feat: add example stubs

spacy/training/example.pyi

@@ -0,0 +1,61 @@
+from typing import Any, Callable, Dict, Iterable, List, Optional, Tuple
+
+from ..tokens import Doc, Span
+from .alignment import Alignment
+
+def validate_examples(examples: Iterable[Example], method: str) -> None: ...
+def validate_get_examples(
+    get_examples: Callable[[], Iterable[Example]], method: str
+): ...
+
+class Example:
+    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) -> Example: ...
+    @property
+    def alignment(self) -> Optional[Alignment]: ...
+    def _get_aligned_vectorized(self, align, gold_values): ...
+    def _get_aligned_non_vectorized(self, align, gold_values): ...
+    def get_aligned(self, field, as_string=False): ...
+    def get_aligned_parse(self, projectivize=True): ...
+    def get_aligned_sent_starts(self): ...
+    def get_aligned_spans_x2y(self, x_spans, allow_overlap=False): ...
+    def get_aligned_spans_y2x(self, y_spans, allow_overlap=False): ...
+    def _get_aligned_spans(self, doc, spans, align, allow_overlap): ...
+    def get_aligned_ents_and_ner(self): ...
+    def get_aligned_ner(self): ...
+    def get_matching_ents(self, check_label: bool = True) -> List[Span]: ...
+    def to_dict(self) -> Dict[str, Any]: ...
+    def _spans_to_dict(self) -> Dict[str, List[Tuple[int, int, str, str]]]: ...
+    def _links_to_dict(self) -> Dict[Tuple[int, int], Dict[str, float]]: ...
+    def split_sents(self) -> List[Example]: ...
+    @property
+    def text(self) -> str: ...
+    def __str__(self) -> str: ...
+    def __repr__(self) -> str: ...
+
+def _annot2array(vocab, tok_annot, doc_annot): ...
+def _add_spans_to_doc(doc, spans_data): ...
+def _add_entities_to_doc(doc, ner_data): ...
+def _parse_example_dict_data(example_dict): ...
+def _fix_legacy_dict_data(example_dict): ...
+def _has_field(annot, field) -> bool: ...
+def _parse_ner_tags(biluo_or_offsets, vocab, words, spaces): ...
+def _parse_links(vocab, words, spaces, links): ...
+def _guess_spaces(text, words): ...