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Fix kb/kb_in_memory.pyx.

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This commit is contained in:
Raphael Mitsch 2023-07-03 10:02:40 +02:00
parent 6c483971b7
commit a0bf50661b
1 changed files with 107 additions and 47 deletions
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148
spacy/kb/kb_in_memory.pyx
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@ -1,5 +1,5 @@
# cython: infer_types=True, profile=True
from typing import Any, Callable, Dict, Iterable, Union
from typing import Any, Callable, Dict, Iterable
import srsly
@ -27,8 +27,9 @@ from .candidate import Candidate as Candidate
cdef class InMemoryLookupKB(KnowledgeBase):
"""An `InMemoryLookupKB` instance stores unique identifiers for entities and their textual aliases,
to support entity linking of named entities to real-world concepts.
"""An `InMemoryLookupKB` instance stores unique identifiers for entities
and their textual aliases, to support entity linking of named entities to
real-world concepts.
DOCS: https://spacy.io/api/inmemorylookupkb
"""
@ -71,7 +72,8 @@ cdef class InMemoryLookupKB(KnowledgeBase):
def add_entity(self, str entity, float freq, vector[float] entity_vector):
"""
Add an entity to the KB, optionally specifying its log probability based on corpus frequency
Add an entity to the KB, optionally specifying its log probability
based on corpus frequency.
Return the hash of the entity ID/name at the end.
"""
cdef hash_t entity_hash = self.vocab.strings.add(entity)
@ -83,14 +85,20 @@ cdef class InMemoryLookupKB(KnowledgeBase):
# Raise an error if the provided entity vector is not of the correct length
if len(entity_vector) != self.entity_vector_length:
raise ValueError(Errors.E141.format(found=len(entity_vector), required=self.entity_vector_length))
raise ValueError(
Errors.E141.format(
found=len(entity_vector), required=self.entity_vector_length
)
)
vector_index = self.c_add_vector(entity_vector=entity_vector)
new_index = self.c_add_entity(entity_hash=entity_hash,
new_index = self.c_add_entity(
entity_hash=entity_hash,
freq=freq,
vector_index=vector_index,
feats_row=-1) # Features table currently not implemented
feats_row=-1
) # Features table currently not implemented
self._entry_index[entity_hash] = new_index
return entity_hash
@ -115,7 +123,12 @@ cdef class InMemoryLookupKB(KnowledgeBase):
else:
entity_vector = vector_list[i]
if len(entity_vector) != self.entity_vector_length:
raise ValueError(Errors.E141.format(found=len(entity_vector), required=self.entity_vector_length))
raise ValueError(
Errors.E141.format(
found=len(entity_vector),
required=self.entity_vector_length
)
)
entry.entity_hash = entity_hash
entry.freq = freq_list[i]
@ -149,11 +162,15 @@ cdef class InMemoryLookupKB(KnowledgeBase):
previous_alias_nr = self.get_size_aliases()
# Throw an error if the length of entities and probabilities are not the same
if not len(entities) == len(probabilities):
raise ValueError(Errors.E132.format(alias=alias,
raise ValueError(
Errors.E132.format(
alias=alias,
entities_length=len(entities),
probabilities_length=len(probabilities)))
probabilities_length=len(probabilities))
)
# Throw an error if the probabilities sum up to more than 1 (allow for some rounding errors)
# Throw an error if the probabilities sum up to more than 1 (allow for
# some rounding errors)
prob_sum = sum(probabilities)
if prob_sum > 1.00001:
raise ValueError(Errors.E133.format(alias=alias, sum=prob_sum))
@ -170,40 +187,47 @@ cdef class InMemoryLookupKB(KnowledgeBase):
for entity, prob in zip(entities, probabilities):
entity_hash = self.vocab.strings[entity]
if not entity_hash in self._entry_index:
if entity_hash not in self._entry_index:
raise ValueError(Errors.E134.format(entity=entity))
entry_index = <int64_t>self._entry_index.get(entity_hash)
entry_indices.push_back(int(entry_index))
probs.push_back(float(prob))
new_index = self.c_add_aliases(alias_hash=alias_hash, entry_indices=entry_indices, probs=probs)
new_index = self.c_add_aliases(
alias_hash=alias_hash, entry_indices=entry_indices, probs=probs
)
self._alias_index[alias_hash] = new_index
if previous_alias_nr + 1 != self.get_size_aliases():
raise RuntimeError(Errors.E891.format(alias=alias))
return alias_hash
def append_alias(self, str alias, str entity, float prior_prob, ignore_warnings=False):
def append_alias(
self, str alias, str entity, float prior_prob, ignore_warnings=False
):
"""
For an alias already existing in the KB, extend its potential entities with one more.
For an alias already existing in the KB, extend its potential entities
with one more.
Throw a warning if either the alias or the entity is unknown,
or when the combination is already previously recorded.
Throw an error if this entity+prior prob would exceed the sum of 1.
For efficiency, it's best to use the method `add_alias` as much as possible instead of this one.
For efficiency, it's best to use the method `add_alias` as much as
possible instead of this one.
"""
# Check if the alias exists in the KB
cdef hash_t alias_hash = self.vocab.strings[alias]
if not alias_hash in self._alias_index:
if alias_hash not in self._alias_index:
raise ValueError(Errors.E176.format(alias=alias))
# Check if the entity exists in the KB
cdef hash_t entity_hash = self.vocab.strings[entity]
if not entity_hash in self._entry_index:
if entity_hash not in self._entry_index:
raise ValueError(Errors.E134.format(entity=entity))
entry_index = <int64_t>self._entry_index.get(entity_hash)
# Throw an error if the prior probabilities (including the new one) sum up to more than 1
# Throw an error if the prior probabilities (including the new one)
# sum up to more than 1
alias_index = <int64_t>self._alias_index.get(alias_hash)
alias_entry = self._aliases_table[alias_index]
current_sum = sum([p for p in alias_entry.probs])
@ -236,12 +260,13 @@ cdef class InMemoryLookupKB(KnowledgeBase):
def get_alias_candidates(self, str alias) -> Iterable[Candidate]:
"""
Return candidate entities for an alias. Each candidate defines the entity, the original alias,
and the prior probability of that alias resolving to that entity.
Return candidate entities for an alias. Each candidate defines the
entity, the original alias, and the prior probability of that alias
resolving to that entity.
If the alias is not known in the KB, and empty list is returned.
"""
cdef hash_t alias_hash = self.vocab.strings[alias]
if not alias_hash in self._alias_index:
if alias_hash not in self._alias_index:
return []
alias_index = <int64_t>self._alias_index.get(alias_hash)
alias_entry = self._aliases_table[alias_index]
@ -249,10 +274,14 @@ cdef class InMemoryLookupKB(KnowledgeBase):
return [Candidate(kb=self,
entity_hash=self._entries[entry_index].entity_hash,
entity_freq=self._entries[entry_index].freq,
entity_vector=self._vectors_table[self._entries[entry_index].vector_index],
entity_vector=self._vectors_table[
self._entries[entry_index].vector_index
],
alias_hash=alias_hash,
prior_prob=prior_prob)
for (entry_index, prior_prob) in zip(alias_entry.entry_indices, alias_entry.probs)
for (entry_index, prior_prob) in zip(
alias_entry.entry_indices, alias_entry.probs
)
if entry_index != 0]
def get_vector(self, str entity):
@ -266,8 +295,9 @@ cdef class InMemoryLookupKB(KnowledgeBase):
return self._vectors_table[self._entries[entry_index].vector_index]
def get_prior_prob(self, str entity, str alias):
""" Return the prior probability of a given alias being linked to a given entity,
or return 0.0 when this combination is not known in the knowledge base"""
""" Return the prior probability of a given alias being linked to a
given entity, or return 0.0 when this combination is not known in the
knowledge base."""
cdef hash_t alias_hash = self.vocab.strings[alias]
cdef hash_t entity_hash = self.vocab.strings[entity]
@ -278,7 +308,9 @@ cdef class InMemoryLookupKB(KnowledgeBase):
entry_index = self._entry_index[entity_hash]
alias_entry = self._aliases_table[alias_index]
for (entry_index, prior_prob) in zip(alias_entry.entry_indices, alias_entry.probs):
for (entry_index, prior_prob) in zip(
alias_entry.entry_indices, alias_entry.probs
):
if self._entries[entry_index].entity_hash == entity_hash:
return prior_prob
@ -288,13 +320,19 @@ cdef class InMemoryLookupKB(KnowledgeBase):
"""Serialize the current state to a binary string.
"""
def serialize_header():
header = (self.get_size_entities(), self.get_size_aliases(), self.entity_vector_length)
header = (
self.get_size_entities(),
self.get_size_aliases(),
self.entity_vector_length
)
return srsly.json_dumps(header)
def serialize_entries():
i = 1
tuples = []
for entry_hash, entry_index in sorted(self._entry_index.items(), key=lambda x: x[1]):
for entry_hash, entry_index in sorted(
self._entry_index.items(), key=lambda x: x[1]
):
entry = self._entries[entry_index]
assert entry.entity_hash == entry_hash
assert entry_index == i
@ -307,7 +345,9 @@ cdef class InMemoryLookupKB(KnowledgeBase):
headers = []
indices_lists = []
probs_lists = []
for alias_hash, alias_index in sorted(self._alias_index.items(), key=lambda x: x[1]):
for alias_hash, alias_index in sorted(
self._alias_index.items(), key=lambda x: x[1]
):
alias = self._aliases_table[alias_index]
assert alias_index == i
candidate_length = len(alias.entry_indices)
@ -365,7 +405,7 @@ cdef class InMemoryLookupKB(KnowledgeBase):
indices = srsly.json_loads(all_data[1])
probs = srsly.json_loads(all_data[2])
for header, indices, probs in zip(headers, indices, probs):
alias_hash, candidate_length = header
alias_hash, _candidate_length = header
alias.entry_indices = indices
alias.probs = probs
self._aliases_table[i] = alias
@ -414,10 +454,14 @@ cdef class InMemoryLookupKB(KnowledgeBase):
writer.write_vector_element(element)
i = i+1
# dumping the entry records in the order in which they are in the _entries vector.
# index 0 is a dummy object not stored in the _entry_index and can be ignored.
# dumping the entry records in the order in which they are in the
# _entries vector.
# index 0 is a dummy object not stored in the _entry_index and can
# be ignored.
i = 1
for entry_hash, entry_index in sorted(self._entry_index.items(), key=lambda x: x[1]):
for entry_hash, entry_index in sorted(
self._entry_index.items(), key=lambda x: x[1]
):
entry = self._entries[entry_index]
assert entry.entity_hash == entry_hash
assert entry_index == i
@ -429,7 +473,9 @@ cdef class InMemoryLookupKB(KnowledgeBase):
# dumping the aliases in the order in which they are in the _alias_index vector.
# index 0 is a dummy object not stored in the _aliases_table and can be ignored.
i = 1
for alias_hash, alias_index in sorted(self._alias_index.items(), key=lambda x: x[1]):
for alias_hash, alias_index in sorted(
self._alias_index.items(), key=lambda x: x[1]
):
alias = self._aliases_table[alias_index]
assert alias_index == i
@ -535,7 +581,8 @@ cdef class Writer:
def __init__(self, path):
assert isinstance(path, Path)
content = bytes(path)
cdef bytes bytes_loc = content.encode('utf8') if type(content) == str else content
cdef bytes bytes_loc = content.encode('utf8') \
if type(content) == str else content
self._fp = fopen(<char*>bytes_loc, 'wb')
if not self._fp:
raise IOError(Errors.E146.format(path=path))
@ -545,14 +592,18 @@ cdef class Writer:
cdef size_t status = fclose(self._fp)
assert status == 0
cdef int write_header(self, int64_t nr_entries, int64_t entity_vector_length) except -1:
cdef int write_header(
self, int64_t nr_entries, int64_t entity_vector_length
) except -1:
self._write(&nr_entries, sizeof(nr_entries))
self._write(&entity_vector_length, sizeof(entity_vector_length))
cdef int write_vector_element(self, float element) except -1:
self._write(&element, sizeof(element))
cdef int write_entry(self, hash_t entry_hash, float entry_freq, int32_t vector_index) except -1:
cdef int write_entry(
self, hash_t entry_hash, float entry_freq, int32_t vector_index
) except -1:
self._write(&entry_hash, sizeof(entry_hash))
self._write(&entry_freq, sizeof(entry_freq))
self._write(&vector_index, sizeof(vector_index))
@ -561,7 +612,9 @@ cdef class Writer:
cdef int write_alias_length(self, int64_t alias_length) except -1:
self._write(&alias_length, sizeof(alias_length))
cdef int write_alias_header(self, hash_t alias_hash, int64_t candidate_length) except -1:
cdef int write_alias_header(
self, hash_t alias_hash, int64_t candidate_length
) except -1:
self._write(&alias_hash, sizeof(alias_hash))
self._write(&candidate_length, sizeof(candidate_length))
@ -577,16 +630,19 @@ cdef class Writer:
cdef class Reader:
def __init__(self, path):
content = bytes(path)
cdef bytes bytes_loc = content.encode('utf8') if type(content) == str else content
cdef bytes bytes_loc = content.encode('utf8') \
if type(content) == str else content
self._fp = fopen(<char*>bytes_loc, 'rb')
if not self._fp:
PyErr_SetFromErrno(IOError)
status = fseek(self._fp, 0, 0) # this can be 0 if there is no header
fseek(self._fp, 0, 0) # this can be 0 if there is no header
def __dealloc__(self):
fclose(self._fp)
cdef int read_header(self, int64_t* nr_entries, int64_t* entity_vector_length) except -1:
cdef int read_header(
self, int64_t* nr_entries, int64_t* entity_vector_length
) except -1:
status = self._read(nr_entries, sizeof(int64_t))
if status < 1:
if feof(self._fp):
@ -606,7 +662,9 @@ cdef class Reader:
return 0 # end of file
raise IOError(Errors.E145.format(param="vector element"))
cdef int read_entry(self, hash_t* entity_hash, float* freq, int32_t* vector_index) except -1:
cdef int read_entry(
self, hash_t* entity_hash, float* freq, int32_t* vector_index
) except -1:
status = self._read(entity_hash, sizeof(hash_t))
if status < 1:
if feof(self._fp):
@ -637,7 +695,9 @@ cdef class Reader:
return 0 # end of file
raise IOError(Errors.E145.format(param="alias length"))
cdef int read_alias_header(self, hash_t* alias_hash, int64_t* candidate_length) except -1:
cdef int read_alias_header(
self, hash_t* alias_hash, int64_t* candidate_length
) except -1:
status = self._read(alias_hash, sizeof(hash_t))
if status < 1:
if feof(self._fp):