Use Generator instead of Iterator for 3rd-party context managers (#12481)

stubs/tensorflow/tensorflow/__init__.pyi

@@ -2,7 +2,7 @@ import abc
 from _typeshed import Incomplete, Unused
 from abc import ABC, ABCMeta, abstractmethod
 from builtins import bool as _bool
-from collections.abc import Callable, Iterable, Iterator, Sequence
+from collections.abc import Callable, Generator, Iterable, Iterator, Sequence
 from contextlib import contextmanager
 from enum import Enum
 from types import TracebackType
@@ -228,7 +228,7 @@ class Graph:
     def add_to_collection(self, name: str, value: object) -> None: ...
     def add_to_collections(self, names: Iterable[str] | str, value: object) -> None: ...
     @contextmanager
-    def as_default(self) -> Iterator[Self]: ...
+    def as_default(self) -> Generator[Self]: ...
     def finalize(self) -> None: ...
     def get_tensor_by_name(self, name: str) -> Tensor: ...
     def get_operation_by_name(self, name: str) -> Operation: ...

stubs/tensorflow/tensorflow/autodiff.pyi

@@ -56,7 +56,7 @@ class GradientTape:
         unconnected_gradients: UnconnectedGradients = ...,
     ) -> ContainerGradients: ...
     @contextmanager
-    def stop_recording(self) -> Generator[None, None, None]: ...
+    def stop_recording(self) -> Generator[None]: ...
     def reset(self) -> None: ...
     def watch(self, tensor: ContainerTensorsLike) -> None: ...
     def watched_variables(self) -> tuple[Variable, ...]: ...

stubs/tensorflow/tensorflow/summary.pyi

@@ -1,6 +1,6 @@
 import abc
 from _typeshed import Incomplete
-from collections.abc import Callable, Iterator
+from collections.abc import Callable, Generator
 from contextlib import AbstractContextManager, contextmanager
 from typing import Literal
 from typing_extensions import Self
@@ -49,7 +49,7 @@ def image(
     description: str | None = None,
 ) -> bool: ...
 @contextmanager
-def record_if(condition: bool | tf.Tensor | Callable[[], bool]) -> Iterator[None]: ...
+def record_if(condition: bool | tf.Tensor | Callable[[], bool]) -> Generator[None]: ...
 def scalar(name: str, data: float | tf.Tensor, step: int | tf.Tensor | None = None, description: str | None = None) -> bool: ...
 def should_record_summaries() -> bool: ...
 def text(name: str, data: str | tf.Tensor, step: int | tf.Tensor | None = None, description: str | None = None) -> bool: ...