def test_good_case3(self):
s = r'''
0 1 0
0 2 -1
1 2 -1
2
'''
fsa = k2.str_to_fsa(s)
self.assertTrue(k2.is_valid(fsa))
def test_good_case2(self):
s = r'''
0 1 0
0 2 0
2 3 -1
3
'''
fsa = k2.str_to_fsa(s)
self.assertTrue(k2.is_valid(fsa))
def test_bad_case2(self):
# only kFinalSymbol arcs enter the final state
s = r'''
0 1 0
0 2 1
1 2 0
2
'''
fsa = k2.str_to_fsa(s)
self.assertFalse(k2.is_valid(fsa))
def test_good_cases1(self):
# empty fsa is valid
array_size = k2.IntArray2Size(0, 0)
fsa = k2.Fsa.create_fsa_with_size(array_size)
self.assertTrue(k2.is_valid(fsa))
def test_bad_case3(self):
# `arc_indexes` and `arcs` in this state are not consistent
arc_indexes = torch.IntTensor([0, 2, 2, 2])
arcs = torch.IntTensor([[0, 1, 0], [0, 2, 1], [1, 2, 0]])
fsa = k2.Fsa(arc_indexes, arcs)
self.assertFalse(k2.is_valid(fsa))
def test_bad_case1(self):
# fsa should contain at least two states
array_size = k2.IntArray2Size(1, 0)
fsa = k2.Fsa.create_fsa_with_size(array_size)
self.assertFalse(k2.is_valid(fsa))