Use spawn for multiprocessing start method

Summary:
CUDA context initialization is not fork-safe. If a CUDA context is created in a parent process, and then the process is forked (using `os.fork()`), the child process may encounter errors or undefined behavior when using CUDA. This is because the CUDA driver and runtime are not designed to be safely duplicated via `fork()`. It's recommended to use `spawn` or `forkserver`.

Among the two, `forkserver` needs to be use carefully and specifically, it's recommended to call `multiprocessing.set_start_method('forkserver')` at the very start of the program, and the parent process also needs to avoid initializing the CUDA context. When upgrading APS to CUDA 12.8, we encountered a test failure, and the test is apparently initializing the CUDA context before starting up two children processes, and I suspect that caused the test to hang - [post](https://fb.workplace.com/groups/319878845696681/posts/1494595861558301).

It's hard to avoid initializing the CUDA context early in this test, because it checks the GPU count in the test method's decorator - [code](https://fburl.com/code/27naz2eg).  Among the `spawn` and `forkserver` start methods, `spawn` is less efficient but it's the most robust. Let's switch to that instead to avoid any potential undefined behaviors with CUDA 12.8 and multiprocessing.

Differential Revision: D80305233

Author: zhuhan0

torchrec/distributed/test_utils/multi_process.py

@@ -102,16 +102,9 @@ def __exit__(self, exc_type, exc_instance, traceback) -> None:
 
 
 class MultiProcessTestBase(unittest.TestCase):
-    def __init__(
-        self, methodName: str = "runTest", mp_init_mode: str = "forkserver"
-    ) -> None:
+    def __init__(self, methodName: str = "runTest") -> None:
         super().__init__(methodName)
 
-        # AMD's HIP runtime doesn't seem to work with forkserver; hipMalloc will fail
-        # Therefore we use spawn for HIP runtime until AMD fixes the issue
-        self._mp_init_mode: str = mp_init_mode if torch.version.hip is None else "spawn"
-        logging.info(f"Using {self._mp_init_mode} for multiprocessing")
-
     @seed_and_log
     def setUp(self) -> None:
         os.environ["MASTER_ADDR"] = str("localhost")
@@ -144,7 +137,7 @@ def _run_multi_process_test(
         # pyre-ignore
         **kwargs,
     ) -> None:
-        ctx = multiprocessing.get_context(self._mp_init_mode)
+        ctx = multiprocessing.get_context(method="spawn")
         processes = []
         for rank in range(world_size):
             kwargs["rank"] = rank
@@ -170,7 +163,7 @@ def _run_multi_process_test_per_rank(
         world_size: int,
         kwargs_per_rank: List[Dict[str, Any]],
     ) -> None:
-        ctx = multiprocessing.get_context(self._mp_init_mode)
+        ctx = multiprocessing.get_context(method="spawn")
         processes = []
         for rank in range(world_size):
             kwargs = {}