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DependencyMatcher improvements (fix #6678) (#6744)

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* Adding contributor agreement for user werew

* [DependencyMatcher] Comment and clean code

* [DependencyMatcher] Use defaultdicts

* [DependencyMatcher] Simplify _retrieve_tree method

* [DependencyMatcher] Remove prepended underscores

* [DependencyMatcher] Address TODO and move grouping of token's positions out of the loop

* [DependencyMatcher] Remove _nodes attribute

* [DependencyMatcher] Use enumerate in _retrieve_tree method

* [DependencyMatcher] Clean unused vars and use camel_case naming

* [DependencyMatcher] Memoize node+operator map

* Add root property to Token

* [DependencyMatcher] Groups matches by root

* [DependencyMatcher] Remove unused _keys_to_token attribute

* [DependencyMatcher] Use a list to map tokens to matcher's keys

* [DependencyMatcher] Remove recursion

* [DependencyMatcher] Use a generator to retrieve matches

* [DependencyMatcher] Remove unused memory pool

* [DependencyMatcher] Hide private methods and attributes

* [DependencyMatcher] Improvements to the matches validation

* Apply suggestions from code review

Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>

* [DependencyMatcher] Fix keys_to_position_maps

* Remove Token.root property

* [DependencyMatcher] Remove functools' lru_cache

Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
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106
.github/contributors/werew.md vendored Normal file
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@ -0,0 +1,106 @@
# spaCy contributor agreement
This spaCy Contributor Agreement (**"SCA"**) is based on the
[Oracle Contributor Agreement](http://www.oracle.com/technetwork/oca-405177.pdf).
The SCA applies to any contribution that you make to any product or project
managed by us (the **"project"**), and sets out the intellectual property rights
you grant to us in the contributed materials. The term **"us"** shall mean
[ExplosionAI GmbH](https://explosion.ai/legal). The term
**"you"** shall mean the person or entity identified below.
If you agree to be bound by these terms, fill in the information requested
below and include the filled-in version with your first pull request, under the
folder [`.github/contributors/`](/.github/contributors/). The name of the file
should be your GitHub username, with the extension `.md`. For example, the user
example_user would create the file `.github/contributors/example_user.md`.
Read this agreement carefully before signing. These terms and conditions
constitute a binding legal agreement.
## Contributor Agreement
1. The term "contribution" or "contributed materials" means any source code,
object code, patch, tool, sample, graphic, specification, manual,
documentation, or any other material posted or submitted by you to the project.
2. With respect to any worldwide copyrights, or copyright applications and
registrations, in your contribution:
* you hereby assign to us joint ownership, and to the extent that such
assignment is or becomes invalid, ineffective or unenforceable, you hereby
grant to us a perpetual, irrevocable, non-exclusive, worldwide, no-charge,
royalty-free, unrestricted license to exercise all rights under those
copyrights. This includes, at our option, the right to sublicense these same
rights to third parties through multiple levels of sublicensees or other
licensing arrangements;
* you agree that each of us can do all things in relation to your
contribution as if each of us were the sole owners, and if one of us makes
a derivative work of your contribution, the one who makes the derivative
work (or has it made will be the sole owner of that derivative work;
* you agree that you will not assert any moral rights in your contribution
against us, our licensees or transferees;
* you agree that we may register a copyright in your contribution and
exercise all ownership rights associated with it; and
* you agree that neither of us has any duty to consult with, obtain the
consent of, pay or render an accounting to the other for any use or
distribution of your contribution.
3. With respect to any patents you own, or that you can license without payment
to any third party, you hereby grant to us a perpetual, irrevocable,
non-exclusive, worldwide, no-charge, royalty-free license to:
* make, have made, use, sell, offer to sell, import, and otherwise transfer
your contribution in whole or in part, alone or in combination with or
included in any product, work or materials arising out of the project to
which your contribution was submitted, and
* at our option, to sublicense these same rights to third parties through
multiple levels of sublicensees or other licensing arrangements.
4. Except as set out above, you keep all right, title, and interest in your
contribution. The rights that you grant to us under these terms are effective
on the date you first submitted a contribution to us, even if your submission
took place before the date you sign these terms.
5. You covenant, represent, warrant and agree that:
* Each contribution that you submit is and shall be an original work of
authorship and you can legally grant the rights set out in this SCA;
* to the best of your knowledge, each contribution will not violate any
third party's copyrights, trademarks, patents, or other intellectual
property rights; and
* each contribution shall be in compliance with U.S. export control laws and
other applicable export and import laws. You agree to notify us if you
become aware of any circumstance which would make any of the foregoing
representations inaccurate in any respect. We may publicly disclose your
participation in the project, including the fact that you have signed the SCA.
6. This SCA is governed by the laws of the State of California and applicable
U.S. Federal law. Any choice of law rules will not apply.
7. Please place an “x” on one of the applicable statement below. Please do NOT
mark both statements:
* [x] I am signing on behalf of myself as an individual and no other person
or entity, including my employer, has or will have rights with respect to my
contributions.
* [ ] I am signing on behalf of my employer or a legal entity and I have the
actual authority to contractually bind that entity.
## Contributor Details
| Field | Entry |
|------------------------------- | -------------------- |
| Name | Luigi Coniglio |
| Company name (if applicable) | |
| Title or role (if applicable) | |
| Date | 10/01/2021 |
| GitHub username | werew |
| Website (optional) | |

367
spacy/matcher/dependencymatcher.pyx
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@ -1,10 +1,10 @@
# cython: infer_types=True, profile=True
from typing import List
from collections import defaultdict
from itertools import product
import numpy
from cymem.cymem cimport Pool
from .matcher cimport Matcher
from ..vocab cimport Vocab
from ..tokens.doc cimport Doc
@ -20,15 +20,13 @@ INDEX_RELOP = 0
cdef class DependencyMatcher:
"""Match dependency parse tree based on pattern rules."""
cdef Pool mem
cdef readonly Vocab vocab
cdef readonly Matcher matcher
cdef readonly Matcher _matcher
cdef public object _patterns
cdef public object _raw_patterns
cdef public object _keys_to_token
cdef public object _tokens_to_key
cdef public object _root
cdef public object _callbacks
cdef public object _nodes
cdef public object _tree
cdef public object _ops
@ -40,30 +38,50 @@ cdef class DependencyMatcher:
validate (bool): Whether patterns should be validated, passed to
Matcher as `validate`
"""
size = 20
self.matcher = Matcher(vocab, validate=validate)
self._keys_to_token = {}
self._patterns = {}
self._raw_patterns = {}
self._root = {}
self._nodes = {}
self._tree = {}
self._matcher = Matcher(vocab, validate=validate)
# Associates each key to the raw patterns list added by the user
# e.g. {'key': [[{'RIGHT_ID': ..., 'RIGHT_ATTRS': ... }, ... ], ... ], ... }
self._raw_patterns = defaultdict(list)
# Associates each key to a list of lists of 'RIGHT_ATTRS'
# e.g. {'key': [[{'POS': ... }, ... ], ... ], ... }
self._patterns = defaultdict(list)
# Associates each key to a list of lists where each list associates
# a token position within the pattern to the key used by the internal matcher)
# e.g. {'key': [ ['token_key', ... ], ... ], ... }
self._tokens_to_key = defaultdict(list)
# Associates each key to a list of ints where each int corresponds
# to the position of the root token within the pattern
# e.g. {'key': [3, 1, 4, ... ], ... }
self._root = defaultdict(list)
# Associates each key to a list of dicts where each dict describes all
# branches from a token (identifed by its position) to other tokens as
# a list of tuples: ('REL_OP', 'LEFT_ID')
# e.g. {'key': [{2: [('<', 'left_id'), ...] ...}, ... ], ...}
self._tree = defaultdict(list)
# Associates each key to its on_match callback
# e.g. {'key': on_match_callback, ...}
self._callbacks = {}
self.vocab = vocab
self.mem = Pool()
self._ops = {
"<": self.dep,
">": self.gov,
"<<": self.dep_chain,
">>": self.gov_chain,
".": self.imm_precede,
".*": self.precede,
";": self.imm_follow,
";*": self.follow,
"$+": self.imm_right_sib,
"$-": self.imm_left_sib,
"$++": self.right_sib,
"$--": self.left_sib,
"<": self._dep,
">": self._gov,
"<<": self._dep_chain,
">>": self._gov_chain,
".": self._imm_precede,
".*": self._precede,
";": self._imm_follow,
";*": self._follow,
"$+": self._imm_right_sib,
"$-": self._imm_left_sib,
"$++": self._right_sib,
"$--": self._left_sib,
}
def __reduce__(self):
@ -86,7 +104,7 @@ cdef class DependencyMatcher:
"""
return self.has_key(key)
def validate_input(self, pattern, key):
def _validate_input(self, pattern, key):
idx = 0
visited_nodes = {}
for relation in pattern:
@ -121,6 +139,16 @@ cdef class DependencyMatcher:
visited_nodes[relation["LEFT_ID"]] = True
idx = idx + 1
def _get_matcher_key(self, key, pattern_idx, token_idx):
"""
Creates a token key to be used by the matcher
"""
return self._normalize_key(
unicode(key) + DELIMITER +
unicode(pattern_idx) + DELIMITER +
unicode(token_idx)
)
def add(self, key, patterns, *, on_match=None):
"""Add a new matcher rule to the matcher.
@ -135,10 +163,15 @@ cdef class DependencyMatcher:
for pattern in patterns:
if len(pattern) == 0:
raise ValueError(Errors.E012.format(key=key))
self.validate_input(pattern, key)
self._validate_input(pattern, key)
key = self._normalize_key(key)
self._raw_patterns.setdefault(key, [])
# Save raw patterns and on_match callback
self._raw_patterns[key].extend(patterns)
self._callbacks[key] = on_match
# Add 'RIGHT_ATTRS' to self._patterns[key]
_patterns = []
for pattern in patterns:
token_patterns = []
@ -146,69 +179,64 @@ cdef class DependencyMatcher:
token_pattern = [pattern[i]["RIGHT_ATTRS"]]
token_patterns.append(token_pattern)
_patterns.append(token_patterns)
self._patterns.setdefault(key, [])
self._callbacks[key] = on_match
self._patterns[key].extend(_patterns)
# Add each node pattern of all the input patterns individually to the
# matcher. This enables only a single instance of Matcher to be used.
# Multiple adds are required to track each node pattern.
_keys_to_token_list = []
tokens_to_key_list = []
for i in range(len(_patterns)):
_keys_to_token = {}
# Preallocate list space
tokens_to_key = [None]*len(_patterns[i])
# TODO: Better ways to hash edges in pattern?
for j in range(len(_patterns[i])):
k = self._normalize_key(unicode(key) + DELIMITER + unicode(i) + DELIMITER + unicode(j))
self.matcher.add(k, [_patterns[i][j]])
_keys_to_token[k] = j
_keys_to_token_list.append(_keys_to_token)
self._keys_to_token.setdefault(key, [])
self._keys_to_token[key].extend(_keys_to_token_list)
_nodes_list = []
for pattern in patterns:
nodes = {}
for i in range(len(pattern)):
nodes[pattern[i]["RIGHT_ID"]] = i
_nodes_list.append(nodes)
self._nodes.setdefault(key, [])
self._nodes[key].extend(_nodes_list)
k = self._get_matcher_key(key, i, j)
self._matcher.add(k, [_patterns[i][j]])
tokens_to_key[j] = k
tokens_to_key_list.append(tokens_to_key)
self._tokens_to_key[key].extend(tokens_to_key_list)
# Create an object tree to traverse later on. This data structure
# enables easy tree pattern match. Doc-Token based tree cannot be
# reused since it is memory-heavy and tightly coupled with the Doc.
self.retrieve_tree(patterns, _nodes_list, key)
self._retrieve_tree(patterns, key)
def retrieve_tree(self, patterns, _nodes_list, key):
_heads_list = []
_root_list = []
for i in range(len(patterns)):
heads = {}
def _retrieve_tree(self, patterns, key):
# New trees belonging to this key
tree_list = []
# List of indices to the root nodes
root_list = []
# Group token id to create trees
for i, pattern in enumerate(patterns):
tree = defaultdict(list)
root = -1
for j in range(len(patterns[i])):
token_pattern = patterns[i][j]
if ("REL_OP" not in token_pattern):
heads[j] = ('root', j)
root = j
else:
heads[j] = (
token_pattern["REL_OP"],
_nodes_list[i][token_pattern["LEFT_ID"]]
right_id_to_token = {}
for j, token in enumerate(pattern):
right_id_to_token[token["RIGHT_ID"]] = j
for j, token in enumerate(pattern):
if "REL_OP" in token:
# Add tree branch
tree[right_id_to_token[token["LEFT_ID"]]].append(
(token["REL_OP"], j),
)
_heads_list.append(heads)
_root_list.append(root)
_tree_list = []
for i in range(len(patterns)):
tree = {}
for j in range(len(patterns[i])):
if(_heads_list[i][j][INDEX_HEAD] == j):
continue
head = _heads_list[i][j][INDEX_HEAD]
if(head not in tree):
tree[head] = []
tree[head].append((_heads_list[i][j][INDEX_RELOP], j))
_tree_list.append(tree)
self._tree.setdefault(key, [])
self._tree[key].extend(_tree_list)
self._root.setdefault(key, [])
self._root[key].extend(_root_list)
else:
# No 'REL_OP', this is the root
root = j
tree_list.append(tree)
root_list.append(root)
self._tree[key].extend(tree_list)
self._root[key].extend(root_list)
def has_key(self, key):
"""Check whether the matcher has a rule with a given key.
@ -235,9 +263,25 @@ cdef class DependencyMatcher:
raise ValueError(Errors.E175.format(key=key))
self._patterns.pop(key)
self._raw_patterns.pop(key)
self._nodes.pop(key)
self._tree.pop(key)
self._root.pop(key)
self._tokens_to_key.pop(key)
def _get_keys_to_position_maps(self, doc):
"""
Processes the doc and groups all matches by their root and match id.
Returns a dict mapping each (root, match id) pair to the list of
tokens indices which are descendants of root and match the token
pattern identified by the given match id.
e.g. keys_to_position_maps[root_index][match_id] = [...]
"""
keys_to_position_maps = defaultdict(lambda: defaultdict(list))
for match_id, start, _ in self._matcher(doc):
token = doc[start]
root = ([token] + list(token.ancestors))[-1]
keys_to_position_maps[root.i][match_id].append(start)
return keys_to_position_maps
def __call__(self, object doclike):
"""Find all token sequences matching the supplied pattern.
@ -253,146 +297,131 @@ cdef class DependencyMatcher:
doc = doclike.as_doc()
else:
raise ValueError(Errors.E195.format(good="Doc or Span", got=type(doclike).__name__))
matched_key_trees = []
matches = self.matcher(doc)
for key in list(self._patterns.keys()):
_patterns_list = self._patterns[key]
_keys_to_token_list = self._keys_to_token[key]
_root_list = self._root[key]
_tree_list = self._tree[key]
_nodes_list = self._nodes[key]
length = len(_patterns_list)
for i in range(length):
_keys_to_token = _keys_to_token_list[i]
_root = _root_list[i]
_tree = _tree_list[i]
_nodes = _nodes_list[i]
id_to_position = {}
for i in range(len(_nodes)):
id_to_position[i]=[]
# TODO: This could be taken outside to improve running time..?
for match_id, start, end in matches:
if match_id in _keys_to_token:
id_to_position[_keys_to_token[match_id]].append(start)
_node_operator_map = self.get_node_operator_map(
doc,
_tree,
id_to_position,
_nodes,_root
)
length = len(_nodes)
matched_trees = []
self.recurse(_tree, id_to_position, _node_operator_map, 0, [], matched_trees)
for matched_tree in matched_trees:
matched_key_trees = []
keys_to_position_maps = self._get_keys_to_position_maps(doc)
cache = {}
for key in self._patterns.keys():
for root, tree, tokens_to_key in zip(
self._root[key],
self._tree[key],
self._tokens_to_key[key],
):
for keys_to_position in keys_to_position_maps.values():
for matched_tree in self._get_matches(cache, doc, tree, tokens_to_key, keys_to_position):
matched_key_trees.append((key, matched_tree))
for i, (match_id, nodes) in enumerate(matched_key_trees):
on_match = self._callbacks.get(match_id)
if on_match is not None:
on_match(self, doc, i, matched_key_trees)
return matched_key_trees
def recurse(self, tree, id_to_position, _node_operator_map, int patternLength, visited_nodes, matched_trees):
cdef bint isValid;
if patternLength == len(id_to_position.keys()):
isValid = True
for node in range(patternLength):
if node in tree:
for idx, (relop,nbor) in enumerate(tree[node]):
computed_nbors = numpy.asarray(_node_operator_map[visited_nodes[node]][relop])
isNbor = False
for computed_nbor in computed_nbors:
if computed_nbor.i == visited_nodes[nbor]:
isNbor = True
isValid = isValid & isNbor
if(isValid):
matched_trees.append(visited_nodes)
return
allPatternNodes = numpy.asarray(id_to_position[patternLength])
for patternNode in allPatternNodes:
self.recurse(tree, id_to_position, _node_operator_map, patternLength+1, visited_nodes+[patternNode], matched_trees)
def _get_matches(self, cache, doc, tree, tokens_to_key, keys_to_position):
cdef bint is_valid
# Given a node and an edge operator, to return the list of nodes
# from the doc that belong to node+operator. This is used to store
# all the results beforehand to prevent unnecessary computation while
# pattern matching
# _node_operator_map[node][operator] = [...]
def get_node_operator_map(self, doc, tree, id_to_position, nodes, root):
_node_operator_map = {}
all_node_indices = nodes.values()
all_operators = []
for node in all_node_indices:
if node in tree:
for child in tree[node]:
all_operators.append(child[INDEX_RELOP])
all_operators = list(set(all_operators))
all_nodes = []
for node in all_node_indices:
all_nodes = all_nodes + id_to_position[node]
all_nodes = list(set(all_nodes))
for node in all_nodes:
_node_operator_map[node] = {}
for operator in all_operators:
_node_operator_map[node][operator] = []
for operator in all_operators:
for node in all_nodes:
_node_operator_map[node][operator] = self._ops.get(operator)(doc, node)
return _node_operator_map
all_positions = [keys_to_position[key] for key in tokens_to_key]
def dep(self, doc, node):
# Generate all potential matches by computing the cartesian product of all
# position of the matched tokens
for candidate_match in product(*all_positions):
# A potential match is a valid match if all relationhips between the
# matched tokens are satisfied.
is_valid = True
for left_idx in range(len(candidate_match)):
is_valid = self._check_relationships(cache, doc, candidate_match, left_idx, tree)
if not is_valid:
break
if is_valid:
yield list(candidate_match)
def _check_relationships(self, cache, doc, candidate_match, left_idx, tree):
# Position of the left operand within the document
left_pos = candidate_match[left_idx]
for relop, right_idx in tree[left_idx]:
# Position of the left operand within the document
right_pos = candidate_match[right_idx]
# List of valid right matches
valid_right_matches = self._resolve_node_operator(cache, doc, left_pos, relop)
# If the proposed right token is not within the valid ones, fail
if right_pos not in valid_right_matches:
return False
return True
def _resolve_node_operator(self, cache, doc, node, operator):
"""
Given a doc, a node (as a index in the doc) and a REL_OP operator
returns the list of nodes from the doc that belong to node+operator.
"""
key = (node, operator)
if key not in cache:
cache[key] = [token.i for token in self._ops[operator](doc, node)]
return cache[key]
def _dep(self, doc, node):
if doc[node].head == doc[node]:
return []
return [doc[node].head]
def gov(self,doc,node):
def _gov(self,doc,node):
return list(doc[node].children)
def dep_chain(self, doc, node):
def _dep_chain(self, doc, node):
return list(doc[node].ancestors)
def gov_chain(self, doc, node):
def _gov_chain(self, doc, node):
return [t for t in doc[node].subtree if t != doc[node]]
def imm_precede(self, doc, node):
def _imm_precede(self, doc, node):
sent = self._get_sent(doc[node])
if node < len(doc) - 1 and doc[node + 1] in sent:
return [doc[node + 1]]
return []
def precede(self, doc, node):
def _precede(self, doc, node):
sent = self._get_sent(doc[node])
return [doc[i] for i in range(node + 1, sent.end)]
def imm_follow(self, doc, node):
def _imm_follow(self, doc, node):
sent = self._get_sent(doc[node])
if node > 0 and doc[node - 1] in sent:
return [doc[node - 1]]
return []
def follow(self, doc, node):
def _follow(self, doc, node):
sent = self._get_sent(doc[node])
return [doc[i] for i in range(sent.start, node)]
def imm_right_sib(self, doc, node):
def _imm_right_sib(self, doc, node):
for child in list(doc[node].head.children):
if child.i == node + 1:
return [doc[child.i]]
return []
def imm_left_sib(self, doc, node):
def _imm_left_sib(self, doc, node):
for child in list(doc[node].head.children):
if child.i == node - 1:
return [doc[child.i]]
return []
def right_sib(self, doc, node):
def _right_sib(self, doc, node):
candidate_children = []
for child in list(doc[node].head.children):
if child.i > node:
candidate_children.append(doc[child.i])
return candidate_children
def left_sib(self, doc, node):
def _left_sib(self, doc, node):
candidate_children = []
for child in list(doc[node].head.children):
if child.i < node:

3
spacy/tokens/token.pyx
View File

@ -680,9 +680,8 @@ cdef class Token:
# Find the widest l/r_edges of the roots of the two tokens involved
# to limit the number of tokens for set_children_from_heads
cdef Token self_root, new_head_root
self_ancestors = list(self.ancestors)
self_root = ([self] + list(self.ancestors))[-1]
new_head_ancestors = list(new_head.ancestors)
self_root = self_ancestors[-1] if self_ancestors else self
new_head_root = new_head_ancestors[-1] if new_head_ancestors else new_head
start = self_root.c.l_edge if self_root.c.l_edge < new_head_root.c.l_edge else new_head_root.c.l_edge
end = self_root.c.r_edge if self_root.c.r_edge > new_head_root.c.r_edge else new_head_root.c.r_edge