Remove stale xfail scan test

Author: ricardoV94

tests/logprob/test_scan.py

@@ -388,58 +388,6 @@ def scan_fn(mus_t, sigma_t, Y_t_val, S_t_val, Gamma_t):
     assert np.allclose(y_logp_val, y_logp_ref_val)
 
 
-@pytest.mark.xfail(reason="see #148")
-@pytensor.config.change_flags(compute_test_value="raise")
-@pytest.mark.xfail(reason="see #148")
-def test_initial_values():
-    srng = pt.random.RandomStream(seed=2320)
-
-    p_S_0 = np.array([0.9, 0.1])
-    S_0_rv = srng.categorical(p_S_0, name="S_0")
-    S_0_rv.tag.test_value = 0
-
-    Gamma_at = pt.matrix("Gamma")
-    Gamma_at.tag.test_value = np.array([[0, 1], [1, 0]])
-
-    s_0_vv = S_0_rv.clone()
-    s_0_vv.name = "s_0"
-
-    def step_fn(S_tm1, Gamma):
-        S_t = srng.categorical(Gamma[S_tm1], name="S_t")
-        return S_t
-
-    S_1T_rv, _ = pytensor.scan(
-        fn=step_fn,
-        outputs_info=[{"initial": S_0_rv, "taps": [-1]}],
-        non_sequences=[Gamma_at],
-        strict=True,
-        n_steps=10,
-        name="S_0T",
-    )
-
-    S_1T_rv.name = "S_1T"
-    s_1T_vv = S_1T_rv.clone()
-    s_1T_vv.name = "s_1T"
-
-    logp_parts = conditional_logp({S_1T_rv: s_1T_vv, S_0_rv: s_0_vv})
-
-    s_0_val = 0
-    s_1T_val = np.array([1, 0, 1, 0, 1, 1, 0, 1, 0, 1])
-    Gamma_val = np.array([[0.1, 0.9], [0.9, 0.1]])
-
-    exp_res = np.log(p_S_0[s_0_val])
-    s_prev = s_0_val
-    for s in s_1T_val:
-        exp_res += np.log(Gamma_val[s_prev, s])
-        s_prev = s
-
-    S_0T_logp = sum(v.sum() for v in logp_parts.values())
-    S_0T_logp_fn = pytensor.function([s_0_vv, s_1T_vv, Gamma_at], S_0T_logp)
-    res = S_0T_logp_fn(s_0_val, s_1T_val, Gamma_val)
-
-    assert res == pytest.approx(exp_res)
-
-
 @pytest.mark.parametrize("remove_asserts", (True, False))
 def test_mode_is_kept(remove_asserts):
     mode = Mode().including("local_remove_all_assert") if remove_asserts else None