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refactor(aggregation): Fix typing issue in Weighting #539

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Merged
ValerianRey merged 1 commit into from
Jan 29, 2026
Merged

refactor(aggregation): Fix typing issue in Weighting #539

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10 changes: 6 additions & 4 deletions src/torchjd/aggregation/_weighting_bases.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,9 +8,9 @@

from torchjd._linalg import PSDTensor, is_psd_tensor

_T = TypeVar("_T", contravariant=True)
_FnInputT = TypeVar("_FnInputT")
_FnOutputT = TypeVar("_FnOutputT")
_T = TypeVar("_T", contravariant=True, bound=Tensor)
_FnInputT = TypeVar("_FnInputT", bound=Tensor)
_FnOutputT = TypeVar("_FnOutputT", bound=Tensor)


class Weighting(Generic[_T], nn.Module, ABC):
Expand All @@ -27,9 +27,11 @@ def __init__(self):
def forward(self, stat: _T) -> Tensor:
"""Computes the vector of weights from the input stat."""

def __call__(self, stat: _T) -> Tensor:
def __call__(self, stat: Tensor) -> Tensor:
"""Computes the vector of weights from the input stat and applies all registered hooks."""

# The value of _T (e.g. PSDMatrix) is not public, so we need the user-facing type hint of
# stat to be Tensor.
return super().__call__(stat)

def _compose(self, fn: Callable[[_FnInputT], _T]) -> Weighting[_FnInputT]:
Expand Down