Allow BUILD/NEWOBJ instruction for items added via torch.serialization.add_safe_globals (#129251)

Previously, allowlisting functions/classes via `torch.serialization.add_safe_globals(obj)` for the `weights_only` Unpickler had the following effect:

- For a [`GLOBAL`](https://github.com/python/cpython/blob/3.12/Lib/pickletools.py#L1926-L1939) instruction, `GLOBAL obj.__module__ obj.__name__` would be allowed and translated back to obj to be pushed back to the stack.
- For a [`REDUCE`](https://github.com/python/cpython/blob/3.12/Lib/pickletools.py#L1926-L1982) instruction where we expect the stack to contain `func` and `args`, `func` is allowed if it was added via `add_safe_globals`

However, it did not have an effect on `BUILD` and `NEWOBJ` instructions

Some classes may be rebuilt via [`NEWOBJ`](https://github.com/python/cpython/blob/3.12/Lib/pickletools.py#L2091-L2104) instruction, which indicates that their constructor should be used to rebuild the class.

Further, a [`BUILD`](https://github.com/python/cpython/blob/3.12/Lib/pickletools.py#L1984-L2007) instruction might be used if an object's `__reduce__`/`__reduce_ex__` returns a non-None value for `state`. Which indicates a `__setstate__` or `__dict__.update`.

**This PR makes sure that adding objects to the allowlist will also allow `NEWOBJ` and `BUILD` instructions for them.**

In particular, the update for `NEWOBJ` should unblock allowlisting of [`ScaledMMConfig`](d4ade877df/float8_experimental/float8_tensor.py (L26-L30)) in float8_experimental @drisspg

Pull Request resolved: https://github.com/pytorch/pytorch/pull/129251
Approved by: https://github.com/albanD
ghstack dependencies: #129244

test/distributed/_tensor/test_dtensor.py

@@ -536,6 +536,16 @@ class DTensorTest(DTensorTestBase):
         buffer.seek(0)
         reloaded_st = torch.load(buffer)
         self.assertEqual(sharded_tensor, reloaded_st)
+        # Test weights_only load
+        try:
+            torch.serialization.add_safe_globals(
+                [DTensor, DeviceMesh, Shard, DTensorSpec, TensorMeta]
+            )
+            buffer.seek(0)
+            reloaded_st = torch.load(buffer, weights_only=True)
+            self.assertEqual(sharded_tensor, reloaded_st)
+        finally:
+            torch.serialization.clear_safe_globals()
 
 
 class DTensorMeshTest(DTensorTestBase):