From 246527b5a9aca67014097dc0ce04f6e03fd82c41 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Val=C3=A9rian=20Rey?= <valerian.rey@gmail.com>
Date: Wed, 7 Oct 2026 17:28:57 +0200
Subject: [PATCH] Remove GradVac weighting alias and hard-coded repr names

GradVac stored its weighting a second time in `_gradvac_weighting`, although
the base class already exposes it as `gramian_weighting`. GradVac.__repr__ and
QuadprogProjector.__repr__ now use `self.__class__.__name__`, like the other
classes, so that subclasses get the right name.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 src/torchjd/_linalg/_dual_cone.py   |  2 +-
 src/torchjd/aggregation/_gradvac.py | 16 +++++++---------
 2 files changed, 8 insertions(+), 10 deletions(-)

diff --git a/src/torchjd/_linalg/_dual_cone.py b/src/torchjd/_linalg/_dual_cone.py
index 7dd32482..01e80f56 100644
--- a/src/torchjd/_linalg/_dual_cone.py
+++ b/src/torchjd/_linalg/_dual_cone.py
@@ -102,7 +102,7 @@ def reg_eps(self, value: float) -> None:
         self._reg_eps = value
 
     def __repr__(self) -> str:
-        return f"QuadprogProjector(norm_eps={self._norm_eps}, reg_eps={self._reg_eps})"
+        return f"{self.__class__.__name__}(norm_eps={self._norm_eps}, reg_eps={self._reg_eps})"
 
     def __call__(self, U: Tensor, G: PSDMatrix) -> Tensor:
 
diff --git a/src/torchjd/aggregation/_gradvac.py b/src/torchjd/aggregation/_gradvac.py
index 73464c11..8d646754 100644
--- a/src/torchjd/aggregation/_gradvac.py
+++ b/src/torchjd/aggregation/_gradvac.py
@@ -165,30 +165,28 @@ class GradVac(GramianWeightedAggregator, Stateful, _NonDifferentiable):
     gramian_weighting: GradVacWeighting
 
     def __init__(self, beta: float = 0.5, eps: float = 1e-8) -> None:
-        weighting = GradVacWeighting(beta=beta, eps=eps)
-        super().__init__(weighting)
-        self._gradvac_weighting = weighting
+        super().__init__(GradVacWeighting(beta=beta, eps=eps))
 
     @property
     def beta(self) -> float:
-        return self._gradvac_weighting.beta
+        return self.gramian_weighting.beta
 
     @beta.setter
     def beta(self, value: float) -> None:
-        self._gradvac_weighting.beta = value
+        self.gramian_weighting.beta = value
 
     @property
     def eps(self) -> float:
-        return self._gradvac_weighting.eps
+        return self.gramian_weighting.eps
 
     @eps.setter
     def eps(self, value: float) -> None:
-        self._gradvac_weighting.eps = value
+        self.gramian_weighting.eps = value
 
     def reset(self) -> None:
         """Clears EMA state so the next forward starts from zero targets."""
 
-        self._gradvac_weighting.reset()
+        self.gramian_weighting.reset()
 
     def __repr__(self) -> str:
-        return f"GradVac(beta={self.beta!r}, eps={self.eps!r})"
+        return f"{self.__class__.__name__}(beta={self.beta!r}, eps={self.eps!r})"