fixes

Author: PierreQuinton

tests/unit/aggregation/_inputs.py

@@ -25,7 +25,7 @@ def _generate_strong_stationary_matrix(m: int, n: int, rank: int) -> Tensor:
     U = torch.hstack([U1, U2])
     Vt = _generate_orthonormal_matrix(n)
     S = torch.diag(torch.abs(torch.randn([rank])))
-    A = U[:, 1 : rank + 1] @ S @ Vt[1 : rank + 1, :]
+    A = U[:, 1 : rank + 1] @ S @ Vt[:rank, :]
     return A
 
 
@@ -46,7 +46,7 @@ def _generate_weak_non_strong_stationary_matrix(m: int, n: int, rank: int) -> Te
     U = torch.hstack([U1, U2])
     Vt = _generate_orthonormal_matrix(n)
     S = torch.diag(torch.abs(torch.randn([rank])))
-    A = U[:, 1 : rank + 1] @ S @ Vt[1 : rank + 1, :]
+    A = U[:, 1 : rank + 1] @ S @ Vt[:rank, :]
     return A
 
 
@@ -109,7 +109,6 @@ def _generate_semi_orthonormal_complement(Q: Tensor) -> Tensor:
     (5, 3, 3),
     (9, 11, 6),
     (7, 13, 2),
-    (3, 5, 3),
 ]
 
 _scales = [0.0, 1e-10, 1e3, 1e5, 1e10, 1e15]

tests/unit/aggregation/_property_testers.py

@@ -113,7 +113,7 @@ class StrongStationarityProperty:
     """
 
     @classmethod
-    @mark.parametrize("stationary_matrix", non_strong_stationary_matrices)
+    @mark.parametrize("matrix", non_strong_stationary_matrices)
     def test_stationarity_property(cls, aggregator: Aggregator, matrix: Tensor):
         cls._assert_stationarity_property(aggregator, matrix)
 

tests/unit/aggregation/test_constant.py

@@ -54,8 +54,8 @@ def test_linear_under_scaling_property(cls, aggregator: Constant, matrix: Tensor
 
     @classmethod
     @mark.parametrize(["aggregator", "matrix"], zip(_aggregators_3, _matrices_3))
-    def test_stationarity_property(cls, aggregator: Constant, non_stationary_matrix: Tensor):
-        cls._assert_stationarity_property(aggregator, non_stationary_matrix)
+    def test_stationarity_property(cls, aggregator: Constant, matrix: Tensor):
+        cls._assert_stationarity_property(aggregator, matrix)
 
 
 @mark.parametrize(