import numpy

from theano.tensor.utils import hash_from_ndarray, hash_from_dict


def test_hash_from_ndarray():
    hashs = []
    rng = numpy.random.rand(5, 5)

    for data in [-2, -1, 0, 1, 2, numpy.zeros((1, 5)), numpy.zeros((1, 6)),
                  # Data buffer empty but different shapes
                  numpy.zeros((1, 0)), numpy.zeros((2, 0)),
                  # Same data buffer and shapes but different strides
                  numpy.arange(25).reshape(5, 5),
                  numpy.arange(25).reshape(5, 5).T,
                  # Same data buffer, shapes and strides but different dtypes
                  numpy.zeros((5, 5), dtype="uint32"),
                  numpy.zeros((5, 5), dtype="int32"),

                  # Test slice
                  rng, rng[1:], rng[:4], rng[1:3], rng[::2], rng[::-1]
                  ]:
        data = numpy.asarray(data)
        hashs.append(hash_from_ndarray(data))

    assert len(set(hashs)) == len(hashs)

    # test that different type of views and their copy give the same hash
    assert hash_from_ndarray(rng[1:]) == hash_from_ndarray(rng[1:].copy())
    assert hash_from_ndarray(rng[1:3]) == hash_from_ndarray(rng[1:3].copy())
    assert hash_from_ndarray(rng[:4]) == hash_from_ndarray(rng[:4].copy())
    assert hash_from_ndarray(rng[::2]) == hash_from_ndarray(rng[::2].copy())
    assert hash_from_ndarray(rng[::-1]) == hash_from_ndarray(rng[::-1].copy())


def test_hash_from_dict():
    dicts = [{}, {0: 0}, {0: 1}, {1: 0}, {1: 1},
             {0: (0,)}, {0: [1]},
             {0: (0, 1)}, {0: [1, 0]},
         ]
    hashs = []
    for idx, d in enumerate(dicts):
        h = hash_from_dict(d)
        assert h not in hashs
        hashs.append(h)

    # List are not hashable. So they are transformed into tuple.
    assert hash_from_dict({0: (0,)}) == hash_from_dict({0: [0]})
