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[BE] Fix B018 useless-expression violations in inductor and fx unific… · pytorch/pytorch@e9cfafa · GitHub
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[BE] Fix B018 useless-expression violations in inductor and fx unification (#191866)
--- ### Addendum (post-review): F811 evidence and runtime verification **Literal F811 output** with the two noqas stripped from the PR's files (CI-pinned ruff 0.14.4): ``` core.py:140:5: F811 Redefinition of unused `unify` from line 118: `unify` redefined here variable.py:63:5: F811 Redefinition of unused `isvar` from line 56: `isvar` redefined here Found 2 errors. ``` With the noqas present, the full-config check reports `All checks passed!` — so under RUF100 both the presence and the placement are exactly what ruff requires. **Why only these two sites**: ruff's F811 exempts underscore-prefixed names (dummy-variable convention). Minimal repro — two identical `@dispatch` overload chains, one named `_priv`, one named `pub`: ``` f811_repro.py:9:5: F811 Redefinition of unused `pub` from line 7: `pub` redefined here Found 1 error. ``` Only `pub` is flagged. That is why the five `_reify` redefinitions (and `_eval_is_ge` in `torch/utils/_sympy/singleton_int.py`) need no suppression while the public `unify`/`isvar` do. **Runtime verification**: imported the changed `unification` package and the unmodified main version side by side as standalone packages (the subtree is stdlib-only + vendored multipledispatch) and compared 18 aspects: `unify`/`reify`/`isvar` behavior on tuples/lists/dicts/vars including exact exception types and messages for the unsupported-signature cases, plus the complete dispatch registries of `unify`, `isvar`, `_unify`, and `_reify`. All 18 identical (package-name normalized). This exercises the import-time `@dispatch` registration side effects directly. Pull Request resolved: #191866 Approved by: https://github.com/jansel
1 parent 01d92f4 commit e9cfafa

4 files changed

Lines changed: 13 additions & 23 deletions

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‎torch/_inductor/comm_lowering.py‎

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -199,7 +199,7 @@ def register_comm_lowerings():
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Register lowerings for the comm subsystem.
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"""
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try:
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torch.ops._c10d_functional.all_reduce
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_ = torch.ops._c10d_functional.all_reduce
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except AttributeError:
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log.info(
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"Inductor support for distributed collectives depends on building "
@@ -483,7 +483,7 @@ def register_symm_mem_lowerings():
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# torch.ops.symm_mem is a lazy namespace that always exists,
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# but the operations may not exist on non-CUDA platforms or
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# when USE_DISTRIBUTED is disabled.
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symm_mem.one_shot_all_reduce
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_ = symm_mem.one_shot_all_reduce
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except AttributeError:
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log.info("symm_mem ops not available, skipping symm_mem lowerings")
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return

‎torch/_inductor/runtime/triton_heuristics.py‎

Lines changed: 5 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -3331,7 +3331,11 @@ def _find_names(obj):
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frame = inspect.currentframe()
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while frame is not None:
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frame.f_locals
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# On CPython <= 3.12 this access materializes the frame's locals
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# dict so gc.get_referrers below can find obj inside it. On 3.13+
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# f_locals is a fresh write-through proxy (PEP 667) and this loop
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# is a no-op, so function-local names are not discoverable there.
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_ = frame.f_locals
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frame = frame.f_back
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obj_names = []
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for referrer in gc.get_referrers(obj):

‎torch/fx/experimental/unification/core.py‎

Lines changed: 3 additions & 16 deletions
Original file line numberDiff line numberDiff line change
@@ -30,33 +30,21 @@ def _reify(t: Iterator[object], s: dict[Var, object]) -> Iterator[object]:
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# return (reify(arg, s) for arg in t)
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_reify
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@dispatch(tuple, dict) # type: ignore[no-redef]
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def _reify(t: tuple[Unpack[_Ts]], s: dict[Var, object]) -> tuple[Unpack[_Ts]]:
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return tuple(reify(iter(t), s)) # pyrefly: ignore[bad-argument-type, bad-return]
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_reify
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@dispatch(list, dict) # type: ignore[no-redef]
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def _reify(t: list[object], s: dict[Var, object]) -> list[object]:
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return list(reify(iter(t), s)) # pyrefly: ignore[bad-argument-type]
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_reify
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@dispatch(dict, dict) # type: ignore[no-redef]
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def _reify(d: dict[object, object], s: dict[Var, object]) -> dict[object, object]:
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return {k: reify(v, s) for k, v in d.items()}
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_reify
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@dispatch(object, dict) # type: ignore[no-redef]
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def _reify(o: object, s: dict[Var, object]) -> object:
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return o # catch all, just return the object
@@ -146,9 +134,8 @@ def unify(
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return _unify(u, v, s)
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unify
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@dispatch(object, object) # type: ignore[no-redef]
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def unify(u: object, v: object) -> dict[Var, object] | bool:
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# The noqa suppresses F811 for this multipledispatch overload redefinition
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# (it replaces the bare-name-statement hack that previously silenced it).
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def unify(u: object, v: object) -> dict[Var, object] | bool: # noqa: F811
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return unify(u, v, {})

‎torch/fx/experimental/unification/variable.py‎

Lines changed: 3 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -57,11 +57,10 @@ def isvar(v: Var) -> Literal[True]:
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return True
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isvar
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@dispatch(object) # type: ignore[no-redef]
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def isvar(o: object) -> bool:
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# The noqa suppresses F811 for this multipledispatch overload redefinition
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# (it replaces the bare-name-statement hack that previously silenced it).
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def isvar(o: object) -> bool: # noqa: F811
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return bool(_glv and hashable(o) and o in _glv)
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