Migrate from Tuple -> tuple in torch/_dynamo (#144261)

Summary:
X-link: pytorch/pytorch#144261
Approved by: https://github.com/aorenste, https://github.com/zou3519

Reviewed By: clee2000

Differential Revision: D68023204

Pulled By: bobrenjc93

fbshipit-source-id: 2f8a435a35083bc00bc6edb2208223364a3c47a6

userbenchmark/dynamo/dynamobench/_dynamo/testing.py

@@ -16,7 +16,6 @@
     Optional,
     overload,
     Sequence,
-    Tuple,
     TypeVar,
     Union,
 )
@@ -141,7 +140,7 @@ def reduce_to_scalar_loss(out: torch.Tensor) -> torch.Tensor:
 
 @overload
 def reduce_to_scalar_loss(
-    out: Union[List[Any], Tuple[Any, ...], Dict[Any, Any]]
+    out: Union[List[Any], tuple[Any, ...], Dict[Any, Any]]
 ) -> float:
     ...
 

userbenchmark/dynamo/dynamobench/_dynamo/utils.py

@@ -54,7 +54,6 @@
     Optional,
     overload,
     Set,
-    Tuple,
     Type,
     TypeVar,
     Union,
@@ -106,7 +105,7 @@
 
     # NOTE: Make sure `NP_SUPPORTED_MODULES` and `NP_TO_TNP_MODULE` are in sync.
     if np:
-        NP_SUPPORTED_MODULES: Tuple[types.ModuleType, ...] = (
+        NP_SUPPORTED_MODULES: tuple[types.ModuleType, ...] = (
             np,
             np.fft,
             np.linalg,
@@ -202,8 +201,8 @@ def log(cls):
 
 
 def tabulate(
-    rows: Union[List[Tuple[str, object]], List[List[object]]],
-    headers: Union[Tuple[str, ...], List[str]],
+    rows: Union[List[tuple[str, object]], List[List[object]]],
+    headers: Union[tuple[str, ...], List[str]],
 ) -> str:
     try:
         import tabulate
@@ -590,7 +589,7 @@ def compile_times(repr: Literal["str"], aggregate: bool = False) -> str:
 @overload
 def compile_times(
     repr: Literal["csv"], aggregate: bool = False
-) -> Tuple[List[str], List[object]]:
+) -> tuple[List[str], List[object]]:
     ...
 
 
@@ -658,7 +657,7 @@ def __init__(self, maxsize: int = 4096) -> None:
     def reset(self):
         self.set = OrderedDict()
 
-    def add(self, key: Union[str, Tuple[object, object]]) -> bool:
+    def add(self, key: Union[str, tuple[object, object]]) -> bool:
         if key in self.set:
             self.set.move_to_end(key, last=True)
             if not config.verbose:
@@ -797,7 +796,7 @@ def istype(obj: object, allowed_types: Type[T]) -> TypeIs[T]:
 
 @overload
 def istype(
-    obj: object, allowed_types: Tuple[Type[List[T]], Type[Tuple[T, ...]]]
+    obj: object, allowed_types: tuple[Type[List[T]], Type[tuple[T, ...]]]
 ) -> TypeIs[T]:
     ...
 
@@ -940,7 +939,7 @@ def is_numpy_ndarray(value):
 
 def istensor(obj):
     """Check of obj is a tensor"""
-    tensor_list: Tuple[type, ...] = (
+    tensor_list: tuple[type, ...] = (
         torch.Tensor,
         torch.nn.Parameter,
         *config.traceable_tensor_subclasses,
@@ -1900,7 +1899,7 @@ def is_namedtuple_cls(cls):
 
 
 @functools.lru_cache(1)
-def namedtuple_fields(cls) -> Tuple[str, ...]:
+def namedtuple_fields(cls) -> tuple[str, ...]:
     """Get the fields of a namedtuple or a torch.return_types.* quasi-namedtuple"""
     if cls is slice:
         return ("start", "stop", "step")
@@ -2188,7 +2187,7 @@ def tuple_iterator_getitem(it, index):
 iter_next = next
 
 
-def normalize_range_iter(range_iter) -> Tuple[int, int, int]:
+def normalize_range_iter(range_iter) -> tuple[int, int, int]:
     _, (range_obj,), maybe_idx = range_iter.__reduce__()
     # In 3.12+, `maybe_idx` could be None, and `range_obj.start` would've been
     # already incremented by the current index.
@@ -3070,7 +3069,7 @@ def tensor_always_has_static_shape(
     tensor: Union[torch.Tensor, Any],
     is_tensor: bool,
     tensor_source: Source,
-) -> Tuple[bool, Optional[TensorStaticReason]]:
+) -> tuple[bool, Optional[TensorStaticReason]]:
     """
     Given a tensor, source, and is_tensor flag, determine if a shape should be static.