More ruff SIM fixes (#164695)

This PR applies ruff `SIM` rules to more files. Most changes are about simplifying `dict.get` because `None` is already the default value.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/164695
Approved by: https://github.com/ezyang
This commit is contained in:
Yuanyuan Chen
2025-10-09 03:24:46 +00:00
committed by PyTorch MergeBot
parent 54ae61c573
commit a029675f6f
49 changed files with 153 additions and 117 deletions

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@ -190,12 +190,12 @@ def map_job_data(jobNames: Any, shaGrid: Any) -> dict[str, Any]:
def is_job_failed(job: Any) -> bool:
conclusion = job["conclusion"] if "conclusion" in job else None
conclusion = job.get("conclusion", None)
return conclusion is not None and conclusion != SUCCESS and conclusion != PENDING
def is_job_skipped(job: Any) -> bool:
conclusion = job["conclusion"] if "conclusion" in job else None
conclusion = job.get("conclusion", None)
return conclusion in (NEUTRAL, SKIPPED) or conclusion is None

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@ -340,7 +340,7 @@ def get_base_name(f: NativeFunction) -> str:
def get_view_info(f: NativeFunction) -> str | None:
base_name = get_base_name(f)
view_info = VIEW_FUNCTIONS.get(base_name, None)
view_info = VIEW_FUNCTIONS.get(base_name)
if view_info is None and base_name in RETURNS_VIEWS_OF_INPUT:
view_info = "self"
return view_info

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@ -30,7 +30,7 @@ cov_data = CoverageData(basename=f".coverage.jit.{time()}")
def is_not_builtin_class(obj: Any) -> bool:
return isclass(obj) and not type(obj).__module__ == "builtins"
return isclass(obj) and type(obj).__module__ != "builtins"
class JitPlugin(CoveragePlugin): # type: ignore[misc, no-any-unimported]

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@ -554,26 +554,30 @@ class Op:
MatchState.SIZE_OR_SYNTAX_MISMATCH,
f"Expected input sizes: '{self.input_sizes}' does not match found output sizes: '{other.output_sizes}'",
)
if self.type in [
"all_gather",
"all_gather_base",
"all_gather_into_tensor_coalesced",
] and not (
math.prod(other.output_sizes[0])
== math.prod(self.input_sizes[0]) * self.pg_size
if (
self.type
in [
"all_gather",
"all_gather_base",
"all_gather_into_tensor_coalesced",
]
and math.prod(other.output_sizes[0])
!= math.prod(self.input_sizes[0]) * self.pg_size
):
return MatchInfo(
MatchState.SIZE_OR_SYNTAX_MISMATCH,
f"Found input numel '{math.prod(other.input_sizes[0])} * pg size {self.pg_size}' "
f"does not match output numel '{math.prod(other.output_sizes[0])}'",
)
if self.type in [
"reduce_scatter",
"_reduce_scatter_base",
"reduce_scatter_tensor_coalesced",
] and not (
math.prod(other.input_sizes[0])
== math.prod(self.output_sizes[0]) * self.pg_size
if (
self.type
in [
"reduce_scatter",
"_reduce_scatter_base",
"reduce_scatter_tensor_coalesced",
]
and math.prod(other.input_sizes[0])
!= math.prod(self.output_sizes[0]) * self.pg_size
):
return MatchInfo(
MatchState.SIZE_OR_SYNTAX_MISMATCH,

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@ -326,7 +326,7 @@ class CMake:
# The default value cannot be easily obtained in CMakeLists.txt. We set it here.
py_lib_path = sysconfig.get_path("purelib")
cmake_prefix_path = build_options.get("CMAKE_PREFIX_PATH", None)
cmake_prefix_path = build_options.get("CMAKE_PREFIX_PATH")
if cmake_prefix_path:
build_options["CMAKE_PREFIX_PATH"] = (
py_lib_path + ";" + cast(str, cmake_prefix_path)

View File

@ -43,7 +43,7 @@ def add_job(
if workflow_name not in workflows:
workflows[workflow_name] = {"when": "always", "jobs": []}
requires = job.get("requires", None)
requires = job.get("requires")
if requires is not None:
for requirement in requires:
dependency = past_jobs[requirement]