torch/distributed: move WorkerInfo registration into libtorch instead of libtorch_python (pytorch#78028)

Summary:
This moves torch::class_<WorkerInfo> into `rpc_agent.cpp` so it gets registered in libtorch instead of libtorch_python. This is intermediate work to getting torch::deploy to load an unmodified copy of libtorch. Current RPC is incompatible due to duplicate registrations.

```
unknown file: Failure
C++ exception with description "Exception Caught inside torch::deploy embedded library:
Custom class with name __torch__.torch.classes.dist_rpc.WorkerInfo is already registered. Ensure that registration with torch::class_ is only called once.
Exception raised from registerCustomClass at ../aten/src/ATen/core/custom_class.cpp:61 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x3e (0x7f3bd9adb92e in /home/tristanr/venvs/multipy/lib/python3.8/site-packages/torch/lib/libc10.so)
frame #1: c10::detail::torchCheckFail(char const*, char const*, unsigned int, std::string const&) + 0x5c (0x7f3bd9ab7068 in /home/tristanr/venvs/multipy/lib/python3.8/site-packages/torch/lib/libc10.so)
frame #2: torch::registerCustomClass(std::shared_ptr<c10::ClassType>) + 0x110 (0x7f3bc2258980 in /home/tristanr/venvs/multipy/lib/python3.8/site-packages/torch/lib/libtorch_cpu.so)
frame #3: torch::detail::class_base::class_base(std::string const&, std::string const&, std::string, std::type_info const&, std::type_info const&) + 0x3b9 (0x7f3bc225a419 in /home/tristanr/venvs/multipy/lib/python3.8/site-packages/torch/lib/libtorch_cpu.so)
frame #4: [0x7f3ba45cfea1]
frame #5: <unknown function> + 0x1b5334 (0x5652bdab9334 in ./test_deploy)
frame pytorch#6: <unknown function> + 0x1b4f3e (0x5652bdab8f3e in ./test_deploy)
frame pytorch#7: <unknown function> + 0x1b519b (0x5652bdab919b in ./test_deploy)
frame pytorch#8: loadSearchFile(char const*) + 0x23e (0x7f3ba62f37f8 in /tmp/torch_deploy9ATEFg)
frame pytorch#9: deploy_set_self + 0x51 (0x7f3ba62f38f9 in /tmp/torch_deploy9ATEFg)
frame pytorch#10: torch::deploy::Interpreter::Interpreter(torch::deploy::InterpreterManager*, std::shared_ptr<torch::deploy::Environment>) + 0x274 (0x5652bdaaa790 in ./test_deploy)
frame pytorch#11: void __gnu_cxx::new_allocator<torch::deploy::Interpreter>::construct<torch::deploy::Interpreter, torch::deploy::InterpreterManager*, std::shared_ptr<torch::deploy::Environment>&>(torch::deploy::Interpreter*, torch::deploy::InterpreterManager*&&, std::shared_ptr<torch::deploy::Environment>&) + 0x81 (0x5652bdaaf58b in ./test_deploy)
frame pytorch#12: void std::allocator_traits<std::allocator<torch::deploy::Interpreter> >::construct<torch::deploy::Interpreter, torch::deploy::InterpreterManager*, std::shared_ptr<torch::deploy::Environment>&>(std::allocator<torch::deploy::Interpreter>&, torch::deploy::Interpreter*, torch::deploy::InterpreterManager*&&, std::shared_ptr<torch::deploy::Environment>&) + 0x4a (0x5652bdaae320 in ./test_deploy)
frame pytorch#13: void std::vector<torch::deploy::Interpreter, std::allocator<torch::deploy::Interpreter> >::_M_realloc_insert<torch::deploy::InterpreterManager*, std::shared_ptr<torch::deploy::Environment>&>(__gnu_cxx::__normal_iterator<torch::deploy::Interpreter*, std::vector<torch::deploy::Interpreter, std::allocator<torch::deploy::Interpreter> > >, torch::deploy::InterpreterManager*&&, std::shared_ptr<torch::deploy::Environment>&) + 0xee (0x5652bdaae4a0 in ./test_deploy)
frame pytorch#14: void std::vector<torch::deploy::Interpreter, std::allocator<torch::deploy::Interpreter> >::emplace_back<torch::deploy::InterpreterManager*, std::shared_ptr<torch::deploy::Environment>&>(torch::deploy::InterpreterManager*&&, std::shared_ptr<torch::deploy::Environment>&) + 0xb6 (0x5652bdaad258 in ./test_deploy)
frame pytorch#15: torch::deploy::InterpreterManager::InterpreterManager(unsigned long, std::shared_ptr<torch::deploy::Environment>) + 0x123 (0x5652bdaa83b1 in ./test_deploy)
frame pytorch#16: TorchpyTest_InitTwice_Test::TestBody() + 0x65 (0x5652bda075a9 in ./test_deploy)
frame pytorch#17: void testing::internal::HandleSehExceptionsInMethodIfSupported<testing::Test, void>(testing::Test*, void (testing::Test::*)(), char const*) + 0x65 (0x5652bda944b7 in ./test_deploy)
frame pytorch#18: void testing::internal::HandleExceptionsInMethodIfSupported<testing::Test, void>(testing::Test*, void (testing::Test::*)(), char const*) + 0x5a (0x5652bda8cfe7 in ./test_deploy)
frame pytorch#19: testing::Test::Run() + 0x100 (0x5652bda68622 in ./test_deploy)
frame pytorch#20: testing::TestInfo::Run() + 0x10f (0x5652bda68fb3 in ./test_deploy)
frame pytorch#21: testing::TestSuite::Run() + 0x121 (0x5652bda6980d in ./test_deploy)
frame pytorch#22: testing::internal::UnitTestImpl::RunAllTests() + 0x38e (0x5652bda756e6 in ./test_deploy)
frame pytorch#23: bool testing::internal::HandleSehExceptionsInMethodIfSupported<testing::internal::UnitTestImpl, bool>(testing::internal::UnitTestImpl*, bool (testing::internal::UnitTestImpl::*)(), char const*) + 0x65 (0x5652bda9586b in ./test_deploy)
frame pytorch#24: bool testing::internal::HandleExceptionsInMethodIfSupported<testing::internal::UnitTestImpl, bool>(testing::internal::UnitTestImpl*, bool (testing::internal::UnitTestImpl::*)(), char const*) + 0x5a (0x5652bda8e0f7 in ./test_deploy)
frame pytorch#25: testing::UnitTest::Run() + 0xc9 (0x5652bda73fd1 in ./test_deploy)
frame pytorch#26: RUN_ALL_TESTS() + 0x11 (0x5652bda169fa in ./test_deploy)
frame pytorch#27: main + 0x27 (0x5652bda10ce2 in ./test_deploy)
frame pytorch#28: <unknown function> + 0x2d310 (0x7f3bc0431310 in /usr/lib/libc.so.6)
frame pytorch#29: __libc_start_main + 0x81 (0x7f3bc04313c1 in /usr/lib/libc.so.6)
frame pytorch#30: _start + 0x25 (0x5652bda063b5 in ./test_deploy)
```

Test Plan: CI

Differential Revision: D36564258

Pull Request resolved: pytorch#78028
Approved by: https://github.com/rohan-varma

Author: d4l3k

torch/csrc/distributed/rpc/rpc_agent.cpp

@@ -5,8 +5,50 @@ namespace torch {
 namespace distributed {
 namespace rpc {
 
+namespace {
+// WorkerInfo needs to be registered exactly once. Since the op registration
+// happens in libtorch_python we wrap the class registration in a helper to make
+// sure that if there's multiple copies of Python such as used in torch::deploy
+// we only ever register it once.
+static std::once_flag workerInfoFlag;
+static c10::optional<torch::class_<WorkerInfo>> workerInfo;
+} // namespace
+
+RegisterWorkerInfoOnce::RegisterWorkerInfoOnce() {
+  std::call_once(workerInfoFlag, []() {
+    workerInfo = torch::class_<WorkerInfo>("dist_rpc", "WorkerInfo")
+                     .def(torch::init<std::string, int64_t>());
+  });
+}
+
 constexpr size_t WorkerInfo::MAX_NAME_LEN;
 
+WorkerInfo::WorkerInfo(std::string name, int64_t id)
+    : WorkerInfo(std::move(name), (worker_id_t)id) {
+  TORCH_CHECK(
+      id <= std::numeric_limits<worker_id_t>::max(),
+      "RPC worker id ",
+      id,
+      " out of bound of int16_t.");
+}
+
+WorkerInfo::WorkerInfo(std::string name, worker_id_t id)
+    : name_(std::move(name)), id_(id) {
+  bool validSize = name_.length() < MAX_NAME_LEN && name_.length() > 0;
+  bool validChar =
+      std::find_if(name_.begin(), name_.end(), [](char c) {
+        return !(std::isalnum(c) || c == '-' || c == '_' || c == ':');
+      }) == name_.end();
+  TORCH_CHECK(
+      validSize && validChar,
+      "Worker name must match ^[A-Za-z0-9-_:]*$, "
+      "and must be non-empty and shorter than ",
+      MAX_NAME_LEN,
+      " chars, "
+      "but got ",
+      name_);
+}
+
 // Large Time Duration for waiting on the condition variable until the map is
 // population. Cannot use
 // std::chrono::time_point<std::chrono::steady_clock>::max() due to a known

torch/csrc/distributed/rpc/rpc_agent.h

@@ -52,31 +52,9 @@ struct RpcBackendOptions {
 
 // A globally unique ID to identify an RpcAgent
 struct TORCH_API WorkerInfo : torch::CustomClassHolder {
-  WorkerInfo(std::string name, int64_t id)
-      : WorkerInfo(std::move(name), (worker_id_t)id) {
-    TORCH_CHECK(
-        id <= std::numeric_limits<worker_id_t>::max(),
-        "RPC worker id ",
-        id,
-        " out of bound of int16_t.");
-  }
+  WorkerInfo(std::string name, int64_t id);
 
-  WorkerInfo(std::string name, worker_id_t id)
-      : name_(std::move(name)), id_(id) {
-    bool validSize = name_.length() < MAX_NAME_LEN && name_.length() > 0;
-    bool validChar =
-        std::find_if(name_.begin(), name_.end(), [](char c) {
-          return !(std::isalnum(c) || c == '-' || c == '_' || c == ':');
-        }) == name_.end();
-    TORCH_CHECK(
-        validSize && validChar,
-        "Worker name must match ^[A-Za-z0-9-_:]*$, "
-        "and must be non-empty and shorter than ",
-        MAX_NAME_LEN,
-        " chars, "
-        "but got ",
-        name_);
-  }
+  WorkerInfo(std::string name, worker_id_t id);
 
   bool operator==(const WorkerInfo& rhs) {
     return (id_ == rhs.id_) && (name_ == rhs.name_);
@@ -88,6 +66,10 @@ struct TORCH_API WorkerInfo : torch::CustomClassHolder {
   const worker_id_t id_;
 };
 
+struct TORCH_API RegisterWorkerInfoOnce {
+  RegisterWorkerInfoOnce();
+};
+
 TORCH_API std::ostream& operator<<(
     std::ostream& os,
     const WorkerInfo& workerInfo);

torch/csrc/jit/runtime/register_distributed_ops.cpp

@@ -22,10 +22,7 @@ namespace torch {
 namespace jit {
 
 namespace {
-
-static auto workerInfo =
-    torch::class_<dist_rpc::WorkerInfo>("dist_rpc", "WorkerInfo")
-        .def(torch::init<std::string, int64_t>());
+distributed::rpc::RegisterWorkerInfoOnce workerInfo{};
 
 // prepare the rpc input arguments and call the C++ impls
 void prepare_and_call_rpc_op(