Adjust numba test

tests/link/numba/test_slinalg.py

@@ -724,25 +724,36 @@ def test_lu_solve(b_func, b_shape: tuple[int, ...], trans: bool, overwrite_b: bo
  np.testing.assert_allclose(b_val_not_contig, b_val)
 
 
-@pytest.mark.parametrize("stride", [1, 2, -1, -2], ids=lambda x: f"stride={x}")
-def test_banded_dot(stride):
+def test_banded_dot():
  rng = np.random.default_rng()
 
+ A = pt.tensor("A", shape=(10, 10), dtype=config.floatX)
  A_val = _make_banded_A(rng.normal(size=(10, 10)), kl=1, ku=1).astype(config.floatX)
 
- x_shape = (10 * abs(stride),)
- x_val = rng.normal(size=x_shape).astype(config.floatX)
- x_val = x_val[::stride]
-
- A = pt.tensor("A", shape=A_val.shape, dtype=A_val.dtype)
- x = pt.tensor("x", shape=x_val.shape, dtype=x_val.dtype)
+ x = pt.tensor("x", shape=(10,), dtype=config.floatX)
+ x_val = rng.normal(size=(10,)).astype(config.floatX)
 
  output = banded_dot(A, x, upper_diags=1, lower_diags=1)
 
- compare_numba_and_py(
+ fn, _ = compare_numba_and_py(
  [A, x],
  output,
  test_inputs=[A_val, x_val],
  numba_mode=numba_inplace_mode,
  eval_obj_mode=False,
  )
+
+ for stride in [2, -1, -2]:
+ x_shape = (10 * abs(stride),)
+ x_val = rng.normal(size=x_shape).astype(config.floatX)
+ x_val = x_val[::stride]
+
+ nb_output = fn(A_val, x_val)
+ expected = A_val @ x_val
+
+ np.testing.assert_allclose(
+ nb_output,
+ expected,
+ strict=True,
+ err_msg=f"Test failed for stride = {stride}",
+ )