Cleanup/remove backwards compat overwrite settings (#11888)

* Remove backwards-compatible overwrite from Entity Linker

This also adds a docstring about overwrite, since it wasn't present.

* Fix docstring

* Remove backward compat settings in Morphologizer

This also needed a docstring added.

For this component it's less clear what the right overwrite settings
are.

* Remove backward compat from sentencizer

This was simple

* Remove backward compat from senter

Another simple one

* Remove backward compat setting from tagger

* Add docstrings

* Update spacy/pipeline/morphologizer.pyx

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

* Update docs

---------

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
This commit is contained in:
Paul O'Leary McCann 2023-02-02 22:13:38 +09:00 committed by GitHub
parent 6920fb7baf
commit 89f974d4f5
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7 changed files with 15 additions and 24 deletions

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@ -27,9 +27,6 @@ ActivationsT = Dict[str, Union[List[Ragged], List[str]]]
KNOWLEDGE_BASE_IDS = "kb_ids"
# See #9050
BACKWARD_OVERWRITE = True
default_model_config = """
[model]
@architectures = "spacy.EntityLinker.v2"
@ -60,7 +57,7 @@ DEFAULT_NEL_MODEL = Config().from_str(default_model_config)["model"]
"entity_vector_length": 64,
"get_candidates": {"@misc": "spacy.CandidateGenerator.v1"},
"get_candidates_batch": {"@misc": "spacy.CandidateBatchGenerator.v1"},
"overwrite": True,
"overwrite": False,
"scorer": {"@scorers": "spacy.entity_linker_scorer.v1"},
"use_gold_ents": True,
"candidates_batch_size": 1,
@ -191,7 +188,7 @@ class EntityLinker(TrainablePipe):
get_candidates_batch: Callable[
[KnowledgeBase, Iterable[Span]], Iterable[Iterable[Candidate]]
],
overwrite: bool = BACKWARD_OVERWRITE,
overwrite: bool = False,
scorer: Optional[Callable] = entity_linker_score,
use_gold_ents: bool,
candidates_batch_size: int,
@ -215,6 +212,7 @@ class EntityLinker(TrainablePipe):
Callable[[KnowledgeBase, Iterable[Span]], Iterable[Iterable[Candidate]]],
Iterable[Candidate]]
): Function that produces a list of candidates, given a certain knowledge base and several textual mentions.
overwrite (bool): Whether to overwrite existing non-empty annotations.
scorer (Optional[Callable]): The scoring method. Defaults to Scorer.score_links.
use_gold_ents (bool): Whether to copy entities from gold docs or not. If false, another
component must provide entity annotations.

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@ -21,10 +21,6 @@ from ..scorer import Scorer
from ..training import validate_examples, validate_get_examples
from ..util import registry
# See #9050
BACKWARD_OVERWRITE = True
BACKWARD_EXTEND = False
default_model_config = """
[model]
@architectures = "spacy.Tagger.v2"
@ -102,8 +98,8 @@ class Morphologizer(Tagger):
model: Model,
name: str = "morphologizer",
*,
overwrite: bool = BACKWARD_OVERWRITE,
extend: bool = BACKWARD_EXTEND,
overwrite: bool = False,
extend: bool = False,
scorer: Optional[Callable] = morphologizer_score,
save_activations: bool = False,
):
@ -113,6 +109,8 @@ class Morphologizer(Tagger):
model (thinc.api.Model): The Thinc Model powering the pipeline component.
name (str): The component instance name, used to add entries to the
losses during training.
overwrite (bool): Whether to overwrite existing annotations.
extend (bool): Whether to extend existing annotations.
scorer (Optional[Callable]): The scoring method. Defaults to
Scorer.score_token_attr for the attributes "pos" and "morph" and
Scorer.score_token_attr_per_feat for the attribute "morph".

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@ -10,9 +10,6 @@ from ..language import Language
from ..scorer import Scorer
from .. import util
# see #9050
BACKWARD_OVERWRITE = False
@Language.factory(
"sentencizer",
assigns=["token.is_sent_start", "doc.sents"],
@ -52,13 +49,14 @@ class Sentencizer(Pipe):
name="sentencizer",
*,
punct_chars=None,
overwrite=BACKWARD_OVERWRITE,
overwrite=False,
scorer=senter_score,
):
"""Initialize the sentencizer.
punct_chars (list): Punctuation characters to split on. Will be
serialized with the nlp object.
overwrite (bool): Whether to overwrite existing annotations.
scorer (Optional[Callable]): The scoring method. Defaults to
Scorer.score_spans for the attribute "sents".

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@ -18,8 +18,6 @@ from ..training import validate_examples, validate_get_examples
from ..util import registry
from .. import util
# See #9050
BACKWARD_OVERWRITE = False
default_model_config = """
[model]
@ -83,7 +81,7 @@ class SentenceRecognizer(Tagger):
model,
name="senter",
*,
overwrite=BACKWARD_OVERWRITE,
overwrite=False,
scorer=senter_score,
save_activations: bool = False,
):
@ -93,6 +91,7 @@ class SentenceRecognizer(Tagger):
model (thinc.api.Model): The Thinc Model powering the pipeline component.
name (str): The component instance name, used to add entries to the
losses during training.
overwrite (bool): Whether to overwrite existing annotations.
scorer (Optional[Callable]): The scoring method. Defaults to
Scorer.score_spans for the attribute "sents".
save_activations (bool): save model activations in Doc when annotating.

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@ -27,9 +27,6 @@ from .. import util
ActivationsT = Dict[str, Union[List[Floats2d], List[Ints1d]]]
# See #9050
BACKWARD_OVERWRITE = False
default_model_config = """
[model]
@architectures = "spacy.Tagger.v2"
@ -99,7 +96,7 @@ class Tagger(TrainablePipe):
model,
name="tagger",
*,
overwrite=BACKWARD_OVERWRITE,
overwrite=False,
scorer=tagger_score,
neg_prefix="!",
save_activations: bool = False,
@ -110,6 +107,7 @@ class Tagger(TrainablePipe):
model (thinc.api.Model): The Thinc Model powering the pipeline component.
name (str): The component instance name, used to add entries to the
losses during training.
overwrite (bool): Whether to overwrite existing annotations.
scorer (Optional[Callable]): The scoring method. Defaults to
Scorer.score_token_attr for the attribute "tag".
save_activations (bool): save model activations in Doc when annotating.

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@ -63,7 +63,7 @@ architectures and their arguments and hyperparameters.
| `entity_vector_length` | Size of encoding vectors in the KB. Defaults to `64`. ~~int~~ |
| `use_gold_ents` | Whether to copy entities from the gold docs or not. Defaults to `True`. If `False`, entities must be set in the training data or by an annotating component in the pipeline. ~~int~~ |
| `get_candidates` | Function that generates plausible candidates for a given `Span` object. Defaults to [CandidateGenerator](/api/architectures#CandidateGenerator), a function looking up exact, case-dependent aliases in the KB. ~~Callable[[KnowledgeBase, Span], Iterable[Candidate]]~~ |
| `overwrite` <Tag variant="new">3.2</Tag> | Whether existing annotation is overwritten. Defaults to `True`. ~~bool~~ |
| `overwrite` <Tag variant="new">3.2</Tag> | Whether existing annotation is overwritten. Defaults to `False`. ~~bool~~ |
| `scorer` <Tag variant="new">3.2</Tag> | The scoring method. Defaults to [`Scorer.score_links`](/api/scorer#score_links). ~~Optional[Callable]~~ |
| `save_activations` <Tag variant="new">4.0</Tag> | Save activations in `Doc` when annotating. Saved activations are `"ents"` and `"scores"`. ~~Union[bool, list[str]]~~ |
| `threshold` <Tag variant="new">3.4</Tag> | Confidence threshold for entity predictions. The default of `None` implies that all predictions are accepted, otherwise those with a score beneath the treshold are discarded. If there are no predictions with scores above the threshold, the linked entity is `NIL`. ~~Optional[float]~~ |

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@ -45,7 +45,7 @@ architectures and their arguments and hyperparameters.
| Setting | Description |
| ----------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model` | The model to use. Defaults to [Tagger](/api/architectures#Tagger). ~~Model[List[Doc], List[Floats2d]]~~ |
| `overwrite` <Tag variant="new">3.2</Tag> | Whether the values of existing features are overwritten. Defaults to `True`. ~~bool~~ |
| `overwrite` <Tag variant="new">3.2</Tag> | Whether the values of existing features are overwritten. Defaults to `False`. ~~bool~~ |
| `extend` <Tag variant="new">3.2</Tag> | Whether existing feature types (whose values may or may not be overwritten depending on `overwrite`) are preserved. Defaults to `False`. ~~bool~~ |
| `scorer` <Tag variant="new">3.2</Tag> | The scoring method. Defaults to [`Scorer.score_token_attr`](/api/scorer#score_token_attr) for the attributes `"pos"` and `"morph"` and [`Scorer.score_token_attr_per_feat`](/api/scorer#score_token_attr_per_feat) for the attribute `"morph"`. ~~Optional[Callable]~~ |
| `save_activations` <Tag variant="new">4.0</Tag> | Save activations in `Doc` when annotating. Saved activations are `"probabilities"` and `"label_ids"`. ~~Union[bool, list[str]]~~ |