functions
-  py::register_exception_translator([](std::exception_ptr e) { // NOLINT
+  // NOLINTNEXTLINE(performance-unnecessary-value-param)
+  py::register_exception_translator([](std::exception_ptr e) {
     try {
       if (e) {
         std::rethrow_exception(e);

torch/csrc/jit/passes/onnx/shape_type_inference.cpp

@@ -2144,10 +2144,8 @@ void ONNXShapeTypeInference(
             ex.what(),
             " on graph: ",
             n_graph->toString());
-        // NOLINTNEXTLINE(modernize-avoid-c-arrays,cppcoreguidelines-avoid-c-arrays)
-        const char shape_err[] = "ShapeInferenceError";
-        // NOLINTNEXTLINE(modernize-avoid-c-arrays,cppcoreguidelines-avoid-c-arrays)
-        const char type_err[] = "TypeInferenceError";
+        constexpr const char* shape_err = "ShapeInferenceError";
+        constexpr const char* type_err = "TypeInferenceError";
         if ((strstr(ex.what(), shape_err) == nullptr) &&
             (strstr(ex.what(), type_err) == nullptr)) {
           throw;

torch/csrc/multiprocessing/init.cpp

@@ -5,6 +5,7 @@
 #include <torch/csrc/utils/pybind.h>
 #include <torch/csrc/utils/python_strings.h>
 
+#include <initializer_list>
 #include <stdexcept>
 
 #if defined(__linux__)
@@ -55,8 +56,8 @@ PyObject* get_thread_name(PyObject* _unused, PyObject* noargs) {
 } // namespace
 
 // multiprocessing methods on torch._C
-// NOLINTNEXTLINE(cppcoreguidelines-avoid-c-arrays,modernize-avoid-c-arrays,cppcoreguidelines-avoid-non-const-global-variables)
-static PyMethodDef methods[] = {
+// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
+static std::initializer_list<PyMethodDef> methods = {
     {
         "_multiprocessing_init",
         multiprocessing_init,
@@ -78,8 +79,8 @@ static PyMethodDef methods[] = {
     {nullptr, nullptr, 0, nullptr},
 };
 
-PyMethodDef* python_functions() {
-  return methods;
+const PyMethodDef* python_functions() {
+  return std::data(methods);
 }
 
 } // namespace torch::multiprocessing

torch/csrc/multiprocessing/init.h

@@ -4,6 +4,6 @@
 
 namespace torch::multiprocessing {
 
-PyMethodDef* python_functions();
+const PyMethodDef* python_functions();
 
 } // namespace torch::multiprocessing

torch/csrc/utils.cpp

@@ -105,7 +105,7 @@ void THPUtils_setError(const char* format, ...) {
 
 void THPUtils_addPyMethodDefs(
     std::vector<PyMethodDef>& vector,
-    PyMethodDef* methods) {
+    const PyMethodDef* methods) {
   if (!vector.empty()) {
     // remove nullptr terminator
     vector.pop_back();

torch/csrc/utils.h

@@ -166,7 +166,7 @@ std::vector<int> THPUtils_unpackIntTuple(PyObject* arg);
 
 TORCH_PYTHON_API void THPUtils_addPyMethodDefs(
     std::vector<PyMethodDef>& vector,
-    PyMethodDef* methods);
+    const PyMethodDef* methods);
 
 int THPUtils_getCallable(PyObject* arg, PyObject** result);