spaCy/spacy/training/example.pyi

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from typing import Any, Callable, Dict, Iterable, List, Optional, 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: Iterable[Span], allow_overlap=False
) -> List[Span]: ...
def get_aligned_spans_y2x(
self, y_spans: Iterable[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: ...
def _parse_example_dict_data(example_dict): ...
def _fix_legacy_dict_data(example_dict): ...