[BE]: Mark more hash impls as noexcept for efficiency (#171388)

Mark hashes as noexcept allow them to be recomputed as needed by STL container objects allowing them to use more efficient implementations. Most of these have very simple hash implementation or cache their hash values anyway

Pull Request resolved: https://github.com/pytorch/pytorch/pull/171388
Approved by: https://github.com/Lucaskabela, https://github.com/drisspg

aten/src/ATen/record_function.h

@@ -50,7 +50,7 @@ enum class C10_API_ENUM RecordScope : uint8_t {
 namespace std {
 template <>
 struct hash<at::RecordScope> {
-  size_t operator()(const at::RecordScope& sc) const {
+  size_t operator()(const at::RecordScope& sc) const noexcept {
     return static_cast<std::size_t>(sc);
   }
 };

c10/core/DispatchKey.h

@@ -738,7 +738,7 @@ struct hash<c10::DispatchKey> {
   typedef size_t result_type;
   typedef c10::DispatchKey argument_type;
 
-  size_t operator()(c10::DispatchKey x) const {
+  size_t operator()(c10::DispatchKey x) const noexcept {
     return static_cast<size_t>(x);
   }
 };

torch/csrc/autograd/python_variable.cpp

@@ -1101,7 +1101,7 @@ class NativeOpSchema {
         comparison_key_ == rhs.comparison_key_;
   }
 
-  std::size_t hash() const {
+  std::size_t hash() const noexcept {
     return hash_;
   }
 
@@ -1131,7 +1131,7 @@ class NativeOpSchema {
 namespace std {
 template <>
 struct hash<NativeOpSchema> {
-  std::size_t operator()(const NativeOpSchema& schema) const {
+  std::size_t operator()(const NativeOpSchema& schema) const noexcept {
     return schema.hash();
   }
 };

torch/csrc/dynamo/compiled_autograd.h

@@ -144,7 +144,7 @@ struct CacheKey {
         std::memcmp(key, other.key, key_size) == 0;
   }
 
-  size_t hash() const {
+  size_t hash() const noexcept {
     // don't bother hashing the key data, common case 1 cache entry per node
     return std::hash<std::type_index>()(node_type) ^ key_size;
   }
@@ -1555,7 +1555,7 @@ struct PackedArgs {
 
 template <>
 struct std::hash<torch::dynamo::autograd::CacheKey> {
-  size_t operator()(const torch::dynamo::autograd::CacheKey& k) const {
+  size_t operator()(const torch::dynamo::autograd::CacheKey& k) const noexcept {
     return k.hash();
   }
 };

torch/csrc/jit/runtime/argument_spec.h

@@ -153,7 +153,7 @@ struct ArgumentSpec {
   bool isPresent(size_t i) const {
     return optional_presence[i];
   }
-  size_t hashCode() const {
+  size_t hashCode() const noexcept {
     return hash_code;
   }
 
@@ -308,7 +308,7 @@ struct CompleteArgumentSpec {
   size_t size() const {
     return ninputs;
   }
-  size_t hashCode() const {
+  size_t hashCode() const noexcept {
     return hash_code;
   }
 
@@ -488,13 +488,14 @@ struct hash<c10::TensorType> {
 
 template <>
 struct hash<torch::jit::ArgumentSpec> {
-  size_t operator()(const torch::jit::ArgumentSpec& spec) const {
+  size_t operator()(const torch::jit::ArgumentSpec& spec) const noexcept {
     return spec.hashCode();
   }
 };
 template <>
 struct hash<torch::jit::CompleteArgumentSpec> {
-  size_t operator()(const torch::jit::CompleteArgumentSpec& spec) const {
+  size_t operator()(
+      const torch::jit::CompleteArgumentSpec& spec) const noexcept {
     return spec.hashCode();
   }
 };

torch/csrc/jit/tensorexpr/hash_provider.h

@@ -27,7 +27,8 @@ struct TORCH_API SimplifierHashType {
 namespace std {
 template <>
 struct hash<torch::jit::tensorexpr::SimplifierHashType> {
-  size_t operator()(const torch::jit::tensorexpr::SimplifierHashType& k) const {
+  size_t operator()(
+      const torch::jit::tensorexpr::SimplifierHashType& k) const noexcept {
     return k._h;
   }
 };