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	Revert "feat: add example stubs (#12679)"
This reverts commit 30bb34533a.
			
			
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				|  | @ -8,7 +8,6 @@ from typing import ( | |||
|     List, | ||||
|     Optional, | ||||
|     Protocol, | ||||
|     Sequence, | ||||
|     Tuple, | ||||
|     Union, | ||||
|     overload, | ||||
|  | @ -135,12 +134,7 @@ class Doc: | |||
|     def text(self) -> str: ... | ||||
|     @property | ||||
|     def text_with_ws(self) -> str: ... | ||||
|     # Ideally the getter would output Tuple[Span] | ||||
|     # see https://github.com/python/mypy/issues/3004 | ||||
|     @property | ||||
|     def ents(self) -> Sequence[Span]: ... | ||||
|     @ents.setter | ||||
|     def ents(self, value: Sequence[Span]) -> None: ... | ||||
|     ents: Tuple[Span] | ||||
|     def set_ents( | ||||
|         self, | ||||
|         entities: List[Span], | ||||
|  |  | |||
|  | @ -6,7 +6,6 @@ from typing import TYPE_CHECKING, Callable, Iterable, Iterator, List, Optional, | |||
| import srsly | ||||
| 
 | ||||
| from .. import util | ||||
| from ..compat import Protocol | ||||
| from ..errors import Errors, Warnings | ||||
| from ..tokens import Doc, DocBin | ||||
| from ..vocab import Vocab | ||||
|  | @ -20,11 +19,6 @@ if TYPE_CHECKING: | |||
| FILE_TYPE = ".spacy" | ||||
| 
 | ||||
| 
 | ||||
| class ReaderProtocol(Protocol): | ||||
|     def __call__(self, nlp: "Language") -> Iterable[Example]: | ||||
|         pass | ||||
| 
 | ||||
| 
 | ||||
| @util.registry.readers("spacy.Corpus.v1") | ||||
| def create_docbin_reader( | ||||
|     path: Optional[Path], | ||||
|  | @ -32,7 +26,7 @@ def create_docbin_reader( | |||
|     max_length: int = 0, | ||||
|     limit: int = 0, | ||||
|     augmenter: Optional[Callable] = None, | ||||
| ) -> ReaderProtocol: | ||||
| ) -> Callable[["Language"], Iterable[Example]]: | ||||
|     if path is None: | ||||
|         raise ValueError(Errors.E913) | ||||
|     util.logger.debug("Loading corpus from path: %s", path) | ||||
|  | @ -51,7 +45,7 @@ def create_jsonl_reader( | |||
|     min_length: int = 0, | ||||
|     max_length: int = 0, | ||||
|     limit: int = 0, | ||||
| ) -> ReaderProtocol: | ||||
| ) -> Callable[["Language"], Iterable[Example]]: | ||||
|     return JsonlCorpus(path, min_length=min_length, max_length=max_length, limit=limit) | ||||
| 
 | ||||
| 
 | ||||
|  | @ -69,7 +63,7 @@ def create_plain_text_reader( | |||
|     path: Optional[Path], | ||||
|     min_length: int = 0, | ||||
|     max_length: int = 0, | ||||
| ) -> ReaderProtocol: | ||||
| ) -> Callable[["Language"], Iterable[Doc]]: | ||||
|     """Iterate Example objects from a file or directory of plain text | ||||
|     UTF-8 files with one line per doc. | ||||
| 
 | ||||
|  | @ -150,7 +144,7 @@ class Corpus: | |||
|         self.augmenter = augmenter if augmenter is not None else dont_augment | ||||
|         self.shuffle = shuffle | ||||
| 
 | ||||
|     def __call__(self, nlp: "Language") -> Iterable[Example]: | ||||
|     def __call__(self, nlp: "Language") -> Iterator[Example]: | ||||
|         """Yield examples from the data. | ||||
| 
 | ||||
|         nlp (Language): The current nlp object. | ||||
|  | @ -188,7 +182,7 @@ class Corpus: | |||
| 
 | ||||
|     def make_examples( | ||||
|         self, nlp: "Language", reference_docs: Iterable[Doc] | ||||
|     ) -> Iterable[Example]: | ||||
|     ) -> Iterator[Example]: | ||||
|         for reference in reference_docs: | ||||
|             if len(reference) == 0: | ||||
|                 continue | ||||
|  | @ -203,7 +197,7 @@ class Corpus: | |||
| 
 | ||||
|     def make_examples_gold_preproc( | ||||
|         self, nlp: "Language", reference_docs: Iterable[Doc] | ||||
|     ) -> Iterable[Example]: | ||||
|     ) -> Iterator[Example]: | ||||
|         for reference in reference_docs: | ||||
|             if reference.has_annotation("SENT_START"): | ||||
|                 ref_sents = [sent.as_doc() for sent in reference.sents] | ||||
|  | @ -216,7 +210,7 @@ class Corpus: | |||
| 
 | ||||
|     def read_docbin( | ||||
|         self, vocab: Vocab, locs: Iterable[Union[str, Path]] | ||||
|     ) -> Iterable[Doc]: | ||||
|     ) -> Iterator[Doc]: | ||||
|         """Yield training examples as example dicts""" | ||||
|         i = 0 | ||||
|         for loc in locs: | ||||
|  | @ -263,7 +257,7 @@ class JsonlCorpus: | |||
|         self.max_length = max_length | ||||
|         self.limit = limit | ||||
| 
 | ||||
|     def __call__(self, nlp: "Language") -> Iterable[Example]: | ||||
|     def __call__(self, nlp: "Language") -> Iterator[Example]: | ||||
|         """Yield examples from the data. | ||||
| 
 | ||||
|         nlp (Language): The current nlp object. | ||||
|  | @ -313,7 +307,7 @@ class PlainTextCorpus: | |||
|         self.min_length = min_length | ||||
|         self.max_length = max_length | ||||
| 
 | ||||
|     def __call__(self, nlp: "Language") -> Iterable[Example]: | ||||
|     def __call__(self, nlp: "Language") -> Iterator[Example]: | ||||
|         """Yield examples from the data. | ||||
| 
 | ||||
|         nlp (Language): The current nlp object. | ||||
|  |  | |||
|  | @ -1,59 +0,0 @@ | |||
| from typing import Any, Callable, Dict, Iterable, List, Optional, Sequence, Tuple | ||||
| 
 | ||||
| from ..tokens import Doc, Span | ||||
| from ..vocab import Vocab | ||||
| from .alignment import Alignment | ||||
| 
 | ||||
| def annotations_to_doc( | ||||
|     vocab: Vocab, | ||||
|     tok_annot: Dict[str, Any], | ||||
|     doc_annot: Dict[str, Any], | ||||
| ) -> Doc: ... | ||||
| def validate_examples( | ||||
|     examples: Iterable[Example], | ||||
|     method: str, | ||||
| ) -> None: ... | ||||
| def validate_get_examples( | ||||
|     get_examples: Callable[[], Iterable[Example]], | ||||
|     method: str, | ||||
| ): ... | ||||
| 
 | ||||
| class Example: | ||||
|     x: Doc | ||||
|     y: Doc | ||||
| 
 | ||||
|     def __init__( | ||||
|         self, | ||||
|         predicted: Doc, | ||||
|         reference: Doc, | ||||
|         *, | ||||
|         alignment: Optional[Alignment] = None, | ||||
|     ): ... | ||||
|     def __len__(self) -> int: ... | ||||
|     @property | ||||
|     def predicted(self) -> Doc: ... | ||||
|     @predicted.setter | ||||
|     def predicted(self, doc: Doc) -> None: ... | ||||
|     @property | ||||
|     def reference(self) -> Doc: ... | ||||
|     @reference.setter | ||||
|     def reference(self, doc: Doc) -> None: ... | ||||
|     def copy(self) -> Example: ... | ||||
|     @classmethod | ||||
|     def from_dict(cls, predicted: Doc, example_dict: Dict[str, Any]) -> Example: ... | ||||
|     @property | ||||
|     def alignment(self) -> Alignment: ... | ||||
|     def get_aligned(self, field: str, as_string=False): ... | ||||
|     def get_aligned_parse(self, projectivize=True): ... | ||||
|     def get_aligned_sent_starts(self): ... | ||||
|     def get_aligned_spans_x2y(self, x_spans: Sequence[Span], allow_overlap=False) -> List[Span]: ... | ||||
|     def get_aligned_spans_y2x(self, y_spans: Sequence[Span], allow_overlap=False) -> List[Span]: ... | ||||
|     def get_aligned_ents_and_ner(self) -> Tuple[List[Span], List[str]]: ... | ||||
|     def get_aligned_ner(self) -> List[str]: ... | ||||
|     def get_matching_ents(self, check_label: bool = True) -> List[Span]: ... | ||||
|     def to_dict(self) -> Dict[str, Any]: ... | ||||
|     def split_sents(self) -> List[Example]: ... | ||||
|     @property | ||||
|     def text(self) -> str: ... | ||||
|     def __str__(self) -> str: ... | ||||
|     def __repr__(self) -> str: ... | ||||
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