Fix Numba pos solve condition number calculation

Author: ricardoV94

pytensor/link/numba/dispatch/slinalg.py

@@ -884,7 +884,7 @@ def _posv(
     overwrite_b: bool,
     check_finite: bool,
     transposed: bool,
-) -> tuple[np.ndarray, int]:
+) -> tuple[np.ndarray, np.ndarray, int]:
     """
     Placeholder for solving a linear system with a positive-definite matrix; used by linalg.solve.
     """
@@ -901,7 +901,8 @@ def posv_impl(
     check_finite: bool,
     transposed: bool,
 ) -> Callable[
-    [np.ndarray, np.ndarray, bool, bool, bool, bool, bool], tuple[np.ndarray, int]
+    [np.ndarray, np.ndarray, bool, bool, bool, bool, bool],
+    tuple[np.ndarray, np.ndarray, int],
 ]:
     ensure_lapack()
     _check_scipy_linalg_matrix(A, "solve")
@@ -918,7 +919,7 @@ def impl(
         overwrite_b: bool,
         check_finite: bool,
         transposed: bool,
-    ) -> tuple[np.ndarray, int]:
+    ) -> tuple[np.ndarray, np.ndarray, int]:
         _solve_check_input_shapes(A, B)
 
         _N = np.int32(A.shape[-1])
@@ -962,8 +963,9 @@ def impl(
         )
 
         if B_is_1d:
-            return B_copy[..., 0], int_ptr_to_val(INFO)
-        return B_copy, int_ptr_to_val(INFO)
+            B_copy = B_copy[..., 0]
+
+        return A_copy, B_copy, int_ptr_to_val(INFO)
 
     return impl
 
@@ -1064,10 +1066,12 @@ def impl(
     ) -> np.ndarray:
         _solve_check_input_shapes(A, B)
 
-        x, info = _posv(A, B, lower, overwrite_a, overwrite_b, check_finite, transposed)
+        C, x, info = _posv(
+            A, B, lower, overwrite_a, overwrite_b, check_finite, transposed
+        )
         _solve_check(A.shape[-1], info)
 
-        rcond, info = _pocon(x, _xlange(A))
+        rcond, info = _pocon(C, _xlange(A))
         _solve_check(A.shape[-1], info=info, lamch=True, rcond=rcond)
 
         return x