From b0228d8ea6f7cce9583c747fb84d9be8ae9a753e Mon Sep 17 00:00:00 2001 From: Basile Dura Date: Wed, 19 Jul 2023 12:03:31 +0200 Subject: [PATCH] ci: add cython linter (#12694) * chore: add cython-linter dev dependency * fix: lexeme.pyx * fix: morphology.pxd * fix: tokenizer.pxd * fix: vocab.pxd * fix: morphology.pxd (line length) * ci: add cython-lint * ci: fix cython-lint call * Fix kb/candidate.pyx. * Fix kb/kb.pyx. * Fix kb/kb_in_memory.pyx. * Fix kb. * Fix training/ partially. * Fix training/. Ignore trailing whitespaces and too long lines. * Fix ml/. * Fix matcher/. * Fix pipeline/. * Fix tokens/. * Fix build errors. Fix vocab.pyx. * Fix cython-lint install and run. * Fix lexeme.pyx, parts_of_speech.pxd, vectors.pyx. Temporarily disable cython-lint execution. * Fix attrs.pyx, lexeme.pyx, symbols.pxd, isort issues. * Make cython-lint install conditional. Fix tokenizer.pyx. * Fix remaining files. Reenable cython-lint check. * Readded parentheses. * Fix test_build_dependencies(). * Add explanatory comment to cython-lint execution. --------- Co-authored-by: Raphael Mitsch --- .github/workflows/tests.yml | 6 + requirements.txt | 1 + spacy/attrs.pxd | 2 +- spacy/attrs.pyx | 2 +- spacy/kb/candidate.pxd | 3 +- spacy/kb/candidate.pyx | 27 +- spacy/kb/kb.pyx | 49 +++- spacy/kb/kb_in_memory.pxd | 62 +++-- spacy/kb/kb_in_memory.pyx | 154 +++++++---- spacy/lexeme.pyx | 17 +- spacy/matcher/dependencymatcher.pyx | 10 +- spacy/matcher/matcher.pyx | 246 +++++++++++------- spacy/matcher/phrasematcher.pyx | 4 +- spacy/ml/parser_model.pxd | 17 +- spacy/ml/parser_model.pyx | 129 +++++---- spacy/morphology.pxd | 8 +- spacy/morphology.pyx | 10 +- spacy/parts_of_speech.pxd | 2 +- .../_edit_tree_internals/edit_trees.pxd | 17 +- .../_edit_tree_internals/edit_trees.pyx | 14 +- .../_parser_internals/_beam_utils.pyx | 6 +- spacy/pipeline/_parser_internals/_state.pxd | 1 - .../pipeline/_parser_internals/arc_eager.pyx | 18 +- spacy/pipeline/_parser_internals/ner.pyx | 17 +- spacy/pipeline/_parser_internals/nonproj.pyx | 12 +- .../pipeline/_parser_internals/stateclass.pyx | 24 +- .../_parser_internals/transition_system.pxd | 14 +- .../_parser_internals/transition_system.pyx | 3 - spacy/pipeline/dep_parser.pyx | 3 +- spacy/pipeline/morphologizer.pyx | 11 +- spacy/pipeline/multitask.pyx | 9 +- spacy/pipeline/ner.pyx | 5 +- spacy/pipeline/pipe.pyx | 6 +- spacy/pipeline/sentencizer.pyx | 28 +- spacy/pipeline/senter.pyx | 1 - spacy/pipeline/tagger.pyx | 11 +- spacy/pipeline/trainable_pipe.pyx | 14 +- spacy/pipeline/transition_parser.pxd | 18 +- spacy/pipeline/transition_parser.pyx | 64 ++--- spacy/strings.pyx | 5 +- spacy/structs.pxd | 2 +- spacy/symbols.pxd | 8 +- spacy/symbols.pyx | 8 +- spacy/tests/package/test_requirements.py | 1 + spacy/tokenizer.pxd | 76 ++++-- spacy/tokenizer.pyx | 37 ++- spacy/tokens/_retokenize.pyx | 27 +- spacy/tokens/doc.pxd | 3 +- spacy/tokens/doc.pyx | 32 +-- spacy/tokens/graph.pyx | 53 ++-- spacy/tokens/morphanalysis.pyx | 1 - spacy/tokens/span.pyx | 9 +- spacy/tokens/span_group.pyx | 6 +- spacy/tokens/token.pxd | 4 +- spacy/tokens/token.pyx | 8 +- spacy/training/align.pyx | 12 +- spacy/training/example.pyx | 15 +- spacy/training/gold_io.pyx | 31 ++- spacy/vectors.pyx | 32 +-- spacy/vocab.pxd | 2 +- spacy/vocab.pyx | 23 +- 61 files changed, 846 insertions(+), 594 deletions(-) diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index d60c90c1c..4099b31e2 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -45,6 +45,12 @@ jobs: run: | python -m pip install flake8==5.0.4 python -m flake8 spacy --count --select=E901,E999,F821,F822,F823,W605 --show-source --statistics + - name: cython-lint + run: | + python -m pip install cython-lint -c requirements.txt + # E501: line too log, W291: trailing whitespace, E266: too many leading '#' for block comment + cython-lint spacy --ignore E501,W291,E266 + tests: name: Test needs: Validate diff --git a/requirements.txt b/requirements.txt index a007f495e..4a131d18c 100644 --- a/requirements.txt +++ b/requirements.txt @@ -38,4 +38,5 @@ types-setuptools>=57.0.0 types-requests types-setuptools>=57.0.0 black==22.3.0 +cython-lint>=0.15.0; python_version >= "3.7" isort>=5.0,<6.0 diff --git a/spacy/attrs.pxd b/spacy/attrs.pxd index 6dc9ecaee..fbbac0ec2 100644 --- a/spacy/attrs.pxd +++ b/spacy/attrs.pxd @@ -96,4 +96,4 @@ cdef enum attr_id_t: ENT_ID = symbols.ENT_ID IDX - SENT_END \ No newline at end of file + SENT_END diff --git a/spacy/attrs.pyx b/spacy/attrs.pyx index dc8eed7c3..97b5d5e36 100644 --- a/spacy/attrs.pyx +++ b/spacy/attrs.pyx @@ -117,7 +117,7 @@ def intify_attrs(stringy_attrs, strings_map=None, _do_deprecated=False): if "pos" in stringy_attrs: stringy_attrs["TAG"] = stringy_attrs.pop("pos") if "morph" in stringy_attrs: - morphs = stringy_attrs.pop("morph") + morphs = stringy_attrs.pop("morph") # no-cython-lint if "number" in stringy_attrs: stringy_attrs.pop("number") if "tenspect" in stringy_attrs: diff --git a/spacy/kb/candidate.pxd b/spacy/kb/candidate.pxd index 9fc4c4e9d..80fcbc459 100644 --- a/spacy/kb/candidate.pxd +++ b/spacy/kb/candidate.pxd @@ -4,7 +4,8 @@ from ..typedefs cimport hash_t from .kb cimport KnowledgeBase -# Object used by the Entity Linker that summarizes one entity-alias candidate combination. +# Object used by the Entity Linker that summarizes one entity-alias candidate +# combination. cdef class Candidate: cdef readonly KnowledgeBase kb cdef hash_t entity_hash diff --git a/spacy/kb/candidate.pyx b/spacy/kb/candidate.pyx index 4cd734f43..53fc9b036 100644 --- a/spacy/kb/candidate.pyx +++ b/spacy/kb/candidate.pyx @@ -8,15 +8,24 @@ from ..tokens import Span cdef class Candidate: - """A `Candidate` object refers to a textual mention (`alias`) that may or may not be resolved - to a specific `entity` from a Knowledge Base. This will be used as input for the entity linking - algorithm which will disambiguate the various candidates to the correct one. + """A `Candidate` object refers to a textual mention (`alias`) that may or + may not be resolved to a specific `entity` from a Knowledge Base. This + will be used as input for the entity linking algorithm which will + disambiguate the various candidates to the correct one. Each candidate (alias, entity) pair is assigned a certain prior probability. DOCS: https://spacy.io/api/kb/#candidate-init """ - def __init__(self, KnowledgeBase kb, entity_hash, entity_freq, entity_vector, alias_hash, prior_prob): + def __init__( + self, + KnowledgeBase kb, + entity_hash, + entity_freq, + entity_vector, + alias_hash, + prior_prob + ): self.kb = kb self.entity_hash = entity_hash self.entity_freq = entity_freq @@ -59,7 +68,8 @@ cdef class Candidate: def get_candidates(kb: KnowledgeBase, mention: Span) -> Iterable[Candidate]: """ - Return candidate entities for a given mention and fetching appropriate entries from the index. + Return candidate entities for a given mention and fetching appropriate + entries from the index. kb (KnowledgeBase): Knowledge base to query. mention (Span): Entity mention for which to identify candidates. RETURNS (Iterable[Candidate]): Identified candidates. @@ -67,9 +77,12 @@ def get_candidates(kb: KnowledgeBase, mention: Span) -> Iterable[Candidate]: return kb.get_candidates(mention) -def get_candidates_batch(kb: KnowledgeBase, mentions: Iterable[Span]) -> Iterable[Iterable[Candidate]]: +def get_candidates_batch( + kb: KnowledgeBase, mentions: Iterable[Span] +) -> Iterable[Iterable[Candidate]]: """ - Return candidate entities for the given mentions and fetching appropriate entries from the index. + Return candidate entities for the given mentions and fetching appropriate entries + from the index. kb (KnowledgeBase): Knowledge base to query. mention (Iterable[Span]): Entity mentions for which to identify candidates. RETURNS (Iterable[Iterable[Candidate]]): Identified candidates. diff --git a/spacy/kb/kb.pyx b/spacy/kb/kb.pyx index a88e18e1f..6ad4c3564 100644 --- a/spacy/kb/kb.pyx +++ b/spacy/kb/kb.pyx @@ -12,8 +12,9 @@ from .candidate import Candidate cdef class KnowledgeBase: - """A `KnowledgeBase` instance stores unique identifiers for entities and their textual aliases, - to support entity linking of named entities to real-world concepts. + """A `KnowledgeBase` instance stores unique identifiers for entities and + their textual aliases, to support entity linking of named entities to + real-world concepts. This is an abstract class and requires its operations to be implemented. DOCS: https://spacy.io/api/kb @@ -31,10 +32,13 @@ cdef class KnowledgeBase: self.entity_vector_length = entity_vector_length self.mem = Pool() - def get_candidates_batch(self, mentions: Iterable[Span]) -> Iterable[Iterable[Candidate]]: + def get_candidates_batch( + self, mentions: Iterable[Span] + ) -> Iterable[Iterable[Candidate]]: """ - Return candidate entities for specified texts. Each candidate defines the entity, the original alias, - and the prior probability of that alias resolving to that entity. + Return candidate entities for specified texts. Each candidate defines + the entity, the original alias, and the prior probability of that + alias resolving to that entity. If no candidate is found for a given text, an empty list is returned. mentions (Iterable[Span]): Mentions for which to get candidates. RETURNS (Iterable[Iterable[Candidate]]): Identified candidates. @@ -43,14 +47,17 @@ cdef class KnowledgeBase: def get_candidates(self, mention: Span) -> Iterable[Candidate]: """ - Return candidate entities for specified text. Each candidate defines the entity, the original alias, + Return candidate entities for specified text. Each candidate defines + the entity, the original alias, and the prior probability of that alias resolving to that entity. If the no candidate is found for a given text, an empty list is returned. mention (Span): Mention for which to get candidates. RETURNS (Iterable[Candidate]): Identified candidates. """ raise NotImplementedError( - Errors.E1045.format(parent="KnowledgeBase", method="get_candidates", name=self.__name__) + Errors.E1045.format( + parent="KnowledgeBase", method="get_candidates", name=self.__name__ + ) ) def get_vectors(self, entities: Iterable[str]) -> Iterable[Iterable[float]]: @@ -68,7 +75,9 @@ cdef class KnowledgeBase: RETURNS (Iterable[float]): Vector for specified entity. """ raise NotImplementedError( - Errors.E1045.format(parent="KnowledgeBase", method="get_vector", name=self.__name__) + Errors.E1045.format( + parent="KnowledgeBase", method="get_vector", name=self.__name__ + ) ) def to_bytes(self, **kwargs) -> bytes: @@ -76,7 +85,9 @@ cdef class KnowledgeBase: RETURNS (bytes): Current state as binary string. """ raise NotImplementedError( - Errors.E1045.format(parent="KnowledgeBase", method="to_bytes", name=self.__name__) + Errors.E1045.format( + parent="KnowledgeBase", method="to_bytes", name=self.__name__ + ) ) def from_bytes(self, bytes_data: bytes, *, exclude: Tuple[str] = tuple()): @@ -85,25 +96,35 @@ cdef class KnowledgeBase: exclude (Tuple[str]): Properties to exclude when restoring KB. """ raise NotImplementedError( - Errors.E1045.format(parent="KnowledgeBase", method="from_bytes", name=self.__name__) + Errors.E1045.format( + parent="KnowledgeBase", method="from_bytes", name=self.__name__ + ) ) - def to_disk(self, path: Union[str, Path], exclude: Iterable[str] = SimpleFrozenList()) -> None: + def to_disk( + self, path: Union[str, Path], exclude: Iterable[str] = SimpleFrozenList() + ) -> None: """ Write KnowledgeBase content to disk. path (Union[str, Path]): Target file path. exclude (Iterable[str]): List of components to exclude. """ raise NotImplementedError( - Errors.E1045.format(parent="KnowledgeBase", method="to_disk", name=self.__name__) + Errors.E1045.format( + parent="KnowledgeBase", method="to_disk", name=self.__name__ + ) ) - def from_disk(self, path: Union[str, Path], exclude: Iterable[str] = SimpleFrozenList()) -> None: + def from_disk( + self, path: Union[str, Path], exclude: Iterable[str] = SimpleFrozenList() + ) -> None: """ Load KnowledgeBase content from disk. path (Union[str, Path]): Target file path. exclude (Iterable[str]): List of components to exclude. """ raise NotImplementedError( - Errors.E1045.format(parent="KnowledgeBase", method="from_disk", name=self.__name__) + Errors.E1045.format( + parent="KnowledgeBase", method="from_disk", name=self.__name__ + ) ) diff --git a/spacy/kb/kb_in_memory.pxd b/spacy/kb/kb_in_memory.pxd index 08ec6b2a3..e0e33301a 100644 --- a/spacy/kb/kb_in_memory.pxd +++ b/spacy/kb/kb_in_memory.pxd @@ -55,23 +55,28 @@ cdef class InMemoryLookupKB(KnowledgeBase): # optional data, we can let users configure a DB as the backend for this. cdef object _features_table - cdef inline int64_t c_add_vector(self, vector[float] entity_vector) nogil: """Add an entity vector to the vectors table.""" cdef int64_t new_index = self._vectors_table.size() self._vectors_table.push_back(entity_vector) return new_index - - cdef inline int64_t c_add_entity(self, hash_t entity_hash, float freq, - int32_t vector_index, int feats_row) nogil: + cdef inline int64_t c_add_entity( + self, + hash_t entity_hash, + float freq, + int32_t vector_index, + int feats_row + ) nogil: """Add an entry to the vector of entries. - After calling this method, make sure to update also the _entry_index using the return value""" + After calling this method, make sure to update also the _entry_index + using the return value""" # This is what we'll map the entity hash key to. It's where the entry will sit # in the vector of entries, so we can get it later. cdef int64_t new_index = self._entries.size() - # Avoid struct initializer to enable nogil, cf https://github.com/cython/cython/issues/1642 + # Avoid struct initializer to enable nogil, cf. + # https://github.com/cython/cython/issues/1642 cdef KBEntryC entry entry.entity_hash = entity_hash entry.vector_index = vector_index @@ -81,11 +86,17 @@ cdef class InMemoryLookupKB(KnowledgeBase): self._entries.push_back(entry) return new_index - cdef inline int64_t c_add_aliases(self, hash_t alias_hash, vector[int64_t] entry_indices, vector[float] probs) nogil: - """Connect a mention to a list of potential entities with their prior probabilities . - After calling this method, make sure to update also the _alias_index using the return value""" - # This is what we'll map the alias hash key to. It's where the alias will be defined - # in the vector of aliases. + cdef inline int64_t c_add_aliases( + self, + hash_t alias_hash, + vector[int64_t] entry_indices, + vector[float] probs + ) nogil: + """Connect a mention to a list of potential entities with their prior + probabilities. After calling this method, make sure to update also the + _alias_index using the return value""" + # This is what we'll map the alias hash key to. It's where the alias will be + # defined in the vector of aliases. cdef int64_t new_index = self._aliases_table.size() # Avoid struct initializer to enable nogil @@ -98,8 +109,9 @@ cdef class InMemoryLookupKB(KnowledgeBase): cdef inline void _create_empty_vectors(self, hash_t dummy_hash) nogil: """ - Initializing the vectors and making sure the first element of each vector is a dummy, - because the PreshMap maps pointing to indices in these vectors can not contain 0 as value + Initializing the vectors and making sure the first element of each vector is a + dummy, because the PreshMap maps pointing to indices in these vectors can not + contain 0 as value. cf. https://github.com/explosion/preshed/issues/17 """ cdef int32_t dummy_value = 0 @@ -130,12 +142,18 @@ cdef class InMemoryLookupKB(KnowledgeBase): cdef class Writer: cdef FILE* _fp - 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 cdef int write_vector_element(self, float element) except -1 - 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 cdef int write_alias_length(self, int64_t alias_length) except -1 - 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 cdef int write_alias(self, int64_t entry_index, float prob) except -1 cdef int _write(self, void* value, size_t size) except -1 @@ -143,12 +161,18 @@ cdef class Writer: cdef class Reader: cdef FILE* _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 cdef int read_vector_element(self, float* element) except -1 - 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 cdef int read_alias_length(self, int64_t* alias_length) except -1 - 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 cdef int read_alias(self, int64_t* entry_index, float* prob) except -1 cdef int _read(self, void* value, size_t size) except -1 diff --git a/spacy/kb/kb_in_memory.pyx b/spacy/kb/kb_in_memory.pyx index e991f7720..02773cbae 100644 --- a/spacy/kb/kb_in_memory.pyx +++ b/spacy/kb/kb_in_memory.pyx @@ -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, - freq=freq, - vector_index=vector_index, - feats_row=-1) # Features table currently not implemented + new_index = self.c_add_entity( + entity_hash=entity_hash, + freq=freq, + vector_index=vector_index, + 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, - entities_length=len(entities), - probabilities_length=len(probabilities))) + raise ValueError( + Errors.E132.format( + alias=alias, + entities_length=len(entities), + 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 = 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 = 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 = 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 = 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(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(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): diff --git a/spacy/lexeme.pyx b/spacy/lexeme.pyx index 00e2c6258..60d22e615 100644 --- a/spacy/lexeme.pyx +++ b/spacy/lexeme.pyx @@ -1,7 +1,6 @@ # cython: embedsignature=True # Compiler crashes on memory view coercion without this. Should report bug. cimport numpy as np -from cython.view cimport array as cvarray from libc.string cimport memset np.import_array() @@ -35,7 +34,7 @@ from .typedefs cimport attr_t, flags_t from .attrs import intify_attrs from .errors import Errors, Warnings -OOV_RANK = 0xffffffffffffffff # UINT64_MAX +OOV_RANK = 0xffffffffffffffff # UINT64_MAX memset(&EMPTY_LEXEME, 0, sizeof(LexemeC)) EMPTY_LEXEME.id = OOV_RANK @@ -105,7 +104,7 @@ cdef class Lexeme: if isinstance(value, float): continue elif isinstance(value, (int, long)): - Lexeme.set_struct_attr(self.c, attr, value) + Lexeme.set_struct_attr(self.c, attr, value) else: Lexeme.set_struct_attr(self.c, attr, self.vocab.strings.add(value)) @@ -137,10 +136,12 @@ cdef class Lexeme: if hasattr(other, "orth"): if self.c.orth == other.orth: return 1.0 - elif hasattr(other, "__len__") and len(other) == 1 \ - and hasattr(other[0], "orth"): - if self.c.orth == other[0].orth: - return 1.0 + elif ( + hasattr(other, "__len__") and len(other) == 1 + and hasattr(other[0], "orth") + and self.c.orth == other[0].orth + ): + return 1.0 if self.vector_norm == 0 or other.vector_norm == 0: warnings.warn(Warnings.W008.format(obj="Lexeme")) return 0.0 @@ -149,7 +150,7 @@ cdef class Lexeme: result = xp.dot(vector, other.vector) / (self.vector_norm * other.vector_norm) # ensure we get a scalar back (numpy does this automatically but cupy doesn't) return result.item() - + @property def has_vector(self): """RETURNS (bool): Whether a word vector is associated with the object. diff --git a/spacy/matcher/dependencymatcher.pyx b/spacy/matcher/dependencymatcher.pyx index a214c0668..348e000ff 100644 --- a/spacy/matcher/dependencymatcher.pyx +++ b/spacy/matcher/dependencymatcher.pyx @@ -108,7 +108,7 @@ cdef class DependencyMatcher: key (str): The match ID. RETURNS (bool): Whether the matcher contains rules for this match ID. """ - return self.has_key(key) + return self.has_key(key) # no-cython-lint: W601 def _validate_input(self, pattern, key): idx = 0 @@ -264,7 +264,7 @@ cdef class DependencyMatcher: def remove(self, key): key = self._normalize_key(key) - if not key in self._patterns: + if key not in self._patterns: raise ValueError(Errors.E175.format(key=key)) self._patterns.pop(key) self._raw_patterns.pop(key) @@ -382,7 +382,7 @@ cdef class DependencyMatcher: 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): @@ -443,7 +443,7 @@ cdef class DependencyMatcher: def _right_child(self, doc, node): return [child for child in doc[node].rights] - + def _left_child(self, doc, node): return [child for child in doc[node].lefts] @@ -461,7 +461,7 @@ cdef class DependencyMatcher: if doc[node].head.i > node: return [doc[node].head] return [] - + def _left_parent(self, doc, node): if doc[node].head.i < node: return [doc[node].head] diff --git a/spacy/matcher/matcher.pyx b/spacy/matcher/matcher.pyx index 3d03f37ae..167f85af4 100644 --- a/spacy/matcher/matcher.pyx +++ b/spacy/matcher/matcher.pyx @@ -12,31 +12,18 @@ import warnings import srsly -from ..attrs cimport ( - DEP, - ENT_IOB, - ID, - LEMMA, - MORPH, - NULL_ATTR, - ORTH, - POS, - TAG, - attr_id_t, -) +from ..attrs cimport DEP, ENT_IOB, ID, LEMMA, MORPH, NULL_ATTR, POS, TAG from ..structs cimport TokenC from ..tokens.doc cimport Doc, get_token_attr_for_matcher from ..tokens.morphanalysis cimport MorphAnalysis from ..tokens.span cimport Span from ..tokens.token cimport Token from ..typedefs cimport attr_t -from ..vocab cimport Vocab from ..attrs import IDS from ..errors import Errors, MatchPatternError, Warnings from ..schemas import validate_token_pattern from ..strings import get_string_id -from ..util import registry from .levenshtein import levenshtein_compare DEF PADDING = 5 @@ -87,9 +74,9 @@ cdef class Matcher: key (str): The match ID. RETURNS (bool): Whether the matcher contains rules for this match ID. """ - return self.has_key(key) + return self.has_key(key) # no-cython-lint: W601 - def add(self, key, patterns, *, on_match=None, greedy: str=None): + def add(self, key, patterns, *, on_match=None, greedy: str = None): """Add a match-rule to the matcher. A match-rule consists of: an ID key, an on_match callback, and one or more patterns. @@ -143,8 +130,13 @@ cdef class Matcher: key = self._normalize_key(key) for pattern in patterns: try: - specs = _preprocess_pattern(pattern, self.vocab, - self._extensions, self._extra_predicates, self._fuzzy_compare) + specs = _preprocess_pattern( + pattern, + self.vocab, + self._extensions, + self._extra_predicates, + self._fuzzy_compare + ) self.patterns.push_back(init_pattern(self.mem, key, specs)) for spec in specs: for attr, _ in spec[1]: @@ -168,7 +160,7 @@ cdef class Matcher: key (str): The ID of the match rule. """ norm_key = self._normalize_key(key) - if not norm_key in self._patterns: + if norm_key not in self._patterns: raise ValueError(Errors.E175.format(key=key)) self._patterns.pop(norm_key) self._callbacks.pop(norm_key) @@ -268,8 +260,15 @@ cdef class Matcher: if self.patterns.empty(): matches = [] else: - matches = find_matches(&self.patterns[0], self.patterns.size(), doclike, length, - extensions=self._extensions, predicates=self._extra_predicates, with_alignments=with_alignments) + matches = find_matches( + &self.patterns[0], + self.patterns.size(), + doclike, + length, + extensions=self._extensions, + predicates=self._extra_predicates, + with_alignments=with_alignments + ) final_matches = [] pairs_by_id = {} # For each key, either add all matches, or only the filtered, @@ -289,9 +288,9 @@ cdef class Matcher: memset(matched, 0, length * sizeof(matched[0])) span_filter = self._filter.get(key) if span_filter == "FIRST": - sorted_pairs = sorted(pairs, key=lambda x: (x[0], -x[1]), reverse=False) # sort by start + sorted_pairs = sorted(pairs, key=lambda x: (x[0], -x[1]), reverse=False) # sort by start elif span_filter == "LONGEST": - sorted_pairs = sorted(pairs, key=lambda x: (x[1]-x[0], -x[0]), reverse=True) # reverse sort by length + sorted_pairs = sorted(pairs, key=lambda x: (x[1]-x[0], -x[0]), reverse=True) # reverse sort by length else: raise ValueError(Errors.E947.format(expected=["FIRST", "LONGEST"], arg=span_filter)) for match in sorted_pairs: @@ -366,7 +365,6 @@ cdef find_matches(TokenPatternC** patterns, int n, object doclike, int length, e cdef vector[MatchC] matches cdef vector[vector[MatchAlignmentC]] align_states cdef vector[vector[MatchAlignmentC]] align_matches - cdef PatternStateC state cdef int i, j, nr_extra_attr cdef Pool mem = Pool() output = [] @@ -388,14 +386,22 @@ cdef find_matches(TokenPatternC** patterns, int n, object doclike, int length, e value = token.vocab.strings[value] extra_attr_values[i * nr_extra_attr + index] = value # Main loop - cdef int nr_predicate = len(predicates) for i in range(length): for j in range(n): states.push_back(PatternStateC(patterns[j], i, 0)) if with_alignments != 0: align_states.resize(states.size()) - transition_states(states, matches, align_states, align_matches, predicate_cache, - doclike[i], extra_attr_values, predicates, with_alignments) + transition_states( + states, + matches, + align_states, + align_matches, + predicate_cache, + doclike[i], + extra_attr_values, + predicates, + with_alignments + ) extra_attr_values += nr_extra_attr predicate_cache += len(predicates) # Handle matches that end in 0-width patterns @@ -421,18 +427,28 @@ cdef find_matches(TokenPatternC** patterns, int n, object doclike, int length, e return output -cdef void transition_states(vector[PatternStateC]& states, vector[MatchC]& matches, - vector[vector[MatchAlignmentC]]& align_states, vector[vector[MatchAlignmentC]]& align_matches, - int8_t* cached_py_predicates, - Token token, const attr_t* extra_attrs, py_predicates, bint with_alignments) except *: +cdef void transition_states( + vector[PatternStateC]& states, + vector[MatchC]& matches, + vector[vector[MatchAlignmentC]]& align_states, + vector[vector[MatchAlignmentC]]& align_matches, + int8_t* cached_py_predicates, + Token token, + const attr_t* extra_attrs, + py_predicates, + bint with_alignments +) except *: cdef int q = 0 cdef vector[PatternStateC] new_states cdef vector[vector[MatchAlignmentC]] align_new_states - cdef int nr_predicate = len(py_predicates) for i in range(states.size()): if states[i].pattern.nr_py >= 1: - update_predicate_cache(cached_py_predicates, - states[i].pattern, token, py_predicates) + update_predicate_cache( + cached_py_predicates, + states[i].pattern, + token, + py_predicates + ) action = get_action(states[i], token.c, extra_attrs, cached_py_predicates) if action == REJECT: @@ -468,8 +484,12 @@ cdef void transition_states(vector[PatternStateC]& states, vector[MatchC]& match align_new_states.push_back(align_states[q]) states[q].pattern += 1 if states[q].pattern.nr_py != 0: - update_predicate_cache(cached_py_predicates, - states[q].pattern, token, py_predicates) + update_predicate_cache( + cached_py_predicates, + states[q].pattern, + token, + py_predicates + ) action = get_action(states[q], token.c, extra_attrs, cached_py_predicates) # Update alignment before the transition of current state @@ -485,8 +505,12 @@ cdef void transition_states(vector[PatternStateC]& states, vector[MatchC]& match ent_id = get_ent_id(state.pattern) if action == MATCH: matches.push_back( - MatchC(pattern_id=ent_id, start=state.start, - length=state.length+1)) + MatchC( + pattern_id=ent_id, + start=state.start, + length=state.length+1 + ) + ) # `align_matches` always corresponds to `matches` 1:1 if with_alignments != 0: align_matches.push_back(align_states[q]) @@ -494,23 +518,35 @@ cdef void transition_states(vector[PatternStateC]& states, vector[MatchC]& match # push match without last token if length > 0 if state.length > 0: matches.push_back( - MatchC(pattern_id=ent_id, start=state.start, - length=state.length)) + MatchC( + pattern_id=ent_id, + start=state.start, + length=state.length + ) + ) # MATCH_DOUBLE emits matches twice, # add one more to align_matches in order to keep 1:1 relationship if with_alignments != 0: align_matches.push_back(align_states[q]) # push match with last token matches.push_back( - MatchC(pattern_id=ent_id, start=state.start, - length=state.length+1)) + MatchC( + pattern_id=ent_id, + start=state.start, + length=state.length + 1 + ) + ) # `align_matches` always corresponds to `matches` 1:1 if with_alignments != 0: align_matches.push_back(align_states[q]) elif action == MATCH_REJECT: matches.push_back( - MatchC(pattern_id=ent_id, start=state.start, - length=state.length)) + MatchC( + pattern_id=ent_id, + start=state.start, + length=state.length + ) + ) # `align_matches` always corresponds to `matches` 1:1 if with_alignments != 0: align_matches.push_back(align_states[q]) @@ -533,8 +569,12 @@ cdef void transition_states(vector[PatternStateC]& states, vector[MatchC]& match align_states.push_back(align_new_states[i]) -cdef int update_predicate_cache(int8_t* cache, - const TokenPatternC* pattern, Token token, predicates) except -1: +cdef int update_predicate_cache( + int8_t* cache, + const TokenPatternC* pattern, + Token token, + predicates +) except -1: # If the state references any extra predicates, check whether they match. # These are cached, so that we don't call these potentially expensive # Python functions more than we need to. @@ -580,10 +620,12 @@ cdef void finish_states(vector[MatchC]& matches, vector[PatternStateC]& states, else: state.pattern += 1 - -cdef action_t get_action(PatternStateC state, - const TokenC* token, const attr_t* extra_attrs, - const int8_t* predicate_matches) nogil: +cdef action_t get_action( + PatternStateC state, + const TokenC * token, + const attr_t * extra_attrs, + const int8_t * predicate_matches +) nogil: """We need to consider: a) Does the token match the specification? [Yes, No] b) What's the quantifier? [1, 0+, ?] @@ -649,53 +691,56 @@ cdef action_t get_action(PatternStateC state, is_match = not is_match quantifier = ONE if quantifier == ONE: - if is_match and is_final: - # Yes, final: 1000 - return MATCH - elif is_match and not is_final: - # Yes, non-final: 0100 - return ADVANCE - elif not is_match and is_final: - # No, final: 0000 - return REJECT - else: - return REJECT + if is_match and is_final: + # Yes, final: 1000 + return MATCH + elif is_match and not is_final: + # Yes, non-final: 0100 + return ADVANCE + elif not is_match and is_final: + # No, final: 0000 + return REJECT + else: + return REJECT elif quantifier == ZERO_PLUS: - if is_match and is_final: - # Yes, final: 1001 - return MATCH_EXTEND - elif is_match and not is_final: - # Yes, non-final: 0011 - return RETRY_EXTEND - elif not is_match and is_final: - # No, final 2000 (note: Don't include last token!) - return MATCH_REJECT - else: - # No, non-final 0010 - return RETRY + if is_match and is_final: + # Yes, final: 1001 + return MATCH_EXTEND + elif is_match and not is_final: + # Yes, non-final: 0011 + return RETRY_EXTEND + elif not is_match and is_final: + # No, final 2000 (note: Don't include last token!) + return MATCH_REJECT + else: + # No, non-final 0010 + return RETRY elif quantifier == ZERO_ONE: - if is_match and is_final: - # Yes, final: 3000 - # To cater for a pattern ending in "?", we need to add - # a match both with and without the last token - return MATCH_DOUBLE - elif is_match and not is_final: - # Yes, non-final: 0110 - # We need both branches here, consider a pair like: - # pattern: .?b string: b - # If we 'ADVANCE' on the .?, we miss the match. - return RETRY_ADVANCE - elif not is_match and is_final: - # No, final 2000 (note: Don't include last token!) - return MATCH_REJECT - else: - # No, non-final 0010 - return RETRY + if is_match and is_final: + # Yes, final: 3000 + # To cater for a pattern ending in "?", we need to add + # a match both with and without the last token + return MATCH_DOUBLE + elif is_match and not is_final: + # Yes, non-final: 0110 + # We need both branches here, consider a pair like: + # pattern: .?b string: b + # If we 'ADVANCE' on the .?, we miss the match. + return RETRY_ADVANCE + elif not is_match and is_final: + # No, final 2000 (note: Don't include last token!) + return MATCH_REJECT + else: + # No, non-final 0010 + return RETRY -cdef int8_t get_is_match(PatternStateC state, - const TokenC* token, const attr_t* extra_attrs, - const int8_t* predicate_matches) nogil: +cdef int8_t get_is_match( + PatternStateC state, + const TokenC* token, + const attr_t* extra_attrs, + const int8_t* predicate_matches +) nogil: for i in range(state.pattern.nr_py): if predicate_matches[state.pattern.py_predicates[i]] == -1: return 0 @@ -860,7 +905,7 @@ class _FuzzyPredicate: self.is_extension = is_extension if self.predicate not in self.operators: raise ValueError(Errors.E126.format(good=self.operators, bad=self.predicate)) - fuzz = self.predicate[len("FUZZY"):] # number after prefix + fuzz = self.predicate[len("FUZZY"):] # number after prefix self.fuzzy = int(fuzz) if fuzz else -1 self.fuzzy_compare = fuzzy_compare self.key = _predicate_cache_key(self.attr, self.predicate, value, fuzzy=self.fuzzy) @@ -1082,7 +1127,7 @@ def _get_extra_predicates_dict(attr, value_dict, vocab, predicate_types, elif cls == _FuzzyPredicate: if isinstance(value, dict): # add predicates inside fuzzy operator - fuzz = type_[len("FUZZY"):] # number after prefix + fuzz = type_[len("FUZZY"):] # number after prefix fuzzy_val = int(fuzz) if fuzz else -1 output.extend(_get_extra_predicates_dict(attr, value, vocab, predicate_types, extra_predicates, seen_predicates, @@ -1101,8 +1146,9 @@ def _get_extra_predicates_dict(attr, value_dict, vocab, predicate_types, return output -def _get_extension_extra_predicates(spec, extra_predicates, predicate_types, - seen_predicates): +def _get_extension_extra_predicates( + spec, extra_predicates, predicate_types, seen_predicates +): output = [] for attr, value in spec.items(): if isinstance(value, dict): @@ -1131,7 +1177,7 @@ def _get_operators(spec): return (ONE,) elif spec["OP"] in lookup: return lookup[spec["OP"]] - #Min_max {n,m} + # Min_max {n,m} elif spec["OP"].startswith("{") and spec["OP"].endswith("}"): # {n} --> {n,n} exactly n ONE,(n) # {n,m}--> {n,m} min of n, max of m ONE,(n),ZERO_ONE,(m) @@ -1142,8 +1188,8 @@ def _get_operators(spec): min_max = min_max if "," in min_max else f"{min_max},{min_max}" n, m = min_max.split(",") - #1. Either n or m is a blank string and the other is numeric -->isdigit - #2. Both are numeric and n <= m + # 1. Either n or m is a blank string and the other is numeric -->isdigit + # 2. Both are numeric and n <= m if (not n.isdecimal() and not m.isdecimal()) or (n.isdecimal() and m.isdecimal() and int(n) > int(m)): keys = ", ".join(lookup.keys()) + ", {n}, {n,m}, {n,}, {,m} where n and m are integers and n <= m " raise ValueError(Errors.E011.format(op=spec["OP"], opts=keys)) diff --git a/spacy/matcher/phrasematcher.pyx b/spacy/matcher/phrasematcher.pyx index c407cf1cc..26633e6d6 100644 --- a/spacy/matcher/phrasematcher.pyx +++ b/spacy/matcher/phrasematcher.pyx @@ -1,14 +1,12 @@ # cython: infer_types=True, profile=True -from libc.stdint cimport uintptr_t from preshed.maps cimport map_clear, map_get, map_init, map_iter, map_set import warnings -from ..attrs cimport DEP, LEMMA, MORPH, ORTH, POS, TAG +from ..attrs cimport DEP, LEMMA, MORPH, POS, TAG from ..attrs import IDS -from ..structs cimport TokenC from ..tokens.span cimport Span from ..tokens.token cimport Token from ..typedefs cimport attr_t diff --git a/spacy/ml/parser_model.pxd b/spacy/ml/parser_model.pxd index ca31c1699..4d2d7b3fe 100644 --- a/spacy/ml/parser_model.pxd +++ b/spacy/ml/parser_model.pxd @@ -40,11 +40,16 @@ cdef ActivationsC alloc_activations(SizesC n) nogil cdef void free_activations(const ActivationsC* A) nogil -cdef void predict_states(CBlas cblas, ActivationsC* A, StateC** states, - const WeightsC* W, SizesC n) nogil - +cdef void predict_states( + CBlas cblas, ActivationsC* A, StateC** states, const WeightsC* W, SizesC n +) nogil + cdef int arg_max_if_valid(const weight_t* scores, const int* is_valid, int n) nogil -cdef void cpu_log_loss(float* d_scores, - const float* costs, const int* is_valid, const float* scores, int O) nogil - +cdef void cpu_log_loss( + float* d_scores, + const float* costs, + const int* is_valid, + const float* scores, + int O +) nogil diff --git a/spacy/ml/parser_model.pyx b/spacy/ml/parser_model.pyx index 5cffc4c2d..ae60972aa 100644 --- a/spacy/ml/parser_model.pyx +++ b/spacy/ml/parser_model.pyx @@ -8,13 +8,13 @@ from thinc.backends.linalg cimport Vec, VecVec import numpy import numpy.random -from thinc.api import CupyOps, Model, NumpyOps, get_ops +from thinc.api import CupyOps, Model, NumpyOps from .. import util from ..errors import Errors from ..pipeline._parser_internals.stateclass cimport StateClass -from ..typedefs cimport class_t, hash_t, weight_t +from ..typedefs cimport weight_t cdef WeightsC get_c_weights(model) except *: @@ -78,33 +78,48 @@ cdef void resize_activations(ActivationsC* A, SizesC n) nogil: A.is_valid = calloc(n.states * n.classes, sizeof(A.is_valid[0])) A._max_size = n.states else: - A.token_ids = realloc(A.token_ids, - n.states * n.feats * sizeof(A.token_ids[0])) - A.scores = realloc(A.scores, - n.states * n.classes * sizeof(A.scores[0])) - A.unmaxed = realloc(A.unmaxed, - n.states * n.hiddens * n.pieces * sizeof(A.unmaxed[0])) - A.hiddens = realloc(A.hiddens, - n.states * n.hiddens * sizeof(A.hiddens[0])) - A.is_valid = realloc(A.is_valid, - n.states * n.classes * sizeof(A.is_valid[0])) + A.token_ids = realloc( + A.token_ids, n.states * n.feats * sizeof(A.token_ids[0]) + ) + A.scores = realloc( + A.scores, n.states * n.classes * sizeof(A.scores[0]) + ) + A.unmaxed = realloc( + A.unmaxed, n.states * n.hiddens * n.pieces * sizeof(A.unmaxed[0]) + ) + A.hiddens = realloc( + A.hiddens, n.states * n.hiddens * sizeof(A.hiddens[0]) + ) + A.is_valid = realloc( + A.is_valid, n.states * n.classes * sizeof(A.is_valid[0]) + ) A._max_size = n.states A._curr_size = n.states -cdef void predict_states(CBlas cblas, ActivationsC* A, StateC** states, - const WeightsC* W, SizesC n) nogil: - cdef double one = 1.0 +cdef void predict_states( + CBlas cblas, ActivationsC* A, StateC** states, const WeightsC* W, SizesC n +) nogil: resize_activations(A, n) for i in range(n.states): states[i].set_context_tokens(&A.token_ids[i*n.feats], n.feats) memset(A.unmaxed, 0, n.states * n.hiddens * n.pieces * sizeof(float)) memset(A.hiddens, 0, n.states * n.hiddens * sizeof(float)) - sum_state_features(cblas, A.unmaxed, - W.feat_weights, A.token_ids, n.states, n.feats, n.hiddens * n.pieces) + sum_state_features( + cblas, + A.unmaxed, + W.feat_weights, + A.token_ids, + n.states, + n.feats, + n.hiddens * n.pieces + ) for i in range(n.states): - VecVec.add_i(&A.unmaxed[i*n.hiddens*n.pieces], - W.feat_bias, 1., n.hiddens * n.pieces) + VecVec.add_i( + &A.unmaxed[i*n.hiddens*n.pieces], + W.feat_bias, 1., + n.hiddens * n.pieces + ) for j in range(n.hiddens): index = i * n.hiddens * n.pieces + j * n.pieces which = Vec.arg_max(&A.unmaxed[index], n.pieces) @@ -114,14 +129,15 @@ cdef void predict_states(CBlas cblas, ActivationsC* A, StateC** states, memcpy(A.scores, A.hiddens, n.states * n.classes * sizeof(float)) else: # Compute hidden-to-output - sgemm(cblas)(False, True, n.states, n.classes, n.hiddens, + sgemm(cblas)( + False, True, n.states, n.classes, n.hiddens, 1.0, A.hiddens, n.hiddens, W.hidden_weights, n.hiddens, - 0.0, A.scores, n.classes) + 0.0, A.scores, n.classes + ) # Add bias for i in range(n.states): - VecVec.add_i(&A.scores[i*n.classes], - W.hidden_bias, 1., n.classes) + VecVec.add_i(&A.scores[i*n.classes], W.hidden_bias, 1., n.classes) # Set unseen classes to minimum value i = 0 min_ = A.scores[0] @@ -134,9 +150,16 @@ cdef void predict_states(CBlas cblas, ActivationsC* A, StateC** states, A.scores[i*n.classes+j] = min_ -cdef void sum_state_features(CBlas cblas, float* output, - const float* cached, const int* token_ids, int B, int F, int O) nogil: - cdef int idx, b, f, i +cdef void sum_state_features( + CBlas cblas, + float* output, + const float* cached, + const int* token_ids, + int B, + int F, + int O +) nogil: + cdef int idx, b, f cdef const float* feature padding = cached cached += F * O @@ -153,9 +176,13 @@ cdef void sum_state_features(CBlas cblas, float* output, token_ids += F -cdef void cpu_log_loss(float* d_scores, - const float* costs, const int* is_valid, const float* scores, - int O) nogil: +cdef void cpu_log_loss( + float* d_scores, + const float* costs, + const int* is_valid, + const float* scores, + int O +) nogil: """Do multi-label log loss""" cdef double max_, gmax, Z, gZ best = arg_max_if_gold(scores, costs, is_valid, O) @@ -179,8 +206,9 @@ cdef void cpu_log_loss(float* d_scores, d_scores[i] = exp(scores[i]-max_) / Z -cdef int arg_max_if_gold(const weight_t* scores, const weight_t* costs, - const int* is_valid, int n) nogil: +cdef int arg_max_if_gold( + const weight_t* scores, const weight_t* costs, const int* is_valid, int n +) nogil: # Find minimum cost cdef float cost = 1 for i in range(n): @@ -204,10 +232,17 @@ cdef int arg_max_if_valid(const weight_t* scores, const int* is_valid, int n) no return best - class ParserStepModel(Model): - def __init__(self, docs, layers, *, has_upper, unseen_classes=None, train=True, - dropout=0.1): + def __init__( + self, + docs, + layers, + *, + has_upper, + unseen_classes=None, + train=True, + dropout=0.1 + ): Model.__init__(self, name="parser_step_model", forward=step_forward) self.attrs["has_upper"] = has_upper self.attrs["dropout_rate"] = dropout @@ -268,8 +303,10 @@ class ParserStepModel(Model): return ids def backprop_step(self, token_ids, d_vector, get_d_tokvecs): - if isinstance(self.state2vec.ops, CupyOps) \ - and not isinstance(token_ids, self.state2vec.ops.xp.ndarray): + if ( + isinstance(self.state2vec.ops, CupyOps) + and not isinstance(token_ids, self.state2vec.ops.xp.ndarray) + ): # Move token_ids and d_vector to GPU, asynchronously self.backprops.append(( util.get_async(self.cuda_stream, token_ids), @@ -279,7 +316,6 @@ class ParserStepModel(Model): else: self.backprops.append((token_ids, d_vector, get_d_tokvecs)) - def finish_steps(self, golds): # Add a padding vector to the d_tokvecs gradient, so that missing # values don't affect the real gradient. @@ -292,14 +328,15 @@ class ParserStepModel(Model): ids = ids.flatten() d_state_features = d_state_features.reshape( (ids.size, d_state_features.shape[2])) - self.ops.scatter_add(d_tokvecs, ids, - d_state_features) + self.ops.scatter_add(d_tokvecs, ids, d_state_features) # Padded -- see update() self.bp_tokvecs(d_tokvecs[:-1]) return d_tokvecs + NUMPY_OPS = NumpyOps() + def step_forward(model: ParserStepModel, states, is_train): token_ids = model.get_token_ids(states) vector, get_d_tokvecs = model.state2vec(token_ids, is_train) @@ -312,7 +349,7 @@ def step_forward(model: ParserStepModel, states, is_train): scores, get_d_vector = model.vec2scores(vector, is_train) else: scores = NumpyOps().asarray(vector) - get_d_vector = lambda d_scores: d_scores + get_d_vector = lambda d_scores: d_scores # no-cython-lint: E731 # If the class is unseen, make sure its score is minimum scores[:, model._class_mask == 0] = numpy.nanmin(scores) @@ -448,9 +485,11 @@ cdef class precompute_hiddens: feat_weights = self.get_feat_weights() cdef int[:, ::1] ids = token_ids - sum_state_features(cblas, state_vector.data, - feat_weights, &ids[0,0], - token_ids.shape[0], self.nF, self.nO*self.nP) + sum_state_features( + cblas, state_vector.data, + feat_weights, &ids[0, 0], + token_ids.shape[0], self.nF, self.nO*self.nP + ) state_vector += self.bias state_vector, bp_nonlinearity = self._nonlinearity(state_vector) @@ -475,7 +514,7 @@ cdef class precompute_hiddens: def backprop_maxout(d_best): return self.ops.backprop_maxout(d_best, mask, self.nP) - + return state_vector, backprop_maxout def _relu_nonlinearity(self, state_vector): @@ -489,5 +528,5 @@ cdef class precompute_hiddens: def backprop_relu(d_best): d_best *= mask return d_best.reshape((d_best.shape + (1,))) - + return state_vector, backprop_relu diff --git a/spacy/morphology.pxd b/spacy/morphology.pxd index 968764b82..ee43aa4ec 100644 --- a/spacy/morphology.pxd +++ b/spacy/morphology.pxd @@ -11,7 +11,7 @@ from .typedefs cimport attr_t, hash_t cdef class Morphology: cdef readonly Pool mem cdef readonly StringStore strings - cdef PreshMap tags # Keyed by hash, value is pointer to tag + cdef PreshMap tags # Keyed by hash, value is pointer to tag cdef MorphAnalysisC create_morph_tag(self, field_feature_pairs) except * cdef int insert(self, MorphAnalysisC tag) except -1 @@ -20,4 +20,8 @@ cdef class Morphology: cdef int check_feature(const MorphAnalysisC* morph, attr_t feature) nogil cdef list list_features(const MorphAnalysisC* morph) cdef np.ndarray get_by_field(const MorphAnalysisC* morph, attr_t field) -cdef int get_n_by_field(attr_t* results, const MorphAnalysisC* morph, attr_t field) nogil +cdef int get_n_by_field( + attr_t* results, + const MorphAnalysisC* morph, + attr_t field, +) nogil diff --git a/spacy/morphology.pyx b/spacy/morphology.pyx index 1062fff09..ecbbed729 100644 --- a/spacy/morphology.pyx +++ b/spacy/morphology.pyx @@ -83,10 +83,11 @@ cdef class Morphology: features = self.normalize_attrs(features) string_features = {self.strings.as_string(field): self.strings.as_string(values) for field, values in features.items()} # normalized UFEATS string with sorted fields and values - norm_feats_string = self.FEATURE_SEP.join(sorted([ - self.FIELD_SEP.join([field, values]) - for field, values in string_features.items() - ])) + norm_feats_string = self.FEATURE_SEP.join( + sorted( + [self.FIELD_SEP.join([field, values]) for field, values in string_features.items()] + ) + ) return norm_feats_string or self.EMPTY_MORPH def normalize_attrs(self, attrs): @@ -192,6 +193,7 @@ cdef int get_n_by_field(attr_t* results, const MorphAnalysisC* morph, attr_t fie n_results += 1 return n_results + def unpickle_morphology(strings, tags): cdef Morphology morphology = Morphology(strings) for tag in tags: diff --git a/spacy/parts_of_speech.pxd b/spacy/parts_of_speech.pxd index a0b2567f1..b5423d113 100644 --- a/spacy/parts_of_speech.pxd +++ b/spacy/parts_of_speech.pxd @@ -8,7 +8,7 @@ cpdef enum univ_pos_t: ADV AUX CONJ - CCONJ # U20 + CCONJ # U20 DET INTJ NOUN diff --git a/spacy/pipeline/_edit_tree_internals/edit_trees.pxd b/spacy/pipeline/_edit_tree_internals/edit_trees.pxd index 3d63af921..41acd2b07 100644 --- a/spacy/pipeline/_edit_tree_internals/edit_trees.pxd +++ b/spacy/pipeline/_edit_tree_internals/edit_trees.pxd @@ -46,11 +46,18 @@ cdef struct EditTreeC: bint is_match_node NodeC inner -cdef inline EditTreeC edittree_new_match(len_t prefix_len, len_t suffix_len, - uint32_t prefix_tree, uint32_t suffix_tree): - cdef MatchNodeC match_node = MatchNodeC(prefix_len=prefix_len, - suffix_len=suffix_len, prefix_tree=prefix_tree, - suffix_tree=suffix_tree) +cdef inline EditTreeC edittree_new_match( + len_t prefix_len, + len_t suffix_len, + uint32_t prefix_tree, + uint32_t suffix_tree +): + cdef MatchNodeC match_node = MatchNodeC( + prefix_len=prefix_len, + suffix_len=suffix_len, + prefix_tree=prefix_tree, + suffix_tree=suffix_tree + ) cdef NodeC inner = NodeC(match_node=match_node) return EditTreeC(is_match_node=True, inner=inner) diff --git a/spacy/pipeline/_edit_tree_internals/edit_trees.pyx b/spacy/pipeline/_edit_tree_internals/edit_trees.pyx index daab0d204..78cd25622 100644 --- a/spacy/pipeline/_edit_tree_internals/edit_trees.pyx +++ b/spacy/pipeline/_edit_tree_internals/edit_trees.pyx @@ -5,8 +5,6 @@ from libc.string cimport memset from libcpp.pair cimport pair from libcpp.vector cimport vector -from pathlib import Path - from ...typedefs cimport hash_t from ... import util @@ -25,17 +23,16 @@ cdef LCS find_lcs(str source, str target): target (str): The second string. RETURNS (LCS): The spans of the longest common subsequences. """ - cdef Py_ssize_t source_len = len(source) cdef Py_ssize_t target_len = len(target) - cdef size_t longest_align = 0; + cdef size_t longest_align = 0 cdef int source_idx, target_idx cdef LCS lcs cdef Py_UCS4 source_cp, target_cp memset(&lcs, 0, sizeof(lcs)) - cdef vector[size_t] prev_aligns = vector[size_t](target_len); - cdef vector[size_t] cur_aligns = vector[size_t](target_len); + cdef vector[size_t] prev_aligns = vector[size_t](target_len) + cdef vector[size_t] cur_aligns = vector[size_t](target_len) for (source_idx, source_cp) in enumerate(source): for (target_idx, target_cp) in enumerate(target): @@ -89,7 +86,7 @@ cdef class EditTrees: cdef LCS lcs = find_lcs(form, lemma) cdef EditTreeC tree - cdef uint32_t tree_id, prefix_tree, suffix_tree + cdef uint32_t prefix_tree, suffix_tree if lcs_is_empty(lcs): tree = edittree_new_subst(self.strings.add(form), self.strings.add(lemma)) else: @@ -108,7 +105,7 @@ cdef class EditTrees: return self._tree_id(tree) cdef uint32_t _tree_id(self, EditTreeC tree): - # If this tree has been constructed before, return its identifier. + # If this tree has been constructed before, return its identifier. cdef hash_t hash = edittree_hash(tree) cdef unordered_map[hash_t, uint32_t].iterator iter = self.map.find(hash) if iter != self.map.end(): @@ -289,6 +286,7 @@ def _tree2dict(tree): tree = tree["inner"]["subst_node"] return(dict(tree)) + def _dict2tree(tree): errors = validate_edit_tree(tree) if errors: diff --git a/spacy/pipeline/_parser_internals/_beam_utils.pyx b/spacy/pipeline/_parser_internals/_beam_utils.pyx index 04dd3f11e..de8f0bf7b 100644 --- a/spacy/pipeline/_parser_internals/_beam_utils.pyx +++ b/spacy/pipeline/_parser_internals/_beam_utils.pyx @@ -1,17 +1,14 @@ # cython: infer_types=True # cython: profile=True -cimport numpy as np - import numpy -from cpython.ref cimport Py_XDECREF, PyObject from thinc.extra.search cimport Beam from thinc.extra.search import MaxViolation from thinc.extra.search cimport MaxViolation -from ...typedefs cimport class_t, hash_t +from ...typedefs cimport class_t from .transition_system cimport Transition, TransitionSystem from ...errors import Errors @@ -146,7 +143,6 @@ def update_beam(TransitionSystem moves, states, golds, model, int width, beam_de cdef MaxViolation violn pbeam = BeamBatch(moves, states, golds, width=width, density=beam_density) gbeam = BeamBatch(moves, states, golds, width=width, density=0.0) - cdef StateClass state beam_maps = [] backprops = [] violns = [MaxViolation() for _ in range(len(states))] diff --git a/spacy/pipeline/_parser_internals/_state.pxd b/spacy/pipeline/_parser_internals/_state.pxd index 24acc350c..c063cf97c 100644 --- a/spacy/pipeline/_parser_internals/_state.pxd +++ b/spacy/pipeline/_parser_internals/_state.pxd @@ -277,7 +277,6 @@ cdef cppclass StateC: return n - int n_L(int head) nogil const: return n_arcs(this._left_arcs, head) diff --git a/spacy/pipeline/_parser_internals/arc_eager.pyx b/spacy/pipeline/_parser_internals/arc_eager.pyx index 2c9eb0ff5..bcb4626fb 100644 --- a/spacy/pipeline/_parser_internals/arc_eager.pyx +++ b/spacy/pipeline/_parser_internals/arc_eager.pyx @@ -9,7 +9,7 @@ from ...strings cimport hash_string from ...structs cimport TokenC from ...tokens.doc cimport Doc, set_children_from_heads from ...tokens.token cimport MISSING_DEP -from ...typedefs cimport attr_t, hash_t +from ...typedefs cimport attr_t from ...training import split_bilu_label @@ -68,8 +68,9 @@ cdef struct GoldParseStateC: weight_t pop_cost -cdef GoldParseStateC create_gold_state(Pool mem, const StateC* state, - heads, labels, sent_starts) except *: +cdef GoldParseStateC create_gold_state( + Pool mem, const StateC* state, heads, labels, sent_starts +) except *: cdef GoldParseStateC gs gs.length = len(heads) gs.stride = 1 @@ -82,7 +83,7 @@ cdef GoldParseStateC create_gold_state(Pool mem, const StateC* state, gs.n_kids_in_stack = mem.alloc(gs.length, sizeof(gs.n_kids_in_stack[0])) for i, is_sent_start in enumerate(sent_starts): - if is_sent_start == True: + if is_sent_start is True: gs.state_bits[i] = set_state_flag( gs.state_bits[i], IS_SENT_START, @@ -210,6 +211,7 @@ cdef class ArcEagerGold: def update(self, StateClass stcls): update_gold_state(&self.c, stcls.c) + def _get_aligned_sent_starts(example): """Get list of SENT_START attributes aligned to the predicted tokenization. If the reference has not sentence starts, return a list of None values. @@ -524,7 +526,6 @@ cdef class Break: """ @staticmethod cdef bint is_valid(const StateC* st, attr_t label) nogil: - cdef int i if st.buffer_length() < 2: return False elif st.B(1) != st.B(0) + 1: @@ -556,8 +557,8 @@ cdef class Break: cost -= 1 if gold.heads[si] == b0: cost -= 1 - if not is_sent_start(gold, state.B(1)) \ - and not is_sent_start_unknown(gold, state.B(1)): + if not is_sent_start(gold, state.B(1)) and\ + not is_sent_start_unknown(gold, state.B(1)): cost += 1 return cost @@ -803,7 +804,6 @@ cdef class ArcEager(TransitionSystem): raise TypeError(Errors.E909.format(name="ArcEagerGold")) cdef ArcEagerGold gold_ = gold gold_state = gold_.c - n_gold = 0 if self.c[i].is_valid(stcls.c, self.c[i].label): cost = self.c[i].get_cost(stcls.c, &gold_state, self.c[i].label) else: @@ -875,7 +875,7 @@ cdef class ArcEager(TransitionSystem): print("Gold") for token in example.y: print(token.i, token.text, token.dep_, token.head.text) - aligned_heads, aligned_labels = example.get_aligned_parse() + aligned_heads, _aligned_labels = example.get_aligned_parse() print("Aligned heads") for i, head in enumerate(aligned_heads): print(example.x[i], example.x[head] if head is not None else "__") diff --git a/spacy/pipeline/_parser_internals/ner.pyx b/spacy/pipeline/_parser_internals/ner.pyx index e1edb4464..6c4f8e245 100644 --- a/spacy/pipeline/_parser_internals/ner.pyx +++ b/spacy/pipeline/_parser_internals/ner.pyx @@ -1,6 +1,3 @@ -import os -import random - from cymem.cymem cimport Pool from libc.stdint cimport int32_t @@ -14,7 +11,7 @@ from ...tokens.span import Span from ...attrs cimport IS_SPACE from ...lexeme cimport Lexeme -from ...structs cimport SpanC, TokenC +from ...structs cimport SpanC from ...tokens.span cimport Span from ...typedefs cimport attr_t, weight_t @@ -141,11 +138,10 @@ cdef class BiluoPushDown(TransitionSystem): OUT: Counter() } actions[OUT][''] = 1 # Represents a token predicted to be outside of any entity - actions[UNIT][''] = 1 # Represents a token prohibited to be in an entity + actions[UNIT][''] = 1 # Represents a token prohibited to be in an entity for entity_type in kwargs.get('entity_types', []): for action in (BEGIN, IN, LAST, UNIT): actions[action][entity_type] = 1 - moves = ('M', 'B', 'I', 'L', 'U') for example in kwargs.get('examples', []): for token in example.y: ent_type = token.ent_type_ @@ -164,7 +160,7 @@ cdef class BiluoPushDown(TransitionSystem): if token.ent_type: labels.add(token.ent_type_) return labels - + def move_name(self, int move, attr_t label): if move == OUT: return 'O' @@ -325,7 +321,6 @@ cdef class BiluoPushDown(TransitionSystem): raise TypeError(Errors.E909.format(name="BiluoGold")) cdef BiluoGold gold_ = gold gold_state = gold_.c - n_gold = 0 if self.c[i].is_valid(stcls.c, self.c[i].label): cost = self.c[i].get_cost(stcls.c, &gold_state, self.c[i].label) else: @@ -486,10 +481,8 @@ cdef class In: @staticmethod cdef weight_t cost(const StateC* s, const void* _gold, attr_t label) nogil: gold = _gold - move = IN cdef int next_act = gold.ner[s.B(1)].move if s.B(1) >= 0 else OUT cdef int g_act = gold.ner[s.B(0)].move - cdef attr_t g_tag = gold.ner[s.B(0)].label cdef bint is_sunk = _entity_is_sunk(s, gold.ner) if g_act == MISSING: @@ -549,12 +542,10 @@ cdef class Last: @staticmethod cdef weight_t cost(const StateC* s, const void* _gold, attr_t label) nogil: gold = _gold - move = LAST b0 = s.B(0) ent_start = s.E(0) cdef int g_act = gold.ner[b0].move - cdef attr_t g_tag = gold.ner[b0].label cdef int cost = 0 @@ -650,7 +641,6 @@ cdef class Unit: cost += 1 break return cost - cdef class Out: @@ -675,7 +665,6 @@ cdef class Out: cdef weight_t cost(const StateC* s, const void* _gold, attr_t label) nogil: gold = _gold cdef int g_act = gold.ner[s.B(0)].move - cdef attr_t g_tag = gold.ner[s.B(0)].label cdef weight_t cost = 0 if g_act == MISSING: pass diff --git a/spacy/pipeline/_parser_internals/nonproj.pyx b/spacy/pipeline/_parser_internals/nonproj.pyx index 66f423b3b..93ad14feb 100644 --- a/spacy/pipeline/_parser_internals/nonproj.pyx +++ b/spacy/pipeline/_parser_internals/nonproj.pyx @@ -125,14 +125,17 @@ def decompose(label): def is_decorated(label): return DELIMITER in label + def count_decorated_labels(gold_data): freqs = {} for example in gold_data: proj_heads, deco_deps = projectivize(example.get_aligned("HEAD"), example.get_aligned("DEP")) # set the label to ROOT for each root dependent - deco_deps = ['ROOT' if head == i else deco_deps[i] - for i, head in enumerate(proj_heads)] + deco_deps = [ + 'ROOT' if head == i else deco_deps[i] + for i, head in enumerate(proj_heads) + ] # count label frequencies for label in deco_deps: if is_decorated(label): @@ -160,9 +163,9 @@ def projectivize(heads, labels): cdef vector[int] _heads_to_c(heads): - cdef vector[int] c_heads; + cdef vector[int] c_heads for head in heads: - if head == None: + if head is None: c_heads.push_back(-1) else: assert head < len(heads) @@ -199,6 +202,7 @@ def _decorate(heads, proj_heads, labels): deco_labels.append(labels[tokenid]) return deco_labels + def get_smallest_nonproj_arc_slow(heads): cdef vector[int] c_heads = _heads_to_c(heads) return _get_smallest_nonproj_arc(c_heads) diff --git a/spacy/pipeline/_parser_internals/stateclass.pyx b/spacy/pipeline/_parser_internals/stateclass.pyx index 0a2657af1..fdb5004bb 100644 --- a/spacy/pipeline/_parser_internals/stateclass.pyx +++ b/spacy/pipeline/_parser_internals/stateclass.pyx @@ -1,6 +1,4 @@ # cython: infer_types=True -import numpy - from libcpp.vector cimport vector from ...tokens.doc cimport Doc @@ -38,11 +36,11 @@ cdef class StateClass: cdef vector[ArcC] arcs self.c.get_arcs(&arcs) return list(arcs) - #py_arcs = [] - #for arc in arcs: - # if arc.head != -1 and arc.child != -1: - # py_arcs.append((arc.head, arc.child, arc.label)) - #return arcs + # py_arcs = [] + # for arc in arcs: + # if arc.head != -1 and arc.child != -1: + # py_arcs.append((arc.head, arc.child, arc.label)) + # return arcs def add_arc(self, int head, int child, int label): self.c.add_arc(head, child, label) @@ -52,10 +50,10 @@ cdef class StateClass: def H(self, int child): return self.c.H(child) - + def L(self, int head, int idx): return self.c.L(head, idx) - + def R(self, int head, int idx): return self.c.R(head, idx) @@ -98,7 +96,7 @@ cdef class StateClass: def H(self, int i): return self.c.H(i) - + def E(self, int i): return self.c.E(i) @@ -116,7 +114,7 @@ cdef class StateClass: def H_(self, int i): return self.doc[self.c.H(i)] - + def E_(self, int i): return self.doc[self.c.E(i)] @@ -125,7 +123,7 @@ cdef class StateClass: def R_(self, int i, int idx): return self.doc[self.c.R(i, idx)] - + def empty(self): return self.c.empty() @@ -134,7 +132,7 @@ cdef class StateClass: def at_break(self): return False - #return self.c.at_break() + # return self.c.at_break() def has_head(self, int i): return self.c.has_head(i) diff --git a/spacy/pipeline/_parser_internals/transition_system.pxd b/spacy/pipeline/_parser_internals/transition_system.pxd index ce17480d4..04cd10d88 100644 --- a/spacy/pipeline/_parser_internals/transition_system.pxd +++ b/spacy/pipeline/_parser_internals/transition_system.pxd @@ -20,11 +20,15 @@ cdef struct Transition: int (*do)(StateC* state, attr_t label) nogil -ctypedef weight_t (*get_cost_func_t)(const StateC* state, const void* gold, - attr_tlabel) nogil -ctypedef weight_t (*move_cost_func_t)(const StateC* state, const void* gold) nogil -ctypedef weight_t (*label_cost_func_t)(const StateC* state, const void* - gold, attr_t label) nogil +ctypedef weight_t (*get_cost_func_t)( + const StateC* state, const void* gold, attr_tlabel +) nogil +ctypedef weight_t (*move_cost_func_t)( + const StateC* state, const void* gold +) nogil +ctypedef weight_t (*label_cost_func_t)( + const StateC* state, const void* gold, attr_t label +) nogil ctypedef int (*do_func_t)(StateC* state, attr_t label) nogil diff --git a/spacy/pipeline/_parser_internals/transition_system.pyx b/spacy/pipeline/_parser_internals/transition_system.pyx index 053c87f22..aabbdfa24 100644 --- a/spacy/pipeline/_parser_internals/transition_system.pyx +++ b/spacy/pipeline/_parser_internals/transition_system.pyx @@ -8,9 +8,7 @@ from collections import Counter import srsly from ...structs cimport TokenC -from ...tokens.doc cimport Doc from ...typedefs cimport attr_t, weight_t -from . cimport _beam_utils from .stateclass cimport StateClass from ... import util @@ -231,7 +229,6 @@ cdef class TransitionSystem: return self def to_bytes(self, exclude=tuple()): - transitions = [] serializers = { 'moves': lambda: srsly.json_dumps(self.labels), 'strings': lambda: self.strings.to_bytes(), diff --git a/spacy/pipeline/dep_parser.pyx b/spacy/pipeline/dep_parser.pyx index cb896c385..57f091788 100644 --- a/spacy/pipeline/dep_parser.pyx +++ b/spacy/pipeline/dep_parser.pyx @@ -1,6 +1,6 @@ # cython: infer_types=True, profile=True, binding=True from collections import defaultdict -from typing import Callable, Iterable, Optional +from typing import Callable, Optional from thinc.api import Config, Model @@ -124,6 +124,7 @@ def make_parser( scorer=scorer, ) + @Language.factory( "beam_parser", assigns=["token.dep", "token.head", "token.is_sent_start", "doc.sents"], diff --git a/spacy/pipeline/morphologizer.pyx b/spacy/pipeline/morphologizer.pyx index 4ca0ce165..7ca3908bd 100644 --- a/spacy/pipeline/morphologizer.pyx +++ b/spacy/pipeline/morphologizer.pyx @@ -2,7 +2,6 @@ from itertools import islice from typing import Callable, Dict, Optional, Union -import srsly from thinc.api import Config, Model, SequenceCategoricalCrossentropy from ..morphology cimport Morphology @@ -14,10 +13,8 @@ from ..errors import Errors from ..language import Language from ..parts_of_speech import IDS as POS_IDS from ..scorer import Scorer -from ..symbols import POS from ..training import validate_examples, validate_get_examples from ..util import registry -from .pipe import deserialize_config from .tagger import Tagger # See #9050 @@ -76,8 +73,11 @@ def morphologizer_score(examples, **kwargs): results = {} results.update(Scorer.score_token_attr(examples, "pos", **kwargs)) results.update(Scorer.score_token_attr(examples, "morph", getter=morph_key_getter, **kwargs)) - results.update(Scorer.score_token_attr_per_feat(examples, - "morph", getter=morph_key_getter, **kwargs)) + results.update( + Scorer.score_token_attr_per_feat( + examples, "morph", getter=morph_key_getter, **kwargs + ) + ) return results @@ -233,7 +233,6 @@ class Morphologizer(Tagger): if isinstance(docs, Doc): docs = [docs] cdef Doc doc - cdef Vocab vocab = self.vocab cdef bint overwrite = self.cfg["overwrite"] cdef bint extend = self.cfg["extend"] labels = self.labels diff --git a/spacy/pipeline/multitask.pyx b/spacy/pipeline/multitask.pyx index 6b62c0811..2a62a50d5 100644 --- a/spacy/pipeline/multitask.pyx +++ b/spacy/pipeline/multitask.pyx @@ -4,13 +4,10 @@ from typing import Optional import numpy from thinc.api import Config, CosineDistance, Model, set_dropout_rate, to_categorical -from ..tokens.doc cimport Doc - -from ..attrs import ID, POS +from ..attrs import ID from ..errors import Errors from ..language import Language from ..training import validate_examples -from ._parser_internals import nonproj from .tagger import Tagger from .trainable_pipe import TrainablePipe @@ -103,10 +100,9 @@ class MultitaskObjective(Tagger): cdef int idx = 0 correct = numpy.zeros((scores.shape[0],), dtype="i") guesses = scores.argmax(axis=1) - docs = [eg.predicted for eg in examples] for i, eg in enumerate(examples): # Handles alignment for tokenization differences - doc_annots = eg.get_aligned() # TODO + _doc_annots = eg.get_aligned() # TODO for j in range(len(eg.predicted)): tok_annots = {key: values[j] for key, values in tok_annots.items()} label = self.make_label(j, tok_annots) @@ -206,7 +202,6 @@ class ClozeMultitask(TrainablePipe): losses[self.name] = 0. set_dropout_rate(self.model, drop) validate_examples(examples, "ClozeMultitask.rehearse") - docs = [eg.predicted for eg in examples] predictions, bp_predictions = self.model.begin_update() loss, d_predictions = self.get_loss(examples, self.vocab.vectors.data, predictions) bp_predictions(d_predictions) diff --git a/spacy/pipeline/ner.pyx b/spacy/pipeline/ner.pyx index 8dd6c3c43..15c092ae9 100644 --- a/spacy/pipeline/ner.pyx +++ b/spacy/pipeline/ner.pyx @@ -1,6 +1,6 @@ # cython: infer_types=True, profile=True, binding=True from collections import defaultdict -from typing import Callable, Iterable, Optional +from typing import Callable, Optional from thinc.api import Config, Model @@ -10,7 +10,7 @@ from ._parser_internals.ner cimport BiluoPushDown from .transition_parser cimport Parser from ..language import Language -from ..scorer import PRFScore, get_ner_prf +from ..scorer import get_ner_prf from ..training import remove_bilu_prefix from ..util import registry @@ -100,6 +100,7 @@ def make_ner( scorer=scorer, ) + @Language.factory( "beam_ner", assigns=["doc.ents", "token.ent_iob", "token.ent_type"], diff --git a/spacy/pipeline/pipe.pyx b/spacy/pipeline/pipe.pyx index 42f518882..90775c465 100644 --- a/spacy/pipeline/pipe.pyx +++ b/spacy/pipeline/pipe.pyx @@ -1,6 +1,6 @@ # cython: infer_types=True, profile=True, binding=True import warnings -from typing import Callable, Dict, Iterable, Iterator, Optional, Tuple, Union +from typing import Callable, Dict, Iterable, Iterator, Tuple, Union import srsly @@ -40,7 +40,7 @@ cdef class Pipe: """ raise NotImplementedError(Errors.E931.format(parent="Pipe", method="__call__", name=self.name)) - def pipe(self, stream: Iterable[Doc], *, batch_size: int=128) -> Iterator[Doc]: + def pipe(self, stream: Iterable[Doc], *, batch_size: int = 128) -> Iterator[Doc]: """Apply the pipe to a stream of documents. This usually happens under the hood when the nlp object is called on a text and all components are applied to the Doc. @@ -59,7 +59,7 @@ cdef class Pipe: except Exception as e: error_handler(self.name, self, [doc], e) - def initialize(self, get_examples: Callable[[], Iterable[Example]], *, nlp: Language=None): + def initialize(self, get_examples: Callable[[], Iterable[Example]], *, nlp: Language = None): """Initialize the pipe. For non-trainable components, this method is optional. For trainable components, which should inherit from the subclass TrainablePipe, the provided data examples diff --git a/spacy/pipeline/sentencizer.pyx b/spacy/pipeline/sentencizer.pyx index 2fe7e1540..76f296644 100644 --- a/spacy/pipeline/sentencizer.pyx +++ b/spacy/pipeline/sentencizer.pyx @@ -7,13 +7,13 @@ from ..tokens.doc cimport Doc from .. import util from ..language import Language -from ..scorer import Scorer from .pipe import Pipe from .senter import senter_score # see #9050 BACKWARD_OVERWRITE = False + @Language.factory( "sentencizer", assigns=["token.is_sent_start", "doc.sents"], @@ -36,17 +36,19 @@ class Sentencizer(Pipe): DOCS: https://spacy.io/api/sentencizer """ - default_punct_chars = ['!', '.', '?', '։', '؟', '۔', '܀', '܁', '܂', '߹', - '।', '॥', '၊', '။', '።', '፧', '፨', '᙮', '᜵', '᜶', '᠃', '᠉', '᥄', - '᥅', '᪨', '᪩', '᪪', '᪫', '᭚', '᭛', '᭞', '᭟', '᰻', '᰼', '᱾', '᱿', - '‼', '‽', '⁇', '⁈', '⁉', '⸮', '⸼', '꓿', '꘎', '꘏', '꛳', '꛷', '꡶', - '꡷', '꣎', '꣏', '꤯', '꧈', '꧉', '꩝', '꩞', '꩟', '꫰', '꫱', '꯫', '﹒', - '﹖', '﹗', '！', '．', '？', '𐩖', '𐩗', '𑁇', '𑁈', '𑂾', '𑂿', '𑃀', - '𑃁', '𑅁', '𑅂', '𑅃', '𑇅', '𑇆', '𑇍', '𑇞', '𑇟', '𑈸', '𑈹', '𑈻', '𑈼', - '𑊩', '𑑋', '𑑌', '𑗂', '𑗃', '𑗉', '𑗊', '𑗋', '𑗌', '𑗍', '𑗎', '𑗏', '𑗐', - '𑗑', '𑗒', '𑗓', '𑗔', '𑗕', '𑗖', '𑗗', '𑙁', '𑙂', '𑜼', '𑜽', '𑜾', '𑩂', - '𑩃', '𑪛', '𑪜', '𑱁', '𑱂', '𖩮', '𖩯', '𖫵', '𖬷', '𖬸', '𖭄', '𛲟', '𝪈', - '｡', '。'] + default_punct_chars = [ + '!', '.', '?', '։', '؟', '۔', '܀', '܁', '܂', '߹', + '।', '॥', '၊', '။', '።', '፧', '፨', '᙮', '᜵', '᜶', '᠃', '᠉', '᥄', + '᥅', '᪨', '᪩', '᪪', '᪫', '᭚', '᭛', '᭞', '᭟', '᰻', '᰼', '᱾', '᱿', + '‼', '‽', '⁇', '⁈', '⁉', '⸮', '⸼', '꓿', '꘎', '꘏', '꛳', '꛷', '꡶', + '꡷', '꣎', '꣏', '꤯', '꧈', '꧉', '꩝', '꩞', '꩟', '꫰', '꫱', '꯫', '﹒', + '﹖', '﹗', '！', '．', '？', '𐩖', '𐩗', '𑁇', '𑁈', '𑂾', '𑂿', '𑃀', + '𑃁', '𑅁', '𑅂', '𑅃', '𑇅', '𑇆', '𑇍', '𑇞', '𑇟', '𑈸', '𑈹', '𑈻', '𑈼', + '𑊩', '𑑋', '𑑌', '𑗂', '𑗃', '𑗉', '𑗊', '𑗋', '𑗌', '𑗍', '𑗎', '𑗏', '𑗐', + '𑗑', '𑗒', '𑗓', '𑗔', '𑗕', '𑗖', '𑗗', '𑙁', '𑙂', '𑜼', '𑜽', '𑜾', '𑩂', + '𑩃', '𑪛', '𑪜', '𑱁', '𑱂', '𖩮', '𖩯', '𖫵', '𖬷', '𖬸', '𖭄', '𛲟', '𝪈', + '｡', '。' + ] def __init__( self, @@ -128,7 +130,6 @@ class Sentencizer(Pipe): if isinstance(docs, Doc): docs = [docs] cdef Doc doc - cdef int idx = 0 for i, doc in enumerate(docs): doc_tag_ids = batch_tag_ids[i] for j, tag_id in enumerate(doc_tag_ids): @@ -169,7 +170,6 @@ class Sentencizer(Pipe): path = path.with_suffix(".json") srsly.write_json(path, {"punct_chars": list(self.punct_chars), "overwrite": self.overwrite}) - def from_disk(self, path, *, exclude=tuple()): """Load the sentencizer from disk. diff --git a/spacy/pipeline/senter.pyx b/spacy/pipeline/senter.pyx index 26f98ba59..37ddcc3c0 100644 --- a/spacy/pipeline/senter.pyx +++ b/spacy/pipeline/senter.pyx @@ -2,7 +2,6 @@ from itertools import islice from typing import Callable, Optional -import srsly from thinc.api import Config, Model, SequenceCategoricalCrossentropy from ..tokens.doc cimport Doc diff --git a/spacy/pipeline/tagger.pyx b/spacy/pipeline/tagger.pyx index 47aae2bb7..4c5265a78 100644 --- a/spacy/pipeline/tagger.pyx +++ b/spacy/pipeline/tagger.pyx @@ -1,26 +1,18 @@ # cython: infer_types=True, profile=True, binding=True -import warnings from itertools import islice from typing import Callable, Optional import numpy -import srsly from thinc.api import Config, Model, SequenceCategoricalCrossentropy, set_dropout_rate -from thinc.types import Floats2d -from ..morphology cimport Morphology from ..tokens.doc cimport Doc -from ..vocab cimport Vocab from .. import util -from ..attrs import ID, POS -from ..errors import Errors, Warnings +from ..errors import Errors from ..language import Language -from ..parts_of_speech import X from ..scorer import Scorer from ..training import validate_examples, validate_get_examples from ..util import registry -from .pipe import deserialize_config from .trainable_pipe import TrainablePipe # See #9050 @@ -169,7 +161,6 @@ class Tagger(TrainablePipe): if isinstance(docs, Doc): docs = [docs] cdef Doc doc - cdef Vocab vocab = self.vocab cdef bint overwrite = self.cfg["overwrite"] labels = self.labels for i, doc in enumerate(docs): diff --git a/spacy/pipeline/trainable_pipe.pyx b/spacy/pipeline/trainable_pipe.pyx index 7aa91ac16..e5865e070 100644 --- a/spacy/pipeline/trainable_pipe.pyx +++ b/spacy/pipeline/trainable_pipe.pyx @@ -55,7 +55,7 @@ cdef class TrainablePipe(Pipe): except Exception as e: error_handler(self.name, self, [doc], e) - def pipe(self, stream: Iterable[Doc], *, batch_size: int=128) -> Iterator[Doc]: + def pipe(self, stream: Iterable[Doc], *, batch_size: int = 128) -> Iterator[Doc]: """Apply the pipe to a stream of documents. This usually happens under the hood when the nlp object is called on a text and all components are applied to the Doc. @@ -102,9 +102,9 @@ cdef class TrainablePipe(Pipe): def update(self, examples: Iterable["Example"], *, - drop: float=0.0, - sgd: Optimizer=None, - losses: Optional[Dict[str, float]]=None) -> Dict[str, float]: + drop: float = 0.0, + sgd: Optimizer = None, + losses: Optional[Dict[str, float]] = None) -> Dict[str, float]: """Learn from a batch of documents and gold-standard information, updating the pipe's model. Delegates to predict and get_loss. @@ -138,8 +138,8 @@ cdef class TrainablePipe(Pipe): def rehearse(self, examples: Iterable[Example], *, - sgd: Optimizer=None, - losses: Dict[str, float]=None, + sgd: Optimizer = None, + losses: Dict[str, float] = None, **config) -> Dict[str, float]: """Perform a "rehearsal" update from a batch of data. Rehearsal updates teach the current model to make predictions similar to an initial model, @@ -177,7 +177,7 @@ cdef class TrainablePipe(Pipe): """ return util.create_default_optimizer() - def initialize(self, get_examples: Callable[[], Iterable[Example]], *, nlp: Language=None): + def initialize(self, get_examples: Callable[[], Iterable[Example]], *, nlp: Language = None): """Initialize the pipe for training, using data examples if available. This method needs to be implemented by each TrainablePipe component, ensuring the internal model (if available) is initialized properly diff --git a/spacy/pipeline/transition_parser.pxd b/spacy/pipeline/transition_parser.pxd index e5e88d521..7ddb91e01 100644 --- a/spacy/pipeline/transition_parser.pxd +++ b/spacy/pipeline/transition_parser.pxd @@ -13,8 +13,18 @@ cdef class Parser(TrainablePipe): cdef readonly TransitionSystem moves cdef public object _multitasks - cdef void _parseC(self, CBlas cblas, StateC** states, - WeightsC weights, SizesC sizes) nogil + cdef void _parseC( + self, + CBlas cblas, + StateC** states, + WeightsC weights, + SizesC sizes + ) nogil - cdef void c_transition_batch(self, StateC** states, const float* scores, - int nr_class, int batch_size) nogil + cdef void c_transition_batch( + self, + StateC** states, + const float* scores, + int nr_class, + int batch_size + ) nogil diff --git a/spacy/pipeline/transition_parser.pyx b/spacy/pipeline/transition_parser.pyx index ef4d9b362..11c8fafc7 100644 --- a/spacy/pipeline/transition_parser.pyx +++ b/spacy/pipeline/transition_parser.pyx @@ -7,20 +7,15 @@ from cymem.cymem cimport Pool from itertools import islice from libc.stdlib cimport calloc, free -from libc.string cimport memcpy, memset +from libc.string cimport memset from libcpp.vector cimport vector import random -import srsly -from thinc.api import CupyOps, NumpyOps, get_ops, set_dropout_rate - -from thinc.extra.search cimport Beam - -import warnings - import numpy import numpy.random +import srsly +from thinc.api import CupyOps, NumpyOps, set_dropout_rate from ..ml.parser_model cimport ( ActivationsC, @@ -42,7 +37,7 @@ from .trainable_pipe import TrainablePipe from ._parser_internals cimport _beam_utils from .. import util -from ..errors import Errors, Warnings +from ..errors import Errors from ..training import validate_examples, validate_get_examples from ._parser_internals import _beam_utils @@ -258,7 +253,6 @@ cdef class Parser(TrainablePipe): except Exception as e: error_handler(self.name, self, batch_in_order, e) - def predict(self, docs): if isinstance(docs, Doc): docs = [docs] @@ -300,8 +294,6 @@ cdef class Parser(TrainablePipe): return batch def beam_parse(self, docs, int beam_width, float drop=0., beam_density=0.): - cdef Beam beam - cdef Doc doc self._ensure_labels_are_added(docs) batch = _beam_utils.BeamBatch( self.moves, @@ -321,16 +313,18 @@ cdef class Parser(TrainablePipe): del model return list(batch) - cdef void _parseC(self, CBlas cblas, StateC** states, - WeightsC weights, SizesC sizes) nogil: - cdef int i, j + cdef void _parseC( + self, CBlas cblas, StateC** states, WeightsC weights, SizesC sizes + ) nogil: + cdef int i cdef vector[StateC*] unfinished cdef ActivationsC activations = alloc_activations(sizes) while sizes.states >= 1: predict_states(cblas, &activations, states, &weights, sizes) # Validate actions, argmax, take action. - self.c_transition_batch(states, - activations.scores, sizes.classes, sizes.states) + self.c_transition_batch( + states, activations.scores, sizes.classes, sizes.states + ) for i in range(sizes.states): if not states[i].is_final(): unfinished.push_back(states[i]) @@ -342,7 +336,6 @@ cdef class Parser(TrainablePipe): def set_annotations(self, docs, states_or_beams): cdef StateClass state - cdef Beam beam cdef Doc doc states = _beam_utils.collect_states(states_or_beams, docs) for i, (state, doc) in enumerate(zip(states, docs)): @@ -359,8 +352,13 @@ cdef class Parser(TrainablePipe): self.c_transition_batch(&c_states[0], c_scores, scores.shape[1], scores.shape[0]) return [state for state in states if not state.c.is_final()] - cdef void c_transition_batch(self, StateC** states, const float* scores, - int nr_class, int batch_size) nogil: + cdef void c_transition_batch( + self, + StateC** states, + const float* scores, + int nr_class, + int batch_size + ) nogil: # n_moves should not be zero at this point, but make sure to avoid zero-length mem alloc with gil: assert self.moves.n_moves > 0, Errors.E924.format(name=self.name) @@ -380,7 +378,6 @@ cdef class Parser(TrainablePipe): free(is_valid) def update(self, examples, *, drop=0., sgd=None, losses=None): - cdef StateClass state if losses is None: losses = {} losses.setdefault(self.name, 0.) @@ -419,8 +416,7 @@ cdef class Parser(TrainablePipe): if not states: return losses model, backprop_tok2vec = self.model.begin_update([eg.x for eg in examples]) - - all_states = list(states) + states_golds = list(zip(states, golds)) n_moves = 0 while states_golds: @@ -500,8 +496,16 @@ cdef class Parser(TrainablePipe): del tutor return losses - def update_beam(self, examples, *, beam_width, - drop=0., sgd=None, losses=None, beam_density=0.0): + def update_beam( + self, + examples, + *, + beam_width, + drop=0., + sgd=None, + losses=None, + beam_density=0.0 + ): states, golds, _ = self.moves.init_gold_batch(examples) if not states: return losses @@ -531,8 +535,9 @@ cdef class Parser(TrainablePipe): is_valid = mem.alloc(self.moves.n_moves, sizeof(int)) costs = mem.alloc(self.moves.n_moves, sizeof(float)) - cdef np.ndarray d_scores = numpy.zeros((len(states), self.moves.n_moves), - dtype='f', order='C') + cdef np.ndarray d_scores = numpy.zeros( + (len(states), self.moves.n_moves), dtype='f', order='C' + ) c_d_scores = d_scores.data unseen_classes = self.model.attrs["unseen_classes"] for i, (state, gold) in enumerate(zip(states, golds)): @@ -542,8 +547,9 @@ cdef class Parser(TrainablePipe): for j in range(self.moves.n_moves): if costs[j] <= 0.0 and j in unseen_classes: unseen_classes.remove(j) - cpu_log_loss(c_d_scores, - costs, is_valid, &scores[i, 0], d_scores.shape[1]) + cpu_log_loss( + c_d_scores, costs, is_valid, &scores[i, 0], d_scores.shape[1] + ) c_d_scores += d_scores.shape[1] # Note that we don't normalize this. See comment in update() for why. if losses is not None: diff --git a/spacy/strings.pyx b/spacy/strings.pyx index 16c3e2b5b..b0799d6fc 100644 --- a/spacy/strings.pyx +++ b/spacy/strings.pyx @@ -2,7 +2,6 @@ cimport cython from libc.stdint cimport uint32_t from libc.string cimport memcpy -from libcpp.set cimport set from murmurhash.mrmr cimport hash32, hash64 import srsly @@ -20,9 +19,10 @@ cdef inline bint _try_coerce_to_hash(object key, hash_t* out_hash): try: out_hash[0] = key return True - except: + except: # no-cython-lint return False + def get_string_id(key): """Get a string ID, handling the reserved symbols correctly. If the key is already an ID, return it. @@ -87,7 +87,6 @@ cdef Utf8Str* _allocate(Pool mem, const unsigned char* chars, uint32_t length) e cdef int n_length_bytes cdef int i cdef Utf8Str* string = mem.alloc(1, sizeof(Utf8Str)) - cdef uint32_t ulength = length if length < sizeof(string.s): string.s[0] = length memcpy(&string.s[1], chars, length) diff --git a/spacy/structs.pxd b/spacy/structs.pxd index 9efb068fd..8cfcc2964 100644 --- a/spacy/structs.pxd +++ b/spacy/structs.pxd @@ -52,7 +52,7 @@ cdef struct TokenC: int sent_start int ent_iob - attr_t ent_type # TODO: Is there a better way to do this? Multiple sources of truth.. + attr_t ent_type # TODO: Is there a better way to do this? Multiple sources of truth.. attr_t ent_kb_id hash_t ent_id diff --git a/spacy/symbols.pxd b/spacy/symbols.pxd index bc15d9b80..73be19145 100644 --- a/spacy/symbols.pxd +++ b/spacy/symbols.pxd @@ -92,7 +92,7 @@ cdef enum symbol_t: ADV AUX CONJ - CCONJ # U20 + CCONJ # U20 DET INTJ NOUN @@ -418,7 +418,7 @@ cdef enum symbol_t: ccomp complm conj - cop # U20 + cop # U20 csubj csubjpass dep @@ -441,8 +441,8 @@ cdef enum symbol_t: num number oprd - obj # U20 - obl # U20 + obj # U20 + obl # U20 parataxis partmod pcomp diff --git a/spacy/symbols.pyx b/spacy/symbols.pyx index b0345c710..d1deeb0e7 100644 --- a/spacy/symbols.pyx +++ b/spacy/symbols.pyx @@ -96,7 +96,7 @@ IDS = { "ADV": ADV, "AUX": AUX, "CONJ": CONJ, - "CCONJ": CCONJ, # U20 + "CCONJ": CCONJ, # U20 "DET": DET, "INTJ": INTJ, "NOUN": NOUN, @@ -421,7 +421,7 @@ IDS = { "ccomp": ccomp, "complm": complm, "conj": conj, - "cop": cop, # U20 + "cop": cop, # U20 "csubj": csubj, "csubjpass": csubjpass, "dep": dep, @@ -444,8 +444,8 @@ IDS = { "num": num, "number": number, "oprd": oprd, - "obj": obj, # U20 - "obl": obl, # U20 + "obj": obj, # U20 + "obl": obl, # U20 "parataxis": parataxis, "partmod": partmod, "pcomp": pcomp, diff --git a/spacy/tests/package/test_requirements.py b/spacy/tests/package/test_requirements.py index 9e83d5fb1..fab1e8218 100644 --- a/spacy/tests/package/test_requirements.py +++ b/spacy/tests/package/test_requirements.py @@ -12,6 +12,7 @@ def test_build_dependencies(): "flake8", "hypothesis", "pre-commit", + "cython-lint", "black", "isort", "mypy", diff --git a/spacy/tokenizer.pxd b/spacy/tokenizer.pxd index f7585b45a..a902ebad9 100644 --- a/spacy/tokenizer.pxd +++ b/spacy/tokenizer.pxd @@ -31,24 +31,58 @@ cdef class Tokenizer: cdef Doc _tokenize_affixes(self, str string, bint with_special_cases) cdef int _apply_special_cases(self, Doc doc) except -1 - cdef void _filter_special_spans(self, vector[SpanC] &original, - vector[SpanC] &filtered, int doc_len) nogil - cdef object _prepare_special_spans(self, Doc doc, - vector[SpanC] &filtered) - cdef int _retokenize_special_spans(self, Doc doc, TokenC* tokens, - object span_data) - cdef int _try_specials_and_cache(self, hash_t key, Doc tokens, - int* has_special, - bint with_special_cases) except -1 - cdef int _tokenize(self, Doc tokens, str span, hash_t key, - int* has_special, bint with_special_cases) except -1 - cdef str _split_affixes(self, Pool mem, str string, - vector[LexemeC*] *prefixes, - vector[LexemeC*] *suffixes, int* has_special, - bint with_special_cases) - cdef int _attach_tokens(self, Doc tokens, str string, - vector[LexemeC*] *prefixes, - vector[LexemeC*] *suffixes, int* has_special, - bint with_special_cases) except -1 - cdef int _save_cached(self, const TokenC* tokens, hash_t key, - int* has_special, int n) except -1 + cdef void _filter_special_spans( + self, + vector[SpanC] &original, + vector[SpanC] &filtered, + int doc_len, + ) nogil + cdef object _prepare_special_spans( + self, + Doc doc, + vector[SpanC] &filtered, + ) + cdef int _retokenize_special_spans( + self, + Doc doc, + TokenC* tokens, + object span_data, + ) + cdef int _try_specials_and_cache( + self, + hash_t key, + Doc tokens, + int* has_special, + bint with_special_cases, + ) except -1 + cdef int _tokenize( + self, + Doc tokens, + str span, + hash_t key, + int* has_special, + bint with_special_cases, + ) except -1 + cdef str _split_affixes( + self, + Pool mem, + str string, + vector[LexemeC*] *prefixes, + vector[LexemeC*] *suffixes, int* has_special, + bint with_special_cases, + ) + cdef int _attach_tokens( + self, + Doc tokens, + str string, + vector[LexemeC*] *prefixes, + vector[LexemeC*] *suffixes, int* has_special, + bint with_special_cases, + ) except -1 + cdef int _save_cached( + self, + const TokenC* tokens, + hash_t key, + int* has_special, + int n, + ) except -1 diff --git a/spacy/tokenizer.pyx b/spacy/tokenizer.pyx index 3861b1cee..8fc95bea0 100644 --- a/spacy/tokenizer.pyx +++ b/spacy/tokenizer.pyx @@ -8,20 +8,18 @@ from libcpp.set cimport set as stdset from preshed.maps cimport PreshMap import re -import warnings - from .lexeme cimport EMPTY_LEXEME from .strings cimport hash_string from .tokens.doc cimport Doc from . import util from .attrs import intify_attrs -from .errors import Errors, Warnings +from .errors import Errors from .scorer import Scorer from .symbols import NORM, ORTH from .tokens import Span from .training import validate_examples -from .util import get_words_and_spaces, registry +from .util import get_words_and_spaces cdef class Tokenizer: @@ -324,7 +322,7 @@ cdef class Tokenizer: cdef int span_start cdef int span_end while i < doc.length: - if not i in span_data: + if i not in span_data: tokens[i + offset] = doc.c[i] i += 1 else: @@ -395,12 +393,15 @@ cdef class Tokenizer: self._save_cached(&tokens.c[orig_size], orig_key, has_special, tokens.length - orig_size) - cdef str _split_affixes(self, Pool mem, str string, - vector[const LexemeC*] *prefixes, - vector[const LexemeC*] *suffixes, - int* has_special, - bint with_special_cases): - cdef size_t i + cdef str _split_affixes( + self, + Pool mem, + str string, + vector[const LexemeC*] *prefixes, + vector[const LexemeC*] *suffixes, + int* has_special, + bint with_special_cases + ): cdef str prefix cdef str suffix cdef str minus_pre @@ -445,10 +446,6 @@ cdef class Tokenizer: vector[const LexemeC*] *suffixes, int* has_special, bint with_special_cases) except -1: - cdef bint specials_hit = 0 - cdef bint cache_hit = 0 - cdef int split, end - cdef const LexemeC* const* lexemes cdef const LexemeC* lexeme cdef str span cdef int i @@ -458,9 +455,11 @@ cdef class Tokenizer: if string: if self._try_specials_and_cache(hash_string(string), tokens, has_special, with_special_cases): pass - elif (self.token_match and self.token_match(string)) or \ - (self.url_match and \ - self.url_match(string)): + elif ( + (self.token_match and self.token_match(string)) or + (self.url_match and self.url_match(string)) + ): + # We're always saying 'no' to spaces here -- the caller will # fix up the outermost one, with reference to the original. # See Issue #859 @@ -821,7 +820,7 @@ cdef class Tokenizer: self.infix_finditer = None self.token_match = None self.url_match = None - msg = util.from_bytes(bytes_data, deserializers, exclude) + util.from_bytes(bytes_data, deserializers, exclude) if "prefix_search" in data and isinstance(data["prefix_search"], str): self.prefix_search = re.compile(data["prefix_search"]).search if "suffix_search" in data and isinstance(data["suffix_search"], str): diff --git a/spacy/tokens/_retokenize.pyx b/spacy/tokens/_retokenize.pyx index 8ed707ab9..f28d2e088 100644 --- a/spacy/tokens/_retokenize.pyx +++ b/spacy/tokens/_retokenize.pyx @@ -1,7 +1,6 @@ # cython: infer_types=True, bounds_check=False, profile=True from cymem.cymem cimport Pool -from libc.stdlib cimport free, malloc -from libc.string cimport memcpy, memset +from libc.string cimport memset import numpy from thinc.api import get_array_module @@ -10,7 +9,7 @@ from ..attrs cimport MORPH, NORM from ..lexeme cimport EMPTY_LEXEME, Lexeme from ..structs cimport LexemeC, TokenC from ..vocab cimport Vocab -from .doc cimport Doc, set_children_from_heads, token_by_end, token_by_start +from .doc cimport Doc, set_children_from_heads, token_by_start from .span cimport Span from .token cimport Token @@ -147,7 +146,7 @@ def _merge(Doc doc, merges): syntactic root of the span. RETURNS (Token): The first newly merged token. """ - cdef int i, merge_index, start, end, token_index, current_span_index, current_offset, offset, span_index + cdef int i, merge_index, start, token_index, current_span_index, current_offset, offset, span_index cdef Span span cdef const LexemeC* lex cdef TokenC* token @@ -165,7 +164,6 @@ def _merge(Doc doc, merges): merges.sort(key=_get_start) for merge_index, (span, attributes) in enumerate(merges): start = span.start - end = span.end spans.append(span) # House the new merged token where it starts token = &doc.c[start] @@ -203,8 +201,9 @@ def _merge(Doc doc, merges): # for the merged region. To do this, we create a boolean array indicating # whether the row is to be deleted, then use numpy.delete if doc.tensor is not None and doc.tensor.size != 0: - doc.tensor = _resize_tensor(doc.tensor, - [(m[0].start, m[0].end) for m in merges]) + doc.tensor = _resize_tensor( + doc.tensor, [(m[0].start, m[0].end) for m in merges] + ) # Memorize span roots and sets dependencies of the newly merged # tokens to the dependencies of their roots. span_roots = [] @@ -267,11 +266,11 @@ def _merge(Doc doc, merges): span_index += 1 if span_index < len(spans) and i == spans[span_index].start: # First token in a span - doc.c[i - offset] = doc.c[i] # move token to its place + doc.c[i - offset] = doc.c[i] # move token to its place offset += (spans[span_index].end - spans[span_index].start) - 1 in_span = True if not in_span: - doc.c[i - offset] = doc.c[i] # move token to its place + doc.c[i - offset] = doc.c[i] # move token to its place for i in range(doc.length - offset, doc.length): memset(&doc.c[i], 0, sizeof(TokenC)) @@ -345,7 +344,11 @@ def _split(Doc doc, int token_index, orths, heads, attrs): if to_process_tensor: xp = get_array_module(doc.tensor) if xp is numpy: - doc.tensor = xp.append(doc.tensor, xp.zeros((nb_subtokens,doc.tensor.shape[1]), dtype="float32"), axis=0) + doc.tensor = xp.append( + doc.tensor, + xp.zeros((nb_subtokens, doc.tensor.shape[1]), dtype="float32"), + axis=0 + ) else: shape = (doc.tensor.shape[0] + nb_subtokens, doc.tensor.shape[1]) resized_array = xp.zeros(shape, dtype="float32") @@ -367,7 +370,8 @@ def _split(Doc doc, int token_index, orths, heads, attrs): token.norm = 0 # reset norm if to_process_tensor: # setting the tensors of the split tokens to array of zeros - doc.tensor[token_index + i:token_index + i + 1] = xp.zeros((1,doc.tensor.shape[1]), dtype="float32") + doc.tensor[token_index + i:token_index + i + 1] = \ + xp.zeros((1, doc.tensor.shape[1]), dtype="float32") # Update the character offset of the subtokens if i != 0: token.idx = orig_token.idx + idx_offset @@ -455,7 +459,6 @@ def normalize_token_attrs(Vocab vocab, attrs): def set_token_attrs(Token py_token, attrs): cdef TokenC* token = py_token.c cdef const LexemeC* lex = token.lex - cdef Doc doc = py_token.doc # Assign attributes for attr_name, attr_value in attrs.items(): if attr_name == "_": # Set extension attributes diff --git a/spacy/tokens/doc.pxd b/spacy/tokens/doc.pxd index d7f092c94..d9719609c 100644 --- a/spacy/tokens/doc.pxd +++ b/spacy/tokens/doc.pxd @@ -31,7 +31,7 @@ cdef int token_by_start(const TokenC* tokens, int length, int start_char) except cdef int token_by_end(const TokenC* tokens, int length, int end_char) except -2 -cdef int [:,:] _get_lca_matrix(Doc, int start, int end) +cdef int [:, :] _get_lca_matrix(Doc, int start, int end) cdef class Doc: @@ -61,7 +61,6 @@ cdef class Doc: cdef int length cdef int max_length - cdef public object noun_chunks_iterator cdef object __weakref__ diff --git a/spacy/tokens/doc.pyx b/spacy/tokens/doc.pyx index 146b276e2..8fc2c4b3c 100644 --- a/spacy/tokens/doc.pyx +++ b/spacy/tokens/doc.pyx @@ -43,14 +43,13 @@ from ..attrs cimport ( attr_id_t, ) from ..lexeme cimport EMPTY_LEXEME, Lexeme -from ..typedefs cimport attr_t, flags_t +from ..typedefs cimport attr_t from .token cimport Token from .. import parts_of_speech, schemas, util from ..attrs import IDS, intify_attr -from ..compat import copy_reg, pickle +from ..compat import copy_reg from ..errors import Errors, Warnings -from ..morphology import Morphology from ..util import get_words_and_spaces from ._retokenize import Retokenizer from .underscore import Underscore, get_ext_args @@ -784,7 +783,7 @@ cdef class Doc: # TODO: # 1. Test basic data-driven ORTH gazetteer # 2. Test more nuanced date and currency regex - cdef attr_t entity_type, kb_id, ent_id + cdef attr_t kb_id, ent_id cdef int ent_start, ent_end ent_spans = [] for ent_info in ents: @@ -987,7 +986,6 @@ cdef class Doc: >>> np_array = doc.to_array([LOWER, POS, ENT_TYPE, IS_ALPHA]) """ cdef int i, j - cdef attr_id_t feature cdef np.ndarray[attr_t, ndim=2] output # Handle scalar/list inputs of strings/ints for py_attr_ids # See also #3064 @@ -999,8 +997,10 @@ cdef class Doc: py_attr_ids = [py_attr_ids] # Allow strings, e.g. 'lemma' or 'LEMMA' try: - py_attr_ids = [(IDS[id_.upper()] if hasattr(id_, "upper") else id_) - for id_ in py_attr_ids] + py_attr_ids = [ + (IDS[id_.upper()] if hasattr(id_, "upper") else id_) + for id_ in py_attr_ids + ] except KeyError as msg: keys = [k for k in IDS.keys() if not k.startswith("FLAG")] raise KeyError(Errors.E983.format(dict="IDS", key=msg, keys=keys)) from None @@ -1030,8 +1030,6 @@ cdef class Doc: DOCS: https://spacy.io/api/doc#count_by """ cdef int i - cdef attr_t attr - cdef size_t count if counts is None: counts = Counter() @@ -1093,7 +1091,6 @@ cdef class Doc: cdef int i, col cdef int32_t abs_head_index cdef attr_id_t attr_id - cdef TokenC* tokens = self.c cdef int length = len(array) if length != len(self): raise ValueError(Errors.E971.format(array_length=length, doc_length=len(self))) @@ -1225,7 +1222,7 @@ cdef class Doc: span.label, span.kb_id, span.id, - span.text, # included as a check + span.text, # included as a check )) char_offset += len(doc.text) if len(doc) > 0 and ensure_whitespace and not doc[-1].is_space and not bool(doc[-1].whitespace_): @@ -1508,7 +1505,6 @@ cdef class Doc: attributes are inherited from the syntactic root of the span. RETURNS (Token): The first newly merged token. """ - cdef str tag, lemma, ent_type attr_len = len(attributes) span_len = len(spans) if not attr_len == span_len: @@ -1624,7 +1620,6 @@ cdef class Doc: for token in char_span[1:]: token.is_sent_start = False - for span_group in doc_json.get("spans", {}): spans = [] for span in doc_json["spans"][span_group]: @@ -1656,7 +1651,7 @@ cdef class Doc: start = token_by_char(self.c, self.length, token_data["start"]) value = token_data["value"] self[start]._.set(token_attr, value) - + for span_attr in doc_json.get("underscore_span", {}): if not Span.has_extension(span_attr): Span.set_extension(span_attr) @@ -1698,7 +1693,7 @@ cdef class Doc: token_data["dep"] = token.dep_ token_data["head"] = token.head.i data["tokens"].append(token_data) - + if self.spans: data["spans"] = {} for span_group in self.spans: @@ -1769,7 +1764,6 @@ cdef class Doc: output.fill(255) cdef int i, j, start_idx, end_idx cdef bytes byte_string - cdef unsigned char utf8_char for i, byte_string in enumerate(byte_strings): j = 0 start_idx = 0 @@ -1822,8 +1816,6 @@ cdef int token_by_char(const TokenC* tokens, int length, int char_idx) except -2 cdef int set_children_from_heads(TokenC* tokens, int start, int end) except -1: # note: end is exclusive - cdef TokenC* head - cdef TokenC* child cdef int i # Set number of left/right children to 0. We'll increment it in the loops. for i in range(start, end): @@ -1923,7 +1915,7 @@ cdef int _get_tokens_lca(Token token_j, Token token_k): return -1 -cdef int [:,:] _get_lca_matrix(Doc doc, int start, int end): +cdef int [:, :] _get_lca_matrix(Doc doc, int start, int end): """Given a doc and a start and end position defining a set of contiguous tokens within it, returns a matrix of Lowest Common Ancestors (LCA), where LCA[i, j] is the index of the lowest common ancestor among token i and j. @@ -1936,7 +1928,7 @@ cdef int [:,:] _get_lca_matrix(Doc doc, int start, int end): RETURNS (int [:, :]): memoryview of numpy.array[ndim=2, dtype=numpy.int32], with shape (n, n), where n = len(doc). """ - cdef int [:,:] lca_matrix + cdef int [:, :] lca_matrix cdef int j, k n_tokens= end - start lca_mat = numpy.empty((n_tokens, n_tokens), dtype=numpy.int32) diff --git a/spacy/tokens/graph.pyx b/spacy/tokens/graph.pyx index 47f0a20d4..1cbec09f4 100644 --- a/spacy/tokens/graph.pyx +++ b/spacy/tokens/graph.pyx @@ -3,7 +3,7 @@ from typing import Generator, List, Tuple cimport cython from cython.operator cimport dereference -from libc.stdint cimport int32_t, int64_t +from libc.stdint cimport int32_t from libcpp.pair cimport pair from libcpp.unordered_map cimport unordered_map from libcpp.unordered_set cimport unordered_set @@ -11,7 +11,6 @@ from libcpp.unordered_set cimport unordered_set import weakref from murmurhash.mrmr cimport hash64 -from preshed.maps cimport map_get_unless_missing from .. import Errors @@ -28,7 +27,7 @@ from .token import Token cdef class Edge: cdef readonly Graph graph cdef readonly int i - + def __init__(self, Graph graph, int i): self.graph = graph self.i = i @@ -44,7 +43,7 @@ cdef class Edge: @property def head(self) -> "Node": return Node(self.graph, self.graph.c.edges[self.i].head) - + @property def tail(self) -> "Tail": return Node(self.graph, self.graph.c.edges[self.i].tail) @@ -70,7 +69,7 @@ cdef class Node: def __init__(self, Graph graph, int i): """A reference to a node of an annotation graph. Each node is made up of an ordered set of zero or more token indices. - + Node references are usually created by the Graph object itself, or from the Node or Edge objects. You usually won't need to instantiate this class yourself. @@ -109,13 +108,13 @@ cdef class Node: @property def is_none(self) -> bool: """Whether the node is a special value, indicating 'none'. - + The NoneNode type is returned by the Graph, Edge and Node objects when there is no match to a query. It has the same API as Node, but it always returns NoneNode, NoneEdge or empty lists for its queries. """ return False - + @property def doc(self) -> "Doc": """The Doc object that the graph refers to.""" @@ -130,19 +129,19 @@ cdef class Node: def head(self, i=None, label=None) -> "Node": """Get the head of the first matching edge, searching by index, label, both or neither. - + For instance, `node.head(i=1)` will get the head of the second edge that this node is a tail of. `node.head(i=1, label="ARG0")` will further check that the second edge has the label `"ARG0"`. - + If no matching node can be found, the graph's NoneNode is returned. """ return self.headed(i=i, label=label) - + def tail(self, i=None, label=None) -> "Node": """Get the tail of the first matching edge, searching by index, label, both or neither. - + If no matching node can be found, the graph's NoneNode is returned. """ return self.tailed(i=i, label=label).tail @@ -171,7 +170,7 @@ cdef class Node: cdef vector[int] edge_indices self._find_edges(edge_indices, "head", label) return [Node(self.graph, self.graph.c.edges[i].head) for i in edge_indices] - + def tails(self, label=None) -> List["Node"]: """Find all matching tails of this node.""" cdef vector[int] edge_indices @@ -200,7 +199,7 @@ cdef class Node: return NoneEdge(self.graph) else: return Edge(self.graph, idx) - + def tailed(self, i=None, label=None) -> Edge: """Find the first matching edge tailed by this node. If no matching edge can be found, the graph's NoneEdge is returned. @@ -283,7 +282,7 @@ cdef class NoneEdge(Edge): def __init__(self, graph): self.graph = graph self.i = -1 - + @property def doc(self) -> "Doc": return self.graph.doc @@ -291,7 +290,7 @@ cdef class NoneEdge(Edge): @property def head(self) -> "NoneNode": return NoneNode(self.graph) - + @property def tail(self) -> "NoneNode": return NoneNode(self.graph) @@ -319,7 +318,7 @@ cdef class NoneNode(Node): def __len__(self): return 0 - + @property def is_none(self): return -1 @@ -340,14 +339,14 @@ cdef class NoneNode(Node): def walk_heads(self): yield from [] - + def walk_tails(self): yield from [] - + cdef class Graph: """A set of directed labelled relationships between sets of tokens. - + EXAMPLE: Construction 1 >>> graph = Graph(doc, name="srl") @@ -372,7 +371,9 @@ cdef class Graph: >>> assert graph.has_node((0,)) >>> assert graph.has_edge((0,), (1,3), label="agent") """ - def __init__(self, doc, *, name="", nodes=[], edges=[], labels=None, weights=None): + def __init__( + self, doc, *, name="", nodes=[], edges=[], labels=None, weights=None # no-cython-lint + ): """Create a Graph object. doc (Doc): The Doc object the graph will refer to. @@ -438,13 +439,11 @@ cdef class Graph: def add_edge(self, head, tail, *, label="", weight=None) -> Edge: """Add an edge to the graph, connecting two groups of tokens. - + If there is already an edge for the (head, tail, label) triple, it will be returned, and no new edge will be created. The weight of the edge will be updated if a weight is specified. """ - label_hash = self.doc.vocab.strings.as_int(label) - weight_float = weight if weight is not None else 0.0 edge_index = add_edge( &self.c, EdgeC( @@ -478,11 +477,11 @@ cdef class Graph: def has_edge(self, head, tail, label) -> bool: """Check whether a (head, tail, label) triple is an edge in the graph.""" return not self.get_edge(head, tail, label=label).is_none - + def add_node(self, indices) -> Node: """Add a node to the graph and return it. Nodes refer to ordered sets of token indices. - + This method is idempotent: if there is already a node for the given indices, it is returned without a new node being created. """ @@ -510,7 +509,7 @@ cdef class Graph: return NoneNode(self) else: return Node(self, node_index) - + def has_node(self, tuple indices) -> bool: """Check whether the graph has a node for the given indices.""" return not self.get_node(indices).is_none @@ -570,7 +569,7 @@ cdef int add_node(GraphC* graph, vector[int32_t]& node) nogil: graph.roots.insert(index) graph.node_map.insert(pair[hash_t, int](key, index)) return index - + cdef int get_node(const GraphC* graph, vector[int32_t] node) nogil: key = hash64(&node[0], node.size() * sizeof(node[0]), 0) diff --git a/spacy/tokens/morphanalysis.pyx b/spacy/tokens/morphanalysis.pyx index 0992a0b66..ba7c638f6 100644 --- a/spacy/tokens/morphanalysis.pyx +++ b/spacy/tokens/morphanalysis.pyx @@ -89,4 +89,3 @@ cdef class MorphAnalysis: def __repr__(self): return self.to_json() - diff --git a/spacy/tokens/span.pyx b/spacy/tokens/span.pyx index 59ee21687..cf90e416b 100644 --- a/spacy/tokens/span.pyx +++ b/spacy/tokens/span.pyx @@ -1,5 +1,4 @@ cimport numpy as np -from libc.math cimport sqrt import copy import warnings @@ -10,11 +9,10 @@ from thinc.api import get_array_module from ..attrs cimport * from ..attrs cimport ORTH, attr_id_t from ..lexeme cimport Lexeme -from ..parts_of_speech cimport univ_pos_t -from ..structs cimport LexemeC, TokenC +from ..structs cimport TokenC from ..symbols cimport dep -from ..typedefs cimport attr_t, flags_t, hash_t -from .doc cimport _get_lca_matrix, get_token_attr, token_by_end, token_by_start +from ..typedefs cimport attr_t, hash_t +from .doc cimport _get_lca_matrix, get_token_attr from .token cimport Token from ..errors import Errors, Warnings @@ -595,7 +593,6 @@ cdef class Span: """ return "".join([t.text_with_ws for t in self]) - @property def noun_chunks(self): """Iterate over the base noun phrases in the span. Yields base diff --git a/spacy/tokens/span_group.pyx b/spacy/tokens/span_group.pyx index 48ad4a516..d245a1425 100644 --- a/spacy/tokens/span_group.pyx +++ b/spacy/tokens/span_group.pyx @@ -1,7 +1,7 @@ import struct import weakref from copy import deepcopy -from typing import TYPE_CHECKING, Iterable, Optional, Tuple, Union +from typing import Iterable, Optional, Union import srsly @@ -34,7 +34,7 @@ cdef class SpanGroup: DOCS: https://spacy.io/api/spangroup """ - def __init__(self, doc, *, name="", attrs={}, spans=[]): + def __init__(self, doc, *, name="", attrs={}, spans=[]): # no-cython-lint """Create a SpanGroup. doc (Doc): The reference Doc object. @@ -311,7 +311,7 @@ cdef class SpanGroup: other_attrs = deepcopy(other_group.attrs) span_group.attrs.update({ - key: value for key, value in other_attrs.items() \ + key: value for key, value in other_attrs.items() if key not in span_group.attrs }) if len(other_group): diff --git a/spacy/tokens/token.pxd b/spacy/tokens/token.pxd index fc02ff624..f4e4611df 100644 --- a/spacy/tokens/token.pxd +++ b/spacy/tokens/token.pxd @@ -26,7 +26,7 @@ cdef class Token: cdef Token self = Token.__new__(Token, vocab, doc, offset) return self - #cdef inline TokenC struct_from_attrs(Vocab vocab, attrs): + # cdef inline TokenC struct_from_attrs(Vocab vocab, attrs): # cdef TokenC token # attrs = normalize_attrs(attrs) @@ -98,12 +98,10 @@ cdef class Token: elif feat_name == SENT_START: token.sent_start = value - @staticmethod cdef inline int missing_dep(const TokenC* token) nogil: return token.dep == MISSING_DEP - @staticmethod cdef inline int missing_head(const TokenC* token) nogil: return Token.missing_dep(token) diff --git a/spacy/tokens/token.pyx b/spacy/tokens/token.pyx index 6018c3112..de967ba25 100644 --- a/spacy/tokens/token.pyx +++ b/spacy/tokens/token.pyx @@ -1,13 +1,11 @@ # cython: infer_types=True # Compiler crashes on memory view coercion without this. Should report bug. cimport numpy as np -from cython.view cimport array as cvarray np.import_array() import warnings -import numpy from thinc.api import get_array_module from ..attrs cimport ( @@ -238,7 +236,7 @@ cdef class Token: result = xp.dot(vector, other.vector) / (self.vector_norm * other.vector_norm) # ensure we get a scalar back (numpy does this automatically but cupy doesn't) return result.item() - + def has_morph(self): """Check whether the token has annotated morph information. Return False when the morph annotation is unset/missing. @@ -545,9 +543,9 @@ cdef class Token: def __get__(self): if self.i + 1 == len(self.doc): return True - elif self.doc[self.i+1].is_sent_start == None: + elif self.doc[self.i+1].is_sent_start is None: return None - elif self.doc[self.i+1].is_sent_start == True: + elif self.doc[self.i+1].is_sent_start is True: return True else: return False diff --git a/spacy/training/align.pyx b/spacy/training/align.pyx index 8bd43b048..79fec73c4 100644 --- a/spacy/training/align.pyx +++ b/spacy/training/align.pyx @@ -37,10 +37,14 @@ def get_alignments(A: List[str], B: List[str]) -> Tuple[List[List[int]], List[Li b2a.append(set()) # Process the alignment at the current position if A[token_idx_a] == B[token_idx_b] and \ - (char_idx_a == 0 or \ - char_to_token_a[char_idx_a - 1] < token_idx_a) and \ - (char_idx_b == 0 or \ - char_to_token_b[char_idx_b - 1] < token_idx_b): + ( + char_idx_a == 0 or + char_to_token_a[char_idx_a - 1] < token_idx_a + ) and \ + ( + char_idx_b == 0 or + char_to_token_b[char_idx_b - 1] < token_idx_b + ): # Current tokens are identical and both character offsets are the # start of a token (either at the beginning of the document or the # previous character belongs to a different token) diff --git a/spacy/training/example.pyx b/spacy/training/example.pyx index abdac23ea..3f0cf5ade 100644 --- a/spacy/training/example.pyx +++ b/spacy/training/example.pyx @@ -1,4 +1,3 @@ -import warnings from collections.abc import Iterable as IterableInstance import numpy @@ -31,9 +30,9 @@ cpdef Doc annotations_to_doc(vocab, tok_annot, doc_annot): attrs, array = _annot2array(vocab, tok_annot, doc_annot) output = Doc(vocab, words=tok_annot["ORTH"], spaces=tok_annot["SPACY"]) if "entities" in doc_annot: - _add_entities_to_doc(output, doc_annot["entities"]) + _add_entities_to_doc(output, doc_annot["entities"]) if "spans" in doc_annot: - _add_spans_to_doc(output, doc_annot["spans"]) + _add_spans_to_doc(output, doc_annot["spans"]) if array.size: output = output.from_array(attrs, array) # links are currently added with ENT_KB_ID on the token level @@ -161,7 +160,6 @@ cdef class Example: self._y_sig = y_sig return self._cached_alignment - def _get_aligned_vectorized(self, align, gold_values): # Fast path for Doc attributes/fields that are predominantly a single value, # i.e., TAG, POS, MORPH. @@ -204,7 +202,6 @@ cdef class Example: return output.tolist() - def _get_aligned_non_vectorized(self, align, gold_values): # Slower path for fields that return multiple values (resulting # in ragged arrays that cannot be vectorized trivially). @@ -221,7 +218,6 @@ cdef class Example: return output - def get_aligned(self, field, as_string=False): """Return an aligned array for a token attribute.""" align = self.alignment.x2y @@ -330,7 +326,7 @@ cdef class Example: missing=None ) # Now fill the tokens we can align to O. - O = 2 # I=1, O=2, B=3 + O = 2 # I=1, O=2, B=3 # no-cython-lint: E741 for i, ent_iob in enumerate(self.get_aligned("ENT_IOB")): if x_tags[i] is None: if ent_iob == O: @@ -340,7 +336,7 @@ cdef class Example: return x_ents, x_tags def get_aligned_ner(self): - x_ents, x_tags = self.get_aligned_ents_and_ner() + _x_ents, x_tags = self.get_aligned_ents_and_ner() return x_tags def get_matching_ents(self, check_label=True): @@ -398,7 +394,6 @@ cdef class Example: return span_dict - def _links_to_dict(self): links = {} for ent in self.reference.ents: @@ -589,6 +584,7 @@ def _fix_legacy_dict_data(example_dict): "doc_annotation": doc_dict } + def _has_field(annot, field): if field not in annot: return False @@ -625,6 +621,7 @@ def _parse_ner_tags(biluo_or_offsets, vocab, words, spaces): ent_types.append("") return ent_iobs, ent_types + def _parse_links(vocab, words, spaces, links): reference = Doc(vocab, words=words, spaces=spaces) starts = {token.idx: token.i for token in reference} diff --git a/spacy/training/gold_io.pyx b/spacy/training/gold_io.pyx index 1e7b3681d..2fc36e41f 100644 --- a/spacy/training/gold_io.pyx +++ b/spacy/training/gold_io.pyx @@ -1,4 +1,3 @@ -import json import warnings import srsly @@ -6,7 +5,7 @@ import srsly from .. import util from ..errors import Warnings from ..tokens import Doc -from .iob_utils import offsets_to_biluo_tags, tags_to_entities +from .iob_utils import offsets_to_biluo_tags def docs_to_json(docs, doc_id=0, ner_missing_tag="O"): @@ -23,7 +22,13 @@ def docs_to_json(docs, doc_id=0, ner_missing_tag="O"): json_doc = {"id": doc_id, "paragraphs": []} for i, doc in enumerate(docs): raw = None if doc.has_unknown_spaces else doc.text - json_para = {'raw': raw, "sentences": [], "cats": [], "entities": [], "links": []} + json_para = { + 'raw': raw, + "sentences": [], + "cats": [], + "entities": [], + "links": [] + } for cat, val in doc.cats.items(): json_cat = {"label": cat, "value": val} json_para["cats"].append(json_cat) @@ -35,13 +40,17 @@ def docs_to_json(docs, doc_id=0, ner_missing_tag="O"): if ent.kb_id_: link_dict = {(ent.start_char, ent.end_char): {ent.kb_id_: 1.0}} json_para["links"].append(link_dict) - biluo_tags = offsets_to_biluo_tags(doc, json_para["entities"], missing=ner_missing_tag) + biluo_tags = offsets_to_biluo_tags( + doc, json_para["entities"], missing=ner_missing_tag + ) attrs = ("TAG", "POS", "MORPH", "LEMMA", "DEP", "ENT_IOB") include_annotation = {attr: doc.has_annotation(attr) for attr in attrs} for j, sent in enumerate(doc.sents): json_sent = {"tokens": [], "brackets": []} for token in sent: - json_token = {"id": token.i, "orth": token.text, "space": token.whitespace_} + json_token = { + "id": token.i, "orth": token.text, "space": token.whitespace_ + } if include_annotation["TAG"]: json_token["tag"] = token.tag_ if include_annotation["POS"]: @@ -125,9 +134,14 @@ def json_to_annotations(doc): else: sent_starts.append(-1) if "brackets" in sent: - brackets.extend((b["first"] + sent_start_i, - b["last"] + sent_start_i, b["label"]) - for b in sent["brackets"]) + brackets.extend( + ( + b["first"] + sent_start_i, + b["last"] + sent_start_i, + b["label"] + ) + for b in sent["brackets"] + ) example["token_annotation"] = dict( ids=ids, @@ -160,6 +174,7 @@ def json_to_annotations(doc): ) yield example + def json_iterate(bytes utf8_str): # We should've made these files jsonl...But since we didn't, parse out # the docs one-by-one to reduce memory usage. diff --git a/spacy/vectors.pyx b/spacy/vectors.pyx index bf79481b8..a88f380f9 100644 --- a/spacy/vectors.pyx +++ b/spacy/vectors.pyx @@ -1,10 +1,8 @@ -cimport numpy as np from cython.operator cimport dereference as deref from libc.stdint cimport uint32_t, uint64_t from libcpp.set cimport set as cppset from murmurhash.mrmr cimport hash128_x64 -import functools import warnings from enum import Enum from typing import cast @@ -119,7 +117,7 @@ cdef class Vectors: if self.mode == Mode.default: if data is None: if shape is None: - shape = (0,0) + shape = (0, 0) ops = get_current_ops() data = ops.xp.zeros(shape, dtype="f") self._unset = cppset[int]({i for i in range(data.shape[0])}) @@ -260,11 +258,10 @@ cdef class Vectors: def __eq__(self, other): # Check for equality, with faster checks first return ( - self.shape == other.shape - and self.key2row == other.key2row - and self.to_bytes(exclude=["strings"]) - == other.to_bytes(exclude=["strings"]) - ) + self.shape == other.shape + and self.key2row == other.key2row + and self.to_bytes(exclude=["strings"]) == other.to_bytes(exclude=["strings"]) + ) def resize(self, shape, inplace=False): """Resize the underlying vectors array. If inplace=True, the memory @@ -520,11 +517,12 @@ cdef class Vectors: # vectors e.g. (10000, 300) # sims e.g. (1024, 10000) sims = xp.dot(batch, vectors.T) - best_rows[i:i+batch_size] = xp.argpartition(sims, -n, axis=1)[:,-n:] - scores[i:i+batch_size] = xp.partition(sims, -n, axis=1)[:,-n:] + best_rows[i:i+batch_size] = xp.argpartition(sims, -n, axis=1)[:, -n:] + scores[i:i+batch_size] = xp.partition(sims, -n, axis=1)[:, -n:] if sort and n >= 2: - sorted_index = xp.arange(scores.shape[0])[:,None][i:i+batch_size],xp.argsort(scores[i:i+batch_size], axis=1)[:,::-1] + sorted_index = xp.arange(scores.shape[0])[:, None][i:i+batch_size], \ + xp.argsort(scores[i:i+batch_size], axis=1)[:, ::-1] scores[i:i+batch_size] = scores[sorted_index] best_rows[i:i+batch_size] = best_rows[sorted_index] @@ -538,8 +536,12 @@ cdef class Vectors: numpy_rows = get_current_ops().to_numpy(best_rows) keys = xp.asarray( - [[row2key[row] for row in numpy_rows[i] if row in row2key] - for i in range(len(queries)) ], dtype="uint64") + [ + [row2key[row] for row in numpy_rows[i] if row in row2key] + for i in range(len(queries)) + ], + dtype="uint64" + ) return (keys, best_rows, scores) def to_ops(self, ops: Ops): @@ -582,9 +584,9 @@ cdef class Vectors: """ xp = get_array_module(self.data) if xp is numpy: - save_array = lambda arr, file_: xp.save(file_, arr, allow_pickle=False) + save_array = lambda arr, file_: xp.save(file_, arr, allow_pickle=False) # no-cython-lint else: - save_array = lambda arr, file_: xp.save(file_, arr) + save_array = lambda arr, file_: xp.save(file_, arr) # no-cython-lint def save_vectors(path): # the source of numpy.save indicates that the file object is closed after use. diff --git a/spacy/vocab.pxd b/spacy/vocab.pxd index 3b0173e3e..43e47af1d 100644 --- a/spacy/vocab.pxd +++ b/spacy/vocab.pxd @@ -32,7 +32,7 @@ cdef class Vocab: cdef public object writing_system cdef public object get_noun_chunks cdef readonly int length - cdef public object _unused_object # TODO remove in v4, see #9150 + cdef public object _unused_object # TODO remove in v4, see #9150 cdef public object lex_attr_getters cdef public object cfg diff --git a/spacy/vocab.pyx b/spacy/vocab.pyx index 520228b51..d1edc8533 100644 --- a/spacy/vocab.pyx +++ b/spacy/vocab.pyx @@ -1,6 +1,4 @@ # cython: profile=True -from libc.string cimport memcpy - import functools import numpy @@ -19,7 +17,6 @@ from .errors import Errors from .lang.lex_attrs import LEX_ATTRS, get_lang, is_stop from .lang.norm_exceptions import BASE_NORMS from .lookups import Lookups -from .util import registry from .vectors import Mode as VectorsMode from .vectors import Vectors @@ -51,9 +48,17 @@ cdef class Vocab: DOCS: https://spacy.io/api/vocab """ - def __init__(self, lex_attr_getters=None, strings=tuple(), lookups=None, - oov_prob=-20., vectors_name=None, writing_system={}, - get_noun_chunks=None, **deprecated_kwargs): + def __init__( + self, + lex_attr_getters=None, + strings=tuple(), + lookups=None, + oov_prob=-20., + vectors_name=None, + writing_system={}, # no-cython-lint + get_noun_chunks=None, + **deprecated_kwargs + ): """Create the vocabulary. lex_attr_getters (dict): A dictionary mapping attribute IDs to @@ -150,7 +155,6 @@ cdef class Vocab: cdef LexemeC* lex cdef hash_t key = self.strings[string] lex = self._by_orth.get(key) - cdef size_t addr if lex != NULL: assert lex.orth in self.strings if lex.orth != key: @@ -183,7 +187,7 @@ cdef class Vocab: # of the doc ownership). # TODO: Change the C API so that the mem isn't passed in here. mem = self.mem - #if len(string) < 3 or self.length < 10000: + # if len(string) < 3 or self.length < 10000: # mem = self.mem cdef bint is_oov = mem is not self.mem lex = mem.alloc(1, sizeof(LexemeC)) @@ -463,7 +467,6 @@ cdef class Vocab: self.lookups.get_table("lexeme_norm"), ) - def to_disk(self, path, *, exclude=tuple()): """Save the current state to a directory. @@ -476,7 +479,6 @@ cdef class Vocab: path = util.ensure_path(path) if not path.exists(): path.mkdir() - setters = ["strings", "vectors"] if "strings" not in exclude: self.strings.to_disk(path / "strings.json") if "vectors" not in exclude: @@ -495,7 +497,6 @@ cdef class Vocab: DOCS: https://spacy.io/api/vocab#to_disk """ path = util.ensure_path(path) - getters = ["strings", "vectors"] if "strings" not in exclude: self.strings.from_disk(path / "strings.json") # TODO: add exclude? if "vectors" not in exclude: