def test_get_valid_actions_adds_lambda_productions_only_for_correct_type(
self):
state = LambdaGrammarStatelet(
["t"],
{("s", "x"): ["t"]},
{
"s": {
"global":
(torch.Tensor([1, 1]), torch.Tensor([2, 2]), [1, 2])
},
"t": {
"global":
(torch.Tensor([3, 3]), torch.Tensor([4, 4]), [3, 4])
},
},
{"s -> x": (torch.Tensor([5]), torch.Tensor([6]), 5)},
is_nonterminal,
)
actions = state.get_valid_actions()
assert_almost_equal(actions["global"][0].cpu().numpy(), [3, 3])
assert_almost_equal(actions["global"][1].cpu().numpy(), [4, 4])
assert actions["global"][2] == [3, 4]
# We're doing this assert twice to make sure we haven't accidentally modified the state.
actions = state.get_valid_actions()
assert_almost_equal(actions["global"][0].cpu().numpy(), [3, 3])
assert_almost_equal(actions["global"][1].cpu().numpy(), [4, 4])
assert actions["global"][2] == [3, 4]
def test_get_valid_actions_uses_top_of_stack(self):
s_actions = object()
t_actions = object()
e_actions = object()
state = LambdaGrammarStatelet(['s'], {}, {'s': s_actions, 't': t_actions}, {}, is_nonterminal)
assert state.get_valid_actions() == s_actions
state = LambdaGrammarStatelet(['t'], {}, {'s': s_actions, 't': t_actions}, {}, is_nonterminal)
assert state.get_valid_actions() == t_actions
state = LambdaGrammarStatelet(['e'],
{},
{'s': s_actions, 't': t_actions, 'e': e_actions},
{},
is_nonterminal)
assert state.get_valid_actions() == e_actions
def test_get_valid_actions_adds_lambda_productions(self):
state = LambdaGrammarStatelet(['s'],
{('s', 'x'): ['s']},
{'s': {'global': (torch.Tensor([1, 1]), torch.Tensor([2, 2]), [1, 2])}},
{'s -> x': (torch.Tensor([5]), torch.Tensor([6]), 5)},
is_nonterminal)
actions = state.get_valid_actions()
assert_almost_equal(actions['global'][0].cpu().numpy(), [1, 1, 5])
assert_almost_equal(actions['global'][1].cpu().numpy(), [2, 2, 6])
assert actions['global'][2] == [1, 2, 5]
# We're doing this assert twice to make sure we haven't accidentally modified the state.
actions = state.get_valid_actions()
assert_almost_equal(actions['global'][0].cpu().numpy(), [1, 1, 5])
assert_almost_equal(actions['global'][1].cpu().numpy(), [2, 2, 6])
assert actions['global'][2] == [1, 2, 5]
def test_get_valid_actions_uses_top_of_stack(self):
s_actions = object()
t_actions = object()
e_actions = object()
state = LambdaGrammarStatelet(["s"], {}, {
"s": s_actions,
"t": t_actions
}, {}, is_nonterminal)
assert state.get_valid_actions() == s_actions
state = LambdaGrammarStatelet(["t"], {}, {
"s": s_actions,
"t": t_actions
}, {}, is_nonterminal)
assert state.get_valid_actions() == t_actions
state = LambdaGrammarStatelet(["e"], {}, {
"s": s_actions,
"t": t_actions,
"e": e_actions
}, {}, is_nonterminal)
assert state.get_valid_actions() == e_actions