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Merge pull request #7220 from svlandeg/docs/has_annotation [ci skip]

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has_annotation docs fix
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Ines Montani 2021-02-27 11:50:34 +11:00 committed by GitHub
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2 changed files with 12 additions and 9 deletions
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5
spacy/scorer.py
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@ -314,6 +314,9 @@ class Scorer:
getter (Callable[[Doc, str], Iterable[Span]]): Defaults to getattr. If
provided, getter(doc, attr) should return the spans for the
individual doc.
has_annotation (Optional[Callable[[Doc], bool]]) should return whether a `Doc`
has annotation for this `attr`. Docs without annotation are skipped for
scoring purposes.
RETURNS (Dict[str, Any]): A dictionary containing the PRF scores under
the keys attr_p/r/f and the per-type PRF scores under attr_per_type.
@ -324,7 +327,7 @@ class Scorer:
for example in examples:
pred_doc = example.predicted
gold_doc = example.reference
# Option to handle docs without sents
# Option to handle docs without annotation for this attribute
if has_annotation is not None:
if not has_annotation(gold_doc):
continue

16
website/docs/api/scorer.md
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@ -137,14 +137,14 @@ Returns PRF scores for labeled or unlabeled spans.
> print(scores["ents_f"])
> ```
| Name | Description |
| ---------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `examples` | The `Example` objects holding both the predictions and the correct gold-standard annotations. ~~Iterable[Example]~~ |
| `attr` | The attribute to score. ~~str~~ |
| _keyword-only_ | |
| `getter` | Defaults to `getattr`. If provided, `getter(doc, attr)` should return the `Span` objects for an individual `Doc`. ~~Callable[[Doc, str], Iterable[Span]]~~ |
| `has_annotation` | Defaults to `None`. If provided, `has_annotation(doc)` should return whether a `Doc` has annotation for this `attr`. Docs without annotation are skipped for scoring purposes. ~~str~~ |
| **RETURNS** | A dictionary containing the PRF scores under the keys `{attr}_p`, `{attr}_r`, `{attr}_f` and the per-type PRF scores under `{attr}_per_type`. ~~Dict[str, Union[float, Dict[str, float]]]~~ |
| Name | Description |
| ---------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `examples` | The `Example` objects holding both the predictions and the correct gold-standard annotations. ~~Iterable[Example]~~ |
| `attr` | The attribute to score. ~~str~~ |
| _keyword-only_ | |
| `getter` | Defaults to `getattr`. If provided, `getter(doc, attr)` should return the `Span` objects for an individual `Doc`. ~~Callable[[Doc, str], Iterable[Span]]~~ |
| `has_annotation` | Defaults to `None`. If provided, `has_annotation(doc)` should return whether a `Doc` has annotation for this `attr`. Docs without annotation are skipped for scoring purposes. ~~Optional[Callable[[Doc], bool]]~~ |
| **RETURNS** | A dictionary containing the PRF scores under the keys `{attr}_p`, `{attr}_r`, `{attr}_f` and the per-type PRF scores under `{attr}_per_type`. ~~Dict[str, Union[float, Dict[str, float]]]~~ |
## Scorer.score_deps {#score_deps tag="staticmethod" new="3"}