Concat namespaces in jit code (pytorch#138976)

Fixes #ISSUE_NUMBER

Pull Request resolved: pytorch#138976
Approved by: https://github.com/Skylion007

Author: cyyever

torch/csrc/jit/backends/backend.h

@@ -5,8 +5,7 @@
 #include <torch/csrc/jit/backends/backend_interface.h>
 #include <torch/custom_class.h>
 
-namespace torch {
-namespace jit {
+namespace torch::jit {
 namespace {
 // NOLINTNEXTLINE(clang-diagnostic-unneeded-internal-declaration)
 inline c10::FunctionSchema getIsAvailableSchema() {
@@ -115,5 +114,4 @@ class backend {
   }
 };
 
-} // namespace jit
-} // namespace torch
+} // namespace torch::jit

torch/csrc/jit/backends/backend_debug_handler.cpp

@@ -2,8 +2,7 @@
 
 #include <stack>
 
-namespace torch {
-namespace jit {
+namespace torch::jit {
 
 std::atomic<DebugHandleType> BackendDebugInfoRecorder::unique_debug_handle_{0};
 
@@ -33,5 +32,4 @@ BackendDebugInfoMapType BackendDebugInfoRecorder::stopRecording() {
   return handles_to_inlined_callstack_ptrs_;
 }
 
-} // namespace jit
-} // namespace torch
+} // namespace torch::jit

torch/csrc/jit/backends/backend_debug_handler.h

@@ -7,8 +7,7 @@
 
 #include <atomic>
 
-namespace torch {
-namespace jit {
+namespace torch::jit {
 
 /*
  *  BackendDebugHandleManager is responsible for issuing debug handles to
@@ -136,5 +135,4 @@ class TORCH_API BackendDebugInfoRecorder {
   BackendDebugInfoMapType handles_to_inlined_callstack_ptrs_;
 };
 
-} // namespace jit
-} // namespace torch
+} // namespace torch::jit

torch/csrc/jit/backends/backend_debug_info.cpp

@@ -1,9 +1,7 @@
 #include <c10/macros/Macros.h>
 #include <torch/csrc/jit/backends/backend_debug_info.h>
 
-namespace torch {
-namespace jit {
-namespace backend {
+namespace torch::jit::backend {
 namespace {
 #ifdef BUILD_LITE_INTERPRETER
 static auto cls = torch::class_<PyTorchBackendDebugInfoDummy>(
@@ -18,6 +16,4 @@ static auto cls = torch::class_<PyTorchBackendDebugInfo>(
 #endif
 
 } // namespace
-} // namespace backend
-} // namespace jit
-} // namespace torch
+} // namespace torch::jit::backend

torch/csrc/jit/backends/backend_debug_info.h

@@ -5,8 +5,7 @@
 #endif
 #include <torch/custom_class.h>
 
-namespace torch {
-namespace jit {
+namespace torch::jit {
 
 constexpr static auto kBackendUtilsNamespace = "backendutils";
 constexpr static auto kBackendDebugInfoClass = "BackendDebugInfo";
@@ -61,5 +60,4 @@ class PyTorchBackendDebugInfoDummy : public torch::CustomClassHolder {
   PyTorchBackendDebugInfoDummy() = default;
 };
 #endif
-} // namespace jit
-} // namespace torch
+} // namespace torch::jit

torch/csrc/jit/backends/backend_detail.h

@@ -6,8 +6,7 @@
 
 #include <functional>
 
-namespace torch {
-namespace jit {
+namespace torch::jit {
 
 using DebugHandleType = int64_t;
 
@@ -37,5 +36,4 @@ TORCH_API Module codegen_backend_module(
     const c10::Dict<IValue, IValue>& method_compile_spec,
     const c10::DictTypePtr& any_dict_ty);
 } // namespace detail
-} // namespace jit
-} // namespace torch
+} // namespace torch::jit

torch/csrc/jit/backends/backend_init.cpp

@@ -7,8 +7,7 @@
 #include <torch/csrc/jit/python/pybind_utils.h>
 #include <torch/csrc/utils/pybind.h>
 
-namespace torch {
-namespace jit {
+namespace torch::jit {
 
 // Get all types that are shared in the module hierarchy rooted at \p mod.
 std::unordered_set<TypePtr> getSharedModuleTypes(Module& mod) {
@@ -189,5 +188,4 @@ void initJitBackendBindings(PyObject* module) {
             "Object ", py::str(orig_module), " is not a ScriptModule"));
       });
 }
-} // namespace jit
-} // namespace torch
+} // namespace torch::jit

torch/csrc/jit/backends/backend_init.h

@@ -3,9 +3,7 @@
 #include <torch/csrc/jit/python/pybind.h>
 #include <torch/csrc/utils/pybind.h>
 
-namespace torch {
-namespace jit {
+namespace torch::jit {
 // Initialize Python bindings for JIT to_<backend> functions.
 void initJitBackendBindings(PyObject* module);
-} // namespace jit
-} // namespace torch
+} // namespace torch::jit

torch/csrc/jit/backends/backend_interface.cpp

@@ -1,10 +1,8 @@
 #include <torch/csrc/jit/backends/backend_interface.h>
 
-namespace torch {
-namespace jit {
+namespace torch::jit {
 
 PyTorchBackendInterface::PyTorchBackendInterface() noexcept = default;
 PyTorchBackendInterface::~PyTorchBackendInterface() = default;
 
-} // namespace jit
-} // namespace torch
+} // namespace torch::jit

torch/csrc/jit/backends/backend_interface.h

@@ -2,8 +2,7 @@
 
 #include <torch/custom_class.h>
 
-namespace torch {
-namespace jit {
+namespace torch::jit {
 
 // Interface for a JIT backend.
 class TORCH_API PyTorchBackendInterface : public torch::CustomClassHolder {
@@ -30,5 +29,4 @@ class TORCH_API PyTorchBackendInterface : public torch::CustomClassHolder {
       c10::IValue handle,
       c10::impl::GenericList inputs) = 0;
 };
-} // namespace jit
-} // namespace torch
+} // namespace torch::jit

torch/csrc/jit/backends/backend_preprocess.h

@@ -1,8 +1,7 @@
 #pragma once
 
 #include <torch/csrc/jit/backends/backend_detail.h>
-namespace torch {
-namespace jit {
+namespace torch::jit {
 class backend_preprocess_register {
   std::string backend_name_;
 
@@ -14,5 +13,4 @@ class backend_preprocess_register {
     detail::registerBackendPreprocessFunction(name, preprocess);
   }
 };
-} // namespace jit
-} // namespace torch
+} // namespace torch::jit

torch/csrc/jit/backends/backend_resolver.cpp

@@ -2,8 +2,7 @@
 #include <torch/csrc/jit/frontend/sugared_value.h>
 #include <torch/custom_class.h>
 
-namespace torch {
-namespace jit {
+namespace torch::jit {
 namespace {
 // Essentially ClassNamespaceValue from import_source.cpp without the
 // SourceImporterImpl reference. This helps resolve the
@@ -67,5 +66,4 @@ std::shared_ptr<Resolver> loweredModuleResolver() {
   return resolver;
 }
 
-} // namespace jit
-} // namespace torch
+} // namespace torch::jit

torch/csrc/jit/backends/backend_resolver.h

@@ -2,9 +2,7 @@
 
 #include <torch/csrc/jit/frontend/resolver.h>
 
-namespace torch {
-namespace jit {
+namespace torch::jit {
 // Create a Resolver for use in generating LoweredModules for specific backends.
 TORCH_API std::shared_ptr<Resolver> loweredModuleResolver();
-} // namespace jit
-} // namespace torch
+} // namespace torch::jit

torch/csrc/jit/backends/coreml/objc/PTMCoreMLTensorSpec.h

@@ -3,10 +3,7 @@
 
 #include <string>
 
-namespace torch {
-namespace jit {
-namespace mobile {
-namespace coreml {
+namespace torch::jit::mobile::coreml {
 
 struct TensorSpec {
   std::string name = "";
@@ -26,7 +23,4 @@ static inline c10::ScalarType scalar_type(const std::string& type_string) {
   return c10::ScalarType::Undefined;
 }
 
-} // namespace coreml
-} // namespace mobile
-} // namespace jit
-} // namespace torch
+} // namespace torch::jit::mobile::coreml

torch/csrc/jit/backends/xnnpack/executor/xnn_executor.h

@@ -8,10 +8,7 @@
 #include <memory>
 #include <vector>
 
-namespace torch {
-namespace jit {
-namespace xnnpack {
-namespace delegate {
+namespace torch::jit::xnnpack::delegate {
 
 class XNNExecutor {
  private:
@@ -68,7 +65,4 @@ class XNNExecutor {
   friend class XNNCompiler;
 };
 
-} // namespace delegate
-} // namespace xnnpack
-} // namespace jit
-} // namespace torch
+} // namespace torch::jit::xnnpack::delegate

torch/csrc/jit/codegen/cuda/interface.cpp

@@ -9,10 +9,7 @@
 #include <torch/csrc/jit/runtime/custom_operator.h>
 #include <torch/csrc/jit/runtime/register_ops_utils.h>
 
-namespace torch {
-namespace jit {
-namespace fuser {
-namespace cuda {
+namespace torch::jit::fuser::cuda {
 
 static std::atomic<bool> cuda_fusion_guard_mode{true};
 
@@ -131,7 +128,4 @@ bool skipNode(const std::string& symbol_str, bool flip) {
       getFuserInterface()->fn_skip_n(symbol_str, flip);
 }
 
-} // namespace cuda
-} // namespace fuser
-} // namespace jit
-} // namespace torch
+} // namespace torch::jit::fuser::cuda

torch/csrc/jit/codegen/cuda/interface.h

@@ -13,10 +13,7 @@
  * Registration is done in torch/csrc/jit/codegen/cuda/register_interface.cpp
  */
 
-namespace torch {
-namespace jit {
-namespace fuser {
-namespace cuda {
+namespace torch::jit::fuser::cuda {
 
 TORCH_API std::atomic<bool>& getCudaFusionGuardMode();
 
@@ -52,7 +49,4 @@ TORCH_API bool isEnabled();
 TORCH_API bool setEnabled(bool is_enabled);
 TORCH_API bool canBeEnabled();
 
-} // namespace cuda
-} // namespace fuser
-} // namespace jit
-} // namespace torch
+} // namespace torch::jit::fuser::cuda

torch/csrc/jit/codegen/fuser/cpu/fused_kernel.h

@@ -13,10 +13,7 @@ namespace at {
 struct DynamicLibrary;
 }
 
-namespace torch {
-namespace jit {
-namespace fuser {
-namespace cpu {
+namespace torch::jit::fuser::cpu {
 
 // Represents a compiled CPU kernel and the metadata necessary to run it
 struct TORCH_API FusedKernelCPU : public FusedKernel {
@@ -43,7 +40,4 @@ struct TORCH_API FusedKernelCPU : public FusedKernel {
   void (*kernel)(uint32_t, void**) = nullptr;
 };
 
-} // namespace cpu
-} // namespace fuser
-} // namespace jit
-} // namespace torch
+} // namespace torch::jit::fuser::cpu

torch/csrc/jit/codegen/fuser/cpu/resource_strings.h

@@ -2,10 +2,7 @@
 
 #include <ATen/code_template.h>
 
-namespace torch {
-namespace jit {
-namespace fuser {
-namespace cpu {
+namespace torch::jit::fuser::cpu {
 
 /*with type_as not checking type of its input, a fusion group can have non-fp32
 tensor as input. Correct code for this case is generated, however, nvrtc does
@@ -101,7 +98,4 @@ JIT_API void ${kernelName}(IndexType totalElements, void ** args) {
 }
 )");
 
-} // namespace cpu
-} // namespace fuser
-} // namespace jit
-} // namespace torch
+} // namespace torch::jit::fuser::cpu

torch/csrc/jit/codegen/fuser/cpu/temp_file.h

@@ -22,10 +22,7 @@
 #include <string>
 #include <vector>
 
-namespace torch {
-namespace jit {
-namespace fuser {
-namespace cpu {
+namespace torch::jit::fuser::cpu {
 
 #ifdef _MSC_VER
 int wmkstemps(wchar_t* tmpl, int suffix_len) {
@@ -135,7 +132,4 @@ struct TempFile {
   std::string name_;
 };
 
-} // namespace cpu
-} // namespace fuser
-} // namespace jit
-} // namespace torch
+} // namespace torch::jit::fuser::cpu

torch/csrc/jit/codegen/onednn/LlgaTensorImpl.cpp

@@ -4,10 +4,7 @@
 #include <c10/core/CPUAllocator.h>
 #include <torch/csrc/jit/codegen/onednn/LlgaTensorImpl.h>
 
-namespace torch {
-namespace jit {
-namespace fuser {
-namespace onednn {
+namespace torch::jit::fuser::onednn {
 
 // Non-default dnnl::graph::allocator needs an allocator.
 // We would let it use c10::GetCPUAllocator's allocator,
@@ -152,9 +149,6 @@ at::ScalarType LlgaTensorDesc::aten_scalar_type() const {
   }
 }
 
-} // namespace onednn
-} // namespace fuser
-} // namespace jit
-} // namespace torch
+} // namespace torch::jit::fuser::onednn
 
 #endif // AT_MKLDNN_ENABLED()

torch/csrc/jit/codegen/onednn/LlgaTensorImpl.h

@@ -6,10 +6,7 @@
 #include <oneapi/dnnl/dnnl_graph.hpp>
 #include <torch/csrc/jit/ir/ir.h>
 
-namespace torch {
-namespace jit {
-namespace fuser {
-namespace onednn {
+namespace torch::jit::fuser::onednn {
 
 // Engine represents a device and its context. From the device kind, the engine
 // knows how to generate code for the target device and what kind of device
@@ -270,7 +267,4 @@ at::Tensor empty_llga(
 
 dnnl::graph::tensor llga_from_aten_tensor(const at::Tensor& tensor);
 
-} // namespace onednn
-} // namespace fuser
-} // namespace jit
-} // namespace torch
+} // namespace torch::jit::fuser::onednn