spaCy/spacy/training/example.pyi

67 lines
2.0 KiB
Python

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): ...