Fix solve_triangular output when overwrite_b=True

pytensor/link/numba/dispatch/slinalg.py

@@ -126,17 +126,17 @@
 
         B_is_1d = B.ndim == 1
 
-        if overwrite_b:
-            B_copy = B
-        else:
-            if B_is_1d:
-                # _copy_to_fortran_order does nothing with vectors
-                B_copy = np.copy(B)
-            else:
-                B_copy = _copy_to_fortran_order(B)
+        A_copy = _copy_to_fortran_order(A)
 
-        if B_is_1d:
-            B_copy = np.expand_dims(B_copy, -1)
+        # This list is exhaustive, but numba freaks out if we include a final else clause
+        if not overwrite_b and not B_is_1d:
+            B_copy = _copy_to_fortran_order(B)
+        elif overwrite_b and not B_is_1d:
+            B_copy = np.asfortranarray(B)
+        elif not overwrite_b and B_is_1d:
+            B_copy = np.copy(np.expand_dims(B, -1))
+        elif overwrite_b and B_is_1d:
+            B_copy = np.expand_dims(B, -1)
 
         NRHS = 1 if B_is_1d else int(B_copy.shape[-1])
 
@@ -155,7 +155,7 @@
             DIAG,
             N,
             NRHS,
-            np.asfortranarray(A).T.view(w_type).ctypes,
+            A_copy.view(w_type).ctypes,
             LDA,
             B_copy.view(w_type).ctypes,
             LDB,

tests/link/numba/test_slinalg.py

@@ -10,6 +10,7 @@
 import pytensor
 import pytensor.tensor as pt
 from pytensor import config
+from pytensor.tensor.slinalg import SolveTriangular
 from tests import unittest_tools as utt
 from tests.link.numba.test_basic import compare_numba_and_py
 
@@ -130,6 +131,48 @@ def A_func_pt(x):
     )
 
 
+@pytest.mark.parametrize("overwrite_b", [True, False], ids=["inplace", "not_inplace"])
+def test_solve_triangular_overwrite_b_correct(overwrite_b):
+    # Regression test for issue #1233
+
+    rng = np.random.default_rng(utt.fetch_seed())
+    a_test_py = np.asfortranarray(rng.normal(size=(3, 3)))
+    a_test_py = np.tril(a_test_py)
+    b_test_py = np.asfortranarray(rng.normal(size=(3, 2)))
+
+    # .T.copy().T creates an f-contiguous copy of an f-contiguous array (otherwise the copy is c-contiguous)
+    a_test_nb = a_test_py.T.copy().T
+    b_test_nb = b_test_py.T.copy().T
+
+    op = SolveTriangular(
+        trans=0,
+        unit_diagonal=False,
+        lower=False,
+        check_finite=True,
+        b_ndim=2,
+        overwrite_b=overwrite_b,
+    )
+
+    a_pt = pt.matrix("a", shape=(3, 3))
+    b_pt = pt.matrix("b", shape=(3, 2))
+    out = op(a_pt, b_pt)
+
+    py_fn = pytensor.function([a_pt, b_pt], out, accept_inplace=True)
+    numba_fn = pytensor.function([a_pt, b_pt], out, accept_inplace=True, mode="NUMBA")
+
+    x_py = py_fn(a_test_py, b_test_py)
+    x_nb = numba_fn(a_test_nb, b_test_nb)
+
+    np.testing.assert_allclose(
+        py_fn(a_test_py, b_test_py), numba_fn(a_test_nb, b_test_nb)
+    )
+    np.testing.assert_allclose(b_test_py, b_test_nb)
+
+    if overwrite_b:
+        np.testing.assert_allclose(b_test_py, x_py)
+        np.testing.assert_allclose(b_test_nb, x_nb)
+
+
 @pytest.mark.parametrize("value", [np.nan, np.inf])
 @pytest.mark.filterwarnings(
     'ignore:Cannot cache compiled function "numba_funcified_fgraph"'