[4/N] Enable clang-tidy in torch/csrc/autograd (#109455)

The PR enables clang-tidy checks in torch/csrc/autograd.

Pull Request resolved: #109455
Approved by: https://github.com/Skylion007

.lintrunner.toml

@@ -274,7 +274,9 @@ exclude_patterns = [
     'c10/test/**',
     'third_party/**/*',
     'torch/csrc/api/**',
-    'torch/csrc/autograd/**',
+    'torch/csrc/autograd/functions/**',
+    'torch/csrc/autograd/generated/**',
+    'torch/csrc/autograd/profiler_legacy.cpp',
     'torch/csrc/CudaIPCTypes.cpp',
     'torch/csrc/cuda/**',
     'torch/csrc/dynamo/*',

tools/autograd/templates/VariableType.h

@@ -52,7 +52,7 @@ namespace VariableType {
   at::Tensor & unpack(Tensor & t, const char * name, int pos);
   const at::Tensor & unpack(const Tensor & t, const char * name, int pos);
   at::Tensor unpack_opt(const Tensor & t, const char * name, int pos);
-  std::vector<at::Tensor> unpack(at::ITensorListRef tl, const char *name, int pos);
+  std::vector<at::Tensor> unpack(const at::ITensorListRef& tl, const char *name, int pos);
 };
 
 }} // namespace torch::autograd

torch/csrc/autograd/TraceTypeManual.cpp

@@ -176,7 +176,8 @@ static void general_trace_function(
     tracer::recordSourceLocation(node);
     const auto& args = op.schema().arguments();
     int i = 0;
-    for (auto iter = stack->end() - input_size; iter != stack->end();
+    for (auto iter = stack->end() - static_cast<std::ptrdiff_t>(input_size);
+         iter != stack->end();
          ++iter, ++i) {
       // TODO we need to refactor graph APIs (e.g., addInputs)
       // appropriately; after that, we can get rid of the giant if-else
@@ -266,7 +267,8 @@ static void general_trace_function(
   if (tracer_state) {
     tracer::setTracingState(std::move(tracer_state));
     int i = 0;
-    for (auto iter = stack->end() - output_size; iter != stack->end();
+    for (auto iter = stack->end() - static_cast<std::ptrdiff_t>(output_size);
+         iter != stack->end();
          ++iter, ++i) {
       const auto& type = op.schema().returns()[i].type();
       if (type->isSubtypeOf(*TensorType::get())) {

torch/csrc/autograd/VariableTypeManual.cpp

@@ -97,7 +97,7 @@ Tensor unpack_opt(const Tensor& t, const char* name, int pos) {
 }
 
 std::vector<at::Tensor> unpack(
-    at::ITensorListRef tl,
+    const at::ITensorListRef& tl,
     const char* name,
     int pos) {
   std::vector<at::Tensor> ret;
@@ -447,13 +447,12 @@ static Tensor detach(c10::DispatchKeySet ks, const Tensor& self) {
   // NB: we can't make detach() a normal view operator because the codegen
   // generates allow_tensor_metadata_change = True for them. In the future we
   // should have an option for this in the codegen.
-  std::function<at::Tensor(const at::Tensor&)> func = nullptr;
   auto result = as_view(
       /* base */ self,
       /* output */ out,
       /* is_bw_differentiable */ false,
       /* is_fw_differentiable */ false,
-      /* view_func */ std::move(func),
+      /* view_func */ nullptr,
       /* creation_meta */ CreationMeta::DEFAULT,
       /*allow_tensor_metadata_change=*/false);
 

torch/csrc/autograd/autograd_not_implemented_fallback.cpp

@@ -270,7 +270,7 @@ static void autogradNotImplementedFallbackImpl(
     }
   }
 
-  int aliased_input_idx = -1;
+  int64_t aliased_input_idx = -1;
   for (const auto i : c10::irange(num_arguments)) {
     if (schema.is_aliasing({c10::SchemaArgType::input, i}) &&
         !schema.is_mutable({c10::SchemaArgType::input, i})) {
@@ -279,7 +279,7 @@ static void autogradNotImplementedFallbackImpl(
           "Expected only a single input in the operator schema to have a non-write alias annotation (i.e., 'Tensor(a)'). "
           "Non-composite functions where multiple inputs are aliased with outputs aren't supported. "
           "Please rewrite your function as a composite function.");
-      aliased_input_idx = i;
+      aliased_input_idx = static_cast<int64_t>(i);
     }
   }
 
@@ -479,7 +479,7 @@ static void autogradNotImplementedInplaceOrViewFallbackImpl(
           "non-write alias annotation (i.e., 'Tensor(a)'). "
           "Non-composite functions where multiple outputs are aliased with inputs aren't supported."
           "Please rewrite your function as a composite function.");
-      aliased_output_idx = i;
+      aliased_output_idx = static_cast<int64_t>(i);
     }
   }
 

torch/csrc/autograd/engine.cpp

@@ -639,6 +639,7 @@ void Engine::reentrant_thread_init() {
 }
 
 void Engine::thread_on_exception(
+    // NOLINTNEXTLINE(performance-unnecessary-value-param)
     std::shared_ptr<GraphTask> graph_task,
     const std::shared_ptr<Node>& fn,
     std::exception& e) {
@@ -953,6 +954,7 @@ static variable_list call_function(
   });
 
   if (has_post_hooks) {
+    // NOLINTNEXTLINE(bugprone-use-after-move)
     return call_post_hooks(fn, std::move(outputs), inputs);
   }
   return outputs;

torch/csrc/autograd/functions/basic_ops.h

@@ -44,7 +44,7 @@ struct TORCH_API NotImplemented : public Error {
 // Identity in forward, Error in backward. Used to implement
 // @once_differentiable
 struct TORCH_API DelayedError : public Node {
-  DelayedError(std::string msg, int num_inputs) : msg(std::move(msg)) {
+  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

torch/csrc/autograd/functions/comm.cpp

@@ -8,7 +8,6 @@
 
 #include <ATen/ATen.h>
 #include <ATen/cuda/CUDAContext.h>
-#include <c10/util/Optional.h>
 
 #include <cstddef>
 #include <memory>
@@ -44,8 +43,8 @@ variable_list Scatter::apply(variable_list&& inputs) {
   auto device_indices = fmap(devices_, [](const at::Device& device) -> int64_t {
     return device.index();
   });
-  auto tensors = torch::cuda::scatter(
-      std::move(input), device_indices, chunk_sizes_, dim_, streams_);
+  auto tensors =
+      torch::cuda::scatter(input, device_indices, chunk_sizes_, dim_, streams_);
 
   std::vector<Variable> variables;
   variables.reserve(tensors.size());

torch/csrc/autograd/functions/comm.h

@@ -5,8 +5,8 @@
 #include <torch/csrc/autograd/variable.h>
 
 #include <ATen/ATen.h>
-#include <ATen/cuda/ATenCUDAGeneral.h>
-#include <ATen/cuda/CUDAContext.h>
+#include <c10/cuda/CUDAStream.h>
+#include <c10/util/Optional.h>
 
 #include <cstddef>
 #include <vector>

torch/csrc/autograd/functions/init.cpp

@@ -31,7 +31,7 @@ struct DelayedErrorCtor {
     auto arg2 = PyTuple_GET_ITEM(args, 1);
     TORCH_CHECK(
         THPUtils_checkLong(arg2), "argument 'num_inputs' must be an int");
-    int num_inputs = THPUtils_unpackLong(arg2);
+    auto num_inputs = THPUtils_unpackLong(arg2);
     return new DelayedError(std::move(msg), num_inputs);
   }
 };

torch/csrc/autograd/profiler_python.cpp

@@ -676,6 +676,7 @@ struct ThreadLocalResults {
 class PythonTracer final : public python_tracer::PythonTracerBase {
  public:
   PythonTracer(torch::profiler::impl::RecordQueue* queue);
+  // NOLINTNEXTLINE(bugprone-exception-escape)
   ~PythonTracer() override;
 
   static int pyProfileFn(
@@ -816,6 +817,7 @@ void PythonTracer::stop() {
   }
 }
 
+// NOLINTNEXTLINE(bugprone-exception-escape)
 PythonTracer::~PythonTracer() {
   if (active_) {
     TORCH_WARN("`PythonTracer::stop()` was not called.");

torch/csrc/autograd/python_hook.cpp

@@ -99,6 +99,7 @@ PyFunctionTensorPreHook::PyFunctionTensorPreHook(
   Py_INCREF(dict);
 }
 
+// NOLINTNEXTLINE(bugprone-exception-escape)
 PyFunctionTensorPreHook::~PyFunctionTensorPreHook() {
   // If python is already dead, leak the wrapped python objects
   if (Py_IsInitialized()) {
@@ -127,6 +128,7 @@ PyFunctionPreHook::PyFunctionPreHook(PyObject* dict) : dict(dict) {
   Py_INCREF(dict);
 }
 
+// NOLINTNEXTLINE(bugprone-exception-escape)
 PyFunctionPreHook::~PyFunctionPreHook() {
   // If python is already dead, leak the wrapped python objects
   if (Py_IsInitialized()) {
@@ -149,6 +151,7 @@ PyFunctionPostHook::PyFunctionPostHook(PyObject* dict) : dict(dict) {
   Py_INCREF(dict);
 }
 
+// NOLINTNEXTLINE(bugprone-exception-escape)
 PyFunctionPostHook::~PyFunctionPostHook() {
   // If python is already dead, leak the wrapped python objects
   if (Py_IsInitialized()) {
@@ -205,6 +208,7 @@ PyFunctionTensorPostAccGradHooks::PyFunctionTensorPostAccGradHooks(
   Py_INCREF(dict);
 }
 
+// NOLINTNEXTLINE(bugprone-exception-escape)
 PyFunctionTensorPostAccGradHooks::~PyFunctionTensorPostAccGradHooks() {
   // If python is already dead, leak the wrapped python objects
   if (Py_IsInitialized()) {

torch/csrc/autograd/python_saved_variable_hooks.cpp

@@ -45,6 +45,7 @@ at::Tensor PySavedVariableHooks::call_unpack_hook() {
   // unpack_hook_ will be manually decrefed when the saved variable is released
 }
 
+// NOLINTNEXTLINE(bugprone-exception-escape)
 PySavedVariableHooks::~PySavedVariableHooks() {
   // If python is already dead, leak the wrapped python objects
   if (Py_IsInitialized()) {

torch/csrc/autograd/record_function_ops.cpp

@@ -82,7 +82,7 @@ c10::intrusive_ptr<c10::ivalue::Future> _call_end_callbacks_on_fut(
     const c10::intrusive_ptr<c10::ivalue::Future>& fut) {
   // Profiling callback that ends the associated record_function
   // and returns the value of the passed in future.
-  std::function<c10::IValue(c10::ivalue::Future&)> futureProfilingFunc =
+  auto futureProfilingFunc =
       [get_record = std::move(get_record)](c10::ivalue::Future& fut) {
         auto& rec = get_record();
         rec.end();

torch/csrc/autograd/variable.h

@@ -267,8 +267,7 @@ struct TORCH_API AutogradMeta : public c10::AutogradMetaInterface {
   /// Sets the `requires_grad` property of `Variable`. This should be true for
   /// leaf variables that want to accumulate gradients, and false for all other
   /// variables.
-  void set_requires_grad(bool requires_grad, at::TensorImpl* self_impl)
-      override {
+  void set_requires_grad(bool requires_grad, at::TensorImpl* self_impl) final {
     TORCH_CHECK(
         !requires_grad ||
             isDifferentiableType(at::typeMetaToScalarType(self_impl->dtype())),