Function test_vectorize_config0

hyperopt/tests/unit/test_vectorize.py:127–199

()

def test_vectorize_config0():
    p0 = hp_uniform("p0", 0, 1)
    p1 = hp_loguniform("p1", 2, 3)
    p2 = hp_choice("p2", [-1, p0])
    p3 = hp_choice("p3", [-2, p1])
    p4 = 1
    p5 = [3, 4, p0]
    p6 = hp_choice("p6", [-3, p1])
    d = locals()
    d["p1"] = None  # -- don't sample p1 all the time, only if p3 says so
    config = as_apply(d)

    N = as_apply("N:TBA")
    expr = config
    expr_idxs = scope.range(N)
    vh = VectorizeHelper(expr, expr_idxs, build=True)
    vconfig = vh.v_expr

    full_output = as_apply([vconfig, vh.idxs_by_label(), vh.vals_by_label()])

    if 1:
        print("=" * 80)
        print("VECTORIZED")
        print(full_output)
        print("\n" * 1)

    fo2 = replace_repeat_stochastic(full_output)
    if 0:
        print("=" * 80)
        print("VECTORIZED STOCHASTIC")
        print(fo2)
        print("\n" * 1)

    new_vc = recursive_set_rng_kwarg(fo2, as_apply(np.random.default_rng(1)))
    if 0:
        print("=" * 80)
        print("VECTORIZED STOCHASTIC WITH RNGS")
        print(new_vc)

    Nval = 10
    foo, idxs, vals = rec_eval(new_vc, memo={N: Nval})

    print("foo[0]", foo[0])
    print("foo[1]", foo[1])
    assert len(foo) == Nval
    if 0:  # XXX refresh these values to lock down sampler
        assert foo[0] == {
            "p0": 0.39676747423066994,
            "p1": None,
            "p2": 0.39676747423066994,
            "p3": 2.1281244479293568,
            "p4": 1,
            "p5": (3, 4, 0.39676747423066994),
        }
    assert (foo[1].keys() != foo[2].keys()) or (foo[1].values() != foo[2].values())

    print(idxs)
    print(vals["p3"])