[BE] Enable Ruff's Flake8 PYI001 (pytorch#112823)

Enable [unprefixed-type-param (PYI001)](https://docs.astral.sh/ruff/rules/unprefixed-type-param/#unprefixed-type-param-pyi001)

Link: pytorch#110950
Pull Request resolved: pytorch#112823
Approved by: https://github.com/Skylion007

Author: isdanni

caffe2/python/context.pyi

@@ -1,13 +1,13 @@
 from typing import Optional, TypeVar, Type
 
-T = TypeVar('T')
+_T = TypeVar('_T')
 
 class Managed:
     @classmethod
-    def current(cls: Type[T], value: Optional[T] = None, required: bool = True) -> T: ...
+    def current(cls: Type[_T], value: Optional[_T] = None, required: bool = True) -> _T: ...
 
-    def __call__(self, func: T) -> T: ...
+    def __call__(self, func: _T) -> _T: ...
 
-    def __enter__(self: T) -> T: ...
+    def __enter__(self: _T) -> _T: ...
 
 class DefaultManaged(Managed): ...

pyproject.toml

@@ -46,7 +46,7 @@ ignore = [
     "G101", "G201", "G202",
     # these ignores are from RUFF perf; please fix!
     "PERF203", "PERF4",
-    "PYI001", # these ignores are from PYI; please fix!
+    # these ignores are from PYI; please fix!
     "PYI019",
     "PYI024",
     "PYI036",

torch/_C/_distributed_rpc.pyi

@@ -15,7 +15,7 @@ _DEFAULT_NUM_WORKER_THREADS: int
 _UNSET_RPC_TIMEOUT: float
 _DEFAULT_RPC_TIMEOUT_SEC: float
 
-T = TypeVar("T")
+_T = TypeVar("_T")
 
 class RpcBackendOptions:
     rpc_timeout: float
@@ -47,24 +47,24 @@ class RpcAgent:
     def get_debug_info(self) -> Dict[str, str]: ...
     def get_metrics(self) -> Dict[str, str]: ...
 
-class PyRRef(Generic[T]):
-    def __init__(self, value: T, type_hint: Any = None) -> None: ...
+class PyRRef(Generic[_T]):
+    def __init__(self, value: _T, type_hint: Any = None) -> None: ...
     def is_owner(self) -> bool: ...
     def confirmed_by_owner(self) -> bool: ...
     def owner(self) -> WorkerInfo: ...
     def owner_name(self) -> str: ...
-    def to_here(self, timeout: float = ...) -> T: ...
+    def to_here(self, timeout: float = ...) -> _T: ...
     def local_value(self) -> Any: ...
     def rpc_sync(self, timeout: float = ...) -> Any: ...
     def rpc_async(self, timeout: float = ...) -> Any: ...
     def remote(self, timeout: float = ...) -> Any: ...
     def _serialize(self) -> Tuple: ...
     @staticmethod
     def _deserialize(tp: Tuple) -> PyRRef: ...
-    def _get_type(self) -> Type[T]: ...
-    def _get_future(self) -> Future[T]: ...
-    def _get_profiling_future(self) -> Future[T]: ...
-    def _set_profiling_future(self, profilingFuture: Future[T]): ...
+    def _get_type(self) -> Type[_T]: ...
+    def _get_future(self) -> Future[_T]: ...
+    def _get_profiling_future(self) -> Future[_T]: ...
+    def _set_profiling_future(self, profilingFuture: Future[_T]): ...
 
 class _TensorPipeRpcBackendOptionsBase(RpcBackendOptions):
     num_worker_threads: int

torch/jit/_script.pyi

@@ -66,7 +66,7 @@ type_trace_db: JitTypeTraceStore
 
 # Defined in torch/csrc/jit/python/script_init.cpp
 ResolutionCallback: TypeAlias = Callable[[str], Callable[..., Any]]
-ClassVar = TypeVar("ClassVar", bound=type)
+_ClassVar = TypeVar("_ClassVar", bound=type)
 
 def _reduce(cls) -> None: ...
 
@@ -230,12 +230,12 @@ def script(  # type: ignore[misc]
 ) -> RecursiveScriptModule: ...
 @overload
 def script(  # type: ignore[misc]
-    obj: ClassVar,
+    obj: _ClassVar,
     optimize: Optional[bool] = None,
     _frames_up: int = 0,
     _rcb: Optional[ResolutionCallback] = None,
     example_inputs: Union[List[Tuple], Dict[Callable, List[Tuple]], None] = None,
-) -> ClassVar: ...
+) -> _ClassVar: ...
 @overload
 def script(  # type: ignore[misc]
     obj: Callable,

torch/nn/utils/rnn.pyi

@@ -23,7 +23,7 @@ class PackedSequence_(NamedTuple):
 
 def bind(optional: Any, fn: Any): ...
 
-T = TypeVar("T")
+_T = TypeVar("_T")
 
 class PackedSequence(PackedSequence_):
     def __new__(
@@ -33,39 +33,39 @@ class PackedSequence(PackedSequence_):
         sorted_indices: Optional[Tensor] = ...,
         unsorted_indices: Optional[Tensor] = ...,
     ) -> Self: ...
-    def pin_memory(self: T) -> T: ...
-    def cuda(self: T, *args: Any, **kwargs: Any) -> T: ...
-    def cpu(self: T) -> T: ...
-    def double(self: T) -> T: ...
-    def float(self: T) -> T: ...
-    def half(self: T) -> T: ...
-    def long(self: T) -> T: ...
-    def int(self: T) -> T: ...
-    def short(self: T) -> T: ...
-    def char(self: T) -> T: ...
-    def byte(self: T) -> T: ...
+    def pin_memory(self: _T) -> _T: ...
+    def cuda(self: _T, *args: Any, **kwargs: Any) -> _T: ...
+    def cpu(self: _T) -> _T: ...
+    def double(self: _T) -> _T: ...
+    def float(self: _T) -> _T: ...
+    def half(self: _T) -> _T: ...
+    def long(self: _T) -> _T: ...
+    def int(self: _T) -> _T: ...
+    def short(self: _T) -> _T: ...
+    def char(self: _T) -> _T: ...
+    def byte(self: _T) -> _T: ...
     @overload
     def to(
-        self: T,
+        self: _T,
         dtype: _dtype,
         non_blocking: bool = False,
         copy: bool = False,
-    ) -> T: ...
+    ) -> _T: ...
     @overload
     def to(
-        self: T,
+        self: _T,
         device: Optional[Union[_device, str]] = None,
         dtype: Optional[_dtype] = None,
         non_blocking: bool = False,
         copy: bool = False,
-    ) -> T: ...
+    ) -> _T: ...
     @overload
     def to(
-        self: T,
+        self: _T,
         other: Tensor,
         non_blocking: bool = False,
         copy: bool = False,
-    ) -> T: ...
+    ) -> _T: ...
     @property
     def is_cuda(self) -> bool: ...
     def is_pinned(self) -> bool: ...