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feat: add example stubs (#12679)
* feat: add example stubs * fix: add required annotations * fix: mypy issues * fix: use Py36-compatible Portocol * Minor reformatting --------- Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> Co-authored-by: svlandeg <svlandeg@github.com>
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@ -8,6 +8,7 @@ from typing import (
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List,
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Optional,
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Protocol,
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Sequence,
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Tuple,
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Union,
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overload,
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@ -134,7 +135,12 @@ class Doc:
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def text(self) -> str: ...
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@property
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def text_with_ws(self) -> str: ...
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ents: Tuple[Span]
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# Ideally the getter would output Tuple[Span]
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# see https://github.com/python/mypy/issues/3004
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@property
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def ents(self) -> Sequence[Span]: ...
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@ents.setter
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def ents(self, value: Sequence[Span]) -> None: ...
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def set_ents(
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self,
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entities: List[Span],
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@ -6,6 +6,7 @@ from typing import TYPE_CHECKING, Callable, Iterable, Iterator, List, Optional,
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import srsly
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from .. import util
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from ..compat import Protocol
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from ..errors import Errors, Warnings
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from ..tokens import Doc, DocBin
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from ..vocab import Vocab
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@ -19,6 +20,11 @@ if TYPE_CHECKING:
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FILE_TYPE = ".spacy"
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class ReaderProtocol(Protocol):
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def __call__(self, nlp: "Language") -> Iterable[Example]:
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pass
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@util.registry.readers("spacy.Corpus.v1")
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def create_docbin_reader(
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path: Optional[Path],
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@ -26,7 +32,7 @@ def create_docbin_reader(
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max_length: int = 0,
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limit: int = 0,
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augmenter: Optional[Callable] = None,
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) -> Callable[["Language"], Iterable[Example]]:
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) -> ReaderProtocol:
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if path is None:
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raise ValueError(Errors.E913)
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util.logger.debug("Loading corpus from path: %s", path)
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@ -45,7 +51,7 @@ def create_jsonl_reader(
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min_length: int = 0,
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max_length: int = 0,
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limit: int = 0,
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) -> Callable[["Language"], Iterable[Example]]:
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) -> ReaderProtocol:
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return JsonlCorpus(path, min_length=min_length, max_length=max_length, limit=limit)
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@ -63,7 +69,7 @@ def create_plain_text_reader(
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path: Optional[Path],
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min_length: int = 0,
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max_length: int = 0,
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) -> Callable[["Language"], Iterable[Doc]]:
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) -> ReaderProtocol:
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"""Iterate Example objects from a file or directory of plain text
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UTF-8 files with one line per doc.
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@ -144,7 +150,7 @@ class Corpus:
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self.augmenter = augmenter if augmenter is not None else dont_augment
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self.shuffle = shuffle
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def __call__(self, nlp: "Language") -> Iterator[Example]:
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def __call__(self, nlp: "Language") -> Iterable[Example]:
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"""Yield examples from the data.
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nlp (Language): The current nlp object.
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@ -182,7 +188,7 @@ class Corpus:
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def make_examples(
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self, nlp: "Language", reference_docs: Iterable[Doc]
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) -> Iterator[Example]:
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) -> Iterable[Example]:
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for reference in reference_docs:
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if len(reference) == 0:
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continue
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@ -197,7 +203,7 @@ class Corpus:
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def make_examples_gold_preproc(
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self, nlp: "Language", reference_docs: Iterable[Doc]
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) -> Iterator[Example]:
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) -> Iterable[Example]:
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for reference in reference_docs:
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if reference.has_annotation("SENT_START"):
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ref_sents = [sent.as_doc() for sent in reference.sents]
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@ -210,7 +216,7 @@ class Corpus:
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def read_docbin(
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self, vocab: Vocab, locs: Iterable[Union[str, Path]]
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) -> Iterator[Doc]:
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) -> Iterable[Doc]:
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"""Yield training examples as example dicts"""
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i = 0
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for loc in locs:
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@ -257,7 +263,7 @@ class JsonlCorpus:
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self.max_length = max_length
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self.limit = limit
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def __call__(self, nlp: "Language") -> Iterator[Example]:
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def __call__(self, nlp: "Language") -> Iterable[Example]:
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"""Yield examples from the data.
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nlp (Language): The current nlp object.
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@ -307,7 +313,7 @@ class PlainTextCorpus:
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self.min_length = min_length
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self.max_length = max_length
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def __call__(self, nlp: "Language") -> Iterator[Example]:
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def __call__(self, nlp: "Language") -> Iterable[Example]:
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"""Yield examples from the data.
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nlp (Language): The current nlp object.
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59
spacy/training/example.pyi
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59
spacy/training/example.pyi
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@ -0,0 +1,59 @@
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from typing import Any, Callable, Dict, Iterable, List, Optional, Sequence, Tuple
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from ..tokens import Doc, Span
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from ..vocab import Vocab
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from .alignment import Alignment
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def annotations_to_doc(
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vocab: Vocab,
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tok_annot: Dict[str, Any],
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doc_annot: Dict[str, Any],
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) -> Doc: ...
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def validate_examples(
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examples: Iterable[Example],
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method: str,
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) -> None: ...
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def validate_get_examples(
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get_examples: Callable[[], Iterable[Example]],
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method: str,
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): ...
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class Example:
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x: Doc
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y: Doc
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def __init__(
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self,
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predicted: Doc,
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reference: Doc,
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*,
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alignment: Optional[Alignment] = None,
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): ...
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def __len__(self) -> int: ...
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@property
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def predicted(self) -> Doc: ...
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@predicted.setter
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def predicted(self, doc: Doc) -> None: ...
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@property
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def reference(self) -> Doc: ...
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@reference.setter
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def reference(self, doc: Doc) -> None: ...
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def copy(self) -> Example: ...
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@classmethod
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def from_dict(cls, predicted: Doc, example_dict: Dict[str, Any]) -> Example: ...
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@property
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def alignment(self) -> Alignment: ...
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def get_aligned(self, field: str, as_string=False): ...
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def get_aligned_parse(self, projectivize=True): ...
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def get_aligned_sent_starts(self): ...
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def get_aligned_spans_x2y(self, x_spans: Sequence[Span], allow_overlap=False) -> List[Span]: ...
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def get_aligned_spans_y2x(self, y_spans: Sequence[Span], allow_overlap=False) -> List[Span]: ...
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def get_aligned_ents_and_ner(self) -> Tuple[List[Span], List[str]]: ...
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def get_aligned_ner(self) -> List[str]: ...
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def get_matching_ents(self, check_label: bool = True) -> List[Span]: ...
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def to_dict(self) -> Dict[str, Any]: ...
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def split_sents(self) -> List[Example]: ...
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@property
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def text(self) -> str: ...
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def __str__(self) -> str: ...
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def __repr__(self) -> str: ...
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