def test_case_1(self):
# a non-connected, non-topsorted, acyclic input fsa;
# the output fsa is topsorted.
s = r'''
0 1 1 0
0 2 2 0
1 3 3 0
1 6 -1 0
2 4 2 0
2 6 -1 0
2 1 1 0
5 0 1 0
6
'''
fsa = k2host.str_to_fsa(s)
connection = k2host.Connection(fsa)
array_size = k2host.IntArray2Size()
connection.get_sizes(array_size)
fsa_out = k2host.Fsa.create_fsa_with_size(array_size)
arc_map = k2host.IntArray1.create_array_with_size(array_size.size2)
status = connection.get_output(fsa_out, arc_map)
self.assertTrue(status)
expected_arc_indexes = torch.IntTensor([0, 2, 4, 5, 5])
expected_arcs = torch.IntTensor([[0, 2, 1, 0], [0, 1, 2, 0],
[1, 3, -1, 0], [1, 2, 1, 0],
[2, 3, -1, 0]])
expected_arc_map = torch.IntTensor([0, 1, 5, 6, 3])
self.assertTrue(torch.equal(fsa_out.indexes, expected_arc_indexes))
self.assertTrue(torch.equal(fsa_out.data, expected_arcs))
self.assertTrue(torch.equal(arc_map.data, expected_arc_map))
def test_case_2(self):
# a cyclic input fsa
# after trimming, the cycle is removed;
# so the output fsa should be topsorted.
s = r'''
0 1 1 0
0 2 2 1
1 3 3 -2
1 6 6 -3
2 4 2 4
2 6 3 5
2 6 -1 6
5 0 1 7
5 7 -1 8
7
'''
fsa = k2host.str_to_fsa(s)
connection = k2host.Connection(fsa)
array_size = k2host.IntArray2Size()
connection.get_sizes(array_size)
fsa_out = k2host.Fsa.create_fsa_with_size(array_size)
arc_map = k2host.IntArray1.create_array_with_size(array_size.size2)
status = connection.get_output(fsa_out, arc_map)
self.assertTrue(status)
self.assertTrue(k2host.is_empty(fsa_out))
self.assertTrue(arc_map.empty())
def test_case_4(self):
# a cyclic input fsa
# after trimming, the cycle remains (it is not a self-loop);
# so the output fsa is NOT topsorted.
s = r'''
0 3 3 1
0 2 2 2
1 0 1 3
2 6 -1 4
3 5 5 5
3 2 2 6
3 5 5 7
4 4 4 8
5 3 3 9
5 4 4 10
6
'''
fsa = k2host.str_to_fsa(s)
connection = k2host.Connection(fsa)
array_size = k2host.IntArray2Size()
connection.get_sizes(array_size)
fsa_out = k2host.Fsa.create_fsa_with_size(array_size)
status = connection.get_output(fsa_out)
self.assertFalse(status)
self.assertFalse(k2host.is_top_sorted(fsa_out))
def test_case_3(self):
# a non-connected, non-topsorted, acyclic input fsa;
# the output fsa is topsorted.
s = r'''
0 3 3 1
0 5 5 2
1 2 2 3
2 1 1 4
3 5 5 5
3 2 2 -6
3 4 4 7
3 6 -1 8
4 5 5 9
4 6 -1 10
5 6 -1 11
6
'''
fsa = k2host.str_to_fsa(s)
connection = k2host.Connection(fsa)
array_size = k2host.IntArray2Size()
connection.get_sizes(array_size)
fsa_out = k2host.Fsa.create_fsa_with_size(array_size)
connection.get_output(fsa_out)
self.assertTrue(k2host.is_top_sorted(fsa_out))
