[1/N] Fix clang-tidy warnings in torch/csrc/autograd (#133180)

Fixes #ISSUE_NUMBER

Pull Request resolved: https://github.com/pytorch/pytorch/pull/133180
Approved by: https://github.com/albanD

torch/csrc/autograd/functions/accumulate_grad.cpp

@@ -12,8 +12,7 @@
 #include <stdexcept>
 #include <utility>
 
-namespace torch {
-namespace autograd {
+namespace torch::autograd {
 
 // AccumulateGrad sets sequence_nr to the max value so it's always called
 // ASAP during backwards.
@@ -104,5 +103,4 @@ variable_list AccumulateGrad::apply_with_saved(
   return variable_list();
 }
 
-} // namespace autograd
-} // namespace torch
+} // namespace torch::autograd

torch/csrc/autograd/functions/accumulate_grad.h

@@ -16,8 +16,7 @@
 
 #include <mutex>
 
-namespace torch {
-namespace autograd {
+namespace torch::autograd {
 
 #define CHECK_RESULT(RESULT, VAR)                                          \
   if (!(RESULT.is_sparse() || VAR.is_sparse() || RESULT.is_sparse_csr() || \
@@ -273,5 +272,4 @@ struct TORCH_API AccumulateGrad : public Node {
 
 #undef CHECK_RESULT
 
-} // namespace autograd
-} // namespace torch
+} // namespace torch::autograd

torch/csrc/autograd/functions/basic_ops.cpp

@@ -10,8 +10,7 @@
 #include <memory>
 #include <utility>
 
-namespace torch {
-namespace autograd {
+namespace torch::autograd {
 
 auto Error::apply(variable_list&& inputs) -> variable_list {
   throw std::runtime_error(msg);
@@ -79,5 +78,4 @@ variable_list GraphRoot::apply_with_saved(
   return result;
 }
 
-} // namespace autograd
-} // namespace torch
+} // namespace torch::autograd

torch/csrc/autograd/functions/basic_ops.h

@@ -9,8 +9,7 @@
 #include <string>
 #include <vector>
 
-namespace torch {
-namespace autograd {
+namespace torch::autograd {
 
 struct TORCH_API Error : public Node {
   Error(std::string msg, edge_list&& next_edges)
@@ -45,9 +44,7 @@ struct TORCH_API NotImplemented : public Error {
 // @once_differentiable
 struct TORCH_API DelayedError : public Node {
   DelayedError(std::string msg, int64_t num_inputs) : msg(std::move(msg)) {
-    // NOLINTNEXTLINE(clang-analyzer-deadcode.DeadStores)
-    for (const auto i : c10::irange(num_inputs)) {
-      (void)i; // Suppress unused variable warning
+    for (const auto _ [[maybe_unused]] : c10::irange(num_inputs)) {
       add_input_metadata(Node::undefined_input());
     }
   }
@@ -107,5 +104,4 @@ struct TORCH_API Identity : public Node {
   variable_list apply(variable_list&& inputs) override;
 };
 
-} // namespace autograd
-} // namespace torch
+} // namespace torch::autograd

torch/csrc/autograd/functions/comm.cpp

@@ -9,12 +9,10 @@
 #include <ATen/ATen.h>
 #include <ATen/cuda/CUDAContext.h>
 
-#include <cstddef>
 #include <memory>
 #include <vector>
 
-namespace torch {
-namespace autograd {
+namespace torch::autograd {
 Scatter::Scatter(
     std::vector<at::Device> devices,
     std::optional<std::vector<int64_t>> chunk_sizes,
@@ -137,5 +135,4 @@ variable_list Gather::apply(variable_list&& inputs) {
   return {variable};
 }
 
-} // namespace autograd
-} // namespace torch
+} // namespace torch::autograd

torch/csrc/autograd/functions/comm.h

@@ -11,8 +11,7 @@
 #include <cstddef>
 #include <vector>
 
-namespace torch {
-namespace autograd {
+namespace torch::autograd {
 
 struct TORCH_CUDA_CU_API Scatter : public Node {
   explicit Scatter(
@@ -43,5 +42,4 @@ struct TORCH_CUDA_CU_API Gather : public Node {
   int64_t dim_;
 };
 
-} // namespace autograd
-} // namespace torch
+} // namespace torch::autograd

torch/csrc/autograd/functions/tensor.cpp

@@ -10,13 +10,11 @@
 #include <ATen/ATen.h>
 #include <c10/util/irange.h>
 
-#include <cstddef>
 #include <memory>
 #include <stdexcept>
 #include <utility>
 
-namespace torch {
-namespace autograd {
+namespace torch::autograd {
 
 auto CopyBackwards::apply(variable_list&& grads) -> variable_list {
   check_input_variables("CopyBackwards", grads, 1, -1, true);
@@ -213,5 +211,4 @@ auto CopySlices::apply(variable_list&& inputs1) -> variable_list {
   });
 }
 
-} // namespace autograd
-} // namespace torch
+} // namespace torch::autograd

torch/csrc/autograd/functions/tensor.h

@@ -11,8 +11,7 @@
 #include <cstdint>
 #include <memory>
 
-namespace torch {
-namespace autograd {
+namespace torch::autograd {
 
 struct TORCH_API CopyBackwards : public Node {
   variable_list apply(variable_list&& grads) override;
@@ -182,5 +181,4 @@ struct TORCH_API CopySlices : public Node {
   std::shared_ptr<Node> fn;
 };
 
-} // namespace autograd
-} // namespace torch
+} // namespace torch::autograd

torch/csrc/autograd/functions/utils.cpp

@@ -6,10 +6,8 @@
 #include <torch/csrc/autograd/variable.h>
 
 #include <sstream>
-#include <vector>
 
-namespace torch {
-namespace autograd {
+namespace torch::autograd {
 
 variable_list wrap_outputs(
     const variable_list& inputs,
@@ -66,5 +64,4 @@ void check_input_variables(
     }
   }
 }
-} // namespace autograd
-} // namespace torch
+} // namespace torch::autograd

torch/csrc/autograd/functions/utils.h

@@ -13,8 +13,7 @@
 #include <memory>
 #include <vector>
 
-namespace torch {
-namespace autograd {
+namespace torch::autograd {
 
 using function_constructor = std::function<std::shared_ptr<Node>(edge_list&&)>;
 
@@ -105,10 +104,9 @@ inline bool isFwGradDefinedTensorList(
   bool ret = false;
   for (auto i : c10::irange(li.size())) {
     auto t = li.get(i);
-    ret |= (t.has_value() && isFwGradDefined(t.value()));
+    ret |= isFwGradDefined(t);
   }
   return ret;
 }
 
-} // namespace autograd
-} // namespace torch
+} // namespace torch::autograd