Enable xdoctest runner in CI for real this time (#83816)

Builds on #83317 and enables running the doctests. Just need to figure out what is causing the failures.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/83816
Approved by: https://github.com/ezyang, https://github.com/malfet

torch/serialization.py

@@ -49,6 +49,7 @@ __all__ = [
     'StorageType',
 ]
 
+
 class SourceChangeWarning(Warning):
     pass
 
@@ -186,10 +187,12 @@ def _cuda_deserialize(obj, location):
         else:
             return obj.cuda(device)
 
+
 def _mps_deserialize(obj, location):
     if location == 'mps':
         return obj.mps()
 
+
 def _meta_deserialize(obj, location):
     if location == 'meta':
         return torch.UntypedStorage(obj.nbytes(), device='meta')
@@ -356,6 +359,7 @@ def _check_seekable(f) -> bool:
         raise_err_msg(["seek", "tell"], e)
     return False
 
+
 def _check_dill_version(pickle_module) -> None:
     '''Checks if using dill as the pickle module, and if so, checks if it is the correct version.
     If dill version is lower than 0.3.1, a ValueError is raised.
@@ -375,12 +379,14 @@ def _check_dill_version(pickle_module) -> None:
                 pickle_module.__version__
             ))
 
+
 def _check_save_filelike(f):
     if not isinstance(f, (str, os.PathLike)) and not hasattr(f, 'write'):
         raise AttributeError((
             "expected 'f' to be string, path, or a file-like object with "
             "a 'write' attribute"))
 
+
 def save(
     obj: object,
     f: FILE_LIKE,
@@ -420,6 +426,7 @@ def save(
         to use the old format, pass the kwarg ``_use_new_zipfile_serialization=False``.
 
     Example:
+        >>> # xdoctest: +SKIP("makes cwd dirty")
         >>> # Save to file
         >>> x = torch.tensor([0, 1, 2, 3, 4])
         >>> torch.save(x, 'tensor.pt')
@@ -753,7 +760,7 @@ def load(
         # Load all tensors onto GPU 1
         >>> torch.load('tensors.pt', map_location=lambda storage, loc: storage.cuda(1))
         # Map tensors from GPU 1 to GPU 0
-        >>> torch.load('tensors.pt', map_location={'cuda:1':'cuda:0'})
+        >>> torch.load('tensors.pt', map_location={'cuda:1': 'cuda:0'})
         # Load tensor from io.BytesIO object
         >>> with open('tensor.pt', 'rb') as f:
         ...     buffer = io.BytesIO(f.read())
@@ -1087,6 +1094,7 @@ def _get_restore_location(map_location):
             return result
     return restore_location
 
+
 class StorageType():
     def __init__(self, name):
         self.dtype = _get_dtype_from_pickle_storage_type(name)
@@ -1094,6 +1102,7 @@ class StorageType():
     def __str__(self):
         return f'StorageType(dtype={self.dtype})'
 
+
 def _load(zip_file, map_location, pickle_module, pickle_file='data.pkl', **pickle_load_args):
     restore_location = _get_restore_location(map_location)