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

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

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

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 @@ public:
   }
 };
 
-}} // 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

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

@@ -5,10 +5,9 @@ namespace at {
 class TensorBase;
 }
 
-namespace at {
-namespace native {
+namespace at::native {
 void launch_gather_topk_kernel(
     const TensorBase& self,
     int64_t k, int64_t dim, bool largest,
     const TensorBase& values, const TensorBase& indices);
-}}
+}

aten/src/ATen/native/cudnn/ConvPlaceholders.cpp

@@ -12,8 +12,7 @@
 #include <ATen/ops/cudnn_convolution_transpose_native.h>
 #endif
 
-namespace at {
-namespace native {
+namespace at::native {
 
 // ---------------------------------------------------------------------
 //
@@ -244,5 +243,4 @@ Tensor cudnn_convolution_add_relu(
 
 #endif // AT_CUDNN_ENABLED
 
-} // namespace native
-} // namespace at
+} // namespace at::native

aten/src/ATen/native/cudnn/MHA.h

@@ -1,8 +1,7 @@
 #pragma once
 #include <ATen/core/Tensor.h>
 
-namespace at {
-namespace native {
+namespace at::native {
 
 void run_cudnn_SDP_fprop(
     int64_t b,
@@ -47,5 +46,4 @@ void run_cudnn_SDP_bprop(
     const Tensor& dropoutseed,
     const Tensor& dropoutoffset);
 
-} // namespace native
-} // namespace at
+} // namespace at::native

aten/src/ATen/native/metal/MetalConvParams.h

@@ -6,7 +6,7 @@
 namespace at::native::metal {
 
 struct Conv2DParams final {
-  Conv2DParams() {}
+  Conv2DParams() = default;
   Conv2DParams(
       c10::IntArrayRef inputSizes,
       c10::IntArrayRef weightSizes,

aten/src/ATen/native/metal/MetalGuardImpl.cpp

@@ -1,8 +1,7 @@
 #include <c10/core/impl/DeviceGuardImplInterface.h>
 #include <c10/macros/Macros.h>
 
-namespace at {
-namespace detail {
+namespace at::detail {
 
 struct MetalGuardImpl final : public c10::impl::DeviceGuardImplInterface {
   MetalGuardImpl() = default;
@@ -60,5 +59,4 @@ struct MetalGuardImpl final : public c10::impl::DeviceGuardImplInterface {
 
 C10_REGISTER_GUARD_IMPL(Metal, MetalGuardImpl)
 
-} // namespace detail
 } // namespace at

aten/src/ATen/native/miopen/BatchNorm_miopen.cpp

@@ -17,7 +17,7 @@
 
 #if !AT_ROCM_ENABLED()
 
-namespace at { namespace native {
+namespace at::native {
 
 // See Note [ATen preprocessor philosophy]
 
@@ -33,7 +33,7 @@ std::tuple<Tensor, Tensor, Tensor> miopen_batch_norm_backward(
   TORCH_CHECK(false, "miopen_batch_norm_backward: ATen not compiled with MIOpen support");
 }
 
-}}  // namespace at::native
+}  // namespace at::native
 
 #else // AT_ROCM_ENABLED
 

aten/src/ATen/native/miopen/RNN_miopen.cpp

@@ -25,7 +25,7 @@
 
 #if !AT_ROCM_ENABLED()
 
-namespace at { namespace native {
+namespace at::native {
 
     std::tuple<Tensor, Tensor, Tensor, Tensor, Tensor> miopen_rnn(
             const Tensor& input_r, TensorList weight, int64_t weight_stride0,
@@ -46,7 +46,7 @@ namespace at { namespace native {
         TORCH_CHECK(false, "miopen_rnn_backward: ATen not compiled with MIOpen support.");
     }
 
-}} //namespace at::native
+} //namespace at::native
 
 #else // AT_ROCM_ENABLED()
 

aten/src/ATen/native/mkl/LinearAlgebra.cpp

@@ -62,7 +62,7 @@ void mkl_gemm_f16f16f32(
 #include <mkl.h>
 #include <c10/util/irange.h>
 
-namespace at { namespace native {
+namespace at::native {
 
 static CBLAS_TRANSPOSE to_cblas(TransposeType x) {
   switch (x) {
@@ -151,7 +151,7 @@ void mkl_gemm_f16f16f32(
 #endif
 }
 
-}} // namespace at::native
+} // namespace at::native
 
 #endif
 C10_DIAGNOSTIC_POP()

aten/src/ATen/native/mkl/LinearAlgebra.h

@@ -10,8 +10,7 @@
 #include <mkl.h>
 #endif
 
-namespace at {
-namespace native {
+namespace at::native {
 
 void mkl_gemm_batched(
     TransposeType trans_A, TransposeType trans_B,
@@ -48,4 +47,4 @@ void mkl_gemm_f16f16f32(
     int M, int N, int K, const float alpha,
     const c10::Half* A, int lda, const c10::Half* B, int ldb,
     const float beta, float* C, int ldc);
-}}  // namespace at::native
+}  // namespace at::native

aten/src/ATen/native/mkl/SparseBlasImpl.cpp

@@ -24,11 +24,7 @@
 #include <ATen/ops/sparse_coo_tensor.h>
 #endif
 
-namespace at {
-namespace native {
-namespace sparse {
-namespace impl {
-namespace mkl {
+namespace at::native::sparse::impl::mkl {
 
 namespace {
 
@@ -713,8 +709,4 @@ void triangular_solve_out_sparse_csr(
 #endif
 }
 
-} // namespace mkl
-} // namespace impl
-} // namespace sparse
-} // namespace native
 } // namespace at

aten/src/ATen/native/mkl/SparseBlasImpl.h

@@ -2,11 +2,7 @@
 
 #include <ATen/Tensor.h>
 
-namespace at {
-namespace native {
-namespace sparse {
-namespace impl {
-namespace mkl {
+namespace at::native::sparse::impl::mkl {
 
 void addmm_out_sparse_csr(
     const Tensor& mat1,
@@ -36,8 +32,4 @@ void triangular_solve_out_sparse_csr(
     bool transpose,
     bool unitriangular);
 
-} // namespace mkl
-} // namespace impl
-} // namespace sparse
-} // namespace native
 } // namespace at

aten/src/ATen/native/mkl/SparseCsrLinearAlgebra.cpp

@@ -40,8 +40,7 @@ Tensor& _sparse_mm_mkl_(
 #include <ATen/ExpandUtils.h>
 #include <ATen/SparseCsrTensorImpl.h>
 
-namespace at {
-namespace sparse_csr {
+namespace at::sparse_csr {
 
 #ifdef MKL_ILP64
 static constexpr ScalarType TORCH_INT_TYPE = at::kLong;
@@ -257,7 +256,6 @@ Tensor& _sparse_mm_mkl_(
   return self;
 }
 
-} // namespace native
 } // namespace at
 
 #endif // AT_MKL_ENABLED

aten/src/ATen/native/mkl/SparseCsrLinearAlgebra.h

@@ -2,8 +2,7 @@
 #include <ATen/core/Tensor.h>
 #include <ATen/SparseCsrTensorUtils.h>
 
-namespace at {
-namespace sparse_csr {
+namespace at::sparse_csr {
 Tensor& _sparse_mm_mkl_(
     Tensor& self,
     const SparseCsrTensor& sparse_,
@@ -11,5 +10,4 @@ Tensor& _sparse_mm_mkl_(
     const Tensor& t,
     const Scalar& alpha,
     const Scalar& beta);
-} // namespace native
 } // namespace at

aten/src/ATen/native/mkl/SpectralOps.cpp

@@ -21,7 +21,7 @@
 #include <ATen/Parallel.h>
 #include <ATen/TensorIterator.h>
 
-namespace at { namespace native {
+namespace at::native {
 // In real-to-complex transform, MKL FFT only fills half of the values due to
 // conjugate symmetry. See native/SpectralUtils.h for more details.
 // The following structs are used to fill in the other half with symmetry in
@@ -200,7 +200,7 @@ Tensor& _fft_c2c_mkl_out(const Tensor& self, IntArrayRef dim, int64_t normalizat
   return out.copy_(result);
 }
 
-}} // namespace at::native
+} // namespace at::native
 #endif /* AT_MKL_ENABLED() || AT_POCKETFFT_ENABLED() */
 
 #if AT_POCKETFFT_ENABLED()
@@ -342,7 +342,7 @@ Tensor _fft_c2c_mkl(const Tensor& self, IntArrayRef dim, int64_t normalization,
 #include <ATen/mkl/Limits.h>
 
 
-namespace at { namespace native {
+namespace at::native {
 
 // Constructs an mkl-fft plan descriptor representing the desired transform
 // For complex types, strides are in units of 2 * element_size(dtype)
@@ -570,7 +570,7 @@ Tensor _fft_c2c_mkl(const Tensor& self, IntArrayRef dim, int64_t normalization,
   return _exec_fft(out, self, self.sizes(), sorted_dims, normalization, forward);
 }
 
-}} // namespace at::native
+} // namespace at::native
 
 #else
 

aten/src/ATen/native/mkldnn/BinaryOps.cpp

@@ -52,8 +52,7 @@ Tensor& mkldnn_mul_(Tensor& self, const Tensor& other) {
 
 #include <ATen/native/mkldnn/MKLDNNCommon.h>
 
-namespace at {
-namespace native {
+namespace at::native {
 
 static Tensor emptyBinaryOp(const Tensor& self, const Tensor& other) {
   if (!self.requires_grad() && !other.requires_grad()) {
@@ -155,7 +154,6 @@ Tensor& mkldnn_mul_(Tensor& self, const Tensor& other) {
   return native::mkldnn_mul_out(self, other, self);
 }
 
-} // namespace native
 } // namespace at
 
 #endif // AT_MKLDNN_ENABLED

aten/src/ATen/native/mkldnn/Common.h

@@ -6,10 +6,9 @@
 #if AT_MKLDNN_ENABLED()
 
 #include <ideep/tensor.hpp>
+#include <utility>
 
-namespace at {
-namespace native {
-namespace mkldnn {
+namespace at::native::mkldnn {
 
 struct ContextConv final {
   ideep::tensor weight_packed_;
@@ -32,15 +31,13 @@ struct ContextConv final {
       ideep::attr_t attr)
       : weight_packed_(std::move(weight_packed)),
         at_bias_(std::move(at_bias)),
-        padding_(padding),
-        stride_(stride),
-        dilation_(dilation),
+        padding_(std::move(padding)),
+        stride_(std::move(stride)),
+        dilation_(std::move(dilation)),
         groups_(groups),
         attr_(attr) {}
 };
 
-} // namespace mkldnn
-} // namespace native
 } // namespace at
 
 #endif // AT_MKLDNN_ENABLED()

aten/src/ATen/native/mkldnn/Conv.cpp

@@ -41,7 +41,7 @@ REGISTER_NO_CPU_DISPATCH(mkldnn_convolution_transpose_backward_stub)
 #include <ATen/native/ConvUtils.h>
 #include <c10/util/irange.h>
 
-namespace at { namespace native {
+namespace at::native {
 
 // follow check rules from native/Convolution.cpp without transpose supported
 static void check_shape_forward(const Tensor& input,
@@ -1080,6 +1080,6 @@ TORCH_LIBRARY_IMPL(mkldnn, Meta, m) {
       TORCH_SELECTIVE_NAME("mkldnn::_convolution_transpose_pointwise"),
       TORCH_FN(mkldnn_convolution_transpose_pointwise_meta));
 }
-}}  // namespace at::native
+}  // namespace at::native
 
 #endif

aten/src/ATen/native/mkldnn/ConvPrepack.cpp

@@ -11,11 +11,7 @@
 
 #if AT_MKLDNN_ENABLED()
 
-namespace at {
-namespace native {
-namespace mkldnn {
-namespace internal {
-namespace convolution {
+namespace at::native::mkldnn::internal::convolution {
 
 c10::intrusive_ptr<mkldnn::ConvOpContext> createConvPrePackOpContext(
     Tensor weight,
@@ -280,10 +276,6 @@ Tensor conv_run(
   return op_context->run(input);
 }
 
-} // namespace convolution
-} // namespace internal
-} // namespace mkldnn
-} // namespace native
 } // namespace at
 
 #endif // AT_MKLDNN_ENABLED()

aten/src/ATen/native/mkldnn/ConvPrepack.h

@@ -6,11 +6,7 @@
 
 #if AT_MKLDNN_ENABLED()
 
-namespace at {
-namespace native {
-namespace mkldnn {
-namespace internal {
-namespace convolution {
+namespace at::native::mkldnn::internal::convolution {
 
 c10::intrusive_ptr<mkldnn::ConvOpContext> createConvPrePackOpContext(
     Tensor weight,
@@ -40,10 +36,6 @@ Tensor run(ContextConv& context, const Tensor& input);
 
 void run(ContextConv& context, const Tensor& input, void* output);
 
-} // namespace convolution
-} // namespace internal
-} // namespace mkldnn
-} // namespace native
 } // namespace at
 
 #endif // AT_MKLDNN_ENABLED()

aten/src/ATen/native/mkldnn/Copy.cpp

@@ -24,8 +24,7 @@ Tensor& copy_mkldnn_(Tensor& self, const Tensor& src, bool non_blocking) {
 
 #include <ATen/native/mkldnn/MKLDNNCommon.h>
 
-namespace at {
-namespace native {
+namespace at::native {
 
 Tensor& copy_mkldnn_(Tensor& self, const Tensor& src, bool non_blocking) {
   TORCH_CHECK(
@@ -43,7 +42,6 @@ Tensor& copy_mkldnn_(Tensor& self, const Tensor& src, bool non_blocking) {
   return self;
 }
 
-} // namespace native
 } // namespace at
 
 #endif // AT_MKLDNN_ENABLED

aten/src/ATen/native/mkldnn/Gelu.cpp

@@ -29,7 +29,7 @@ Tensor mkldnn_gelu_backward(const Tensor& grad_output, const Tensor& input, c10:
 #include <ATen/native/mkldnn/MKLDNNCommon.h>
 #include <ATen/native/mkldnn/Utils.h>
 
-namespace at { namespace native {
+namespace at::native {
 
 Tensor mkldnn_gelu(const Tensor& input, c10::string_view approximate) {
   if (input.scalar_type() == ScalarType::BFloat16) {
@@ -59,6 +59,6 @@ Tensor mkldnn_gelu_backward(const Tensor& grad_output, const Tensor& input, c10:
                                  grad_output.options().device_opt());
 }
 
-}}
+}
 
 #endif // AT_MKLDNN_ENABLED

aten/src/ATen/native/mkldnn/Linear.cpp

@@ -54,8 +54,7 @@ std::tuple<Tensor, Tensor, Tensor> mkldnn_linear_backward(
 #include <ATen/native/mkldnn/MKLDNNCommon.h>
 #include <ATen/native/mkldnn/Utils.h>
 
-namespace at {
-namespace native {
+namespace at::native {
 
 Tensor mkldnn_linear(
     const Tensor& self,
@@ -445,7 +444,6 @@ TORCH_LIBRARY_IMPL(mkldnn, MkldnnCPU, m) {
       TORCH_FN(mkldnn_linear_pointwise_binary));
 }
 
-} // namespace native
 } // namespace at
 
 #endif // AT_MKLDNN_ENABLED

aten/src/ATen/native/mkldnn/Linear.h

@@ -5,8 +5,7 @@
 
 #if AT_MKLDNN_ENABLED()
 
-namespace at {
-namespace native {
+namespace at::native {
 C10_API Tensor mkldnn_linear_pointwise(
     const Tensor& input_t,
     const Tensor& weight_t,
@@ -33,7 +32,6 @@ C10_API Tensor mkl_linear(
 
 #endif// AT_MKL_ENABLED
 
-} // namespace native
 } // namespace at
 
 #endif // AT_MKLDNN_ENABLED()

aten/src/ATen/native/mkldnn/MKLDNNCommon.cpp

@@ -7,7 +7,7 @@
 
 #include <ideep.hpp>
 
-namespace at { namespace native {
+namespace at::native {
 
 /**
  * `IntrusivePtrTargetWrapper` wraps a custom storage handle  of a tensor
@@ -209,6 +209,6 @@ TORCH_LIBRARY_IMPL(mkldnn, MkldnnCPU, m) {
       TORCH_FN(nbytes_from_mkldnn));
 }
 
-}}
+}
 
 #endif // AT_MKLDNN_ENABLED()

aten/src/ATen/native/mkldnn/MKLDNNConversions.cpp

@@ -22,7 +22,7 @@
 #endif
 
 
-namespace at { namespace native {
+namespace at::native {
 
 #if AT_MKLDNN_ENABLED()
 
@@ -637,4 +637,4 @@ TORCH_LIBRARY_IMPL(mkl, CPU, m) {
 
 #endif // AT_MKL_ENABLED && AT_MKLDNN_ENABLED
 
-}}
+}

aten/src/ATen/native/mkldnn/Matmul.cpp

@@ -93,8 +93,7 @@ void mkldnn_matmul_i8i8i32(
 #include <ATen/native/mkldnn/MKLDNNCommon.h>
 #include <ATen/native/mkldnn/Utils.h>
 
-namespace at {
-namespace native {
+namespace at::native {
 
 static bool use_mkldnn_bf16_matmul() {
   return at::globalContext().userEnabledMkldnn() && mkldnn_bf16_device_check();
@@ -513,7 +512,6 @@ void mkldnn_matmul_i8i8i32(
   }
 }
 
-} // namespace native
 } // namespace at
 
 #endif // AT_MKLDNN_ENABLED

aten/src/ATen/native/mkldnn/Matmul.h

@@ -4,7 +4,7 @@
 #include <ATen/Config.h>
 #include <ATen/native/LinearAlgebraUtils.h>  // For TransposeType
 
-namespace at { namespace native {
+namespace at::native {
 
 // result = beta * result + alpha * gemm(mat1, mat2)
 TORCH_API void mkldnn_matmul(
@@ -74,5 +74,3 @@ TORCH_API void mkldnn_matmul_i8i8i32(
     const Tensor &result);
 
 }
-
-}

aten/src/ATen/native/mkldnn/Normalization.cpp

@@ -85,8 +85,7 @@ std::tuple<Tensor, Tensor, Tensor> _new_batch_norm_backward_mkldnn(
 #include <ATen/native/layer_norm.h>
 #include <ideep/abstract_types.hpp>
 
-namespace at {
-namespace native {
+namespace at::native {
 
 std::tuple<Tensor, Tensor, Tensor> mkldnn_layer_norm_last_index_weight_bias_f32(
     const Tensor& input,
@@ -279,7 +278,6 @@ std::tuple<Tensor, Tensor, Tensor> mkldnn_batch_norm_backward(const Tensor& grad
                                               weight.options().device_opt())));
 }
 
-} // namespace native
 } // namespace at
 
 #endif // AT_MKLDNN_ENABLED

aten/src/ATen/native/mkldnn/OpContext.cpp

@@ -3,9 +3,7 @@
 #if AT_MKLDNN_ENABLED()
 #include <ATen/native/mkldnn/ConvPrepack.h>
 
-namespace at {
-namespace native {
-namespace mkldnn {
+namespace at::native::mkldnn {
 
 c10::intrusive_ptr<ConvOpContext> MkldnnConvOpContext::create_context(
     at::Tensor&& weight,
@@ -40,8 +38,6 @@ void MkldnnConvOpContext::run(const Tensor& input, void* output) {
   mkldnn::internal::convolution::run(op_context_, input, output);
 }
 
-} // namespace mkldnn
-} // namespace native
 } // namespace at
 
 #endif // AT_MKLDNN_ENABLED()

aten/src/ATen/native/mkldnn/OpContext.h

@@ -6,9 +6,7 @@
 
 #if AT_MKLDNN_ENABLED()
 
-namespace at {
-namespace native {
-namespace mkldnn {
+namespace at::native::mkldnn {
 
 const static std::map<std::string, ideep::attr_t> fusion_attr_map = {
     {"none", ideep::attr_t()},
@@ -92,8 +90,6 @@ class MkldnnConvOpContext final : public ConvOpContext {
       const ideep::attr_t& attr);
 };
 
-} // namespace mkldnn
-} // namespace native
 } // namespace at
 
 #endif // AT_MKLDNN_ENABLED()

aten/src/ATen/native/mkldnn/Pooling.cpp

@@ -195,8 +195,7 @@ Tensor mkldnn_adaptive_avg_pool2d_backward(
 #include <ATen/native/mkldnn/MKLDNNCommon.h>
 #include <ATen/native/mkldnn/Utils.h>
 
-namespace at {
-namespace native {
+namespace at::native {
 
 static Tensor _mkldnn_pooling(
     const Tensor& input,
@@ -667,7 +666,6 @@ Tensor mkldnn_adaptive_avg_pool2d_backward(
       /*algo*/ ideep::algorithm::pooling_avg_exclude_padding);
 }
 
-} // namespace native
 } // namespace at
 
 #endif // AT_MKLDNN_ENABLED

aten/src/ATen/native/mkldnn/Prelu.cpp

@@ -22,7 +22,7 @@ std::tuple<Tensor, Tensor> mkldnn_prelu_backward(const Tensor& grad_output, cons
 #include <ATen/native/mkldnn/MKLDNNCommon.h>
 #include <ATen/native/mkldnn/Utils.h>
 
-namespace at { namespace native {
+namespace at::native {
 
 Tensor mkldnn_prelu(const Tensor& input, const Tensor& weight) {
   if (input.scalar_type() == ScalarType::BFloat16) {
@@ -67,6 +67,6 @@ std::tuple<Tensor, Tensor> mkldnn_prelu_backward(const Tensor& grad_output, cons
                                                 weight.options().device_opt())));
   }
 }
-}}
+}
 
 #endif // AT_MKLDNN_ENABLED

aten/src/ATen/native/mkldnn/RegisterMkldnnOpContextClass.cpp

@@ -9,9 +9,7 @@
 #include <torch/custom_class.h>
 #include <torch/library.h>
 
-namespace at {
-namespace native {
-namespace mkldnn {
+namespace at::native::mkldnn {
 
 using namespace internal::convolution;
 
@@ -96,17 +94,13 @@ TORCH_LIBRARY_IMPL(mkldnn_prepacked, CPU, m) {
       TORCH_SELECTIVE_NAME("mkldnn_prepacked::conv2d_run"), TORCH_FN(conv_run));
 }
 
-} // namespace mkldnn
-} // namespace native
 } // namespace at
 
 #endif // AT_MKLDNN_ENABLED()
 
 #if AT_MKL_ENABLED() && AT_MKLDNN_ENABLED()
 
-namespace at {
-namespace native {
-namespace mkl {
+namespace at::native::mkl {
 
 TORCH_LIBRARY(mkl, m) {
   m.def(TORCH_SELECTIVE_SCHEMA(
@@ -115,8 +109,6 @@ TORCH_LIBRARY(mkl, m) {
       "mkl::_mkl_linear(Tensor X, Tensor MKL_W, Tensor ORI_W, Tensor? B, int batch_size) -> Tensor"));
 }
 
-} // namespace mkl
-} // namespace native
 } // namespace at
 
 #endif // AT_MKL_ENABLED && AT_MKLDNN_ENABLED

aten/src/ATen/native/mkldnn/Relu.cpp

@@ -32,7 +32,7 @@ Tensor mkldnn_relu_backward(const Tensor& grad_output, const Tensor& input, cons
 #include <ATen/native/mkldnn/MKLDNNCommon.h>
 #include <ATen/native/mkldnn/Utils.h>
 
-namespace at { namespace native {
+namespace at::native {
 
 Tensor mkldnn_relu(const Tensor& input) {
   if (input.scalar_type() == ScalarType::BFloat16) {
@@ -71,6 +71,6 @@ Tensor mkldnn_relu_backward(const Tensor& grad_output, const Tensor& input, cons
                                  grad_output.options().device_opt());
 }
 
-}}
+}
 
 #endif // AT_MKLDNN_ENABLED

aten/src/ATen/native/mkldnn/SoftMax.cpp

@@ -27,8 +27,7 @@ Tensor mkldnn_softmax(
 
 #include <ATen/native/mkldnn/MKLDNNCommon.h>
 
-namespace at {
-namespace native {
+namespace at::native {
 
 Tensor mkldnn_softmax(
     const Tensor& self,
@@ -45,7 +44,6 @@ Tensor mkldnn_softmax(
                                  self.options().device_opt());
 }
 
-} // namespace native
 } // namespace at
 
 #endif // AT_MKLDNN_ENABLED

aten/src/ATen/native/mkldnn/TensorFactories.cpp

@@ -8,7 +8,7 @@
 #include <ATen/ops/empty_native.h>
 #endif
 
-namespace at { namespace native {
+namespace at::native {
 
 #if AT_MKLDNN_ENABLED()
 
@@ -32,4 +32,4 @@ Tensor empty_mkldnn(IntArrayRef sizes, std::optional<ScalarType> dtype, std::opt
 
 #endif // AT_MKLDNN_ENABLED()
 
-}}
+}

aten/src/ATen/native/mkldnn/TensorShape.cpp

@@ -45,8 +45,7 @@ Tensor& mkldnn_transpose_(Tensor& self, int64_t dim0, int64_t dim1) {
 
 #include <ATen/native/mkldnn/MKLDNNCommon.h>
 
-namespace at {
-namespace native {
+namespace at::native {
 
 Tensor mkldnn_view(const Tensor& self, IntArrayRef size) {
   TORCH_CHECK(false,
@@ -95,7 +94,6 @@ Tensor& mkldnn_transpose_(Tensor& self, int64_t dim0, int64_t dim1) {
   TORCH_CHECK(false, "mkldnn_transpose_: in-place mkldnn operations are not supported yet");
 }
 
-} // namespace native
 } // namespace at
 
 #endif // AT_MKLDNN_ENABLED

aten/src/ATen/native/mkldnn/TensorShape.h

@@ -3,8 +3,7 @@
 #include <ATen/ATen.h>
 #include <c10/core/SymIntArrayRef.h>
 
-namespace at {
-namespace native {
+namespace at::native {
 
 Tensor mkldnn_view(const Tensor& self, IntArrayRef size);
 
@@ -12,5 +11,4 @@ Tensor mkldnn_view_symint(const Tensor& self, c10::SymIntArrayRef size);
 
 Tensor mkldnn_clone(const Tensor& self);
 
-} // namespace native
 } // namespace at

aten/src/ATen/native/mkldnn/UnaryOps.cpp

@@ -37,8 +37,7 @@ Tensor& mkldnn_tanh_(Tensor& self) {
 
 #include <ATen/native/mkldnn/MKLDNNCommon.h>
 
-namespace at {
-namespace native {
+namespace at::native {
 
 Tensor mkldnn_sigmoid(const Tensor& self) {
   ideep::tensor& x = itensor_from_mkldnn(self);
@@ -72,7 +71,6 @@ Tensor& mkldnn_tanh_(Tensor& self) {
   return self;
 }
 
-} // namespace native
 } // namespace at
 
 #endif // AT_MKLDNN_ENABLED

aten/src/ATen/native/mkldnn/Utils.cpp

@@ -3,7 +3,7 @@
 #include <ATen/native/Pool.h>
 #include <c10/util/irange.h>
 
-namespace at { namespace native {
+namespace at::native {
 
 std::vector<int64_t> pool_output_sizes(
     IntArrayRef input_size,
@@ -174,4 +174,4 @@ const std::map<c10::string_view, ideep::algorithm>& fusion_binary_alg_map() {
 }
 
 #endif // AT_MKLDNN_ENABLED()
-}}
+}

aten/src/ATen/native/quantized/AffineQuantizer.h

@@ -5,8 +5,7 @@
 #include <ATen/native/DispatchStub.h>
 #include <ATen/native/quantized/AffineQuantizerBase.h>
 
-namespace at {
-namespace native {
+namespace at::native {
 
 TORCH_API Tensor& quantize_tensor_per_tensor_affine(
     const Tensor& rtensor,
@@ -126,5 +125,4 @@ TORCH_API Tensor dequantize_tensor(
     double scale,
     int64_t zero_point);
 
-} // namespace native
 } // namespace at

aten/src/ATen/native/quantized/AffineQuantizerBase.h

@@ -2,8 +2,7 @@
 #include <c10/macros/Export.h>
 #include <c10/core/ScalarType.h>
 
-namespace at {
-namespace native {
+namespace at::native {
 
 // Quantize a float value into a uint value given scale and zero_point
 template <typename T>
@@ -43,5 +42,4 @@ requantize_from_int(double multiplier, int64_t zero_point, int64_t src);
 
 int quantize_val_float_qparams(float scale, float zero_point, float value, int qmin, int qmax);
 
-} // namespace native
 } // namespace at

aten/src/ATen/native/quantized/Copy.h

@@ -2,9 +2,7 @@
 
 #include <ATen/core/Tensor.h>
 
-namespace at {
-namespace native {
+namespace at::native {
 
 Tensor& quantized_copy_from_float_(Tensor& self, const Tensor& src);
-}
 } // namespace at

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

@@ -2,8 +2,7 @@
 #include <ATen/native/DispatchStub.h>
 #include <ATen/native/TensorIterator.h>
 
-namespace at {
-namespace native {
+namespace at::native {
 using masked_fill_kernel_quantized_fn = void(*)(TensorIterator& iter, const Scalar& value, double scale, int zero_point);
 using index_put_kernel_quantized_fn = void(*)(TensorIterator& iter, IntArrayRef index_size, IntArrayRef index_stride, bool accumulate, double scale, int zero_point);
 
@@ -11,5 +10,4 @@ DECLARE_DISPATCH(masked_fill_kernel_quantized_fn, masked_fill_kernel_quantized_s
 DECLARE_DISPATCH(index_put_kernel_quantized_fn, index_put_kernel_quantized_stub)
 
 
-} // native
 } // at

aten/src/ATen/native/quantized/cpu/OnednnUtils.h

@@ -46,7 +46,7 @@ using DeconvDesc = dnnl::deconvolution_forward::primitive_desc;
 using DeconvParams = ideep::deconv_forward_params;
 
 struct LinearPrimitiveCache : PrimitiveCache {
-  LinearPrimitiveCache() {}
+  LinearPrimitiveCache() = default;
 
   LinearPrimitiveCache(
       const PrimitiveCacheKey& key,
@@ -74,7 +74,7 @@ struct LinearPrimitiveCache : PrimitiveCache {
 };
 
 struct ConvPrimitiveCache : PrimitiveCache {
-  ConvPrimitiveCache() {}
+  ConvPrimitiveCache() = default;
 
   ConvPrimitiveCache(
       const PrimitiveCacheKey& key,
@@ -91,7 +91,7 @@ struct ConvPrimitiveCache : PrimitiveCache {
 };
 
 struct DeconvPrimitiveCache : PrimitiveCache {
-  DeconvPrimitiveCache() {}
+  DeconvPrimitiveCache() = default;
 
   DeconvPrimitiveCache(
       const PrimitiveCacheKey& key,

aten/src/ATen/native/transformers/attention.h

@@ -5,8 +5,7 @@
 #include <ATen/native/transformers/attention.h>
 #include <optional>
 
-namespace at {
-namespace native {
+namespace at::native {
 
 using fused_sdp_choice_fn = int64_t (*)(const Tensor& query_, const Tensor& key, const Tensor& value,
         const std::optional<Tensor>& attn_mask_, double dropout_p, bool is_causal, std::optional<double> scale, bool enable_gqa);
@@ -68,5 +67,4 @@ using flash_attention_backward_fn = void (*)(
 DECLARE_DISPATCH(flash_attention_fn, flash_attention_kernel)
 DECLARE_DISPATCH(flash_attention_backward_fn, flash_attention_backward_kernel)
 
-} // namespace native
 } // namespace at

aten/src/ATen/native/transformers/transformer.cpp

@@ -18,9 +18,7 @@
 #include <ATen/ops/layer_norm.h>
 #endif
 
-namespace at {
-
-namespace native {
+namespace at::native {
 
 namespace {
 Tensor linear_for_ffn(
@@ -147,5 +145,4 @@ Tensor transformer_encoder_layer_forward(
   return x;
 }
 
-} // namespace native
 } // namespace at

aten/src/ATen/native/utils/Factory.cpp

@@ -4,9 +4,7 @@
 #include <c10/core/CPUAllocator.h>
 #include <c10/util/accumulate.h>
 
-namespace at {
-namespace native {
-namespace mobile {
+namespace at::native::mobile {
 
 Tensor empty_with_tail_padding(
     const IntArrayRef size,
@@ -61,6 +59,4 @@ Tensor allocate_padded_contiguous_if_needed(
   return padded_input.copy_(input);
 }
 
-} // namespace mobile
-} // namespace native
 } // namespace at

aten/src/ATen/native/utils/Factory.h

@@ -2,9 +2,7 @@
 
 #include <ATen/core/Tensor.h>
 
-namespace at {
-namespace native {
-namespace mobile {
+namespace at::native::mobile {
 
 Tensor allocate_padded_contiguous_if_needed(
     const Tensor& input,
@@ -19,6 +17,4 @@ at::Tensor empty_with_tail_padding(
     c10::MemoryFormat memory_format,
     std::optional<DimnameList> maybe_names);
 
-} // namespace mobile
-} // namespace native
 } // namespace at

aten/src/ATen/native/vulkan/VulkanGuardImpl.cpp

@@ -1,8 +1,7 @@
 #include <c10/core/impl/DeviceGuardImplInterface.h>
 #include <c10/macros/Macros.h>
 
-namespace at {
-namespace detail {
+namespace at::detail {
 
 namespace {
 
@@ -79,5 +78,4 @@ struct VulkanGuardImpl final : public c10::impl::DeviceGuardImplInterface {
 
 C10_REGISTER_GUARD_IMPL(Vulkan, VulkanGuardImpl)
 
-} // namespace detail
-} // namespace at
+} // namespace at::detail

aten/src/ATen/native/xnnpack/Convolution.cpp

@@ -11,8 +11,7 @@
 #include <c10/util/irange.h>
 
 namespace at::native::xnnpack {
-namespace internal {
-namespace convolution2d {
+namespace internal::convolution2d {
 
 namespace {
 
@@ -464,7 +463,6 @@ Tensor conv2d_transpose_clamp_run(
   return op_context->run(input);
 }
 
-} // namespace convolution2d
 } // namespace internal
 
 bool use_convolution2d(

aten/src/ATen/nnapi/nnapi_bind.cpp

@@ -7,9 +7,7 @@
 #include <ATen/nnapi/nnapi_model_loader.h>
 #include <c10/util/irange.h>
 
-namespace torch {
-namespace nnapi {
-namespace bind {
+namespace torch::nnapi::bind {
 
 // NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
 nnapi_wrapper* nnapi;
@@ -208,6 +206,4 @@ void NnapiCompilation::get_operand_type(const at::Tensor& t, ANeuralNetworksOper
   CAFFE_THROW("Bad dtype: " + std::to_string(static_cast<int8_t>(t.scalar_type())));
 }
 
-} // namespace bind
-} // namespace nnapi
 } // namespace torch

aten/src/ATen/nnapi/nnapi_bind.h

@@ -8,9 +8,7 @@
 
 #include <ATen/nnapi/nnapi_wrapper.h>
 
-namespace torch {
-namespace nnapi {
-namespace bind {
+namespace torch::nnapi::bind {
 
 // NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
 TORCH_API extern nnapi_wrapper* nnapi;
@@ -59,8 +57,6 @@ struct NnapiCompilation : torch::jit::CustomClassHolder {
     int32_t num_outputs_ {};
 };
 
-} // namespace bind
-} // namespace nnapi
 } // namespace torch
 
 #endif // NNAPI_BIND_H_

aten/src/ATen/nnapi/nnapi_model_loader.cpp

@@ -21,8 +21,7 @@
 #define NNAPI_CHECK(res) CAFFE_ENFORCE(res == ANEURALNETWORKS_NO_ERROR, "NNAPI returned error: ", res)
 
 
-namespace caffe2 {
-namespace nnapi {
+namespace caffe2::nnapi {
 
 namespace {
 
@@ -264,4 +263,4 @@ int load_nnapi_model(
   return 0;
 }
 
-}} // namespace caffe2::nnapi
+} // namespace caffe2::nnapi

aten/src/ATen/nnapi/nnapi_model_loader.h

@@ -1,13 +1,12 @@
 #ifndef NNAPI_MODEL_LOADER_H_
 #define NNAPI_MODEL_LOADER_H_
 
-#include <stdint.h>
+#include <cstdint>
 
 #include <ATen/nnapi/NeuralNetworks.h>
 #include <ATen/nnapi/nnapi_wrapper.h>
 
-namespace caffe2 {
-namespace nnapi {
+namespace caffe2::nnapi {
 
 int load_nnapi_model(
     struct nnapi_wrapper* nnapi,
@@ -24,6 +23,6 @@ int load_nnapi_model(
     int32_t* out_output_count,
     size_t* out_bytes_consumed);
 
-}} // namespace caffe2::nnapi
+} // namespace caffe2::nnapi
 
 #endif // NNAPI_MODEL_LOADER_H_

aten/src/ATen/nnapi/nnapi_wrapper.h

@@ -17,8 +17,8 @@
 // This file is generated by nnapi/codegen.py
 #ifndef NNAPI_WRAPPER_H_
 #define NNAPI_WRAPPER_H_
-#include <stddef.h>
-#include <stdint.h>
+#include <cstddef>
+#include <cstdint>
 #include <ATen/nnapi/NeuralNetworks.h>
 struct nnapi_wrapper {
   int(*_getDeviceCount)(uint32_t* numDevices);