hybrid_tree_utils.py
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from collections import defaultdict
from . import tree_utils
from .constants import (
EMPTY,
UPPERCASE,
LEMMAS,
LEMMA_CASES,
LEMMA_RULES,
TAGS,
HEADS,
DEPRELS,
SPINES,
ANCHORS,
ANCHOR_HS,
)
def make_lemma(token, case, rule):
cut_prefix, cut, suffix = rule.split('_', maxsplit=2)
cut_prefix, cut = int(cut_prefix), int(cut)
lemma = token.lower()
if cut_prefix:
lemma = lemma[cut_prefix:]
if cut:
lemma = lemma[:-cut]
lemma += suffix
# failsafe
if not lemma:
return token
if case == UPPERCASE:
lemma = lemma[0].upper() + lemma[1:]
return lemma
def correct_lemma(token, lemma, tag, morfeusz):
match = [interp[2] for interp in morfeusz.analyse(token) if interp[2][0] == token and interp[2][2] == tag]
match_lemmas = set(interp[1].split(':')[0] if ':' not in interp[0] else interp[1] for interp in match)
if match_lemmas and lemma.lower() not in [l.lower() for l in match_lemmas]:
if len(match_lemmas) != 1:
print(token, lemma, tag, '->', sorted(match_lemmas))
print(' ---> >1 matching lemma, will take alphabetically first!')
return sorted(match_lemmas)[0]
return lemma
def normalize(chart):
N = len(chart)
norm = [max(1e-12, sum(chart[i][j] for j in range(N))) for i in range(N)]
normalized = [[chart[i][j] / norm[i] for j in range(N)] for i in range(N)]
return normalized
def add_root(chart):
N = len(chart)
chartr = [[0.0 for j in range(N + 1)] for i in range(N + 1)]
for i in range(N):
for j in range(N):
if i == j:
chartr[i + 1][0] = chart[i][i]
else:
chartr[i + 1][j + 1] = chart[i][j]
return chartr
def mst(chart):
edges = []
N = len(chart)
paths = {(i, i) for i in range(N)}
for i, row in enumerate(chart):
edges += [(weight, j, i) for j, weight in enumerate(row)]
edges = list(reversed(sorted(edges)))
tree = set()
while edges and len(tree) < N - 1:
w, i, j = edges[0]
if w == 0:
break
tree.add((i, j))
# there can be only one root!
if i == 0:
edges = [e for e in edges if e[1] != 0]
new_paths = {(i, j)}
for p1 in paths:
for p2 in paths:
if p1[1] == i and p2[0] == j:
new_path = (p1[0], p2[1])
new_paths.add(new_path)
paths.update(new_paths)
edges = [e for e in edges if e[2] != j and (e[2], e[1]) not in paths]
assert(len(tree) == N - 1)
return tree
def get_heads(matrix):
chart_n = normalize(matrix)
chart_r = add_root(chart_n)
heads = {dep - 1: hd - 1 for hd, dep in mst(chart_r) if dep > 0}
return [hd for dep, hd in sorted(heads.items())]
def make_head_path(path, token, lemma, tag, index):
node = tree_utils.TreeNode(0, (token, lemma, tag), True, {'index' : index}, [])
if path == EMPTY:
return node
for cat in reversed(path.split('_')):
node = tree_utils.TreeNode(0, cat, True, {}, [node])
return node
def append_dependent(head_path, dep_path, anchor_cat, anchor_h, decompress=False):
problem = None
#print('APPENDING:', dep_path.to_brackets())
#print('TO:', head_path.to_brackets())
#print('AT:', anchor_cat, 'H:', repr(anchor_h))
anchor_node = head_path
head_chain = [head_path]
while head_chain[-1].children:
heads = [child for child in head_chain[-1].children if child.is_head]
try:
assert len(heads) == 1
head_chain.append(heads[0])
except:
head_path.pretty_print()
head_chain[-1].pretty_print()
raise
matching_heads = [hd for hd in head_chain if hd.category == anchor_cat]
if not matching_heads:
#hp = '->'.join(h.category for h in head_chain if type(h.category) == str)
#print(f'COULDN’T FIND {anchor_cat} ANCHOR FOR {dep_path.category}, APPENDING TO TOP: {hp}')
anchor_node = head_path
problem = (dep_path, anchor_cat)
else:
# fallback: take the highest
if anchor_h is None:
anchor_h = len(matching_heads)
elif anchor_h > len(matching_heads) and not decompress:
anchor_h = len(matching_heads)
elif anchor_h > len(matching_heads) and decompress:
#print([hd.category for hd in head_chain])
#print(anchor_cat, anchor_h)
expand = anchor_h - len(matching_heads)
#print('NEED TO ADD', expand, anchor_cat, 'NODE(S)')
#head_path.pretty_print()
for i in range(expand):
child = matching_heads[0]
parent = child.parent
new_node = tree_utils.TreeNode(0, anchor_cat, child.is_head, {}, [child])
child.is_head = True
if parent:
parent.children.remove(child)
parent.add_child(new_node)
if head_path == child:
head_path = new_node
matching_heads.insert(0, new_node)
#head_path.pretty_print()
anchor_node = matching_heads[-anchor_h]
anchor_node.add_child(dep_path)
dep_path.is_head = False
return head_path, problem
def rearrange(tree, compress=False):
if tree.children:
children = [rearrange(child, compress=compress) for child in tree.children]
tree.children = sorted(children, key=lambda child: child.features['from'])
tree.features['from'] = tree.children[0].features['from']
tree.features['to'] = max(child.features['to'] for child in tree.children)
else:
tree.features['from'] = tree.features['index']
tree.features['to'] = tree.features['index'] + 1
return tree
POS2PRE = {
'aglt' : 'aglt',
'conj' : 'spójnik',
'dig' : 'formalicz',
'fin' : 'formaczas',
'interp' : 'punct',
'num' : 'formalicz',
'praet' : 'formaczas',
'_' : '???',
}
def add_dummy_pre(path):
pos = path.category[2].split(':')[0]
return tree_utils.TreeNode(0, f'{POS2PRE[pos]}', True, {}, [path])
def check_no_cycles(heads):
children_dict = defaultdict(set)
for i, hd in enumerate(heads):
children_dict[hd].add(i)
visited = {-1}
queue = [-1]
while queue:
children = children_dict.pop(queue[0], set())
if children.intersection(visited):
return False
visited.update(children)
queue = queue[1:] + list(children)
return not children
# find any <EMPTY>’s children and reattach them to <EMPTY>’s head
def try_reattach(heads, spines, tokens):
to_reattach = [i for i, spine in enumerate(spines) if spine == EMPTY and i in heads]
k = 0
while to_reattach:
k += 1
if k == 50:
1/0
print('------- TO REATTACH:')
for i in to_reattach:
print(' ===>', i, tokens[i], '->', [t for t, h in zip(tokens, heads) if h == i])
tr = to_reattach[0]
hd_idx = heads[tr]
assert(hd_idx != -1)
new_heads = heads.copy()
for i, hd in enumerate(heads):
if hd == tr:
new_heads[i] = hd_idx
if check_no_cycles(new_heads):
heads = new_heads
else:
print('can’t reattach (cycle!)')
1/0
to_reattach = [i for i, spine in enumerate(spines) if spine == EMPTY and i in heads]
return heads
def reconstruct_tree(tokens, tags, decompress=False, root_label='ROOT'):
#tokens, heads, deprels, spines, anchors, anchor_hs
morph_tags = tags.get(TAGS, ['_' for _ in tokens])
lemmas = tags.get(LEMMAS, ['_' for _ in tokens])
heads = tags[HEADS]
deprels = tags[DEPRELS]
spines = tags[SPINES]
anchors = tags[ANCHORS]
anchor_hs = tags[ANCHOR_HS]
problems = []
spines = list(spines)
children = defaultdict(set)
for i, (head, spine) in enumerate(zip(heads, spines)):
if (head == -1 and root_label not in spine):
spines[i] = (f'{root_label}_' + spines[i]).replace(f'_{EMPTY}', '')
if (head != -1 and root_label in spine):
assert(spines[i].startswith(root_label))
spines[i] = EMPTY if spines[i] == root_label else spines[i].replace(f'{root_label}_', '')
reattach = False
#print(heads)
#print(spines)
new_heads = try_reattach(heads, spines, tokens)
if new_heads != heads:
heads = new_heads
reattach = True
head_paths = [
make_head_path(p, tok, lemma, tag, i) for i, (p, tok, lemma, tag)
in enumerate(zip(spines, tokens, lemmas, morph_tags))
]
# if a spine is some other spine’s head and consists of a terminal only, add a dummy preterminal to append to
head_paths = [add_dummy_pre(hp) if (type(hp.category) == tuple and i in heads) else hp for i, hp in enumerate(head_paths)]
anchor_hs = [int(h) if h != '<ROOT>' else None for h in anchor_hs]
root = None
for i, head in enumerate(heads):
if deprels[i] is not None:
head_paths[i].features['deprel'] = deprels[i]
if head == -1:
root = i
else:
head_paths[head], problem = append_dependent(
head_paths[head], head_paths[i], anchors[i], anchor_hs[i], decompress=decompress)
if problem:
problems.append(problem)
if reattach:
problems.append('reattach')
return rearrange(head_paths[root], compress=(not decompress)), problems
def make_tree(tokens, tags, root_label, decompress=True):
tree, problems = reconstruct_tree(tokens, tags, decompress=decompress, root_label=root_label)
return tree
# copied and modified from parser_server.py
def _node2dict(tree):
children = [_node2dict(child) for child in tree.children]
leaves = tree.get_yield()
#tok_indices = [leaf.features['index'] for leaf in leaves]
node = {
'is_head' : tree.is_head,
'span' : {'from' : tree.features['from'], 'to' : tree.features['to']},
}
if 'deprel' in tree.features:
node['deprel'] = tree.features['deprel']
if tree.features:
node['attributes'] = tree.features
if children:
node.update({
'category' : tree.category,
'children' : children,
})
else:
node.update(dict(zip(('orth', 'base', 'tag'), tree.category)))
return node
def tree2dict(tree, metadata={}):
return {'tree' : _node2dict(tree), 'metadata' : metadata}