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Revert "Update ruff to 0.13.1 (#163744)"

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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))
This commit is contained in:
PyTorch MergeBot
2025-09-25 18:54:03 +00:00
parent 151e66e50d
commit 7bad9c5a64
8 changed files with 13 additions and 12 deletions
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4
.lintrunner.toml
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@ -1453,7 +1453,7 @@ init_command = [
'--dry-run={{DRYRUN}}', '--dry-run={{DRYRUN}}',
'usort==1.0.8.post1', 'usort==1.0.8.post1',
'isort==6.0.1', 'isort==6.0.1',
'ruff==0.13.1', # sync with RUFF 'ruff==0.12.9', # sync with RUFF
] ]
is_formatter = true is_formatter = true
@ -1587,7 +1587,7 @@ init_command = [
'python3', 'python3',
'tools/linter/adapters/pip_init.py', 'tools/linter/adapters/pip_init.py',
'--dry-run={{DRYRUN}}', '--dry-run={{DRYRUN}}',
'ruff==0.13.1', # sync with PYFMT 'ruff==0.12.9', # sync with PYFMT
] ]
is_formatter = true is_formatter = true

1
pyproject.toml
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@ -182,6 +182,7 @@ ignore = [
"SIM117", "SIM117",
"SIM118", "SIM118",
"UP007", # keep-runtime-typing "UP007", # keep-runtime-typing
"UP038", # Was removed from newer versions, results in slower code
"UP045", # keep-runtime-typing "UP045", # keep-runtime-typing
"TC006", "TC006",
# TODO: Remove Python-3.10 specific suppressions # TODO: Remove Python-3.10 specific suppressions

2
torch/_functorch/_aot_autograd/autograd_cache.py
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@ -507,7 +507,7 @@ def autograd_cache_key(
TOut = TypeVar("TOut", bound=OutputCode) TOut = TypeVar("TOut", bound=OutputCode)
class InductorOutput(ABC, Generic[TOut]): class InductorOutput(Generic[TOut], ABC):
""" """
Class representing a single inductor output Class representing a single inductor output
""" """

4
torch/_inductor/autoheuristic/artifacts/_MMRankingA100.py
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@ -17,7 +17,7 @@ from torch._inductor.autoheuristic.learnedheuristic_interface import (
class MMRankingA100(LearnedHeuristicDecision): class MMRankingA100(LearnedHeuristicDecision):
def __init__(self) -> None: def __init__(self) -> None:
self.choices: list[Choice] = [] self.choices: List[Choice] = []
self.fill_choices() self.fill_choices()
def check_precondition(self, metadata: AHMetadata, context: AHContext,) -> bool: def check_precondition(self, metadata: AHMetadata, context: AHContext,) -> bool:
@ -238,7 +238,7 @@ class MMRankingA100(LearnedHeuristicDecision):
def get_name(self) -> str: def get_name(self) -> str:
return 'mm' 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('arith_intensity') <= 52.6245059967041:
if context.get_value('n') <= 34.0: if context.get_value('n') <= 34.0:
if context.get_value('n') <= 18.0: if context.get_value('n') <= 18.0:

4
torch/_inductor/autoheuristic/artifacts/_MMRankingH100.py
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@ -17,7 +17,7 @@ from torch._inductor.autoheuristic.learnedheuristic_interface import (
class MMRankingH100(LearnedHeuristicDecision): class MMRankingH100(LearnedHeuristicDecision):
def __init__(self) -> None: def __init__(self) -> None:
self.choices: list[Choice] = [] self.choices: List[Choice] = []
self.fill_choices() self.fill_choices()
def check_precondition(self, metadata: AHMetadata, context: AHContext,) -> bool: def check_precondition(self, metadata: AHMetadata, context: AHContext,) -> bool:
@ -242,7 +242,7 @@ class MMRankingH100(LearnedHeuristicDecision):
def get_name(self) -> str: def get_name(self) -> str:
return 'mm' 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('arith_intensity') <= 29.89772129058838:
if context.get_value('n') <= 34.0: if context.get_value('n') <= 34.0:
if context.get_value('n') <= 18.0: if context.get_value('n') <= 18.0:

4
torch/_inductor/autoheuristic/artifacts/_MixedMMA100.py
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@ -17,7 +17,7 @@ from torch._inductor.autoheuristic.learnedheuristic_interface import (
class MixedMMA100(LearnedHeuristicDecision): class MixedMMA100(LearnedHeuristicDecision):
def __init__(self) -> None: def __init__(self) -> None:
self.choices: list[Choice] = [] self.choices: List[Choice] = []
self.fill_choices() self.fill_choices()
def check_precondition(self, metadata: AHMetadata, context: AHContext,) -> bool: def check_precondition(self, metadata: AHMetadata, context: AHContext,) -> bool:
@ -62,7 +62,7 @@ class MixedMMA100(LearnedHeuristicDecision):
def get_name(self) -> str: def get_name(self) -> str:
return 'mixed_mm' 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 str(context.get_value('1LEQmLEQ16')) != 'True':
if context.get_value('m') <= 32.5: if context.get_value('m') <= 32.5:
if context.get_value('n') <= 6976.0: if context.get_value('n') <= 6976.0:

4
torch/_inductor/autoheuristic/artifacts/_MixedMMH100.py
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@ -17,7 +17,7 @@ from torch._inductor.autoheuristic.learnedheuristic_interface import (
class MixedMMH100(LearnedHeuristicDecision): class MixedMMH100(LearnedHeuristicDecision):
def __init__(self) -> None: def __init__(self) -> None:
self.choices: list[Choice] = [] self.choices: List[Choice] = []
self.fill_choices() self.fill_choices()
def check_precondition(self, metadata: AHMetadata, context: AHContext,) -> bool: def check_precondition(self, metadata: AHMetadata, context: AHContext,) -> bool:
@ -61,7 +61,7 @@ class MixedMMH100(LearnedHeuristicDecision):
def get_name(self) -> str: def get_name(self) -> str:
return 'mixed_mm' 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('arith_intensity') <= 15.988086223602295:
if context.get_value('n') <= 25280.0: if context.get_value('n') <= 25280.0:
if context.get_value('n') <= 1344.0: if context.get_value('n') <= 1344.0:

2
torch/fx/experimental/symbolic_shapes.py
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@ -2048,7 +2048,7 @@ _T1 = TypeVar("_T1")
@dataclass(frozen=True) @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 Create symbols in ``create_symbolic_sizes_strides_storage_offset`` via
a symbolic_context determination as given by ``DimDynamic`` and ``DimConstraint``. a symbolic_context determination as given by ``DimDynamic`` and ``DimConstraint``.