def test_forward(self):
     precise_guess_loss = PreciseGuessLoss()
     predicted_cubes = (torch.stack([
         Magma(FOUR_GROUP).probabilistic_cube,
         CyclicGroup(4).probabilistic_cube,
     ]).to(CURRENT_DEVICE).view(-1, 4, 4, 4))
     target_cubes = (torch.stack([
         Magma(FOUR_GROUP).probabilistic_cube,
         Magma(FOUR_GROUP).probabilistic_cube,
     ]).to(CURRENT_DEVICE).view(-1, 4, 4, 4))
     self.assertEqual(precise_guess_loss(predicted_cubes, target_cubes),
                      0.5)
     self.assertEqual(precise_guess_loss(target_cubes, target_cubes), 1.0)
Beispiel #2
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 def test_forward(self):
     cayley_cube = (torch.stack([
         Magma(FOUR_GROUP).probabilistic_cube,
         Magma(FOUR_GROUP).probabilistic_cube,
     ]).view(-1, 4, 4, 4).to(CURRENT_DEVICE))
     self.assertEqual(
         self.magma_dae(cayley_cube).detach().sum().item(),
         32.0,
     )
     self.assertEqual(
         self.magma_vae(cayley_cube).detach().sum().item(),
         32.0,
     )
Beispiel #3
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def random_semigroup(dim: int,
                     maximal_tries: int) -> Tuple[bool, torch.Tensor]:
    """
    randomly search for a semigroup Cayley table.
    Not recommended to use with dim > 4

    :param dim: number of elements in a semigroup
    :param maximal_tries: how many times to try at most
    :returns: a pair (whether the Cayley table is associative, a Cayley table of a magma)

    """
    associative = False
    try_count = 0
    magma = Magma(cardinality=dim)
    while not associative and try_count <= maximal_tries:
        magma = Magma(cardinality=dim)
        associative = magma.is_associative
        try_count += 1
    return associative, magma.cayley_table
Beispiel #4
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def get_magma_by_index(cardinality: int, index: int) -> Magma:
    """
    find a magma from a lexicographical order by its index

    :param cardinality: the number of elements in a magma
    :param index: an index of magma in a lexicographical order
    :returns: a magma with a given index
    """
    square = cardinality**2
    if index < 0 or index >= cardinality**square:
        raise ValueError("""
        An index must be non negative and less than $n^(n^2)$""")
    cayley_table = list()
    residual = index
    for _ in range(square):
        cayley_table.append(residual % cardinality)
        residual = residual // cardinality
    return Magma(
        torch.tensor(list(reversed(cayley_table))).reshape(
            cardinality, cardinality))
 def test_guessed_ratio(self):
     ratio = guessed_ratio(
         Magma(FOUR_GROUP).probabilistic_cube.view(-1, 4, 4, 4),
         Magma(FOUR_GROUP).probabilistic_cube.view(-1, 4, 4, 4),
     )
     self.assertTrue(torch.tensor(1.0).allclose(ratio))
 def test_associate_ratio(self):
     ratio = associative_ratio(
         Magma(FOUR_GROUP).probabilistic_cube.view(-1, 4, 4, 4),
         torch.tensor(0.0),
     )
     self.assertTrue(torch.tensor(1.0).allclose(ratio))
 def test_is_associative(self):
     self.assertFalse(Magma(torch.tensor([[0, 0], [1, 0]])).is_associative)
     self.assertTrue(self.klein_group.is_associative)
     self.assertFalse(self.some_magma.is_associative)
 def setUp(self):
     torch.manual_seed(777)
     self.some_magma = Magma(NON_ASSOCIATIVE_MAGMA)
     self.klein_group = Magma(FOUR_GROUP)