<reponame>bridgeland/Theano-PyMC
from theano.gof.sched import (
    make_dependence_cmp,
    sort_apply_nodes,
    reverse_dict,
    _toposort,
    posort,
)

from theano import tensor
from theano.gof.graph import io_toposort
from theano.compat import cmp


def test_dependence():
    dependence = make_dependence_cmp()

    x = tensor.matrix("x")
    y = tensor.dot(x * 2, x + 1)
    nodes = io_toposort([x], [y])

    for a, b in zip(nodes[:-1], nodes[1:]):
        assert dependence(a, b) <= 0


def test_sort_apply_nodes():
    x = tensor.matrix("x")
    y = tensor.dot(x * 2, x + 1)

    def str_cmp(a, b):
        return cmp(str(a), str(b))  # lexicographical sort

    nodes = sort_apply_nodes([x], [y], cmps=[str_cmp])

    for a, b in zip(nodes[:-1], nodes[1:]):
        assert str(a) <= str(b)


def test_reverse_dict():
    d = {"a": (1, 2), "b": (2, 3), "c": ()}
    # Python 3.3 enable by default random hash for dict.
    # This change the order of traversal, so this can give 2 outputs
    assert reverse_dict(d) == {1: ("a",), 2: ("a", "b"), 3: ("b",)} or reverse_dict(
        d
    ) == {1: ("a",), 2: ("b", "a"), 3: ("b",)}


def test__toposort():
    edges = {
        1: set((4, 6, 7)),
        2: set((4, 6, 7)),
        3: set((5, 7)),
        4: set((6, 7)),
        5: set((7,)),
    }
    order = _toposort(edges)
    assert not any(
        a in edges.get(b, ()) for i, a in enumerate(order) for b in order[i:]
    )


def test_posort_easy():
    nodes = "asdfghjkl"

    def mycmp(a, b):
        if a < b:
            return -1
        elif a > b:
            return 1
        else:
            return 0

    assert posort(nodes, mycmp) == list("adfghjkls")


def test_posort():
    l = list(range(1, 20))
    cmps = [
        lambda a, b: a % 10 - b % 10,
        lambda a, b: (a / 10) % 2 - (b / 10) % 2,
        lambda a, b: a - b,
    ]
    assert posort(l, *cmps) == [
        10,
        1,
        11,
        2,
        12,
        3,
        13,
        4,
        14,
        5,
        15,
        6,
        16,
        7,
        17,
        8,
        18,
        9,
        19,
    ]

from theano.gof.sched import (
    make_dependence_cmp,
    sort_apply_nodes,
    reverse_dict,
    _toposort,
    posort,
)

from theano import tensor
from theano.gof.graph import io_toposort
from theano.compat import cmp


def test_dependence():
    dependence = make_dependence_cmp()

    x = tensor.matrix("x")
    y = tensor.dot(x * 2, x + 1)
    nodes = io_toposort([x], [y])

    for a, b in zip(nodes[:-1], nodes[1:]):
        assert dependence(a, b) <= 0


def test_sort_apply_nodes():
    x = tensor.matrix("x")
    y = tensor.dot(x * 2, x + 1)

    def str_cmp(a, b):
        return cmp(str(a), str(b))  # lexicographical sort

    nodes = sort_apply_nodes([x], [y], cmps=[str_cmp])

    for a, b in zip(nodes[:-1], nodes[1:]):
        assert str(a) <= str(b)


def test_reverse_dict():
    d = {"a": (1, 2), "b": (2, 3), "c": ()}
    # Python 3.3 enable by default random hash for dict.
    # This change the order of traversal, so this can give 2 outputs
    assert reverse_dict(d) == {1: ("a",), 2: ("a", "b"), 3: ("b",)} or reverse_dict(
        d
    ) == {1: ("a",), 2: ("b", "a"), 3: ("b",)}


def test__toposort():
    edges = {
        1: set((4, 6, 7)),
        2: set((4, 6, 7)),
        3: set((5, 7)),
        4: set((6, 7)),
        5: set((7,)),
    }
    order = _toposort(edges)
    assert not any(
        a in edges.get(b, ()) for i, a in enumerate(order) for b in order[i:]
    )


def test_posort_easy():
    nodes = "asdfghjkl"

    def mycmp(a, b):
        if a < b:
            return -1
        elif a > b:
            return 1
        else:
            return 0

    assert posort(nodes, mycmp) == list("adfghjkls")


def test_posort():
    l = list(range(1, 20))
    cmps = [
        lambda a, b: a % 10 - b % 10,
        lambda a, b: (a / 10) % 2 - (b / 10) % 2,
        lambda a, b: a - b,
    ]
    assert posort(l, *cmps) == [
        10,
        1,
        11,
        2,
        12,
        3,
        13,
        4,
        14,
        5,
        15,
        6,
        16,
        7,
        17,
        8,
        18,
        9,
        19,
    ]
# lexicographical sort # Python 3.3 enable by default random hash for dict. # This change the order of traversal, so this can give 2 outputs