mirror of
https://github.com/explosion/spaCy.git
synced 2024-11-10 19:57:17 +03:00
Fix names of pipeline components
NeuralDependencyParser --> DependencyParser NeuralEntityRecognizer --> EntityRecognizer TokenVectorEncoder --> Tensorizer NeuralLabeller --> MultitaskObjective
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@ -18,8 +18,8 @@ from .tagger import Tagger
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from .lemmatizer import Lemmatizer
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from .syntax.parser import get_templates
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from .pipeline import NeuralDependencyParser, TokenVectorEncoder, NeuralTagger
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from .pipeline import NeuralEntityRecognizer, SimilarityHook, TextCategorizer
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from .pipeline import DependencyParser, Tensorizer, Tagger
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from .pipeline import EntityRecognizer, SimilarityHook, TextCategorizer
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from .compat import json_dumps, izip, copy_reg
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from .scorer import Scorer
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@ -75,9 +75,6 @@ class BaseDefaults(object):
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infixes = tuple(TOKENIZER_INFIXES)
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tag_map = dict(TAG_MAP)
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tokenizer_exceptions = {}
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parser_features = get_templates('parser')
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entity_features = get_templates('ner')
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tagger_features = Tagger.feature_templates # TODO -- fix this
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stop_words = set()
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lemma_rules = {}
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lemma_exc = {}
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@ -102,9 +99,9 @@ class Language(object):
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factories = {
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'tokenizer': lambda nlp: nlp.Defaults.create_tokenizer(nlp),
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'tensorizer': lambda nlp, **cfg: TokenVectorEncoder(nlp.vocab, **cfg),
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'tagger': lambda nlp, **cfg: NeuralTagger(nlp.vocab, **cfg),
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'parser': lambda nlp, **cfg: NeuralDependencyParser(nlp.vocab, **cfg),
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'ner': lambda nlp, **cfg: NeuralEntityRecognizer(nlp.vocab, **cfg),
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'tagger': lambda nlp, **cfg: Tagger(nlp.vocab, **cfg),
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'parser': lambda nlp, **cfg: DependencyParser(nlp.vocab, **cfg),
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'ner': lambda nlp, **cfg: EntityRecognizer(nlp.vocab, **cfg),
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'similarity': lambda nlp, **cfg: SimilarityHook(nlp.vocab, **cfg),
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'textcat': lambda nlp, **cfg: TextCategorizer(nlp.vocab, **cfg)
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}
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@ -1,21 +0,0 @@
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from .syntax.parser cimport Parser
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#from .syntax.beam_parser cimport BeamParser
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from .syntax.ner cimport BiluoPushDown
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from .syntax.arc_eager cimport ArcEager
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from .tagger cimport Tagger
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cdef class EntityRecognizer(Parser):
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pass
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cdef class DependencyParser(Parser):
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pass
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#cdef class BeamEntityRecognizer(BeamParser):
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# pass
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#
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#
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#cdef class BeamDependencyParser(BeamParser):
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# pass
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@ -26,11 +26,8 @@ from thinc.neural.util import to_categorical
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from thinc.neural._classes.difference import Siamese, CauchySimilarity
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from .tokens.doc cimport Doc
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from .syntax.parser cimport Parser as LinearParser
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from .syntax.nn_parser cimport Parser as NeuralParser
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from .syntax.nn_parser cimport Parser
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from .syntax import nonproj
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from .syntax.parser import get_templates as get_feature_templates
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from .syntax.beam_parser cimport BeamParser
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from .syntax.ner cimport BiluoPushDown
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from .syntax.arc_eager cimport ArcEager
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from .tagger import Tagger
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@ -217,7 +214,7 @@ def _load_cfg(path):
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return {}
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class TokenVectorEncoder(BaseThincComponent):
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class Tensorizer(BaseThincComponent):
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"""Assign position-sensitive vectors to tokens, using a CNN or RNN."""
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name = 'tensorizer'
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@ -329,7 +326,7 @@ class TokenVectorEncoder(BaseThincComponent):
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link_vectors_to_models(self.vocab)
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class NeuralTagger(BaseThincComponent):
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class Tagger(BaseThincComponent):
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name = 'tagger'
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def __init__(self, vocab, model=True, **cfg):
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self.vocab = vocab
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@ -513,7 +510,11 @@ class NeuralTagger(BaseThincComponent):
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return self
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class NeuralLabeller(NeuralTagger):
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class MultitaskObjective(Tagger):
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'''Assist training of a parser or tagger, by training a side-objective.
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Experimental
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'''
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name = 'nn_labeller'
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def __init__(self, vocab, model=True, target='dep_tag_offset', **cfg):
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self.vocab = vocab
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@ -532,7 +533,7 @@ class NeuralLabeller(NeuralTagger):
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self.make_label = target
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else:
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raise ValueError(
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"NeuralLabeller target should be function or one of "
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"MultitaskObjective target should be function or one of "
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"['dep', 'tag', 'ent', 'dep_tag_offset', 'ent_tag']")
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self.cfg = dict(cfg)
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self.cfg.setdefault('cnn_maxout_pieces', 2)
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@ -752,45 +753,7 @@ class TextCategorizer(BaseThincComponent):
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link_vectors_to_models(self.vocab)
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cdef class EntityRecognizer(LinearParser):
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"""Annotate named entities on Doc objects."""
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TransitionSystem = BiluoPushDown
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feature_templates = get_feature_templates('ner')
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def add_label(self, label):
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LinearParser.add_label(self, label)
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if isinstance(label, basestring):
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label = self.vocab.strings[label]
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cdef class BeamEntityRecognizer(BeamParser):
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"""Annotate named entities on Doc objects."""
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TransitionSystem = BiluoPushDown
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feature_templates = get_feature_templates('ner')
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def add_label(self, label):
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LinearParser.add_label(self, label)
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if isinstance(label, basestring):
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label = self.vocab.strings[label]
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cdef class DependencyParser(LinearParser):
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TransitionSystem = ArcEager
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feature_templates = get_feature_templates('basic')
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def add_label(self, label):
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LinearParser.add_label(self, label)
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if isinstance(label, basestring):
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label = self.vocab.strings[label]
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@property
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def postprocesses(self):
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return [nonproj.deprojectivize]
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cdef class NeuralDependencyParser(NeuralParser):
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cdef class DependencyParser(Parser):
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name = 'parser'
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TransitionSystem = ArcEager
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@ -800,17 +763,17 @@ cdef class NeuralDependencyParser(NeuralParser):
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def init_multitask_objectives(self, gold_tuples, pipeline, **cfg):
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for target in []:
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labeller = NeuralLabeller(self.vocab, target=target)
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labeller = MultitaskObjective(self.vocab, target=target)
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tok2vec = self.model[0]
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labeller.begin_training(gold_tuples, pipeline=pipeline, tok2vec=tok2vec)
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pipeline.append(labeller)
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self._multitasks.append(labeller)
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def __reduce__(self):
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return (NeuralDependencyParser, (self.vocab, self.moves, self.model), None, None)
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return (DependencyParser, (self.vocab, self.moves, self.model), None, None)
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cdef class NeuralEntityRecognizer(NeuralParser):
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cdef class EntityRecognizer(Parser):
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name = 'ner'
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TransitionSystem = BiluoPushDown
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@ -818,31 +781,14 @@ cdef class NeuralEntityRecognizer(NeuralParser):
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def init_multitask_objectives(self, gold_tuples, pipeline, **cfg):
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for target in []:
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labeller = NeuralLabeller(self.vocab, target=target)
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labeller = MultitaskObjective(self.vocab, target=target)
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tok2vec = self.model[0]
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labeller.begin_training(gold_tuples, pipeline=pipeline, tok2vec=tok2vec)
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pipeline.append(labeller)
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self._multitasks.append(labeller)
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def __reduce__(self):
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return (NeuralEntityRecognizer, (self.vocab, self.moves, self.model), None, None)
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return (EntityRecognizer, (self.vocab, self.moves, self.model), None, None)
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cdef class BeamDependencyParser(BeamParser):
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TransitionSystem = ArcEager
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feature_templates = get_feature_templates('basic')
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def add_label(self, label):
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Parser.add_label(self, label)
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if isinstance(label, basestring):
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label = self.vocab.strings[label]
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@property
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def postprocesses(self):
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return [nonproj.deprojectivize]
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__all__ = ['Tagger', 'DependencyParser', 'EntityRecognizer', 'BeamDependencyParser',
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'BeamEntityRecognizer', 'TokenVectorEnoder']
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__all__ = ['Tagger', 'DependencyParser', 'EntityRecognizer', 'Tensorizer']
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@ -10,7 +10,8 @@ import pytest
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def test_doc_add_entities_set_ents_iob(en_vocab):
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text = ["This", "is", "a", "lion"]
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doc = get_doc(en_vocab, text)
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ner = EntityRecognizer(en_vocab, features=[(2,), (3,)])
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ner = EntityRecognizer(en_vocab)
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ner.begin_training([])
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ner(doc)
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assert len(list(doc.ents)) == 0
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@ -9,7 +9,7 @@ from ...attrs import NORM
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from ...gold import GoldParse
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from ...vocab import Vocab
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from ...tokens import Doc
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from ...pipeline import NeuralDependencyParser
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from ...pipeline import DependencyParser
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numpy.random.seed(0)
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@ -21,7 +21,7 @@ def vocab():
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@pytest.fixture
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def parser(vocab):
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parser = NeuralDependencyParser(vocab)
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parser = DependencyParser(vocab)
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parser.cfg['token_vector_width'] = 8
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parser.cfg['hidden_width'] = 30
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parser.cfg['hist_size'] = 0
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@ -6,7 +6,7 @@ import numpy
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from ..._ml import chain, Tok2Vec, doc2feats
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from ...vocab import Vocab
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from ...pipeline import TokenVectorEncoder
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from ...pipeline import Tensorizer
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from ...syntax.arc_eager import ArcEager
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from ...syntax.nn_parser import Parser
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from ...tokens.doc import Doc
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@ -8,7 +8,7 @@ from ...attrs import NORM
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from ...gold import GoldParse
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from ...vocab import Vocab
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from ...tokens import Doc
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from ...pipeline import NeuralDependencyParser
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from ...pipeline import DependencyParser
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@pytest.fixture
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def vocab():
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@ -16,7 +16,7 @@ def vocab():
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@pytest.fixture
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def parser(vocab):
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parser = NeuralDependencyParser(vocab)
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parser = DependencyParser(vocab)
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parser.cfg['token_vector_width'] = 4
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parser.cfg['hidden_width'] = 32
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#parser.add_label('right')
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@ -1,11 +1,11 @@
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import pytest
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from ...pipeline import NeuralDependencyParser
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from ...pipeline import DependencyParser
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@pytest.fixture
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def parser(en_vocab):
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parser = NeuralDependencyParser(en_vocab)
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parser = DependencyParser(en_vocab)
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parser.add_label('nsubj')
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parser.model, cfg = parser.Model(parser.moves.n_moves)
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parser.cfg.update(cfg)
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@ -14,7 +14,7 @@ def parser(en_vocab):
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@pytest.fixture
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def blank_parser(en_vocab):
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parser = NeuralDependencyParser(en_vocab)
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parser = DependencyParser(en_vocab)
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return parser
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@ -2,8 +2,8 @@
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from __future__ import unicode_literals
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from ..util import make_tempdir
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from ...pipeline import NeuralDependencyParser as DependencyParser
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from ...pipeline import NeuralEntityRecognizer as EntityRecognizer
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from ...pipeline import DependencyParser
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from ...pipeline import EntityRecognizer
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import pytest
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@ -2,7 +2,7 @@
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from __future__ import unicode_literals
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from ..util import make_tempdir
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from ...pipeline import NeuralTagger as Tagger
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from ...pipeline import Tagger
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import pytest
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@ -2,7 +2,7 @@
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from __future__ import unicode_literals
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from ..util import make_tempdir
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from ...pipeline import TokenVectorEncoder as Tensorizer
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from ...pipeline import Tensorizer
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import pytest
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