Modernize C++ code in aten/src/ATen/ (pytorch#141424)

Clang-tidy modernize checkers were applied, and most changes were concatenation of namespaces.

Pull Request resolved: pytorch#141424
Approved by: https://github.com/eqy

Author: cyyever

aten/src/ATen/core/boxing/impl/boxing.h

@@ -12,8 +12,7 @@
 #include <c10/util/Metaprogramming.h>
 #include <type_traits>
 
-namespace c10 {
-namespace impl {
+namespace c10::impl {
 
 //
 // utils
@@ -391,5 +390,4 @@ struct BoxedKernelWrapper<
   }
 };
 
-} // impl
 } // c10

aten/src/ATen/core/op_registration/infer_schema.cpp

@@ -4,8 +4,7 @@
 
 namespace c10 {
 
-namespace detail {
-namespace infer_schema {
+namespace detail::infer_schema {
 namespace {
 
 std::vector<Argument> createArgumentVector(c10::ArrayRef<ArgumentDef> args) {
@@ -40,7 +39,6 @@ FunctionSchema make_function_schema(
     c10::ArrayRef<ArgumentDef> returns) {
   return make_function_schema("", "", arguments, returns);
 }
-} // namespace infer_schema
 } // namespace detail
 
 std::optional<std::string> findSchemaDifferences(

aten/src/ATen/core/op_registration/infer_schema.h

@@ -9,9 +9,7 @@
 #include <c10/util/Metaprogramming.h>
 
 namespace c10 {
-namespace detail {
-
-namespace infer_schema {
+namespace detail::infer_schema {
 
 /// The templated inference code creates `ArgumentDef` instead of `Argument`,
 /// because that can be constructed at compile time and has a much smaller
@@ -142,7 +140,6 @@ FunctionSchema createFunctionSchemaFromTraitsSingleReturn(std::string&& name, st
  return make_function_schema(std::move(name), std::move(overload_name), arguments, returns);
 }
 
-}
 }
 
 template<class FuncType>

aten/src/ATen/cuda/nvrtc_stub/ATenNVRTC.cpp

@@ -1,7 +1,7 @@
 #include <ATen/cuda/nvrtc_stub/ATenNVRTC.h>
 #include <iostream>
 
-namespace at { namespace cuda {
+namespace at::cuda {
 
 NVRTC* load_nvrtc() {
   auto self = new NVRTC();
@@ -10,4 +10,4 @@ NVRTC* load_nvrtc() {
   return self;
 }
 
-}} // at::cuda
+} // at::cuda

aten/src/ATen/cuda/nvrtc_stub/ATenNVRTC.h

@@ -4,7 +4,7 @@
 #include <cuda.h>
 #include <nvrtc.h>
 
-namespace at { namespace cuda {
+namespace at::cuda {
 
 
 // NOTE [ USE OF NVRTC AND DRIVER API ]
@@ -132,4 +132,4 @@ extern "C" typedef struct NVRTC {
 } NVRTC;
 
 extern "C" TORCH_CUDA_CPP_API NVRTC* load_nvrtc();
-}} // at::cuda
+} // at::cuda

aten/src/ATen/hip/impl/HIPAllocatorMasqueradingAsCUDA.h

@@ -5,7 +5,7 @@
 
 // Use of c10::hip namespace here makes hipification easier, because
 // I don't have to also fix namespaces.  Sorry!
-namespace c10 { namespace hip {
+namespace c10::hip {
 
 // Takes a valid HIPAllocator (of any sort) and turns it into
 // an allocator pretending to be a CUDA allocator.  See
@@ -28,4 +28,4 @@ class HIPAllocatorMasqueradingAsCUDA final : public Allocator {
   }
 };
 
-}} // namespace c10::hip
+} // namespace c10::hip

aten/src/ATen/native/Distributions.h

@@ -155,7 +155,7 @@ C10_DEVICE scalar_t binomial_inversion(scalar_t count, scalar_t prob, BaseSample
 
   accscalar_t logprob = compat_log1p(-prob);
 
-  while (1) {
+  while (true) {
     U = standard_uniform.sample();
     accscalar_t geom = compat_ceil(compat_log(U) / logprob);
     geom_sum += geom;
@@ -185,7 +185,7 @@ C10_DEVICE scalar_t btrs(scalar_t count, scalar_t prob, BaseSampler<accscalar_t,
   const accscalar_t alpha = (2.83 + 5.1 / b) * stddev;
   const accscalar_t m = compat_floor((count + 1) * prob);
 
-  while (1) {
+  while (true) {
     U = standard_uniform.sample() - 0.5;
     V = standard_uniform.sample();
 

aten/src/ATen/native/PixelShuffle.h

@@ -1,8 +1,7 @@
 #include <ATen/core/Tensor.h>
 #include <c10/util/Exception.h>
 
-namespace at {
-namespace native {
+namespace at::native {
 
 inline void check_pixel_shuffle_shapes(const Tensor& self, int64_t upscale_factor) {
   TORCH_CHECK(self.dim() >= 3,
@@ -44,4 +43,4 @@ inline void check_pixel_unshuffle_shapes(const Tensor& self, int64_t downscale_f
       downscale_factor);
 }
 
-}} // namespace at::native
+} // namespace at::native

aten/src/ATen/native/SharedReduceOps.h

@@ -63,7 +63,7 @@ inline C10_DEVICE scalar_t min_propagate_nan(scalar_t a, scalar_t b) {
 #define compat_pow std::pow
 #endif
 
-namespace at { namespace native {
+namespace at::native {
 
 namespace detail {
 
@@ -539,7 +539,7 @@ struct MinMaxOps {
 #endif
 };
 
-}} // namespace at::native
+} // namespace at::native
 
 #undef MAX
 #undef MIN

aten/src/ATen/native/ao_sparse/quantized/cpu/fbgemm_utils.cpp

@@ -8,8 +8,7 @@
 #include <ATen/native/ao_sparse/quantized/cpu/packed_params.h>
 #include <ATen/native/ao_sparse/quantized/cpu/qnnpack_utils.h>
 
-namespace ao {
-namespace sparse {
+namespace ao::sparse {
 int register_linear_params() {
   static auto register_linear_params =
       torch::selective_class_<LinearPackedParamsBase>(
@@ -42,4 +41,4 @@ int register_linear_params() {
 namespace {
 [[maybe_unused]] static auto linear_params = register_linear_params();
 } // namespace
-}}  // namespace ao::sparse
+}  // namespace ao::sparse

aten/src/ATen/native/ao_sparse/quantized/cpu/fbgemm_utils.h

@@ -90,7 +90,6 @@ struct TORCH_API PackedLinearWeight
 
 #endif // USE_FBGEMM
 
-namespace ao {
-namespace sparse {
+namespace ao::sparse {
 int register_linear_params();
-}}  // namespace ao::sparse
+}  // namespace ao::sparse

aten/src/ATen/native/ao_sparse/quantized/cpu/packed_params.h

@@ -4,8 +4,7 @@
 
 #include <ATen/core/ivalue.h>
 
-namespace ao {
-namespace sparse {
+namespace ao::sparse {
 
 // <Weight, bias, out_features_block_size, in_features_block_size>
 using LinearPackedSerializationType =
@@ -72,4 +71,4 @@ struct LinearPackedParamsBase : public torch::jit::CustomClassHolder {
   const int64_t out_features_block_size_, in_features_block_size_;
 };
 
-}}  // namespace ao::sparse
+}  // namespace ao::sparse

aten/src/ATen/native/ao_sparse/quantized/cpu/qlinear.cpp

@@ -15,8 +15,7 @@
 #include <ATen/ops/empty.h>
 #endif
 
-namespace ao {
-namespace sparse {
+namespace ao::sparse {
 
 int register_linear_params();
 
@@ -257,4 +256,4 @@ TORCH_LIBRARY_IMPL(sparse, QuantizedCPU, m) {
 }
 
 } // namespace
-}} // namespace ao::sparse
+} // namespace ao::sparse

aten/src/ATen/native/ao_sparse/quantized/cpu/qlinear_deserialize.cpp

@@ -7,8 +7,7 @@
 #include <ATen/native/ao_sparse/quantized/cpu/qnnpack_utils.h>
 #endif
 
-namespace ao {
-namespace sparse {
+namespace ao::sparse {
 
 namespace {
 constexpr int64_t serialization_version_index [[maybe_unused]] = 0;
@@ -317,5 +316,4 @@ PackedLinearWeightQnnp::PackedLinearWeightQnnp(
 }
 #endif // USE_PYTORCH_QNNPACK
 
-} // namespace sparse
 } // namespace ao

aten/src/ATen/native/ao_sparse/quantized/cpu/qlinear_dynamic.cpp

@@ -18,8 +18,7 @@
 #include <ATen/ops/empty.h>
 #endif
 
-namespace ao {
-namespace sparse {
+namespace ao::sparse {
 
 int register_linear_params();
 
@@ -195,4 +194,4 @@ TORCH_LIBRARY_IMPL(sparse, CPU, m) {
 }
 
 } // namespace
-}} // namespace ao::sparse
+} // namespace ao::sparse

aten/src/ATen/native/ao_sparse/quantized/cpu/qlinear_prepack.cpp

@@ -18,8 +18,7 @@
 
 #include <algorithm>
 
-namespace ao {
-namespace sparse {
+namespace ao::sparse {
 
 int register_linear_params();
 
@@ -246,4 +245,4 @@ TORCH_LIBRARY_IMPL(sparse, QuantizedCPU, m) {
       TORCH_FN(QLinearPackWeightInt8::run));
 }
 }  // namespace
-}}  // namespace ao::sparse
+}  // namespace ao::sparse

aten/src/ATen/native/ao_sparse/quantized/cpu/qlinear_serialize.cpp

@@ -9,8 +9,7 @@
 #include <utility>
 #endif
 
-namespace ao {
-namespace sparse {
+namespace ao::sparse {
 
 namespace {
 /**
@@ -245,5 +244,4 @@ BCSRSerializationType PackedLinearWeightQnnp::serialize() {
 
 #endif // USE_PYTORCH_QNNPACK
 
-} // namespace sparse
 } // namespace ao

aten/src/ATen/native/ao_sparse/quantized/cpu/qlinear_unpack.cpp

@@ -15,8 +15,7 @@
 #include <ATen/ops/from_blob.h>
 #endif
 
-namespace ao {
-namespace sparse {
+namespace ao::sparse {
 int register_linear_params();
 
 #ifdef USE_FBGEMM
@@ -139,4 +138,4 @@ TORCH_LIBRARY_IMPL(sparse, CatchAll, m) {
       TORCH_FN(QLinearUnpackWeightInt8::run));
 }
 }  // namespace
-}}  // namespace ao::sparse
+}  // namespace ao::sparse

aten/src/ATen/native/ao_sparse/quantized/cpu/qnnpack_utils.h

@@ -11,8 +11,7 @@
 #include <pack_block_sparse.h>
 #include <ATen/native/ao_sparse/quantized/cpu/packed_params.h>
 
-namespace ao {
-namespace sparse {
+namespace ao::sparse {
 
 struct TORCH_API PackedLinearWeightQnnp
     : public LinearPackedParamsBase {
@@ -87,6 +86,6 @@ struct TORCH_API PackedLinearWeightQnnp
   at::Tensor apply_dynamic_impl(const at::Tensor& input);
 };
 
-}}  // namespace ao::sparse
+}  // namespace ao::sparse
 
 #endif // USE_PYTORCH_QNNPACK

aten/src/ATen/native/cuda/Activation.h

@@ -7,7 +7,7 @@ struct TensorIteratorBase;
 class TensorBase;
 }
 
-namespace at { namespace native {
+namespace at::native {
 
 void launch_glu_backward_kernel(const TensorIteratorBase& iter,
                                 int64_t gI_stride, int64_t I_stride);
@@ -17,4 +17,4 @@ void launch_log_sigmoid_forward_kernel(TensorIteratorBase& iter);
 void GeluCUDAKernelImpl(TensorIteratorBase& it, GeluType approximate);
 void GeluBackwardCUDAKernelImpl(TensorIteratorBase& it, GeluType approximate);
 
-}}  // namespace at::native
+}  // namespace at::native

aten/src/ATen/native/cuda/GridSampler.h

@@ -6,8 +6,7 @@ namespace at {
 class TensorBase;
 }
 
-namespace at {
-namespace native {
+namespace at::native {
 
 void launch_grid_sampler_2d_forward_kernel(
     const TensorBase &output, const TensorBase &input, const TensorBase &grid,
@@ -29,4 +28,4 @@ void launch_grid_sampler_3d_backward_kernel(
     const TensorBase &grid, int64_t interpolation_mode, int64_t padding_mode,
     bool align_corners, std::array<bool, 2> output_mask);
 
-}}  // namespace at::native
+}  // namespace at::native

aten/src/ATen/native/cuda/IndexKernel.h

@@ -7,10 +7,9 @@ struct TensorIteratorBase;
 class TensorBase;
 }
 
-namespace at {
-namespace native {
+namespace at::native {
 /// @param maskPrefixSum[in,out]
 void launch_masked_scatter_kernel(
     const TensorBase &self, const TensorBase &mask,
     const TensorBase &maskPrefixSum, const TensorBase &source);
-}}
+}

aten/src/ATen/native/cuda/ReduceOps.h

@@ -7,7 +7,7 @@ namespace c10 {
 class Scalar;
 }
 
-namespace at { namespace native {
+namespace at::native {
 
 void norm_launch_kernel(TensorIterator &iter, double val);
 void min_launch_kernel(TensorIterator &iter);
@@ -17,4 +17,4 @@ void min_all_launch_kernel(TensorIterator &iter);
 void max_all_launch_kernel(TensorIterator &iter);
 void aminmax_allreduce_launch_kernel(TensorIterator &iter);
 
-}}  // namespace at::native
+}  // namespace at::native

aten/src/ATen/native/cuda/Sorting.h

@@ -5,8 +5,7 @@ namespace at {
 class TensorBase;
 }
 
-namespace at {
-namespace native {
+namespace at::native {
 
 void launch_kthvalue_kernel(
     const TensorBase &values, const TensorBase &indices,
@@ -15,4 +14,4 @@ void launch_median_kernel(
     const TensorBase &vals, const TensorBase &inds,
     const TensorBase &in, int64_t dim, bool ignore_nan);
 
-}}  // namespace at::native
+}  // namespace at::native

aten/src/ATen/native/cuda/TensorModeKernel.h

@@ -5,8 +5,7 @@ namespace at {
 class TensorBase;
 }
 
-namespace at {
-namespace native {
+namespace at::native {
 
 void launch_fused_mode_kernel(
     const TensorBase &values, const TensorBase &indices,
@@ -16,4 +15,4 @@ void launch_apply_mode_kernel(
     const TensorBase &values, const TensorBase &indices,
     const TensorBase &self, int64_t dim, int64_t ndim);
 
-}}  // namespace at::native
+}  // namespace at::native