def test_iter_nodes_by_layer(self):
E = DependencyNode('E', 5, 'CE')
D = DependencyNode('D', 4, 'CD')
C = DependencyNode('C', 3, 'BC', [D, E])
A = DependencyNode('A', 1, 'BA')
B = DependencyNode('B', 2, 'CB', [A, C])
tree = DependencyTree('answer')
tree.root = B
res = tree.iter_nodes_from_root()
self.assertTrue(res.index(B) == 0)
self.assertTrue(0 < res.index(A) < 3)
self.assertTrue(0 < res.index(C) < 3)
self.assertTrue(2 < res.index(D) < 5)
self.assertTrue(2 < res.index(E) < 5)
def test_train_runs(self):
# "bravo 42 also wrong alpha"
# 1 2 3 4 5
# root: also
# dep0: bravo
# dep1: 42
# dep1: wrong
# dep0: alpha
vocab = {
'alpha': 0,
'bravo': 1,
'42': 2,
'not 42': 3,
'also': 4,
'wrong': 5
}
deplist = {'dep0': 0, 'dep1': 1}
d = 3
answers = ['42', 'not 42']
tree = DependencyTree('42')
tree.add(DependencyNode('also', 3, None)) # root
tree.add(DependencyNode('bravo', 1, 'dep0'), 3)
tree.add(DependencyNode('42', 2, 'dep1'), 1)
tree.add(DependencyNode('wrong', 4, 'dep1'), 3)
tree.add(DependencyNode('alpha', 5, 'dep0'), 4)
root2 = DependencyNode('not 42', 1, None, [])
tree2 = DependencyTree('not 42')
tree2.add(root2)
q = model.QANTA(d, vocab, deplist)
q.train([tree, tree2])
def test_train_runs(self):
# "bravo 42 also wrong alpha"
# 1 2 3 4 5
# root: also
# dep0: bravo
# dep1: 42
# dep1: wrong
# dep0: alpha
vocab = {'alpha':0, 'bravo':1, '42':2, 'not 42':3, 'also': 4, 'wrong':5}
deplist = {'dep0':0, 'dep1':1}
d = 3
answers = ['42', 'not 42']
tree = DependencyTree('42')
tree.add(DependencyNode('also', 3, None)) # root
tree.add(DependencyNode('bravo', 1, 'dep0'), 3)
tree.add(DependencyNode('42', 2, 'dep1'), 1)
tree.add(DependencyNode('wrong', 4, 'dep1'), 3)
tree.add(DependencyNode('alpha', 5, 'dep0'), 4)
root2 = DependencyNode('not 42', 1, None, [])
tree2 = DependencyTree('not 42')
tree2.add(root2)
q = model.QANTA(d, vocab, deplist)
q.train([tree, tree2])
def __init__(self, arg):
super(TestPredict, self).__init__(arg)
self.trees = []
tree = DependencyTree('Margaret')
tree.add(DependencyNode('is', 2, 'b'), None)
tree.add(DependencyNode('She', 1, 'a'), 2)
tree.add(DependencyNode('Denmark\'s', 3, 'c'), 2)
tree.add(DependencyNode('queen', 4, 'd'), 3)
self.trees.append(tree)
tree = DependencyTree('BMW')
tree.add(DependencyNode('car', 3, 'b'), None)
tree.add(DependencyNode('famous', 2, 'c'), 3)
tree.add(DependencyNode('brand', 4, 'd'), 3)
tree.add(DependencyNode('A', 1, 'a'), 2)
self.trees.append(tree)
tree = DependencyTree('Horse')
tree.add(DependencyNode('large', 2, 'c'), None)
tree.add(DependencyNode('A', 1, 'd'), 2)
tree.add(DependencyNode('scary', 3, 'b'), 2)
tree.add(DependencyNode('animal', 4, 'a'), 3)
self.trees.append(tree)
def __init__(self, arg):
super(TestPredict, self).__init__(arg)
self.trees = []
tree = DependencyTree('Margaret')
tree.add(DependencyNode('is',2, 'b'), None)
tree.add(DependencyNode('She', 1, 'a'), 2)
tree.add(DependencyNode('Denmark\'s', 3, 'c'), 2)
tree.add(DependencyNode('queen', 4, 'd'), 3)
self.trees.append(tree)
tree = DependencyTree('BMW')
tree.add(DependencyNode('car', 3, 'b'), None)
tree.add(DependencyNode('famous',2, 'c'), 3)
tree.add(DependencyNode('brand', 4, 'd'), 3)
tree.add(DependencyNode('A', 1, 'a'), 2)
self.trees.append(tree)
tree = DependencyTree('Horse')
tree.add(DependencyNode('large',2, 'c'), None)
tree.add(DependencyNode('A', 1, 'd'), 2)
tree.add(DependencyNode('scary', 3, 'b'), 2)
tree.add(DependencyNode('animal', 4, 'a'), 3)
self.trees.append(tree)
