Revert "Update ruff to 0.13.1 (#163744)"

This reverts commit 3dd89a079f2b0c1d39351f98ff5d5ca882523152.

Reverted https://github.com/pytorch/pytorch/pull/163744 on behalf of https://github.com/malfet due to Broke lint, see https://github.com/pytorch/pytorch/actions/runs/18016220484/job/51261729375 looks like a landrace with PR that updated min-version to 3.10 ([comment](https://github.com/pytorch/pytorch/pull/163744#issuecomment-3335534084))

.lintrunner.toml

@@ -1453,7 +1453,7 @@ init_command = [
     '--dry-run={{DRYRUN}}',
     'usort==1.0.8.post1',
     'isort==6.0.1',
-    'ruff==0.13.1',  # sync with RUFF
+    'ruff==0.12.9',  # sync with RUFF
 ]
 is_formatter = true
 
@@ -1587,7 +1587,7 @@ init_command = [
     'python3',
     'tools/linter/adapters/pip_init.py',
     '--dry-run={{DRYRUN}}',
-    'ruff==0.13.1',  # sync with PYFMT
+    'ruff==0.12.9',  # sync with PYFMT
 ]
 is_formatter = true
 

pyproject.toml

@@ -182,6 +182,7 @@ ignore = [
     "SIM117",
     "SIM118",
     "UP007", # keep-runtime-typing
+    "UP038", # Was removed from newer versions, results in slower code
     "UP045", # keep-runtime-typing
     "TC006",
     # TODO: Remove Python-3.10 specific suppressions

torch/_functorch/_aot_autograd/autograd_cache.py

@@ -507,7 +507,7 @@ def autograd_cache_key(
 TOut = TypeVar("TOut", bound=OutputCode)
 
 
-class InductorOutput(ABC, Generic[TOut]):
+class InductorOutput(Generic[TOut], ABC):
     """
     Class representing a single inductor output
     """

torch/_inductor/autoheuristic/artifacts/_MMRankingA100.py

@@ -17,7 +17,7 @@ from torch._inductor.autoheuristic.learnedheuristic_interface import (
 class MMRankingA100(LearnedHeuristicDecision):
 
     def __init__(self) -> None:
-        self.choices: list[Choice] = []
+        self.choices: List[Choice] = []
         self.fill_choices()
 
     def check_precondition(self, metadata: AHMetadata, context: AHContext,) -> bool:
@@ -238,7 +238,7 @@ class MMRankingA100(LearnedHeuristicDecision):
     def get_name(self) -> str:
         return 'mm'
 
-    def get_best_choices(self, context: AHContext) -> Optional[list[tuple[float, int]]]:
+    def get_best_choices(self, context: AHContext) -> Optional[List[tuple[float, int]]]:
         if context.get_value('arith_intensity') <= 52.6245059967041:
             if context.get_value('n') <= 34.0:
                 if context.get_value('n') <= 18.0:

torch/_inductor/autoheuristic/artifacts/_MMRankingH100.py

@@ -17,7 +17,7 @@ from torch._inductor.autoheuristic.learnedheuristic_interface import (
 class MMRankingH100(LearnedHeuristicDecision):
 
     def __init__(self) -> None:
-        self.choices: list[Choice] = []
+        self.choices: List[Choice] = []
         self.fill_choices()
 
     def check_precondition(self, metadata: AHMetadata, context: AHContext,) -> bool:
@@ -242,7 +242,7 @@ class MMRankingH100(LearnedHeuristicDecision):
     def get_name(self) -> str:
         return 'mm'
 
-    def get_best_choices(self, context: AHContext) -> Optional[list[tuple[float, int]]]:
+    def get_best_choices(self, context: AHContext) -> Optional[List[tuple[float, int]]]:
         if context.get_value('arith_intensity') <= 29.89772129058838:
             if context.get_value('n') <= 34.0:
                 if context.get_value('n') <= 18.0:

torch/_inductor/autoheuristic/artifacts/_MixedMMA100.py

@@ -17,7 +17,7 @@ from torch._inductor.autoheuristic.learnedheuristic_interface import (
 class MixedMMA100(LearnedHeuristicDecision):
 
     def __init__(self) -> None:
-        self.choices: list[Choice] = []
+        self.choices: List[Choice] = []
         self.fill_choices()
 
     def check_precondition(self, metadata: AHMetadata, context: AHContext,) -> bool:
@@ -62,7 +62,7 @@ class MixedMMA100(LearnedHeuristicDecision):
     def get_name(self) -> str:
         return 'mixed_mm'
 
-    def get_best_choices(self, context: AHContext) -> Optional[list[tuple[float, int]]]:
+    def get_best_choices(self, context: AHContext) -> Optional[List[tuple[float, int]]]:
         if str(context.get_value('1LEQmLEQ16')) != 'True':
             if context.get_value('m') <= 32.5:
                 if context.get_value('n') <= 6976.0:

torch/_inductor/autoheuristic/artifacts/_MixedMMH100.py

@@ -17,7 +17,7 @@ from torch._inductor.autoheuristic.learnedheuristic_interface import (
 class MixedMMH100(LearnedHeuristicDecision):
 
     def __init__(self) -> None:
-        self.choices: list[Choice] = []
+        self.choices: List[Choice] = []
         self.fill_choices()
 
     def check_precondition(self, metadata: AHMetadata, context: AHContext,) -> bool:
@@ -61,7 +61,7 @@ class MixedMMH100(LearnedHeuristicDecision):
     def get_name(self) -> str:
         return 'mixed_mm'
 
-    def get_best_choices(self, context: AHContext) -> Optional[list[tuple[float, int]]]:
+    def get_best_choices(self, context: AHContext) -> Optional[List[tuple[float, int]]]:
         if context.get_value('arith_intensity') <= 15.988086223602295:
             if context.get_value('n') <= 25280.0:
                 if context.get_value('n') <= 1344.0:

torch/fx/experimental/symbolic_shapes.py

@@ -2048,7 +2048,7 @@ _T1 = TypeVar("_T1")
 
 
 @dataclass(frozen=True)
-class StatelessSymbolicContext(SymbolicContext, Generic[_P1, _T1]):
+class StatelessSymbolicContext(Generic[_P1, _T1], SymbolicContext):
     """
     Create symbols in ``create_symbolic_sizes_strides_storage_offset`` via
     a symbolic_context determination as given by ``DimDynamic`` and ``DimConstraint``.